Chemical Bio Refinery Perspectives

Chemical Biorefinery Perspectives The valorisation of functionalised chemicals from biomass resources

compared to the conventional fossil fuel production route

Ben Brehmer

Dissertation Report

© Agrotechnology and Food Sciences Group B.V., member of Wageningen UR 2

©Agrotechnology & Food Sciences Group B.V. Member of Wageningen UR 3

Table of Contents

Chapter 1 5

The Dissertation Report Layout

Chapter 2 11

Energy and Exergy

Chapter 3 37

Life Cycle Assessment vs. Exergy

Chapter 4 75

Crop Output

Chapter 5 115

Prime Energy Input

Chapter 6 217

Secondary Energy Input

Chapter 7 295

Process Energy Input

Chapter 8 389

Fossil Fuel Savings



Chapter 1 The Dissertation Report Layout

Ben Brehmer

Dissertation Report



The Hypothesis This entire dissertation report is based on the notion that vast amounts of fossil fuel energy can

be mitigated should biomass be utilized as a feedstock for the chemical industry. Biomass has

unique biochemical structures that when employed for the production of existing chemicals

(which have the same functionality) could lead to vast increases of fossil fuel energy savings in

comparison to standard biomass applications (i.e. producing fuels, heat, or power). The final

calorific energy content of these chemical products are identical should existing and not novel

chemicals be produced in the biorefinery. In standard petrochemical refineries, numerous

process steps are required to introduce such chemical functionality into the base structures.

Conversely, many of the biochemical constituents found in biomass often contain similar

functionalities. Therefore, it is attractive to exploit this situation to by-pass many of steps

required to add functionality and thus by utilizing well-suited biomass-based precursors to

possibility eliminate several of these energy intensive processing steps. The following figure

(Figure 1) visually illustrates the idea of producing the different types of functionalized chemicals

(e.g. hydrocarbons, amines, oxides) from both the traditional petrochemical and potential

biorefinery route. Although the final calorific values are equal, the total embedded process energy

involved is expected to be substantially lower for the biomass route.

Figure 1 Petrochemical Refinery and Biorefinery Comparison Adapted from Johan Sanders – Dissertation mentor

Inclusion of both the feedstock energy and the process energy on a life cycle assessment basis

should reveal major fuel fossil energy savings from biomass. In short, the hypothesis is to argue

that functionality upheaval is something to strive for in industrial biomass applications.



The Book Layout This book-style report is constructed in such a way to systematically and accurately compile all

the required data to determine the fossil fuel energy and exergy replacement potential of the

conceptualized chemical biorefinery in respect to the existing traditional petrochemical layouts.

The chosen methodology is a comparative energetic and exergetic cradle-to-factory gate assessment. The

following layout is a visual representation of the major aspects in producing the chemicals via the

biorefinery concept; and the respective chapters.

Figure 2 Simplified System Boundaries for Chemical Biorefinery

Chapter 2 – Energy and Exergy

…acts as a documentation for the theoretical differences between energy and exergy while also

describing their practical impact to the matrix calculations. Thermodynamical background is

provided with succinct mathematical formulas to stress the contrast between the two values. It

forms the basis of the calculations and assumptions for the assessment.

Chapter 3 – Life Cycle Assessment versus Exergy

…discusses the various methods and analysis tools available to compare the life cycle of different

processes, production methods and products. It determines the best amalgamation of the various

life cycle analysis tool components for provoking a raw material change in the petrochemical

industry to a biorefinery system. The comparative energetic and exergetic cradle-to-factory gate assessment

methodology is described along with the benefits of exergy inclusion and the reasons fro

excluding common environmental impact factors.


Chapter 4 – Crop Output

…lists the biomass energy crops chosen to be representative and included in the assessment.

Listed in the created crop guide for 16 popular bioenergy crops are all the cultivation dependent

variables required to systematically compare the different energy and exergy inputs. The values

are central to the system layout as illustrated in Figure 2; “crop yields” - it covers the crop

selection, yields, and usable constituents for potential biochemical production. All aspects of the

life cycle revolve around the selected crops and their representative cultivation region.

Chapter 5 – Prime Energy Input

…encapsulates the “prime energy” input box highlighted in Figure 2. It describes and lists in full

detail those inputs directly attributed to biomass growth; namely fertilizers, irrigation, drainage

and crop protection. All the processes and methods are adopted and expanded to include both

energy and exergy values, essentially being related to the primary energy and material use.

Chapter 6 – Secondary Energy Input

…encapsulates the “secondary energy” input box highlighted in Figure 2. It describes and lists in

full detail those inputs indirectly attributed to biomass growth; namely farming procedures,

transportation and storage operations, and pre-processing and drying techniques. All the

processes and methods are adopted and expanded to include both energy and exergy values,

essentially being related to the primary energy and material use. The summation of the prime and

secondary energy input leads to the total biomass acquisition energy input, which provides a biomass

feedstock cost for the chemical biorefinery processing.

Chapter 7 – Process Energy Input

…encapsulates the “process energy” input box highlighted in Figure 2. It describes and lists in

full detail those inputs directly attributed to the internal biorefinery processing. Each biochemical

processing step within the biorefinery involves internal process energy; separated into direct

thermal and electric energy, and indirect energy (plus exergy). All the processes and methods are

adopted and expanded to lead to total bioprocessing energy requirements, essentially being related to the

primary energy and material use. It provides the base data needed for further matrix calculations

of the feedstock dependent biorefinery layouts.

Chapter 8 – Fossil Fuel Energy Savings

…encapsulates the “chemical yields” output box highlighted in Figure 2. It is the summation of

the determined total biomass acquisition energy intensity from Chapter 6 in combination with the total

bioprocessing energy requirements from Chapter 7. Combined they are used to determine the potential

fossil fuel energy and exergy savings for each chemical biorefinery cropping system. Results and

discussion are presented which predominantly used to validate the hypothesis that functionality

upheaval is something to strive for in industrial biomass applications.


Chapter 2 Energy and Exergy

Ben Brehmer

Dissertation Report


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Abstract The calculation methodology briefly highlighted in the previous chapter and to be conducted in

the succeeding chapters is based on the simplifications and assumptions performed in this

chapter; all relative to energy and exergy determination. It acts as a documentation for the

theoretical differences between energy and exergy and the practical differences for their

calculation. The thermodynamical background is provided with succinct mathematical formulas

to stress the contrast between the two values. It provides all information needed to derive at the

their base values and additional methodology to derive at their cumulative demands. It acts as a

guide for the cumulative fossil fuel energy and exergy demand calculations which may not

necessarily be described in sufficient detail in the succeeding chapters. And lastly, the cumulative

energy and exergy values for the select petrochemicals to be replaced is provided.

Key Words:

Thermodynamics, Energy, Exergy, Fossil Fuels, Base Assumptions



Content

1 Introduction 17

1.1 Chapter Purpose 18

2 Thermodynamics 19

2.1 First Law 19

2.2 Second Law 19

2.3 Difference between energy and exergy 20

2.3.1 Energy 20

2.3.2 Carnot efficiency 20

2.3.3 Exergy 21

2.3.4 Simple Terms: Energy vs. Exergy 22

3 Base Values and Calculations 23

3.1 Solar Radiation Energy and Exergy 23

3.2 Fossil Fuel Source Energy and Exergy 23

3.2.1 Natural Gas 23

3.2.2 Diesel 24

3.3 Energy Carrier Conversions 24

3.3.1 Electric Production 25

3.3.2 Steam 26

3.3.3 Standardized Ratios 28

4 Detailed Processing Values and Calculations 29

4.1 Aspen+ 29

4.2 Process Flow Diagrams 30

4.2.1 Energy - Sankey Diagram 30

4.2.2 Exergy – Grassman Diagram 30

5 Cradle-to-Factory Gate Methodology 31

5.1 Mass and energy balances 31

5.2 Existing Chemical Production Routes 31

6 Conclusion 33



1 Introduction If someone were to recommend using a chainsaw to cut a piece of butter, the obvious reaction

should be one of bewilderment followed by a complete rejection of the idea. Laconically replying;

why use a chainsaw when a small knife is sufficient? Metaphorically speaking in many industrially

energetic processes, however, this type of action is nearly being conducted on a regular basis.

Vast amounts of energy are being squandered to perform simple tasks that with a more

appropriate technique or process could be drastically reduced.

Manufacturers of hot water boilers, for instance, systematically claim close to 100% energetic

conversion efficiency. Heating 1m³ of water from 15°C to 38°C for the average person to take a

shower requires 2.2m³ of natural gas. From a calorimetric standpoint this is indeed a very

efficient process, as practically all the chemical energy of the natural gas has been converted to an

increase of thermal energy in the water. On the other hand, natural gas has the potential to

combust at temperatures exceeding 2000°C, meaning heating water from 15 to 38°C using

natural gas is analogous to cutting butter with a chainsaw.

This example is an attempt to simply explain what “work potential” is. In many scientific and

applied engineering practices, the traditional “calorimetric” approach to thermodynamics has

dominated energy (or fuel) utilization. It adamantly follows the 1st law of thermodynamics (the

conservation of energy) which proves it to be very successful, at least in the case of the hot water

boiler. Entire process schemes and developmental layouts can be dominated by such studies;

strictly revolving around the 1st law. Despite the 2nd law (increase of entropy or less order) being

taught in advanced classes, it is classically separated and merely introduced for theoretical merit.

Actually applying its concepts in practice proves difficult and challenging, forcing many to avoid

its principles.

Exergy is the measurable and determinable value of work potential. It is the combination

between both the 1st and 2nd laws of thermodynamics, incorporating both energy conservation

and maximum conversion potential. When calculated properly it can be a helpful guide to

applying different techniques or processing options to increase the overall energy efficiency for

many energetically intensive processes. And with the current advancements made in computing

power, its determination is no longer as difficult as previously anticipated.

The differences between the 1st and 2nd law of thermodynamics (i.e. energy and exergy) and their

calculation methods are covered in this chapter. To perform and list these comparative

differences, more detailed knowledge of the process systems are required to enable the correct

determination of enthalpy and entropy flows, in order to finally calculate exergy. At this deeper

level of understanding the process system, energy and exergy flow values can pin-point potential

improvements for an increased overall energy (fuel) efficiency. In many systems however,

processing data is insufficient which can prevent the accurate calculation of exergy flows. In such


situations, there are calculation shortcuts using assumed ratios and relations to standard energy

calculations; enabling the determination of a representative value for exergy.

For an entire process chain-based system, as is the case with chemical biorefineries, the

difference resulting values of energy and exergy illustrate major improvement options.

Regardless, in many situations, the standard calorimetric approach suffices in indicating many

straightforward and large energy efficiency improvement options. But by expanding the

assessment to include exergy other less obvious improvement option should be noticeable.

The entire calculation methodology conducted in the succeeding chapters is based on the

simplifications and assumptions made in this chapter, all related to energy and exergy

determinations. Considering the complexity of the calculation matrix model, these descriptions

primarily provide a systematic approach to convert direct energy streams (heat, power, and fuels)

into cumulative energy and exergy values. The basis of those conversion/calculations are

presented in this chapter to help avoid unnecessary energy squander.

1.1 Chapter Purpose

This chapter is used to document the theoretical differences between energy and exergy and the

practical differences for their calculation. In addition to explaining the thermodynamic theory, it

is also used to list the base values and calculation routes needed to obtain figures for practical

purposes. It is essentially the background piece to the conversion efficiencies and thermodynamic

considerations required to calculate the cumulative energy and exergy demand.


2 Thermodynamics The entire field of macroscopically analysing the transformation of energy into different forms in

relation to variables, such as temperature and pressure etc., is thermodynamics. The word and study

of thermodynamic originates from the Greek meanings of heat and power; both functional units

of energetic flows to generate work. Heat can be regarded as energy in transit whereas dynamics can

be regarded as a relative motion. In a sense, seeing that the word itself comprising of two parts it is

logical to include both laws needed for the calculation of exergy. There are in fact five laws of

thermodynamics, ranging from the zeroth law to Onsager reciprocal relations law, nonetheless only

two are needed to study energy flows in relation to work potential in the realm of biomass

production chains to determine exergy.

2.1 First Law

“The increase in the internal energy of a system is equal to the amount of energy added by heating the system,

minus the amount lost as a result of the work done by the system on its surroundings.”

The first law can be stated mathematically as:

WQdU δδ −=

dU = a differential (infinitely small) increase in the internal energy of the system

δQ = a differential (infinitely small) amount of heat added to the system

δW = a differential (infinitely small) amount of work done by the system

The first law of thermodynamics is about the conservation of energy; that energy cannot be

created or destroyed, only transformed. In determining useful work within thermodynamical

systems, the quotient enthalpy (denoted as H or h) is primarily used. It expresses the heat content

which can be obtained from a closed system under constant pressure and entropy.

2.2 Second Law

There is no single expression used to describe the second law but one of the succinct

interpretations from Kelvin is fitting and states:

“It is impossible to convert heat completely into work.”

The second law can be stated mathematically as:

0≥dt

dS

dS = a differential (infinitely small) increase in the entropy of the system

dt = a differential (infinitely small) amount of time


The second law of thermodynamics is about the increase of irreversibility; that while energy

cannot be created or destroyed, its quality is decreased upon each transformation. In determining

useful work within thermodynamical systems, the quotient entropy (denoted as S or s) is

additional considered along with enthalpy. Entropy expresses the unavailability of a system to

perform work. As expressed in the mathematical formula, the total entropy of any isolated

thermodynamic system will increase over time eventually approaching a maximum value or zero

availability of work potential.

2.3 Difference between energy and exergy

Energy calculations are first law-based using only enthalpy and is therefore based on ideal

conditions (simplified assumptions). Exergy calculations are second law-based using both

enthalpy and entropy and is therefore based on real irreversible conditions.

2.3.1 Energy

There are many different interpretations and colloquial meanings of energy, but it is generally

intended to mean the ability to do work. There are many forms of energy ranging from kinetic to

mechanical to nuclear to gravitational, etc. In calculations pertaining to thermodynamic systems

or industrial processes it can be narrowed down to the thermal energy potential…to do work. The

following mathematical formula describes the energy flow of a system:

( )0υυ −⋅⋅= ipcMEn &

M = mass flow, kg/h

cp = heat capacity, kJ/K⋅mol ϑi = output temperature, °C

ϑ0 = output temperature, °C

It is essentially a summation of mass and heat flows, which can be regarded as enthalpy (H).

2.3.2 Carnot efficiency

The so-called “father of thermodynamics”, Sadi Carnot, took it upon himself to study mass and

heat flows in an engine cycle. Simplified, his study lead to the discovery of the Carnot cycle:

h

ccarnot

T

T−=1η

Tc = Temperature of cold reservoir (i.e. atmosphere), K

Th = Temperature of hot reservoir (i.e. exhaust), K

It describes the most efficient cycle possible for converting a given amount of thermal energy

(enthalpy) into useable work.


Thermal energy expressed by enthalpy does not have the ability to indicate the sources of or the

magnitude of irreversible energy limitations. It is based on the conjecture that entropy is

constant. Followings the calculations described by Carnot’s cycle, no engine can produce more

work than determined by the thermal limitations of the reservoirs. Furthermore, in practice, work

efficiencies are never able to reach the calculated maximum work potential indicated by the cycle

suggesting the influence of irreversibility within thermodynamic systems. Studying engine systems

was the first step into understanding the limitations of the 1st law and energy calculations. While

second law considerations were made in determining the cycle’s pathway, the step towards

calculating maximum work potential of reversible energy streams was not performed.

2.3.3 Exergy

Exergy is the quotient for the maximum amount of work that can be extracted from a physical

stream by exchanging mass and energy with reservoirs in a reference state. The reference state

reservoir is the atmospheric conditions of earth, which itself has an exergy content but is zero in

relation to itself. The first law (or enthalpy calculations) states that energy cannot be created or

destroyed only transformed. The second law (or entropy calculations) states that the irreversibility

is increased upon a transformation process. Exergy takes into account both laws; so while energy

cannot be destroyed exergy can and always is within a process destroyed; or while there is a

constant amount of energy in the universe, the amount of exergy is constantly decreasing with

every conversion process.

Since the time of Carnot’s cycle many theorems and mathematical hypothesis have been

developed which can all be considered as exergy. Some famous synonymous terms are:

availability, maximum work content, reversible work, ideal work, etc. The determination of

exergy is broken down into three separate terms; physical, chemical and mixing1:

mixchemph ExExExEx ++=

Physical Exergy Flows

The physical exergy flow is a term for the transfer of work potential from one state to another

influenced by the thermal (temperature, T) and mechanical (pressure, p) states.

( )STHnExph ∆−∆= 0& or more detailed ( ) ( )[ ]000 SSTHHMEx iii −⋅−−⋅= &

n& or iM& = molar flow, mol/s

Hi = enthalpy output, cal/mol

H0 = enthalpy reference, cal/mol

Si = entropy output, cal/mol⋅K

S0 = entropy reference, cal/mol⋅K T0 = reference temperature, °C


Physical exergy is the link between the 1st and 2nd laws for both enthalpy and entropy are

considered in the system dynamics; it is thus the true measure of maximum work potential. In

case where a portion of a process layout (system) is studied, the calculation is performed for both

the input and output conditions of the streams surrounding the process unit; like a black box in

relation to the reference point.

Chemical Exergy

The chemical exergy potential states the work potential of materials in relation to their molecular

composition; i.e. molecular form, orientation, and group formation. Much like chemical energy

potentials, the values are determined by tables and charts2. In most cases, the chemical exergy and

energy do not differ sustainably.

∑ ⋅=i chemiichem ExyEx

yi = stoichiometric coefficient of molecular structure i

Exchemi = exergy content or contribution of molecular structure i

It is a summation of each individual molecular group’s contribution to reaction potential in the

whole chemical element, i.e. tabular determination.

Mixing Exergy

Mixing exergy incorporates the effect of dilution or concentration of various elements in relation

to the reference point.

∑ ⋅⋅⋅⋅=i iimix yyTRnEx ln0&

The result is usually negligible. It is only significant for highly energetic minerals such as

radioactive elements; for example the influence of the centrifugal purification (or concentration)

step. In these calculations, however, it is omitted.

2.3.4 Simple Terms: Energy vs. Exergy

In simple terms, energy and exergy can be expressed by the following3:

(1) energy is motion or ability to produce motion and

(2) exergy is work (ordered motion) or ability to produce work.

Basically exergy is a measure of the useable portion of energy for work potential – energy being

quantity and exergy being quality. Differences between exergy versus energy results are mainly

noticeable in thermal processes or those system layouts which rely on the thermal release of

chemical energy: i.e. in cases where the physical exergy flow is greatly different than the enthalpy

flow. As mentioned chemical energy and exergy do not differ substantially.


3 Base Values and Calculations

3.1 Solar Radiation Energy and Exergy

During the early phases of large-scale fossil fuel usage, significant levels of

sulphur was emitted into the atmosphere (otherwise known as smog). The

effects of these large quantities of sulphuric gases in the atmosphere led to so-

called global dimming, wherein the solar radiation is partially blocked and has a

reduced intensity. Traditionally this effect has been limited to volcanic

eruptions. And since the 1980’s stricter environmental laws have pushed for

lower sulphur emission levels. As a direct result sulphur levels in the atmosphere have continually

decreased and the reverse effect of global brightening is occurring, where the solar radiation level

increases4. Global brightening has been attributed to a 2W/m² increase of solar radiation annually

since 1986.

Seeing that solar radiation is the principal source of energy for biomass to create material and

thus lock in chemical energy, any deviations in solar radiation have a direct effect on growth

levels. Here the relationship between the energy content and exergy content of solar radiation

could play a vital role. Following a detailed study pertaining to the maximum work obtainable by

solar radiation, the difference is however only minor: solar exergy is 0.9327 of the energy value5.

Nonetheless the relevance of solar radiation both energetically and exergetically, as described in

Chapter 4, is excluded from consideration. Biomass growth and potential chemical energy/exergy

yields are brought into relation to land use consumption. It should be mentioned, though, that

the chemical exergy of biomass material is slightly higher than the chemical energy and as the

solar radiation exergy is lower than the energy content, plants are actually more exergetically

efficient than energetically efficient. This phenomenon could also be thermodynamically brought

into perspective of thermal-based processes; plants function at near atmospheric conditions,

further proof that nature operates optimally.

3.2 Fossil Fuel Source Energy and Exergy

Fossil fuels are typically combusted to release their chemicals energy and exergy but are also used

as chemical feedstocks. In both situations their cumulative energy and exergy demand is

determined by their chemical energy content and the exergetic ratio. Two examples will be given;

natural gas and diesel to illustrate the procedure.

3.2.1 Natural Gas

Natural gas used for both fuel energy and feedstock requirements and is expressed in

terms of energetic output: lower heating value (LHV - GJ/ton). This correlates to a

stark difference in gas qualities as each natural gas source has varying calorific values.

To calculate the amount of gas (mass) this relates to, the following assumptions and

calculation path has been set up:


δ⋅=L

out

H

EM

Natural gas source = Groningen

Eout = Energetic output/requirement, process dependent

HL = Lower heating value (LHV), 31.65MJ/m³

δ = Natural gas density, 783.6kg/m³ at STP (standard temperature and pressure)

Natural gas can originate from many sources around the world with a large corresponding

deviation of its calorific value (i.e. LHV). At this stage a major assumption is made, that for all

calculations natural gas originates from Groningen6. The chemical energy content of natural gas

directly coming from the Groningse Slochteren is 31.65MJ/m³. The energy content is typically

upgraded through gas purification to a Wobbe-indexed value ranging from 43.5 – 44.4MJ/m³. In

the base calculations the original energy and exergy content of the gas at the point of extraction

will be selected, indicating its original chemical energy content. Natural gas has a chemical energy

and exergy ratio of 1.0:1.052.

Therefore:

CED = 40.39GJ/ton, CExD =42.41GJ/ton

3.2.2 Diesel

Diesel and other transportation fuels are used throughout the biomass

chains, primarily as a fuel for internal combustion engines in logistics.

There are two main diesel fuel types for consideration; transport and

industrial variant. Therefore, the first assumption is that diesel

referenced throughout the calculation matrix is transportation

diesel. Little difference is noticeable in the contained chemical energy of transport grade diesel;

according to ACEA it is 45.5MJ/kg7. Diesel is one of the primary fossil fuel products originating

from the crude oil cracker; the allocated process energy involved in its production and ground

extraction will be omitted. This can only be performed when all cracked products embedded in

both the biomass routes and petrochemical routes are treated equally. Thus, in this calculation

matrix a simplification is made: all cracker products are the starting point for replacement and

their cumulative energy and exergy is relative to their chemical energy and exergy. Diesel has a

chemical energy and exergy ratio is 1.0 to 1.02.

Therefore:

CED = 45.5GJ/ton, CExD = 45.5GJ/ton

3.3 Energy Carrier Conversions

In process schematics (process flow diagrams – PFD’s), energy inputs are usually expressed in

heat and power terms; more specifically steam and electricity requirements. Both steam and

electricity are not the original fossil fuel energy (exergy) form. To determine the relative fossil fuel

energy (exergy) involved the actual conditions, production efficiencies and local production mix


of fuels to generate heat and power need to be known. This calls for several assumptions, which

will be listed for electricity and steam:

3.3.1 Electric Production

In nearly all cases, electrical inputs are documented in the kWh terms.

First, these values must be converted to MJ with the easy factor of

3.6MJ/kWh to arrive at the direct energy demand. Secondly, the method

to produce electricity must be set to determine the cumulative energy

demand. In most quick and dirty LCA studies (conducted by non-experts)

this step is frequently overlooked: giving electricity a 1:1 ratio for fossil fuel energy demand. Only

by including the typical electricity production efficiency can the primary fossil fuel energy and

exergy can be proper allocated:

ηel

prime

EE =

Eprime = Prime energy, MJ

Eel = Electrical energy, MJ

η = Electrical production efficiency, 45%

The electric production efficiency is dependent on many factors from the regional fuel mixture

for power generation to the technological state of the region. In France for instance, they have a

nearly 85% nuclear powered electric grid, which depending on the study has a fossil fuel energy

content 10-50%8. So the first assumption is the power mix, here standard coal will be chosen. In

Holland, its hinterland, and for the large part the rest of the world, coal is still the most used fuel

feedstock for the production of electricity. Secondly, the conversion efficiency of coal to

electricity has greatly increased over the past decades, hereby selecting a 45% energy and 35%

exergy efficiency for a modern coal power plant2, 9. A standard coal power plant (CP) ranges from

35 – 45% with future perspectives at 55%, whereas a gasification clean coal plant (IGCC) range

from 45 – 50% with future perspectives at 60%.

The utilization of off-heat is not considered in this report because typically

CP’s and IGCC’s are on the large grid-based production scales and do not

make adequate use of the off-heat. One often visualizes the large cooling

towers, which is indeed the standard. Only in a few isolated instances is a

portion of the off-heat actually utilized (for example district heating) which

would increase the overall cumulative energy efficiency. Coke (coal) has a

chemical energy and exergy ratio is 1.0:1.0 and electricity as a product has an energy to exergy

ratio of 1.0:1.02.

Therefore:

CED = 8.0MJ/kWh, CExD = 10.2MJ/kWh


3.3.2 Steam

In nearly all PFD’s, steam is documented in mass terms of the type of steam. These figures alone

are sufficient in calculating the energy content. Pressure is the main influences of the energy

content of steam; high-pressure steam contains vastly more energy than low-pressure steam. The

correlation between pressure and energy content can be found using steam tables and

consequently related to the total energy content10. The first step is converting the mass figures

(kg, ton, etc.) values into energy figures.

steampTsteamMhE ⋅=

,

hT,p = Total specific enthalpy (usable heat) at corresponding pressure

Msteam = Steam mass quantity, kg

It is common engineering practice to mention the stream pressure along with the mass flow. The

second step in energy determination is to find the corresponding enthalpies:

peplpT hhh ,,, +=

hl,p = Specific enthalpy of saturated liquid at corresponding pressure

hl,p = Specific enthalpy of saturated vapour at corresponding pressure

The resulting graph depicts the enthalpy content for steam at varying pressures. The formulas are

used to compile a calculative model based on pressure inputs.

Total Steam Specific (Usable) Enthalpy

y = 384.4x + 2291

y = 246.85Ln(x) + 2989.1

2500

2750

3000

3250

3500

3750

4000

4250

0 20 40 60 80 100 120

Pressure /bar

Enthalpy /kJ.kg

-1

Figure 1 Steam Chart for Energy


Using the same steam charts and tables the entropy values can also be collected to determine the

exergy content following the physical exergy formula:

( ) ( )0000 STHSTHEx ⋅−−⋅−=

H = enthalpy content at corresponding pressure

H0 = enthalpy reference, 104.8kJ/kg

T0 = reference temperature, 298.15K

S = entropy content at corresponding pressure

S0 = entropy reference, 0.367kJ/kg⋅K

The resulting graph depicts the exergy content for steam at varying pressures.

Total Steam Exergy Content

y = 136.46Ln(x) + 499.78

y = 366.58x - 297.75

y = -0.0165x2 + 3.3112x + 891.99

200

400

600

800

1000

1200

0 20 40 60 80 100 120

Pressure /bar

Exergy /KJ.kg-1

Figure 2 Steam Chart for Exergy

The result of these empirical graphical depictions is that steam does not have an energy and

exergy content ratio of 1:1 and is a function of the steam pressure. At standard pressure steam

conditions (11bar and 180°C) the ratio between exergy and energy content in steam is 0.231. The higher the pressure (and temperature), the higher the energy-to-exergy ratio. The maximum ratio

is 0.26 at pressure of 50 – 75bar (or 260 - 290°C). This translates to means a greatly lower work

potential than energy content of steam.

The third step is determining the cumulative energy and exergy content. It follows the same

procedural steps and assumption as with electricity. Modern steam generation plants are highly

energetically efficient and are fed by the most suitable fossil fuel for the maximum transfer of


chemical energy to heat energy…natural gas. The boiler is the naturally the largest source of

losses; energetically ranges from 80 – 90%, 86.5% for standard conditions. It certain

circumstances it can approach 100% energy transfer with high tech methods, but is usually not

done: 85% will be assumed. Exergetically the work potential transfer is much worse rangingn

between 40 – 50% depending on the system layout. The upper-range value of 50% will be taken

to represent a BAT plant.

Combining the relation between production requirements and the contained output in steam

there is actually more energy necessary than exergy. Following logic, as was the case with

electricity, one could conclude that more exergy is required to produce steam than energy. This is

not the case as is illustrated by the following example:

Example – 1ton of steam at 11bar:

Energy: 1ton of steam = 3.6GJ

- at a production efficiency of 85% yields 4.2GJ of input which in terms of natural gas translates

to 133m³ of natural gas.

Exergy: 1ton of steam = 0.827GJ

- at a production efficiency of 50% yields 1.65GJ of input which in terms of natural gas

(0.03165GJ/m³ and 1.05Ex/En) translates to 49.7m³ natural gas.

3.3.3 Standardized Ratios

The following table lists the standardized ratios for the chemical energy and exergy for the major

fossil fuels present in the calculation matrix.

Table 1 Energy source factor

Factor Naphtha Natural Gas Coke Fuel Oil Electricity Steam*

Energy 1.0 1.0 1.0 1.0 1/0.45 1.0 Exergy 1.055 1.05 1.0 1/1.07 1/0.35 1/0.231

*At 150°C/4.8bar the energy to exergy ratio is 0.231 (see Section 3.3.2)


4 Detailed Processing Values and Calculations Many of the bioprocessing steps within the conceptual layout of the biorefinery do not yet exist

necessitating the development of process schematics which are generated from scratch using

process-based assumptions. The process conditions, values and data needed to calculate the

direct energy and exergy and the corresponding cumulative energy and exergy can be determined

using process simulation software.

4.1 Aspen+

There are scores of process simulation software available on the

market for industrial systems. The most popular and powerful in

terms of chemical processes is Aspen+. It does however have a major

drawback; for many of the newer biobased processes it does not have the base chemical

components standard in their database. NREL developed an add-in update for biocomponents

which are related to, in particular, bioethanol processing11. Furthermore, many bioprocesses are

batch processes and also do not necessarily make use of standard chemically-based unit

operations. This fact can lead to difficulties. Aspen+ is still nonetheless the best simulation

program available. Once the process flow diagram has been entered in the program the resulting

streams are used to determine the energy and exergy.

Figure 3 Distillation Unit Cut

Energy is easier to determine as they are included in Aspen as heat and work streams, assuming

the layout has been properly constructed. Exergy is slightly more complex which requires a

detailed look at the individual process unit operations. Take for example the above distillation

unit (Figure 3). The streams of relevance are the input streams (both material and heat) and the

state of the output streams (both material and heat/work). The program calculates the enthalpy

and entropy state of each stream. The physical exergy flow of the bottoms-stream is determined

by using the B-M02 and B-M04A thermodynamical state and subtracted by the work/thermal

stream influence (B-Q05). Each unit operation can be treated like a block box with the details of

minor importance, only the input and output mass and work streams matter. This procedure

calculates the direct energy and exergy flows in the individual unit operations; it must be repeated

throughout the entire process layout. Lastly, the type of energy stream involved in the unit

operation is brought into relation to determine the cumulative energy and exergy demand.


4.2 Process Flow Diagrams

With the detailed knowledge of the entire process dynamics the energy and exergy flows can be

used to construct two graphical diagrams; a Sankey diagram for energy flows and a Grassman

diagram for exergy flows12. They highlight the losses in energy and exergy throughout the entire

system, respectively. It becomes vastly more difficult and complex to construct such a diagram

over an entire life cycle process chains but could in theory be done. They are primary used to

highlight the stark difference between energy and exergy flows in highly thermal processes.

4.2.1 Energy - Sankey Diagram

1050kW

Gas Burner

30 kW

2 82kW

4 35kW

Electr icity

30kW Air Comp ressor

36kW

R290 Compressor

370kW Elect ricity

150 °C H eat Stream

Dist illation

273kW

6kW

70 °C

H eat Stream

115kW111kW

10kW Heat Chan ge

100kW Loss

40°C Heat Stream

1kW Transpor t Lo sses

Heat Pump

38kW

Heat Ch ange

28 kW Lo sses

36kW R290 Compresso r

304k W Losses

166kW

Hea t Ch ange

4kW L osses

29kW

Figure 4 Sankey diagram – example power plant with off-heat utilization

4.2.2 Exergy – Grassman Diagram

1000kW

Gas

B urner

199kW

381kW

435kW

E lectr icity

30kW

Air C ompressor

36kW R290 C ompressor

370kW Electricity

150°C Heat Stre am

Distillation

356kW

24kW

70°C Heat S tream

356kW

Greenhouse

381kW

318kW

Heat Potential

68kW H eat Loss

40°C Hea t Stream

50kW Transpor t Losses

Heat P ump

30kW

H eat Losses

155kW

Heat Tr ansfer

36kW R290 Compr essor

Figure 5 Grassman diagram – example power plant with off-heat utilization


5 Cradle-to-Factory Gate Methodology

5.1 Mass and energy balances

For those processes that are well documented, the thermodynamic state of the internal heat and

power streams can be studied to accurately determine the cumulative energy and exergy demand.

In other systems, key information may be confidential or simple not present. In such situations,

the simplification of relying on the mass and energy type balances is utilized with the above

conversions table (Table 1) frequently being used. In rare cases, the details pertaining to the

energy type is not mentioned, but instead a total value is provided. Here a comparison between

plausible and similar processes is made to determine the heat and power mix involved to be able

to estimate the relative cumulative energy and exergy demands. Many other inputs streams are

straightforward directly using conversions. It is merely the task of tracing the process chain back

to the original fossil fuel energy input and, in cases of cracker products, to the cracker.

5.2 Existing Chemical Production Routes

The entire purpose of compiling cumulative energy and exergy demand calculations is to

determine the largest fossil fuel replacement potential within the existing petrochemical chain

through systematic comparison. The LCA database and program Boustead (with portions of

BASF internal processing figures) was employed to acquire the direct energy demand of existing

petrochemicals13. Using the detailed information regarding the electric/stream inputs and

feedstock quantities the CED for some major petrochemical products is as follows (Figure 6):

54.16

70.52

61.58

53.48

84.29

85.56

78.43

30.99

34.64

68.04

132.09

45.5

43.2

70.81

65.48

114.7

93.51

81.07

67.03

133.2

54.48

35.69

59.11

73.57

36.25

73.85

50.1

19.65

142.31

180.52

128.2

76.46

53.39

44.16

67.44

80.02

83.98

72.67

46.38

74.7

66.71

0 20 4 0 60 80 100 1 20 140 160 180 200

Ace tic Acid

Aceto ne

Acrylamide

Acrylic Acid

Acrylic Est ers

Acrylon itrile

Ad ipic Acid

Ammo nia

Ammo nium Nitr ate

Benze ne

Ben zoic Acid

Bu tadie ne

Buta ne

Butan diol

Bute ne

Capr olactu m

Cyclo hexa ne

Dime thylamine

Ethyle ne

Ethylen diamine

Et hylene Glycol

Fo rmaldeh yde

Hexa ne

Hydr oge n Cyan ide

Metha nol

Meth yl Met hacr ylate

Naph tha

Nit ric Acid

Nylon 66

Nylon Fib er

O xalic Acid

Phe nol

Pho spho ric Acid

Pro pan ioc Acid

Prop yle ne

Stea ric Acid

Styre ne

Tolue ne

Ur ea

Vinyl Acet ate

Xyle ne

Cumulative Fossil Fuel Energy Demand GJ/ton P roduct Figure 6 CED – Cumulative Energy Demand of Major Petrochemicals


With the same detailed process information the cumulative exergy demand can be determined. In

most cases it is only a small factor of 5% higher due to the large influence of the feedstock, i.e.

naphtha and natural gas. Nevertheless, each chemical product is follows an independent process

route and can vary. Presented below is a graph (Figure 7) of the cumulative energy and exergy

demand for those petrochemicals which are envisioned to be replaced by the potential chemical

biorefinery layout presented in this dissertation report:

Relevent Petrochemical Products for Biorefinery

67.0

76 .5

84.0

72.7

114.7

61.6

78.4

31 .0

114.7

81.1

133.2

119 .0

119 .0

87.3

34.6

35.7

67.4

81.1

128.2

4 6.4

45.5

68.1

75.8

8 4.5

73.7

110.7

6 2.0

75 .4

23.0

110.7

7 3.6

130 .4

119.4

119.4

84.3

32 .3

33 .9

68.4

7 3.6

120.2

4 3.2

45.7

0 20 40 60 80 100 120 140

Ethylene

Phenol

Styrene

Toluene

1,4-butandiami ne

Acrylami de

Adipic acid

Amm onia

e-caprolactum

Ethylami ne

Ethylenediami ne

F eed grade cystei ne

Feed grade m ethioni ne

g-butyrolactum

Ionic liquids

Isobutyraldehyde

Isoprene

Isopropanolami ne

Oxalic acid

Urea

B iolubricants

Fossil Fuel Demand (GJ/ton)

Exergy

Energy

Figure 7 CED & CExD of Petrochemicals Relevant for a Biorefinery


6 Conclusion In conducting a comparative energy and exergy life cycle analysis detailed information pertaining

to the individual processes must be known. In some situations, sufficient details are not present

meaning simplifications and assumptions must be taken. A dilemma faced by many professionals

conducting LCA’s (life cycle assessments) is that different forms of energy inputs and different

expressions for these energy types are commonly presented. It is standard practice to list the

energy inputs separately, such as steam or electricity, but also common to simply combine the

inputs as one total figure. Calculation of the cumulative energy demand requires the energy life

cycle to be brought to the cradle. Only then can the extent of the original fossil fuel energy input

be properly assessed. This requires base values and assumptions. Such were listed for their

determination, but solely following the first law of thermodynamics makes no distinction

between the quality of these different energy forms. Therefore, along with the base values and

assumptions for energy calculations the same information was provided for determining the

cumulative exergy demand. Exergy is the thermodynamic measure of the quality of energy flows.

These base data form the guidelines for all the subsequent calculations of the various inputs in

the cradle-to-factory gate matrix. And despite no concrete examples been given on the

importance of exergy, potentially large differences that could emerge between energy and exergy

within the compilation of the calculation matrix will reveal major energy efficiency improvement

options. In the broad field of alternative energy, additionally assessing the quality of energy flows

(read – exergy) can provide the necessary insight to vastly save on the fossil fuel energy

feedstocks throughout the process chain.



References 1. Arons, J. d. S.; Kooi, H. v. d.; Sankaranarayanan, K., Efficiency and Sustainability in the Energy and

Chemical Industries. Marcel Dekker, Inc.: New York, 2004; p 299. 2. Szargut, J.; Morris, D. R.; Steward, F. R., Exergy Analysis of Thermal, Chemical, and Metallurgical

Processes. Springer-Verlag: 1988; p 332. 3. Wall, G. Exergy - A Useful Concept. Chalmers University ofTechnology, Göteborg, 1986. 4. Wild, M.; Ohmura, A.; Makowski, K., Impact of global dimming and brightening on global

warming. Geophysical Research Letters 2008, 34, doi:10.1029/2006GL028031. 5. Petela, R., Exergy of heat radiation. J. Heat Transfer 1964, 86, (1964), 187-192. 6. Gasterra.nl Groningen Natural Gas.

http://www.gasterra.nl/aardgas/Documents/Woordenlijst_140508.pdf (10.2008), 7. ACEA - European Automotive Manufacturers' Association, Diesel versus petrol engines. In

2000. 8. Fthenakis, V. In Nuclear Power - Greenhouse Gas Emissions & Risks A Comparative Life Cycle

Analysis, California Energy Commission Nuclear Issues Workshop, Sacramento, CA, 2007; Sacramento, CA, 2007.

9. ECN Coal and Climate Change; 2004. 10. Rocchetti, M., Free Engineering Software Website In 2005. 11. Wooley, R. J.; Putsche, V. Development of an ASPEN PLUS Physical Property Database for Biofuels

Components; NREL: Golden, CO, 1996. 12. Yamamoto, M.; Ishida, M., Process vectors both to create functional structures and to

represent characteristics of an entire system. Energy Conversion and Management 2002, 43, (9-12), 1271-1282

13. Boustead Consulting Ltd. Boustead Model 5.0, West Sussex, 2007.



Chapter 3 Life Cycle Assessment vs. Exergy

Ben Brehmer

Dissertation Report


Colophon



ISO 9001:2000.

Title Chapter 3 – LCA vs. Exergy Author(s) Ben Brehmer A&F number - ISBN-number - Date of publication 1. December, 2004 Confidentiality No OPD code - Approved by - Agrotechnology & Food Innovations B.V. P.O. Box 17 NL-6700 AA Wageningen Tel: +31 (0)317 475 190 E-mail: [email protected] Internet: www.agrotechnologyandfood.wur.nl © Agrotechnology & Food Sciences Group B.V. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch, hetzij mechanisch, door fotokopieën, opnamen of enige andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. De uitgever aanvaardt geen aansprakelijkheid voor eventuele fouten of onvolkomenheden. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher. The publisher does not accept any liability for inaccuracies in this report.


Abstract Common sense may give the impression that utilising biomass, as a feedstock source for the

petrochemical industry instead of fossil fuels, is an environmentally sound alternative. Looking at

environmental issues alone will not justify or stimulate a change; implementation of biobased

resources must also be a profitable venture for the industry. Proper consideration of both issues

should be based on performing an entire life cycle comparison, from raw material extraction to

production to transport to final end use, a so-called cradle-to-grave approach. There are an

insurmountable amount of different methods and analysis tools available to compare the life

cycle of different processes, production methods and products. A problem is determining which

of these methods and tools is the best for this specific comparison and why. In terms of shifting

the raw material source of an entire industry reliable and incontestable results are more than just

essential, they are a prerequisite.

Over the last several decades, one life cycle analysis tool has dominated the field, namely the life

cycle assessment (LCA). It had expanded from small internal comparisons to large industrial

sector-based comparisons. More recently an ISO standard has been written providing

practitioners with the procedural steps to execute an LCA. From careful review of the inner

workings of the standard it becomes apparent that it is more like a suggestive guideline than an

actual standard. The lack of true standardisation places a greater emphasis on personal

interpretation and raises doubt about the reliability of the results. Therefore, it may not be the

most appropriate tool for this comparison, but many of the methodologies are advantageous.

Other available tools are also unsuitable when followed exclusively, but contain many useful

approach variations. This chapter will determine the best amalgamation of the various life cycle

analysis tool components for the provoking a raw material change in the petrochemical industry.

Key Words:

Life Cycle Analysis, Life Cycle Assessment, LCA, Exergy, ELCA, LLCA, Paradigm Shift



Content

1 Introduction 43


2 Driving Force 45

2.1 Consumers 45

2.2 Industry 45

2.3 Public 46

2.4 Government Bodies 47

2.5 Research Centres 48

2.5.1 Valorisation of plant production chains 49

3 Life Cycle Assessment 51

3.1 Description 51

3.2 Brief History 51

3.2.1 Timeline 52

3.2.2 Application 52

3.3 ISO 14040 53

3.3.1 Recipe 53

3.3.2 Framework 54

3.3.3 Goal and Scope Definition 55

3.3.4 Inventory 55

3.3.4.1 System Boundaries 55

3.3.4.2 Flow Diagram 56

3.3.4.3 Data Collection 58

3.3.4.4 Data Estimation 59

3.3.5 Impact Assessment 60

3.3.5.1 Impact Categories 60

3.3.5.2 Normalisation and Weighting Factors 61

4 Limited Life Cycle Assessment 63

4.1 Overview 63

4.2 Application 64

4.3 Environmental Impact Units 65

5 Exergy 67

5.1 Comparative Exergetic Cradle-to-Factory Gate Analysis 67

6 Paradigm Shift 69

7 Conclusion 73



1 Introduction Switching from fossil fuels to biomass as a raw material for the petrochemical industry entails a

paradigm shift. Nobody likes change; this holds true for most individuals as for most companies,

corporations and especially entire industries. Many corporate strategies are focused on the short-

term performance (i.e. quarterly profits) and systematically follow the business-as-usual pitch to

appease stakeholders. Declining fossil fuel stocks is an issue to consider and will eventually force

a paradigm shift but is still too far off in the distant future to grant serious acknowledgement by

the petrochemical industry. Government policy and regulations currently have little effect on the

economic freedom that the globalized market is providing. Thus, sparking a pre-depletion raw

material change must be beneficial to the company and stakeholders, which is essentially

expressed in monetary figures or phenomenal environmental benefits.

Life Cycle Assessment (or LCA for short) is a methodology to analyse the ecological

environmental burden of a product from cradle-to-grave. Environmental issues and concerns are

almost entirely used by policy makers. Industry is adjusting to the policies and regulations

becoming more environmentally sound, but the forced developments are still rather minimal. In

regards to the petrochemical industry, all passed policies are symptom treatments and are not

addressing the route cause, i.e. end of tailpipe solutions. It would make little sense to ban the use

of fossil fuel feedstocks in the petrochemical industry. An LCA, and what it basically stands for,

has next to no effect on influencing their strategic planning nor is it being taken all too seriously

by the industry. That is not to say that LCA’s are entirely useless, the framework, procedures and

particular figures can be borrowed to perform a similar cradle-to-grave analysis tool.

Exergy as described earlier (see Chapter 2), relates all energy, materials and services into one

figure; a work potential. The expression could be correlated with how much economic input is

required; the higher difference in input to output exergy the higher the general costs. Following

the guidelines set forth by the ISO-LCA the overall economic representation can be obtained.

Comparing the exergy differences between the petrochemical route and biochemical route from

cradle-to-grave could justify a pre-depletion raw material shift. Some key and less disputed

factors addressed in an LCA can also be beneficial to implement.

1.1 Chapter Purpose

This chapter describes the various life cycle assessment tools, their construct methodology, their

internal workings, and their limitations. As there are many different types and alterations to the

standard environmental LCA. In this chapter, the standard methodology is borrowed to create a

comparative energetic and exergetic cradle-to-factory gate assessment. The advantages of relying on exergy

values and not subjective environmental factors for the impact category is highlighted.



2 Driving Force Each sector of a society has a different stance on which issues are important and which are not.

When a change does occur their own personal interests stipulate the direction, for the outcome

should not result in a disadvantage. The best interests of one sector may not be compatible with

the interests of another societal sector. For example, a empty spot of land in a city centre;

professionals may want to see it converted into a parking lot, students into a bike stall, the elderly

into a park, families into a playground and so on. By thinking only by about their own benefits

and desires their stance is a selfish one. As Adam Smith hypothesized, self interest in a

competitive environment provides a greater good for society. Yet, the decisions are actually

determined by the city counsel deliberating over the best compromise to satisfy the majority

while satisfying developmental needs. The driving force of change is just that, a balance between

wants and needs. The following subsections relate and extend the analogy of driving force to the

petrochemical industry:

2.1 Consumers

There is not a single consumer good, which does not rely of some form of chemical treatment

and/or material supply. At some stage in the entire production chain, chemicals are required. The

consumer can be anywhere along the chain from the initial purchasers of chemical raw materials

to the end-user of manufactured goods. Yet, their wants and needs are precisely the same:

Needs

• Constant supply • Consistent quality • Consistent physical and chemical properties Wants

• Low and stable prices The driving force of the consumer is simply lowering the prices without degrading the product.

As an example, it is understandable why bioplastics like Poly Lactic Acid (PLA) have not become

a grand commercial success. They simply do not meet the driving force of consumers. Although

the physical and chemical properties are similar (they are in fact slightly worse), the increased

price does not go over well. Paying more for less.

2.2 Industry

With the progress of a free capitalistic market economy, all industries slowly lose sight of moral

and societal obligations and further focus on revenue and profit. The petrochemical industry is

amongst the largest and most influential in the world, consisting of but a few global corporations.

Such companies are organised much like a hierarchical dictatorship and operate in response to

customer demands and shareholder interests. Their wants and needs are all monetarily motivated:

Needs

• Cheap raw materials • Continuous supply of raw materials • To satisfy the consumers driving force


Wants

• Reduce overhead • Maximize profit • Continually increase production and areas of activity • Improve public image Having a continuous supply of raw materials seems like a contradiction to their apprehension

towards shifting away from fossil fuel resources. However, considering that the majority of the

petrochemical companies are less than 100 years old and the projected worldwide reserves are

anywhere between 50 –100 years, the shift is not yet of major urgency. The current crude oil and

natural gas situation is able to supply the industry with all of its needs for at least several

generations to come. Essentially, the driving force of the petrochemical industry is to further

capitalize and expand while continually meeting the demands of the consumers. In light of the

PLA example, it does indeed comply with the goal of increased activity and improved public

perception, but only that. The raw material and production is more costly than the traditional

chemical route and to be able to satisfy the consumers driving force, the lower properties must

be compensated with an even lower sales price. Overall that would sacrifice profit, increase

overhead and be in contradiction to the industry’s driving force.

2.3 Public

In the developed world, citizens are becoming ever more affluent at a tremendous pace. The

prosperity is shifting the desires of the people from basic necessity to materialism. Simply put, if

they can afford more they want more. To cover these demands nearly everything that can be

mass-produced is. Along side this increase of secular wealth an increase of informational wealth

has come. Public awareness and general knowledge provided by affluence is beginning to address

the indirect problems associated with affluence driven materialism. The environmental burdens

of their lifestyle are becoming apparent and the general consensus would like to see mother earth

and her nature preserved without any serious harm or long-term damage. This warrants an

inconsistency in the needs and wants of the public:

Needs

• Basic survival, i.e. food and shelter • Extras as stipulated by Maslow’s hierarchy of need Wants

• More availability and selection of consumer goods • Increased quality and functionality of consumer goods • Lower prices for consumer goods • Preservation of nature • Lastly, lowered environmental damage impact Generally speaking the public aspires to further increase their quality of life. In assessing the

public’s view the wants clearly distort the needs. Receiving adequate food and shelter is such a

basic right in the entire developed world that it does not need to be addressed in the driving

force. Thus everything that steers the public driving force are basically wants, and yet even within


these desires are contradicting issues. It places a great uncertainty of what the actual driving force

is. Continuing with the example of PLA, being derived from biomass has the perception of being

environmental sound and less damaging. However, comparing it to the standard fossil derived

plastic it is inferior in the quality-to-price ratio. The lack of public acceptance indicates that the

general populace are not willing to pay additional money for a lesser product solely in the name

of the environment. On one hand they point the finger at industry for polluting the environment

and on the other hand they are not willing to pay for its protection. The driving force of the

public can be paraphrased as thriving for more and better products at cheaper prices with the

environmental issue lingering in the background.

2.4 Government Bodies

In a democratic government the voice of the people and the societal fractions are all represented.

A healthy system provides many different viewpoints, stances, and options of representation

while including many of the grey areas. The majority of the voices are taken into account and are

acted upon with the best intentions of the society as a whole. In many cases, however, the

holistic approach is faced with severe opposition. To maintain power, seat, and the popular vote

they will often side step or completely disregard unfavourable issues. The needs and wants

illustrate the popular voice bias:

Needs

• Voice of the public • Voice of the industry • Voice of the consumer Wants

• Win the popular vote and become re-elected • Change the system to match their political agenda Peaceful governments have the power to shift and mould society’s structure through the use of

policies, regulations, guidelines, taxes, subventions and research grants. It is a tedious and

difficult task to govern a society on a holistic approach or even determine what the best

intentions could be. Many governments succumb to their wants and base policies to gain the

popular vote through small gradual changes. Heated issues, which involve a large paradigm shift,

can be proposed by contracting and granting research institutes the finances necessary to

determine a multitude of different alternatives with usable results always the next parliament’s

concern. Decisions are usually based on the popular voice of the public, but also take other

fractions and political agendas into consideration. Therefore, the driving force of government

bodies is to maintain their rule by finding the most popular compromise between the societal

fractions. In regards to the PLA example, government bodies could force their implementation.

Perhaps by placing high tariffs on fossil-based plastics and providing large subsidies for biobased

plastics. The public (representing the popular vote) would be pleased, however, the

petrochemical industry and their consumers would not and they could argue unfair trading

practices which could cause performance losses on the international free market. Losing market

share could spiral down into the local economy and influence the public’s affluence thus


effectively removing the popular vote. The environment an aspect of the driving force, but is a

contradiction within itself. In cases of uncertainty, concerning environmental policy, is it best to

consult outside research groups to gather enough information to properly assess the best

compromise.

2.5 Research Centres

Technology over the last century has reached such a complexity that mere individuals can no

longer contribute to new innovations and breakthroughs. Key historical figures like Gottlieb

Daimler, Karl Benz and Wihlem Maybach were responsible for the invention of the automobile.

Alone they could not make such a significant technological discover today. Presently, horrendous

sums of money and a collective of highly educated personnel are required for even the smallest

contribution. Research centres are just that, institutions with the finances and intellect to perform

minor technological advancements. There are two major types of research centres; progressive

development centres geared towards consumers desires, mainly funded and operated by industry,

and innovative development centres geared towards public desires for example of environmental

concerns, independently operated but funded almost exclusively by government. Paradigm shifts

are the product of the latter but have trouble balancing their own needs or wants:

Needs

• Grants and funding • To specialize and operate in a niche sector • To satisfy the public driving force Wants

• To see full-scale implementation of their research, i.e. acknowledgment • Additional grants and funding Being independently operated does not imply an independent choice of research topics. No, to

be eligible for funding they must address issues of public interest deemed worthy of or of interest

by the governmental policy makers. Seeing that governmental grants are limited the centres must

chiefly operate on a specific niche within the two major categories within the biobased economy;

fossil fuel replacement and environmental protection. Their driving force is to expand financial

and operational capabilities by encompassing the concerns of the public. Linking this drive to the

PLA example a blind spot becomes apparent. Research on the PLA alternative is conducted

because it is based on a renewable biomass feedstock and thus should simultaneously tackle the

problem of fossil fuel depletion and environmental destruction. Numerous different areas of

research are possible; plant cultivation, plant modification, logistics, production, enzyme

engineering, synthesis, extraction, applications, policy, environmental benefits, and so on. The list

is nearly infinite; however, there is a standard emerging addressing both fossil fuel use and

environmental factors, the LCA. Once the fundamentals have been determined an LCA can be

employed to fulfil their driving force. It is meant as the final corroboration that the government

bodies are seeking. Yet, by focusing on public concerns and government desires considerations

of the industry are clouded. To overcome this vital flaw reports are written in passive voice to

stress that they are possible long-term alternatives, always 10-years away. PLA may be better for


the environment and require less fossil fuel but it still remains too expensive for acceptance in

the current market. Although not directly foreseeable, but disregard to industrial desires will

prevent research centres from ever obtaining their own wants.

2.5.1 Valorisation of plant production chains

Shifting from a fossil fuel based economy to a renewable fuel based economy is clearly a

challenge. Presently, nearly the entire economy is based on the abundance of cheap fossil fuel

resources; sparking or suggesting a change is bound to generate some opposition. Yet, this does

not have to be. Several technologies and methods are already available to convert some industrial

sectors to renewables without economic concessions. LCA is the valorisation of production

chains following the standard driving force. To entice implementation for the immediate future

an addition need must be added:

Addition needs:

• To satisfy the industrial driving force To satisfy the interests of industry environmentally-based LCA’s are insufficient and must be

expanded upon. Incorporating exergy, as an additional impact category parameter, can valorize

the production chains following the revised driving force. Alterations and careful consideration

are, however, still necessary as an LCA is littered with inconsistencies, flaws and most

importantly doubts. Ascertaining the shortcomings while preserving the benefits and key

characteristics in combination with an exergetic analysis will create a new tool:

An ELCA, Exergetic Life Cycle Assessment.



Cradle-to-grave Assessment considers impacts at each stage of a product's life-cycle, from the time natural resources are extracted from the

ground and processed through each subsequent stage of manufacturing, transportation, product use, and ultimately, disposal

Source: EEA

3 Life Cycle Assessment

3.1 Description

As with most terms laid out in the English language, life cycle assessment uses esoteric

nomenclature to add a hint of confusion in aims of suggesting more than what is intended.

German on the other hand, is direct and describes more or less exactly what is intended. Before

the term LCA was conjured up, the German term Ökologischerbilanzerung or Ökobilanz had been

assigned. Translated it means ecological balancing or eco-balance. Taking the mathematical

understanding of the word balancing (equality with respect to the net number of reduced

symbolic quantities on each side of an equation) the term is almost self-explanatory. The essence

of an LCA is thus to quantify all factors of a particular product or service completely from the

beginning to end (cradle-to-grave) in light of ecology. It

will result in assigning all the various ecological and

environmental impact categories with numerical figures.

The English term has focused upon the cradle-to-grave

portion, which has been substituted by the broad term life

cycle. Negating the term ecology and using general

terminology suggests a much larger impact and area of

“assessment”. Yet the heart of the assessment remains the same, to balance and quantify the

ecological factors. The first associated problem already appears with the simple naming of the

analysis tool. For even research groups dealing with LCA’s are becoming misled and are starting

to view it as a final corroboration.

3.2 Brief History

Long before the presence of life cycle assessments and analyses, industry had based their process

optimisation on a straightforward energetic reduction approaches. This was achieved by focusing

efforts on optimising existing energy intensive processes and individual production steps.

Towards the latter part of the 20th century industry began to look at other cost saving methods in

a more holistic approach. A transition in reducing energy consumption from individual energy

flows to entire energy flows from raw materials to end products slowly emerged. They were

basically performing an energetic life cycle analysis yet the term of choice was a multiciteria study. It is

rarely disputed that the first was back in 1969, when Coca-Cola had contracted the Midwest

Institute of Kansas City to perform a multiciteria study of their bottle production. The aim of the

study was to determine the lowest energy and environmentally related costs between the option

of using glass or plastic bottles to market their product. In addition, it was discussed whether to

have internal or external production. Afterwards, many other large companies had started using

multiciteria studies to compare different product options. The main focus remained on energy

and material flows, ultimately those streams connected with an economical value. It was not until

decades later when environmental impact took centrefold, see Figure 1.


3.2.1 Timeline

Figure 1 Developmental Timeline of Life Cycle Assessment

3.2.2 Application

One of the first eco-balance methodologies was created by EMPA (Eidgenössische Materialprüfungs-

und Forschungsanstalt or Swiss Federal Laboratories for Material Testing and Research). Their self-

proclaimed purpose was directed at the internal determination for process optimization based on

ecological considerations for industry. Companies would carry out internal life cycle comparisons

following their methods to help conclude which of the product or process options has the least

environmental burden. At the time focus was on energy, raw material use, and complying with

pollution regulations. Industry was in effect employing (although limited) the eco-balancing based

on fulfilling their own driving force. Partly because of increasing environmental regulations and

fines and partly because of government body interest, the shift became predominately

environmentally based. As more standards and guidelines were created the LCA took shape and

by 1997 the LCA as it is known today was born. Institutionalized standards have made it possible

for outside appraisers to perform analyses for not only comparative purposes of minor changes

but of large scope paradigm shifts. Here the first problem is confronted; the rationale had been

altered. Comparisons were being shifted from internal company issues to entire industrial sector

issues. Due to the shear broadness, a lack of precision emerged questioning the accuracy of such

analyses. Fortunately standards may help overcome this problem, but the standards are in fact

general guidelines. Emphasis of personal interpretation has removed absolute quantitative figures

with subjective quantitative figures.

1965 1970 1975 1980 1985 1990 1995 2000 2005

1969Coca-Cola

Multi citeriaBottle Production

1974

EMPAMethodology for

eco-balance

1984EMPA

First publication “ecologicalreport of packaging material”

1991

SETACFirst works

1992EU

Scheme foreco-labelling

1992

SPOLDData exchange

standard

1992

FranceNFX30-300

LCA standard

1996

GermanyDIN33926

LCA standard

1997-2001ISO

ISO14000 to 14050 asinternational LCA standard


3.3 ISO 14040

ISO is not an acronym for the International Organisation of Standards as is commonly believed;

it is derived from Greek isos, meaning equal. The organisation has been established to unify other

national standards for worldwide industrial and commercial use. Seen any way ISO represents

efforts towards global standardisation. The ISO 14040 series is meant to be the standard for

executing an LCA study. Unfortunately it is not actually a standard per se and therefore is not a

clear-cut procedure, method, or formulation to follow. The room for personal intervention and

interpretation makes it more like a guideline or even as nebulous as a general recommendation.

3.3.1 Recipe

For those people familiar with the ISO 14040 series, its methodology has been compared to that

of a cookbook recipe. Indeed, there are sequential procedures to follow much like a cooking

recipe. The cookbook analogy has become common LCA terminology that most, if not all

textbooks refer to the recipe format. Again here, the terminology is misleading and

presumptuous in its abilities. Making an analogy between the cooking procedures and the

procedures of a standard like that of an ISO standard is possible and actually quite clever. Both

require specific input figures and precise procedural steps to produce a coherent final result. The

problem with the ISO 14040 series is that it is not an actual standard, so the justification to

continue with the analogy is annulled. A cooking recipe is designed to consistently reproduce the

same culinary product every time should the steps are meticulously followed. For example, when

preparing the internationally renown Dutch pastry, the Spacecake, specific ingredients and

quantities, preparations, oven settings, cooking utensils, etc. are all listed and well documented.

Anyone following the recipe correctly, with adequate knowledge in the fundamentals of cooking,

should bake the exact same cake every time. A guideline does not comply. In terms of cooking a

guideline would be like having a general recommendation of what ingredients to use in baking a

cake while proving the principles of baking. Everyone following the recipe guideline would bake

something slightly different, they may all be cakes but rarely will they be the same. This is

precisely the problem with the ISO14040, for the results will vary with each individual analysis

and is only worsened by the scope size, since broadening the scope will simultaneously broaden

the deviation and uncertainty. A large scope may yield extreme deviations like an Chocolate cake

to a Vanilla cake. Looking back to the origins of the eco-balance system, the scope was much

smaller and kept within the companies’ own knowledge base. Following a guideline, like an LCA

for narrow internal options will reduce the deviance and dilemma of variance. A small scope may

yield minor deviations, like a particular type of icing on a chocolate cake. As ingenious as the

recipe analogy may appear it is completely inappropriate for the new ISO 14040 series and only

increases the doubt surrounding its application.


3.3.2 Framework

The heart of the ISO 14040 series is graphically expressed by the following figure:

Goal and ScopeDefinition

InventoryAnalysis

Impact

Assessment

Interpretation

Direct Applications- Product

development andimprovement

- Strategic planning- Public policy

making- Marketing

- Other

Figure 2 ISO 14040 Life Cycle Assessment framework procedure

The largest box and largest factor in Figure 2 interpretation. All other aspects and steps are

dependent on the interaction of the appraisers interpretation. This is undoubtedly the fatal

problem associated with an LCA; how can anything be concretely determined if the analysis is

entirely based on personal interpretation. In a world of some 6 odd billion people, the amount of

viewpoints, intelligence, education, logic and experience is just as diverse as the population.

Interpretation is a mix of these and other factors of an individuals personal feeling. Who is to say

who is right and who is wrong? Even within the relative fields, different specialists will interpret

the same set of data differently. A classic example of contradicting views of data interpretation is

that of global warming. Most scientists agree that there is enough conclusive evidence available to

deduce that carbon dioxide and other manmade emission gases are responsible, whereas other

scientists interpret the data as being inconclusive. The debate continues to this day and who can

without hindsight really say who is right. General logic is also unreliable, as a global issue will

present a global array of logic. Any capable scientist should be able to draw the conclusions they

want simply by interpreting the data differently. But as before, these problems are relative to the

scope size, for a narrow highly specific topic assessed by relative specialists will bare a strikingly

similar interpretation. This stems back to the issue of application. An internal process or product

option comparison will involve specialists in their own relative field of specialty in a relatively

narrow scope of assessment. For these industrial applications, the problems of interpretation in

the LCA framework is limited and can even be beneficial, should there be a unanimous


agreement. Conversely, as the scope expands and is addressed by various external bodies with

differing stances, the interpretation becomes increasingly subjective. It is best to comment on

each of the framework points separately to comment on their strong and weak points.

3.3.3 Goal and Scope Definition

When starting an analysis of any kind one must raise the questions; what to do and how to do it.

The goal and scope accomplish precisely that and dictate all the procedures and views thereafter.

SETAC, the society of environmental toxicology and chemistry states: “The study goal and scope are

crucial to managing and co-ordinating a life-cycle study by bringing together the LCA information needed to make

an identified decision and an understanding of the reliability and representativeness of the LCA.” Like most

reports and analysis, in a few sentences the goal portion explains the purpose and reasoning for

carrying out such an investigation. The scope on the other hand is slightly more complex in its

execution; the type of LCA and the extent of the investigation are laid out. This step will govern

how the analysis will be handled and what conditions will be considered. Along with it figures

and settings, such as functional units and reference flow, for a correlative comparison are listed.

Expressed in a short text, readers have the opportunity overlook the base assumptions and

simplifications. This is a wise and sound procedure, for should the reader spot any disagreements

or discrepancies they can immediately disregard the study. A similar layout can be adopted for

other analysis tools such as with the ELCA. The only problem is the freedom in the depth of the

scope, which can only really be properly ascertained in the following inventory step.

3.3.4 Inventory

3.3.4.1 System Boundaries

The single most important aspect of any cradle-to-grave analysis is the proper and complete set-

up of the system boundaries. It makes little difference which analysis tool is used this step will

always be filled with doubt, incompleteness, and problems. Where to “draw-the-line” is a question

that can never be properly answered. The scope definition of the analysis is able to reduce the

size of the system boundaries through simplifications. Here the route of the scope problem can

be pinpointed; for the larger the scope, the larger the necessary simplifications and assumptions.

Obviously with a higher demand of simplicity the more inaccurate the results become.

Take again PLA as an example, the entire cradle-to-grave production of the bioplastic must be

determined and compared to the standard plastics. Where to draw the line? At the harvesting

stage, should the production of trackers be accounted for? Should the production of the tires for

the trackers be accounted for? Should the production of the machines for the rubber extraction

for the tires be accounted for? Should the production of steel for the rubber extractors be

accounted for? The list is endless and would eventually cover every aspect of human activity. The

nature of the ISO guideline provides freedom of interpretation to simplify the boundaries as seen

best fit. However, this freedom allows anyone performing an LCA to arbitrarily draw the cut-off

line. It is argued that a sensible cut-off has an error in the range under a single percent. Perhaps


this is true, but as each individual LCA will deviate based on personal choice and further increase

with the scope, a complex LCA could become inconclusive. A smaller comparison like with Coca-

Cola’s bottle choice has much less emphasis on cut-off determination. In contrast to a large

assessment like PLA, many of the chains remain the same or are similar between the two options.

Drawing the few necessary cut-off lines is uncontested in light of the scope. Generally speaking,

the smaller the scope the more accurate and reliable the LCA becomes.

The system boundaries required for an exergetic analysis are slightly different and remarkably

more constricted. Only the steps with an induced change of exergy or require an exergy input will

it be contained and considered within the system. In terms of PLA, the trackers increase the

exergy by collecting the crops to a central location and consume exergy in the form of fuel;

thermodynamically the entropy is increased. How they are made or how much input they require

is practically negligible in exergy terms. The boundaries are clearer, more transparent.

3.3.4.2 Flow Diagram

If a picture says a thousand words than a process flow diagram says ten thousand. Groups of all

processes, inputs and output stream are linked together to illustrate the entire system within the

specified boundaries. It acts as the graphical representation to better describe the entire life cycle

of the process and better develop the process. Errors and inconsistency can be found with

relative ease and while through flow diagram comparison location of gaps or missing streams is

greatly improved. It is a valuable tool and acts more like a true standard than a guideline. The

room for personal intervention is limited to the visual representation and not the content. A

small portion of a flow diagram can easily expand on the comparison of the system boundary

difference between the LCA concept and the exergy concept for PLA:

Harvesting

cropsdiesel

DieselSeparation

& Purification

Cultivation

lubricants

Botteling

fresh water

harvesters

Harvester

Manufacture

trackers

Tracker

Manufacture

waste

electronics

steel

electricity

rubber

Figure 3 LCA flow diagram section


Harvesting

cropsdiesel

DieselSeparation

& Purification

Cultivation

lubricants

Botteling

fresh water

harvesters

Harvester

Manufacture

trackers

TrackerManufacture

waste

electronics

steel

electricity

rubber

Figure 4 Exergy flow diagram section

In these flow diagram exurbs, all the steps proceeding and connected to the harvesting step are

depicted. It can be seen that the life cycle components and flows are identical in both procedures.

However, there is a clear and substantial difference regarding the boundaries and thus the cut-off.

The purple dashed line indicates the system boundaries. In the LCA exurb (Figure 3) the

manufacture of the harvester and tracker are considered but could be cut-off at this point. This

may or may not have a large impact on the result, for the chance is present that another appraiser

could incorporate processes further down the line. Incidentally the opposite could also happen

and machinery could be considered as a single input flow without other process considerations.

The freedom for interpreting the system boundary is less with the exergetic flow exurb diagram

(Figure 4). Only those process steps, were an induced exergy change is subjected upon the overall

product chain are contained, are assessed within the system boundaries. The result from cradle-

to-grave will be the total cumulative amount of exergy flow to the product to derive at the final

product. The side chains are not as important as they adhere to their own production chain route,

which is exergy terms are generally negligible. Using a tracker with a harvester is not the only way

to harvest crops; it could very well be performed by manual labour. The result of the product in

question (here PLA) is influenced by the exergy fuelling that choice, but optimising these side

chains does indeed require a separate independent analysis. An LCA should be handled in the

same manner to prevent personal intervention, especially when comparing paradigm shifts.

Unfortunately, this is not the case because the ISO 14040 series calls for personal interpretation

and the process flow diagram merely strengthens the fallacy of scope size.


Limited Scope Large Scope

Figure 5 Scope size difference illustrated on process flow diagram

With help of the graphical flow diagram (Figure 5) the differences between scope size is clearly

evident. Above is a fictitious process with two different scope sizes definitions, one limited and

the other large. Freedom of definition allows the boundary to be drawn anywhere between the

two extremities. Here the problem of increasingly large scope size is visualised.

3.3.4.3 Data Collection

“Get your facts first, and then you can distort them as much as you please.” – Mark Twain.

To quantify the system and processes within, numerical values are required. An LCA practitioner

must collect data from various sources to fulfil the necessary process information. The

methodology is logical, straightforward, and corresponds with any other form of data collection.

It is suggested to obtain the data how ever possible through an assortment of means like

industrial questioners, interviews, reports, references, articles, databases and so on. To this day

there is still no international standard for data exchange, stressing careful consideration of the

figures and units. Conversion and use of matching nomenclature such as CAS chemical numbers

is strongly advised. Several life cycle inventory (LCI) databases have been created in the last few

years; such as EcoInvent, EcoSpold, APME plastics to name a few. These process values are a

great start but are in no means perfect and must be thoroughly examined before being verified.

The reason is that LCI databases are a collection of independently conducted LCA’s adhering to

their own assumptions and simplifications. Process data can vary from LCI database and for

implementation in another LCA the goal and scope (or base assumptions) must coincide to be

realised. Regardless of how many thousands of processes are registered in the databases they are

still insufficient to complete most LCA’s, especially new biobased production routes. At this

point, an obstacle for the environmental aspects of an LCA appears. Industry has extensive

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knowledge and figures regarding their energy (heat and electricity) consumption, raw material use

and their basic pollutant emissions. Many companies are unwilling to relinquish even this limited

information to the public. Eco-balancing in the traditional sense, does not encounter this hurdle

as it based on internal assessments and therefore has access to all values. The term hurdle and

obstacle is a prudent choice as the lack of data can be overcome.

3.3.4.4 Data Estimation

“Where facts are few, experts are many” – Donald R. Gannon

Process data must correspond to several specific specifications for realisation in the system. The

exact specifications are listed in the scope definition and are analogous with where, what, and

when. What is understood with ‘where’ are the locations and local environmental conditions.

What is understood with ‘what’ are the desired emissions and assessment aspects. What is

understood with ‘when’ is the technology status, like state-of-the-art or conventional. No matter

how complicated or elementary the system, the collection of data will never completely satisfy the

specifications. Estimations are inevitably required. Although, it may seem like a reoccurring

theme, data estimation is another form of personal interpretation. Again here an increasingly

large scope puts extra strain on the field of estimation and raises the question of doubt.

The Coca-Cola multiciteria eco-balance is a great example to demonstrate the problems

associated with data estimation through scope size and viewpoint. The small scale and internal

comparison between plastic and glass bottle production must have required little estimation.

Working with specific goals and production specifications internally, they had access to accurate

and directly corresponding data; i.e. the Atlanta glass production plant and the Atlanta plastic

bottle production plant would have readily provided all the required input and output figures.

Other local companies contained within the system boundary must have also provided the

appraisers with complete and actual up-to-date data of the production. Representative data

estimation was kept at a sheer minimum, as the actual production figures were available. An

outsider may not have had access to all the data and may even want to address the entire industry

and not a specific plant. Assumptions, simplifications, and averages are necessary. To the ‘where’

issue, it may be extended to a country, continent or even world averages. Should data from

existing worldwide conventional glass plants be used or the western state-of-the-art facilities? To

the ‘what’ issue, the differences in emissions levels regulations vary from district to district and to

a much larger extent from country to country. Should the regulations of one area be extrapolated

to another? To the ‘when’ issue, the time of data collection and representation is covered. Can

production data from the 1990’s be descriptive enough for a plant proposed for 2010?

Accordingly, considering an outside practitioner following the same ISO guideline, is it wise to

estimate that a conventional Western Canadian glass manufacture of 1983 is representative to a

proposed Atlanta glass manufacturing plant of 2005? Probably not!

The freedom of interpretation expressed in the ISO guideline allows each practitioner to argue

his or her own views on data estimation. Large scope and process boundaries will contain an


insurmountable number of different process steps and require, in cases of insufficient data,

interpreted estimations. The estimation of data is by far the most important and controversial

step. It is not a problem that can be prevented, but can be kept at a minimum. The more specific

the comparison the more accurate the estimations will become. Lack of data availability to the

public places an insurmountable doubt on the data collected and estimated for sector based

paradigm shift LCA’s performed by outside appraisers. It is best to perform a representative LCA

comparison with as much insider data as possible. Deficiency of accurate industrial data places

more strain on data estimation and increases the doubt and lowers the value of the LCA. Data

estimation must be avoided as much as possible.

3.3.5 Impact Assessment

Environmental impacts and societal concerns remain the key focus of any LCA. This is

unmistakably indicted by the procedures listed within the impact assessment step. Because the

collection of system data is considered inadequate in expressing the desired results, the ISO

14042 guideline recommends that a list of specific categories should be defined to “better”

express the results. Some of the categories are solid in their foundation and cannot be contested,

but others are more subjective and may be surrounded by an air of controversy. Those subjective

categories can seem counterproductive to the actual purpose of an LCA execution. From the

start, it has been signified that an LCA is meant to quantify the environmental aspects of

different products or processes. How can subjective personally defined empirical category results

express environmental aspects in concrete numbers? The same problem with interpretation and

ambiguity arises in these procedures.

3.3.5.1 Impact Categories

A list of best practice impact categories has been drawn up by SETAC (see Table 1). They claim

to have created a list of default impact categories, ranging from ‘baseline’ to ‘study-specific’ to

‘other’. It is up to the practitioner to choice between the categories in order to express the most

relevant in correspondence to the initially laid-out goal and scope definition. A slight phrase

modification in the goal and scope can result in a huge deviation in the final result, simply based

on the chosen impact categories. Many of the categories have been set-up following models

specified by environmental organisations and institutes, yet not a single one is universally agreed

upon. Any room for discussion is exploited, especially industries unwilling to change, preventing

the concession of results. Table 1 lists the default categories with the respective subjective doubt

factor:


Table 1 Examples of Best Practice Impact Categories

Category Relative Doubt

Depletion of Abiotic Resources Low Depletion of Biotic Resources Low Land Competition High Loss of Biodiversity Medium Loss of Life Support Function Very High Desiccation High Climate Change Low Stratospheric Ozone Low Human Toxicity Very High Various Ecotoxicity High Photo-oxidant Formation Low Acidification Medium Eutrophication Low Waste Heat Low Odour Very High Malodorous Air Very High Malodorous Water Very High Noise High

It is hard to characterise the relative doubt properly but some categories are clearly subjective and

are present with large degree of doubt. For example human toxicity; toxic levels for each person

are different and how is it even possible to relate the different effects into one empirical value.

Japanese policy makers refuse to express values in any these categories but present them as

absolutes figures. CO2, SO2 and NOx are considered worthy enough topics for individual

categories and are not expressed within the various SETAC categories like Climate Change,

Stratospheric Ozone, Photo-oxidant Formation and so on. The ISO 14042 guideline permits this

expression and actually therefore contains less doubt and allows for better interaction between

different LCA results. This approach presents the data in a much more transparent and

understandable form, if the system produces 400kg of CO2 and 25kg of CH4 who is to argue. But

if the system produces 500kg of CO2 equivalent there is a potential dispute. These expressions

also conform to other more generally discussed industrial environmental concerns, such as

adhering to the Kyoto protocol. In 2000, the Waste Department of the Dutch Ministry of

Environmental Affairs compiled their OMA project aiming at waste policy options. They are

quoted to say “There is no systematic approach to the use of integral environmental analysis in waste policy”.

This statement can easily be extended to all the environmental impact categories. As long as

doubt and scepticism exists the ISO 14040 series cannot produce a final corroboration.

3.3.5.2 Normalisation and Weighting Factors

To further extend the associated problems and branch further away from compatibility, the

values can be normalised and assigned weighting factors. These steps make perfect sense in

presenting a single final result in a succinct form but make it practicably unusable in transferring

to another LCA. See Table 2 for examples of resulting normalized values:


Table 2 Examples of normalised indicator categories

Normalised Indicator Category Value

Depletion of Abiotic Resources 1.2E-15yr Depletion of Biotic Resources 5.6E-13yr Land Competition 4.5E-12yr

The use of esoteric terms is continued in the result expression, for so many negative exponents

of years can only be understood by fellow expert practitioners. The guideline defines the

normalisation step as “calculation of the magnitude of indicator results relative to reference information”. As

with many concepts the praxis never works as well as the theory sounds. Relating the reference

information to one particular community, person or other system is next to impossible with a

broad global scope. Nonetheless, its procedure and execution is strongly recommended. The

values are frequently used as an intermediate for the preparation of further steps, like weighting

factors, further employing personal interpretation. Figure 6 is an illustration of equal results with

different weighting factors for the individual categories:

Impact Assessment

0

5

10

15

20

25

30

35

40

Climate Change Ecotoxicity Human Toxicity Loss of

Biod iversity

Acidifaction Abiotic

Resources

Biotic

Resources

Total Eco-

Indicator

Impact Level

Absolute Values

Weighting Scale 1

Weighting Scale 2

Figure 6 Example of Resulting Weighted Impact Assessment Factors

Although in this hypothetical impact assessment the core data is the same, the weighting scale has

drastically changed the end result. The total eco-indicator presents an either higher or lower value

to the actual absolute value. The room for personal interpretation is capable of shifting the end

figures to whatever result is desired. The ISO 14040 series fails in providing a standard procedure

for LCA practitioners to derive at an unambiguous end result. In fact, its procedures and focus

on interpretation is a catalyst for deviations.


4 Limited Life Cycle Assessment

4.1 Overview

After years of research and work with the allegedly “standardised” LCA, it become apparent to

many practitioners that the scope was simply getting out-of-hand. All the major problems

associated with an LCA are in someway connected to the size of the investigation. A smaller

more concise scope would alleviate the bulk of an LCA’s shortcomings. By 1994 two Swiss

practitioners, Schaltegger und Sturm, had developed a succinct version while preserving the basic

LCA principles. Their aim was to again shift focus back towards economical factors for industry

in light of environmental considerations. They have essentially redefined the old eco-balancing

with the usable portions of the ISO 14040 series through new extensions. Correspondingly to the

original nomenclature, the German term is again more appropriate, Ökonomisch-Ökologischer

Effizienz or Ökoeffizienz (Economical-Ecological Efficiency or Eco-efficiency). In words, an LCA

measures the total environmental impact throughout the life of a product, whereas a limited LCA

measures the relative environmental impacts of various options that may arise for dealing with

issues that can occur anywhere during the life cycle of a product. This definition is sounds cryptic

as the earlier argumentation arrived at a consensus that an LCA is actually very subjective and

thus also relative. It is better to express this definition visually using Figure 7:

Beginning to End

Figure 7 Visual depiction of a process chain and sectional relevance

Depicted above is a representative production chain with all the inter-linked branched

production chains accounted for. An LCA is supposed to address and include the entirety of the

chains from cradle-to-grave within the system boundary. As highlighted in red, a limited LCA can

address a specific section of the production chain. It is a gate-to-gate approach as the inter-linked


branches occurring within the section are completely covered. A limited LCA is essentially a

sectional but more focused LCA with a singularity of dimensions.

4.2 Application

By reducing the span of the scope the systematic procedures of the ISO 14040 series can finally

focus on practical problems. It can investigate specific process alternatives within the grand

product life cycle. Many of the new practitioners of Limited LCA’s regard the scope as being the

vertical assessment and a typical LCA as being horizontal assessment.

Revisiting the PLA example, the difference in directional assessment is apparent. The process

steps joining cultivation to harvesting to storage and so forth is the horizontal chain.

Manufacturing of the trackers from cradle-to-gate is on the vertical path. Another harvesting

alternative could be compared, for instance manual labour, without affecting the horizontal

process chain, visualized by Figure 8: Harvesting with trackers

TrackerManufacture

Tire Production

Storage

Harvesting

Cultivation

Horizontal

Vertical

RubberExtraction

Harvesting with oxen

Oxen Feed

Feed Storage

Storage

Harvesting

Cultivation

Horizontal

Vertical

FeedProduction

Figure 8 Vertical and Horizontal Production Chain Differentiation

In a Limited LCA, the vertical production chain can be isolated without effecting the layout of

the horizontal chain. It can deal with as little as one link in the chain and vertically relate the

cradle-to-grave links thereafter. In this example, different harvesting alternatives can be


compared separately and later incorporated in the grand life cycle chain. By isolating a smaller

portion of the production chain the scope size is greatly reduced effectively solving the vast

majority of the LCA associated problems.

It was stated earlier (in Section 3.3.4.1) that a sensible cut-off would result in a standard deviation

of roughly one percent. If that was in regards to an entire LCA, the nature of an LLCA should

provide a much smaller deviation. Computation of vertical production chains is thus accurate and

concise. It is best suited within the chemical engineering field containing a diversity of minor

production alternatives. Yet, nearly any industry containing a multitude of production steps can

utilise an LLCA to determine the most environmental and economical appealing option. The

Ford Motor Company and Volkswagen AG are amongst the largest corporations currently

working with Limited LCA investigation techniques. Similarly as with the eco-balance

multiciteria, an LLCA is aimed at the internal validation of production options.

4.3 Environmental Impact Units

The ISO 14042 guideline highly recommends the procedure of normalisation and subsequent

weighing factors to express the impact results. Limited LCA’s follow these guidelines but in their

own unique way. All values are to be converted into numerical Pollution Factors (PE) and

similarly weighed based on importance to become expressed in Environmental Impact Units

(EIU). The major difference is that the factors are based on legal pollution regulations and actual

concentration limits. The idea is to provide a precise indicator for policy change based on

economic realities. The room for interpretation and personal intervention nonetheless, still

persists meaning that the procedure while addressed differently, contains the same drawbacks.

This portion is equally as misleading as with the other impact assessment procedures and should

not be taken into account as a usable segment for indicating paradigm shifts. Kept within internal

appraisers and policy makers it can however endorses a transparent data exchange.



5 Exergy Proposing an exergy analysis to be a sole impact category from an LCA or even an LLCA would

be a tad presumptuous, for flawless would hardly be an appropriate description. Neglecting many

of the life-cycle tree branches required to produce, but not directly part of the product, will

greatly affect the result. Exergy, at least within industry, is a decisive factor in the argumentation

for a production shift. It should be additionally contained in any life cycle comparison to include

the voice of industry.

5.1 Comparative Exergetic Cradle-to-Factory Gate Analysis

Any proficient professional working in the area of life cycle analyses has their own reservations

or praises for the ISO 14040 series. Nobody disagrees with the purpose and need of such analysis

tools but several minor and major disputes are directed at the use. LCA can be considered by

some as incomplete. Adding, and to a lesser extent substituting some impact categories with the

cumulative exergy consumption is one proposal for completing an LCA. The result of the

amalgamation is an Exergetic Life Cycle Analysis or ELCA for short. Many of the guidelines

are followed exactly as written in the ISO 14040 series. For determining the potential fossil fuel

reduction potential of using biomass as a feedstock for the chemical industry requires an

adaptation is required: a comparative exergetic cradle-to-factory gate analysis. Factory gate

implies that the chemicals produced from the traditional fossil fuel route and conceptual biomass

route are identical. This greatly simplifies the assessment by reducing the need to further study

the process chains to the grave, effectively reducing the scope. Figure 9 illustrates the cut-off

point, being labelled as the “functionalized chemical” product:

Functionalized

Chemical

Fossil Route

Biomass Route

Functionalized

Chemical

Fossil Route

Biomass Route

Figure 9 Chemical Biorefinery Comparative Exergetic Cradle-to-Factory Gate Analysis Layout

The goal and scope is identical. The inventory analysis is identical, however far more elaborate in

its execution. The mass and energy streams of all the different production steps are required. The

streams must be closed or literally speaking balanced. The impact assessment also follows the

ISO guidelines but is limited only to the factors vital in calculating the exergy flows along the

process chains. In this respect, it is contradictory to suggest that the inventory analysis is more

elaborate. Assuming the availability of the data, it is easier to collect detailed data associated with

energy and material streams as opposed to small traces of pollutants because industry is directly


concerned with their function on an economic level. Even though, the inventory is encumbered

with the vision of loop closure, disregard of information not directly connected to exergy fluxes

can greatly reduce the size of the inventory. The goal of an ELCA is to ascertain the levels of

exergetic consumption along the various production processes. Applying a simplified black box

approach to the system boundaries incorporates only the basic inlet and outlet flows of a process.

A further benefit of the chosen tool is the issue of comparison: as all the goal and scope is equal

the base assumptions are also equal meaning that while the resulting data could vary from

practitioner to practitioner the general trend between the two streams will remain. There is a

downfall to the ELCA as well; for because the life cycle is more direct and only concerning the

processes, which have a change of exergy, many side chains are neglected (Figure 4). Finally,

environmental aspects are not taken into account and there is only a heavy interpretation based

extension in relating the cumulative exergy demand to environment emission. All-in-all an ELCA

is an interesting and value tool and is in many fields a serious LCA substitution possibility.


6 Paradigm Shift

Switching from fossil fuel resources to biomass resources for the production of chemicals entails

a paradigm shift. The entire industrial name “petrochemicals” is based on the fact that the raw

materials almost exclusively originate from petroleum. Performing a complete life cycle analysis

of the industry is an arduous task and will involve a process tree of immense magnitude.

Comparing the raw material extraction and production with an alternative route of a totally

different nature cannot be taken lightly. It is safe to assume that the process tree of the

alternative will be even larger and more complex than the conventional route. Analysing the two

production routes for a quantitative comparison must be dealt with utmost scrupulousness to

avoid any doubt or confusion. For the whole purpose of carrying out a complete comparative

cradle-to-factory gate is to provide concrete argumentation for the switch. The petrochemical

industry is such an influential and powerful body that adopting a paradigm shift will have to

appeal to their desires. They have two main wants, which following a life cycle analysis do not

necessarily have to be contradictions; improving the public image through environmentally sound

processes and products, and maximising profits and revenues through process optimisation. The

life cycle analysis tool must encompass both desires to a high degree of certainty and precision.

There are many analysis tools to chose from and all possess their own inadequacies. A

combination of the different methodologies and practices from various analysis tools is a logical

approach to minimise the inadequacies and to satisfy the specific goal and scope of a raw material

paradigm shift.

A series of international standards and guidelines for executing a life cycle assessment have been

collected and presented in the ISO 14040 series. From investigating the inner workings of the

ISO standard and the ambitions of those employing it, it becomes apparent that it alone is an

unacceptable tool for this specific paradigm shift. LCA’s derives from internal industrial

comparisons for improvements projects. It is still the best-suited tool for straightforward process

option comparisons of a small nature. Complete, accurate, and reliable data is essential for the

Paradigm: A set of assumptions, concepts, values, and practices that constitutes a way of viewing reality for

the community that shares them, especially in an intellectual discip line

Paradigm Shift: Describes the process and result of a change in paradigm - usually total revolution in theory

or worldview. It was orig inally a term referring to science but has become more widely applied to other

realms of human experience as well. The term was first used by Thomas Kuhn in his famous 1962 book The

Structure of Scientific Revolutions.

Examples of parad igm shifts in science: � The transition from a Ptolemaic cosmology to a Copernican one. � The unif ication of classical physics by New ton into a coherent mechanical worldview.

� The transition between the Maxwellian Electromagnetic w orldview and the Einsteinian Relativistic worldview. � The development of Quantum Mechanics, which overthrew classical mechanics. � The development of Darwin’s theory of evolution by natural selection, which overturned Lamarckian theories of

evolution by inheritance of acquired characteristics.

� The acceptance of Plate tectonics as the explanation for large-scale geologic changes.


New Business

Venture Possibility The petrochemical industry supplies the downstream chemical and plastics

industries w ith all their raw materials needs. Those industrial sectors are the consumers and as consumers

their driving force is a steady supply of those materials at the low est possible price.

It is common know ledge that the companies within the petrochemical industry are

notoriously conservative. Old wealth interests constrict them to traditional business practices and major changes

are virtually unheard of. A life cycle analysis should be successful in ratifying the economic feasibility and

environmental benefits of biobased raw materials. A paradigm shift can than be

justif ied. If the petrochemical industry does not act quickly on efforts to change, another may. From w here or from who

the raw materials originate is not of importance for the consumers, just a consist supply with low costs.

Many chemical and plastic enterprises are already beginning preliminary

research into alternative material supplies. The supply of chemicals to this sector is worth billions and does not

necessarily have to be controlled by the petrochemical industry. They

can supply themselves or…whoever!

proper execution of an LCA, which is readily available if kept

internally. With the success of small-scale assessments, practitioners

voyaged into ever increasingly large-scope sizes. A paradigm shift of a

raw material feedstock requires a very large and detailed scope size

indeed. In the aspects where LCA’s performed superbly within the

realms of small scopes they fail miserably at larger scopes. Data is no

longer complete and personal interpretation dominates the results.

One large scope LCA can greatly differ from another and increasing

the scope size only worsens the deviation. Deviation fuels doubt and

leads to undeceive results and the dependency of personal

interpretation does not correspond to a high degree of certainty and

precision. The ISO guideline is a great tool, but being in its infancy it

currently cannot provide the corroboration necessary for a paradigm

shift of the petrochemical industry.

Another drawback of the LCA is that monetary consideration is non-

existent, even the energy and raw material flows are insufficient.

Since the development of the ISO 14040 series the main focus has

progressively leaned towards solely assessing the environmental

impacts. Proposals and research has gone into altering the LCA to

incorporate exergy and more recently to an extent monetary cost.

Exergy calculations place a higher demand on material and energy

flows and compensates for the LCA’s inadequacy. The ELCA is

however, also an unacceptable tool for this specific paradigm shift

investigation. The process flow diagram is developed with the

processes containing an exergy consumption or induction as the sole

considerations. Although this does alleviate doubt, it neglects many

secondary side processes. In comparing an option to possibly replace

or change an entire industry “to neglect” is an utterly unacceptable

word phrase.

The other analysis tool previously mentioned was the Limited LCA, the so-called vertically

oriented assessment. It may seem absurd to even acknowledge a tool focused at narrow and

segmented life cycle analyses considering the necessary scope for a paradigm shift, but it does not

have to be applied independently or even singularly. It can be combined with another tool to

mitigate the inadequacies. The ELCA is entirely horizontally oriented with few vertical

considerations; assigning LLCA’s to the secondary side processes will add the extra dimension

and effectively remove the word neglect. The impact categories of the LLCA and ELCA are

however incompatible, but the LCA ISO 14042 provides the practitioner with the freedom to

choose the impact categories almost arbitrarily. As the other tools are derivations of an LCA, the


same liberties can be applied. All the raw material and energy flows (economic flows) are not only

necessary for the calculation of exergy but are also relevant on their own accord. Gathering this

data for the LLCA side production chains would accommodate the possibility of performing

additional exergetic calculations. Combined as assessed for a shift feedstock for the

petrochemical industry the comparative exergetic cradle-to-factory gate assessment provides the best

solution to gather knowledge in regards to the paradigm shift.



7 Conclusion Justifying a grand paradigm shift, such as converting the type of raw material feedstock for the

petrochemical industrial sector, requires a complete and accurate analysis assessing all the

economical and environmental issues corresponding to their driving force. Expressing those

issues in a life cycle comparison will provide the maximum amount of scope and depth to

address all economical and environmental flows connected to the raw material harnessing. The

flows and processes connected to the production and preparation is immense and must be

represented thoroughly and accurately by the chosen life cycle analysis tool. The so-called

standard and most frequently used tool for calculating a life cycle, the ISO 14040 series LCA, is

not suitable for this large comparison. An LCA is best suited for small-scale internal process

comparison with sufficiently available data. When addressing larger scale issues, like for a raw

material shift, many problems arise which greatly jeopardise the reliability of the results. When in

doubt interpret, is the undisclosed motto of the ISO guideline. Any interpretation relies on

human intervention, personal judgement, meaning the assessors are free to choose what is

important and what it not. In this specific topic all LCA’s are bound to deviate greatly, even with

a small deviation a final corroboration cannot be ascertained. Another life cycle tool expressed

within a detailed collection of international standards does not yet exist. However, there are other

tools that derive from the standard LCA, which can borrow the positive aspects of the guideline

for this specific comparison. One such derivative, the Exergetic LCA, is capable of collecting the

exergy consumed of both raw material production chains from cradle-to-factory gate without any

data being contested, potentially alleviating deviation and doubt. The ELCA is incomplete in

addressing the issues require for the paradigm shift as it is mainly horizontal in its assessment

nature and is only expressed in exergy. Consolidating all the vertical side chains of the larger

Exergetic LCA with Limited LCA’s will cover the grand scope completely and express the

necessary issues to a high degree of precision. Therefore the chosen analysis tool is the

comparative exergetic and energetic cradle-to-factory gate assessment. Through the proper

execution of this assessment tool the best and most realistic raw material alternative can be

compared to the conventional route with the essential certainty and precision. Both the main

environmental and economical issues important for industry are calculated in exergy terms,

providing them with a potentially translucent figure capable of warranting a pre-oil-depletion

paradigm shift to biobased raw resources.



Chapter 4 Crop Output

Ben Brehmer

Dissertation Report


Colophon



ISO 9001:2000.

Title Chapter 4 – Crop Output Author(s) Ben Brehmer A&F number - ISBN-number - Date of publication 1. June, 2006 Confidentiality No OPD code - Approved by - Agrotechnology & Food Innovations B.V. P.O. Box 17 NL-6700 AA Wageningen Tel: +31 (0)317 475 190 E-mail: [email protected] Internet: www.agrotechnologyandfood.wur.nl © Agrotechnology & Food Sciences Group B.V. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch, hetzij mechanisch, door fotokopieën, opnamen of enige andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. De uitgever aanvaardt geen aansprakelijkheid voor eventuele fouten of onvolkomenheden. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher. The publisher does not accept any liability for inaccuracies in this report.


Abstract To assist in the selection process of determining the plants best suited for the production of a

particular biochemical, a large investigation of various crops is needed. A crop guide for 16

popular choice crops has been compiled which lists all the cultivation dependent variables to

systematically compare the different energy inputs. The crops are classified based on their

biochemical constituent yields in hopes of identifying trends, barriers, and opportunities for the

various aspects attributed to the cultivation. The parameters for the biomass cultivation itself are

based on typical regional growth figures for the individual crops along with best practice

operations. Standard yield figures are based (when available) on 5-year average yield trends of

such regions and have all been related to total green dry biomass production. The normalized

yield figures are conversely based on the best agricultural practice for the regionally dependent

cultivated biomass crop. By using the yield figures, chemical composition and cultivation

practices a ten year average yield for the usable constituents for potential biochemical production

is created. Combined with the group contribution method, the output energy and exergy of the

crops is determined. These energetic output figures will prove the basis of many calculations to

follow. Included in this chapter is the chief energy input, solar radiation. It is most dependent on

regional constraints. The total annual solar energy/exergy input has been calculated for each crop

by using the crop specific growth period and monthly solar radiation of the region. Solar

radiation is a large energetic input but is better linked to land use efficiency than energy.

However, the energy/exergy and efficiency analysis used in all preceding chapters are outlined for

the solar input. Finally a list of the Top 3 choice crops for each category is created as the main

findings of the chapter.

Key Words:

Biomass, Crop Guide, Yield, Composition, Solar Radiation, Energy, Exergy, Efficiency



Content

1 Introduction 81


2 Crop Guide 83

2.1 The List 83

2.2 The Classifications 83

2.3 The Crop Guide 85

2.3.1 General Information 85

2.3.2 Growth Details 85

2.3.3 Fertilizer Use 85

2.3.4 Yield and Composition 86

2.3.5 Detailed Information 86

2.4 The Source of Information 87

3 Output 89

3.1 Yields 89

3.1.1 Best Practice 89

3.1.2 Total Crop Yields Explanations 91

3.1.3 Total Crop Yields 93

3.1.4 Growth Cycle 94

3.2 Chemical Composition 95

3.2.1 Unusable components 97

3.3 Energetic Output 98

3.3.1 Calorific Values 98

3.3.2 Group Contribution Formation Energy 98

3.4 Results 99

3.4.1 Total Energetic Output 99

3.4.1.1 Comparative Analysis 100

4 Solar Input 103

4.1 Location 103

4.2 Cultivation Period 104

4.3 Results 105

4.3.1 Total Energetic Input 105

4.3.2 Efficiency 106

4.3.3 Analysis 107

5 Results and Discussion 109



1 Introduction Arable land will become the raw resource of the future. Today we may be scheming and fighting

over oil deposits in unfavourable lands like deserts, deep seas and even polar ice shields;

tomorrow it may likely be over the lush, green, favourable lands of high arability. Conflicts have

always arisen over territory and land to control natural resources; the biobased economy may just

adjust the emphasis to agricultural production capability. It is our duty and responsibility not to

replace one aspect of scarcity with another, all in the name of energy sustainability.

Many dedicated critics against the biobased economy have a very justified argument; there is not

enough land to go around. That is to say there is not enough fertile land to go around and several

industrial corporations and politicians have begun debates under the motto “fuel for the rich or food

for the poor”1. Although, some studies have concluded that there is sufficient arable land around

the entire world to accommodate our future energy needs2. Hoogwijk suggests that if the total

global surface area were converted to accommodate bioenergy crops a maximum of 3500EJ/y is

possible. And by 2050, following the best scenario including proper technical and socio-

economical development, 657EJ/y is achievable. This is a lot more than current (2000) global

energy demand of 400 – 450EJ/y. If there is enough arable land on a global scale to fulfil our

energy needs is debatable, one thing is clear, that vast and unfathomable amounts of land are

needed for bioenergy.

Proposals for energy production from biomass, bioenergy, are always put into the context of

global proportions. One of the main reasons behind the critique is the high land use intensity in

combination with low solar energy conversion efficiency. Indeed the conversion rate of solar

energy to actual bioenergy stored in the crop is in the magnitude of 1% with figures below 1%

common for many crops. Bioenergy must be able to compete against other solar conversion

device like PV cells which have much higher conversion efficiencies in the range of 15-20%, with

experimental devices surpassing 40%. Additionally such an alternative option does not necessitate

arable land for production, but does have other stipulations. The similarity between the two

forms is solar radiation as the primary energy input. It is regarded as a free source of energy

which may be true, but its cost is land.

Burning biomass for the creation of heat and subsequently energy is the lowest form of

harnessing the exergy of the solar radiation. Biofuels are slightly higher but still do not maximize

the exergy content delivered to the surface. As arable land is undoubtedly the most important

factor in biomass production the goal should be to maximum land use efficiency. Production of

chemicals from biomass, when harnessed properly, will utilize the highest amount of the

incoming solar exergy and thus achieve the highest land use efficiency.

It is common practice in the research field of biomass to mention the yield of particular crops,

for instance in ton dry matter per hectare. The relationship between the calorific value and yield


is used to present energetic terms per land area, i.e. MJ/ha. This is indeed a valuable tool which is

also conducted for the select crops investigated in this study; however it is not enough to

properly address land use efficiency. The additional conjunction to solar energy input provides

the link to relate all factors together in a degree of land utilization. As stated chemicals are of

interest and the biochemical constituent compositions can further shed light into the potential

land requirements for the production of such chemicals. It is paramount to the success of the

biochemical industry that the land use intensity is kept to a minimum. For bioenergy it is even

more vital to strive for maximum land use efficiency.

Maximum land use efficiency, should it be for bioenergy, biofuels or biochemicals may not

necessarily coincide with the highest yielding crop; the relation to solar input is the key. Any

application for biomass will require vast land space and regional dependencies will provide

different levels of solar radiation input. When compiling a cradle-to-factory gate study for

chemicals from a biomass origin the solar input should not be handled as an energy input but as a

factor for the efficient land use. As chemicals, like energy, are commodities replacing them by an

alterative, should it be a renewable, must be sustainable by way of supply. To prevent any land

conflicts that may arise from large-scale biomass cultivation efficient use of the future raw

resource must be foreseen before it can become a conflict.

1.1 Chapter Purpose

By systematically listing a handful of select crops a basis for comparison is created. The crop

guide will provide all the base datasets, values, assumptions and parameters necessary for all

proceeding calculations. The standardization of value expression is essential to create a reference

point. In addition to covering the crop information the resulting output figures are to be covered.

This is understood as yield, composition and energy/exergy content. The output figures will also

serve as a basis for proceeding efficiency relation calculations. As solar radiation is an input but a

special one at that the methodology of the input/output relation will be presented. However

solar radiation will be assessed not as a true energy input but as an indication for land use

efficiency. This chapter essentially forms the heart of the investigation for all following chapters

are dependent on the created reference points and calculation methodology.


2 Crop Guide Several crops are already considered as classical crops for bioenergy and biomaterials. Two such

examples immediately come into mind (at least mine); the Brazilian sugar cane for bioethanol and

Malaysian palm tree for biodiesel production. Even in the relatively young field of research

several crops have already been sufficiently documented and proposed for a large array of

biomass applications. The exact species of choice are typically based on a maximum yield of the

particular component used for the intended purpose. For example: a high sucrose yield in the

sugar cane to convert to ethanol. To be able to make a subjective comparison of crops a diverse

variety of crops, growing conditions and farming techniques must be evaluated. A list of 16 crops

has been chosen as a starting point for this assessment. They are based on many different

grounds from popularity, to location, to botanical classification, to national development

considerations and as far as gut feeling. By linking the required inputs to the crops a clearer

picture will be created, providing the argumentation necessary to select crops based on energetic

savings and no longer simply on high yielding assumptions.

2.1 The List

The corresponding data in Table 1 are based on typical growing conditions in the main/native

areas of cultivation. All following information and data is related to the mentioned location.

Table 1 Choice of Crops Species

Botanical Nomenclature Common Name Continent Country/State

Beta vulgaris Sugar beet Europe Germany

Brassica napus Rapeseed Europe Belgium

Elaeis guineensis jacq. Oil palm South Pacific Malaysia

Glycine max Soya bean North America Illinois

Helianthus annuus Sunflower Europe France

Manihot esculenta Cassava Africa Nigeria

Medicago sativa Lucerne North America South Dakota

Nicotiana tabacum Tobacco Oceania Australia

Lolium perenne Grass Europe Holland

Panicum virgatum Switchgrass North America Iowa

Saccharum officinarum Sugar cane South America Brazil

Salix alba Willow tree Europe Sweden

Solanum tuberosum Potato Europe Holland

Sorghum bicolor Sorghum Africa Kenya

Triticum aestivum Wheat Europe France

Zea mays Maize North America Iowa

2.2 The Classifications

It is necessary to group the different crops into classification categories to be able to compare the

individual crops within the group as well as create a general group trend. Classifying the crops,

however, becomes a tricky matter as crops used for food and non-food purposes have different

stipulations. Several crops can even fall into different categories. For this reason both the generic


agricultural practices classification and constituent based non-food classification will be

employed. At least two crops must be present in a category to validate the comparison.

Table 2 Classifications of Crops Species

Agricultural (Food) Biomass (Non-Food) Cereal Crops

• Maize (Zea mays)

• Sorghum (Sorghum bicolor)

• Wheat (Triticum aestivum)

Fibrous/Trees • Oil Palm (Elaeis guineensis jacq.)

• White Willow (Salix alba)

Grasses/Shrubs • Lucerne (Medicago sativa)

• Ryegrass (Lolium perenne)

• Switchgrass (Panicum virgatum)

• Tobacco (Nicotiana tabacum)

Legumes • Lucerne (Medicago sativa)

• Soya Beans (Glycine max)

Oil Crops • Oil Palm (Elaeis guineensis jacq.)

• Rapeseed (Brassica napus)

• Soya bean (Glycine max)

• Sunflower (Helianthus annuus)

Root/Tuber Crop • Cassava (Manihot esculenta)

• Potato (Solanum tuberosum)

Sugar Crops • Sugar beet (Beta vulgaris)

• Sugar cane (Saccharum officinarum)

• Sweet sorghum (Sorghum bicolor)

The biomass (non-food) classification of Table 2 are grouped into the five main groups of

biochemical constituents present in plants. Naturally, carbohydrates are found in great abundance

in all plants, yet by dubbing them either rich in simple and/or complex carbohydrates can allow

for more specific grouping. Simple carbohydrates are those, which can be fermented relatively

easy, like starches and sugars. Complex carbohydrates are those, which have traditionally been

more difficult, like cellulose and hemicellulose. The other categories are self-explanatory.

Simple Carbohydrate Rich • Cassava (Manihot esculenta)




• Sweet sorghum (Sorghum bicolor)

• Sugar beet (Beta vulgaris)

• Sugar cane (Saccharum officinarum)


Complex Carbohydrate Rich • Cassava (Manihot esculenta)




• Sweet sorghum (Sorghum bicolor) • Sugar cane (Saccharum officinarum)


• White willow (Salix alba)


Lignin Rich • Maize (Zea mays)


• White willow (Salix alba)

• Oil palm (Elaeis guineensis jacq.)

Protein Rich • Cassava (Manihot esculenta)

• Lucerne (Medicago sativa)

• Ryegrass (Lolium perenne)



• Tobacco (Nicotiana tabacum)

Oil/Fat Crops • Oil Palm (Elaeis guineensis jacq.)

• Rapeseed (Brassica napus)




Classifying the crops based on their constituents is a far better approach in determining which

chemicals are best suited to be synthesized from a particular crop.

2.3 The Crop Guide

Creating a systematic comparison calls for a standardized listing of the key factors concerning the

various crops. This is essentially the crop guide (found in Chapter 8). Listed are the most

important issues involving the cultivation of the crops (input) and their potential chemical use

(output). The guide itself can be broken down into five sections:

2.3.1 General Information

Along side the visual representation (picture) the basic information regarding the nature of the

plant is listed. Using very short and direct points the reader can build an adequate depiction of

the crop in question, should it not already be known.

2.3.2 Growth Details

Not every plant is capable of growing everywhere. This is what the VOC understood all to well

as they travelled half the world over for coffee and a handful of spices, whilst the tulip was

introduced on native soil. Temperature, climate, participation and soil type are all major factors in

determining the areas of successful growth. Although the locations have been pre-determined

using the current main production sights, the other locations do not differ immensely. Listed are

all the farming details, enabling the determination of the operational input values. The large

variety of farming techniques is equally diverse in energy input. Hand-planting rice stocks in a

shallow basin is much more energy intensive than broadcasting ryegrass seeds. Cultivation and

harvesting times are of particular importance as the utilized solar energy is a function of this

growth period. Rainfall/irrigation is another key value; in areas where rainfall is inadequate

irrigation is the only option, one of the energy input figures. A companion crop can be of

significance should it be of a leguminous order, saving on nitrogenous fertilizers. The values and

terms are for the most part normalized to ensure the transparency in the comparison.

2.3.3 Fertilizer Use

Just as humans require essential amino acids to sustain life, plants require essential nutrients.

They are broken down into 3 types: macro (primary), macro (secondary), and micro. In total

there are 16, yet in the crop guide graphs only 12 are indicated. The reasoning is that carbon (C),

hydrogen (H), and oxygen (O) are not applied in the form of fertilizers or present in the soil as

nutrients. Chlorine (Cl) is never added in its virgin state but frequently linked with potassium in

the molecular form KCl. There are two common practices to interpret the nutrient requirements,

either common fertilizer application rates (i.e. kg/ha) or by nutrient uptake based on the plants

chemical analysis (i.e kg/kg). This report will take into account only the actual nutrient uptake,

for losses occurring on the field (see Chapter 6) can be further reduced as better farming

techniques evolve. Even the specific kind of fertilizer will affect the level of nutrients that can be

taken up or leached. The values expressed in the graphs are thus the amount the crop removes


from the soil and must not to be confused with the amount applied to the field. These values

can, however, be considered (and re-expressed) as the theoretical minimum fertilizer application

rate. Generally the nutrient uptake levels and yield rates respond in a linear proportion with each

other with the slope being unique for each nutrient and crop. The deviation is apparent in the

graphs and some relationships are not linear but follow a logarithmic trend. To ovoid major

errors when extrapolating to specific yields, all figures have been brought into the graph to

determine the exact uptake at the corresponding yield under investigation. Closer attention is

paid to the interrelationship between yield and uptake levels in Chapter 5. Additional crop

specific comments are mentioned only to help in the fertilizer understanding. The graphs have

been broken down into macronutrients and micronutrients as for the large part only trace

amounts of the micronutrients are removed, although in the long-term they must be

reintroduced.

2.3.4 Yield and Composition

To provide a good contrast the normal, optimal and worldwide cultivation figures are listed. They

can quite often have huge deviations. When available, the 5-year averaged and best practice yield

in the region to be assessed is also listed. Furthermore, food application agriculturists are mainly

interested in the yield of the eatable portion of the crop and state such values in a variety of

forms best suited for their food industry. As a clear example, winter wheat, yields are measured in

terms of dry grain. In the odd case that the stalk is even mentioned, documentation is in wet

weight. In tune with standardization all values have been converted into dry weight figures for

the entire plant. Food yield terms are still listed for most crops. As the crops are intended for

biochemical processing the chemical constituents are systematically listed. Practically all of the

crops consist of three main parts: leafs, stem and the fruit/seed. Characteristically these three

components share radically different constituent compositions. In this respect they have been

listed separately with their associated moisture content. The heating values (also known as the

lower calorific value) are also listed for the various crop parts. These are vital for comparing the

calculation method used to determine the resulting output energy.

2.3.5 Detailed Information

Each crop has a specific trait, which can be utilized in sight of biochemical processing. Leafy

plants are particularly well adapted at containing high levels of protein. Protein is a component

that will be investigated in further detail (see Chapter 7). Proteins are a complex of the 20 amino

acids. Listing the free amino acids is a good indication of the actual protein composition.

Quantifying amino acid concentration is a complicated procedure resulting in many “unknown”

levels. In such cases it can be assumed that the levels are or approach zero. Much of the other

information is very crop specific, yet the added information is crucial in justify the final product

processing possibilities.

The complied information contained in the crop guide will act as the source and basis on further

calculations. It is imperative for any sceptical reader to review the crop guide.


2.4 The Source of Information

Several online databases have been used to compile the bulk of the crop guide. They include:

• World Fertilizer Use Manual, IFA (International Fertilizer Association)3 http://www.fertilizer.org/ifa/publicat/html/pubman/namtype.htm#Crop%20index%20-%20Type%20of%20crops

• Crop Index, Center for New Crops & Plant Products, Purdue University4 o James A. Duke. 1983. Handbook of Energy Crops. Unpublished

http://www.hort.purdue.edu/newcrop/Indices/index_ab.html

• Biomass Feedstock Composition and Property Database, Energy Efficiency and Renewable Energy, DOE (U.S. Department of Energy)5 http://www.eere.energy.gov/biomass/feedstock_databases.html

• Phyllis: database for biomass and waste, ECN (Energy research Centre of the Netherlands)6 http://www.ecn.nl/phyllis/

• FAO (Food and Agricultural Organization) o Agricultural Date, FAOSTAT7

http://faostat.fao.org/faostat/collections?subset=agriculture

o Grassland Index8 http://www.fao.org/ag/AGP/AGPC/doc/GBASE/mainmenu.htm

• Index of Top Crops, Leaf for Life9 http://www.leafforlife.org/PAGES/TOPINDEX.HTM

• IENICA (Interactive European Network for Industrial Crops and their Applications)10 http://www.ienica.net/cropsdatabase.htm

• BIOBIB - A Database for biofuels, University of Technology Vienna11 http://www.vt.tuwien.ac.at/biobib/oxford.html

Even the collective data of these databases is insufficient to complete the demands of the crop guide. Other crop specific references are listed as they occur.



3 Output The grass is always greener on the other side of the fence.

This old English phrase translates to: people are

never satisfied with their own situation; they always

think others have it better. Science and geometry

are able to solve this mystery in regards to the

colour of the grass (see adjacent illustration), yet the

perception continues. Except in the case of the

English, where this actually holds true when they

look towards the other side of the Channel. This

expression can also be related to actual farming issues. It is ambitious to set just one figure in one

specific region to represent an entire species. Precise crop yields are affected by a large multitude

of complex factors. Somewhere, someone, on some field, will always have a higher harvested

yield. Cropping experiments are conducted the world over and will always outperform the

average. Most experiments that are performed for maximum yield neglect to mention the input

requirements by shifting focus on the trifling details associated with the great success of increased

yield. Surely an accelerated selectively bred crop in combination with ample water, ample sunlight

and ample nutrients will result in huge yields on a carefully controlled test field. It may be

perceived as greener, but the colour of the grass is not the full story. That is not to say that the

experimental techniques cannot be utilized later in large-scale applications, only that it is a matter

of perception. On the browner side of the fence, figures are readily available for all aspects of

cultivation including typical yields, composition and calorific

values. To mitigate any errors by mixing experimental figures with

typical figures, only the average and best practice figures acquired

from the mentioned locations (see Section 2.1) will be adopted.

This will create a proportional ratio between the inputs and

outputs allowing for an ease of extrapolation; i.e. a location shift

or yield increase. There are two factors that can affect the output,

such as yield, while not directly labelled as inputs: firstly a revised

farming technique and secondly a modified (GMO) species. These

factors will be intentionally left out of the calculations but their

implications will be discussed later in detail (see Chapter 6 and 9).

3.1 Yields

3.1.1 Best Practice

Photosynthetically Active Radiation (PAR) designates the spectral

range of solar light from 400 to 700 nanometres that is useful to

terrestrial plants in the process of photosynthesis. Assuming that

there are no other constraints or restrictions (such as water or

nutrients) in plant growth, PAR is used to determine the

Theoretical Maximum

Experimental/Optimal

Best Practice Farmers

Higher Regional Average

Regional Average

Lower Regional Average

Poor Practice Farmers

Zero ProductionYie

ld:

ton

/ha

Natural Deviation: - Year- Region- Study, etc.

Theoretical Maximum

Experimental/Optimal

Best Practice Farmers

Higher Regional Average

Regional Average

Lower Regional Average

Poor Practice Farmers

Zero ProductionYie

ld:

ton

/ha

Natural Deviation: - Year- Region- Study, etc.


theoretical maximum biomass yield of a crop. In practice these yields are by far not obtainable

and only on small test plots carefully monitored with measures to minimize other limitations are

high experimental yields reached. These yields represent the uppermost possible in a region and

are well above the average. Regional average yields are provided yearly by local governmental

bodies for a specific crop. In the figures themselves a natural deviation is present based on the

year of the data collection, the specific region of cultivation and the body conducting the study.

These deviations are indicated on the graph as the higher and lower regional average and can

easily vary by 25%. Several underlining problems exist when applying average figures for non-

food biomass applications. For in the average figures all farms are taking into account including

poor practice farms, small-scale farms, inefficient farms, biologically oriented farms (eco-farms)

and other farms that contribute to lower overall yields. Best practice farms employ currently

available technology and agronomic know-how to obtain significantly higher yields than the

average. As the biomass sector will entail large industrial interest and investment it is foreseeable

that the current best practice will represent the near future standard practice. Furthermore as

quality concerning food regulations is not a major concern (in most production situations) the

eco-farming practices and typical quality over quantity sacrifice practices will not be present in

the biomass sector. The best practice farms are the most logical choice in setting the yield for

near future biomass implementations. Depicted in Figure 1 are the low, 5-year average and best

practice yields of the crops in terms commonly presented in the agricultural industry.

Agricultural Yields

0

25

50

75

100

125

150

Tu

be

r

Dry

Bio

ma

ss

Dry

Bio

ma

ss

Grain

Fru

it/S

eed

Tu

be

r

Se

ed

Gre

en

Bio

mas

s

Se

ed

Tu

be

r

Gre

en

Bio

mas

s

Se

ed

Dry

Bio

ma

ss

Dry

Bio

ma

ss

Grain

Dry

Bio

ma

ss

Cassava Grass Lucer ne Maize Oil Palm Potato Rapeseed Sor ghum Soya bean Sugar beet Sugar cane Sunflower Switchgrass Tobacco Wheat W illow tree

ton/ha/year

Low

Average

Best Practice

Figure 1 Various documented agricultural yield figures


For some crops the difference between the average and best practice is large whereas for others it

is marginal. Found in accompanying database spreadsheets are another graphical representations

displaying the ratio between the average and best practice. For all the crops on average the best

practice yields are 192% higher, although have a standard deviation of 106%. Narrowing the

investigation down to only common crops cultivated in prosperous areas with a long tradition of

that particular crop reviles a yield increase of 161% with a standard deviation of only 18.6%.

Thus it can be assumed that the best practice farmers will yield 1.6 times more biomass from

crops cultivated in areas with an advanced and intense agricultural tradition.

3.1.2 Total Crop Yields Explanations

As previously mentioned (see Section 2.3.4) the various plant parts have different yield values and

expressions along with varying moisture content. In conforming to standardization all figures

must be converted into one common term; total dry biomass. This is understood, as above

surface biomass with the clear exception of tuber-based crops, meaning rooting systems are not

included. Roots are indeed a form of biomass and can constitute a considerable quantity of mass

structure. For example, the rooting system of winter wheat can be reach depths of up to 2 meters

and represent slightly less than 10% of the total biomass (dry). But, due to the overwhelmingly

high expenses linked with harvesting and isolating root mass plus the added soil benefits of

leaving the roots in place (e.g. erosion and soil fertility), this biomass portion will not be included.

Although dry weight is occasionally listed, for transparency and unison the table has been

designed to calculate transiting from wet weight to dry weight; meaning that some values have

been calculated backwards. Since there are large discrepancies concerning the actual yield figures,

the lower (or poor practice), average regional conditions and best practice conditions have been

listed together. The source yields figures and explanations behind the yields are as follows:

Cassava

Low = poor conditions: 8ton/ha tuber

Average = poor conditions: Nigeria 5-year average at 9.36ton/ha tuber

Best Practice = high commercial yield: 50ton/ha tuber

Grass

Low = low hay production

Average = EU hay production with 2-3 cuttings per year

Best Practice = upper regions approaching 14.1ton/ha dry weight

Lucerne

Low = USA average of 1.25ton/ha of dry hay

Average = typical US figures when using fertilizers

Best Practice = high range with good soil conditions yielding 15ton/ha dry weight

Maize

Low = lower US yields, based on total crop

Average = good conditions: Iowa 5-year average at 9.35ton/ha grains (cob)

Best Practice = high large scale US yields, 13.8ton/ha grains


Oil Palm

Low = 10ton/ha fruits

Average = normal conditions: Malaysian 5-year average at 19.47ton/ha fruit

Best Practice = good conditions: Malaysian yields of 25ton/ha fruits

Potato

Low = low for temperate regions: 20ton/ha tuber

Average = good conditions: Dutch 5-year average at 43.5ton/ha tuber

Best Practice = optimal Dutch conditions at 65ton/ha tuber

Rapeseed

Low = EU average: 3.0ton/ha seeds

Average = good conditions: Belgian 5-year average at 3.81ton/ha seeds

Best Practice = optimal Belgian conditions at 5.5ton/ha seeds

Sweet Sorghum

Low = poor regions: 25ton/ha green matter

Average = poor conditions: Kenyan 5-year average at 0.74ton/ha grain

Best Practice = good commercial practices: 75ton/ha green matter

Soya Bean

Low = lower levels of normal practice: 1.7ton/ha seeds

Average = good conditions: Illinois 3-year average at 2.61ton/ha seeds

Best Practice = optimal US practices: 4.0ton/ha seeds

Sugar Beet

Low = low for temperate regions: 30ton/ha beet

Average = good conditions: German 5-year average at 57.6ton/ha beets

Best Practices = obtainable high level: 100ton/ha beets

Sugar Cane

Low = lower boundaries: 15ton/ha cane

Average = good conditions: Brazilian 5-year average at 72.3ton/ha cane

Best Practice = upper typical yields: 100ton/ha green matter

Sunflower

Low = world average: 1.23ton/ha seeds

Average = typical: French 5-year average at 2.29ton/ha seeds

Best Practice = optimal conditions: 5.5ton/ha seeds

Switchgrass

Low = low scale of Pacific Northwest

Average = Typical yield for American Alamo species when grown as energy crop

Best Practice = middle range of optimal conditions, 14.0ton/ha

Tobacco

Low = high yield range for smoking tobacco: 4.0ton/ha dry weight

Average = Australian conditions when treated like grass: 24.0ton/ha DW

Best Practice = higher boundary of Australian site: 28.8ton/ha DW


Wheat

Low = low/normal: 6.0ton/ha grains

Average = typical: French 5-year average at 6.98ton/ha grains

Best Practice = optimal average: 10.3ton/ha grains

Willow Tree

Low = low Swedish yield: 3.0ton/ha oven dry wood

Average = typical: Swedish sites 4-5ton/ha oven dry wood

Best Practice = optimal range start: 8ton/ha oven dry wood

3.1.3 Total Crop Yields

In addition, when applicable, the 5-year averaged yield data for the crop in the relevant region of

interest is also listed in detail. The following excel table excerpt (Table 3) clearly plots the

calculation route and input values to acquire the final total dry biomass. The wet weight yields

represent the total green matter yield.

Table 3 Wet Weight and Resulting Dry Weight Yields

Low Average High Name Wet Weight Moisture Name Wet Weight Moisture Name Wet Weight Moisture Low Average High

Common Name - - -

Cassava 13.3 15.6 83.4 Tuber 60 69.9 Leafs 15 81.0 Stem 25 15.0 5.6 6.6 35.1Grass 57.0 71.5 80.5 Whole 100 82.5 10.0 12.5 14.1

Lucerne 5.0 18.1 60.0 Whole 100 75.0 1.3 4.525 15.0

Maize 14.0 46.8 69.0 Ear 20 20.6 Stover 80 75.0 5.0 16.8 24.8Oil palm 30.0 58.4 72.0 Fruit 33 26.0 Fronds 50 69.9 Trunk 17 50.0 14.4 28.0 34.5

Potato 22.5 48.9 73.1 Tuber 89 78.0 Stover 11 60.0 5.4 11.7 17.5

Rapeseed 48.0 61.0 88.1 Seed 6 10.0 Pod 60 87.4 Stem 34 83.3 8.9 11.4 16.4Sorghum 25.0 35.0 75.0 Panicle 10 12.5 Leafs 15 80.0 Stalk 75 50.0 12.3 17.2 36.9

Soya bean 9.3 14.5 22.0 Seed 18 10.2 Stover 82 60.0 4.6 7.1 10.8

Sugar beet 42.9 82.3 142.8 Beet 70 76.6 Leafs 30 86.4 8.8 16.8 29.2Sugar cane 20.0 96.4 140.0 Cane 89 67.5 Leafs 11 80.6 6.2 30.0 43.5

Sunflower 3.5 6.5 15.7 Seed 35 20.0 Husk 15 30.0 Stover 50 70.0 1.9 3.5 8.4

Switchgrass 3.5 9.3 15.9 Whole 100 12.0 3.1 8.1 14.0Tobacco 33.2 200.0 221.0 Whole 100 88.0 4.0 24.0 26.5

Wheat 36.0 41.9 61.8 Grain 17 20.0 Stover 83 80.0 10.9 12.6 18.7

Willow tree 7.5 11.3 20.0 Whole 100 60.0 3.0 4.5 8.0

Crop

WW tonnes/ha

Wet Weight Constiguent Distribution Annual Yield

% DW tonnes/ha

Annual Yield

% %

In terms of biomass production only dry weight is of interest. The following graph (Figure 2)

illustrates the great differences present between wet and dry weight figures. The calculated

differences between the low and high total dry biomass figures are also present in the form of the

error bars. It is apparent that the water content can lead to some extreme differences in wet and

dry yields. As an example, from a wet weight basis one could assume that the sugar beet is a

much higher yielding crop than maize, where in fact on dry terms is in not. Using wet weight can

be misleading. To alleviate any discrepancies regarding yield, all figures will contain the prefixes

DW (dry weight) and WW (wet weight) alongside the ton/ha term.


Wet Weight and Dry Weight Yields

0

10

20

30

40

50

60

70

80

90

100

Cas

sava

Grass

Luce

rne

Maize

Oil pa

lm

Pota

to

Rap

esee

d

Sor

ghum

Soya

bea

n

Sug

ar bee

t

Sug

ar can

e

Sunflower

Switc

hgra

ss

Toba

cco

Whe

at

Willo

w tr

ee

ton/ha

Wet Weight

Dry Weight

142.8 186.6 240

Total Biomass Production

Best Practice Yields

Figure 2 Wet Weight and Resulting Dry Weight Yields

3.1.4 Growth Cycle

Not every crop is perennial or systematically cultivated on a regular annual cycle. Some crops

require more then one year before harvesting can commence. In the Table 4, it has been dubbed

as establish and growth:

Table 4 Cultivation Figures

Establish Growth Harvest 10-year

Common Name Per Cycle Replanting Rotation Gap factor

Cassava 12 12 1 2 0 0 0.50

Grass 0 8 1 1 0 0 1.00

Lucerne 0 7 4 7 8 1 1.00

Maize 0 9 1 1 3 1 1.00

Oil palm 36 12 2 25 0 0 0.88

Potato 0 6 1 1 1 3 1.00

Rapeseed 0 10 1 1 1 2 1.00

Sorghum 0 10 1 1 4 1 1.00

Soya bean 0 6 1 1 3 1 1.00

Sugar beet 0 7 1 1 1 3 1.00

Sugar cane 8 12 1 3 0 0 0.78

Sunflower 0 6 1 1 1 4 1.00

Switchgrass 12 7 4 10 0 0 0.90

Tobacco 0 12 4 1 2 1 1.00

Wheat 5 10 1 1 3 1 0.58

Willow tree 24 12 1 30 0 0 0.93

CropCultivation Figures

Rotation Years

Months

It is common practice to present the yield figures in the form ton/ha. The majority of crops (here

10 out of 16) are indeed annuals and harvested but once a year, so it can be assumed that the unit

ton/ha is analogous with ton/ha/y. For the other crops that have a growth cycle longer than one


year it can be confusing if the figures refer to annual yields or harvestable yields. If the listed yield

figures are indeed in reference to the harvesting period, the actual annual yield for such crops is

substantially less. Frequently the yield of the willow tree, for example, is based on a 3rd or 4th

year harvest. However the figures presented in Table 3 have been adjusted for the most part to

the average yield during an annum. By mentioning the establishment period and replanting

frequency adjustments can be made for those figures that do not refer to consistent yearly yields.

These yield corrections are of particular importance in determining the yields for a 10-year

average to be utilized in the pending efficiency calculations.

Arguably the greatest farming development during the Medieval Ages was the crop rotation

system. It was found that yields improved drastically by rotating different crop species on the

same field. In some instances the fields were even left uncultivated to allow the soil to recover.

Over the generations the best rotation practices were discovered and continue for the most part

to this day. The above table lists, if any, the common rotation periods and gap years. However,

the gap and rotation figures have been mentioned for informational purposes only and are not

included in any subsequent calculations. The replanting periods are on the other hand indeed

utilized in calculating the 10-year average values. The following calculation statement is used in

the excel formulation sheets as the 10-year average adjustment factor:

⋅

⋅

−

⋅

=

yearyear

months

establishreplanting

yearyear

year

months

F

1012

101012

10

For crops that require an establishment period and/or have a replanting frequency more than a

year will drop yields significantly over a 10-year period. The cassava, for instance has an

establishment period of a year and a growth period of a year, while requires no rotation.

Following the above calculations the actual cassava yields will be 50% less than previously listed

over a ten-year period. The white willow, in contrast has an establishment period of 2 years while

replanted only every 30 years. In this case, meaning the root structure is left in the ground for

sprout propagation. Again following the above calculations the actual white willow yields will be

93% of the listed yields. The losses connected to establishment time are partly circumvented

because of the long growth/rotation period. These calculations are included for all the crops in

the efficiency sections.

3.2 Chemical Composition

Another misleading aspect of the yield figures is the lack of depth. They say nothing about the

yield of the individual biochemical constituents. Using the crop guide the relationship between

each plant component, the chemical composition, moisture content and weight contribution

were used to calculate the biochemical constituents. Figure 3 depicts the proportional

relationship between the various constituents in the selected crops:


Constituents Proportions

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Pot

ato

Rap

esee

d

Sorgh

um

Soy

a be

an

Sug

ar b

eet

Sug

ar can

e

Sunflo

wer

Switc

hgrass

Toba

cco

Whe

at

Wi llow

tree

kg/kg

Ash

FatProtein

Lignin

Complex Carbohydrates (C5)

Complex Carbohydrates (C6)Simple Carbohydrate (S.C.)

Figure 3 Crop biochemical constituents proportions

Without words, this visual representation is perfectly capable of explaining the great variety of

composition each crop possesses. It is very important to convey this knowledge when selecting a

crop for industrial biochemical processing. The yield of the individual constituents is far more

useful tool in determining the possible chemical production routes. For an overall low yielding

crop may be a high yielding crop in a constituent of particular interest. Figure 4 displays such.

At a quick glance of all the choice crops, grass has one of the highest levels of protein, yet in

terms of total dry biomass it is on the lower end of the pack. No wonder cows are so big, simply

from eating grass all day. Compared to the soya bean, which is grown especially as a fodder for

rumen husbandry, grass has a noticeably higher yield of protein. One could falsely assume that by

following this graph it would be better to cultivate grass as a feedstock. However the absolute

terms of protein says nothing about to essential amino acids required by cows or other livestock.

The same holds true for the production of the functionalized chemicals, providing the reasoning

into the creation of the detailed information section of the crop guide. Nonetheless this

information is immensely valuable and will provide the basis for many subsequent calculations.


Usable Constituents Yields

0.0

2.5

5.0

7.5

10.0

12.5

15.0

Cassav

a

Grass

Luce

rne

Maize

Oil p

alm

Potato

Rape

seed

Sorghum

Soya

bean

Sugar b

eet

Sugar cane

Sunflower

Swit chgra

ss

Tobacco

Whe

at

Wi ll

ow t r

ee

ton/ha DW

Simple Carbohydrate (S .C.)Complex Carbohydrates (C6)

Complex Carbohydrates (C5)LigninProteinFat

17.3 18.4

Figure 4 Crop biochemical constituents yields

3.2.1 Unusable components

The biochemical constituents represent the portion of the plant that can be processed in some

form or another to engineer a viable product. These, however, do not embody the entire plant

mass. Ash, minerals and other trace elements are also present. Yet because these components

cannot be converted into viable products following traditional biochemical pathways, they are

considered unusable. The possible alternative uses (e.g. agricultural nutrients) of these biochemically

unusable components are discussed later in detail (see Chapter 7). In terms of potential yield for

biomass applications the unusable components must be regarded as a material loss. Yield figures

are consequently adjusted for use in further calculations. The following excel excerpt (Table 5)

outlines the material loss values:

Table 5 Unusable biomass portion

Name Name Name

Common Name - Constituent Plant Part - Constituent Plant Part - Constituent Plant Part Value %

Cassava Tuber 3.9 0.4 Leafs 11.3 0.1 Stem 5.0 0.5 0.050 5.0

Grass Whole 11.4 1.0 - 0.0 - 0.0 0.114 11.4

Lucerne Whole 20.1 1.0 - 0.0 - 0.0 0.201 20.1

Maize Ear 3.0 0.3 Stover 9.9 0.7 - 0.0 0.081 8.1

Oil palm Fruit 1.7 0.5 Fronds 20.1 0.3 Trunk 12.0 0.2 0.093 9.3

Potato Tuber 8.5 0.8 Stover 5.0 0.2 - 0.0 0.079 7.9

Rapeseed Seed 6.0 0.3 Pod 11.9 0.4 Stem 4.9 0.3 0.081 8.1

Sorghum Panicle 8.1 0.2 Leafs 5.0 0.1 Stalk 4.9 0.8 0.055 5.5

Soya bean Seed 10.2 0.3 Stover 5.0 0.7 - 0.0 0.067 6.7

Sugar beet Beet 10.7 0.8 Leafs 13.6 0.2 - 0.0 0.113 11.3

Sugar cane Cane 5.9 0.7 Leafs 10.0 0.3 - 0.0 0.071 7.1

Sunflower Seed 6.1 0.5 Husk 9.3 0.2 Stover 11.1 0.3 0.081 8.1

Switchgrass Whole 17.8 1.0 - 0.0 - 0.0 0.178 17.8

Tobacco Whole 5.2 1.0 - 0.0 - 0.0 0.052 5.2

Wheat Grain 2.3 0.0 Stover 10.2 0.0 - 0.0 0.000 0.0

Willow tree Whole 2.8 1.0 - 0.0 - 0.0 0.028 2.8

CropTotal Material LossDry Weight Dry Weight Dry Weight

(Isolated Minerals, Ash, and Trace Elements)


It is remarkable that of the listed crops, the three grass types all have a significantly large portion

of material loss, ranging from 11.4 – 20.1%. This can greatly affect the resulting crop efficiency.

3.3 Energetic Output

3.3.1 Calorific Values

Utilizing biomass to produce energy is by all means

nothing new. The first human application, fire, sparked

the genesis of human civilization. For millennia forests

provided huge reservoirs of accessible burnable material

and formed the bulk of civilizations early energy

demands. The discovery of coal, and later other fossil

fuels, combined with the rapid diminishing rate of

forests brought about an energy source shift. In more

recent years bioenergy has since seen a rebirth, at least in

the research sector. Yet, wood is no longer the sole focal

point of investigation, practically all types of biomass are

considered feasible and subjected to analysis. They can range from agricultural waste, to un-

utilized agricultural forage, to the primary cultivated product. The potential energy release during

combustion of each biomass forms can be determined using modern engineering practices (see

Textbox). Such calorific values have since been documented for the vast majority of crops and

crop residues.

Despite the previous sentiment, the current blunt of bioenergy research has focused on utilizing

agricultural residues. This causes precisely the same conflict as with determining the yield figures;

a problem of unison. For example, the calorific values for winter wheat are expressed separately

for the dry grain as for the residual straw. It is desirable to attain a common expression for the

entire crop, a total calorific value. By knowing the moisture content, weight distribution and

calorific values for the individual plant parts the total calorific values can be calculated, higher

and lower heating value.

3.3.2 Group Contribution Formation Energy

The calorific values for a few of the plant parts are absent and have been logically estimated in

large part from comparison amongst the other crops. For instance, the stem/stover (based on the

known crop values for stem/stover) is set at 17000MJ/ton LHV and 17500MJ/ton HHV when

undetermined. This presents a slight uncertainty when using the calorific values and also neglects

the entire aspect of exergy. Another calculation method is readily available that employs more

accurate and abundant data supplied from the crop guide while tackling the notion exergy. The

group contribution method addresses in detail the formation bond energy/exergy required for

the individual biochemicals. In the previous section, biochemical constituents, the yield and

distribution of the biochemicals composed in the crop biomass was calculated. The group

Heating value (or calorific value) is used to define the amount of heat released during the combustion of a fuel or food. It is measured in units of energy per amount of material. Depending on the context, heating values may be reported as Btu/m³, kcal/kg, J/mol, or a variety of other combinations of units. Heating value in commonly determined by use of a bomb calorimeter. The quantity known as higher heating value, HHV, (or gross calorific value or gross energy) is determined by bringing all the products of combustion back to the original pre-combustion temperature. The quantity known as lower heating value, LHV, (or net calorific value) is determined by subtracting the heat of vaporization of the water in the by-product from the higher heating value results

Source: Wikipedia.org


contribution method can be used to calculate the energy and exergy present in all of the

biochemicals, including the ash. Table 6 is an exemplary guide to the method:

Table 6 Group Contribution Method

Component Picture Formula Mole Weight Group b

och H

oAmount Exergy Enthalpy

Name g/mol #

Glucose C6H12O6 180.16

Sum 2922.15 2357.78

(Simple Carbohydrates) Value 16.22 13.09

kJ/mol kJ/mol

545.27 485.75

-52.59 -85.11

6

5

3271.62 2914.5

-262.95 -425.55

-86.52 -131.17 1-86.52 -131.17

CH

CH OH

O

*Enthalpy of devaluation (Ho) and standard chemical exergy (boch) are supplied by Szargut12

Listed in the accompanying database spreadsheet are the calculations for the other

biocomponents and further details regarding the method. Protein is a special component as it

consists of a combination of 20 different amino acids. Only for several of the crops (and for that

matter, plant part) is the amino acid distribution of the protein known. For this reason the

average, so-called base amino acid, structure was taken to be representative. The same procedure

has been adapted for the fatty acids (oils), due to lack of detailed oil composition data. Even so

the affect of such simplifications are negligible. It is noticeable that ash has a chemical energy and

exergy of 2.89MJ/kg and 2.43MJ/kg respectively, which is significantly lower than the other

components. Ash, as handled here, is the oxidized (combusted) result of the trace minerals and

biochemicals. The amount of energy/exergy present in such materials while present in the plant

is easy several magnitudes larger, yet since they are regarded as a material loss (as per current

technique) the oxidized values are best suited for biochemical applications.

3.4 Results

3.4.1 Total Energetic Output

Yield figures, calorific values and formation energy alone are not enough to pronounce a final

representative output for a crop species. As the biochemical group contribution method is more

accurate than the calorific value method it will be used henceforth to represent the crop energy

content. A function between the yield and energy content, however, leads to the workable energy

output on the basis of land area:

Total dry biomass yield ⋅ total formation energy = total energetic output [MJ/ha]

Figure 5 has plotted the resulting energetic and exergetic output for the selected crops.


Energetic and Exergetic Result

0.0E+00

1.0E+05

2.0E+05

3.0E+05

4.0E+05

5.0E+05

6.0E+05

7.0E+05

8.0E+05

9.0E+05

1.0E+06

Cas

sava

Gra

ss

Luce

rne

Maize

Oi l pa

lm

Potat

o

Rap

esee

d

Sorg

hum

Soya

bea

n

Sug

ar b

eet

Sug

ar can

e

Sunflo

wer

Swi tc

hgrass

Toba

cco

Whe

at

Willow

tree

MJ/ha

Energy

Exergy

Based On Total Group Contribution Method

Figure 5 Resulting Crop Energetic Output

The amount of usable energy (exergy) obtainable per land area is greater than the energy due to

the higher chemical exergy in relation to chemical energy of the biochemicals. A stark difference

between the various crops is apparent, reflecting the land use intensity.

3.4.1.1 Comparative Analysis

Describing and visualising the resulting energy output figures is a very good way to present the

individual crop figures that will compose the basis of all the subsequent efficiency calculations.

Yet, a systematic comparison must be developed for the various categories to help further

judgement in crop choice selection. It is best to create a simple table outlining the main points of

argumentation. Within the output section, resulting energetic output is only one factor of interest.

Even if it is by far the most important, the other categories must be mentioned to provide an

adequate overview. See Table 7 for the resulting dry weight yields and the individual biochemical

constituents as two such important output figures:


Table 7 Comparative Output Overview

Crop Yields Biochemical Constituents Output

Common Name Total DW Simple C. Complex C. Lignin Protein Fats Energy Exergy

Cassava + + + + + O + + Grass O O O - + O - O Lucerne O - O O + - - - Maize + + + + + O O + Oil Palm + - + + - + + + Potato O + O - O - - O Rapeseed O - O O + + O O Sorghum + + + + O - + + Soya Beans O - O O O O - O Sugar Beet + + O - O O O O Sugar Cane + + + O - O O + Sunflower - - O O O + - - Switchgrass O - O + - - - O Tobacco + - + + + - O + Wheat O O O O + - - O Willow Tree - - O O - - - -

Total DW: + above 20ton/ha, - below 10ton/ha, O between 10 – 20ton/ha Simple C.: + above 5ton/ha, - below 1ton/ha, O between 1 – 5ton/ha Complex C.: + above 10ton/ha, - below 2.5ton/ha, O between 2.5 – 10ton/ha Lignin: + above 2.5ton/ha, - below 0.5ton/ha, O between 0.5 – 2.5ton/ha Protein: + above 2.5ton/ha, - below 1.5ton/ha, O between 1.5 – 2.5ton/ha Fats: + above 1ton/ha, - below 0.25ton/ha, O between 0.25 – 1ton/ha

Total energy: + above 5.0⋅105MJ/ha, - below 2.5⋅105MJ/ha, O between 2.5⋅105 – 5.0⋅105MJ/ha Total exergy: + above 5.0⋅105MJ/ha, - below 2.5⋅105MJ/ha, O between 2.5⋅105 – 5.0⋅105MJ/ha



4 Solar Input The major source of energy input in plants is quite obviously the sun. Determining the solar

input is based on two factors, the location and the cultivation period. Common sense suggests

that a plant cultivated in the tropics will have higher yields than one cultivated in Siberia. On a

general stance this is indeed true, yet the solar efficiency is another matter completely. The

amount of energy out (yield ⋅ caloric value) per energy in (solar energy) can widely vary from crop species regardless of location. Based on these indications, it could be advisable to cultivate some

species in a non-native area, granted it complies with the growth details.

4.1 Location

Solar radiation values are based on a monthly basis over a 10-year average. Data is available for

the entire world over and was obtained from:

• NASA Surface meteorology and Solar Energy: SolarSizer Data13 The location is stipulated using the global coordinate system and through an

interactive graphical map program (see adjacent picture). A 1x1 deg square

region is set (highlighted in red). The accuracy of the database is 0.1deg

longitude and 0.1deg latitude. Seeing that the world is a sphere the

corresponding distances are different for each specific location. However, an

estimate can be made that regions above the Tropic of Cancer and below the

Tropic of Capricorn are roughly 100x100km. Those regions in between are

closer to 150x150km. In regards to the cultivation areas, these differences are

insignificant.

The location choices listed previously (see Table 1) in many cases span vast land areas. In cases

where hundreds of kilometres scope is present a known cultivation region is selected. Common

sense and well-documented cultivation information dictate the region choice, which are used to

set the exact coordinates. The following excel table excerpt (Table 8) indicates the chosen

location, chosen coordinates and resulting solar monthly solar radiation input:

Table 8 Location Based Solar Radiation Values

Lat itude Longitude Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecCommon Name

Cassava Africa Nigeria 8 7 188 179 193 180 169 152 146 138 145 164 173 177Grass Europe Holland 51 5 23 40 78 114 153 147 154 131 85 53 28 19

Lucerne North America South Dakota 44 -103 53 70 106 141 180 192 199 173 128 92 55 44

Maize North America Iowa 41 -91 57 74 108 133 167 180 190 165 128 92 56 46

Oil palm South Pacific Malaysia 2 113 140 137 152 148 152 151 155 159 150 154 141 143

Potato Europe Holland 51 5 23 40 78 114 153 147 154 131 85 53 28 19

Rapeseed Europe Belgium 50 5 25 43 78 112 148 143 155 133 88 56 30 20

Sorghum Africa Kenya 0 35 178 168 190 164 166 154 153 157 171 178 168 174

Soya bean North America Illinois 41 -90 57 75 103 133 167 180 184 161 123 89 50 47

Sugar beet Europe Germany 52 8 22 38 70 109 150 140 145 123 82 50 25 17

Sugar cane South America Brazil -25 -50 173 143 141 119 100 95 104 122 129 157 170 171

Sunflower Europe France 48 0 29 48 83 116 149 150 163 138 100 62 35 25

Switchgrass North America Iowa 41 -91 57 74 108 133 167 180 190 165 128 92 56 46

Tobacco South Pacific Australia -34 145 231 193 171 122 92 74 80 105 145 185 209 222

Wheat Europe France 48 0 29 48 83 116 149 150 163 138 100 62 35 25Willow tree Europe Sweden 56 13 17 32 69 113 169 165 166 132 84 47 23 16

khW/m²/month

Crop

Degrees

Continent Country/RegionLargest Producer

Representative Area Solar Radiation Values (Energy)


These figures will be used throughout the rest of the solar radiation calculations. The exergy

values are not displayed, but are a function of solar radiation values (see Chapter 2) and differ

only marginally from the energy terms. It must be stated that there are several possible cultivation

regions for the same crop as mentioned in the crop guide (see Section 2.3.2). The solar radiation

figures will be different for each. As a common example, the potato can and is cultivated in

Holland, Germany and France, which have 154, 145 and 163khW/m² in July respectively. This

represents a standard deviation just over 5%. To circumvent this error the yield figures (see

Section 3.1) correspond to the specified region. In the following efficiency section, this topic will

go into more detail.

4.2 Cultivation Period

It is common mistake applied by most researchers in the field of agriculture and biomass

technology to simply assume an average solar radiation input for all crops. Typically a figure of

1000khW/m²/y is chosen. This is approximately the Northern Hemisphere annual average. It is

also a major fundamental error that should be present in the form of an erratum, but sadly is not.

There are two principal argumentations reasoning against this widespread simplification. The first

is the differences of solar radiation dependent on cultivation location, which has been mentioned

above. The second is the cultivation period.

What is understood by cultivation period is basically the duration of time the crop is actually in

the ground. This starts with propagation (should it be from seed, fruit or re-sprouting) until the

final harvesting. During the periods a crop is not present in the ground the solar radiation cannot

be incorporated as an input. In many cases another crop could be planted in between the

cultivation cycles and could thus theoretically benefit from the otherwise squandered solar

radiation input. Winter wheat is perfect example to illustrate this point:

In the beginning of autumn, around October, the seeds are drilled into place. They remain in the soil until the following spring. During the autumn the solar radiation is not converted into biomass, yet the crop (in the form of the seed) is present in the ground. Only in the beginning spring do they begin to sprout. This facilitates the crop to utilize the maximum amount of springtime solar radiation. In the month of July the harvesting procedure begins and by mid July the grains are ready for storage. The time between mid-July and October is the prime months in terms of solar radiation in the Northern Hemisphere. Since the crop is not occupying the field at the time, these values must be deducted from the total solar input. If it is necessary that the field use this time for recovery, before the next cultivation, then indeed the months must be included. However, a simple crop like ryegrass or lu cerne could most likely strive during that period and yield additional biomass; a so-called catch crop.

The various combinations of growth cultivations are best left to the farmers based on regional

circumstances. Success is of course questionable, yet in any case the option does exist. From this

standpoint the solar radiation input is a function of the cultivation period. The following excel

table excerpt (Table 9) indicates the growth period as extracted from the crop guide:


Table 9 Cultivation Period for Solar Radiation Input

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Common Name

Cassava 1 1 1 1 1 1 1 1 1 1 1 1

Grass 0 0 1 1 1 1 1 1 1 1 0 0

Lucerne 0 0 0 1 1 1 1 1 1 1 0 0

Maize 0 0 1 1 1 1 1 1 1 1 1 0

Oil palm 1 1 1 1 1 1 1 1 1 1 1 1

Potato 0 0 0 1 1 1 1 1 1 0 0 0

Rapeseed 1 1 1 1 1 1 1 0 0 1 1 1

Sorghum 1 1 1 0 0 1 1 1 1 1 1 1

Soya bean 0 0 0 0 1 1 1 1 1 1 0 0

Sugar beet 0 0 0 0 1 1 1 1 1 1 1 0

Sugar cane 1 1 1 1 1 1 1 1 1 1 1 1

Sunflower 0 0 0 1 1 1 1 1 1 0 0 0

Switchgrass 0 1 1 1 1 1 1 1 0 0 0 0

Tobacco 1 1 1 1 1 1 1 1 1 1 1 1

Wheat 1 1 1 1 1 1 1 0 0 1 1 1

Willow tree 1 1 1 1 1 1 1 1 1 1 1 1

Occurrences

CropCorresponding Growth Period

4.3 Results

4.3.1 Total Energetic Input

By combining both the monthly solar radiation values with the cultivation period the amount of

intercepted solar energy can be determined. This is expressed per land area and acts as the

resulting solar radiation input component. Figure 6 illustrates the large differences location and

cultivation practices exert on input solar energy:

Solar Radiation Input

0.0E+00

2.5E+07

5.0E+07

7.5E+07

Cass

ava

Gra

ss

Luce

rne

Maiz

e

Oil p

alm

Potato

Rape

seed

Sorghu

m

Soya bea

n

Sugar b

eet

Sug

ar can

e

Sunflower

Switc

hgras

s

Tobacc

o

Whea

t

Willo

w tree

MJ/ha

Annual Growth Period (energy)

Annual Growth Period (exergy)

Figure 6 Resulting Solar Radiation Input


If one were to average the solar radiation for all the crops, the value of 1000kWh/m²

(3.6⋅107MJ/ha) would indeed be a good approximate. It is however clear that there are large differences between the various crops, ranging from roughly 700 to 2000kwh/m² (2.5⋅107 to 7.0⋅107MJ/ha). This represents a deviation of more than 250%. It should now be apparent why the simplification is unacceptable. When referring to solar radiation the SI-units kWh/m²/y are

generally implied. They can easily be converted into the more workable and transparent SI-units

MJ/ha. Only the latter is indicated on the above graph.

4.3.2 Efficiency

Converting the solar radiation figures from kWh/m² into MJ/ha is preformed because the total

resulting energy output (see Section 3.4.1) is expressed in terms of MJ/ha. Relating the two

figures will result in the solar efficiency as indicated by the simple formula:

[ ]haMJInputSolar

haMJOutputEnergeticEfficiencySolar

/_

]/[__ =

Figure 7 displays the resulting solar efficiency for the total yield with 10-year average and the

yield error bars included:

Efficiencies

0.00

0.25

0.50

0.75

1.00

1.25

1.50

Cas

sava

Gra

ss

Luce

rne

Maize

Oi l pa

lm

Pot

ato

Rap

esee

d

Sor

ghum

Soy

a be

an

Sugar

bee

t

Sug

ar can

e

Sun

flower

Switc

hgra

ss

Toba

cco

Whe

at

Willo

w tr

ee

Conversion Percent [%

]

Energy

Exergy

Based on Solar Radiation Input Energy

1.90

Figure 7 Resulting Solar Radiation Utilization Efficiency


Solar input, the largest and most significant input factor, when converted into efficiency terms

displays completely different results than the corresponding yield outputs or energetic outputs.

The sugar cane, for example, is a high-yielding, high-energy crop, but fairs rather average in this

respect.

4.3.3 Analysis

Table 10 Comparative Solar Input Overview

Crop Solar Radiation (energy) Solar Radiation (exergy)

Common Name Input Efficiency Input Efficiency Cassava + - + - Grass - O - O Lucerne O O O O Maize O + O + Oil Palm + + + + Potato - O - + Rapeseed - + - + Sorghum + O + + Soya Beans - O - O Sugar Beet - + - + Sugar Cane + O + O Sunflower - O - O Switchgrass O - - O Tobacco + O + O Wheat - - - O Willow Tree O - - -

Input: + above 5.0⋅107MJ/ha - below 3.6⋅107MJ/ha, O between 3.6 – 5.0⋅107MJ/ha Efficiency: + above 1.0%, - below 0.5%, O between 0.5 – 1.0%



5 Results and Discussion The top 3 choice crops for each category will be handled separately.

Yield is the term to express the mass gained per cultivated area. It is presented in a multitude of

different ways, ranging from the food based component to the entire wet biomass. Both the total

wet weight and dry weight figures were determined. Additionally the total dry weight has been

related to the solar radiation energy to create a land use factor. Table 11 lists the top 3 crop

results from the yield category:

Table 11 Top 3 Crops on total mass premises

Wet Weight Yield Dry Weight Yield Land Use Factor

Top Crops ton/ha g/GJ

1. Tobacco: 240 Sorghum: 36.9 Sugar Beet: 1133 2. Sugar Cane: 186.6 Cassava: 35.1 Maize: 711.6 3. Sugar Beet: 142.8 Sugar Cane: 35.0 Potato: 621.5 4.* Rapeseed: 88.1 - -

*A 4th top crop has been added because the tobacco crop is base in large part on experimental data and cannot be taken to properly represent the yield figures. The experimental data is based on a small plot of 100ha Australian test plot, meaning it is most likely that practical yields will be but a fraction. Whenever the tobacco crop is present on the list an addition crop will accompany 4th place, should yields not be reproducible when brought to full-scale applications. For instance, the wet leaf (smoking tobacco) yield in America is 25ton/ha and at 65% moisture is around 9ton/ha DW; about two thirds less.

It is clearly noticeable, also from Figure 2, that the differences between dry weight and wet

weight yields are great. The deviation in weight terms for the select crops ranges from 12% up to

88%. This enormous range clearly stresses the importance of having the yield figures presented in

a standardized term. Dry weight is the most logical term for this task, yet wet weight cannot be

excluded as moisture content will play a deceive role in harvesting techniques and downstream

processing. The ranking positions between the two are also slightly altered with the sorghum

resulting as the leader for yield. The last column has been dubbed “land use factor” and has the unit

g/GJ. It indicates the relationship between the crop productivity and the input of solar radiation.

Assuming that farming practices are to be upheld in a different and compatible region, the yields

will be intrinsically correlated to solar radiation. Temperate crops (like the potato and sugar beet)

are grown in wealthy regions which have highly intensified agriculture. Tropical versions are less

likely to yield the same land use factor, as other agricultural limitations like less intensified

farming and water shortages are present. It could be fathomable that if the crops were properly

adjusted and managed for sunny regions that the yields would be incredible. This aspect is only

one piece of the puzzle as increased energy intensive agriculture will reduce the land use factor.

Those particular topics are covered in the subsequent chapters, yet the solar factor on land use is

quite arguably the largest determinant.

Total yield is a useful tool is displaying general trends for biomass production, but to address the

specific demands of a chemical industry more detailed information is required. The same

procedure is applied to the yield of the individual biocomponents contained in the crop, Table 12


Table 12 Top 3 Crops on Carbohydrate Yields

Simple Complex Total Simple Complex Total

Top Crops ton/ha (DW) g/GJ

1. Sugar Beet: 18.6

Tobacco: 20.4

Sugar Cane: 29.3

Sugar Beet: 713

Tobacco: 309

Sugar Beet: 911

2. Sorghum: 17.3

Sugar Cane: 17.5

Sorghum: 29.2

Potato: 368

Sugar Cane: 299

Maize: 507

3. Sugar Cane: 11.8

Cassava: 14.4

Cassava: 26.2

Sorghum: 285

Maize: 273

Sugar Cane: 501

4.* - Maize: 14.3

- - Rapeseed: 239

-

The simple carbohydrates are important for the production of 1st generation biofuels (ethanol);

the higher the yield of simple carbohydrates the more biofuel per land can be produced. Whereas

complex carbohydrates are becoming more important as they can also be utilized for biofuel

production using so-called 2nd generation technology. In fact, 2nd generation can utilize both

simple and complex forms. What is clear from looking at the list is that both maize and cassava

do not score very well against the competition in the simple carbohydrate section but make the

list for complex. Such crops should thus only be cultivated for biofuels when a 2nd generation

processing plant is available, else the sugar beet, for example, would fair better. The total

carbohydrate yield is conversely a much better indication as 1st generation is being phased out for

2nd generation. By the time full-scale implementation is properly realised it would be wasteful to

construct a 1st generation installation. In the realm of chemical products carbohydrates are also

important for many bulk chemicals, yet of no or low order of functionality. The biochemical

constituents with more functionality and thus a higher energy saving potential are in Table 13:

Table 13 Top 3 Crops on Lignin Yields

Dry Weight Yield Land Use Factor


1. Cassava: 4.2 Maize: 87.8 2. Maize: 3.9 Switchgrass: 67.2 3. Oil Palm: 3.7 Cassava: 58.4

Lignin is the biocomponent associated with aging for strength and stability of crops. Logic would

figure that a fast-growing perennial tree, like the willow, would dominate this category. It does

score above normal, but far below expectations, mainly due to the relatively low Swedish yields.

There is more lignin developed in the stem of the maize than the trunk of the willow.

Table 14 Top 3 Crops on Protein Yields



1. Rapeseed: 4.3 Rapeseed: 147 2. Lucerne: 3.6 Lucerne: 91.7 3. Tobacco: 3.5 Grass: 83.1 4.* Maize: 3.3 -


Protein contains the highest degree of functionality. All amino acids include an amine group

(nitrogen) and are interrelated to the level of nitrogen fertilization. The following chapter will use

the above table (14) to analysis the relationship between the yield and level of fertilization.

Table 15 Top 3 Crops on Fatty Acid Yields



1. Oil Palm: 13.1 Oil Palm: 204 2. Rapeseed: 2.6 Rapeseed: 90.8 3. Sunflower: 2.4 Sunflower: 82.2

As listed in Table 15 it is not surprisingly the crops with the highest fats/oil yield are those

currently employed in biodiesel production. From looking at the yield differences between them

the obvious choice (should land productivity be an issue) is the oil palm. Europe will never be

able to compete against Malaysian imports on an open market. That is, without a biorefinery

producing other high value products.

The amount of weight produced on the fields is only one aspect handled in this chapter, the

energetic output and ratio to incoming solar radiation is the other, Table 16.

Table 16 Top 3 Crops on Energy/Exergy Output

Top Crops Energy Exergy Solar Efficiency (Input/Output)

GJ/ha Energy Exergy

1. Oil Palm: 833 Oil Palm: 923 Sugar Beet: 1.47% Sugar Beet: 1.90% 2. Cassava: 538 Sorghum: 639 Oil Palm: 1.14% Oil Palm: 1.36% 3. Sorghum: 537 Cassava: 638 Rapeseed: 1.06% Rapeseed: 1.32%

In the context of energy and exergy content the differences between output may be slight but are

noticeable. The underlining reasoning is the difference between the energy and exergy content of

protein, having a deviation of 22.6%. For the production of bioenergy this table is of utmost

importance but is not of terrible significance in the chemical field. Burning protein for its

calorific value is quite different than the potential process energy savings in the chemical industry.

For such considerations the above biochemical yield relations with land use guides are much

better suited. Furthermore the chemical production from biomass will not be a single product

but a multitude as defined by the concept of a biorefinery. Concrete conclusions for the

biochemical industry cannot be drawn from any of these values alone, but will act as a strong

basis in all proceeding calculations.



References

1. Eerste Kamer (Upper House) 10de Vergadering; The Hague, 12 December, 2005, 2005; p 41. 2. Hoogwijk, M. M. On the Global and Regional Potential of Renewable Energy Sources.

University of Utrecht, Utrecht, 2004. 3. International Fertilizer Industry Association (IFA) World Fertilizer Use Manual.

http://www.fertilizer.org/ifa/publicat/html/pubman/manual.htm 4. Duke, J. A. Handbook of Energy Crops.

http://www.hort.purdue.edu/newcrop/Indices/index_ab.html 5. U.S. Department of Energy Biomass Feedstock Composition and Property Database.

http://www1.eere.energy.gov/biomass/feedstock_databases.html 6. Energy research Centre of the Netherlands (ECN) Phyllis: Database for biomass and waste.

http://www.ecn.nl/phyllis/info.asp 7. Food and Agriculture Organization of the United Nations (FAO) FAOSTAT: FAO

Statistical Databases. http://faostat.fao.org/faostat/default.jsp?language=EN&version=ext&hasbulk=

8. Food and Agriculture Organization of the United Nations (FAO) Grassland Species: Profiles. http://www.fao.org/ag/AGP/AGPC/doc/GBASE/Default.htm

9. Leaf for Life Index of Top Crops. http://www.leafforlife.org/PAGES/TOPINDEX.HTM 10. Interactive European Network for Industrial Crops and their Applications (IENICA) Crops

Database. http://www.ienica.net/cropsdatabase.htm 11. Reisinger, K.; Haslinger, C.; Herger, M.; Hofbauer, H. BIOBIB - A Database for Biofuels.

http://www.vt.tuwien.ac.at/biobib/oxford.html 12. Szargut, J.; Morris, D. R.; Steward, F. R., Exergy Analysis of Thermal, Chemical, and Metallurgical

Processes. Springer-Verlag: 1988; p 332. 13. NASA Surface meteorology and Solar Energy: SolarSizer Data. http://eosweb.larc.nasa.gov/



Chapter 5 Prime Energy Input

Required energy and exergy input to promote the cultivation of biomass

Ben Brehmer

Dissertation Report


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Abstract The modern mechanized cultivation of biomass requires significant energy and material inputs

from a multitude of different sources and forms. Seen from the cradle-to-grave they can be

separated into direct (prime) and indirect (secondary) energy and material streams. Those directly

attributed to biomass growth are covered within this chapter; namely fertilizers, irrigation,

drainage and crop protection. Fertilizers per se contain very little usable energy for the crops so

the energy requirements for fertilizers are based on the entire production chain for the nutrients.

Plant nutrients are classified in two groups, primary and secondary; the production processes for

the primary nutrients have been thoroughly investigated. As there are many types and grades of

fertilizers available on the market, those representing the typical and expected market share on

the European market were calculated. The process chains behind those specific fertilizers are

based on logically selected routes from the Best Available Techniques to represent likely near

future averages. Crop nutrient uptake levels were chosen instead of various fertilizer application

rates to avoid discrepancies in farming techniques. Combining the process dependent energy

requirements with the nutrient requirements generates the fertilizer energy and material input

figures. Irrigation is also calculated based on regional rainfall levels versus crop water uptake

levels on a monthly basis. The difference between effective rainfall and crop evapotranspiration

must be supplied via irrigation and drained should it exceed the optimum levels. The process

energy behind typical irrigation systems and water sources were calculated on the regional based

scale for the individual crop. Crop protection measures are performed using agrichemicals called

pesticides. As with the fertilizers the process energy have been tabulated, but as there are more

than 2500 different pesticides on the market only a select few commonly applied chemicals have

been investigated. All the input figures have been set against the resulting energy output of each

crop to determine and compile an overall efficiency comparison as was previously conducted in

Chapter 4. The inefficiencies of fertilizer and pesticide application will be handled in the

following chapter. All the processes and methods were adopted and expanded to include both

energy and exergy values.

Key Words:

Fertilizer, Nutrients, Irrigation, Drainage, Pesticide, Energy, Exergy, Efficiency



Content

Abstract 117

1 Introduction 123


2 Fertilizer Input 125

2.1 Preface 125

2.1.1 Historical Background 125

2.1.2 Industrialization 125

2.1.3 Best Available Techniques 126

2.1.3.1 Assumptions 126

2.2 Nitrogen 129

2.2.1 Brief Description and Nutrient Importance 129

2.2.2 Process Choice and Description 132

2.2.2.1 Ammonia 133

2.2.2.2 Nitric Acid 135

2.2.2.3 Ammonium Nitrate 136

2.2.2.4 Urea 138

2.2.2.5 Urea Ammonium Nitrate 139

2.2.3 Energetic Result 140

2.3 Sulphur 143



2.3.2.1 Hydrogen Sulphide - Sulphur 145

2.3.2.2 Sulphuric Acid 147


2.4 Phosphorous 150



2.4.2.1 Phosphate Rock 152

2.4.2.2 Phosphoric Acid 153


2.5 Potassium 157



2.5.2.1 Potash 158


2.6 Calcium and Magnesium 161


2.6.1.1 Calcium 161


2.6.1.2 Magnesium 162


2.6.2.1 Dolomite Limestone 163


2.7 Micronutrients 164




2.8 Complex Fertilizers 166



2.8.2.1 NPK 167

2.8.2.2 CAN 169


2.9 Nutrient Uptake 173

2.10 Results 176



2.10.3 Analysis 180

3 Water Input 181

3.1 Crop Water Demand 182

3.1.1 Seasonal Amount 182

3.1.2 Relation to Monthly Evapotranspiration 183

3.1.2.1 Growth Stage Factor 183

3.1.2.2 Solar Radiation Factor 185

3.1.2.3 Solar Radiation Factor Assumption Valorization 186

3.1.2.4 Evapotranspiration 188

3.2 Rainfall 189

3.2.1 Regional Figures 189

3.2.2 Effective Rainfall 190

3.3 Irrigation/Drainage Requirements 191

3.3.1 Systems and Sources 191

3.3.1.1 Furrow 191

3.3.1.2 Basin 192

3.3.1.3 Drip 192

3.3.1.4 Sprinkler (travelling gun) 192

3.3.1.5 Sprinkler (center pivot) 192

3.3.1.6 Water body 192

3.3.1.7 Drainage 192

3.3.2 Irrigation Levels 193


3.3.3 Pump 193

3.3.3.1 Fuel Source 194

3.4 Resulting Energy 195


3.4.2 Conversion Efficiency 195

3.4.3 Analysis 196

4 Pesticide Input 197

4.1 Preface 197


4.1.2 Agricultural Applications 197

4.2 Process Energy 199

4.2.1 Source of Data 199

4.2.2 Grouping 200

4.2.3 Calculations 201

4.3 Crop Pesticide Application Rates 202

4.3.1 Crop and Regional Comments 202

4.3.1.1 Cassava – Nigeria 202

4.3.1.2 Grass – Holland 202

4.3.1.3 Lucerne – Wyoming 202

4.3.1.4 Maize – Iowa 202

4.3.1.5 Oil Palm – Malaysia 203

4.3.1.6 Potato – Holland 203

4.3.1.7 Rapeseed – Belgium 203

4.3.1.8 Sorghum – Kenya 203

4.3.1.9 Soya Beans – Illinois 203

4.3.1.10 Sugar Beet – Germany 203

4.3.1.11 Sugar Cane – Brazil 203

4.3.1.12 Sunflower – France 204

4.3.1.13 Switchgrass – Oregon 204

4.3.1.14 Tobacco – Australia 204

4.3.1.15 Wheat – France 204

4.3.1.16 Willow Tree – Sweden 204

4.3.2 Results 204




4.4.3 Analysis 208


References 213



1 Introduction In basic science books, written for our credulous children, photosynthesis would appear to be the

only system dictating plant growth. Water plus Air plus Solar Radiation will be converted via the

Calvin Cycle into glucose or respectively biomass. The other thousands of biochemical pathways

are ignored for simplification reasons, as they are indeed not the reactions yielding energy for

growth. For the most part this knowledge has remained engraved in the minds that span the

duration of our lives. In the antiquities, this sediment could very well hold true, even amongst the

ranks of the educated. Plant a seed, add some water and during the sunny months a crop will

emerge. This over simplification cannot be used when arguing the entire input requirements for

modern larger scale industrial applications of biomass.

As an interesting tidbit, in Mesopotamia “the cradle of civilization” for example, winter wheat

had an average grain yield of 2ton/ha1. In Holland, during the medieval period with an arguably

gloomier climate (probably what drove Van Gogh into depression) the average grain yield of

winter wheat was slightly below 1ton/ha. Today, the Dutch yields have increased nearly ten fold.

What can be attributed to this incredible increase of plant growth? Surely global warming has not

yielded ten times more sunny days in Holland. Should that be true, most locals would look like a

typical English tourist visiting Mallorca, lobster red.

Farming techniques, cultivation methods and centuries of experience have given farmers a feeling

of the best spacing and seedling ratio for any particular crop. Mechanization is definitely one of

the major advancements and contributions. Combined they have allowed a near optimum of

ground coverage, timing and speed to maximize the solar radiation component. In fact, seen on

the cradle-to-grave, operating and maintaining farming tools is already a significant required

input. Diesel to drive tractors, harvesters, combines, etc., food to supply the workers on the fields

and so on. However, in comparison to solar energy, this is practically insignificant. Ra, the Sun

God, is clearly more important than the Slaves working the fields.

The Dutch in particular are masters of their lands (God created the world, yet the Dutch created The

Netherlands – Voltaire); generations of their engineers have allowed swamps to be converted into

dry, liveable and more importantly arable land. Redirecting aqua bodies in the form of irrigation

is essential in providing the necessary water for the photosynthesis process. This is another key

component of the optimized farming techniques that can be attributed to the leap in plant

growth (yield). What started off, as those cute picturesque windmill driven channels, has quickly

become an integral part of mechanized farming. Large sprinkler systems, large dam networks,

compressors and pumps are all intertwined with an electrical energy input.

Air, in the sense of photosynthesis, is associated with supplying the necessary carbon dioxide.

Modern greenhouses even utilise the off-gases of power plants to raise the atmospheric CO2

level. Yields do indeed raise for most (all C-3 species) plants, for instance the widely popular


“Dutch waterbombs” (known on the domestic market as tomatoes). As much as the Kyoto Protocol

is trying to curb emissions of such greenhouse gases (not named for this beneficial effect), the

fractional atmospheric increase cannot be associated with any noteworthy yield increases in

outdoor cultivations.

This is as far as traditional photosynthesis (air, water, sun) optimizations can go; yet these

collective improvements cannot be solely attributed to a ten-fold increase in yield. This is where

the previously ignored biochemical pathways make a loud return. Increasing the metabolic

reaction rates (and adversely photosynthesis) is achieved by systematically applying the necessary

enzymatic and biochemical nutrients. In laymen’s terms these are referred to as fertilizers. On

fertile land, crops produce higher yields, obviously. The lack of this now common farming

knowledge, of what makes a land fertile, is probably what caused the eventual downfall of the

Mesopotamian civilization. It has been hypothesized that over-farming allowed wheat yields to

drop from 2ton/ha down to 0.8ton/ha in a matter of decades and most likely continued to drop

to critical starvation levels. Ironically the single most important nutrient, nitrogen, is abundantly

present in air, yet cannot be easily harnessed by plants. Vast amounts of energy are required to

convert atmospheric air into its useable nutrient constituent, ammonium. Similar trends hold true

for the remaining nutrients.

In fact of all the farming technique improvements, fertilizer technology, is the single most

important factor in increasing yields. As it stands today, with the available arable land and

farming techniques, the world could only sustain circa 3-4 billion human inhabitants without

artificial fertilizers. In as little as 80 years, huge production factories have been constructed

around the world converting ores, minerals, fossil fuels and other components into fertilizers. It

is estimated that more than 3% of the total global energy demand is utilized in fertilizer

production alone1. Yet, again in comparison to the energetic levels of solar radiation these levels

are also negligible. This is an additional reason supporting the choice to handle solar radiation in

land terms.

1.1 Chapter Purpose

In the following chapter all the required primary inputs will be calculated and expressed in a

comparative form for the previously selected crops. The values mentioned herein are based on a

straightforward energy/mass balance in excel and thermodynamic conversion to obtain the

exergy values. This chapter is the first of three energy inputs categories required for the creation

chemicals from biomass. Primary, secondary and process energy inputs comparison will all be

addressed independently from solar energy.


Guano (from the Quechua 'wanu') Is a collection of droppings of seabirds and bats. It can be used as an effective fertilizer due to its high levels of nitrogen. Soil that is deficient in organic matter can be made much more productive by addition of this manure. Guano consists of ammonia, along with uric, phosphoric, oxalic, and carbonic acids, as well as some earth salts and impurities. The high concentration of nitrates also made guano an important strategic commodity; in fact, the War of the Pacific between the Peru-Bolivia alliance and Chile was primarily based upon Bolivia's attempt to tax Chilean guano harvesters. Guano is harvested on various islands in the Pacific (for example the Chincha Islands and Nauru) and in other oceans (for example Juan de Nova Island). These islands have been home to mass seabird colonies for many centuries, and the guano has collected to a depth of many metres. Guano has been harvested over several centuries along the coast of Peru, where islands and rocky shores have been sheltered from humans and predators and administered by private and state companies

Source: Wikipedia.org

Fertilizer: Any of a large number of natural and synthetic materials spread on or worked into soil to increase its capacity to support plants.

2 Fertilizer Input

2.1 Preface

2.1.1 Historical Background

“The Netherlands, as any European can tell you, has

become a land of giants. In just over a century, the Dutch

have gone from being amongst the smallest people in Europe

to become the tallest in the world”2. The men now

average 182cm (18cm taller than in Van Gogh’s

day) while the women average 176cm. The start of

this continued growth spout is recorded to have

commenced around the 1840’s. Socio-economical

issues aside, there is one particular event, which

plays a decisive factor in this trend. Guano.

Beginning in the 1840’s a common load for any

European ship returning from a South American

voyage was guano. Chilean guano contained 14%

N and 14% P2O5, two of the major nutrients required for accelerated plant growth. Previously

local animal manure and crop foliage posed as the only major source to maintain field fertility. By

exploiting guano, an external source of nutrients was available providing the crops with and

resulting in an increased nutritional value of the harvest. This gave rise to the soaring heights of

the aardappeleters.

2.1.2 Industrialization

By 1875 South American sources of guano were basically exhausted, yet the benefits of applying

outside sources of nutrients remained in the minds of the agricultural sector. Other means of

producing (at the time focus was only on nitrogen) nitrate were quickly adopted but could not

maintain with the demand increase for long. In 1898, the English chemist Sir William Crookes

called out to all chemists to find a process to fix nitrogen from the air3. He urged that unless a

new nitrogen source was discovered, famine would be inevitable within several decades. In 1908,

the German professor of chemistry Fritz Haber discovered how to synthesis ammonia from air.

With the help of BASF’s German industrialist Carl Bosch, large-scale production facilities were

erected by 1917. Once the problem of supplying agriculture with enough nitrogen was overcome,

depletion of the other nutrients became apparent.

Since then a wide variety of heavy industrial processes for all the plant nutrients have been

developed and are constantly being improved. Combined they fuel the current fertilizer industry.

Manure and sewage when applied to agricultural fields are also considered as fertilizers, so those

that derive from industrial processing are now referred to as “artificial fertilizers”. The health-


crazed trend of using bio-fertilizers (i.e. manure), amongst other things, for the luxury niche

market of bio-labelled food products represents but a hairline fraction of the current total

worldwide fertilizer market. And in any case for non-food application designs, the cost of such

methods is far too high with no added benefit. The fertilizer market has within 80 years evolved

into one of the core industrial sectors. Many economists even assess the economic growth and

stability of a nation by their fertilizer use/production.

2.1.3 Best Available Techniques

Artificial fertilizers require enormous amounts of energy for a variety of processing requirements

(extraction, pumps/compressors, heat, etc.) and as a raw material source. Today the industry is as

diverse as any other. Every production plant is constructed slightly differently and designed to

produce a final product of a slightly different specification. This is on top of the already huge

array of possible raw materials sources available, all with their own process considerations.

Furthermore, the advancements of traditional processing techniques, development of new

process techniques and the revamping of older production plants are constantly redefining the

energy requirements of the industry. To make matters even more complex, there are practically

countless varieties of final fertilizer products. Each country, each agricultural region, each field,

each farmer, each crop even each season exert a preference to the exact type and form of

fertilizer to be administered. To be able to even fathom the energy input requirements of nutrient

production, a set of carefully laid out assumptions must be listed.

2.1.3.1 Assumptions

For existing commodity products, industry continually strives to maximize profits by reducing

production costs and increase production capacity. On a technological level this is obtained

through maximizing material utilization and energy efficiency. Exploiting cheap labour forces of

impoverished regions (like Poland) is another method to reduce production costs, but usually

does not reflect the newest technological practices. The best available techniques (BAT) found in

the industrial affluent regions (like Germany) reflect the newest technological practices. In 1999,

the European Fertilizer Manufacturers Association (EFMA) had prepared an 8 booklet series

outlining the BAT within the EU fertilizer industry. The IFA has also summarized the processes

in a more compact booklet4. Although they both have focused on conforming to the EU

Directive on integrated pollution prevention and control (IPPC Directive), they describe with

great detail several production options. The EFMA books highlight the industries most widely

used, accepted and technically feasible BAT production routes. Within the described processes

those that achieve the lowest possible material use and energy use will be selected. Thus the

following calculations will represent the highest energy efficiency within the BAT; that is the

European BAT. Therefore the energy/mass balance results will be quite different from world

average estimates, developed world average estimates and even BAT average estimates.

1. Highest energy efficient processes within the EU best available technology from 1999

As briefly mentioned before, there are many different fertilizers, for each region has its own

specific preferences. To conform with the purpose of primarily validating Dutch and European


biochemical production, the common fertilizer forms for those markets will be chosen. The

artificial complex fertilizer, NPK, which can be manufactured to contain all nutrients, is very

popular in Europe. In contrast straight nitrogen fertilizers, primarily urea is a widely used

fertilizer in the developing world in place of the nitrogen component in NPK. CAN, calcium

ammonium nitrite, on the other hand, is a derivative of both AN (ammonium nitrate) and NPK

that is extensively applied on European soils but barely makes it to the developing worlds fields.

2. NPK and CAN are the main artificial fertilizers of interest

NPK and CAN are, however, by far not the only artificial fertilizers on the European market.

The following process flow diagram illustrates the main production route for the most popular

forms of European fertilizers. Those appearing in bold are commonly applied as separate

fertilizers. Yet, they are all linked to the final production of NPK and CAN.

3. The NPK and CAN production route also produces individual fertilizers of interest

Ammonia

Natural Gas

Water

Air

Urea

NPKNitric Acid

Phosphate Rock

(Super Phosphorous)

Phosphoric AcidAmmoniumNitrate

(UAN)

Urea

AmmoniumNitrate

(CAN)

Calcium

AmmoniumNitrate

Sulphuric Acid Sulphur

PotashWater

Air

Dolomite

Hyd ro gen Sulphide

Air

Water

Air

Water

Micronutri ents

Ammonia

Natural Gas

Water

Air

Urea

NPKNitric Acid

Phosphate Rock

(Super Phosphorous)

Phosphoric AcidAmmoniumNitrate

(UAN)

Urea

AmmoniumNitrate

(CAN)

Calcium

AmmoniumNitrate


PotashWater

Air

Dolomite

Hyd ro gen Sulphide

Air

Water

Air

Water

Micronutri ents

Figure 1 Simplified Artificial Fertilizer Process Flow Diagram

Europe is by all means not autonomous. In regard to the above process flow diagram (Figure 1)

not all of the production routes can be and/or are located in Europe. As an example, potash used

to be big business in Europe, now mines are being phased out. In France the last mines have

already been shut down and plans are underway for the remaining mines in Germany5. In these

cases, the areas with the largest worldwide production and reserves will be chosen. To continue

with the example of potash, that implies Saskatchewan, Canada. Even when selecting a logical

region, there can be a multitude of production options. The first assumption will be extended to

these situations when applicable.

4. When little or no EU production is present then the highest energy efficient processes within the largest area

of world production and reserves will be taken instead


Many of the individual production steps contained within the entire fertilizer industry produce

off-streams (such as heat, steam, electricity, various materials, etc.). In several cases those off-

streams are identical to the input requirements of other production steps. Frequently large

production facilities are constructed manufacturing a multitude of different fertilizers, which are

primarily designed to integrate the off-streams; basically maximizing the material and energy

efficiency. In other occasions, isolated plants do not have this integration. In terms of the

following calculations it will be assumed that the whole production process could be interlinked:

5. Complete energy and material integration is possible

CAN is definitely not the cheapest way to apply the calcium nutrient to the soil. Applying straight

lime is far less expensive and energy intensive, contradicting assumption #1. It is only according

to assumption #2 and now #5 that the CAN production process has such an emphasis. The

production of NPK produces large excess amounts of calcium carbonate. CaCO3 is the main

input for CAN.

6. When NPK is produced, CAN must be produced


2.2 Nitrogen

2.2.1 Brief Description and Nutrient Importance

Air is all around us and 78.084 volume percent of it is nitrogen. With this vast abundance one

could be lead to believe that nitrogen poses no problems. Atmospheric nitrogen is present in its

diatomic virgin gas form N2, yet only the functionalised forms of nitrogen, such as

hydrides and oxides, can be utilized in the biosphere. Nitrogen gas is considered

inert, so inert that Antoine Lavoiser referred to it as azote (without life). This

inactive reactivity is due to the very high bonding energy between the triple

covalent bond, N≡N = 945.33±0.59 kJ/mol. To transform nitrogen gas into its

biosphere constituents, energy levels exceeding the triple bond enthalpy must be induced to

support functionalization. Nitrogen is indeed in abundance in the atmosphere, but is not readily

available for use in the biosphere. And the problem of availability is strictly determined by energy

accessibility.

There is a naturally occurring mineral nitrate (a functionalized nitrogen

compound) source, potassium nitrate KNO3 or better known as

saltpetre. Solid combustion will trigger the release of a large bonding

energy, for saltpetre 495 kJ/mol. This high energetic value is primarily

attributed to the functionalised nitrogen component. Saltpetre is a natural

explosive and the understanding of its thermodynamics eventually

blasted way for the synthesis of other nitrogen based chemicals. Quite literally, nitro-glycerine

and trinitrotoluene (TNT) was the dynamite that became the nitrogen-based explosive. TNT has a

heat of explosion of 616.4 kJ/mol.

Although diatomic nitrogen is labelled azote and nitrogen explosives can destroy life, nitrogen is

not only essential but also vital to all forms of life. It is the most important nutrient determining

plant growth and yield. Soils containing low levels of nitrogen are called infertile; this is not the

case with the other nutrients. Nitrogen plays such a key role because amino acids, proteins,

enzymes, chlorophyll and genetic material all contain nitrogen as a functional element. Basically

all metabolic systems are indirectly dependent and limited by nitrogen quantity. For plant uptake

and usage, at some stage diatomic nitrogen must be converted into a functionalised form. Nitrate

and ammonium are the preferred nutrient forms for root uptake. The process by which

atmospheric nitrogen gas is converted into ammonia is called nitrogen fixation. Breaking the

triple covalent bond and reacting it with a hydrogen source (water) is very energy intensive and

proves to be a major limiting factor in plant growth.

Nature is capable of fixing nitrogen in several different ways. The least common, but most

impressive in terms of shear energy intensity, is lightning. Each striking flash wields incredible

temperatures and pressures on the soil and is capable of fixing 0.14kgN on average. During


sunny days the intensity of the solar rays is also able to initiate photochemical reactions on the

topsoil. Combined they represent nearly 10% of naturally fixed nitrogen nutrients1. Many

different forms of bacteria present in the soil are able to fix nitrogen. Their source of energy is

loose organic material present in the soil; they can convert annually 2 kgN/ha. During periods of

abscission, leafs and other remaining foliage supply a recycling of nutrients for following years.

Without external nitrogen nutrient supply, the levels of further growth/yield is limited to the

small amounts of fixed nitrogen added to the soil.

There is another form of natural nitrogen fixation, a true symbiosis. Legumes are a group of plant

species, which can form a symbiotic relationship with the Rhizobium bacteria strain. As illustrated

on the adjacent photo, small nodules are formed on the roots. Most

plants store simple carbohydrates as access energy for reproduction and

transport them within their xylem vessels. The bacteria strains intercept

this source of energy to fix atmospheric nitrogen. It is a trade off for the

plant: carbon-based material (energy) for nitrogen-based material

(nutrients). Legumes will always have a relatively low overall yield as

large amounts of the simple carbohydrates were leached from the

bacteria. However, legumes are generally very high in protein content

and concentration as high levels of ammonia are present for the plant. A

clover, for example, can sustain an average uptake of 200 kgN annually6. This is a striking

contrast to natures other levels of nitrogen fixation.

Nature is able to supply itself with a certain quantity of nitrogen nutrients, but the amount

represents a mere fraction of modern fertilizer application rates. Legumes are appealing because

they reduce the need for external nitrogenous fertilizer applications, yet even under the best

growth conditions their natural fixation is insufficient to obtain good yields. Quite simply

nitrogen-based fertilizers have the largest immediate effect on crop growth, yield and quality.

This fact is best portrayed using world figures:

Worldwide (2001)7: Industrial fixation = 165Mton

Biological fixation = 100-140Mton

Today, crops obtain a larger proportion of their nitrogen-based nutrients through external

synthetic routes than natural.


Yie

ld [t/

ha

]

Nitrogen Fertilizer Applicat ion Rate [kgN/ha]

Maximum Yield

Yie

ld [t/

ha

]

Nitrogen Fertilizer Applicat ion Rate [kgN/ha]

Maximum Yield

Figure 2 Yield vs. Nitrogen Fertilizer Application Rates Trend

There is a near linear proportional yield gain due to nitrogen fertilizer applications rates.

However, the yield increases will eventually reach a maximum, the highest genetically and

environmentally possible yield. Beyond that it has been noticed that negative trends can occur.

This is most apparent with the potato, where the above graphic (Figure 2) is a reality.

The discovery of the quick and effective benefits exponentially propelled the nitrogenous

fertilizer production. The developing worlds are continually increasing their share of production,

whereas the EU (Western Europe) is capping application rates. This is noticeable in the levelling

off the growth trend in World production and the decreasing/flattening trend of the Western

European production, as seen in Figure 3.

0

25

50

75

100

1840 1860 1880 1900 1920 1940 1960 1980 2000

Year

Total [M

tN]

West Europe W orld

1840's

Beginning of guano

and nitrate shipm ents

1920

First ammonia reformer

1960's

Single-line plants

1970's

Large-scale natural gas reformers

2000's

Growth stabilization

Figure 3 Nitrogen Fertilizer Production Rates and Major Developments

Source of Data: EMFA & IFA


There are several motivations for the decrease in applications rates in Europe. Firstly, Europe is a

completely developed continent meaning food production is stabilizing, arable land allocation is

more or less set and population growth is minimal. These factors in combination with the above-

mentioned trend (Figure 2) associating nitrogen application rates have yielded an optimal

nitrogenous fertilizer usage. This however, should result in a very slight increase and not a

decreasing trend. Environmental considerations from the last several decades have resulted in a

set of strict regulations. Around 30% of global N2O emissions are from agriculture; this is

equivalent to 6% total greenhouse gases. That is a clear example of environmental pollution, but

does not influence the regulation decisions. Administering too much nitrogenous fertilizer results

in a disproportional increase of leached nitrates, which can spread to ground water and rivers (see

Chapter 6). These levels are controlled. Ground leaching has been partly remedied by the

development of better forms of nitrogen fertilizers. An additional advantage of the newer forms

of fertilizers is also a more affective uptake by the crops. Along with better farming techniques in

the sense of application timing and location a capping/decreasing trend is understandable.

Nevertheless nitrogenous fertilizers will remain the largest produced, administered and influential

nutrient for as long as it is conceivable to do so.

2.2.2 Process Choice and Description

European farmers have a full range and access to fertilizers. The distribution is relatively even

whereas, in sharp contrast, the developing world focuses mainly on urea. This is attributed to the

extreme variance of soil types, climate conditions, crop specific preferences and superior farming

techniques of Europe. The following pie chart (Figure 4) indicates the types and distribution of

the various nitrogenous fertilizers7.

NPK/NP/NK

21%

Other Complex

3%

CAN

26%

AN

22%

Urea

12%

UAN

10%

Other Straight

6%

Figure 4 Western European Nitrogen Fertilizer Distribution, 1997


All of the principle production routes will be described herein. CAN is considered a nitrogenous

fertilizer, yet it will be not mentioned until the calcium section (see Section 2.6). An entire section

will be devoted to NPK and CAN’s (see Section 2.8).

2.2.2.1 Ammonia

Every single nitrogenous fertilizer is based on ammonia. The amount of

energy and fuel (feedstock) required to produce ammonia will

consequently result in the overall energy requirements of the downstream

fertilizers. The discovery of the Haber-Bosch steam reforming process

was a great leap in reducing the energy demand. Compared to the electric arc furnace, which had

an energy consumption of 800MJ/kgN, the initial steam reformer at 100MJ/kgN was a major

improvement. Since then the Haber-Bosch process has been further improved. Figure 5

illustrates the trend of energy reduction8:

Ammonia Production

25

50

75

100

1910 1935 1960 1985 2010

Timeline [year]

Energy Consumtion [MJ/kg]

25 MJ/kg NH3

Thoeret ical Minimum

Haber-Bosch Process

Figure 5 Energy Consumption for Ammonia Production

The average European energy consumption in 2004 for ammonia was 28.8-31.5MJ/kg NH3,

depending on the feedstock. The theoretically minimum specific energy demand or specific

energy consumption (SEC) of ammonia production is 24.1 GJ/ton N (or 24.8MJ/kg NH3).

Current technology is approaching SEC values meaning any new improvements will have only a

minor effect on the overall energy demand. The BAT outlined herein comes also very close to

SEC values.

Process Choice & Argumentation

9

There are several feedstock and processing options; steam reforming light hydrocarbons

(naphtha, natural gas, liquefied petroleum) and partial oxidation of heavy fuel oil and coal. The

most energy efficient is the steam reforming of light hydrocarbons and especially natural gas.


85% of the world ammonia production is based on light hydrocarbon reforming and 90.5% of

that is based on natural gas, so the feedstock choice is easy:

�� Natural Gas Feedstock

There are three major types of reforming when dealing with natural gas: conventional reforming,

excess air reforming and autothermal reforming. The feedstock requirements are higher for the

excess air and autothermal reforming than for the conventional, yet the reverse is true for the

energy demands. The excess air reformer incorporates a much more efficient second stage

integration. Since only 30-40% of the feed is converted in the primary reformer, this makes for a

significant improvement. The autothermal goes even further, having the absolute best heat

integration. The difference in saved heating value is larger then the increase in feedstock

demands. The autothermal is also the most recently developed reforming system:

�� Autothermal Reformer Process

Process Results

For transparency the following table lists the major streams only, the material and energy streams.

Minor waste streams and process related streams have been left out intentionally. However, the

minor (trace and waste) streams were also taken in consideration for the final calculations. Refer

to the accompanying database spreadsheets for more detailed in/out flows and the calclations.

Table 1 Ammonia processing figures

Component Symbol Use Quantity Unit Exergy Content

Natural Gas CH4 Carbon Source 24.8 (0.607)

GJ (ton)

26.04GJ/ton

Natural Gas CH4 Energy Source 3.6 (0.088)

GJ (ton)

3.78GJ/ton

Water H2O Hydrogen Source 0.700 ton 0.04GJ/ton

Input

Air N2 Nitrogen Source 1.650 ton 0.03GJ/ton

Ammonia NH3 Intermediate 1 ton 19.84GJ/ton Output

Carbon Dioxide CO2 Intermediate 1.290 ton 0.58GJ/ton

It can be seen that the material (feedstock) use of natural gas greatly exceeds that of the energy

(fuel) requirements. Yet, because natural gas is a primary energy source, values are better left

expressed in energetic terms:

�� Total process energy: 28.4 GJ/ton NH3

Exery Input: 29.96GJ/tonNH3 Exery Output: 20.42GJ/tonNH3

�� Exergetic efficiency: 68.2% The large amounts of carbon dioxide are used in connected downstream processes (urea and

NPK) and not simply vented into the atmosphere. Justifying the inclusion of the exergetic value

as an output, for typically the waste and side streams are not included as an output, i.e. losses.


2.2.2.2 Nitric Acid

Manufacturing of synthetic ammonia is only half the story behind the

industries mass-producing artificial fertilizers and explosives; nitric acid is

the second half. Also discovered and invented by a German, in 1917

Wilhelm Ostwald had designed the industrial process for manufacturing

nitric acid that would later be named after him, the Ostwald process. Nitric

acid is a strong organic acid. It is useful as an oxidizing agent to yield

nitrates (fertilizers and explosives), digestion of mineral ores (in particular those associated to the

complex fertilizer NPK) and for other industrial organic chemical production (adipic acid). A

nitric acid plant is frequently coupled directly with an ammonia plant, partly because being in

liquid form at room temperature saves on storage and transportation facilities. Those coupled to

fertilizer bound ammonia production plants produce a low concentration of nitric acid, a weak

acid ranging from 30-70% weight. Nitric acid applications in other industries require higher

concentrations (above 70wt%) and thus necessitate additional production steps. These steps will

not be mentioned in this chapter, as they are not related to the fertilizer industry. All following

processes involving nitric acid are based on the 65wt% final product. The BAT outlined herein is

typical of a new 65wt% nitric acid production plant.


10

The Ostwald process is a rather simple two-step oxidation process. By reacting ammonia with air,

nitric oxide is created. A further oxidation reaction will yield nitrogen dioxide and when absorbed

in water a solution of nitric acid is obtained. The efficiencies of the two steps are however

favoured by contradicting pressures; the first (oxidation) prefers low pressure (below 1.7 bar)

whilst the second (absorption) high (above 13 bar). This had allowed for a variation of pressure

combinations within two main classifications, dual pressure and single pressure plants (original

Ostwald process). Better process control and design has made the single pressure system

obsolete. All new plants are built following the dual pressure system.

�� Dual pressure process

There are two dual pressure configurations, low/medium and medium/high pressure. The latter

has the disadvantage that the nitric oxide yield is 1% lower, from 97 to 96%, yet has the

advantage that the secondary reaction at high pressure is greatly favoured. Since additional

material, air and water, have been added to the second reaction stream, slight yield gains and

better energy integration in the second stage outweighs the yield loss of the first reaction. This is

in addition to the fact that the most recent plants are all based on the medium/high pressure

configuration.

�� Medium/high pressure

Process Results

Just as with ammonia, minor waste streams and process related streams have been left out

intentionally. The following table corresponds to a nitric acid concentration of 65wt%.


Table 2 Nitric acid processing figures


Ammonia NH3 Oxidation 0.277 ton 5.50GJ/ton Air O2 Oxygen Source 1.324 ton 0.16GJ/ton Water H2O Hydrogen Source 0.186 ton 0.03GJ/ton

Input

Water H2O Dilution to 65% 0.536 ton 0.01GJ/ton

Output Nitric Acid HNO3 Intermediate 1 ton 0.69GJ/ton

A modern nitric acid plant is essential energy neutral. The excess heat created by the exothermic

reactions is used to generate steam and drive gas turbines necessary to cover the compressor and

electrical pump duties. Conversely oxidizing ammonia greatly degrades the exergy content.

�� Total process energy: neutral Exery Input: 5.87GJ/tonNNO3 Exery Output: 0.69GJ/tonNNO3

�� Exergetic efficiency: 11.8%

2.2.2.3 Ammonium Nitrate

AN is a high-nitrogen, high-oxidative derivative of both ammonia and

nitric acid. It is primarily used as a fertilizer (in its virgin state and as

an intermediate), yet due to the high-energy bonds it is also commonly

connected with the explosives industry. In order to alleviate the need

for farmers to undertake a course in explosives handling, the final

manufacturing process of the two main applications are different. Fertilizer-grade ammonium

nitrate (FGAN) is in a compact form with a low porosity, in order to achieve more stability and

less sensitivity to detonation. On the other hand technical grade ammonium nitrate (TGAN)

granules are louse and porous for better absorption of fuel and exert high reactivity. This

difference does not completely prevent the explosive nature of FGAN, for as recently as

September 21st, 2001 a fertilizer factory in Toulouse, France, was the centre of a disastrous

spectacle11. The huge explosion has been attributed to a warehouse storing large quantities of off-

specification granular AN. Even though it seems apparent that large amounts of energy are

released from the molecule the production, on the contrary, is exothermic. The BAT outlined

herein is typical for a modern AN production plant left in its melt form to be used as an

intermediate:


12

The exact process route of manufacturing ammonium nitrate is undefined as there are many

explicit end-product specifications. Considerations for production layout are thus greatly

influenced by the final product choice. As ammonium nitrate can be used as an intermediate or

as a final product, this option will have the biggest influence on processing design. As described

in the assumptions section (see Section 2.1.3.1) those final products highlighted in bold will be

used to calculating final production requirements. AN is thus an intermediate, as is urea, to

produce UAN. Both urea and AN when used as virgin fertilizers are converted into their solid


constituents typically through a granulation or less commonly prilling step. This adds a significant

amount of extra process energy, primary by the air circulation fan. There are two possible

feedstock states for UAN manufacturing, solid and liquid, so by leaving AN and urea in their

respective melt/liquid state a great deal of process energy is saved.

�� Solidification processing is not included

The first step of the process is neutralization and in Europe alone there are at least 10 different

configurations. By inducing an elevated pressure, the resulting steam is at a higher temperature

and can fully cover the steam requirements of the subsequent evaporation stage while producing

a sizeable amount of low-pressure steam for export.

�� High-pressure neutralization with excess steam production

Since the process information listed in the EFMA booklets includes the solidification options

another source was taken. The ThyssenKrupp Uhde process data for the above mentioned route

was taken instead as it lists the steps leading up to solidification13.

�� Uhde specific process

Process Results

Table 3 lists only the major streams.

Table 3 Ammonium nitrate (AN) processing figures


Ammonia NH3 Oxidation 0.213 ton 4.23GJ/ton Nitric Acid (65%) HNO3 Reduction 1.700 ton 1.17GJ/ton

Steam (10bar) H2O Heating/Synthesis 0.052 (0.179)

ton (GJ)

0.04GJ/ton Input

Electricity kWh Utilities 4.8 (0.017)

kWh (GJ)

0.02GJ/ton

Output Ammonium Nitrate NH4NO3 Intermediate 1 ton 3.68GJ/ton

Steam (4.5bar) H2O Power/Heat 0.240 (0.770)

ton (GJ)

0.17GJ/ton

Water H2O Excess 0.911 ton 0.05GJ/ton The excess water can be integrated in other processes so is not a waste stream

Since the solidification step is not included the overall energy requirements are negative, meaning

an excess of energy has been produced. The neutralisation step is in fact an exothermic reaction,

yet normally the high solidification energy requirements shadow this gain in steam. The electrical

utilities demand is relatively low because the generated low-pressure steam is integrated in the

down-stream steps; the excess is (or could be) exported.

�� Total process energy: -0.574GJ/ton NH4NO3 Exery Input: 5.48GJ/tonNH4NO3 Exery Output: 3.90GJ/tonNH4NO3



2.2.2.4 Urea

Chemicals found in the excreted liquid streams of vagrant drunken

individuals are known to decimate public buildings, in particular stone

churches. Yet, when the same waste streams are introduced into the

biosphere, positive affects can be observed such as accelerated plant

growth. The key to this phenomenon is the word urine. The liver

produces urea and supplies the kidneys with this metabolic agent necessary to flush waste

molecules from the body. This high concentration of urea is the origin of the word urine.

Perhaps trees will once again become the main outdoor urinal facilities? In fact probably not, as

many other waste products are contained alongside urea, which may have detrimental effects on

plant life. Pure urea, however, is currently the world’s most popular form of nitrogenous

fertilizer. The methods and materials have changed a lot since the German chemist Friedrich

Wöhler first synthesized urea from inorganic molecules in 1828. That discovery is even attributed

to launching the separate discipline of organic chemistry and today the materials used for the

synthesis are even organic. In reality urea is simply a further reaction step added to the existing

ammonia production. The ammonia by-product carbon dioxide is reintroduced to the system to

yield ammonium carbonate, which is subsequently dewatered to form urea. Market deliverable

urea is sold in its solid concentrated form, which (in the case of urea) is much more affective at

providing nutrients and has less associated leaching problems than the natural liquid product.

However, as mentioned above, urea will be left in its liquid form to be used as an intermediate in

the UAN production. The BAT outlined herein is typical for a modern urea production plant left

in its melt form:


14

Producing ammonium carbonate is an exothermic reaction, which goes to completion. The

following endothermic dewatering reaction is slow and does not go to completion. The

conversion rate is in the order of 50-80%. Increasing the material utilization stream requires a

recycling stream. What started as a partial recycle system has, through a network of loops,

become a total recycle process. The first option of processing is the choice of stripping agent,

ammonia or carbon dioxide. Of the four available layouts, the two newer and most energy

efficient processes utilize carbon dioxide as a stripping agent.

�� CO2 as stripping agent

The carbon dioxide stripping process has been further improved, implementing the maximum

amount of material and energy utilization to the point of classifying it as a separate production

layout. The advanced cost & energy (ACES) process employs a serious of strippers and

condensers to minimize the steam and electrical requirements.

�� ACES process

As with the AN production, the solidification step is not present, leaving the solution in its melt

form, saving on energy requirements.

�� Solidification processing is not included


Process Results


Table 4 Urea processing figures


Ammonia NH3 Nitrogen Source 0.570 ton 11.3GJ/ton Carbon Dioxide CO2 Carbon Source 0.740 ton 0.33GJ/ton

Steam (98bar) H2O Heating/Synthesis 0.700 (2.905)

ton (GJ)

0.74GJ/ton Input

Electricity kWh Utilities 0.108 GJ 0.11GJ/ton

Output Urea CO(NH2)2 Intermediate 1 ton 11.5GJ/ton

These calculations are based on a 99.7% pure melt concentration of urea, which is quite typical

for a modern plant. Large quantities of low-pressure steam are released from the primary reactor

and are integrated in the secondary dewatering process with no excess. The exergy efficiency is

quite high since synthesis steam has a very low exergy content.

�� Total process energy: 3.01 GJ/ton CO(NH2)2 Exery Input: 12.5GJ/tonNH4NO3 Exery Output: 11.5GJ/tonNH4NO3


2.2.2.5 Urea Ammonium Nitrate

Liquid (or solution) fertilizers are rapidly increasing in popularity and with it

their production capabilities. They are particularity common in North

America, while they currently represent only 12% of the European market7.

Several various types of liquid nitrogenous fertilizers exist on the market, yet

UAN dominate the sector; arguably applying an analogous connotation for

UAN with solution fertilizers. There are several strong advantages of utilizing solution-based

fertilizers over their solid-based counterpart that have prompted the production increase of

UAN. Urea ammonium nitrate comprises of just that; urea, ammonium and nitrate. Each has a

unique time specific release and uptake time period, giving the fertilizer a unique 3-phase nutrient

release property. This is very attractive for an effective nutrient management and soil/nutrient

efficiency (see Chapter 6). Being in the liquid state also allows a more uniform field distribution,

should it be separately dosed. However, it is commonly fed directly into the water supply (like

sprinkler systems and irrigation cannels) reducing the associated application costs plus adding

other side benefits (also see Chapter 6). On the manufacturing side, there is the even greater

advantage of negating the need for the energy intensive solidifying process. This is even

circumvented three times over as urea and AN are both left in their liquid melt state for UAN

intermediate handling. Liquid UAN has been chosen as the straight nitrogen fertilizer for excess

nitrogen supply simply because it has the lowest energetic production and it is foreseeable that it

will represent a larger share on the European market in the near future. The BAT outlined herein

is typical for a coupled UAN production plant:

UAN:

-CO(NH2)2

-NO3

-NH4


Process Choice & Argumentation14

Combining urea and ammonium nitrate together with water in a vessel will result in an aqueous

solution. Reaction heating energy is not necessary. The amount of water supplied determines the

overall nitrogen content of the UAN-solution and varies from production site. For instance in

Canada 28%N is typical, America prefers 32%N, where in Europe 30%N is more common.

�� Process data for 30%N

Many production sites for UAN are based on the solid feedstocks. This method requires an

additional steam-dissolving step and necessitates a batch reactor set-up. By focusing on the liquid

feedstocks the process is not only continuous but requires no addition of steam.

�� Liquid feedstocks

Process Results


Table 5 Urea-ammonium nitrate (UAN) processing figures


Urea CO(NH2)2 Nitrogen Source 0.328 ton 3.77GJ/ton Ammonium Nitrate NH4NO3 Nitrogen Source 0.426 ton 1.57GJ/ton Water H2O Dilution 0.245 ton 0.01GJ/ton Input

Electricity kWh Utilities 10 (0.036)

kWh (GJ)

0.04GJ/ton

Output Urea-Ammonium Nitrate UAN Fertilizer 1 ton 5.35GJ/ton

These calculations are based on a 30%N concentration of UAN, which is quite typical for a

modern European plant. The process is a straightforward mixing procedure requiring only the

relatively low associated electrical utilities.

�� Total process energy: 0.036 GJ/ton UAN Exery Input: 5.39GJ/tonUAN Exery Output: 5.35GJ/tonUAN


2.2.3 Energetic Result

Presenting the input in terms of process specific energy demands can be slightly ambiguous, as

they must be coupled with the previous energy requirements of the relative feedstock. The typical

production route for steam and electricity originating from fossil fuels (as specified in Chapter 2)

are included to calculate their cumulative values. By incorporating the feedstock specific demands

the cumulative input is calculated. Furthermore, relating the specific compound with the nitrogen

content presents a clear indication of the actual energy requirements for the nutrient.


Ammonia

Natural Gas

Water

Air

Urea

Nitric Acid

AmmoniumNitrate

(UAN)

Urea Ammonium

Nitrate

Water

Ai r

Energy: 28.4GJ/ton

0.277 ton

0.570 ton

Energy: 0GJ/ton

0.213 ton

0.789 ton

Energy: 0.57GJ/ton

Energy: 3 .01GJ/ton

0.426 ton

0.328 ton

Energy: 0 .04GJ/ton

Water

Ammonia

Natural Gas

Water

Air

Urea

Nitric Acid

AmmoniumNitrate

(UAN)

Urea Ammonium

Nitrate

Water

Ai r

Energy: 28.4GJ/ton

0.277 ton

0.570 ton

Energy: 0GJ/ton

0.213 ton

0.789 ton

Energy: 0.57GJ/ton

Energy: 3 .01GJ/ton

0.426 ton

0.328 ton

Energy: 0 .04GJ/ton

Water

Figure 6 Nitrogenous fertilizer simplified mass/energy balance flow diagram

Listed in Table 6 are the conversion factors of the nutrient content in the fertilizers

Table 6 Nutrient Conversion Factors in w/w

The nutrient conversion factors are based on the ratio between the core elements in the molecule. For example: H3PO4� P2O5 (P is the core element) H3PO4 = 3⋅1.00974 + 1⋅30.97376 + 4⋅15.9994 = 97.99518 (31.61%P) P2O5: 2⋅30.97376 + 5⋅15.9994 = 141.9445 (43.64%P) � H3PO4/P2O5: 31.61%P/43.64%P = 0.724 � P2O5/H3PO4: 43.64%P/31.61%P = 1.381

NH3 � N 0.822 N � NH3 1.216 HNO3 � N 0.222 N � HNO3 4.499 HNO3 (65%) � N 0.145 N � HNO3 (65%) 6.921

NH4NO3 � N 0.350 N � NH4NO3 2.857 CO(NH2)2 � N 0.466 N � CO(NH2)2 2.144

UAN � N 0.300 N � UAN 3.333 S � SO3 2.497 SO3 � S 0.401

H2SO4 � SO3 0.816 SO3 � H2SO4 1.225 H2SO4 (78%) � SO3 0.636 SO3 � H2SO4 (78%) 1.571

P � P2O5 2.291 P2O5 � P 0.436 Ca3(PO4)2 � P2O5 0.458 P2O5 � Ca3(PO4)2 2.185

H3PO4 � P2O5 0.724 P2O5 � H3PO4 1.381 H3PO4 (52%) � P2O5 0.376 P2O5� H3PO4 (52%) 2.656

KCl � K2O 0.631 K2O � KCl 1.583

CaCO3 � CaO 0.400 CaO � CaCO3 2.497

MgCO3 � MgO 0.321 MgO � MgCO3 3.118


Table 7 Resulting energy requirements for nitrogenous fertilizers

Process Energy Cumulative Energy Nitrogen Content Relative Nutrient Energy

Compound GJ/ton GJ/ton % GJ/tonN

Ammonia 28.4 28.4 82.2 34.5 Nitric Acid (65%) 0 7.9 14.5 54.5 Ammonium Nitrate (melt)*

-0.57 19.1 35.0 54.6

Urea (melt)*

3.01 19.8 46.6 42.5

Urea-Ammonium Nitrate

0.04 14.7 30.0 49.0

*The results are not representative of the direct fertilizer application as those production processes were left in liquid phase for use as intermediates. For direct fertilizer use a granulation/prilling process is necessary which requires 25-60kWh electricity and ~50kg steam extra.

Table 8 Resulting exergy requirements for nitrogenous fertilizers

Input Exergy Cumulative Exergy Nitrogen Content Relative Nutrient Exergy

Compound GJ/ton GJ/ton % GJ/tonN

Ammonia 29.96 30.0 82.2 36.5 Nitric Acid 5.87 8.7 14.5 60.0 Ammonium Nitrate (melt)*

5.48 21.1 35.0 60.3

Urea (melt)*

12.5 18.9 46.6 40.6

Urea-Ammonium Nitrate

5.39 15.3 30.0 50.2

As mentioned these figures represent the most energy efficient choice amongst the best available

technology (BAT) in Europe as of 2002. They are in significantly lower then the commonly

available technology of America from 198215. For example, ammonia is listed as 55GJ/tonN or

33.6% more energy intensive. Seeing that ammonia is the base of all subsequent nitrogenous

fertilizers, the rest will approach similar differences. Urea presents the largest variance being

listed at 70GJ/tonN or 42% more energy intensive. A select choice within the most recent BAT

figures can provide a better indication of the energy requirements for the near future.


2.3 Sulphur


Sulphur is the 13th most abundant element in the

earth’s crust and it is possible to find native sulphur in

its pure elemental form as well as in its simple oxidized

forms like sulphite and sulphate. These sources are

however very scarce or isolated to potentially

hazardous regions. Investing in extraction practices

along side an active volcano may not go over well with

workers and deep mine exploration may proof to

cause a heated affair with unions. In fact, sulphur has

long been associated with volcanic activity and was

first referred to as brimstone, or as “the fuel of hell” in biblical terms. Yet sulphur is not a

scarcity but a commodity, meaning human capabilities are not pushed to the limit.

There are indeed a variety of sulphur sources, all of which share one common attribute; sulphur

is considered as the by-product and occasionally even as the waste stream. This is how abundant

sulphur is. Natural sulphides are most commonly contained in metal ores and are regarded as an

impurity in metal production. Iron ore in particular has a high concentration of sulphur in the

range of 28-32% and is sometimes referred to as sulphur ore. Iron disulfide, FeS2, is called pyrite,

the so-called fool's gold. Striking pyrites upon steel will release a spark and explains why the

Greek word for fire was taken for the ore. Sulphur therefore contains an oxidizing potential

which when combusted can release heat and light (energy). 592,2 kJ/mol is released when

burning pure solid sulphur, which is close to TNT. Sulphur is a key component of gunpowder

and fireworks.

Combusting sulphur for energy production is a very undesirable process as the resulting SOx is

responsible for photochemical smog and acid rain. Besides, sulphur has a vast diversity of

industrial applications and derivatives meaning burning it would make no economical sense.

Fossil fuels also contain large quantities of sulphur, yet

unlike their mineral ore counterparts are present as

hydrogen sulphide. In the last 30 years great lengths have

gone into processes to reduce the sulphur content of

fossil fuels and the SOx of exhaust gases. Transport fuels

above all, employ modern absorption technology to

remove large levels of H2S. Several government bodies

have introduced clean air policies to further reduce the

sulphur content. European Union environmental

regulations are especially stringent having reduced the Shell-Vol kswagen Transport F uel Development Predicti on

In proper British English (as in the rest of

the commonwealth) the element S is spelt S-U-L-P-H-U-R, whereas American

English has opted for S-U-L-F-U-R. In 1990 the IUPAC announced that it has jurisdiction over the English language and

adopted the spelling “sulfur” to be the international norm. However, the IFA and

EFMA both continue to use the British spelling.

As the context of this report is towards fertilizer production “sulphur” will be used.


sulphur content from more than 3000ppm before 1996 to 50ppm by 2005 and are granting

financial incentives to promote a reduction below 10ppm. Certain EU countries are already

transitioning towards the 10ppm limit. The above graph estimates that in less than 10 years all

transport fuels will contain less than 10ppm sulphur. This has two major consequences.

There are three ways in which crop life can utilize sulphur as a nutrient. First, the weathering of

metallic ores will wash sulphate anion (SO4-2) in the soil. This form is free (or mobile) in the soil

and is very susceptible to leaching. The second and third are from the atmosphere with different

mechanisms and represent the vast majority. Leaves are able to directly absorb SO2 from the air

and the roots are able to directly absorb the SO3 constituent from acid rain. These sources are

directly related to the emissions of industry and the transport sector. Until relatively recent times,

agricultural soils have received sufficient sulphur from the deposition in air and rain from such

sources. Now due to the reduction in SOx emissions, sulphur deficiencies are becoming apparent

for the first time since the industrial revolution16. Plus the shift away from ammonia-sulphate

fertilizers towards other nitrogenous fertilizers is also contributing to lower sulphur levels.

Previously little attention was paid to the issue of sulphur; it was free, abundant and in the air.

The first consequence of the sulphur politics in fossil fuels is becoming visible and attention has

been directed towards the effects exerted by sulphur on plant life. It is essential for enzyme and

vitamin production, nodule growth in legumes and for chlorophyll formation. Three amino acids

(cystine, cysteine and methionine) also contain sulphur. As mentioned above sulfates are mobile

and prone to heavy losses though volatization, immobilization and leaching (mentioned further

in Chapter 6). Despite this, natural sulphur deficiencies are mainly isolated to dry sands. Artificial

sulphur nutrient application rates already represent roughly 10% that of the nitrogenous

fertilizers. It is already being considered as the 4th macronutrient and regarded as a primary

nutrient even though it is a secondary nutrient17. This fact is best portrayed using world figures: Worldwide (2002)7: Total production = 59Mton

Phosphoric acid production (e.g. NPK) = 27Mton

Sulphur containing fertilizers = 10Mton

Worldwide sulphur reserves are very plentiful and even the economically feasible reserves are

abundant. And as policies regarding the sulphur concentrations in fossil fuels further push the

envelope, even more sulphur will become available. Desulphurisation implementation for crude

oil and natural gas are already so common that only about 5% of elemental sulphur is harnessed

from mining operations18. There is so much sulphur being removed from these fossil fuel sources

that sulphur production is exceeding the demand and is for a large part heavily stockpiled. This is

supplying the sulphur industry. So, the second consequence of the sulphur politics is that prices

are cheap but unstable and start to further spread the notion that sulphur is exceedingly cheap or

even a free resource.


However, it is incorrect to consider the sulphur content of crude oil or natural gas as energy free.

When left in the fuel it would have (although reduced the energetic density) increased the overall

calorific value. Isolating hydrogen sulphide for combustion will release a large quantity of energy.

The overall heat of combustion for hydrogen sulphide is 33.0GJ/ton19. In the article “energetic

and exergetic life cycle analysis to explain the hidden costs of current sulphur utilisation” the

feedstock cost of sulphur was systematically investigated, calculated and assigned: 25.2GJ/ton

energy and 20.9GJ/ton exergy20. This presents large influence on the remaining fertilizers.


Sulphur itself is can be used as a virgin fertilizer when prilled but is primarily altered to a sulphate

(SO3) to be taken up by the root systems of crops. Sulphuric acid (H2SO3) is the preferred form.

The majority of the sulphuric acid in the fertilizer industry is used to decompose phosphorous

rock, which when incorporated in the NPK production also yields sulphur nutrients. The

production of sulphuric acid will be based on the liquid sulphur from fossil fuel desulphurisation

and used as a virgin fertilizer and as an intermediate and dissolving agent for NPK production.

2.3.2.1 Hydrogen Sulphide - Sulphur

Today, 98% of the worlds sulphur production is supplied by recovery

methods and are for a large part associated with fossil fuel desulphurisation21.

Of which 25% of worldwide elemental sulphur originates from the

desulphurisation of fossil fuels. It is even more than 63% of the U.S. (1989)

and 38.6% of the EU30 (2002) production21. Although by-products from metallic ores still

constitute the single largest source of sulphur production, its market share is falling, as recovered

sulphur from fossil fuels is continuing to rise. Natural gas can contain up to 28% (volume) of

H2S and must be removed before consumption (theoretically an ammonia plant could be coupled

with a sulphuric acid plant, for optimal process integration). The same holds true for crude oil,

yet the concentrations are significantly lower, typically between 2 – 5%. Removal of hydrogen

sulphide is preformed using an amine extraction absorption system. The residual stream, called

acid gas, also contains small amounts of carbon dioxide. In 1883, the German Carl Friedrich

Claus patented the first catalytic oxidation process to convert hydrogen sulphide (acid gas) into

liquid sulphur. Approximately 90% of all recovered sulphur is produced using the Claus process.

Many improvements have been implemented in the last century, especially in catalyst technology.

Current designs can utilize a great share of the heat energy and have a near complete material

yield conversion. The BAT outlined herein represents the newest desulphurisation process:


22, 23

In the original Claus layout, which is still common, the acid gas is sent directly to a series of

catalytic reactors. In newer designs, more energy efficient, the acid gas is first introduced into a

free flame reactor. About 1/3 of the H2S is combusted into sulphur dioxide. In the most modern

heat integration systems, about 80% of that heat energy is converted into high-pressure steam.

�� Flame reactor with 80% heat conversion to HP steam


The remaining (unreacted) H2S is converted in a series of catalytic reactors to sulphur using the

SO2 from the burner. Several different alterations to the process have been developed for this

step. Normally a single pass through a catalytic reactor will not go to completion, as the reaction

is an equilibrium chemical reaction. By condensing the stream the sulphur component is liquefied

and can be separated from the gases. The reaction is exothermic and the released heat is used to

generate low-pressure steam. The vast majority of the LP-steam is required to re-heat the

condensed stream back to reaction temperatures. A moderate amount is exported. Typically the

overall recovery is between 95 and 97%, depending on the system. However, Jacobs Comprimo

of The Netherlands has developed a system with a material conversion rate of 99.5 – 99.7%. This

system incorporates 4 stages and has been patented as the Euroclaus system.

�� Euroclaus process with LP steam

The high sulphur yield also greatly lowers the emission of SOx in the residual stream and reduces

the costs related to tail gas purification. The tail gas is treated to reconvert all sulphur-containing

products back into hydrogen sulphur to be reintroduced in the acid gas stream. The heat energy

required to run the process is also supplied by the LP-stream from the catalytic reactors.

Process Results

Table 9 Liquid sulphur processing figures


Hydrogen Sulphide H2S Sulphur Source 1.066 (26.9)

ton (GJ)

22.24GJ/ton

Air O2 Oxidation Source 2.162 ton 0.268GJ/ton Input


kWh (GJ)

0.19GJ/ton

Sulphur S2 Intermediate 1 ton 19.01GJ/ton

Steam (8bar) H2O Export (Excess) 0.370 (1.30)

ton (GJ)

0.29GJ/ton Output

Steam (40bar) H2O Export, Power 2.23 (8.70)

ton (GJ)

2.24GJ/ton

Several calculations and assumptions must be made to determine the steam energy levels: The amount of energy transferred into the HP-steam can be calculated. The heat of combustion is known, the hydrogen sulphide mass flow is known and the energy efficiency is known:

EHP-steam = -33.0GJ/tonH2S ⋅ 1.066tonH2S/tonS2 ⋅ 1/3 ⋅ 80% = 8.70GJ/tonS2 By setting the pressure of the HP-steam at 40bar, the amount of steam can be calculated:

MHP-steam = 2.23ton It is known that a total of 2.6ton of steam is produced using the Claus process. The difference between this value and the calculated HP-steam is the excess LP-steam:

MLP-steam = 0.37ton By setting the pressure of the LP-steam at 8bar, the energy contained in the steam can be calculated:

ELP-steam = 1.30GJ/ tonS2


The calculations are based on 1 ton of liquid sulphur (160°C, 16bar), which is a diatomic molecule. For sulphur as an element (S) the figures identical.

�� Total process energy: 17.28GJ/ton S2 Exery Input: 22.70GJ/tonS Exery Output: 21.54GJ/tonS


The exergy efficiency appears high only because the feedstock exergy input is set at 20.9GJ/ton;

pure hydrogen sulphide burning yields a lower efficiency.

2.3.2.2 Sulphuric Acid

Sulphuric acid has many applications; it is included in many chemical reactions

and production processes. It is the most widely used and single most produced

industrial chemical in the world. In fact, sulphuric acid is so extensively exploited

that its consumption rate, like steel production or electric power, can be used to

indicate a nation’s prosperity. Principal applications include chemical synthesis,

wastewater processing, oil refining, ore processing and of course fertilizer

manufacturing. The fertilizer sector is the largest area of practice amounting to more than 70% of

the total market7. It is primarily used for the processing of phosphorous rock to make phosphate

fertilizers, so a large portion of ore processing is related to the fertilizer industry. Virgin sulphuric

acid can also be applied in the agricultural sector without being per se a fertilizer. As a strong acid

is it frequently employed as a soil neutralizer and pH adjuster, while supplying the soil with the

necessary sulphur nutrients. The sulphuric acid industry has reached maturity and little room for

improvements is foreseeable. The BAT outlined herein represents the standard technology from

liquid sulphur:


24

Being such a large industry there is of course a large diversity of sulphuric acid production

processes, yet the main stipulation is the feedstock choice. Typical sources of sulphur (or SO2)

are from pyrite burning, sulphide roasting, metal sulphate roasting, sulphuric acid regeneration,

combustion of hydrogen sulphide containing gases and pure sulphur burning. For each of the

processes the layouts differ immensely, however for sulphur burning the options are limited.

There are only two options, single or double absorption. Double absorption is with out a doubt

the most energy and material efficient; the conversion rate is increased from 97.5 – 98.5% to

99.6% and along with it the energy generation.

�� Double catalysis based on sulphur burning

The production of sulphuric acid is a very exothermic process and many energy-harnessing

methods have been implemented. Steam is typically generated at varying pressure to be

implemented within the process; excess steam however is frequently set at 11-bar to be used in a

steam turbine. The listed net energy values are listed for energy content, in this case the steam.

�� Excess energy in terms of 11-bar steam


Process Results

Table 10 Sulphuric acid processing figures


Sulphur S2 Sulphur Source 0.327 ton 6.83GJ/ton Air O2 Oxidation Source 7.795 ton 0.97GJ/ton Water H2O Hydrogen Source 0.555 ton 0.03GJ/ton

Input

Water H2O Dilution Source 1.190 ton 0.06GJ/ton

Sulphuric Acid H2SO4 Intermediate 2.19 ton 3.66GJ/ton Output

Steam (11bar) H2O Export (Excess) 0.720 (2.50)

ton (GJ)

0.60GJ/ton

The mass balances are based on 1ton of 100% sulphuric acid concentration; the water stream is

added to bring it to its final 78% concentration causing a mass dilution of 45.6%.

�� Total process energy: -1.15 GJ/ton H2SO4 (78%) Exery Input: 7.89GJ/ton H2SO4 (100%) Exery Output: 4.26GJ/ton H2SO4 (100%)



As with the nitrogen section, by incorporating the feedstock specific energy demands (H2S) the

cumulative energy input is calculated. In the case of the nutrient sulphur, the element S is not the

nutritional indication figure. The industry prefers sulphate (SO3) as this is related to the form

taken up by the rooting system of the crop; so all energy production figures will be calculated for

the relative SO3 content.


Hydrogen Sulphide

Air

Water

Air

Energy: 17.28GJ/ton

0.327 ton

Energy: 1.15GJ/ton


Hydrogen Sulphide

Air

Water

Air

Energy: 17.28GJ/ton

0.327 ton

Energy: 1.15GJ/ton

Figure 7 Sulphur fertilizer simplified mass/energy balance flow diagram

Table 11 Resulting energy requirements for sulphur fertilizers

Process Energy Cumulative Energy Sulphate Content Relative Nutrient Energy

Compound GJ/ton GJ/ton % GJ/tonSO3

Sulphur 17.28 17.51 250 7.00 Sulphuric Acid -1.15 1.44 63.6* 2.27

*Dilution to 78%H2SO4


Table 12 Resulting exergy requirements for sulphur fertilizers

Input Exergy Cumulative Exergy Sulphate Content Relative Nutrient Exergy

Compound GJ/ton GJ/ton % GJ/tonSO3

Sulphur 22.70 1.16 250 0.61 Sulphuric Acid -3.20 3.28 63.6* 5.16

*Dilution to 78%H2SO4

All articles (currently known to this author) relating fertilizer nutrients with production energy

requirements are focused solely on the macronutrients; N, P and K. It is understandable using

logic, for the primary macronutrients require large external dose rates and are energy intensive

processes. As sulphur has only recently gained attention as a plant relevant nutrient very little, if

any, data is available. The uptake levels of sulphur are relatively high (see Section 2.9). Previously

these high levels of uptake were free, being available in the atmosphere (see Section 2.3.1), now

being incorporated as an artificially produced nutrient itself, it cannot be regarded as free. These

results indicate that just about 2GJ/tonSO3 is required to manufacture the sulphur nutrient and

over 5GJ/tonSO3 in terms of exergy. The large difference in energy and exergy can be traced

back to the low exergy content in steam. Exothermic reactions used to generate steam typically

have much lower exergy efficiencies then indicated by the energy value alone. Calculating the

sulphur uptake levels as an artificial fertilizer production can provide a better indication of the

energy requirements for the near future. But assigning sulphur a feedstock cost has its greatest

influence on the following nutrient, phosphorous.


2.4 Phosphorous


Phosphorus, P, is the 11th most abundant element in the earths crust. However, unlike the other

key nutrient groups such as hydrogen and oxygen (water), nitrogen and sulphur (air), phosphorus

has no atmospheric component in the biotic cycle. It is so highly reactive that it will

spontaneously combust (i.e. without a spark) in the presence of oxygen to form oxides, typically

P4O10. Tetraphosphorus decoxide has a heat of formation of –597kJ/mol. Due to this extremely

high reaction potential, pure elemental phosphorus is not present in nature. Vast amounts of

phosphorus are nevertheless present in minerals and sediments, with apatite (Ca5(PO4)3,OH,Cl,F)

being the most common source. Compounds and molecules

containing an element phosphorus component have been labelled

with the alternative spelling, phosphorous. Since elemental

phosphorus is rare and the spelling difference is so minute, it is a

common mistake to refer to the element P with its adjectival

form of a smaller valency (i.e. reacted P). Sediment and mineral

rock (like apatite) containing P are on the other hand referred to

as phosphate rock.

Phosphate rock acquires its name from the PO4-3 (phosphate) compound contained in the rock

mineral. Mining and extraction operations for phosphate rock are enormous. It is the 4th largest

bulk mineral currently mined in the world, only slightly behind salt5. In 1999, over 144 million

tonnes were extracted. Roughly 80% of that quantity is directly utilized in the fertilizer industry

with the other 20% going to the detergent, fodder, explosives and other industries. It has become

common practice to couple a phosphate rock mining operation with a phosphorous fertilizer

plant in the form of a phosphoric acid production plant.

Typical concentration of phosphorus in topsoil, without artificial fertilizer applications, range

between 0.005 – 0.15%17. These are very low levels. Lacking an atmospheric component in the

biotic cycle exerts a slow process on nutrient regeneration. Sources of natural phosphorus

components are from the weathering of phosphate minerals and from the remains of mobile

organic species present in the soil. Yet, phosphorus is an essential component in growth and

development of plant life.

All forms of organic life require phosphates. They form the backbone of DNA and RNA, are the

main component of a cell membrane in the form of phospholipids and are used in ATP. The

high reaction speed and potential of phosphorus is exploited in the intercellular energy transfer

molecule adenosine triphosphate (ATP). Phosphorus is obviously a primary macronutrient and

its applications grew along side the development of nitrogenous fertilizers, yet most crops require

an 8:1 ratio of N to P.


Even though phosphate is present in both phosphate rock and phosphoric acid and is the only

form utilized in biology, PO4-3 it is not the form expressed by the fertilizer industry. Phosphorus

pentoxide P2O5 has been traditionally chosen. In fact, it and the combustible product P4O10 are

readily interchangeable and represent the same reaction. There is a history behind this expression

choice. In the 1880’s, basic steel production produced large amounts of by-product waste streams

called slag. Slag is the oxide of many components including phosphorus (i.e. P4O10) and for

several decades was the main supplier of the phosphorus fertilizer industry. To this day mining

operations still refer to amount or quality of phosphorus in terms of representative P2O5. All

phosphorous fertilizers are listed as the content of P2O5. In this sense the ratio of N to P2O5 is

closer to 3:1. Because the element phosphorus is not expressed as the nutrient form,

phosphorous will be used as the generic term for all phosphorus containing fertilizers.


European farmers have a full range and access to fertilizers. The following pie chart indicates the

types and distribution of the various phosphorous fertilizers7.

TSP

10%DSP

3%

Other Straight3%

NPK/NP

50%

PK

12%

DAP/MAP22%

Figure 8 Western European phosphorous fertilizer distribution, 1997

Unlike with nitrogenous fertilizers, the balance of phosphorous sources is rather uneven. In

Europe the trend is shifting towards a large portion of complex fertilizers, like NPK and NP.

Since phosphorous is produced at about a third of the level of nitrogen, the complex fertilizers

represent a larger portion of the phosphorous market. In contrast, America and other parts of

the world, application of complex fertilizers are less common, so mono- and diammonium

phosphate (MAP and DAP) represents a large portion. TSP, triple superphosphate is analogous

to phosphoric acid and represents the largest single blend application form.


2.4.2.1 Phosphate Rock

Today only a small fraction of the phosphorous fertilizers are still supplied by

the slag of the steel industry. Development of oxygen steel making in the

1960’s crippled the oxidized slag supply. Now, more than 99% originates from

phosphate rock5. Unprocessed phosphate rock still represents about 2% of

the total phosphorous fertilizers. Yet, such application methods are less

efficient at supplying the nutrient to the crops and contain a smaller

concentration of P2O5. Phosphate rock is typically extracted and treated using a beneficiation step

to increase the concentration of P2O5 for further downstream processing. The methods used in

the phosphate rock mining explorations are very dependent on rock quality, quantity, location

and depth. The BAT outlined herein represents the best-practiced technology of an easily

extractable, average quality rock source:


5, 25, 26

It is expected that even with the high production of 144Mton, there should be enough phosphate

rock to supply the agricultural sector for thousands of years. That is however not the case with all

mining operation locations, for the reserves in the USA (Florida) are expected to be depleted by

2035. The world’s largest reserves and 2nd largest production site (behind China) is located in

Morocco27. Regrettably very little detailed process information is known (or published) over the

Moroccan production site. The mining techniques and rock composition are known and are very

close to that of the Florida production site.

Table 13 Phosphate rock composition

Location P2O5 CaO SiO2 F CO2 Al2O3 Fe2O3 MgO Na2O K2O Rest/Trace

Khouribga 33.4 50.6 1.9 4.0 4.5 0.4 0.2 0.3 0.7 0.1 3.9 Florida 34.3 49.8 3.7 3.9 3.1 1.1 1.1 0.3 0.5 0.1 2.1

The two main constituents, P2O5 and CaO are both within one percent of each other meaning

such a small deviation in composition is negligible in terms of production energy. Since detailed

information is readily available for Florida from the Florida Institute of Phosphates Research,

their production figures will be used hypothetically for the Moroccan site. It can be safely

assumed that the Florida operations are more advanced and energy efficient than their Moroccan

counterparts. And as production and demand shifts towards the latter, the better production

figures can provide a good indication of near future requirements.

�� Khouribga site, Florida process figures

Both sites are based on surface opencast dragline mining operations. This is the most energy

efficient mining method, especially compared to underground mining operations employed in

other locations.

�� Surface opencast dragline

Depending on the quality of the rock one or more beneficiation steps are required to increase the

concentration of P2O5. A value of 42% is preferred. Major impurities can include organic matter,


clay, siliceous material, carbonates, iron bearing minerals and other trace elements. The Florida

site does indeed perform beneficiation steps, yet since it is coupled to a phosphoric acid plant the

duties are not directly associated to the phosphate rock alone. A calcination step, for example is

not executed, as photogypsum is produced in the down stream process. The beneficiation

process and duties included here are for both production plants.

�� Included all beneficiation step for phosphate rock processes

Data is available for a 10-year time span, from 1984 to 1994. The 10-year mean figures will be

chosen for the energy input/output values and processing streams.

�� 10-year average figures

Process Results

Table 14 Phosphate rock processing figures


P2O5 0.334 ton CaO 0.506 ton SiO2 0.019 ton F 0.040 ton CO2 0.045 ton

Phosphate Rock

Other

Phosphorus Source

0.056 ton

0.06GJ/ton*


kWh (GJ)

0.39

Input

Water H2O Various 5.678 ton 0.28

Output Phosphate Rock Ca3(PO4)2 Intermediate 1 ton 0.06 *based on Ca3(PO4)2 and 1ton extracted rock, waste streams are included in the output. In fact only 840kg Ca3(PO4)2 per ton is present

The water usage in the mining industry is notably high, however recent recycling initiatives have

reached rates above 88%, so the actual fresh water consumption is closer to 0.680ton.

�� Total process energy: 0.39 GJ/ton Ca3(PO4)2 Exery Input: 0.73GJ/ton H2SO4 (100%) Exery Output: 0.06GJ/ton H2SO4 (100%)


2.4.2.2 Phosphoric Acid

Phosphoric acid is a powerful organic growth accelerator. About 10% of the

production is provided to the detergent additive industry to manufacture

water softeners. Phosphorous compounds bind calcium and magnesium ions

present in hard water, thus softening the water. Simple aquatic life (like algae)

in the vicinity of a sewage exit pipes are known to flourish; as a direct reaction

from the phosphorus contained in the sewage water. During the past 30 years the largest

proportion of the net addition to the phosphorous fertilizer production has been in the form of

phosphoric acid based fertilizers. Now, more than two thirds of all phosphorous fertilizers are

currently based on phosphorous acid derived from phosphate rock. The industry is extremely

diversified as it needs to constantly adjust to a wide variety of rock quality, ranging from 5 – 40%

P2O5. Khouribga sediment is of a relatively high quality, meaning a better selection of processes is


possible. Nevertheless in Europe, the acidulation process with sulphuric acid is preferred. The

BAT outlined herein represents the best-practiced sulphuric acid treatment possible with the

relative phosphate rock composition:


25

There are three main types of sulphuric acid treatment; dihydrate, hemihydrate and hemihydrate

recrystallization processes. Each has their own advantages and disadvantages, yet only one, in the

sense of maximum energy and material efficiency, stands out. The key advantages of the

hemihydrate process are that it is able to use coarser rocks and produce a purer strong acid

directly. This saves on utilities for crushing and evaporation/concentration. The P2O5 yield

efficiency is 90 – 94%, which is lower than the 94 – 96% of the dihydrate, but the energy savings

greatly outweigh that slight material yield reduction.

�� Hemihydrate acidulation process Since sulphuric acid is used in very high quantities for phosphoric acid production it is becoming

standard practice to also couple those two production plants. The excess steam from the

sulphuric acid plant is, in many cases, able to cover the electric and heating requirements for the

concentration step. Seeing that the hemihydrate process produces 52%mass P2O5 directly, it does

not require additional concentration steps and can save on that steam energy. In this case, the

clear advantage of coupling the two plants is compromised.

�� No concentration step, no steam requirements

Process Results

Table 15 Phosphoric acid processing figures


Phosphate Rock Ca3(PO4)2 Phosphorus Source 2.600 ton 0.16GJ/ton Sulphuric Acid H2SO4 Reactant 3.320 ton 5.54GJ/ton

Electricity kWh Crushing, Utilities 120 (0.43)

kWh (GJ)

0.43GJ/ton Input

Water H2O Dilution 0.770 ton 0.89GJ/ton

Phosphoric Acid H3PO4 Intermediate, Fertilizer 2.656 ton 2.82GJ/ton Photogypsum CaSO4 Waste 4.800 ton 0.24GJ/ton Output

Fluosilicic Acid H2SiF6 Waste 0.020 ton 0.03GJ/ton

The mass balances are based on a 52%mass P2O5 relative concentration; 2656kg of phosphoric

acid contains 1 ton of P2O5. This is the commercial concentration for phosphoric acid for use in

downstream fertilizer production, namely NPK. Virgin phosphoric acid can also be used as a

fertilizer and is nearly identical to triple-superphosphorous (TSP).


�� Total process energy: 0.43 GJ/ton P2O5 Exery Input: 7.11GJ/ton P2O5 Exery Output: 2.82GJ/ton P2O5



Seen relatively, the extraction and processing of phosphate rock is in itself not all that

energetically demanding. However, by incorporating the cumulative energy input for sulphuric

acid (based on the feedstock specific energy demands of H2S) the resulting energy requirements

are significant. In the case of the nutrient phosphorus, the element P is not the nutritional

indication figure. The industry prefers phosphorus pentoxide (P2O5) for traditional reasons; so all

energy production figures will be calculated for the relative P2O5 content.

Figure 9 Phosphorous fertilizer simplified mass/energy balance flow diagram

Phosphate

Rock

(Super Phosphorous)

Phosphoric Acid

Sulphuric Acid

Water

Energy: 1.44GJ/ton

Energy: 0.39GJ/ton

3.320 ton

2 .60 ton

Energy: 0.43GJ/ton

Phosphate

Rock

(Super Phosphorous)

Phosphoric Acid

Sulphuric Acid

Water

Energy: 1.44GJ/ton

Energy: 0.39GJ/ton

3.320 ton

2 .60 ton

Energy: 0.43GJ/ton

Table 16 Resulting energy requirements for phosphorous fertilizers

Process Energy Cumulative Energy P2O5 Content Relative Nutrient Energy

Compound GJ/ton GJ/ton % GJ/tonP2O5

Phosphate Rock 0.38 0.86 33.4 2.57 Phosphoric Acid 0.48 3.00 37.6 7.97

Table 17 Resulting exergy requirements for phosphorous fertilizers

Input Exergy Cumulative Exergy P2O5 Content Relative Nutrient Exergy

Compound GJ/ton GJ/ton % GJ/tonP2O5

Phosphate Rock 0.73 1.14 33.4 3.41 Phosphoric Acid 7.11 6.57 37.6 17.48

In the 1987 works published by Mudahar (and sited in many others), regarding the energy

calculations for phosphorous fertilizer production the following assumption was made28: “For recovered sulfur whether energy is involved in recovering the sulfur in a saleable form is charged to the main product (natural gas or oil) so the sulfur receives zero energy charge.”

That assumption was also made in this paper (see Section 5.3.1) except that herein sulphur

received a positive energy charge based on the heat of combustion of hydrogen sulphide. This

fundamental difference in analysis results in an enormous deviation in relative nutrient energy

requirements. The straightforward mining and extraction figures, on the other hand, are


comparable, with the progression of time accountable for the reduction. In 1983, the world

average for phosphate rock was 0.963GJ/ton (or 3.01GJ/tonP2O5). Yet, following the

hemihydrate wet rock fed for phosphoric acid the total energy use is –1.20GJ/ton54%P2O5.

Included was a sulphuric acid energy use of –6.06GJ/ton P2O5. That is in stark contrast to the

+7.97GJ/ton P2O5 when incorporating fossil fuel feedstock energy costs (H2S). More than three

tons of sulphuric acid is needed to convert phosphate rock into phosphoric acid; neglecting one

aspect of its production has a significant affect on many downstream fertilizers. Following these

calculations it is striking that phosphorous fertilizers require about a third of the exergetic input

as their nitrogenous counterparts, whereas traditional calculations indicate a factor of 5 – 10 less.


2.5 Potassium


With the arrival of settlers in the New World more arable land was needed to supply the constant

influx of migrants. The fastest and most effective way of converting the dense wooded area into

agricultural land was “slash and burn” outfits. This being long before the day of environmental

concerns, the only issue was the haste removal of the ash to make the land

quickly available for farming. Through the combustion of plant matter, like

trees, potassium oxide (K2O) is formed and remains in the ash. It was found

that this water-soluble alkali could be harnessed by cooking the ash with

water in a pan or pot. They dubbed it “potash”. Potash is potassium oxide.

Until the 20th century, potash was one of the most important chemicals in the

European market, used for glassware and earthware (pottery) and to a lesser

extent fertilizer. It was not until 1807 that potassium was discovered and

isolated as a new element. In the English language its name derives from

potash, while the Germanic languages use the Arabic word for “calcined ashes” (kalium). Now

the fertilizer industry refers to all potassium containing fertilizers by the generic term potash and

refers to the nutrient level in terms of K2O.

Despite slash and burn outfits continuing in many parts of the globe, potash is no longer

supplied by the traditional source of ash. Large salt deposits based on potassium chloride, KCl,

provide the industry with the potassium nutrient. The term potash has since become ambiguous,

because potassium chloride salt mines are called potash mines and are even referred to by the

relative quantity of potassium oxide. The plants uptake of potash is in the form of potassium

ions, K+, so even the biological function is speculated by the historical application methods.

The potassium nutrient is one of the three primary macronutrients and has been added to soil

directly and indirectly since antiquity. It is required for many functions and if is often referred to

as the “regulator” in crop production. Potassium does not have one particular function in plant

growth, but works together with scores of basic functions. There are 8 major functions which it

is directly associated with: enzyme activation, efficient use of water, photosynthesis, transport of

sugars, water and nutrient movement, protein synthesis, starch formation and crop quality.

Many soils do contain large amounts of potassium, yet only 0.1 – 2% of these levels are available

for plant uptake17. Various forms of weathering (mainly that of crystalline minerals) provide

potassium to the soil, but also remove it through leaching. The natural cycle of potassium

regeneration is (like phosphorus) a very slow process, which cannot sustain large-scale

agricultural growth. High amounts of potash are thus added to the soil. 36.3Mton of K2O were

applied in the year 1998, with 4.15Mton in Europe alone7.



European farmers have a full range and access to fertilizers. The following pie chart indicates the

types and distribution of the various potassium fertilizers7.

KCl

27%

K2SO4

0% Other Straight

6%

NPK/NK

51%PK

16%

Figure 10 Western European potassium fertilizer distribution, 1997

Muriate of potash, KCl, can be added to the soil directly and represents the largest proportion of

straight potassium fertilizers. What is noticeable is that the vast majority of the potassium

production is in the form of complex fertilizers, chiefly NPK. However, in both PK and NPK,

the source of potassium is also the muriate of potash. The only problem associated with KCl, is

that some crops are particularly sensitive to high levels of chlorine and is mitigated by using the

other forms of potassium fertilizers, namely potassium sulphate. They however, represent such a

small fraction that only muriate of potash will be included in the following calculations.

2.5.2.1 Potash

In a potash mine there are many types of salts present. Isolated potassium

chloride has been called “muriate of potash” and is used for 95% in the

fertilizers industry. It is by far the cheapest and most effective form of the

potassium nutrient. Compared to the other forms of potassium fertilizers,

muriated potash has the highest plant uptake level and is no coincidence

that it has become the single largest source of the nutrient. The methods used in potash mining

explorations are very dependent on rock quality, quantity, location and depth. The BAT outlined

herein represents the figures from the largest production site with the largest reserve area:

Process Choice & Argumentation5, 29, 30

Canada currently produces one third of the total potash consumed in the world and holds the

world’s largest reserves. There is enough potash available for well over 100 years of continued


exploration. The largest company is the PotashCorp; their 11 mines together represent 23% of

the world capacity. The giant among their production is the Lanigan site, which has a production

rate of 2.34MtonK2O per year. Ore composition for this site is known.

Table 18 Lanigan potash composition

Component Percentage

Potassium Chloride (KCl) 33 Sodium Chloride (NaCl) 56 Insoluble Clay 8 Other Salts 3

�� Lanigan ore composition The Canadian Office of Energy Efficiency has composed a detailed analysis of the energy

consumption for the potash industry. The industry in itself can be broken down into two

sections, conventional and solution-based mining operations. Most mines are conventional

relying on electric operated underground cutters and diggers (shaft mining). When the ore

becomes scarce and conventional extraction too difficult, solution-based mining is employed. It

is however, about 2-3 times more energy intensive and still only represents 20% of the industry.

�� Conventional shaft mining Data is available for all the conventional potash mining/milling operations for the year 2001. The

average figures for the 8 sites will be chosen for the energy input/output values and processing

streams. There is a deviation of around 50% between the highest and lowest energy consuming

operation. The lowest energy consumption will not be chosen because the ore location, depth

and grade can even within the operational duration of one mine greatly vary.

�� 8 mine average figures

Process Results

Table 19 Potash (potassium) processing figures


KCl 0.33 ton 0.09GJ/ton NaCl 0.56 ton 0.13GJ/ton Clay 0.08 ton 0

Potash

Salts

Potassium Source

0.03 ton 0

Electricity kWh Mining, Utilities 39.6 (0.143)

kWh (GJ)

0.14GJ/ton Input

Natural Gas CH4 Energy Source 0.29 (0.007)

GJ (ton)

0.30GJ/ton

Muriated Potash KCl Intermediate 0.300 ton 0.08GJ/ton Output

Salts NaCl Waste/Table Salt 4.800 ton 0.15GJ/ton

The potassium ratio of KCl in terms of K2O is 63.1%, meaning that 330kg of muriated

potassium (excluding 30kg loss) is equivalent to 187kg of potash. All process energy and material

streams are listed above as per tonne of product (i.e. 30% of 63.1% K2O equivalent).

�� Total process energy: 1.42 GJ/ton KCl Exery Input: 2.20GJ/ton KCL


Exery Output: 0.26GJ/ton KCL



The extraction and beneficiation of potash is straightforward. Since it is a one-step process in the

chain there is no need to display flow diagram interpretation.

Table 20 Resulting energy requirements for potassium fertilizers

Process Energy Cumulative Energy K2O Content Relative Nutrient Energy

Compound GJ/ton GJ/ton % GJ/tonK2O

Potash 1.42 2.01 63.1 3.20

Table 21 Resulting exergy requirements for potassium fertilizers

Input Exergy Cumulative Exergy K2O Content Relative Nutrient Exergy

Compound GJ/ton GJ/ton % GJ/tonK2O

Potash 2.20 2.59 63.1 4.11

In 1984, the typical world potash production average was considered to be 3.80GJ/ton product

(6.40GJ/ton K2O)28. The energy requirements for North American and European mines are

noticeably lower than the world average. Yet since 1984, a production shift has focused a greater

proportion of production on the Canadian sites. Most European sites are exhausted or simply

being shutdown; France no longer mines potash and Germany is expected to cease production

by 20065. The largest stipulation in potash production and energy intensity is the ore grade, the

so-called ore/product ratio. The U.S. and Europe varies between 4 and 6, whereas the Canadian

sites have a higher grade typically ranging from 2 – 3, resulting in less energy intensity. This one

of the major factors explaining why the relative nutrient energy input argued in this case is

3.20GJ/ton K2O compared to 5.0GJ/ton K2O.


2.6 Calcium and Magnesium


2.6.1.1 Calcium

The natural occurrences of calcium are in limestone. Limestone is a

sedimentary rock composing primarily of calcite, calcium carbonate

(CaCO3). Nearly 10% of all sedimentation worldwide is limestone and

composes of 75% of the crushed rock market31. Surprisingly, calcium was

first discovered and isolated in its oxide from, CaO, better known as lime.

By carefully adding water to limestone at high temperatures the calcite can be oxidized to form

lime, dubbed as the endothermic calcination step. CaO is very reactive with water and will form

calcium hydroxide Ca(OH)2 nearly spontaneously (slaking process), rightfully granting the

alternative name of “quicklime”. In the case of fertilizer it is crushed limestone (CaCO3) that is

added to the soil but the calcium nutrient is indicated in terms of lime concentration. Although

virgin limestone (calcite) is extensively used as a building material, the ore composition is often

described as the relative CaO concentration, not only due to fertilizers but partly because slaked

lime (Ca(OH)2) is so common.

The Dutch can thank their beautiful big-teethed smiles to the vast quantities of dairy products

they consume. It is calcium that helps humans develop strong teeth and bones. Plants do not

have teeth nor bones but do require calcium nevertheless. They also do not use calcite directly,

but separate the calcium ions out of the limestone. If that were not the case, we too would eat

limestone powder in place of cheese (though a lot less tasty). In plant life, the benefits of calcium

are quite different than that of humans. The main function calcium plays in plant growth is the

development of new points of growth, like root-tips, buds, stems, etc. It also helps in the uptake

of other nutrients, primarily phosphorus and other micronutrients. For legumes it aids in the

inoculation and increases the nitrogen fixation, this can be noticeable with the relative higher

application rates of calcium for legumes17. Calcium also provides cells with elastic properties,

stimulating the elongation and multiplication of cells. Calcium is a secondary macronutrient and

plants can thank their cell develop to the vast quantities of lime they consume.

Application of lime also has another benefit not associated to any nutritional value. Calcium

products are the primary method of pH control. They are frequently added to soils to

counterbalance the acidic properties of the other nutrients. Hydrated lime (or slaked lime) has the

strongest acid neutralization potential, followed by dolomite and limestone. The course texture

also improves the structure of the soils, being the reason why the other nutrients become more

readily available.


2.6.1.2 Magnesium

The last macronutrient to be discussed is magnesium. It too, like calcium,

occurs naturally in sedimentary rock. It occurs in a magnesium containing

limestone variant called dolomite or dolostone. In dolomite, the calcium and

magnesium source are combined together forming the crystal compound

calcium magnesium carbonate, CaMg(CO3)2. In theory there should be a molar

ratio of magnesium to calcium of 1:1. Pure sources of dolomite are however

rare, more common is a sediment mixture between dolomite and limestone, commonly referred

to as dolomite limestone. A mass percentage of magnesium is in the range of 15-20% to be

classified as dolomite limestone. Plants require more calcium than magnesium; a typical molar

ratio of calcium to magnesium ions supplied by the fertilizer industry is 6:1. The ore composition

can be set based on this specification and with the knowledge that dolomite limestone contains

around 7% impurities32.

Table 22 Dolomite limestone composition

Ore Grade CaCO3 MgCO3 Trace Pure Dolomite 54.35 45.65 0 Typical Dolomite Limestone 17.5 75.5 7.0

In general magnesium has the smallest uptake figures of the macronutrients, though is fairly close

to sulphur levels and surpasses it in several crop species. Magnesium is utilized in the

photosynthesise process to harness the solar energy and along with calcium acts as a soil

neutralizer.


As with the rest of the fertilizers there are a variety of sources and options to supply the calcium

and magnesium nutrient component. Gypsum, basic slag, different grades of limestone, hydrated

lime and nature manures are common sources for calcium. Hydrated lime is especially preferred

as a neutralizing agent as opposed to strictly being for nutrient supply. The most common source

is the limestones. Dolomite limestone, magnesia, basic slag, Epsom salts and some other

magnesium solutions are common sources for magnesium. The most common however is

dolomite limestone. Since both calcium and magnesium are present and commonly applied in the

form of crushed dolomite, this will be the chosen production path for the nutrients.


2.6.2.1 Dolomite Limestone

Crushed rock, like limestone, is one of the basic raw materials used in countless

numbers of industries. The most obvious is the construction industry with cement,

building stone, plaster and mortar being directly derived from limestone. The metal

industry however, is the single largest consumer of limestone serving as a flux to

remove impurities during the refining processes. In comparison, the agricultural

industry is only a minor player, using around 1% of the total production. The

mining and beneficiation steps are for all industries the same. Limestone is actually

one of the most accessible natural resources in the world. Surface opencast mining with blasting

operations is the commonly practiced; even though several underground operations are

becoming more frequent. The BAT outlined herein represents the average figures for the entire

industry:


31

The U.S. mining industry has composed a detailed energetic analysis of the crushed rock industry

for the years 1987 to 1997 and the mining and processing sector for the year 2000. Their source

for limestone mining operations is BCS Incorporated using the SHERPA mine cost estimating model.

The hypothetical mine operates for a 10-year period; so the results are a ten year average for the

industry. The energy consumption has been broken down into each operation of the surface

mining and beneficiation step.

�� Surface limestone mining and beneficiation (2000)

Process Results

Table 23 Limestone dolomite (calcium and magnesium) processing figures


CaCO3 0.755 ton MgCO3 0.175 ton Dolomite Limestone Other

Calcium & Magnesium Source

0.070 ton 0.08GJ/ton

Diesel C16+ Mining, Utilities 0.056 (2128)

GJ (L)

0.06GJ/ton Input

Natural Gas CH4 Energy Source 0.022 (5.4E-4)

GJ (ton)

0.023GJ/ton

Calcium Carbonate CaCO3 Fertilizer 0.707 ton 0.057GJ/ton Magnesium Carbonate MgCO3 Fertilizer 0.164 ton 0.013GJ/ton Output

Losses Other Waste 0.133 ton 0.011GJ/ton

�� Total process energy: 0.078 GJ/ton dolomite CaMg(CO3)2 Exery Input: 0.18GJ/ton CaMg(CO3)2 Exery Output: 0.07GJ/ton CaMg(CO3)2




The extraction and beneficiation of dolomite limestone is straightforward. Since it is a one-step

process in the chain there is no need to display flow diagram interpretation. Calculating the

relative nutrient content is slightly more complicated since two separate nutrients are present. For

each nutrient the relative mass ratio must first be related to the cumulative energy: calcium is

81.2% and magnesium is 18.8% of the fertilizer, i.e. 6:1 Ca to Mg. The resulting relative nutrient

energy is very low for dolomite compared to any of the other macronutrients.

Table 24 Resulting energy requirements for calcium and magnesium fertilizers

Process Energy Cumulative Energy Nutrient Content Relative Nutrient Energy

Compound GJ/ton GJ/ton CaO MgO GJ/tonCaO GJ/tonMgO

Dolomite 0.078 0.078 39.6 7.8 0.160 0.187

Table 25 Resulting exergy requirements for calcium and magnesium fertilizers

Process Exergy Cumulative Exergy Nutrient Content Relative Nutrient Exergy

Compound GJ/ton GJ/ton CaO MgO GJ/tonCaO GJ/tonMgO

Dolomite 0.179 0.179 39.6 7.8 0.341 0.400

2.7 Micronutrients


Macronutrients are needed in high quantities and substantial plant growth acceleration is

observable with the application of additional fertilizers. They do not cover all the nutritional

demands of a plant, for there are many essential nutrients, which are only required in very small

quantities. Micronutrients are basically those elements that are vital for normal functionality but

are only needed in minute amounts. To give an indication of the scale between the two

classifications, the macronutrients uptake is in the several hundred kg/ha whereas the

micronutrients uptake is in the couple kg/ha range. That is practically a factor of more than a

hundred.

Essentially any element/compound that is taken up in small amounts by plant life can be

considered as a micronutrient. But despite this, there are several elements that are truly regarded

as micronutrients. They directly affect the growth and function of plant life. Iron (Fe), Copper

(Cu), Zinc (Zn), Molybdenum (Mo), Manganese (Mn), and Boron (B) are the six micronutrients.

They are all metal components of enzymes. It is sometimes disputed whether chlorine (Cl),

silicon (Si) and sodium (Na) should be included in the list, but are frequently left out.

The uptake levels of the metal ions (Cu+2, Mn+2, MoO4-2, Ni+2, Zn+2) by plants is so low that in

most cases the quantity contained in the soil (and even the regeneration speed) is sufficient to

supply the crop for decades. However, not all soils contain sufficient levels from the beginning of

industrial agricultural exploitation or for prolonged cropping. Two of the micronutrients are


notorious for being the cause of deficiencies; iron and boron. Many soils contain insufficient

levels of those two metal ions and others that can hinder the healthy growth of the crops.

The management of micronutrients is complex and difficult, due to the small quantities involved

and the similar symptoms of macronutrient deficiency. When a micronutrient is determined to be

deficient they are supplied to the soil like any other fertilizer. But since they are metal ions, it is

common practice to bind many of the nutrients with a chelating agent to form a metal complex, a

chelate. This results in a stable compound, more available to the crop without the losses

associated with the loose ions. Another difficult aspect is

the possibility of toxicity. The micronutrients are only

needed in small amounts, too high concentrations can

be just as detrimental as insufficient concentrations (see

adjust illustration.) Deficiency produces a similar trend.

The effect of proper micronutrients management is not

observed growth acceleration, but the continued healthy

growth of the crops.


The micronutrients will not be investigated individually as any deviation in the process energies

will have next to no effect on the total nutrient energy level due to the low quantities involved.

Furthermore they are all metals, meaning their origin is of a similar nature reflecting in only slight

differences in energy and material streams. It will be assumed that all micronutrients will require

equal amounts of process energy to manufacture. The assumed process steps are as follows:

• Mining of metallic ore • Beneficiation of metallic ore • Production of metal • Production of final chelate

For the mining and beneficiation of metallic ore, the previous macronutrients can be of

assistance. Sulphur, or more specifically pyrites, is a metallic ore with data available on extraction

and processing costs (7.38GJ/tonS with 0.2GJ/tonOre). Dolomite is also a type of metallic ore,

although the processing mentioned only covers extraction and crushing. Potassium is not a pure

metal per se, but an alkali metal extracted from ore by analogous methods. Comparing the three

sources can give a rough indication of energy requirements to mine and isolate metal ore:

�� Mining process energy: 0.5 GJ/ton metal ore

�� Beneficiation process energy: 3 GJ/ton metal ore

Unlike the other macronutrients, the micronutrients must be further refined into metals. The

most common metal produced worldwide is the ferrous-metal steel. There are two different

production methods for steel, blast furnace and electric arc, with independent energy demands.

Source: OSU Dept. of Horticulture. & Crop Science


The best practice average of both processes from the European steel industry can be used can

give a rough indication of BAT energy requirement to refine metals33:

�� Refining process energy: 15.5 GJ/ton metal

A typical chelator for stable complex binding is EDTA (ethylenediaminetetraacetic acid). There

are however, many other possibilities including simple salts and even water. The production

energies of course greatly differ when producing a monodentates (low) or a polydentates (high).

It is also neither necessary for all of the micronutrients to be converted into chelates nor is it

always preformed. The following process is just a very rough estimate for the average chelate

production for all the micronutrients:

�� Chelate process energy: 1 GJ/ton nutrient


The resulting process energy is an average for all micronutrients based on the above assumptions.

Table 26 Resulting energy requirements for micronutrient fertilizers


Compound GJ/ton GJ/ton % GJ/ton

Micronutrients 20.0 20.0 100 20.0

In terms of exergy, due to the typical trend of being slightly higher, a value of 25GJ/ton is set.

2.8 Complex Fertilizers


Fertilizers that contain more than one particular nutrient are called multi-nutrient fertilizers.

Dolomite limestone can be considered as a multi-nutrient fertilizer, as it contains both calcium

and magnesium. A compound fertilizer is a type of multi-nutrient fertilizer, which underwent

some chemical alteration to incorporate more than one nutrient. Physical mixing is not enough to

constitute a compound; meaning dolomite limestone is a multi-nutrient fertilizer but not a

compound fertilizer. “Complex fertilizer” is the generic term used for all multi-nutrient fertilizers

containing the primary macronutrients regardless if physical or chemically blended. In the case of

actual compound fertilizers (chemically treated), they are designed to contain at least two of the

three primary macronutrients (N, P and K) with supplementary secondary macronutrients.

Complex fertilizers are extremely popular in Europe. They account for 83% of all phosphorus,

67% of all potassium and 25% of all nitrogen consumed in the EU7. In other countries,

particularly in the developing world, complex fertilizers are not as extensively used as in Europe.

The main reason behind this trend is shear economics; it costs more money to produce complex

fertilizers then their straight versions. The advantages, balancing the increased cost, only come

into focus when combined with advanced precision farming (a term unheard of to the average

Chinese peasant farmer). Complex fertilizers maximize nutrient application, use and efficiency.

With knowledge of the exact nutrient requirements of a specific crop in a specific field, the


educated farmer can supply a complex fertilizer costume tailored to meet all its nutritional needs.

That practice has been titled “balanced fertilization”. It can greatly reduce the application costs, by

reducing the frequency and quantity. An added benefit is that the soil is less travelled on,

resulting in less soil compaction, further increasing crop yield. Complex fertilizers do cost more

money (and energy) to produce but are a more efficient form saving in downstream agriculturally

related costs (see following chapter). It is expected that complex fertilizer production will

continue to rise in Europe as in the rest of the world.


There is essentially an infinite array of possible complex

fertilizer combinations and over 200 blends exist on the EU

market alone. The most common are NPK blends containing all

three macronutrients. The number labelling of complex

fertilizers lists the content of the relevant nutrients. On the

adjust illustration a blend of 20-5-10 is indicated, meaning that it

contains 20%N, 5%P2O5 and 10%K2O in mass percentage.

There are however process limitations to the composition levels.

NPK, for example, can range between 5-24% for the individual primary micronutrients and must

contain less than 8% of the secondary macronutrients34. The process descriptions listed in the

EMFA booklets adhere to a 15-15-15 composition, the average grade. Calcium carbonate is

produced as a waste stream from NPK processing, which is the primarily CAN multi-nutrient

production ingredient.

2.8.2.1 NPK

In Europe, the secondary and micronutrients are frequently added to the NPK

production process to include all plant nutrients. The labelling is thus extended to

mention the all the contained nutrients, usually in brackets or separately listed

underneath. The BAT outlined herein represents the most energy and material

efficient process for the 15-15-15 grade NPK compound fertilizer with typical

levels of added secondary nutrients:


35, 36

The first industrial process to create a compound fertilizer was the Odda process. It is based on

the acidification of phosphate rock using nitric acid, justifying the other name it is commonly

referred to as – the nitrophosphate process. At the time of its development in 1927, it was

designed to avoid using expensive sulphuric acid. In recent times, sulphuric acid has become one

of the cheapest chemicals, negating the main advantage of the Odda process (see Section 2.3.1).

NPK fertilizers are now produced using four different methods, yet only two are for the

production of the compound NPK’s. They are the Odda process and the mixed-acid process.

The mixed acid process relies on sulphuric acid as the acidification agent to dissolve phosphate

rock. Most European NPK production sites are phasing out the Odda process in favour of the


mixed-acid production method. Both BASF and DSM, which previously employed the Odda

process, already produce NPK’s solely via the mixed-acid process. The transition is for economic

reasons. It is a more flexible process capable of handling a larger variation of material feedstocks,

i.e. lower grades.

�� Mixed-acid production route

Within the process category of the mixed-acid route there are three different approaches:

granulation with a pipe reactor, drum granulation with ammoniation and sulphuric acid process

with phosphate rock digestion. Mixed-acid routes refer to all processes not based on nitric acid

digestion. The advantages listed above are in fact related only to the sulphuric acid process with

phosphate rock digestion. The other two options require high grades of feedstocks and are not as

flexible in producing various grades of NPK. The sulphuric acid process does require the most

direct energy, but is still considered more energy and material efficient due to upstream savings.

�� Sulphuric acid process with phosphate digestion

The digestion of phosphate rock can be preformed using various grades. Two examples of 60%

and 80% water solubility were mentioned. The energy intensity of both grades is identical, but

less total material is required for the 80% water solubility.

�� 80% water solubility of phosphates

Process Results

Table 27 NPK processing figures


Phosphate rock P2O5 Phosphorus Source 0.148 ton 0.01GJ/ton Nitric Acid HNO3 Acid Digestion/Nitrogen Source 0.434 ton 0.30GJ/ton Ammonia NH3 Nitrogen Source 0.111 ton 2.20GJ/ton Phosphoric Acid H3PO4 Ammoniation 0.200 ton 0.56GJ/ton Sulphuric Acid H2SO4 Ammoniation/Sulphur Source 0.097 ton 0.16GJ/ton Potash KCl Potassium Source 0.239 ton 0.02GJ/ton Dolomite Ca, Mg Calcium & Magnesium Source 0.075 ton 0.002GJ/ton Carbon Dioxide CO2 Carbonate 0.148 ton 0.07GJ/ton


kWh (GJ)

0.18GJ/ton

Input

Steam (10bar) H2O Heating, Synthesis 0.130 (0.45)

ton (GJ)

0.11GJ/ton

N 0.150 P2O5 0.150 K2O 0.150 SO3 0.062 CaO 0.030

NPK

MgO

Fertilizer

0.006

ton 0.44GJ/ton

Calcium Carbonate CaCO3 Intermediate 0.324 ton 0.00GJ/ton Quartz Si Waste 0.010 ton 0.00GJ/ton

Output

Hydrogen Fluoride HF Waste 0.006 ton 0.02GJ/ton

Just as with the Odda process, nitric acid is still used as the phosphate rock digestion material.

Differentiation between the nitrophosphorous process and the sulphuric acid process is that the


neutralization and ammoniation agent (creating the resulting compound solution) is sulphuric

acid (along with phosphoric acid); that has the advantage of mixing all the nutrients in one

(flexible) step. For every ton of NPK produced there is 324kg of calcium carbonate produced as

a waste stream. Since it is the main feed stream for CAN, it is not a waste stream but an

intermediate stream. The following section describes the integrated CAN processing choice.

�� Total process energy: 0.63 GJ/ton NPK Exery Input: 3.62GJ/ton NPK Exery Output: 0.44GJ/ton NPK


2.8.2.2 CAN

Ammonium nitrate decomposes in temperatures above 200°C. Pure AN is

stable and will stop decomposing once the heat source is removed, but in

presence of catalysts (or other combustible materials) the reaction can become

self-sustaining (known as self-sustaining decomposition, SSD). This is a well-

known phenomenon and is responsible for loss of several cargo ships and

production facilities (see Section 2.2.2.3). Calcium ammonium nitrate (CAN) is a blend between

calcium carbonate and ammonium nitrate. The calcium carbonate acts as a filler for AN creating

a more stable fertilizer. The result still contains a relatively high nitrogen content (21-28%) and

represents 30% of free nitrogen share in European soils. With the additional benefit of

containing a calcium component, CAN acts as a nitrogenous fertilizer, calcium fertilizer and as a

soil neutralizer; basically a multi-nutrient fertilizer with soil treatment properties. In the previous

calcium section (see Section 2.6.1.1) it was mentioned that the source for calcium is (dolomite)

limestone, however in the case of process integration with NPK it is the calcium impurities

found in phosphate rock. To utilize all the calcium carbonate by-product from the NPK

production 1.6 ton of CAN must be produced. The BAT outlined herein represents the most

energy efficient process for a 20:80 blend of calcium carbonate to ammonium nitrate:


12, 13

It is also quite common for CAN to be produced from limestone sources. That feed stock source

will not be calculated because of the vast potential quantities of the NPK related CaCO3.

�� CaCO3 from NPK production

As mentioned previously it is advantageous to leave AN in its melt form when used as an

intermediate. Final CAN product requires a granulations step to solidify the blended mix. The

lowest available process requirements for the granulation steps are taken.

�� Includes solidification

CAN: -CaCO3

-NO3

-NH4


Process Results

Table 28 CAN processing figures


Calcium Carbonate CaCO3 Filler/Calcium Source 0.200 ton 0.00GJ/ton Ammonium Nitrate NH4NO3 Nitrogen Source 0.800 ton 2.94GJ/ton


kWh (GJ)

0.04GJ/ton Input

Steam (10bar) H2O Heating, Granulation 0.150 (0.52)

ton (GJ)

0.12GJ/ton

Output Calcium-Ammonium Nitrate

CAN Fertilizer 1 ton 2.95GJ/ton

The highest nitrogen content of commercially produced CAN is 28%. This 80:20 mix ratio

results in 264kg of N (or 26.4%N) and 112kg of CaO.

�� Total process energy: 0.548 GJ/ton CAN Exery Input: 3.10GJ/ton CAN Exery Output: 2.95GJ/ton CAN



Since CAN must be produced to fully integrate all streams connected to the production of NPK

the overall nutrient content must also include the amount contained in CAN. The figure below

illustrates all the connecting streams. When 1ton of NPK is produced 1.6ton of CAN is also

produced. Meaning the nutrient values correlates to the contents of 38.5%NPK and 61.5%CAN.

The resulting nutrient content is listed in the table below (Table 29) for 1ton total fertilizer

quantity. Calculating the relative nutrient energy requirement for multi-nutrient fertilizers is

complicated. The key assumptions and explanations for the distribution and association of

material and energy streams to the individual nutrients are as follows:


Table 29 NPK+CAN nutrient related energy distribution

Nutrient Stream Proportion Reasoning

100% Ammonia Production Source of Nitrogen 22% Nitric Acid Production Mainly used for digestion, yet 22%N 33% NPK Process Energy Represents 1/3 of main products 80% CAN Process Energy 80:20 ratio AN:CaCO3

Nitrogen (N)

100% AN Production Source of Nitrogen

39.5% Phosphate Rock Production Phosphorus to calcium ratio 100% Phosphoric Acid Production Source of Phosphorus 78% Nitric Acid Production Digestion agent, other 22% for N

Phosphorous (P2O5)

33% NPK Process Energy Represents 1/3 of main products

100% Potash Production Source of Potassium Potassium (K2O)

33% NPK Process Energy Represents 1/3 of main products

Sulphur (SO3) 100% Sulphuric Acid Production Source of Sulphur

60.5% Phosphate Rock Production Calcium to phosphorus ratio 54.4% Dolomite Production Calcium to magnesium ratio Calcium (CaO) 20% CAN Process Energy 80:20 ratio AN:CaCO3

Magnesium (MgO) 45.6% Dolomite Production Magnesium to calcium ratio

Ammonia

Natur al Gas

Water

Air

Nitric Acid

Wat er

Air

Energy: 28 .4GJ/t on

0.277 ton0 .111 t on

Energy: 0GJ /ton

0 .434 t on

NPK

(CAN)

CalciumAmmonium

Nitrate

M icronut rients

Phosphate Rock

(Super Phosphorous)

Phosphoric Acid

Sulphuric Acid

Water

Ene rgy: 0.39 GJ/ton

1. 205 ton

0.9 79 ton

Energy: 0.16GJ /ton

Potash

Dolomite

Sulphur

Hydro gen Sulphide

Air

Water

Air

Energy: 1 7.287GJ /ton

0.327 ton



Ammonium

Nit rate

0 .213 t on

0.789 ton

Ene rgy: 0.5 5GJ/ton

0 .324 t onCaCO3


1 .298 t on

0 .268 t on

0 .148 t on

Energy: 1 .42GJ/ ton

Energy: 0 .08GJ/ ton0 .239 t on

0 .075 t on

0.09 7 ton

Potassium Salts

Dolom ite Limest one

Ammonia

Natur al Gas

Water

Air

Nitric Acid

Wat er

Air


0.277 ton0 .111 t on

Energy: 0GJ /ton

0 .434 t on

NPK

(CAN)

CalciumAmmonium

Nitrate

M icronut rients

Phosphate Rock

(Super Phosphorous)

Phosphoric Acid

Sulphuric Acid

Water

Ene rgy: 0.39 GJ/ton

1. 205 ton

0.9 79 ton

Energy: 0.16GJ /ton

Potash

Dolomite

Sulphur

Hydro gen Sulphide

Air

Water

Air

Energy: 1 7.287GJ /ton

0.327 ton



Ammonium

Nit rate

0 .213 t on

0.789 ton

Ene rgy: 0.5 5GJ/ton

0 .324 t onCaCO3


1 .298 t on

0 .268 t on

0 .148 t on

Energy: 1 .42GJ/ ton

Energy: 0 .08GJ/ ton0 .239 t on

0 .075 t on

0.09 7 ton

Potassium Salts

Dolom ite Limest one

Figure 11 NPK+CAN fertilizer simplified mass/energy balance flow diagram

Table 30 Resulting energy requirements for NPK+CAN fertilizers



NPK 5.08 CAN 3.10

7.37* - -

N - - 22.24 50.9 P2O5 - - 5.77 25.5 K2O - - 5.77 5.1 SO3 - - 2.38 2.3 CaO - - 8.13 0.9 MgO - - 0.24 0.2

*1ton total (0.385tonNPK and 0.615tonCAN)


Table 31 Resulting exergy requirements for NPK+CAN fertilizers

Input Exergy Cumulative Exergy Nutrient Content Relative Nutrient Exergy


NPK 0.63

CAN 0.55 14.86* - -

N - - 22.24 54.0 P2O5 - - 5.77 31.6 K2O - - 5.77 6.3 SO3 - - 2.38 5.2 CaO - - 8.13 0.7 MgO - - 0.24 0.4

*1ton total (0.385tonNPK and 0.615tonCAN)

In the brief description and nutrient importance section for complex fertilizers (see Section 2.8.1) it was

stated that compound fertilizers are more expensive than straight fertilizers. From comparing the

relative nutrient energy results, that statement is debatable. On energetic terms, the compound

fertilizers actually require less and similar process energy for most of the nutrients, providing an

additional plus point for their production and exploitation. Complex fertilizers appear to be the

most energy efficient form of fertilizers, but the alleged higher cost is probably connected by

other factors such as additional investment costs. Phosphorous is the one nutrient that requires

significantly more relative energy then its straight counterpart, superphosphorous. Fully

understandable considering that nearly half a ton of nitric acid is required to digest 150kg of

phosphate rock. And by associating 78% of nitric acids production requirements to phosphorous

the resulting figure is about half that of nitrogen. Through the production of 1ton (NPK+CAN)

385kg of NPK and 615kg of CAN is produced, in which roughly 4-times more available nitrogen

is yielded than any of the other nutrients. That corresponds nicely against typical fertilizer

application trends.


2.9 Nutrient Uptake

Nutrient uptake levels are presented in terms of kg/ha to coincide with the most commonly

adopted term for the fertilizer application industry. Presenting the nutrient requirements based

on mass/area is a desirable from, but can only be compared to other crops when standardized to

a common yield. The similar problem of yield specific terminology again appears in the values

given for nutrient uptake levels. The ambiguities between dry weight, wet weight, total plant or

component specific yield reoccur. As before the values need to be adjusted to one common unit.

Generally the values were presented as kg/ha for a specific wet weight yield, considering that in

chapter 4 wet weight and dry weight absolute figures were both calculated, the nutrient uptake

levels can first easily be related to kg/tonne wet weight for the entire crop.

Several of the selected crops have a bacterial symbiotic relationship or sown together with

leguminous plant material reducing the external nitrogen nutrient demand. The crop guide lists

the inoculation strain and states the inoculation rate. The inoculation rate is essentially the

percentage of nitrogen nutrient demand covered by the nitrogen fixating bacterial strain. In many

cases it is not 100%, meaning that additional nitrogenous fertilizer must be added to satisfy the

uptake demand. The nitrogen requirement levels are adjusted to include those figures.

From the plant analysis data, for the nutrient composition, several elements are in the trace

quantity range and are unknown. As opposed to setting trace elements at zero it will be assumed

that a minimum uptake level of 0.1kg/tonWW for the macronutrients and 0.001kg/tonWW for

the micronutrient is present.

The following table illustrates the resulting uptake levels for the macro- and micronutrients in

terms of kg/tonne wet weight after all the adjustments.

Table 32 Nutrient uptake levels (kg/tonWW)

N Inoculation N P2O5 K2O CaO MgO SO3 Fe Mn B Zn Mo Cu

Common Name kg/ tonne rate

Cassava 2.9 0.00 2.9 1.1 4.4 2.5 2.0 0.2 0.015 0.018 0.003 0.011 0.001 0.001

Grass 5.2 0.59 2.1 1.4 5.3 1.5 0.6 0.4 0.018 0.028 0.001 0.007 0.001 0.001

Lucerne 10.0 0.80 2.0 2.3 9.3 4.3 1.8 0.8 0.015 0.013 0.008 0.006 0.000 0.002

Maize 2.6 0.00 2.6 1.4 4.5 0.1 1.4 0.3 0.025 0.013 0.002 0.005 0.000 0.002

Oil palm 2.7 0.00 2.7 0.9 4.5 3.1 1.4 0.0 0.007 0.002 0.003 0.002 0.002 0.003

Potato 2.7 0.00 2.7 0.8 4.5 0.2 0.3 0.4 0.018 0.018 0.002 0.004 0.001 0.002

Rapeseed 4.0 0.00 4.0 0.4 5.8 1.4 0.1 0.3 0.023 0.008 0.004 0.007 0.000 0.001

Sorghum 3.5 0.00 3.5 1.0 3.9 0.3 0.3 0.3 0.001 0.001 0.001 0.001 0.001 0.001

Soya bean 14.8 1.00 0.0 2.6 6.0 4.4 3.3 0.5 0.067 0.016 0.007 0.011 0.001 0.005

Sugar beet 2.7 0.00 2.7 1.0 3.1 1.7 0.8 0.3 0.002 0.014 0.007 0.001 0.000 0.001

Sugar cane 0.6 0.70 0.2 0.2 1.0 0.3 0.4 0.2 0.004 0.004 0.000 0.000 0.000 0.000

Sunflower 13.1 0.00 13.1 8.7 38.5 21.0 7.0 2.0 0.073 0.041 0.040 0.035 0.000 0.006

Switchgrass 22.4 0.30 15.7 5.3 36.2 5.3 4.1 2.0 0.075 0.062 0.018 0.029 0.000 0.006

Tobacco 1.5 0.00 1.5 0.3 1.2 1.4 0.3 0.2 0.002 0.008 0.001 0.001 0.000 0.000

Wheat 15.1 0.00 15.1 3.4 24.5 2.5 2.5 1.2 0.032 0.032 0.005 0.003 0.000 0.004

Willow tree 7.5 0.00 7.5 7.5 7.5 0.1 0.1 0.1 0.001 0.001 0.001 0.001 0.001 0.001

kg/tonne WW

Macronutrients MicronutrientsBacterial FixationCrop

The values highlighted in bold are supplied via artificial fertilizers, the rest (not-bold) are currently supplied by sufficient levels in the soil


Due to the great difference in macro- and micronutrient uptake levels, it is best to display the

nutrient classifications in two separate graphs and using dry weight figures as to present a more

comprehensive contrast between each crop and each nutrient.

Macronutrient Requirements

0

10

20

30

40

50

Cas

sava

Gra

ss

Luce

rne

Maize

Oi l pa

lm

Pot

ato

Rap

esee

d

Sorgh

um

Soy

a be

an

Sugar b

eet

Sug

ar can

e

Sun

flower

Switc

hgra

ss

Toba

cco

Whe

at

Willo

w tr

ee

kg/ton DW

N

P2O5

K2O

CaO

MgO

SO3

72.0

Figure 12 Macronutrient uptake levels

One would expect nitrogen to dominate the uptake figures but it is noticeable that for the

majority of crops potassium (K2O) has the highest requirements. The level 25kg/tonDW

represents 2.5% of the total crop biomass and several crops have individual nutrient

requirements approaching and exceeding 25kg/tonDW. Sunflower for example needs

72kg/tonDW of K2O, which is 7.2% of the total dry biomass. It may appear abnormally high,

but considering the high ash and protein content, it is realistic. Potassium is amongst the main

contributing minerals to the ash content. The ash composition for all crops is unique as can be

best described with the grasses. Switchgrass, lucerne and grass are particularly high containing

20.1, 17.8 and 11.4% ash respectively. It can be seen in the above graph that indeed the

potassium uptake in proportion to the other nutrients and in absolute terms is rather high for the

grasses. Potassium and the above nutrients are only one factor determine the ash levels as lucerne

in particular has SiO2 for the bulk of its ash content 37.


Figure 13 Micronutrient uptake levels

Micronutrient Requirements

0 .000

0 .025

0 .050

0 .075

0 .100

0 .125

0 .150

Cas

sava

Gra

ss

Luce

rne

Maize

Oi l pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Sugar

bee

t

Sug

ar can

e

Sun

flower

Switc

hgra

ss

Toba

cco

Whe

at

Wil lo

w tree

kg/ton DW

Fe

Mn

B

Zn

Mo

Cu

0.16

As mentioned in the micronutrient explanation (see Section 2.7.1) iron (Fe) and boron (B) are the

two micronutrients commonly prone for deficiencies. On average they along with Manganese

(Mn) do indeed have the highest uptake requirement levels of the micronutrients.

To be able to incorporate the fertilizer production energy, it is more desirable to present the

nutrient uptake levels in terms of kg/ha. As the appropriate yield adjustments have been

considered, the actual “kg/ha” figures are calculated using the wet weight yield figures. The sum

of the entire crop nutrient uptake has also been calculated for display purposes.

Table 33 Nutrient uptake levels (kg/ha)

Total

N P2O5 K2O CaO MgO SO3 Fe Mn B Zn Mo Cu All

Common Name kg/ha

Cassava 241.3 88.2 363.4 207.8 166.6 20.4 1.216 1.473 0.270 0.892 0.081 0.108 1092Grass 170.7 112.8 423.0 118.4 47.7 33.8 1.410 2.256 0.100 0.564 0.100 0.113 911

Lucerne 120.0 135.0 555.0 255.0 105.0 45.0 0.900 0.750 0.450 0.375 0.005 0.105 1218

Maize 228.6 123.9 388.2 5.8 121.0 26.6 2.170 1.104 0.217 0.474 0.016 0.164 898Oil palm 193.9 63.0 323.7 220.2 98.3 0.0 0.500 0.125 0.250 0.125 0.125 0.188 900

Potato 199.3 61.3 329.1 14.3 21.0 27.6 1.300 1.333 0.130 0.260 0.065 0.127 656

Rapeseed 351.5 34.6 507.7 122.0 10.8 28.3 2.001 0.661 0.374 0.657 0.009 0.071 1059

Sorghum 260.0 76.6 290.0 24.5 24.5 24.5 0.110 0.105 0.100 0.095 0.090 0.085 701Soya bean 0.0 56.0 132.0 96.0 72.0 12.0 1.464 0.360 0.156 0.244 0.028 0.100 370

Sugar beet 383.3 139.7 443.3 238.3 116.0 38.3 0.300 2.000 1.000 0.150 0.050 0.100 1363

Sugar cane 33.6 42.0 184.8 58.8 70.0 35.0 0.770 0.700 0.070 0.063 0.004 0.001 426

Sunflower 205.9 136.7 605.0 330.0 110.0 31.4 1.150 0.647 0.622 0.547 0.000 0.093 1422Switchgrass 249.2 84.0 576.0 84.0 65.0 32.0 1.200 0.980 0.280 0.460 0.006 0.098 1093

Tobacco 330.0 75.0 264.0 316.0 66.0 35.0 0.442 1.767 0.177 0.221 0.110 0.088 1089

Wheat 281.9 62.9 459.8 46.4 46.4 23.2 0.608 0.608 0.102 0.050 0.005 0.081 922Willow tree 150.0 150.0 150.0 2.0 2.0 2.0 0.020 0.020 0.020 0.020 0.020 0.020 456

MicronutrientsMacronutrients

kg/ha

Crop


2.10 Results


By combining both the nutrient uptake levels with the nutrient production requirements the total

energetic input for the individual nutrients can be determined. The calculated NPK+CAN

fertilizer relative nutrient energy requirements will cover the blunt of the energy input flow. But,

due to restrictions in the composition of NPK fertilizers, the relative nutrient energy for several

straight fertilizers will also cover a portion of the energy input flow. The following assumptions

have been made to overcome the NPK composition restriction.

Nutrient input energy assumptions: 1. When any of the macronutrients is larger than 25% of the nitrogen

level than that nutrients straight route will be used for the dividend 2. When the level of nitrogen is larger than both potassium and

phosphorous combined than UAN will be used for the dividend 3. The adjacent table illustrates the resulting relative nutrient energy

input for each nutrient and chosen production route in terms of MJ/kg.

Table 34 Resulting nutrient energy input

N P2O5 K2O CaO MgO SO3 Fe Mn B Zn Mo Cu Added All

Comm on Name

Cassava 12280 2251 1626 196 31 46 24.3 29.5 5.4 17.8 1.6 2.2 16174 16511

Grass 8690 2879 1685 112 9 77 28.2 45.1 2.0 11.3 2.0 2.3 13253 13542

Lucerne 6108 3445 2015 135 20 102 18.0 15.0 9.0 7.5 0.1 2.1 6817 11877

Maize 11637 3163 1682 5 23 60 43.4 22.1 4.3 9.5 0.3 3.3 16557 16653

Oil palm 9871 1607 1409 208 18 0 10.0 2.5 5.0 2.5 2.5 3.8 10632 13139

Potato 10147 1565 1436 13 4 63 26.0 26.7 2.6 5.2 1.3 2.5 13148 13292

Rapeseed 17889 882 2298 115 2 64 40.0 13.2 7.5 13.1 0.2 1.4 21069 21326

Sorghum 13234 1956 1480 23 5 56 2.2 2.1 2.0 1.9 1.8 1.7 16728 16765

Soya bean 0 446 426 15 13 27 29.3 7.2 3.1 4.9 0.6 2.0 885 975

Sugar beet 19511 3564 2263 225 22 87 6.0 40.0 20.0 3.0 1.0 2.0 25645 25744

Sugar cane 1710 1072 659 36 13 79 15.4 14.0 1.4 1.3 0.1 0.0 1902 3602

Sunflower 10478 3489 2338 214 21 71 23.0 12.9 12.4 10.9 0.0 1.9 16317 16672

Switchgrass 12684 2144 2326 79 12 73 24.0 19.6 5.6 9.2 0.1 2.0 17154 17378

Tobacco 16796 1914 1348 298 12 79 8.8 35.3 3.5 4.4 2.2 1.8 20436 20504

Wheat 14349 1606 2013 44 9 53 12.2 12.2 2.0 1.0 0.1 1.6 18040 18101

Willow tree 7635 3828 766 2 0 5 0.4 0.4 0.4 0.4 0.4 0.4 0 12238

MJ/ha

Tota l

MJ/ha

Macronutrients MicronutrientsCrop

The total “added” represents the summation of the bold figures, thus added through the use of artificial fertilizer

Energy Exergy

(N) Nitrogen NPK+CAN 50.90 53.99

(N) Nitrogen UAN 49.02 50.22

(P) Phosphorous NPK+CAN 25.52 31.63

(P) Phosphorous SuperP 7.97 17.48

(K) Potass ium NPK+CAN 5.10 6.31

(K) Potass ium Potash 3.22 4.11

(S) Sulphur NPK+CAN 2.27 5.16

(S) Sulphur H3SO4 2.27 5.16

(Ca) Calcium NPK+CAN 0.94 0.74

(Ca) Calcium Dolomite 0.16 0.34

(Mg) Magnesium NPK+CAN 0.19 0.40

(Mg) Magnesium Dolomite 0.19 0.40

Energy Exergy

Various Ore 20.0 25.0

Overview

Nutirent

MJ/kgNutirent Route

Macronutrients

RouteMJ/kg

Micronutrients


Figure 14 Resulting macronutrient energy input

Macronutrient Requirements

0

2500

5000

7500

10000

12500

15000

Cas

sava

Grass

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Sugar b

eet

Sug

ar can

e

Sun

flower

Swi tc

hgrass

Toba

cco

Whe

at

Willo

w tr

ee

MJ/ha

N

P2O5

K2O

CaO

MgO

SO3

Energy Relation

17.9GJ/h 19.5GJ/h 16.8GJ/h

Average input levels for all the choice crops:

N = 10.8GJ/ha, P2O5 = 2.2GJ/ha, K2O = 1.6GJ/ha, CaO = 0.11GJ/ha, MgO = 0.01GJ/ha, SO3 = 0.06GJ/ha.

This graphic perfectly illustrates the importance of the nitrogen nutrient. The energy input

associated with it is significantly higher than any of the other nutrients. For the legumes the levels

are zero for full inoculation and lower than average for the partly inoculated species. Switchgrass,

however, has such a large demand for nitrogen that even with partial inoculation (AMF) it is

amongst on of the most intense per land area. Phosphorous, although applied in high amounts,

corresponds to only a fraction of the energy input of nitrogen but is significantly higher than the

rest of the nutrients, affectively making it an important nutrient energy input and a major

contributor to the total nutrient energy input.


Figure 15 Resulting macronutrient energy input

Micronutrient Requirements

0.0

12.5

25.0

37.5

50.0

Cassav

a

Gra

ss

Luce

rne

Maiz

e

Oil pal

m

Pot

ato

Rapes

eed

Sorghu

m

Soya

bean

Sugar b

eet

Sugar can

e

Sunflo

wer

Switchg

rass

Tobacc

o

Whe

at

Wi llo

w tr

ee

MJ/ha

Fe

Mn

B

Zn

Mo

Cu

Energy Relation

Average input levels for all the choice crops:

Fe = 19.5MJ/ha, Mn = 18.6MJ/ha, B = 5.4MJ/ha, Zn = 6.5MJ/ha, Mo = 0.9MJ/ha, Cu = 1.9MJ/ha.

When comparing the energy input requirement of the micronutrients with the macronutrients

they are in terms of MJ/ha as opposed to GJ/ha. Thus their influence is miniscule. The figures

for exergy are very similar and can be found in the Appendix (see Section 5.16 – 5.18)

Figure 16 Total resulting nutrient energy/exergy input

0

5000

10000

15000

20000

25000

Cassa

va

Gra

ss

Lucern

e

Maiz

e

Oil pa

lm

Pot

ato

Rapesee

d

Sorghu

m

Soy

a be

an

Sugar b

eet

S ugar c

ane

Sunflower

Swit chgr

ass

Tobacco

Wheat

Willow

tree

MJ/ha

Energy

Exergy

Nutrient Requirements

25.7GJ/ha

28.4GJ/ha


2.10.2 Efficiency

Displaying the total nutrient input energy in terms of land area is misleading as each crop has

different yields and resulting energy output content. It is preformed because the total resulting

energy output (see Chapter 4) is expressed in terms of land area. Relating the two figures will

result in the nutrient efficiency as indicated by the simple formula:

[ ]haMJInputNutrient

haMJOutputEnergeticEfficiencyNutrient

/_

]/[__ =

The following graph displays the resulting nutrient efficiency for the best practice yield:

Figure 17 Resulting nutrient utilization efficiency

Efficiencies

0

1000

2000

3000

4000

5000

6000

7000

Cas

sava

Grass

Luce

rne

Mai

ze

Oi l pa

lm

Pot

ato

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar c

ane

Sun

fl ower

Switc

hgra

ss

Toba

cco

Whe

at

Wi llo

w tr

ee


]

Energy

Exergy

Ba se d on Fe rtilizer Proces In put En erg y

10555

10677

19000

The same graph format has been chosen as with the solar radiation utilization. The nutrient

energy input involved compared with the solar energy input is not comparable, for this reason

the conversion efficiencies are in the thousands of percent. That basically means that the shear

fertilizer manufacturing energy involved is but a fraction of the resulting output. Displaying the

nutrient efficiencies does however provide a good stance at comparing the individual crops. The

visible difference between energy and exergy for the soya bean, as an example, is attributed to the

leguminous nature of the crops. As little or nitrogen is not required, NPK is cannot be applied,

meaning the large demand of phosphorous is supplied by superphosphorous, which has a clear

deviation between process energy and exergy.


2.10.3 Analysis

Table 35 Comparative nutrient input overview

Crop Nutrient Requirements (energy) Nutrient Requirements (exergy) Common Name Input Efficiency Input Efficiency

Cassava - O - O Grass O O - O Lucerne O O O O Maize - + - + Oil Palm O + O + Potato O O O O Rapeseed - O - O Sorghum - + - + Soya Beans + + + + Sugar Beet - O - O Sugar Cane + + + + Sunflower - - - - Switchgrass - - - - Tobacco - O - O Wheat - - - - Willow Tree O - O -

Input: + below 5.0GJ/ha, - above 15.0GJ/ha, O between 5.0 – 15.0GJ/ha Efficiency: + above 2500%, below 1250%, O between 1250 – 2500%


3 Water Input Water is life and without water there is no life. It is the most

limiting factor in growth. Just as a student is practically

unproductive on a Friday morning due to the previous night’s

excessive obligations, insufficient water levels will also affect

plant productively as badly as a dehydrating hangover. To

attain optimal and projected crop yields it is imperative to

constantly regulate the levels of water on the field. Too much

water, like that from a monsoon or flood can be equally as

detrimental as a long dry spell or drought. This has resulted in

a wide variety of farming systems developed to regulate water

levels; irrigation to supply and drainage to remove excess

water. Civilizations have been founded upon proper understanding of water management

eventually involving massive engineering undertakings to regulate water flows. Although water

has many other purposes aside from crop production, for instance drinking and washing, globally

seen more than 70% of the freshwater is used for agricultural purposes. It can take more than

500 litres of water to produce just one kg on cereals38. The relation to energy, however, may not

be easy to comprehend as in the Northern regions rain is one thing not in short supply. Dark

humour is even said to have its birth from excessive rain. In fact, with the additional water flows

from rivers, many regions have too much water. In these cases water needs to be pumped out

where in the other cases water needs to be pumped in; pumps being the energy consumer.

Alongside solar radiation and nutrients, it is the third primary energy input for plant growth. The

level of energy required is naturally different being climate, topography and water source

dependent. In many areas the input is next to zero where in some regions it is the most expensive

input. As the biobased economy is realized, the global crop production will further increase

alongside the increased demands of a raising population with higher affluence, consequently

necessitating more water. The process energy input and relative price of water is still (generally

speaking) low but as competition and demand rises, irrigation/drainage capacities need to be

supplemented through expanding existing and by adding new and possibly different systems. The

world over freshwater is being mined faster then it is being regenerated, it is almost certain that

water will become more energy intensive and expensive. Desalination of saltwater is the extreme,

presently costing between 17.3 – 34.2MJ/m³ to purify39.

Understanding the regional and crop based relation towards water

demand can mitigate the looming energy increase or at least

identify possible saving options. The goal being, the most “crop for

the drop.” This section will outline the current irrigation and

drainage requirements for the specified crops in the correlating

regions and relate it to energy and exergy input.

Water Like sw eat, plants use w ater mainly for

temperature control. Aside from temperature control the transport of nutrients from the soil is of utmost importance for the survival of plant life.

From a biological standpoint, w ater has many other distinct properties that are critical for the proliferation of life. It

allow s organic compounds to react in w ays that ultimately provide the conditions for replication. It is a good solvent and has a high surface

tension, and thus allow s organic compounds and living things to be

transported in it.


3.1 Crop Water Demand

The amount of water a crop needs has many variables, but is primarily a function of the plant in

question, current growth stage and regional climate factors. A single farm may have sufficient

data to calculate the exact quantity of water needed in a particular week based on the current

seasonal weather and growth developments. Yet to create a model for location-based crop needs,

some estimates and generalizations are necessary. This is mainly due to the insufficient data, but

good estimates are possible by following the steps mentioned.

3.1.1 Seasonal Amount

Specified in the crop guide (Chapter 8) ) is the range of water demand for each crop. The growth

season water need for several popular crops is provided by FAO40. The following table outlines

the seasonal water uptake for each crop:

Table 36 Seasonal crop water demand

Low Average High Best Practice

Crop mm

Cassava 50 150 200 175 Grass 210 500 820 660 Lucerne 800 1030 1600 1315 Maize 500 750 800 775 Oil palm 1750 2000 2300 2150 Potato 500 600 700 650 Rapeseed 100 250 830 540 Sorghum 200 500 750 625 Soya bean 450 600 700 650 Sugar beet 550 600 750 675 Sugar cane 1500 1675 2500 2088 Sunflower 600 900 1000 950 Switchgrass 300 350 400 375 Tobacco 400 500 600 550 Wheat 450 550 650 600 Willow tree 500 600 2000 1300

The maximum water tolerance is also listed in the crop guide for many of the crops, in regards to

flood and heavy rain periods. This is not related to the high mentioned above; the high figures

represent to maximum level of water before negatively affecting plant production. It will be used

for the eventual calculation of drainage. Since the typical growth regions were specially selected

for the various crops, the average water uptake values are representative for those particular

regions. However, as the best practice yields were choice over the regional average it is wise to

compensate, for best practice farmers are more likely to actively regulate irrigation and drainage

levels to obtain the higher yields. And simply by having more biomass the crops will necessitate

more water. The median between the average and high water demand will be used to represent

the best practice water demands, listed in the table.


3.1.2 Relation to Monthly Evapotranspiration

When speaking in terms of irrigation and crop water uptake, figures are mainly presented on a

monthly basis. This corresponds well with the rainfall figures (following section) and the growth

characteristics of the crop, which are also usually expressed in monthly terms. Each crop has a

different growing season and growth development trends. Depending on the stage of

development and the time of the year, the crop will require different levels of water. The amount

of water uptake required by a plant is called evapotranspiration. It is the combined effect of

evaporation and transpiration. Evaporation being the amount of water in the soil converted to

vapour (i.e. climate dependent) and transpiration being the amount of additional water sucked

through the roots and emitted by the leafs (i.e. growth stage dependent). Using those two factors,

growth stage and solar radiation, the seasonal water uptake can be converted to monthly

evapotranspiration.

3.1.2.1 Growth Stage Factor

Each crop has four stages in growth; initial (or emergence), crop development (or rapid growth),

mid-season (or full size), and late season (or maturity). The following picture illustrates the

seasonal growth stages for the various crops types41:

Figure 18 Crop growth stages

A selection of available crop figures was used to calculate the generalized duration percentage for

the three applicable groups of crops over the entire growing season. Figure 19 plots the crops

with known values and is used to create Table 37 for the group types.


Crop Development

15

20

5 55 5

40

25

80

10

85

50

10

20

30

40

50

60

70

80

90

In itial Development Mid-Season Late Season

Stages

Duration Percentage

wheat

maize

potato

sorghum

soybean

sugarbeet

sunflower

Annual Average

Annual Chosen

Perennial Grasses

Perennial Scrubs/Trees

Figure 19 Crop Growth Stages

Table 37 Crop growth stage duration percentage

Initial Development Mid-Season Late Season

Crop Classification Percentage of growing season (%)

Annual 15 25 40 20 Perennial Grasses 5 10 80 5 Perennial Scrubs/Trees 5 5 85 5

These values essentially relate to the green leaf area index (LAI) or in other words the total

surface area of leafs in relation to the ground coverage. High LAI figures correspond to a higher

leaf mass and therefore a higher respiration rate of the crop and thus more transpiration. At full

growth (i.e. mid-season) the LAI can range from max 3 for succulent leafs (like grass) to 5 – 6 for

thin leafs (like maize). The following graph depicts the LAI development of the maize crop over

the growing season41:

Initial Development Mid-Season Late-Season

Peak

Average Mid-Season

Figure 20 Crop leaf area index development


The actual LAI figures vary for each crop, but are not of importance for the calculation of

evapotranspiration as the curves follow the same trend. It is the relationship that will be used for

calculation. By marking each growth stage alone the curve figures can be generated. Maximum

transpiration occurs during the entire span of the mid-season. As mid-season is reached before

the peak, the 100% LAI in relation to transpiration is set to the stage average allowing the other

growth stage leaf cover percentages to be determined:

• Initial: 12.5% • Development: 68.8% • Mid-Season: 100% • Late Season: 75%

Combing the leaf cover percentage values, the duration in the particular growing stage and the

growing season together will yield the growth stage factor

3.1.2.2 Solar Radiation Factor

The most common and FAO recommended formula for calculating the reference

evapotranspiration is the Penman-Monteith method41. Reference evapotranspiration is more or

less just the soil evaporation of the specific region, as it is based solely on the regional climate and

soil conditions and is accurate for a daily figure:

( ) ( )

( )2

2

34.01273

900408.0

u

eeuT

GR

ETasn

o +⋅+∆

−⋅⋅−

⋅+−⋅=

γ

γ

Rn: Net radiation (MJ⋅m -2⋅day-1) G: Soil heat flux density (MJ⋅m -2⋅day-1) T: Mean daily air temperature at 2 meter height (°C) u2: Wind speed at 2 meter height (m⋅s-1) es: Saturation vapour pressure (kPa) ea: Actual vapour pressure (kPa)

∆: Slope vapour pressure cu rve (kPa⋅°C-1) γ: Psychrometric constant (kPa⋅°C-1)

On the farm scale it is possible to obtain all the necessary data to calculate the actual reference

evapotranspiration for that particular plot over the course of a year. However, on a global scale,

regional climate deviations make it vastly complex to calculate reference evapotranspiration to a

high degree of accuracy. By taking a closer look at the formula it is apparent that the solar (net)

radiation (Rn) has the largest influence in the result. Solar radiation for each month is known for

each crop. The monthly percentage ratio of solar radiation can be calculated by using the total

input over the growing season. It is therefore assumed and simplified that only solar radiation has

an influence on the reference evapotranspiration, effectively becoming the solar radiation factor.

A detailed calculation comparison and description was conducted under Dutch conditions for the

potato crop to validate the simplification.


3.1.2.3 Solar Radiation Factor Assumption Valorization

The Penman-Monteith formula is accurate enough for a single day, but in the calculation path

monthly figures will be used instead. Each factor will be mentioned and handled individually:

• Net Radiation: Same data as in the solar radiation input section • Soil Heat Flux Density: Typically the figures range from 1-5% of the net radiation. It is the

effect of the soil cooling and emitting heat. A value of 2.5% will be taken

• Mean Temperature: For the region average highs and lows are well documented. The mean of those two figures will be used for the monthly temperature figures

• Wind Speed: Wind speed data is hard to come across as most studies are designed for wind turbine applications (i.e at a height of 50m+) or nautical purpose (i.e over water). Wind

speeds of 1-4m/s are typical in most regions of the surface. The reason for choosing

2.25m/s will be discussed later

• Saturation Vapour Pressure and Actual Vapour Pressure: The high and low of the relative humidity is well known and documented for the region. By adjusting the mean relative

humidity to the saturation vapour pressure of around 2atm, the difference is determined.

• Slope Vapour Pressure: Slope vapour pressure is calculated using a large formula which has only one variable, mean temperature

• Psychrometric Constant: It is not actually constant as it is a function of pressure and temperature. It is also calculated for each month

The following table illustrates the calculation path of the reference evapotranspiration:

Formula based ETo Month - jan feb mar apr may jun jul aug sep oct nov dec

Days/Month day 31 28 31 30 31 30 31 31 30 31 30 31

MJ/m²/month 22.9 39.8 77.5 113.7 152.5 147.0 153.8 131.1 84.9 52.7 27.6 18.6

MJ/m²/day 0.740 1.420 2.500 3.790 4.920 4.900 4.960 4.230 2.830 1.700 0.920 0.600

Soil Heat Flux Density MJ/m²/day 0.019 0.036 0.063 0.095 0.123 0.123 0.124 0.106 0.071 0.043 0.023 0.015

Low (oC) 0 1 3 6 10 13 13 15 13 9 5 2

High (oC) 4 5 8 11 16 17 20 20 17 13 7 5

Average (oC) 2.0 3.0 5.5 8.5 13.0 15.0 16.5 17.5 15.0 11.0 6.0 3.5

Wind Speed m/s 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25

Low 60 61 62 64 68 72 76 77 68 71 65 63

High 94 95 94 93 96 97 97 97 89 97 97 97Average (%) 77.0 78.0 78.0 78.5 82.0 84.5 86.5 87.0 78.5 84.0 81.0 80.0

Slope vapour pressure kPa/C 0.050 0.054 0.063 0.075 0.098 0.110 0.119 0.126 0.110 0.087 0.065 0.055

Latent Heat of Vapourization MJ/kg 2.496 2.494 2.488 2.481 2.47 2.466 2.462 2.46 2.466 2.475 2.487 2.493

Atmospheric Pressure kPa 101 101 101 101 101 101 101 101 101 101 101 101Psychrometric Constant kPa/C 0.066 0.066 0.066 0.066 0.067 0.067 0.067 0.067 0.067 0.067 0.066 0.066

mm/day -2.78 -1.22 1.187 3.69 5.13 4.672 4.463 3.109 1.331 -0.92 -2.46 -3.23

mm/month -86.3 -34.1 36.78 110.7 159 140.2 138.4 96.37 39.93 -28.4 -73.9 -100

mm/month 0.0 0.0 36.8 110.7 159.0 140.2 138.4 96.4 39.9 0.0 0.0 0.0

Evapotranspiration

Net Radiation

Mean Daily Temperure

Relative Humidity

Reference evapotranspiration is only the first step in determining the crop specific

evapotranspiration. Each crop has a so-called “crop factor” for each stage of development in

relation to water uptake. The growth stages and duration were already determined as a

prerequisite for the LAI assumption; the same figures will be taken. The crop factor for the

potato is available for several sources and is based on the development stage of the growth

season. The following table illustrates the crop factor and the resulting evapotranspiration:


Potato crop factor Crop Potato

Growth yes/no 0 0 0 1 1 1 1 1 1 0 0 0

Stage - 0 0 0 I D D M M L 0 0 0

Crop Factor Kc 0 0 0 0.45 0.75 0.75 1.15 1.15 0.85 0 0 0

Water Needs mm 0.0 0.0 0.0 49.8 119.3 105.1 159.1 110.8 33.9 0.0 0.0 0.0

It was mentioned previously that exact wind figures are not available and a best guess was

necessary. It is known that the potato requires 500 – 700mm/year of water with an average of

600mm. Holland is has a mild climate, so the water requirements will tend to be on the low side.

By adjusting the wind figures the total potato evapotranspiration is set to a value just below

600mm. In this case by setting the wind speed at 2.25m/s the resulting total water uptake for the

crop is 578mm.

Comment:

During months were the temperature is below 5°C and/or the solar radiation is below 75MJ/m² the evapotranspiration is negative, meaning that evaporation does not take place. Any rainfall

occurring at that time is collected and contained in the soil. This correlates well with the other

assumptions of using the rain water during the off-growing seasons.

Comparison

The following graphs represent the comparison between the actual formula, data specific method

and the assumption listed in Chapter 5

Reference Evapotranspiration

Reference Evapotranspiration

0

25

50

75

100

125

150

175

jan feb mar apr may jun jul aug sep oct nov dec

mm

Penman-Monteith Formula

Adapted Assumption


Crop Water Requirements

Crop Water Requirements

0

25

50

75

100

125

150

175

jan feb mar apr may jun jul aug sep oct nov dec

mm

Penman-Monteith and Crop Factor

Assumption and LAI

It appears that the differences between the two and more importantly the final crop

evapotranspiration are small, valorizing the assumption.

3.1.2.4 Evapotranspiration

Monthly Evapotranspiration

0

20

40

60

80

100

120

140

160

180

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

Monthly W

ater Uptake /mm

Cassava Africa Nigeria

Grass Europe Holland

Lucerne North America Wyoming

Maize North America Iowa

Oil palm South Pacif ic Malaysia

Potato Europe Holland

Rapeseed Europe Belgium

Sorghum Africa Kenya

Soya bean North America I llinois

Sugar beet Europe Germany

Sugar cane South America Brazil

Sunflower Europe France

Switchgrass North America Oregon

Tobacco South Pacific Australia

Wheat Europe France

Willow tree Europe Sweden

Figure 21 Resulting monthly evapotranspiration


Combing both the growth stage factor and the solar radiation factor will yield the monthly

evapotranspiration (or crop water demand). The Penman-Monteith also contains a factor of

0.408 for the solar radiation. This additional factor will be included to lower the impact of the

solar radiation while placing more stress on the growth stage. The evapotranspiration for all

plants have a bell-curve trend over the course of the growing season. The following graph

illustrates the resulting monthly evapotranspiration for the selected crops. It is noticeable that

indeed bell-curves are present, suggesting the method was successful in converting seasonal water

demand to monthly figures.

3.2 Rainfall

In regions where sufficient rainfall is present for the cultivation of a particular crop, the

agricultural practice is called dryland farming or more appropriately rainfed farming. The previous

term may sound contradictory since these are in fact wet regions, but because no additional water

in the form of irrigation is required; they are kept “dry”. Arid regions have less than 500mm of

rainfall per annum and fundamentally rely on irrigation for crop production40. The level of rainfall

reduces the need for supplementary irrigation and as a result the associated water management

costs. Rainwater (or precipitation) is free as it falls from the sky. And the gravitational potential

energy is too spread out to be utilized or to be assigned an energy charge, save for the large

hydrodams consisting of vast ridges and valleys. However, should too much rain fall and surpass

the high range of monthly evapotranspiration drainage is required, meaning the free source

receives a negative cost. But for the large part, crops have been selected to grow in the best suited

regions keeping drainage and irrigation to a minimum. Rainfall generally reduces the need to

apply water.

3.2.1 Regional Figures

Rainfall values are based on a monthly basis over a 10-year average from the years 1961 to 1990.

Data is available for the entire world over and was obtained from:

• The Deutscher Wetterdienst (National Meteorological Service of Germany)42 The location is stipulated using the global coordinate system and through a formula to derive at

the values listed in the provided excel table.

• Row=((90-Latitude)*360)+1+(180+Longitude)+17 Just as with the solar radiation figures, the accuracy is based on 1deg. This results in a location

grid area of 100x100km for regions above the Tropic of Cancer and below the Tropic of

Capricorn and 150kmx150km for those in between. Likewise in regards to cultivation areas, these

differences are insignificant. Table 38 lists the monthly precipitation values for the corresponding

locations


Table 38 Location based rainfall values

GCPP

Latitude Longitude Grid Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Common Name 1.0deg

Cassava Africa Nigeria 8 7 29725 6 12 47 107 179 197 211 219 245 144 11 3

Grass Europe Holland 51 5 14243 66 57 68 59 68 78 75 68 60 66 75 76

Lucerne North America South Dakota 44 -103 16655 9 12 24 49 72 80 59 41 31 24 12 11

Maize North America Iowa 41 -91 17747 39 36 74 98 98 104 104 94 94 74 53 51

Oil palm South Pacific Malaysia 2 113 31991 411 259 278 259 233 232 221 265 274 314 370 404

Potato Europe Holland 51 5 14243 66 57 68 59 68 78 75 68 60 66 75 76

Rapeseed Europe Belgium 50 5 14603 76 64 72 59 71 77 66 64 65 72 83 84

Sorghum Africa Kenya 0 35 32633 68 77 108 176 125 65 63 66 55 57 97 77

Soya bean North America Illinois 41 -90 17748 41 39 76 100 97 104 101 88 90 68 58 57

Sugar beet Europe Germany 52 8 13886 65 43 64 48 68 79 66 63 59 52 63 71

Sugar cane South America Brazil -25 -50 41548 178 162 146 92 104 103 85 80 116 138 118 158

Sunflower Europe France 48 0 15318 63 59 56 50 63 47 46 46 53 59 67 63

Switchgrass North America Iowa 41 -91 17747 39 36 74 98 98 104 104 94 94 74 53 51

Tobacco South Pacific Austral ia -34 145 44983 35 26 34 37 45 30 32 38 34 39 25 30

Wheat Europe France 48 0 15318 63 59 56 50 63 47 46 46 53 59 67 63

Willow tree Europe Sweden 56 13 12451 53 33 43 40 42 53 68 58 61 60 68 60

mm/month

Crop Continent Country/RegionRepresentative Area

Largest Producer

Precipitation Values

Degrees

3.2.2 Effective Rainfall

Not all of the rainfall can be utilized by the crop; there are many limiting factors which prevent

the full use of the rainfall. The actual amount of rainfall that can be utilized by a crop is called the

effective rainfall.43 It is essentially the rainfall minus runoff, immediate evaporation and deep

percolation (leaching). The factors affecting effective rainfall are: Climate, Soil Moisture Content

Soil Texture, Soil Structure, Depth of Roots and Topography. There are several empirical

formulas available at various levels of detail44. Seeing that the only information available is the

regional rainfall figures a formula pertaining to the relation between actual rainfall and effective

rainfall must be chosen. There are two such methods; the Renfro and the US Bureau of

Reclamation. The following graphic depicts the relationship between actual and effective rainfall:

Figure 22 Effective rainfall

Effective Rainfall

y = 0.0044x2 + 0.1845x - 1.4167

y = 0.7984x - 24.695

y = -0.003x2 + 1.1743x - 1.7168

0

25

50

75

100

125

150

175

0 50 100 150 200 250

Actual Rainfall /mm

Effective Rainfall /mm

Renfro

Pe=0.6*P-10 for under 75

Pe=0.8*P-25 for over 75mm

US Bureau of Reclamation

Pe=0.95*P for <25.4mm

Pe=24.1+0.90(P-25.4) for 25.4<P<50.8

Pe=47.0+0.82(P-50.8) for 50.8<P<76.2

Pe=67.8+0.65(P-76.2) for 76.2<P<101.6

Pe=84.3+0.45(P-101.6) for 101.6<P<127.0

Pe=95.8+0.25(P-127.0) for 127.0<P<152.4

Pe=102.1+0.05(P-152.4) for >152.4mm


The US Bureau of Reclamation is better suited for arid to temperate regions which do not have

particularly high amounts of rain, whereas the Renfro method is better suited for regions of high

rainfall. The borderline will be drawn at 150mm. Should a location have more than 150mm actual

rainfall in any month the Renfro method will be applied, else the USBR method.

3.3 Irrigation/Drainage Requirements

In cases where the monthly effective rainfall does not meet the level of monthly

evapotranspiration irrigation is required. Moreover, when the monthly effective rainfall exceeds

the high monthly evapotranspiration drainage is required. The water for irrigation has many

sources and systems, which can be generalized for an entire region. In more advanced systems

irrigation can also be used to provide fertilizers, pesticides, herbicides and insecticide, control the

soil temperature and balance the salinity (covered in Chapter 6). Depending on the quality of the

source water and the extent of supplements, it may become necessary to flush more than the

required levels of water to leach salts, acids and alkalis out of the soil45. The maximum height of

the water table is of great importance for drainage systems. In the event that the water table has

risen above the root line, the problem of “wet feet” and water logging can occur, greatly stunting

crop growth.

3.3.1 Systems and Sources

The vast majority of irrigation systems are based on using the gravitational force to redirect large

bodies of water, i.e. rivers and lakes. In these cases the differential height the water needs to be

pumped up and down for control is kept very low, essentially keeping the energy costs at a

minimum. The same source and diversion systems can however have a different application

adding significantly to the energy costs. In Babylon the world could wonder at their great

construction, The Hanging Gardens. It was the first irrigation system in the world to emulate

rainfall. Today sprinklers are common in many parts of the world. They require high pressure to

operate and thus require large amounts of energy input, but are more effective. Each system has a

different rate of water application efficiency. The rate of efficiency stipulates how much

additional water must be supplied to obtain the stipulated irrigation requirement. In several parts

of the world water sources cannot be redirected using gravity, but must employ large pumping

systems. Underground aquifers are a good and ample source of water for many highly productive

regions but require substantial amounts of energy for the extraction; the cost being dependent on

the surface depth of the reservoir. The following outlines the various systems and related

assumptions needed to calculate the level of irrigation, drainage and energy demand46, 47.

3.3.1.1 Furrow

Furrows are small parallel channels made to transport water to and from the

field. The crop is usually grown on the ridges between the furrows. It is

suitable for the largest array of crops.

Circulation/additional height: 2.0m, Efficiency: 50-90% � 70%


3.3.1.2 Basin

Basins are large but shallow artificial bodies of water contained within bunds.

They are used to slightly flood the fields. There are also a variant between a

furrow and a basin, called border irrigation, used to guide water down slopes.

Border irrigation has the same properties, so will be classified as basin.


3.3.1.3 Drip

Drip systems consists of a series of thin pipes distributed alone the fields in a

similar configeration as furrows. The heads are places at the base of the plant

to ensure a very high water efficiency and are cheifly utilized in hot regions.


3.3.1.4 Sprinkler (travelling gun)

Sprinklers pressurize water in order to distribute it through a series of pipes

and finally sprayed, simulating natural rainfall. It is sprayed into the air to

reduce the water droplets that fall on the crops. Rotor heads have pressures

between 2.75-9bars. Typical is 4.5bar. It is suitable for all row crops.


3.3.1.5 Sprinkler (center pivot)

Another variant of the sprinkler system is the center pivot, using a series of

tracks to guide the overhead spray in a circular path alone the field. The water

efficiency and energy use is immensely improved. Pressures are reduced to

2.75bar while the air losses are kept to a minimal.


3.3.1.6 Water body

Redirecting a river will require 0m of pumping height. Tapping a lake to allow

it to flow, presumably into a gravitational powered channel, will require about

5m initial pumping height. The surface depth of an aquifer can range from

several meters to several hundred. Of those in question the range more

around 20 – 100mm, so the average will be set at 50m.

3.3.1.7 Drainage

Water collected at the desirable water table must be pumped up and out of

the fields and back into the channels. A system of underground pipes and

porous material are used to divert the water to a central pump. The pipe

depth is slightly below the root length, so a value of 3meters is typical.

Subirrigation works in the same way but reversed with the exception that the

pipes are at more or less at root level close to the surface, so 0.5meters.


3.3.2 Irrigation Levels

The following graph illustrates the resulting irrigation and drainage requirements, the values and

calculations behind the graph are found in the accompanying database spreadsheets:

Figure 23 Irrigation and drainage requirements

Irrigation and Drainage Requirements

0

500

1000

1500

2000

2500

3000

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar c

ane

Sun

fl ower

Swi tc

hgrass

Toba

cco

Whe

at

Will o

w tr

ee

Wa

ter

/mm

Water Uptake

Corrolating Effective Rainfall

I rrigation

Drainage

It is clear that most crops require next to no irrigation and drainage, whereas some on the

contrary need large amounts. The cassava in particular needs lots of drainage and the sugar cane

large amounts of supplementary irrigation.

3.3.3 Pump

The most common pump for liquid displacement, like

that of water systems, is the centrifuge pump48. They

deliver high flow rates at comparably low pressures

meaning that the energy consumption is kept fairly low.

The volume displacement efficiency is in the range of

90-98%, with 98% being frequently obtained. The

pressure efficiency (or pressure loss) is slightly worse,

but still high, ranging from 80-90%; 85% being set as typical. The following formula is used to

calculate the power based on the amount of displaced water (irrigation/drainage), the static

height (pump level) and the pump efficiencies:


( )( )pv

gHVP ηδη ⋅⋅⋅⋅⋅= &

V& : Volume flow (m³⋅s-1)

vη : Volume displacement efficiency (%)

H: Dynamic height (m)

δ: Fluid density (kg⋅m -3)

g: Gravitational acceleration (9.81m⋅s-2)

pη : Pressure displacement efficiency (%)

The yearly volume flow (resulting irrigation and drainage requirements) must be converted to

seconds. The resulting power is terms of kW and must be multiplied by the factor 8760 for yearly

kWh and again by 3.6 for MJ.

3.3.3.1 Fuel Source

The sources of energy to fuel the irrigation/drainage pumps are as diverse as the regions where

they are operated. The common three are pure electricity from the grid, natural gas and diesel. In

some rare cases other fuels may be used, for instance fuel oil may be easier and cheaper to

acquire in Africa than diesel, but these minor exceptions have little significance. On the pump

itself the various fuels have negligible influence on the pumping efficiency. However, the major

significance of incorporating the fuel source is for cumulative energy and exergy. The conversion

factors were covered in chapter 2. To increase energy efficiency, in many regions it has been

proposed to switch from electricity to natural gas driven pumps. Subsides have even been

imposed in America to help farms make the switch49. The following table gives an overview of

the systems for the region and crop, resulting dynamic height for both irrigation and drainage and

the fuel type, some this information was already incorporated to determine the irrigation levels:

Table 39 Irrigation system layout for region and crop

Type Source Hir rigation Hdrainage

Common Name Region - - type energy exergy

Cassava Nigeria Drip Lake 2 3 Diesel 1 1

Grass Holland Sprinkler-TG River 45 3 Natural Gas 1 1.05

Lucerne South Dakota Sprinkler-CP Aquifer 77.5 3 Electrici ty 0.45 0.35Maize Iowa Sprinkler-CP Aquifer 77.5 3 Electrici ty 0.45 0.35

Oil Palm Malaysia Basin River 1 3 Diesel 1 1

Potato Holland Furrow River 2 3 Natural Gas 1 1.05

Rapeseed Belgium Basin River 1 3 Natural Gas 1 1.05

Sorghum Kenya Drip River 2 3 Diesel 1 1

Soya Beans Illinois Sprinkler-TG Aquifer 95 3 Electrici ty 0.45 0.35

Sugar Beet Germany Sprinkler-TG River 45 3 Electrici ty 0.45 0.35

Sugar Cane Brazil Subirrigation River 0.5 3 Diesel 1 1

Sunflower France Sprinkler-TG River 45 3 Electrici ty 0.45 0.35

Switchgrass Oregon Furrow River 2 3 Electrici ty 0.45 0.35

Tobacco Australia Drip Aquifer 2 3 Diesel 1 1

Wheat France Sprinkler-TG River 45 3 Electrici ty 0.45 0.35Willow Tree Sweden Furrow River 2 3 Electrici ty 0.45 0.35

CropIrrigation Dynamic Height Pump Configuration

Fuel

m

Producer

Kenya: typically a furrow system is employed but drip systems are advisable for near future developments Australia: currently a basin-like system is frequent, but tobacco figures based on a system similar to drip Nigeria: basin is currently used as easy to make, when large scale investments in region drip should be employed America: centre pivot only employed in mid-west


3.4 Resulting Energy


The difference in quantitive levels of water requirements and the relation to energy demands are

stark. The following graph incorporates all factors mentioned in terms of MJ/ha:

Figure 24 Resulting irrigation/drainage input

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sorgh

um

Soy

a be

an

Suga

r bee

t

Sug

ar can

e

Sun

flower

Switc

hgra

ss

Toba

cco

Whe

at

Wil lo

w tree

MJ/

ha

Irrigation/Drainage Energy

Irrigation/Drainage Exergy

Irrigation and Drainage

22.9GJ/ha

29.4GJ/ha

10.5GJ/ha

13.5GJ/ha

Lucerne (or alfalfa) is grown in a region that requires a high level of irrigation, supplied in

particular from an aquifer via an electric pump control system. It has an input well above

20GJ/ha. Despite the center pivot improvement, irrigation is probably the most expensive input.

The sugar cane had high irrigation requirements, nearly a factor 2 more than the lucerne, but due

to the cost effective system results in a much less energy intense input.

3.4.2 Conversion Efficiency

As opposed to the other energy input streams where all crops in all regions had an energetic

input in many regions crops can be cultivated without the need of an energy intensive water

management system. For this reason it makes little sense to present the figures for those few

crops in a conversion efficiency graph.


3.4.3 Analysis

The water requirements can be seen in two ways; as being the absolute total amount of displaced

water needed or as being the related energy costs. For as technology progresses the costs of

irrigation and drainage could decrease. As an example, several large scale installation in the Great

Plains of America have recently employed low pressure pivot sprinkler systems

and have reduced the energy demand by a substantial amount (see adjustment

picture). This trend could be realized for many of the systems and the different

regions. But, as previously mentioned, the foreseeable increase in water

competition may make water a limited and costly resource to obtain. It is hard

to speculate which direction the relative irrigation and drainage energy cost will

go. This is why the following table is expressed in both absolute terms and in

relative energy terms:

Table 40 Comparative irrigation/drainage input overview

Crop Irrigation and Drainage Requirements

Irrigation Drainage Combined Common Name

Level Level Energy Exergy Cassava O - O O Grass O O - - Lucerne - + - - Maize O O - O Oil Palm O O O O Potato - O O O Rapeseed O O + + Sorghum O O + + Soya Beans O O - - Sugar Beet O O - - Sugar Cane - + O O Sunflower - + - - Switchgrass + O + + Tobacco O O O O Wheat O O - - Willow Tree - + O -

Level: + 0mm, - above 250mm, O between 0 – 250mm Energy: + 0MJ/ha, - above 500MJ/ha, O between 0 – 500MJ/ha

Any crops with a negative sign should be paid special attention to. But, for those crops that have

a negative level and an “O” for energy, already have a good and energy efficiency system.


Pest: A plant or animal regarded as injurious or unwanted; in agricultural terms competing for or limiting the human supply chain (crops)

4 Pesticide Input

4.1 Preface


Connecting the vast oceans of the Pacific with the Atlantic has been an overzealous dream of

world leaders for centuries. It was not until after the success of the Suez Canal, that in 1880, the

French undertook the vast engineering project to construct the Panama Canal. Their failure can

only partly be attributed to natural circumstances and miscalculations; malaria and the yellow

fever had killed over 22000 workers in a span of just 8 years. The route cause of such diseases

was unknown until shortly before the Americans restarted the project in 1904. A theory had been

developed suggesting that mosquitoes harboured and transmitted

the deadly diseases. At the time, the best mitigation and most

ingenious infection prevention system was simply sanitation and

larvae eradication. By providing shielding for the workers dwellings

and hospitals (portable fever cages) and oiling over small water

bodies, mosquito population drastically fell, as did the cases of

malaria and yellow fever. These methods are expensive, time consuming and are a far cry from a

final solution to the problem. In regions were international trade incentives were not important

the diseases continued to spread, killing millions.

Although dichlorodiphenyltrichloroethane (DDT) was first

synthesized in 1873, it was not until the early stages of the

Second World War that Swiss chemist Paul Hermann Müller

discovered its poisoning affects against arthropods like

mosquitoes. DDT was initially and extensively employed by the

Allies to regionally control both malaria and typhus. In the 50’s

and 60’s DDT was sprayed the world over and is credited for

the elimination of malaria in Europe and North America. For

his discovery of the high contact poison efficiency of DDT,

Müller was awarded the Nobel Prize in 1948. It is in affect the first pesticide and the transition to

agricultural applications did not take long. The crop related advantages were so great that in the

mean time more than 2500 different pesticides have since been developed (of which more than

1100 have ISO nomenclatures50), creating an entirely new industry…the agrichemical sector.

4.1.2 Agricultural Applications

Sufficient solar radiation, nutrients and water is not enough to guarantee high crop yields. What

are classified as pests can greatly reduce the potential yield of the crop by utilizing the favourable

conditions provided by modern farming techniques; more or less striving from the inputs

A mosquito cried out in pain: “A chemist has poisoned my brain!”

The cause of his sorrow

Was para-dichloro

Diphenyltrichloroethane

- Adam Bernard


intended for the crop. There are four main types of pests hindering the crop growth in

completely different ways that necessitate a unique method/chemical of treatment:

1. Unwanted plants (mainly weeds) will compete against the crop for the

same nutrients, water and ground cover (solar radiation)

o Manual Method: Burning fields, physically removing weeds

o Agrichemical Method: Herbicides

2. Insects and other arthropods will eat at the crop leafs/fruits destroying

or stunting growth

o Manual Method: Screens, generally very little

o Agrichemical Method: Insecticides

3. Fungal infection will decompose the plant matter and use the nutrient

stream to further spread

o Manual Method: Remove the infected section

o Agrichemical Method: Fungicides

4. Roundworms living in the soil can either infect the plant and use its

nutrients or multiply in the soil affectively competing against the crop

o Manual Method: Selective breeding, generally very little

o Agrichemical Method: Nematicides

These four groups represent practically all the crop pests and protection measures. There are of

course other pests, like animals and birds, but chemical prevention is not a socially accepted

method of protection and their influence for the most part is minute. A scarecrow works just

fine. The manual methods of plant protection are hardly carried out in the develop world

anymore as it is very labour intensive with relatively ineffective results compared to the chemical

treatment. In many developing countries, however, pesticides are too expensive to use and is a

major factor why their crop yields are so pathetic.

All crops and thus crop yields are prone to other more serious pests, namely viral infections and

diseases. In worst cases scenarios entire harvests can be lost, lowering the regional yield of such

crops. The manual method sacrifices the entire harvest, by completely disposing of the infected

fields. In food production the yield is affectively zero, yet for industrial applications it is easily

foreseeable that the energy and materials can still be retrieved. Nonetheless the physical yields are

lowered. Much investigation has gone into plant breeding, both in the lab and on the field, to

create protection methods against the pest. However, since agrichemicals (like bactericides and

virucides) are in their infancy and only represent a minor fraction of cure techniques these pests

will not be considered in this section. Furthermore since such pests are fact, the regional yield

figures incorporate these losses.

Some of the amazing crop yields recorded in recent times simply could not have been possible

without the widespread use of pesticides. Water, sun and nutrients can be used by any organism

on the field. Pesticides make sure that it is, to the highest degree, the desired crop. The use of


pesticides can be especially exuberant in highly intensified farming regions like Holland,

exceeding the typical application rates of between 2 – 10 kg active ingredient per hectare51. Yet,

when balanced with the yield benefits still prove very profitable. Since the 1950’s the production

of pesticides has increased more than 50-fold with current worldwide production at more than

2.5 million tonnes annually and the EU alone consuming 0.3 million tonnes52. Due to the many

environmental problems associated with pesticides, like persistent organic pollutants (POP), a

gradual transition on the field level is occurring. For example, Integrated Pest Management is a new

method intended to reduce the level of pesticides applied to a field by making their use more

effective. But more drastic are the chemicals themselves, many older pesticides have been banned

and phased out by newer, more pest specific and less harmful agrichemicals. DDT, the world’s

first pesticide (insecticide), is now completely banned in 98 countries.

4.2 Process Energy

Pesticides are not a primary energy input in the sense of being directly used as a source for crop

growth. They are however, designed to maximize the use of the other primary energy inputs

while requiring a hefty amount of process energy themselves. Compared to fertilizers the

applications rates per field are but a small fraction, yet due to the complex and large chemical

structure of the pesticides, the required production energy is several magnitudes larger. Process

energy range from 50 to 900MJ per kilogram of active ingredient, roughly ten times the amount

required for fertilizers. The deviation correlating to the range of 50 to 900MJ/kg is fairly large as

the chemical structures and associated process energy vary substantially. Example: 2,4-D has a relatively simple structure consisting of a carboxylic acid attached to a benzene ring with two straight chlorine functionalities. Cypermethrin has in contrast has a very large structure with several different forms of functionalities; oxides, amides, chlorides, etc.

2,4-D Cypermethrin

The difference in process energy between the two pesticides is 824 – 115 = 709MJ/kg

Assuming one averaged value for all pesticides can lead to high uncertainties in the calculations

of the pesticide input energy requirements. The calculation path described here within has been

specially chosen to reduce the impact of assumptions by avoiding large averages whenever

possible, thus increasing the certainty. In some cases where data is scarce it is unavoidable to use

such simplifications.

4.2.1 Source of Data

There are currently over 2500 different pesticides on the market and with the high degree of

secrecy over their formulation and process schemes, the availability of information is limited. In

1987, Green compiled an investigation into the process requirements for 38 common and no-


longer patent protected pesticides53. They represent only ~1% of the chemical spectrum but

represent a large proportion of the market share. For instance, Glyphosate (better known as

Roundup) is the world’s most known/used pesticide and even agrichemical. 80% of US Soya

production is been genetically modified for Roundup protection. Information concerning the

pesticide industry is explicitly expressed in terms of active ingredients, those chemicals

responsible for the desired function. Because of their highly toxic and hazardous nature

pesticides are delivered in formulation, either as a liquid, powder or granule form. It is not

exceptional for the formulation to contain as little as 10% of the active ingredient. Although

seemingly large, when related to total process energy, the influence of formulation is minor. In

addition to the process energy flows, Green had also assessed energy costs of formulation,

packaging and distribution of pesticides. Formulation is naturally the largest of the three at

~20MJ/kg for miscible oil, ~30MJ/kg for wettable powder and ~10MJ/kg for granules.

Packaging and distribution combined are only 3MJ/kg. It is even suggested that shipping to the

heart of Africa has roughly the same figure. These aspects will be covered in the following

chapter as they match better with farming practices. More recent process data from the industry

is simply not available and a more detailed investigation would bring little addition benefit in the

scope of further certainty. As with the fertilizer industry the BAT is desirable to best describe the

future trends when the large scale biomass implementation is realized. Pesticides are fine

chemicals with large profit margins, so it is expected that little effort has gone into process

optimization. Therefore, it will be assumed that no significant technological and energy saving

advancements have been made in the agrichemical sector since 1987.

�� BAT of pesticide production are based solely on Green’s 1987 process energy

4.2.2 Grouping

Since there are well over 2500 different pesticides, the industry has grouped them based on their

working chemical functionalities. Each classification of pesticide works on the same principle

against the pests, but due to industrial proprietary rights each manufacturer produces a slightly

different chemical. In many cases the chemical structural differences between some of the

pesticides are so miniscule that the process energy requirements have next to no difference. As

the agricultural industry has access to the entire spectrum they are free to choice any of the

available pesticides. The accuracy of relating this to the energy input can be increased by using

the given 38 chemicals and grouping them on different degrees of detail available. The grouping

and related accuracy levels are as follows:

Table 41 Pesticide grouping accuracy

Grouping Assumption Example Accuracy Level

Listed, one of the 38 pesticide Alachlor Very High Pesticide Specific Classification Chloroacetanilide Herbicide High Pesticide Type Herbicide Acceptable Pesticide Average Pesticide Low


4.2.3 Calculations

Under the investigation of the required process energies for the 38 pesticides, the various types

of energy origins are listed. They are presented in a cumulative manner including feedstock and

processing costs. However, electricity for instance, is best converted to a fossil origin to

correspond with the other energy inputs. The calculation factors for cumulative energy and

exergy as described in chapter 2 are incorporated.

The resulting calculations for the individual pesticides and the various grouping classifications are

not presented. For sake of visualization the pesticide type herbicide with the individual energy/exergy

values is illustrated:

Herbicides

0

100

200

300

400

500

600

700

800

900

2,4,5-

T

2,4-

D

Ala

chlo

r

Atraz

ine

Bentazo

n

But

ylate

Chlor

ambe

n

Chlor

sulfu

ron

Cya

nazine

Dicam

ba

Dino se

b

Diq

uat

Diuro

n

EPT

C

Fluaz

ifop-b

utyl

Glyph

osat

e

Linu

ron

MCPA

Met

olach

lor

Para qu

at

Pro

pach

lor

Prop

anil

Trif lur

ali n

Ave

rage

GJ/ton

Energy

Exergy

Figure 25 Herbicides process energy

The herbicides have a noticeable variation between the different active ingredients. The average

cumulative process energy is 368MJ/kg with a standard deviation of 196MJ/kg, meaning that an

accuracy of 46.7% is present when using the average. It is slightly better in terms of exergy at

385±199MJ/kg. This is a perfect indication of why it is better to strive for the listed values or the pesticide specific classification. For example, the classification “phenoxyacetic herbicides” has an

average of 158±37MJ/kg, yielding an accuracy of 76.6%. The other specific classifications have similar trends justifying Table 40. The chemicals covered under the assessment for the other

pesticide type groups (insecticide, fungicide and nematicide) are significantly less leading to

higher inaccuracies:

• Nematicide: Energy = 503±159MJ/kg (68.3%) Exergy = 534±150MJ/kg (71.9%) • Insecticide: Energy = 318±236MJ/kg (25.8%) Exergy = 344±323MJ/kg (32.6%) • Fungicide: Energy = 244±216MJ/kg (11.6%) Exergy = 256±218MJ/kg (14.8%)


4.3 Crop Pesticide Application Rates

Pesticide application rates are dependent on three factors; the crop, the specific crop pests in the

region and the wealth of the region. The latter is the main factor limiting the availability of data.

In affluent regions, which have strict environmental legislation, the exact pesticide use is carefully

monitored. It is so well documented in some areas that even the exact chemicals, treated area and

typical application ratios are listed, whereas in more impoverished regions specific data is difficult

to acquire. Application rate figures can be presented in a multitude of different manners and level

of detail, yet all figures are converted into kg/ha. By expressing the figures in kg/ha the relation

to energy input is possible. Each crop is strongly dependent on the region and will be assessed

individually; however for the most part, the regional crop-based trend is suggestive of the crop

protection issues as a whole and can be extrapolated. There are of course exceptions and very

regional based problems. These and other comments regarding the crop and region based

pesticide use and information are described by the following:

4.3.1 Crop and Regional Comments

For the calculation tables and more specific data consult the accompanying database spreadsheets

4.3.1.1 Cassava – Nigeria

Nigeria is poor in the sense of agricultural practices. It is suggested that only 3% of the cassava

farmed has access to pesticides and additional detail simply does not exist. These low rates are a

major cause for the low non-commercial yields compared to other regions. This does however

present a large improvement possibility.

4.3.1.2 Grass – Holland

The European Commission had conducted a country based appraisal of the various types of

pesticides used on different types of agricultural fields51. This presents moderately accurate data

for grass. Grass, like that for grazing, requires proportional seen very small amounts of pesticides.

4.3.1.3 Lucerne – Wyoming

In America, state-based data is available on the exact pesticide chemical, the treated area and

average application rates on the treated area54. These values can be use to calculate the state-based

application rate and relative energy requirements to a high degree of accuracy. Lucerne (for

fodder) in Wyoming is known for having a very small demand of pest control.

4.3.1.4 Maize – Iowa

As with lucerne the level of detail is very high and specific. In some isolated areas of treatment

the application rates can be quite high, exceeding 5kg/ha, yet on a state-based average the

application rate is large but not substantial54.


4.3.1.5 Oil Palm – Malaysia

The availability of specific data is limited and distinctly plantation based55. Typical figures for

pesticides as a whole are present, with suggestions that a large portion of the protection

originates from herbicides use. The rates are not particularly high, quite unlike the uncertainty.

4.3.1.6 Potato – Holland

As with grass a detailed study has been conducted per country and field type51. The potato uses

plenty of pesticides, especially in the form of fungicides and more decisively nematicides.

Throughout Europe but moreover in Northern Netherlands, the problem of Potato Cyst

Nematodes (PCN) is immense requiring excessive amounts of nematicide to control56. However,

since 1993 regulations have been installed that greatly limit the use of nematicides, yet on the

fields that are approved for treatment the levels are enormous. Nematode Control Strategies are

the under experimental phase to reduce the further usage, but are still under investigation. It is

conceivable that within a few years the levels will drop significantly.

4.3.1.7 Rapeseed – Belgium

Information regarding Belgian conditions have not been found, however German and Swedish

conditions have51, 57. As with grass and potato, the German conditions are narrowed to the

national average for the pesticide types regarding the rapeseed fields. It has been mentioned that

German and Belgian practices are analogous. The Swedish conditions are used only to confirm

the trend that herbicide consist the vast majority of applied pesticides. Rates are average.

4.3.1.8 Sorghum – Kenya

Kenya is poor in the sense of agricultural practices and is currently based primarily on small

family farms. There is no recorded data on the use of pesticides for sorghum in Kenya. It is

plausible that they are simply too expensive. Again this is a major cause for the low yields

compared to other regions and presents a large improvement possibility.

4.3.1.9 Soya Beans – Illinois

As with lucerne and maize the level of detail is very high and specific54. On a state-based average

the application rate is moderate.

4.3.1.10 Sugar Beet – Germany

As with other European countries, the German conditions are narrowed to the national average

for the pesticide types regarding the sugar beets plantations51. The application rate of herbicides

in particular is large but not substantial.

4.3.1.11 Sugar Cane – Brazil

The ease of obtaining pesticide information for Brazil is problematic as any available report is

written in Portuguese. However, general data has been collected for the use of herbicides and

insecticides58. The application rate of herbicides is fairly high, but improvement options have


been investigated and already hit the market (Bayer CropScience). All these factors combined

present a large uncertainty.

4.3.1.12 Sunflower – France

Data available for France is based on market share of the various types of pesticides51. This

presented the task of linking total consumption rate and cultivated area together to convert the

information. As it turns out the pesticide use is fairly low with an acceptable accuracy.

4.3.1.13 Switchgrass – Oregon

Switchgrass is one of the recommended bio-energy crops, partly chosen for its low cultivation

intensity. Since it is principally under investigation, broad averages are not yet available. Current

practices in Canada suggest moderately high use of herbicides59. However, precise data based on

fallowland farming in Oregon will be chosen as representative; necessitating low levels54.

4.3.1.14 Tobacco – Australia

Tobacco cultivation in Australia is in its infancy, yielding little valuable information. Cultivation

in America on the other hand is mature. Detailed information was complied to average out the

exact pesticides used on a national level54. It is noticeable that the application rate of insecticides

is very high, well above 10kg/ha. This is due to the fact that tobacco is a value added crop with

highly intense farming practices. When cultivated for biomass production the need for large and

healthy leafs is irrelevant, greatly reducing the pesticide use. However, based on the little

Australian data available it appears to be around 15kg/ha or even higher. The uncertainty of this

crop in the region is very high.

4.3.1.15 Wheat – France

Just as with the sunflower the available data is given as market share and was calculated back to

application rates using production statistics51, 60. What is noticeable is the dominant use of

fungicides, which is typical in Europe as local grains are prone to fungal infection. Rates are

average.

4.3.1.16 Willow Tree – Sweden

A detailed case study on a Swedish bio-energy willow production site was conducted, narrowed

down to specific chemicals indicating a high accuracy61. The application rate of herbicide is

surprisingly higher than expected of a perennial tree.

4.3.2 Results

For ease of comparison, due to the strikingly diverse level of detail, all the various application

rates have been tabulated for all the crops and expressed solely as kg/ha of total pesticides. The

following graphical representation best illustrates the differences amongst the various crops:


Figure 26 Pesticide requirements

Total

0.0

2.5

5.0

7.5

10.0

Cassava

Gra

ss

Lucern

e

Maize

Oil p

alm

Potato

Rapese

ed

Sorghum

Soya

bean

Sugar b

eet

Sugar c

ane

Sunfl o

wer

Switc

hgrass

Tobacco

Wheat

Willow

tree

kg/ha

Pesticide Requirements

15.5kg/h

a

15.0kg/h

a

There are clearly large deviations amongst the various crops, they range from 0 to just over

6kg/ha. Both the potato and tobacco require larger amounts of pesticide, but the arguments for

why this is the case was mentioned above. For the rest it is best left unsaid until related in terms

of energy input.



Based on the combination of the previous two subsections the calculation of the total energy and

exergy input of pesticides is possible. The following table lists the results:

Table 42 Resulting pesticide input energy

Total Energy Exergy

Common Name kg/ha

Cassava Africa Nigeria 0.1 36.4 38.4

Grass Europe Holland 1.0 318.4 338.7

Lucerne North America Wyoming 0.2 92.7 97.1

Maize North America Iowa 4.0 1348.0 1423.7

Oil palm South Pacific Malaysia 2.0 715.9 752.7

Potato Europe Holland 15.5 3686.3 3857.2

Rapeseed Europe Belgium 2.9 1017.6 1067.2

Sorghum Africa Kenya 0.0 0.0 0.0

Soya bean North America Illinois 1.3 556.6 593.0

Sugar beet Europe Germany 4.5 1609.4 1691.1

Sugar cane South America Brazil 5.1 1862.7 1954.0

Sunflower Europe France 1.4 523.0 547.6

Switchgrass North America Oregon 0.4 171.9 184.4

Tobacco South Pacific Australia 15.0 6222.4 6600.2

Wheat Europe France 3.4 932.1 977.8

Willow tree Europe Sweden 6.4 2103.1 2245.4

Pesticide Input

MJ/haLargest Producer

Crop Continent Country/Region


A graphical representation of the total energy correlation is better to visualize the figures. It is

noticeable that the relative differences between mass input and energy input do differ if only

slightly, but nevertheless justifying the additional workload necessary to avoid the one averaged

value assumption.

Figure 27 Resulting pesticide input

0

500

1000

1500

2000

2500

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Pot

ato

Rap

esee

d

Sorgh

um

Soy

a be

an

Suga

r bee

t

Sug

ar can

e

Sun

flower

Switc

hgra

ss

Tobac

co

Whe

at

Will o

w tr

ee

MJ/ha

Energy

Exergy

Pesticide Requirements

3.67GJ/ha3.86GJ/h

6.22GJ/h

6.60GJ/ha

Cassava and sorghum aside, it is the grasses (grass, lucerne and switchgrass) that require the least

amount of energy input. Not surprising the crops with the highest yield (maize, potato, sugar

beet, sugar cane) require the highest amount of pesticide energy input. Most probably the best

method to boast the production yield for cassava and sorghum is not through primary energy

inputs, but through the use of pesticides. The comparatively high input associated with the

willow tree production perfectly illustrates the affects when large scale biomass production is

implemented, maximized agricultural techniques to accelerate growth/yield, for wild variants

need none.

4.4.2 Efficiency

Precisely as with the other primary energy inputs it is misleading to visualize the total pesticide

input energy in terms of land without relating it to the resulting energy output. Relating the two

figures will result in the pesticide efficiency as indicated by the simple formula:

[ ]haMJInputPesticide

haMJOutputEnergeticEfficiencyPesticide

/_

]/[__ =

The following graph displays the resulting pesticide efficiency for the best practice yield:


Figure 28 Resulting pesticide utilization efficiency

Efficiencies

0

25000

50000

75000

100000

Cas

sava

Grass

Luce

rne

Mai

ze

Oil pa

lm

Pot

ato

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar c

ane

Sun

fl ower

Switc

hgra

ss

Toba

cco

Whe

at

Willo

w tr

ee


]

Energy

Exergy

Based on Pe st icide Proces Inp ut Ene rgy

7.3E5

8.3E5

2.1E5

2.5E5

1.0E5

1.1E5

1.0E5

1.1E5

As the energy input associated with pesticides is quite low compared to the energy output, the

efficiencies are manly above 25000%, meaning that the required pesticide energy only represents

an energy loss of 0.4%. The grasses have even larger conversion efficiencies (well above 60000%)

demonstrating the minor significance and influence of pesticides. This is the leading reason why

pesticides are generally overlooked or greatly simplified using, for example, the one averaged

value assumption. But the insignificance of pesticides does not pertain to all of the crops, as the

influence of the pesticides presents a noticeable energy loss in several of the crops. For instance,

the potato suffers a 1.5% energy loss due to pesticide application, which approaches the losses

associated to its nutrient input. The most extreme case is that of the willow tree, at 5832%

conversion efficiency an energy loss of 1.7% is present. That is only a few magnitudes smaller

than the influence of nutrients.


4.4.3 Analysis

Table 43 Comparative pesticide input overview

Crop Pesticide Requirements (energy) Pesticide Requirements (exergy) Common Name Input Efficiency Input Efficiency

Cassava + + + + Grass + + + + Lucerne + + + + Maize O O O O Oil Palm O + O + Potato - - - - Rapeseed O O O O Sorghum + + + + Soya Beans O O O O Sugar Beet - O - O Sugar Cane - O - O Sunflower O O O O Switchgrass + + + + Tobacco - - - - Wheat O O O O Willow Tree - - - -

Input: + below 0.5GJ/ha, - above 1.5GJ/ha, O between 0.5 – 1.5GJ/ha Efficiency: + above 50000%, - below 10000%, O between 10000 – 50000%

Any crop with a negative sign in the efficiency category should be paid special attention to. Those

crops have a pesticide intensity that can influence the overall positive energy gain.


5 Results and Discussion The top 3 choice crops for each category will be handled separately along with the total result for

the entire group “primary energy inputs” in terms of energy to material production.

Nutrients, in the form of fertilizers, by far constitute the largest portion of the energy demands of

the primary energy inputs. The values expressed in this chapter represent the actual plant uptake

levels and not the typical application levels. The differences between the two are the losses and

being most dependent on farming techniques will be covered in the following chapter.

Table 44 Top 3 crops on low nutrient/fertilizer demand

Energy Exergy Nutrient Efficiency (Input/Output)

Top Crops GJ/ha Energy Exergy

1. Soya Bean: 0.98 Soya Bean: 3.48 Soya Bean: 19001 Sugar Cane: 10677 2. Sugar Cane: 3.60 Sugar Cane: 4.26 Sugar Cane: 10555 Soya Bean: 6226 3. Lucerne: 11.9 Lucerne: 13.8 Oil Palm: 5580 Oil Palm: 5620

The clear advantage of the legumes requiring less supplementary nitrogen and thus less relative

energy demand can be seen in the list. All the crops, save oil palm, have to various degrees

bacterially fixed nitrogen. For soya bean 100% of the nitrogen demand is covered by inoculation

and sugar cane is up to 90% due to companion species. Generally speaking legumes will always

require less fertilizer input energy as nitrogen is so much more costly to manufacture than the

other nutrients. For point of illustration the top 3 crops of a non-leguminous nature have been

investigated separately. They differ by several magnitudes.

Table 45 Top 3 crops on low nutrient/fertilizer demand (non-leguminous)

Energy Exergy Nutrient Efficiency (Input/Output) Top

Crops GJ/ha Energy Exergy

1. Willow Tree: 12.2 Willow Tree: 13.8 Oil Palm: 5580 Oil Palm: 5620 2. Oil Palm: 13.1 Oil Palm: 14.5 Sorghum: 3204 Sorghum: 3463 3. Potato: 13.3 Potato: 14.7 Maize: 2831 Maize: 2995

Crops with the best water conditions need neither irrigation nor drainage. There is no placement

for those particular crops as they score equally well, and the best achievable is zero energy/exergy

input. Of the crops investigated 1 has absolutely no and 2 have close to no water requirements:

sorghum, rapeseed and switchgrass. Several other crops also have no or little water requirements

under normal conditions, but when aiming for best practice yields (or water demand) do. They

are: cassava, grass, maize, oil palm, sugar beet, tobacco, wheat and willow. All of these crops are

essentially rainfed crops in the set regions.

Although, as just mentioned, many of the crops have zero energy demand in the form of water

requirements a similar story holds for the pesticide inputs. Cassava and sorghum both have

practically no pesticide requirements, not because they do not need them but because the

particular region of cultivation is impoverished and cannot afford the additional burden of crop


protection measures. This is not realistic when speaking of creating a chemical feedstock. Should

cassava and/or sorghum be realised the yields will dramatically increase with the addition of

pesticides. The other crops however already represent more or less expected figures. In some

particular cases, like that of the potato in Holland, government regulation is the major stipulation

for change and can be expected to swing future application levels. But compared to the nutrients

and water the levels are still quite low, i.e. terms are MJ and not GJ.

Table 46 Top 3 crops on low pesticide demand

Energy Exergy Pesticide Efficiency (Input/Output)

Top Crops MJ/ha Energy Exergy

1. Lucerne: 92.7 Lucerne: 97.1 Lucerne: 2.16⋅105 Lucerne: 2.46⋅105 2. Switchgrass: 172 Switchgrass: 184 Oil Palm: 1.0⋅105 Oil Palm: 1.08⋅105 3. Grass: 318 Grass: 339 Grass: 6.50⋅104 Grass: 7.29⋅104

It is noticeable that the grasses all require the least amount of pesticides, understandable as they

are low maintenance crops. At those efficiency rates, an energy loss of less than 0.5% is achieved

and is in affect lower than the inaccuracies of the yield figures; basically negligible. This is true for

practically all of the selected crops, yet for some pesticides are a significant input.

In chapter 4 the term land use efficiency was employed to indicate the relationship between the yield

and the incoming solar radiation; affectively compiling the land requirements for material

production. The same procedure can be performed in regards to the primary energy inputs. By

relating the dry weight yields and total primary energy input an “energy use efficiency” is created with

the same unit, g/GJ. This indicates the energy requirements for material production.

Figure 29 Primary energy use efficiency

Energy Use Figures

0.0E+00

5.0E+05

1.0E+06

1.5E+06

2.0E+06

2.5E+06

Cass

ava

Gra

ss

Lucern

e

Maiz

e

Oi l

palm

Pota

to

Rap

eseed

Sorghu

m

Soya b

ean

Sugar

beet

Sugar c

ane

Sunflower

Switc

hgrass

Tobacco

Whe

at

Will o

w t r

ee

g/GJ

Energy

Exergy

Based on Dry Weight Figures and Primary Energy and Exergy

6.3E6

5.5E6


The crops with a biological symbiosis perform relatively well in terms of low associated nutrient

uptake energy demand. Yet as can be seen in the graph the others factors, primarily water, reduce

the overall benefit to the point of only having one crop in the top 3. And in fact, sugar cane is

not even truly a legume but is sown together with leguminous plant residues. This clearly

illustrates the fact that the benefits of one input, regardless of how large, cannot be used as an

indicator for the whole. Local constraints, in this case water has a large impact of the overall

energy demands but generally the nutrient input dictate the primary input demand.

Table 47 Top 3 crops on energy use efficiency

Energy Exergy

Top Crops g/GJ

1. Sugar Cane: 6.27⋅106 Sugar Cane: 5.53⋅106 2. Oil Palm: 2.49⋅106 Oil Palm: 2.27⋅106 3. Sorghum: 2.20⋅106 Sorghum: 2.00⋅106

The energy use efficiency term will be transferred to each proceeding section to create the overall

indication of the best choice crop. It will determine the highest exergetically and energetically

efficient crop in relation to material production and finally to chemical production. As solar

radiation is handled in terms of land demand, this energy use factor will present a term for fossil

energy demand. This chapter covered the primary energy inputs and only in combination with

the follow chapters, the secondary (farming procedures) and bioprocessing energy inputs, can

solid conclusions be drawn. Nevertheless, it is noticeable that several crops perform already fairly

bad on this intermediary energy use section, rendering the success of large scale implementation

for those crops highly improbable. They are namely lucerne, rapeseed, sunflower, wheat and

willow. The crops themselves are not necessary poor or unsuitable, for the regional influences are

the route cause. Lucerne (or the Midwest) and the sunflower (or Southern France) both rely a

very costly forms of irrigation. Cultivation in another region might possibility alleviate the stress

on water demand while attention must be paid to the change of the other factors; the potential of

the crops is not yet fully ruled out.

In the realm of primary energy input the distinct leader is the sugar cane. This is mainly attributed

to the common practice of mixing leguminous green manure with the plantation, accounting for

up to 70% nitrogen fixation. This corresponds to 23.5kg/ha and indeed typical Brazilian

application rates are 0-50kg/ha. The blunt of the primary energy inputs are embodied by the

nutrients and legumes are an effective method to reduce the cost. There is a trade off, however,

for absolute yields and thus land use efficiency is sacrificed. Denoting that in areas with limited

land, the cost saving option of using legumes should be avoided or carefully assessed.



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bin/byteserver.pl/archive/upload/uhde_brochures_pdf_en_3.00.pdf file:///M:/Reports/Fertilizer/Uhde%20-%20Nitrate.pdf 14. European Fertilizer Manufacturers' Association (EFMA) Booklet No. 5 of 8: Production of Urea

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Kansas, 1999; p 4. 47. Rogers, D. H.; Lamm, F. R.; Alam, M., Efficiencies and Water Losses of Irrigation Systems.

In Irrigation Management Series, Kansas, 1997; p 6.


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49. Wateright Energy Use/Costs for Pumping. http://www.wateright.org/site2/advisories/energy.asp

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cropping system. Biomass & Bioenergy 2003, 25, 147-165.



Chapter 6 Secondary Energy Input

Required energy and exergy involved in agricultural practices, storage, pre-processing and

transportation of biomass

Ben Brehmer

Dissertation Report


Colophon



ISO 9001:2000.

Title Chapter 6 – Secondary Energy Input Author(s) Ben Brehmer A&F number - ISBN-number - Date of publication 6. September, 2007 Confidentiality No OPD code - Approved by - Agrotechnology & Food Sciences Group B.V. P.O. Box 17 NL-6700 AA Wageningen Tel: +31 (0)317 475 190 E-mail: [email protected] Internet: www.afsg.wur.nl © Agrotechnology & Food Sciences Group B.V. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch, hetzij mechanisch, door fotokopieën, opnamen of enige andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. De uitgever aanvaardt geen aansprakelijkheid voor eventuele fouten of onvolkomenheden. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher. The publisher does not accept any liability for inaccuracies in this report.


Abstract The modern mechanized cultivation of biomass requires significant energy and material inputs

from a multitude of different sources and forms. Seen from the cradle-to-grave they can be

separated into direct (prime) and indirect (secondary) energy and material streams. Those

indirectly attributed to biomass growth are covered within this chapter; namely farming

procedures, transportation and storage operations and pre-processing and drying techniques.

Farming is based on the employment of tractors and other self-propelled machinery to perform

one of four basic field procedures; tillage, planting, soil treatment and harvesting. Several of the

most commonly occurring procedures within the groups are investigated based on the implement

parameters, field capacity and diesel consumption. The assessment is separated into two regional

categories, developing and industrialized, to represent the energy intensity differences of the

corresponding crop cultivation practices in the selected regions. The indirect fossil fuel input for

manual labour was also calculated for the two different regions and used to determine the

machinery operation as well as any foreseen separate manual farming procedures. A systematic

approach was used to link the selected procedures for the various regions to the crops under

investigation. The amount of energy and exergy required to transport a certain tonnage of

harvested biomass over a kilometre was calculated for tractor, truck, train, inland barge and sea

vessel transportation systems. As with the farming procedure a differentiation was made between

the regions and their relative requirements. The Port of Rotterdam is chosen as the central

destination point to satisfy the European chemical industry and marks the grave of the LCA

scope. In between each mode of transportation material handling and in many cases storage is

necessary. Storage and transfer energy demands are based on those systems commonly in place to

handle the biomass feedstocks and used between the different transportation modalities. To

reduce transportation and distribution costs densification options were investigated including

cutting, crushing and various forms of drying operations. After careful assessment for each of the

regionally based crops an optimal logistical network system was stipulated using the trade-off

relationship between the transportation and preprocessing procedure requirements. All of the

input figures have been set against the resulting energy output of each crop to determine and

compile an overall efficiency comparison as was previously conducted in the two preceding

chapters. The secondary energy input is the combination of the farming and logistics systems

results and when further combined with the primary energy input leads to the total agricultural

input energy demand. Combined the value represents the total biomass feedstock cost from

cradle-to-chemical factory gate, inducing a total energetic material loss of 15 – 60% of the crops

calorific value.

Key Words:

Biomass, Farming Procedures, Transportation, Logistics, Drying, Energy, Exergy



Content

1 Introduction 225


2 Input Types 227

2.1 Preface 227


2.1.2 Industrial Considerations 227

2.1.3 Regional Considerations 228

2.2 Labour Costs 229

2.3 Farm Equipment Costs 230

2.3.1 Tractor 230

2.3.2 Tillage Implements 232

2.3.2.1 Plough 233

2.3.2.2 Cultivator 233

2.3.2.3 Harrow 233

2.3.3 Planting Implements 234

2.3.3.1 Drill 234

2.3.3.2 Row Crop Planter 235

2.3.3.3 Cuttings Planter 235

2.3.3.4 Tuber Planter 235

2.3.4 Soil Treatment 236

2.3.4.1 Fertilizer Spreader 236

2.3.4.2 Pesticide 236

2.3.5 Harvesting 237

2.3.5.1 Combine Harvester 237

2.3.5.2 Forage Harvester 237

2.3.5.3 Tuber Harvester 239

2.3.6 Trailer Transportation 240

2.4 Transportation Costs 241

2.4.1 Heavy Goods Vehicle (Truck) 242

2.4.2 Train 244

2.4.3 Inland Barge 246

2.4.4 Sea Vessel 247

2.5 Storage and Transfer Costs 249

2.5.1 Storage Description 249

2.5.1.1 Transfer Points 250

2.5.2 Loading/Unloading Equipment 251

2.5.2.1 Wheel Loaders 251

2.5.2.2 Conveyors 251

2.5.2.3 Stacker/Reclaimer 252


2.5.2.4 Crane 253

2.6 Pre-processing and Drying Costs 253

2.6.1 Size-Reduction 254

2.6.1.1 Cutting 255

2.6.1.2 Crushing and Shearing 256

2.6.2 Moisture Reduction 257

2.6.2.1 Natural Air Drying 258

2.6.2.2 Filter Press Dewatering 258

2.6.2.3 Conveyor Belt Drying 259

2.6.2.4 Rotary Drum Drying 259

2.6.2.5 Silo/In-Bin Drying 260

2.6.2.6 Exergy and Energy Efficiency 260

2.6.3 Compaction 261

2.7 Manufacture, Transport and Repairs (MTR) 261

2.7.1 Manufacturing Energy 261

2.7.2 Transport Energy 262

2.7.3 Repair Energy 262

2.7.4 Farm Equipment MTR 263

2.7.5 Transportation and other equipment MTR 263

2.8 Overview Input Type Costs 264

3 Farming Operations 267

3.1 Machinery Employment 267

3.1.1 Operational Labour Requirements 267

3.1.2 Cultivation Practice Factors 268

3.2 Labour Employment 268




3.3.3 Analysis 271

4 Biomass Logistics 273

4.1 Rotterdam 273

4.2 Distance to Rotterdam 274

4.2.1 Starting Point 274

4.2.2 Mode of Transport 275

4.2.2.1 Road 275

4.2.2.2 Rail 275

4.2.2.3 Inland Waterways 275

4.2.2.4 Ocean 275

4.2.3 Topography 276

4.2.4 Resulting Distance and Mode of Transportation 276


4.3 Size and Moisture Reduction 277

4.3.1 Transfer and Storage Systems 278

4.3.2 Balancing Size and Moisture Reduction and Transport Energy Costs 279




4.4.3 Analysis 282


6 Total Agricultural Energy Input 287

6.1 Graphical Overview 287

6.2 Results and Discussion 289

6.3 Individual Regional Crop Explanations and Recommendations 290

References 293



1 Introduction In the previous chapter much stress was placed on the importance of supplying sufficient

nutrients via artificial fertilizers to promote the high yields associated with modern agricultural

practices. Indeed water, carbon dioxide, solar radiation, pesticides and fertilizers have a direct

impact on the agriculturally harvestable yields. Farming techniques, cultivation methods and

other mechanized agricultural practices on the other hand facilitate the optimal use of those

growth determining inputs. And in many instances the intensity of modern agricultural practices

is visualized by a large combine harvester rather than a sack of fertilizer.

True, diesel is needed to operate tractors and the other agricultural machinery involved in

modern agricultural practices and when related back to the primary fossil fuel energy content

does place a large energy intensity on the overall farming operations. It is especially common in

areas of moderate sunshine for seasonal crops to heavily rely on agricultural machinery to

maximize the yield potential. “Working the land” and “harvesting the fruits of labour” are beginning to

take new meaning as the only manual labour is hooking the proper implements to the tractor. In

newer tractors outfitted with GPS guidance and sensory assistance driving has even become a

quest of programming skills. In fact, all aspects and inputs of modern agriculture have a fossil

fuel source alluding at the notion that the industry is converting oil products into food products.

Achieving the lowest agricultural energy intensity respective to the energy content of the yielded

harvest must be seen as a primary prerogative for supplying feedstocks to the biobased sector.

Many of the potentially highest yielding crops are cultivated in regions of the world that take

advantage of ample and yearly distributed solar radiation and precipitation. These “tropical”

regions have a highly underdevelopment agricultural sector involving manual labour for the bulk

of their harvesting operations. And feeding fieldworkers requires only a minor amount of indirect

fossil fuel energy; operating a combine harvester for one hour is roughly equivalent to

contracting 200 man-hours of developing world fieldworkers. As unmoral as the wide scale

exploitation of underdeveloped workers may appear, it also presents a paradox as those regional

practices and crops promote the potentially highest fossil fuel energy savings. Yet as high as these

local potential energy savings and higher yields are, they must be counterbalanced with the

logistical cost of intercontinental transport.

Fresh biomass is alive and so long as sufficient water is contained in the biomass nature is free to

take its course, reducing the yields through digestion and decomposition. If there is one thing

long-haul transportation of biomass is, it is a time consuming process caused by long travel time

and long layover times. Time enough to promote the decay of fresh biomass. The obvious

solution to preserve the biomass over the entire logistical chain ensuring a high deliverable yield

is to reduce the moisture content. The food industry has done well to market the benefits of

dried foods with the preparation instructions boldly stating “easy - just add water”, despite the

underlining corporate benefits of lower transport costs and longer storage life. Drying biomass,


like food goods, is still an energy intensive process and can for particular systems be the most

energy intensive portion for feedstock acquisition.

Along with biomass moisture reduction, size reduction procedures will increase the net bulk

density of the biomass facilitating less transportation loads. Capacities of the different transport

modalities are limited by either weight or volume but for feedstock material the actual deliverable

weight is all important. A dried and size reduced material will provide more deliverable feedstock

per load than fresh biomass. As many size reduction techniques necessitate a dry input material,

size reduction and moisture reduction procedures are essentially performed in combination.

Combined the procedures are considerably energy intensive and should be balanced to the energy

saved through less frequent transportation shipments.

International shipping has never been so cheap and efficient as it is today, yet it still remains an

energy intensive industry primarily based on fossil fuels, chiefly various grades of diesel. The

chemical industry is comprised of factory clusters situated in areas of high industrial activity with

an accompanying distribution network in a select few locations around in the world. Rotterdam is

the central hub for the European chemical industry. Biomass on the other hand is cultivated and

harvested in areas scattered across the globe; partly grown in the direct hinterland and partly

overseas. Transportation will always be an inevitable and unavoidable energy intensive

component of acquiring a biomass feedstock. Where the locally grown biomass in the temperate

regions may be burdened with high farm related inputs, the imported biomass is burdened with

high logistical inputs.

The summation of the previous chapters primary energy inputs with the inputs related to the

farming procedures, the moisture and size reduction techniques, and the transportation network

results in the total agricultural energy and exergy input to supply a biomass feedstock to the

chemical industry for each crop in the respective region.

1.1 Chapter Purpose

In the following chapter all the secondary inputs will be calculated and expressed in a

comparative form for the previously selected crops. The values mentioned herein are based on a

straightforward energy/mass balance in excel, thermodynamic conversions, and energy relations

to obtain the exergy values. This chapter is the second of three energy input categories required

for the creation of chemicals from biomass. Primary, secondary and process energy inputs will all

be addressed independently from solar energy. The combination of the primary and secondary

energy inputs are used to compile the total agricultural energy input as a feedstock cost.


2 Input Types

2.1 Preface


Although a partly a conjecture it is widely accepted that, as a species,

humans (Homo sapiens) have existed for around 200000years and the

earliest African fossil findings date back to 130000years. In the beginning

humans were nomadic hunter/gatherers struggling to nourish themselves

adequately; life revolved around acquiring food. Between 7000-9000BC

marks the Neolithic Revolution, when in the Fertile Crescent the

domestication of crops and animals is thought to have begun. This first

agricultural revolution was brought on by the depletion of biological

potential (food) through the hunter/gatherer practices for an ever

increasing population. Initially converting forests to pastures by slash-and-burn practices the

population densities flourished leading to an agrarian based life-style. The land cultivation could

continue for 2 years before the nutrients became depleted and needed to be returned as fallow.

Successful systems required a minimum of 2 hectares of cultivated land per person and 10

hectares of land to supply the cultivated land. Land use may have been high but energy input

however was low, being directly coupled to manpower with simple tools. By the point of wide

spread maize cultivation 1144hours of labour (or 60% total adult labour output) was required per

hectare1. This meant that life still revolved around acquiring food. The first major reduction in

energy and land use intensity was by implementing the animal draft. Oxen and horse drawn

ploughing systems reduced the land intensity from 10ha/person to 4. Gradual improvements in

agricultural practices allowed for an ever smaller percentage of the population to labour on the

fields and facilitated the development of a civilization which in turn led to further improvements

on land use efficiency and manpower reduction.

2.1.2 Industrial Considerations

In the 10000 years since the Neolithic Revolution the agricultural sector has seen many changes,

improvements and revolutions that have further reduced the land use intensity (i.e. higher yields)

and manual labour requirements. Probably the single

most important invention in reducing manual labour

was the (steam) tractor. Introduced in 1840, over the

course of 100years the transition from animal draft

to machinery was nearly complete (for the

industrialized world). Currently in a modern highly

intensive maize field less than 10hours of manual

labour is required per hectare2. Agricultural activity is

now located in areas of a low population density.

And with the advent of low cost international Steam tractor and gang plough, 1916


transport excess biomass/food can be shipped and sold anywhere in the world. All of the

improvements to maximize the crop yields with the least amount of labour and subsequent

distribution to highly populated areas require fossil fuel energy. Along the production and

distribution chains diesel is needed to operate the tractors, fuel the trucks, trains and ships and

other forms of indirect fossil fuel energy is also inherently involved. The agricultural sector has

transformed from a highly labour intense sector to a highly fossil fuel intense sector.

Cultivation practice and biomass logistics are as diverse as the crops and regions where they are

cultivated. Determining the life cycle energy input of the chains first requires a breakdown of the

components involved in the regions of activity. Each secondary input form will be assessed

separately to be able to create a matrix for the 16 choice crops.

2.1.3 Regional Considerations

The selected regions for the crops under investigation are diverse, scattering the world. Yet, they

can be grouped into two general categories, industrialized and developing. The industrialized

world has many names; like developed, rich, western, advanced or

more commonly the 1st world nations. The OECD (Organisation for

Economic Co-operation and Development) is an international

organisation of those developed countries that accept the principles of representative democracy

and a free market economy. Categorizing the industrialized and developing regions will be based

on OECD membership or not. The following table lists the crops and corresponding regional

category based on OECD membership:

Table 1 Crops choice with regional development category

Botanical Nomenclature Common Name Continent Country/State Development Category

Beta vulgaris Sugar beet Europe Germany Industrialized

Brassica napus Rapeseed Europe Belgium Industrialized

Elaeis guineensis Oil palm South Pacific Malaysia Developing

Glycine max Soya bean North America Illinois Industrialized

Helianthus annuus Sunflower Europe France Industrialized

Manihot esculenta Cassava Africa Nigeria Developing

Medicago sativa Lucerne North America South Dakota Industrialized

Nicotiana tabacum Tobacco Oceania Australia Industrialized

Lolium perenne Grass Europe Holland Industrialized

Panicum virgatum Switchgrass North America Iowa Industrialized

Saccharum officinarum Sugar cane South America Brazil Developing

Salix alba Willow tree Europe Sweden Industrialized

Solanum tuberosum Potato Europe Holland Industrialized

Sorghum bicolor Sorghum Africa Kenya Developing

Triticum aestivum Wheat Europe France Industrialized

Zea mays Maize North America Iowa Industrialized

The agricultural practices and tools/machinery employed differ heavily in the industrialized and

developing world. On a global scale, still 40.7% of the world population is involved directly in


agriculture (i.e. farmers) yet only represent 4.0% of the total GDP. In highly advanced societies,

like Holland, no more than 2% of the population are farmers providing slightly more than 2% of

the GDP3. This illustrates perfectly well the differences in practice and efficiency, especially in

terms of manual labour. For all the individual input types both the common industrialized

representative types with a leaning to best available technology (BAT) and common developing

representative types will be investigated. It is however foreseeable that with large scale financial

investment in biomass cultivation practices adopting efficient industrial practices will be

employed even in the developing world.

2.2 Labour Costs

A worker labouring on a field for biomass production has two sources of energy input. One is

the energy associated with food uptake and the other is the indirect fossil fuel consumption based

on the standard of life. A worker in an industrialized world will both eat more and consume more

luxuriously to sustain the higher quality of life.

Firstly, assigning the calorific food uptake value directly to fossil fuel demands is fundamentally

wrong. For example, the calorific value of a loaf of bread is 10.3MJ/kg whereas following a full

LCA yields between 4.0 – 9.0MJ/kg with 0.01 – 18.6MJ/kg additionally for the mode of

transportation involved in the purchase4. Bread is a simple product. Another detailed LCA study

pertained to the cumulative energy demand (CED) of a typical Swedish meal5. The typical meat-

based meal (containing 100g meatballs (50/50 beef/pork), 160g potatoes, 36g bread, 60g carrots

and 200g milk) requires, regardless on the preparation method involved, around 9.4MJ/meal. The

calorific value of the meal itself is however 3.5MJ, which indicates a factor of nearly 3. For exotic

foods, like fruits and off-season commodities, the CED will further increase. And one of the

oldest studies in the field used a factor of 6.8 to account for the sequestered energy in the food

chain6. The recommended daily food intake as dictated by the EU is 11.4 and 9.1MJ/day for an

adult male and female, respectively. In the modern industrialized societies both men and women

perform for the large part the same occupations and can both work equally well in the

agricultural sector. Sweden’s typical meal will be used as a norm for all industrialized regions,

meaning the total fossil fuel input related to food intake is set at 30MJ/day. The recommended

daily food intake were set for an individual with moderate physical activity and are not

representative of the harsher conditions faced by a developing world farmer. An adult male field

labourer doing highly physical work will require considerably more energy, at 16.8MJ/day. The

fossil fuel energy involved in cultivating, collecting and preparing a typical developing world meal

is lower than that of the industrial region, considering the heavy reliance on man power and

biomass fuel. And as the transportation and acquisition of the food is generally not per truck or

car that relative energy component approaches zero. Simple meals based on the local food

availability (like beans, cassava, jatropha, fruits, etc.) will approach a ratio between input and

calorific output similar to the bread example, meaning around 60%. Thus the total fossil fuel

input related to food intake for a developing region farmer is set at 10MJ/day.


The second aspect revolving around the energy input of a labourer is the indirect energy

associated with the lifestyle. Lifestyle support energy varies considerably per region depending on

the standard of living as measured by products and services consumed in relation to fossil fuel

energy. A farmer in the industrialized regions, being an average member of society, will use the

average amount of fossil energy common for the developed world. A farmer in the developing

regions however, is better described as adhering to the poorest 10% of the world. Following a

recent Science article the average person in the developed (industrialized) world consumes nearly

40barrels of oil equivalent and residents of the poorest 10% consume 1barrel per year7. A single

barrel of crude oil (at 0.853kg/l and 44.9GJ/ton) contains 6.09GJ. Thus an industrialized farmer

and a developing world farmer have an indirect fossil energy cost of 603MJ/day and 16.7MJ/day,

respectively. Compared to the costs attributed to the food consumption, it is clear that

supporting the lifestyle of the industrialized farmer is around 20-fold that of the direct energy

involved in nutrition whereas the developing farmer is less than 2-fold. As no data is available in

terms of exergy for these systems a factor of 5% will be added; the energy-to-exergy ratio of

crude oil. The following depicts the contrast between the labour cost for the industrialized

regions and developing regions both visually and numerically.

Figure 30 Labour costs in developing and industrial regions

Developing Regions Industrialized Regions - Primarily manual labour farming - Primarily mechanized farming

- Food fossil fuel input: 10MJ/day - Food fossil fuel input: 30MJ/day

- Lifestyle fossil fuel input: 16.7MJ/day - Lifestyle fossil fuel input: 603MJ/day

- Total fossil fuel input costs: 26.7MJ/day - Total fossil fuel input costs: 633MJ/day

2.3 Farm Equipment Costs

2.3.1 Tractor

The primary purpose of agricultural tractors is to perform drawbar work. The origins of the word

tractor reflect this, being a combination between the noun tractus (to pull or draw) and the noun

motor (self-powered movement). Drawbar power is defined by pull (or historically called draft)

and travel speed. The efficient operation of farm tractors has three factors:

1. Maximizing the engine fuel efficiency and mechanical drive train efficiency


2. Maximizing the traction device

3. Optimizing the travel speed

In modern agricultural practices practically all steps in the cultivation and harvesting

of crops is derived from employing tractors. The so-called PTO (Power Take-off)

unit provides power to the specific equipment attached to the tractor both front

and/or back, meaning that the operational costs for each crop specific farm

procedure is a function of the tractor. The sole direct energy input of a tractor is diesel fuel as in

the last 25 years only a select few tractor engines have been outfitted with another fuel type. The

diesel fuel consumption of a tractor is based on several

factors, although mainly engine efficiency, operation

conditions and procedures are influential. Tractor

manufacturers supply two key technical specifications needed

to calculate the fuel consumption, namely the rated power as

a function of rated engine speed (kW/rpm) and the specific

volumetric fuel consumption (SVFC) given in g/kW⋅h. In the adjacent illustration the rated power versus the rated engine

speed can be seen for a modern tractor. Under low drawbar

power requirements (like positioning or street travel) the grey

trends apply whereas under high drawbar power requirements (like ploughing) the blue/upper

trends apply. For a farmer it is important to have a tractor that can deliver the needed power to

perform the task at hand. Each operational tool/attachment has a tractor power level for the

particular operation, calculated to kW. SVFC for diesel engines typically range from 0.244 –

0.57l/kW⋅h (0.202 – 0.472g/kW⋅h)8. Simply multiplying the tractor power requirements with the SVFC and the relative field capacity will yield the diesel fuel consumption. The first step is the

selection of representative tractors for the industrialized and developing regions and the

corresponding specifications. Data is based upon two tractor specification sheets9. Take

particular notice to the two graphs outlining the power and the fuel consumption as function of

the rated engine speed (kW/rpm and g/kW⋅h/rpm).

Industrialized Region To represent the near future best practices a recent (2001)

highly fuel efficient tractor model in the mid/upper power

range was selected.

New Holland TM-16510 - MWD (mechanical front wheel d rive)

- Nominal Power & Engine Rotation: 107kW @ 2300rpm

- Maximum Power & Engine Rotation: 110.6kw @ 2160rpm

- Total Weight: 6600kg

- Speed Range: 2.27 – 40km/h, 13.6km/h @ max power

- SVFC: 251g/kW⋅h, 262g/kW⋅h @ max power

- Slip factor: 16.4% under typical soil conditions


Developing Region Throughout the world one, if not the most popular and most

sold tractors is the Massey-Fergusson MF200 series. It is a

hallmark in p roven strength, quality and low-costs.

Massey-Ferguson MF24011 - 2WD

- Nominal Power & Engine Rotation: 32kW @ 2250rpm

- Maximum Power & Engine Rotation: 26.2kW @ 175rpm

- Total Weight: 1730kg

- Speed Range: 1.6 – 30km/h, 5.8km/h @ max power

- SVFC: 273g/kW⋅h, 328g/kW⋅h @ max power

- Slip factor: 18.7% under typical soil conditions

Reports from the Nebraska Tractor Test Laboratory (NTTL) was used to compile an excel

spreadsheet comprising of a database with 700 tractors, 12 major and 7 minor tillage and 12

seeding farm equipment attachments12. Furthermore the German Department of Agriculture

(DLG) has an online database full of tests listing the detailed technical data for essentially all

farming procedures13. In both sources the New Holland TM-165 and Massey Ferguson MF240

(MF340) tractors were included. The NTTL spreadsheet has been developed to calculate the

tractor performance under various conditions and settings for common farm procedures using

the attached equipment (referred to as implementations). Amongst the considerations are tire size,

travelling speed, weight distribution, tractor configuration and terrain conditions. Three different

soil types can be chosen based on the so-called cone index (tear strength measured in pressure).

Good soil (having a cone index of 1725kPa) will be set for industrial regions and medium grade

soil (cone of index of 860kPa) is set for the developing regions. The dimensions and operating

conditions of the implements are calculated for the general tractor settings of the two. Important

resulting estimations are operating depth, operating width, field capacity, draft force, drawbar

power and of course fuel consumption8. For the implements not included in the NTTL

spreadsheet the specific manufacturer and DLG online database will be used to determine the

fuel consumption. The manufacturers of the tractor attachment tools and self-propelled farm

machinery frequently supply the PTO equivalent requirements per set dimension (kW/m width).

Also listed for each implement procedure is the “field efficiency” which, is understood as the

proportion of time actually performing the task. Positioning and turning time, street travel, idle

and general down time all contribute to lower the field efficiency. Field efficiency is found in the

NTTL spreadsheet and in the collection of life cycle assessment data pertaining specifically to

utilities vehicles from the IFEU Institute for Energy and Environment14. As there are a wide

variety of very specific implements they will be grouped together following a generalized

procedural category and calculated for both industrial and developing region capacities.

2.3.2 Tillage Implements

The first step in biomass production systems is the preparation of the land to accommodate the

cultivation of crops, called tillage. There are three major tillage tool classifications, namely

ploughs, cultivators and harrows. The PTO equivalent requirement is used by the farmer to


optimize the size of the ordered attachment tool based on the tractor specifications. Listed are

the parameters and explanation for the three major tillage tools12, 15:

2.3.2.1 Plough

Ploughing has several beneficial effects and is common in almost all agricultural practices.

Originally ploughs were used to break up and turn over the upper layer of the soil adding the

previous crop residue into the soil. Deep ploughing will also mix the subsoil with the topsoil to

promote an even distribution of organic content. The method will reduce the prevalence of

weeds, loosen and aerate the soil creating a porous structure promoting the ease and success of

subsequent planting. Over the long term many disadvantages have arisen including loss of

organic content and erosion. A chisel plough was developed which like the mouldboard plough

will aerate and loosen the soil but will not invert or turn the soil over. This characteristic is a part

of the no-till and limited tillage farming, heading towards more sustainable agricultural practices.

Substantial power requirements are needed for the deep chisel plough:

Chisel Plough - Specific Type: 2-in straight point

- Operation Speed: 6.5 – 10.5km/h

- Field Efficiency: 70 – 90%, set: 85%

- Capacity: 1.41ha/h (TM165), 0.37ha/h (MF240)

- Fuel Usage: 24.11l/ha (TM165), 22.03l/ha (MF240)

2.3.2.2 Cultivator

Similar to a plough a field cultivator breaks up, stirs and pulverises the soil. It is common as a

secondary tillage operation, preceding the plough as the depths and forces involved are much

lower. In some cropping layouts it is however employed as the primary tillage unit. It will further

aerate and loosen the soil mitigating the problems associated with compacted soil. It works by

dragging a series of small pikes along the field.

Field Cultivator - Specific Type: secondary tillage





2.3.2.3 Harrow

A harrow is also a secondary tillage unit used to cultivate the top surface of the soil. It is strictly

employed after a field plough to break up the clods and lumps created by the ploughing. Basically

it provides the fine finish to the top soil, sometime referred to as a “good tilth”. The most

common form of the harrow is the disk harrow and several systems combine a disk harrow and

field cultivator into one implement unit.


Harrow - Specific Type: single disk gang, secondary tillage





2.3.3 Planting Implements

Upon completion of the tillage operation the seeds can be sown into the land. The starting

material for the propagation of crops is however not always in the direct form of a seed and the

size can also vary considerably, although all forms are referred to as seed material. There are three

major classifications of starting material; a true seed (like grass seeds), a seed covered in a husk or

shell (like sunflower seeds) and a pre-grown stub or cutting of a plant (like cane setts). The

implements for the planting procedure are very crop specific and depend heavily on the form of

plantation and growth system employed. The following implements cover the types required for

the 16 chosen biomass crops.

2.3.3.1 Drill

Carried in a large distribution tank small seeds are sent through a series of tubes to be drilled into

the soil. The distance between injections and row spacing is exact to maximise the seeding rate

with the desired growth conditions. There is a wide variety of seed drill techniques and in many

cases the seeds are mixed or pre-laced with fertilizers and pesticides. Within the drilling

implements there are two major types, those designed especially for grain seeds (like wheat) and

those designed for a more universal application. The grain drill is typically accompanied with

press wheel rollers to cover and compact the soil after seed injection. It is significantly faster than

the pneumatic drill which in turn increases the field capacity and decreases the fuel usage.

Grain Drill - Specific Type: with press wheel





Drill - Specific Type: pneumatic (airseeders)






2.3.3.2 Row Crop Planter

Similar to the drill procedures, seeds are injected into the soil based on the desired position. The

depth of the injected seeds is less, being only a few centimetres below the surface, speeding up

the process. Again it is common for the seeds to be mixed with the necessary fertilizers and

pesticides for early emergence. One clear difference however, is the layout of the implement

being much broader allowing for a faster field operation resulting in an even lower fuel usage.

Row Crop Planter - Specific Type: drawn





2.3.3.3 Cuttings Planter

Several crops are planted not as seeds but as portions of the previous season’s mature crop. The

cuttings are shaved of any branches and leaves and sized to the desired length to include the

largest portion of dormant plant material. The planted biomass can be referred to as setts, whips,

rods, cuttings etc. all depending on the biomass crop, length of the stem and regional terming.

Upon plantation of the stem both roots and shoots will sprout within a few weeks. The most

common and efficient planter is the step planter which requires two personal to feed the stems

into the otherwise fully mechanized implement. A coulter prepares the ground while the stem is

fed and planted into place, 4 rows at a time. These machines are primarily on the European

market as cutting planters in developing areas operate at only two rows at a time.

Cuttings Planter - Specific Type: step planter





2.3.3.4 Tuber Planter

Crops harvested for tuber production are planted using smaller seed tuber starting material. The

basic concept is the same for all the implement varieties; to pre-form the soil in a series of bed

rows, plant the seed tuber into beds and finalize the bed form. However, forming the soil into

raised beds while injecting the tubers has a high PTO demand restricting the width of the

implement, effectively lowering the field capacity and increasing the fuel consumption compared

to the other planting implements. Like the other seeding operations fertilizers and pesticides can

and are frequently pre-mixed into the bed.


Tuber Planter - Specific Type: 4-row bed planter





2.3.4 Soil Treatment

After the planting and throughout the growth and development stages of the crop occasional soil

treatment operations need to be conducted. The fertility of the land will decrease as the crop

consumes the nutrients for biomass production. In some instances the solid fertilizer laced to the

seeds, being time-released, is sufficient in providing the required nutrients throughout the entire

crop cultivation period. In other instances additional fertilization needs to be added, almost

exclusively in the liquid form. Furthermore as the crop matures pesticides need to be supplied.

2.3.4.1 Fertilizer Spreader

In some irrigation systems (sprinklers) the liquid fertilizers can be added with the irrigation water.

With the other systems spraying tanks need to be employed when additional fertilizer demand is

present. The long beam/boom attached with multiple pressure nozzles ensures a quick

application with as little tractor wheel contact on the field as possible.

Fertilizer Spreader - Specific Type: 20m boom sprayer





2.3.4.2 Pesticide

Pesticides can be added in several methods. In small and precise doses farmers can walk through

the crop fields with a hand-held sprayer applying the pesticides directly on the leaves or close to

the root structure. It can also be combined with the liquid fertilizer and applied via the fertilizer

spreader. Another common route that is able to mitigate large areas of crop plantations prone to

similar pests is a crop duster.

Crop Duster - Specific Type: small aerial duster

- Operation Speed: 220 – 280km/h


- Capacity: 395ha/h

- Fuel Usage: 2.32l/ha (kerosene)


2.3.5 Harvesting

The last step in biomass cultivation is harvesting; separation and collection of the final desired

product. Several unique machines and implements have been developed for the particular crop to

harvest. As most of the select biomass crops are traditionally eatable crops, the eatable portion

and non-eatable portion are harvested separately. In fact through advances of intensive farming

procedures the separation of the crop components is done on the field whilst harvesting. Food

based agriculture residue, being typically straw, is considered as agricultural waste and frequently

left on the field. In the non-food agricultural sector this residue will also contribute to biomass

production and will require additional harvesting options. The typical machines and implements

used in harvesting and sorting of the components required by the 16 chosen biomass crops will

be investigated. They are split into three broad categories.

2.3.5.1 Combine Harvester

A combine harvester, or simply combine as it is generally referred to, is a stand-alone agricultural

machine that “combines” the task of harvesting, threshing, cleaning and separating grain plants.

It can operate alone or with a tractor pulling a trailer to store the grains in larger volumes. The

desired grain/seed is separated from the rest of the plant through a series of complex mechanical

processing stages with the loose straw discarded to the rear. Combines are used for a wide variety

of crops that produce seeds and grains. Sorghum is the only grain crop located in the developing

regions; however for biomass production purposes it is harvested as sweet sorghum before the

emergence of the grains. Thus combines are strictly for the industrialized regions.

Combine Harvester - Specific Type: standalone New Holland TX63

16

- Operation Speed: 3.0 – 6.5km/h, set 5.0km/h

- Nominal Power: 175kW

- Operational Width: 4.57 – 6.10m, set 5.5m

- Capacity: 4.23ha/h

- Fuel Usage: 12.27l/ha

2.3.5.2 Forage Harvester

Forage is described as herbaceous plant matter consumed by grazing animals. It consists mainly

of leafy material and is commonly associated with grasses and hay. Residues from grain

harvesting (straw) can be used and classified as forage. For biomass production the collected

forage material will not be fed to animals but contribute to the overall yields. The collection of

biomass forage material involves several steps before it is delivered to the storage facility. The

precise steps involved are crop type dependent; grasses, stalk green biomass and residues are all

handled slightly differently with a specific series of unit implements.

Mower, cutting unit

Grasses and other plant material grown uniformly over the field and with a limited height must

first be cut loose from the ground. There are many types of cutting units available and one of the

most common and efficient is the rotary mower, also called a drum mower. Mounted on a bar

sharpened edges of rapidly rotating bars or disks will cut the crop. Best practices employ a twin


mounted system, having both a front and rear mounted implement. Combined they are easily

capable of operating at speeds up to 32km/h for young (low-lignin) crops, like ryegrass. More

recent implement systems, called autoswathers, can also combine the task of placing the cuttings

into windrows (densely rowed collection of cuttings) and eliminate the need for rakes.

Mower - Specific Type: trip le mounted rotary mower conditioner

- Operation Speed: 19.0 – 32.0km/h, set 20km/h




Rake, windrow unit

Not all mowers and cutting units place the biomass in the desired windrow alignment for

subsequent collection. Residues especially from the combines are generally scattered across the

field requiring the rake implement to distribute into the windrow form.

Rake - Specific Type: side delivery wheel rake

- Operation Speed: 6.5 – 13.0km/h, set 10km/h




Chopper, collection unit

The loose forage that has been positioned in the windrow alignment and left partially to dry is fed

into a chopper that further cuts and blows the material into a large silage collection trailer. The

cutting size is significantly reduced to increase the packing density and the ease of downstream

process handling. The collection trailer is pulled by a secondary tractor and must operate parallel

to one another reducing the field capacity.

Forage Harvester - Specific Type: drawn forage harvester



- Capacity (2.5:1 row spacing): 4.65ha/h (TM165), 3.25ha/h (MF240)

- Fuel Usage (2 tractors): 7.00l/ha (TM165), 3.89l/ha (MF240)

Bailer, collection unit

The power consumption and blade maintenance costs sharply rise with mature forage containing

high levels of lignin, like the crop residue from the combine. In these particular cases it is typical

to gather, compact and press the straw into bails. Bailers can produce either round or rectangular

shaped bails to be collected later. Each bail can weigh 500-700kg and will add transportation

costs to the system over the forage harvester as the bails must be collected from the field.


Bailer - Specific Type: large rectangular bailer



- Capacity (2.5:1 row spacing): 7.45ha/h (TM165), 5.20ha/h (MF240)


Self-propelled forage harvester, mower/chopper/collection unit

A large proportion of the grain and seed crops are not cultivated for human consumption but are

strictly dedicated as forage for animals. The separation of the human edible and non-edible

portion is thus redundant. In these cases a so-called self-propelled forage harvester is assigned

the task of harvesting. It cuts, crushes and blows the entire crop into a parallel tractor pulled

silage trailer. For near future biomass applications it would probably be advisable to handle

dedicated non-food biomass crops in a similar manner, although only in cases where it is

beneficial for all the material to be processed in the same reactor. That can save on combine,

mowing, raking and multiple stream handling costs. The self-propelled harvester is very versatile

as practically any crop can be harvested with the proper accompanied head attachment. The

engine size and resulting power of the machine is quite high in comparison to the other machines

and implements as cutting, crushing and blowing are included. Self-propelled forage harvesters

are a relatively recent invention, developed first in 1974, so there is not a developing world

equivalent meaning a new model would apply for both regions.

Self-Propelled Forage Harvester - Specific Type: New Holland FX40

17



- Operational Width: 3.27 – 6.5m, set 5.5m

- Capacity: 3.03ha/h

- Fuel Usage: 21.6l/ha

2.3.5.3 Tuber Harvester

Universal tuber harvester

Harvesting underground biomass crops requires a very specialized machine, a tuber harvester.

The most state-of-the-art versions are self-propelled and act similar to a self-propelled forage

harvester in the sense that it performs a multitude of tasks feeding a trailer pulled by a paralleling

tractor. First the top portion of the crop is trimmed, crushed and left on the field behind the

harvester. In sugar beet harvesting it is however advisable to first remove the stalks and collect

them before tuber harvests is to commence, whereas with the potato it is optional. This is

performed to maintain higher operational speeds while harvesting and to make use of the high

yielding top portion of the biomass. Next the soil bed row containing the tuber is dug up and

feed along a series of filters and grinding rolls to isolate the tuber. The nearly pure tubers are fed

via a conveyer belt to the trailer and the rests are dumped back onto the field. There is an


operational speed difference between potato harvesting and sugar beet harvesting, which also

includes the extra passage advised for efficient sugar beet harvesting

Self-Propelled Tuber Harvester - Specific Type: Grimme SF3000

18

- Operation Speed (Potato): 2.5 – 10.0km/h, set 5.5km/h

- Operation Speed (Beet): 6.5 – 10.0km/h, set 8.0km/h



- Operational Width: 2 or 4 rows, 4 rows at 3.3m

- Capacity: 1.82ha/h (potato), 2.64ha/h (beet)

- Fuel Usage: 45.7l/ha (potato), 31.5l/ha (beet)

Root digger

The cassava roots could be harvested mechanically and are to a degree. Root diggers are a much

simplified version of the tuber harvester. After the removal of the stalk the tractor implement

digs up the entire root structure with the soil and separates the crop with a primitive sieve

conveyor belt. A collection basket or even trailer is possible, but is not yet widely employed.

Stones, vines and undesired solid components are also removed with the rooting structure.

Root Digger - Specific Type: API cassava root digger



- Capacity: 0.67ha/h (MF240)

- Fuel Usage: 13.1l/ha (MF240)

2.3.6 Trailer Transportation

Directly following the harvest the crop must be brought to a central farm scale storage facility to

await subsequent distribution. Depending on the scale of the farm, storage operations can range

from a small barn to a large silo. For non-food crops intended for industrial biomass production

large-scale silos coupled with crop specific pre-processing procedures, such as drying and

pressing, are foreseen (see Chapter 7). For these relatively short distances of only a few

kilometres tractors using trailer implements are employed. A portion travel occurs on the fields,

whereas the large part of the short haul is on side and rural streets.

Trailer - Specific Type: 1 axis

- Capacity: 16ton/100m³ (TM165), 6ton/40m³ (MF240)

- Operation Speed: 5.0 – 22.5km/h (field), 20 – 50km/h (street)

- Travelling Speed: 35km/h (TM135), 25km/h (MF240)


- Fuel Usage: 25.3MJ/km (TM165), 10.9MJ/km (MF240)

- Fuel Consumption: 2.10MJ/t⋅km (TM165), 2.42MJ/t⋅km (MF240)


Dry Bulk Cargo: Grains Liquid Bulk Cargo: Chemical

2.4 Transportation Costs

Today anything can be shipped at anytime to anywhere in the entire world. An immensely

complex and efficient logistical infrastructure has facilitated the transportation of goods to no

longer be regarded as regionally bound, but globally free. This proves very advantageous for

industrially grown biomass crops, for biomass production will require vast quantities of arable

land to replace even the smallest portions of current fossil fuel consumption. To obtain a

significant reduction of fossil fuel intensity through biomass implementation can only be

achieved on a global scale. Furthermore, biomass grown regionally and harvested seasonally can

only supply the processing plants with a material feedstock for a limited portion of the

operational year. And as practically all modern processing plants are built on the economical

principle of continuous operation with a constant supply of material, it is imperative to ensure a

constant supply of feedstock. Thus to prevent any operational downtime biomass must be

imported from regions detached from the regional growing season. Although in some regions

perennial crops may suffice in providing enough biomass feedstock for the entire operational

year, the major chemical industries are located in temperate regions consisting of 4 distinct

seasons. The biomass transportation routes and destinations are described in (Section 4).

Raw biomass, pre-processed biomass and first stage biomass products can be separated into two

different categories: dry bulk and liquid bulk cargo. Bulk cargo is unpacked, homogenous and is

usually dropped or poured into a bulk cargo holder. Standard containers are generally not

employed as they are not very well suited for large quantities of biomass transportation.

Containerization has however revolutionized freight handling in the last

century, greatly reducing cost, increasing speed and shipping efficiency.

It is possible to transport dry and wet bulk material in container shaped

and ISO-standardized units. A so-called “bulkcontainer” contains an

open-top and can hold dry bulk goods and a so-called “tankcontainer”

can be used for liquid bulk cargo. As crop harvesting is seasonally based a large quantity of

biomass will be made available in a relatively short period of time, usually over the course of only

a few weeks. To be able to transport these high

volumes of cargo the specialized containers will not be

employed as they are designed for smaller distribution

levels. Two good examples of existing dry and liquid

bulk cargo in the biomass sector are grains and ethanol,

respectively. Dry bulk cargo (like grains) are handled by

conveyer belts, elevators, shovel buckets, etc. Liquid

bulk cargo (like ethanol) is handled primarily by piping equipment. The transportation capacity of

the cargo is gauged by two units of measurement; mass (tons) or volume (m³). One of the two

will be the limiting factor in transportation quantity. In case of raw biomass it is possible that

certain untreated crops will have a packing weight density lower than 500kg/m³, meaning that

volume is limiting. The packing densities of the biomass crops and pre-processed material are


listed in (Section 2.6). Aside from a few exceptions mass and not volume is the limiting factor in

transportation quantity. The fossil energy requirement for transportation will thus be presented in

relation to distance and weight, MJ/t⋅km, for the four major modes.

2.4.1 Heavy Goods Vehicle (Truck)

Traffic jams are a constant frustration to anyone travelling on any major

motorway in highly densely populated areas. Peak rush-hour periods congest

the roads for a couple of hours on a daily basis. And seasonal vacation

periods cause a great deal of the prolonged congestion and jams, inflicted in

Germany by the waves of slow moving Dutch caravan drivers, facetiously

dubbed during queues as “eine Campingplatz”. Even when taking the great

deal of social benefits (holidays) of northern countries like the Netherlands

into account the roads should only be congested about a dozen times a year.

And even if that is not taken into account, a more lingering and ever increasing dilemma is

arising…truck traffic. The vast majority of cargo is currently transported by truck. In Germany

alone, 66% of all the cargo is transported via the roads14. This high proportion is synonymous to

any industrialized region and reliance on truck transport is increasing yearly. Economically seen

transporting cargo via trucks makes perfect sense; the goods are delivered directly from A � B in

the fastest period of time. And despite the current high prices in diesel, fuel costs contribute to

only a small fraction of the overall transportation costs. Seen purely energetically however poses

a different reality. Out of all the transportation options trucks have the highest energy demand

per distance and weight transported. Even the most energy efficient biomass logistical and

distribution chain options will invariably rely heavily on truck transport, especially in transporting

smaller batches (one truck load) of farm collected biomass to a transfer centre for long haul

distribution. Large scale implementation of biomass for industrial purposes will undoubtedly

further congest motorways, adding an additional socio-economic incentive to foresee and

properly assess biomass chains.

There are a great deal of trucks and manufacturers

worldwide, with close to half a million being produced

each year. The largest manufacturer with a considerable

lead is DaimlerChrysler, badged under Mercedes-Benz

and Freightliner, producing 241,500 in 2005 (NTEA).

Due to the rapid road damage caused by trucks they are

classified and restricted by their maximum allowable

gross weight. In most European countries 40ton is the norm, with the Scandinavian countries

allowing 60ton as the exception, in response to their large logging industry. In other Western

countries, 50ton is the common maximum allowable gross weight, while in Eastern/Orient

countries mid-sized 20ton trucks are popular due to dense urban infrastructure. Other

restrictions and regulations concerning truck transport have also been developed. A clear result

of strict EU directives can be seen in the form, fuel efficiency and emission of gaseous pollutants

Truck vs. Lorry vs. Large Goods Vehicle The word “truck” comes from the Greek “trochos”,

meaning wheels and during the time of horse drawn wagon transport the big wheels were called trucks.

In Britain the word “lorry” was used by the railways

to describe a long, flat wagon, derived from “lurry”

meaning to pull. With the advent of motorized vehicle transport, in America the word “motor-

truck” was adopted and in England “lorry”. Large

Good Vehicle (LGV) is however the official EU term,

but is not used in common speech.


of trucks. Most visually apparent are European length restrictions being based on the overall

vehicle length including trailer and cab, where in many non-European OECD countries length

restrictions are either based on the trailer length or allow for longer lengths. This led to the

distinct splitting of truck design in where the Cab Over Engine (COE) “flat-nose” design is

prevalent in Europe and the Conventional “long-nose” design is prevalent in North America. The

long-nose design also facilitates a larger engine block needed to pull the extra 10-20ton of load,

ranging from 300 – 450kW, compared to 200 – 375kW for flat-nose trucks. In 1988, European

measures were taken to regulate the gaseous pollutants from diesel engines chiefly pertaining to

those from large goods vehicles, called 88/77/EEC. The “Euro I” norm placed upper limits on

CO, NOx, HC’s and particle emissions per power unit. Limiting carbon monoxide emission

indirectly affects the fuel efficiency through a higher lambda λ value and the most recent Euro IV

norm (2005) has 3.25 times less CO emission limits than the Euro I norm, at 1.50g/kWh. Thus

trucks constructed in 2005 for the European market are considerably more fuel efficient than a

model from the 1980’s. The separation between industrialized and developing world as

mentioned earlier can no longer hold for truck transport. Here the distinction will be made

between long-nose, full-sized flat-nose and mid-sized flat-nose. The truck classification has a

continental stipulation as opposed to a development stipulation. To date limited effort has gone

into improving the fuel efficiency of long-nosed trucks, meaning that even a new model is

comparable to an outdated flat-nose in terms of energy per distance and tonnage. Three different

truck configurations will be used: for European regions a 40ton gross (28ton net) Euro IV norm

flat-nosed truck will be used, for the Americas a 50ton gross (35ton net) Euro I norm long-nose

will be used and for regions that fall outside of these two categories a 16ton (8ton net) Euro II

flat-nose will be investigated. Much of the data in relation to the Euro norms can be taken from a

recently developed transportation tool (EcoTransIT)19.

Truck transportation in particular has several highly influential factors that can affect the diesel

consumption, namely the road category and characteristics and the transported load. Standard

consumption values are based on motorways in hilly regions, like Germany. Flat regions, like the

Netherlands require less fuel and mountainous regions, like Switzerland require more fuel. A

study by (INFRAS, 1995) found that a deviation of 5-10% occurs based on the regional topology

differences. Thus, like in the EcoTransIT study, flat regions are assumed to consume 5% less and

mountainous regions 5% more. Driving on extra-urban roads (with traffic lights, lower speed

limits and fewer lanes) consumes slightly more fuel than driving on motorways; 12% more on

average14. Wide-spread use of motorways is commonplace only in the originally defined

industrialized regions. Finally, a truck destined for a pick-up will arrive unloaded (empty) and will

consume roughly 1/3 the fuel as when fully loaded. It will be assumed that the trucks used for

biomass transportation are dedicated, meaning that deliveries are made at full load capacity and

returned empty. Both the fully loaded and empty load fuel consumption needs to be addressed.


European Regions (Euro IV) To represent the near future best practices a recent (2006)

highly fuel efficient 40t flat-nose model was selected.

Mercedes-Benz Actros II14, 19, 20 - Type: 3336 Articulated, Single Cab

- Nominal Power: 235 – 350kw, (265kW)

- Net Transportation Size: 28ton/100m³

- Norm: Euro V

- Diesel Consumption: 22 – 35l/100km

- Energy Requirements (loaded): 0.65MJ/t⋅km - Energy Requirement (empty): 11.2MJ/km

Americas/Oceanic Regions (Euro I) To represent the lower fuel efficiency of a Euro I classed

truck a standard, recent 50t long-nose model was selected

Freightliner Century Class - Type: S/T Art iculated, Fu ll Cab

- Nominal Power: 260 - 375kW, (325kW)


- Norm: Euro I


- Energy Requirements (loaded): 0.88MJ/t⋅km - Energy Requirement (empty): 13.3MJ/km

Asian/African Regions (Euro II) To represent the fuel efficiency of a Euro II classed midsized

truck a standard, recent 20t flat-nose model was selected

Mitsubishi FUSO Fighter21 - Type: FM280M6, Single Cab

- Nominal Power: 100 - 210kW, (207kW)


- Norm: Euro II


- Energy Requirements (loaded): 1.63 MJ/t⋅km - Energy Requirement (empty): 5.79MJ/km

The compensation factors (like topography and road type) as mentioned above will be taken into

account, as based on the region of transport, in the transportation system layout (Section 3.2).

2.4.2 Train

Before the boom of truck transport the major land-based transportation mode was by freight

train. Today in Germany less than 15.9% of all the cargo is transported by rail14. Though other

countries without good inland waterway systems will have a higher percentage, the general

reliance on railway transport is falling. The major drawback of rail transport is the lack of

flexibility and speed. They must follow the set track routes and wait at transfer points, for


coupling/decoupling of locomotives, wagons, etc. With distances below 100km transport via

train is simply uneconomical and is in many cases even less energetically efficient. Under certain

circumstances, however, transportation via rail is far more economical and energetically efficient

than via road. From a cost standpoint only a few engineers need be occupied versus scores of

truckers and from an energy standpoint far more cargo can be transferred per power demand.

Several governmental bodies are even pushing rail transportation on environmental grounds. The

greatest benefits (economically and environmentally) of rail transportation are achieved with

long-haul bulk cargo. Future large-scale biomass production schemes, being classified as bulk

cargo, should capitalize on the benefits of train transportation. In some foreseen areas of large-

scale biomass cultivation it may be a prerequisite to invest in adequate railway systems. Heavy

initial investment costs in new railway lines are a leading factor in the current decline of rail

transportation reliance. Long term dedicated biomass production schemes and lower operation

costs and energy demand should overcome the initial investment burden.

When assessing the energy input requirements of freight train cargo transport the type of

locomotive plays a decisive role. In vast areas of open space without the option of electrified

railway tracks diesel/electric traction units (an onboard diesel generator powers electric traction

motors) are employed, whereas electric trains

can be employed in areas powered via electric

feed cables. The energy required per tonnage

and distance varies considerably depending on

the traction unit. Following the guidelines of a

limited LCA the electric production will be

traced back to its initial fossil fuel input. As described in Chapter 2 many factors influence the

specific conversion rate, like the grid power mix and power station thermal conversion levels,

45% will be taken. The internal power conversion of a diesel/electric locomotive is 37%.

Transporting bulk cargo involves specially designed wagons tailored to the specific properties of

the material. In Europe self-loading funnel wagons are common for dry bulk cargo whereas in

the rest of the world covered hopper wagons are predominant. Liquids are transported in tanks

for all regions. The size, net weight and volume capacity of each wagon is unique, but total length

and number of wagons is not of terrible importance as the train size capacity is based on total

weight pulled. A typical train load can range anywhere from 500 to a maximum of 2000ton gross

weight. The longer the train (more weight) the more efficient the transportation and a large, long-

haul setup can be expected for dedicated biomass transport, resulting in a gross weight of

1500ton and net weight of 800ton/2400m³. The recent EcoTransIT project/report was

commissioned by the major European railway companies implying a high degree of accuracy for

the rail transportation under different conditions19. Electric range from 23.2 – 90.6Wh/net-t⋅km (0.18 – 0.72MJ/net-t⋅km) and diesel range from 2.6 – 9.7g/gross-t⋅km (0.22 – 0.83MJ/net-t⋅km). Topography conditions have a much larger effect on train transport than on truck transport. Flat

regions require 25% less power demand and mountainous regions require 20% more power


demand over the standardized hilly regions. Proportional travelling time empty is incorporated in

the resulting figures for both electric and diesel traction train systems. In many developing

regions the option to transport via rail is not wide spread. Infrastructural investments will be

required to allocate large portions of possible biomass transportation by rail and in such cases

electrified railway lines are not foreseen making the diesel/electric traction units the most likely

choice.

Industrialized Region (Electric) To represent the best practice, most efficient option, a long

electrified locomotive was chosen19

- Type: Electric

- Gross Pulling Weight: 1500ton

- Net Pu lling Weight: 800ton/2400m³

- Configurat ion: Dedicated, block train

- Cargo Type: Bu lk

- Electric Consumption: 29.0Wh/t⋅km - Energy Requirements (roundtrip): 0.232MJ/t⋅km

Developing Region (Diesel/Electric) To represent the areas without electrified railway systems a

long diesel/electric locomotive was chosen14

- Type: Diesel/Electric

- Gross Pulling Weight: 1500ton

- Net Pu lling Weight: 800ton/2400m³

- Configurat ion: Dedicated, block train

- Cargo Type: Bu lk

- Electric Consumption: 0.36Wh/t⋅km - Diesel Consumption: 0.391MJ/t⋅km - Energy Requirements (roundtrip): 0.394MJ/t⋅km

The topography compensation factors as mentioned above will be taken into account, as based

on the region of transport, in the transportation system layout (Section 4).

2.4.3 Inland Barge

Rivers and canals have always enabled trading between settlements and industries. Before the

onset of rail and truck transport, waterways were the primary method of transport. Historically

industries have been located along bodies of water to supply the factory with process water, a

cooling medium, a reservoir to wash away by-products and as an easy position for transportation.

Inland trading via barge is still today very economically attractive being able to efficiently

transport large quantities of cargo with low associated loading and unloading costs. Many large

processing plants have trading harbours specially constructed to facilitate inland barge transport.

But similarly to rail transport the transportation destinations and flexibility are greatly limited.

Transport via inland waterways is only feasible in areas with large rivers and canals linking the

industries. The European waterways and the current trading volumes are immense and open


many possibilities. The waterway transport options do span for large areas but are not suitable

everywhere. In fact inland barge transportation is limited to only a few regions in North Western

Europe and the Midwest-South of America. Inland barge transport is strictly an industrialized

region mode of transportation, meaning no classification difference will be made.

The energy required to transport cargo over waterways depends on several factors. Firstly, the

trend of inland barges continually growing in size, getting more powerful with an increasingly

large payload reduces the consumption. Typically barges can range from 800 – 2500ton load

carrying capacity with 300 – 750kW engine power. Despite the fuel consumption reduction the

highly powerful barges are chiefly employed in heavy-goods transport, like metals. Biomass and

biomass related products are best suited for modern upper/mid-range capacity, 1750ton. This

still represents more freight than an entire train load. River direction is another major factor, as

travelling upstream requires significantly more fuel than travelling downstream. The form of the

river also affects the fuel consumption. Sluices and slices built along the banks regulate the river

flow velocity and reduce the overall fuel consumption of barges, especially when travelling

upstream. In the areas most reliant on inland transportation sluices are commonplace. Finally,

like with the other modes, dedicated transport implies empty loads.

Industrialized Region To represent the best practice, most efficient option,

mid/upper sized self-propelled barge was chosen19

- Type: Self-Propelled River Barge


- Net Cargo Weight: 1750ton

- Energy Requirements (Loaded)

Downstream: 0.17MJ/t⋅km Upstream: 0.24MJ/t⋅km - Energy Requirements (Empty)

Downstream: 261MJ/km

Upstream: 356MJ/km

2.4.4 Sea Vessel

Globalization would not be possible without sea vessel transportation. During the time of the

Dutch East India Trading Company (VOC) a rigged ship manned with a crew of at least a

hundred took several months to complete a journey collecting a couple tonnes of spices. Today

modern bulk carriers can complete a trading journey in a matter of few weeks with less than a

dozen crew collecting on average 40 000 tons of cargo. The newest and largest of the classes can

carry up to 325kton of cargo. Bulk carrier is the general name for dedicated ships transporting

bulk cargo; bulkers describe dry cargo types and tankers for wet cargo types. Bulk carriers

comprise of a large section of the global transport of goods, representing one third of the total

merchant fleet. The bulk carrier fleet includes 6,263 ships with a total capacity of 294million tons

(in 2004)22. Transportation on the open seas is an international business with no clear distinction

between nations. The largest fleet, 1700 bulkers, sail under the Panama flag as they are registered


there for tax reasons. And 41% of the world’s bulkers were built before 1986, meaning regional

discrepancies cannot be made. Classification of sea vessels is thus done by total carrying capacity,

the hulls width, length and draft and type of configuration. The largest proportion of bulk

carriers, 32%, are in the Handysize class having a deadweight tonnage (DWT) of 10 – 35kton, but is

quickly shifting to the larger Handymax class of 35 – 55kton22. Net cargo capacity is 85% dwt for

bulk carriers and 95% for tankers. Nowhere more than in the sea vessel transportation sector is

the economics of scale so apparent and beneficial. Many of the newly built bulkers and tankers

cannot fit through the Panama Canal and Suez Canal called post-panamax and post-suezmax,

respectively. Sailing around Cape Horn and the Cape of Good Hope is simply more economical.

Fuel costs almost represent the entire portion of the operation costs of sea vessels, ranging from

90 – 95%23. The larger the dwt the lower the proportional fuel costs per transported tonnage.

Relating the heavy diesel oil consumption to the transported cargo will be based upon the two

types of cargo, wet and dry. Tankers are considerably more energy efficient than bulkers, simply

due to the higher packing density of liquid cargo. Although the trend of the shipping industry is

to increase ship size, following the economics of scale, the typical sizes will be taken instead. For

it is unlikely that in the biobased economy a single port would process such high levels of

biomass to warrant the employment of supertankers or superbulkers, at least in the initial phases.

Furthermore bulk carriers are strictly dedicated, port-to-port business returning empty. The

option of collecting biomass material on-the-way is not possible or rational as it is with container

ships. A ship returning with empty cargo (but full ballast tanks) holds requires 65% the fuel levels

as during full load conditions. Since most ships are built before 1986 there is not much relevancy

in the age of the sources of information. Borken14, collected shipping information from a wide

variety of international studies reflecting the years 1985 – 1996.

Industrialized and Developing Regions To represent the expected transport conditions involved in

the biomass sector a typical sized ship was chosen. - Type: Tanker

- Cargo Type: wet, liquids

- Size Class: Panamax

- Nominal Power: 9,760 – 12,200kW

- Cargo Weight (dwt): 60,000 – 82,000ton

- Diesel Consumption: 0.7 – 2.6g/t⋅km

- Energy Requirements (roundtrip): 0.031 – 0.118MJ/t⋅km Set: 0.057MJ/t⋅km (1.25g/t⋅km)


Industrialized and Developing Regions To represent the expected transport conditions involved in

the biomass sector a typical sized ship was chosen. - Type: Bu lker

- Cargo Type: d ry, loose

- Size Class: Handymax

- Nominal Power: 6,730 – 10,600kW

- Cargo Weight (dwt): 35,000 – 55,000ton

- Diesel Consumption: 2.2 – 4.9g/t⋅km

- Energy Requirements (roundtrip): 0.101 – 0.224MJ/t⋅km Set: 0.114MJ/t⋅km (2.5g/t⋅km)

2.5 Storage and Transfer Costs

2.5.1 Storage Description

In any logistical chain, simple or complex, storage of material is inherently included and is located

almost exclusively at a transfer point between the different scales and types of modalities. In

terms of large-scale biomass transportation there are two major cause and effects necessitating

storage capacities. Both relate to the fact that each arable piece of cultivated land is independent,

scattered and can only supply moderate quantities of biomass per each harvest period. Tractor

transport will collect the freshly harvested crop and deliver it to a central storage location, such as

a farm-scale barn. Until the collected biomass weighs sufficiently to warrant the next mode and

scale of transportation (such as truck), the material must be stored. The long-haul, high-quantity

transportation types (especially water bound vessels) can transport many hundred-fold the freight

of a tractor and truck load. These differences will result in a bottleneck of delivery flows

mitigated through the use of centralized storage systems. An articulated truck can perform other

tasks during downtimes, whereas the economics and energetics of charting a ship at less than full

capacity is not advantageous. Furthermore biomass being a seasonally dependent commodity

means the time of harvest does not necessarily couple well with the production window. A

limited factory production flow either on the pre-processing or final processing side can create

another bottleneck. Over-sizing of equipment to increase throughput is not economical in light

of cheap storage options. Thus biomass storage facilities follow the simple rule of supply and

demand. As the biomass chain cannot supply a constant flow of material when needed (transfer

point or processing plant) storage is inherent.

Storage of biomass material for non-food purposes does not generally require energy in itself.

Large areas of land are required for its place, which will minutely lower the actually crop yield in

terms of ton/ha. Considering new and large areas of storage facilities must be constructed to

accommodate the near future flows of biomass material, possible arable land is lost. It is however

greatly difficult to place a precise lost yield value considering the different land types and actual

storage positions and sizes. Locations designed for material storage and transfer (i.e. a harbour)

do not classify as arable land. Even on the farmland barns, silos and other agricultural buildings


represent a mere fraction (1-5%) of the arable land. It should only be mentioned that large-scale

biomass production has a relationship on the land requirements. As a land consuming factor,

storage of biomass and related products must be expressed in volume (m³) terms and not weight

(tons), for the dimensions of the storage facilities differ immensely and are very feedstock

dependent. As an example, wet biomass will require a larger surface area than dry biomass, but

dry grains can be stored in high silos (grain elevators) whereas wet grass cannot. In (Section 2.6)

the pre-processing options and types will be investigated. The packing density, moisture content

and particle form determine the storage facility type and land consumption of the biomass

feedstock.

One of the major drawbacks of storage options is the loss of material. Long-term storage can

promote the digestion of the material through bacterial and fungal contamination. The loss of

biomass material is evident by the formation of carbon dioxide, methane, other volatiles and cell

mass from the decomposition of biomass material. It is a function of the type of biomass and of

the degree of moisture, for no decomposition occurs for most biomass feedstocks below 20%

moisture content. Wet materials degrade at a rate of 3% dry mass content per month24. Yet for

example, the first stage of storage being the roadside/farmland can reduce the moisture content

from 50% to 30% purely by the environment without charge or material loss24. Furthermore,

ensiling is a storage technique that can preserve green forage with no notice loss of material.

However in general, pre-processing techniques will need to be implemented to reduce the

moisture content, increase the packing density and lower the particle size/form; all of which will

lower the storage needs, transportation costs and prevent loss of material.

2.5.1.1 Transfer Points

Biomass is stored at a point of logistical transfer. The specific location and feedstock material

properties determine the storage facility and as mentioned, storing biomass does not directly

consume energy. It is the transfer equipment that consumes primary energy. They are determined

by the type of storage facility and the mode of transportation. There are many types of storage

facilities; typically barns, covered halls, and small silos are present for farm based systems and as

collected volumes and masses increase further down the transportation chain large bunkers, silos

and tanks become more apparent. Each of the storage systems relies on a different set of

equipment to perform the unloading, arranging and reloading. Under certain circumstances some

transfer points do not need to rely of any storage systems and can directly transfer the material to

the next mode of transportation, adhering to the just-in-time business model. For example, loading

the funnel wagons of a long-haul train from regional trucks can be immediate given the right

logistical planning. This will avoid one step of unloading, arranging for storage and subsequent

reloading. Akin to storage facilities there are numerous tools and equipment utilized to load,

unload and transfer materials. Figures must be kept in volumetric terms for the operational speed

of transfer equipment is limited by throughput. Bulkier material (lower packing density) will take

more transfer operational time and will thus consume more energy in the process.


Assuming that the material decomposition loss due to inappropriate moisture content levels are

resolved through adequate pre-processing methods, material loss is still present. A minimal loss

of biomass occurs through traditional inefficiencies involving in storage and transferring

operations, namely spillage, being blown away, leaching, leftovers, etc. Typically 1-5% results per

transfer and is system dependent. This material loss is on top of the unavoidable biological

degradation and will be related to the transfer points and the operational equipment involved.

2.5.2 Loading/Unloading Equipment

The major transfer equipment types covering the general expected forms of biomass material

presented by the choice crops will be investigated. Transfer equipment is understood as loading,

unloading and arranging storage facilities. They will be grouped by transfer point stage and

related to feedstock property type. Included in the assessment will be the transfer speed, material

loss and primary energy consumption per volume. Separate grouping of industrialized regions

and developing regions has little effect on the mechanical transfer operations values. The only

true difference in practice is on the farm level and transfer to trucks. For it is commonplace in

the developing regions to heavily rely on manual labour to load outbound vehicles.

2.5.2.1 Wheel Loaders

Wheel loaders are classified as construction equipment fitted with a front movable arm designed

for moving and lifting material and/or freight. A wide variety of front attachments are available

specially fitted for the material to handle, predominantly shovels, buckets and picks. Nearly

anything can be handled with a wheel loader and the operational speed is dependent on the form

of the material handled, the size of the machine and the distances required for transfer. For

agricultural purposes and loading/unloading of trucks a small/mid sized model will be chosen.

Tractors can also be fitted with a front end loading implement and made to operate like a wheel

loader, yet positioning speeds are compromised.

Wheel Loader - Specific Type: Liebherr L509

25

- Nominal Power: 52kW, 275g/kWh

- Loading/Unloading Capacity: 10 – 100runs/h, set 30runs/h (assumed)

- Bucket Capacity: 1.0 – 2.0m³, set 1.1m³ (loose material)

- Fork Capacity: 4.0 – 4.4ton, set 3.0m³ (packed material)

- Material Loss: 0.3%26

- Diesel Consumption: 0.39l/m³ (loose), 0.19l/m³ (packed)

- Energy Requirements: 14.5MJ/m³ (loose), 7.3MJ/m³ (packed)

2.5.2.2 Conveyors

Some of the dry bulk biomass products will be stored in silos; particularly grains are stored in tall

silos, called grain elevators. A system of conveyors is used to transport the material to the top of

the structure for filling. Conveyors operate by a system of electrically powered pulleys with a

looping transport band. Many different configurations are possible with conveyance systems. The


grain elevator for example employs a bucket conveyor track, yet the most common for biomass

applications is the common belt conveyor. They are usually open and capable of transporting

large quantities with very low energy costs. Screw-type conveyors are enclosed and have thus

lower material loss and are best suited for moist biomass material. Conveyors can be utilized in

several transfer points and being coupled with typically large silos are located at major

distribution hubs awaiting transfer. Conveyers are also used to load vessels, called shiploaders.

The energy demand for conveyance has four influencing factors; speed, height, density (weight)

and total rate. It was found that 2.80kWh/t⋅km (+0.2 – 1.0kWh/t⋅km depending on the slope) is typical for conveyor belts27. 3.0kWh/t⋅km will be used with the following assumptions to relate to biomass applications, resulting in MJ/ton.

Conveyor - Specific Type: Belt

27

- Electrical Power Demand: 3.0kWh/t⋅km - Typical Silo Height: 10-100m, set 50m (dry), 10m (wet)

- Set Conveyor Length: 75m (dry), 15m (wet)

- Material Loss: 0.2%26

- Electrical Consumption: 0.23kWh/ton (dry), 0.05kWh/ton (wet)

- Energy Requirements: 1.8MJ/ton (dry), 0.36MJ/ton (wet)

- Add 50m for ship loading: +0.15kWh/ton, +1.2MJ/ton

2.5.2.3 Stacker/Reclaimer

A stacker also operates on the principle of a conveyance system for handling bulk materials. The

difference is that a stacker creates open stockpiles along on a guided track and therefore does not

place them in a silo. Without the benefit of a silo structure gravity cannot be used to further feed

the material to the next transport modality. For this transfer operation a reclaimer distributes the

stockpile affectively reversing the process. Although the height of the stockpile is less than a

common grain elevator, the conveyor belt total length is longer due to the long distribution of

the tracked storage area. Biomass not prone to climatically induced degradation and/or in regions

with minimal rainfall during periods of storage can be stored in stockpiles, preferably in areas

with a high throughput of material. Being stored in the open will nevertheless promote additional

material loss regardless of moisture and weather conditions. Compared to the enclosed silo

storage type an additional factor of 3 will be set for the material loss. The electrical consumption

per ton and distance will be used as was for the conveyor belt.

Stacker/Reclaimer - Specific Type: Belt/Scope

27

- Electrical Power Demand: 3.0kWh/t⋅km - Stacker Boom Length: 20 - 40m, set 38m (all)

- Set Conveyor Length: 100 - 500m, set 200m (all)

- Material Loss: 0.6%

- Electrical Consumption: 1.42kWh/ton (pile and reclaim)

- Energy Requirements: 11.4MJ/ton


2.5.2.4 Crane

Unloading of vessels (both sea and inland) is performed by bulk handling port cranes. They come

in many forms and sizes depending on the specific material being transferred and transversely

effect the berthing time. A large bulk carrier can take several days to properly unload taking into

account the dangers of capsizing. Most common is the gantry grab unloaders using a bucket to

scoop dozens of tonnes in one go and place the material via the gantry on the shore in bulk

holders, in stockpiles or directly on feed conveyors. Ports equipped with cranes are close to or

are part of the industrial terrain of the destined chemical factory meaning cranes are the final

phase in long-haul transport. Highly modernized port operations (like in Rotterdam) employ

large continuous suction systems connected to conveyor belt systems; the unloading speed is

enhanced while the energy requirements are comparable.

Crane - Specific Type: Gantry Bucket

28

- Bucket Size: 25 – 63tons/scope

- Unloading Capacity: 800 – 3000ton/h, set 1500ton/h

- Material Loss: 0.1%

- Energy Requirements29: 2.32MJ/m³ (bucket type)

- Energy Requirements29: 3.13MJ/m³ (shovel type)

An older study from 1995 found 10MJ/ton for train transfer points and 40MJ/ton at ship

transfer points26. The EcoTransIT uses the average estimate of 1.3kWh/t (10.4MJ/ton) for all

bulk and general cargo transfer types19. These figures are either lower or higher than the ones

they calculated above with respect to the specific transfer action performed. Depending on the

moisture content, the transported biomass has an energy content of 2 – 20GJ/m³ which when

brought into perspective means that the transfer costs are two orders of magnitude lower. Thus

the exact figures of storage and transfer energy demand do not greatly influence the overall

energy costs, but should nonetheless be included. For transfer options not covered above,

5MJ/m³ energy and 6.4MJ/m³ exergy (since most equipment is electric based) will be taken.

2.6 Pre-processing and Drying Costs

Transportation of bulk materials with a bulk density below

500kg/m³ are considered to be light, volume dependent

materials and are not suitable for cost and energy effective

long-distance transport. At bulk densities below 500kg/m³,

more air is being transported than actual material. A classic

example in the logistics world is the beach ball; inflated or

deflated? Being manufactured in China the balls must be

transported across the world to reach their desired markets.

A large inflated beach ball has a bulk density of only a few grams per cubic meter, while a pile of

vacuum packed deflated beach balls can reach nearly 900kg/m³. Practically 100 extra

transportation journeys would be required to transport a shipment of inflated over deflated beach

Bulk Density

A property of particulate m aterials.

It is the m ass of m any particles of

the material divided by the volum e

they occupy. The volum e includes

the space between particles as

well as the space inside the pores

of individual particles.


balls; but than again half the fun of a beach ball is blowing it up. Beach balls are the extreme. In

the biomass sector many crop components are harvested with bulk densities below 500kg/m³.

Biomass has an additional dilemma concerning transportation; high moisture content. Not only

air but water is being transported greatly reducing the net dry biomass material. Thus pre-

processing and drying are a prerequisite before any long distance logistics of biomass can

commence. Processing in the sense of refining biomass to other materials in centralized factories

will be covered in the succeeding chapter. In this section pre-processing and drying is understood

solely as the straightforward, common methods employed to increase the bulk density and lower

the moisture content for longer distance bound biomass; essentially compacting the material and

removing a large portion of the water content.

Sizing and drying are energy intensive steps that can also inflict material loss and degradation.

The higher the desired resulting “dry” bulk density the higher the processing energy costs and

potential for material loss (burning, dust creation, etc.) There is a clear trade-off between the

reduction of transport cost and the increase in processing costs, particularly for short distances.

An optimum must be found to ensure that the least amount of energy and exergy has been lost in

the transportation of biomass material. Little can be done about the required moisture content

for long distance transportation, for as mentioned in (Section 2.5.1) the decomposition of

biomass material ceases at values below 20%. For food-grade grains the moisture content is

brought down to 15% to avoid any decomposition and bacterial infection. Seeing that long-haul

intercontinental transportation can take several weeks and even months, 20% moisture content is

set as a minimum for forage and waste-type biomass feedstocks and 15% moisture content for

grains and seeds. Lower moisture content is not required or advised. Fortunately several of the

crop components already adhere or come close to these levels and require little or no additional

drying procedures. Size reduction is feedstock dependent as there is a multitude of options

available to comply to the specific biomass properties. The demand for and energy intensity of

sizing is a function of the required bulk density and physical feed properties (such as lignin

content and initial size). First the procedures for drying and sizing will be listed and presented in

MJ/ton wet weight, which will later relate to MJ/m³. The optimal settings in combination with

the transport costs will be covered in Section 4. This section will follow the same layout as the

farm equipment costs, systematically listing the equipment options and energy demand as a

general input.

2.6.1 Size-Reduction

Harvesting biomass material inevitably reduces the size and increases the bulk density through

the harvesting techniques. A forage harvester, for example is in fact a crude size-reduction devise

yielding particle sizes between 10 – 25mm. Yet for transportation beyond the regional storage

facility additional size-reduction is necessary to further increase the bulk density. There are three

basic unit operations for biomass size reduction techniques; cutting, crushing and shearing.

Cutting is performed close to the field or initial storage facility to allow for better stockpiling of

bulky material and promote a more effective drying process. After moisture reduction (Section


2.6.2) crushing and shearing further reduce the material into finer particles, usually in the form of

a pulp or course flour. The benefits of employing the final two size-reduction installation options

is only realised for certain logistical operations. System incorporation and the degree of size-

reduction requirements are feedstock, location and destination dependent. In practice, a wide

multitude of installations are custom tailored to the specific needs of the feedstock. Yet, general

installation types follow standard energy demands with only a minor influence of the specific

crop properties. The following size-reduction installations are based on the common parameters

for the three types.

2.6.1.1 Cutting

Initial cutting is already performed for certain crops by the forage harvesting procedures, greatly

increasing the bulk density and facilitating field collection. Grinders, shredders and chippers are

all synonymous as essentially being first stage size-reduction units for those crops and/or crop

components not exposed to the forage harvester or further cutting the material into smaller,

more workable sizes. There are two basic design concepts for cutting units as defined by the

mechanism involved; the drum and the disk chippers. The drum type works by two parallel

rotating steel drums providing the feed and crushing force. This design type can easily take

advantage from the economies of scale and is frequently employed in larger factory installations.

The disk type works by a series of rotating disks mounted with cutting blades. The resulting size

of the material for both types is similar at 5 – 50mm, which lies in the same range as the forage

harvester. The disk type chipper however has been designed primarily for operational safety and

is common for smaller applications and material through-put. Even though being unable to take

much advantage of the economies of scale, the drum chipper has a significantly lower energy

demand per processed amount of material. Currently, drum chippers are primarily employed for

forestry products and are especially useful in sizing of hard and bulky materials. Certain forage

material and other agricultural residues, with their high lignin content, behave similarly to woody

material that has been subjected to forage harvestation.

Several independent studies have investigated the energy demand of drum/roll chippers. A

slightly dated case study for the woodchip industry found a diesel consumption of 6.7l/ton chips

(0.25GJ/ton WW)30. Around the same time a collection of data was presented for the chipping of

various grains at differing moisture contents31. The primary energy consumption ranged from

0.032 – 0.266GJ/ton WW for a roller mill. A more recent study for forestry residue biomass

sizing found considerably lower figures of 0.029 – 0.064GJ/ton DW (0.06 – 0.12GJ/ton WW)32.

While a recent industrial assessment of various chipping machines for woody biomass chips

revealed 0.13 – 0.23GJ/ton DW (0.26 – 0.46GJ/ton WW)23. In summary, these studies show that

the energy requirements for a chipping unit range anywhere from 0.032 – 0.46GJ/ton WW, being

very feedstock dependent. As it is foreseen that even the harder/woody biomass will first be

forage harvested, the energy requirements of employing a cutting unit is on the lower scale:

0.075GJ/ton WW will be assumed to be representative.


Cutting - Specific Type: drum/roll ch ipper

- Motor Size: 50 – 1500kW, set as large 1000kW

- Operation Capacity: 10 – 100tonWW/h

- Chipped Size: 15 – 50mm, set 20mm

- Energy Consumption: 0.075GJ/tonWW

2.6.1.2 Crushing and Shearing

Crushing and shearing reduce biomass to even finer particles, typically below 1.0cm in diameter.

In many of the biorefinery plants these units will be invariably foreseen as the first step in

handling the feedstock before subsequent processing. It is essentially a mechanical pre-processing

step. In some logistical systems it may be of advantage to have this step before transportation to

the biorefinery. For these size reduction units a low moisture content is necessary to ensure a

fluid operation, effectively making drying a prerequisite for most of the biomass feedstocks.

Furthermore with the creation of fine particles certain internal crop components become

exposed to the environment and become sensitive to degradation conditions, adding the need for

a possible secondary drying procedure. Fine particle creation is energy intensive and larger scale

industrial units will have a better energy-to-feedstock ratio than smaller scale units while also

reducing or even avoiding the drying steps, being coupled to the biorefinery. Nonetheless many

systems will benefit from localized size reduction steps before long distance transportation.

There are two major types of crushing and shearing units for biomass applications. Hammer mills

are amongst the most common machines in industry to crush coarse material into finer sizes,

particularly in mining operations. They are also used on fibrous and grain biomass to produce

fine feeds and flour. By circulating a beating hammer the material is crushed to size and passed

through a sieve. For even finer particular sizes a burr mill is employed, which grinds the material

into size via two circling plates with jagged surfaces. The energy intensity of a burr mill is

significantly higher as the generated particle sizes are much smaller, in the order under a few

millimetres. A study into the specific energy demand of woody biomass found a general formula

correlated to the final particle size33:

Fine Particles (<1mm) Coarse Particles (>1mm)

742.0)ln(731.0 +−= mdpE 11.206)log(06.203 +−= mdpE E: Grinding/Shearing electrical energy [MJ/kg DW] E: Grinding/Shearing electrical energy [kWh/ton DW] dpm: Middle(average) diameter particles [mm] dpm: Middle(average) diameter particles [mm]

Other studies found the primary energy consumption of a hammer mill to range from 0.032 –

0.263GJ/ton DW23, 31. A recent study into the energy costs of hammer-milling palm-kernel

revealed remarkably low values of 0.0142 – 0.0315GJel/ton DW34, whereas hammering

switchgrass revealed 0.201GJel/ton WW35. As mentioned the burr mill requires significantly

higher energy demands at 0.192 – 0.696GJ/ton WW31, for finer particle sizes. Burr mills are

among of the earliest size reduction machines as is noticeable from the higher energy


consumption, faster wear and will eventually phase out in favour of hammer mill technology.

Furthermore the burr mill advantages are in food processing techniques (i.e small particle size

distribution), which for non-food bares little relevance. Yet, many biomass crops are still based

on the classical food portion of crops warranting its inclusion. Due to the big variations in energy

input and resulting particle size several assumptions will be made based on the above formulae:

for cut and partially dried fibrous residues, forages, the hammer mill will be employed producing

5mm particles and for grains and other dry feedstocks the hammer mill will be employed to yield

1.5mm particles.

Crushing and Shearing - Specific Type: hammer mill

- Input Moisture Content: 10 - 25%, set 20% forage, 15% grains

- Chipped Size (forage): 0.5 – 5.0mm, set: 5mm

- Chipped Size (g rains):, 0.1 – 2.5mm, set: 1.5mm

- Energy Consumption (5mm): 0.231GJel/tonDW: 0.44GJ/tonWW

- Energy Consumption (1.5mm): 0.613GJel/tonDW: 1.09GJ/tonWW

2.6.2 Moisture Reduction

In the cereal/grains sector, around 60% of the total process energy demand originates from

water removal. In the forestry sector it is even higher at 70%. Depending on the methodology,

between 9 – 25% of the total industrial energy consumption in developing countries is allocated

for drying operations36. Biomass, especially green biomass, has an inherently high moisture

content in the order of 10 up to 90%. Upon the transportation of wet biomass the embodied

water serves no purpose except to negatively influence the transportation costs and energy

requirements. Long-term storage and long-haul transportation have the additional problem of

accelerated product degradation through increased activity under the presence of water. In the

perishable food industry moisture reduction techniques permit arbitrary harvesting dates reducing

losses attributed to early and late harvestation, for as much as 10 – 15% additional yield is

achieved31. Before the advent of direct crop drying easily 10% of the yield perished in the storage

facilities. Non-food biomass with the intended purpose as a feedstock for chemical biorefineries

have three basic reasons supporting the removal of water. Firstly, it minimizes deterioration of

the product during lengthy logistical systems. Secondary, it enables fully mechanized material

handling in logistical systems. Thirdly and most importantly, it increases the net dry bulk density.

Although quite material dependent, for the large part the biomass structure remains constant

regardless of the moisture content implying that drying in itself has a rather negligible effect on

the resulting volume of the product. Only when coupled with a size reduction step is the net dry

bulk density increased by a significant amount.

Adhering to thermodynamic tables 2.28MJ is required to directly evaporate 1kg of water, which

for thermal drying implies 2.3GJ/ton water removal as a bare minimum, without heat recovery or

integration. Moisture reduction is an energy intensive process further intensified with relatively

low energy/drying efficiencies. Typical energetic drying efficiencies for crop drying installations


lie between 15 – 60% with a strong interdependence on the initial and final moisture levels. For

instance, standard hot air dryers consume 4 – 10GJ per ton of water removed from biomass

materials31. There is an array of dryers and moisture reduction systems available that are highly

specified and effective to the particular biomass feedstock with an equally wide range of energy

demands. The typical systems required for the biomass materials under investigation are

described, listed and calculated for the energy demand in relation to the feedstock and moisture

content.

2.6.2.1 Natural Air Drying

Leaving the harvested crops on the field or under an open-air shelter for a few days can reduce

the moisture content to as low as 30% with no fossil fuel energy charge or loss of material. Many

forage crops in particular are handled this way, being raked into windrows and left to partially dry

before collection. Harvested biomass with a moisture content between 30 and 60% are best

treated in such a fashion to drive drying costs down. Local weather conditions do effect the

speed and extent of moisture reduction, but typically crops are harvested during the warmer and

drier periods of the year. Thus, even in temperate climates drying to 30% with natural

environmental conditions is possible. A moisture content approaching 20% is however generally

not possible with natural air drying alone; additional treatment is necessary for many of

feedstocks. For very wet biomass (>70%) goes to 50%, others (<70%) go to 30%.

Natural Air Drying - Specific Type: none

- Biomass Types: green biomass, forages, stems, leaves, etc.

- Input Moisture Content: 30 – 60% and 70 – 90%

- Output Moisture Content: 20 – 40%, set at 30% and 50%

- Energy Consumption: 0GJ/ton

2.6.2.2 Filter Press Dewatering

Extraordinarily wet biomass that upon harvest exceeds 50% moisture cannot be properly air

dried without complications, such as contamination and loss of material. A filter press can speed

up the dewatering process with a moderate addition of electric energy. By applying pressure via a

hydraulic press large amounts of water are forced out of the feedstock through a filter body (belt

or sheets). The filters minimize the permeation of smaller soluble materials but loss is

unavoidable although kept below a few percent when employed as an initial water removal

device. Filter presses are commonplace in wastewater treatment facilities as a first step in

removing large quantities of water. Typically, sludge feedstocks of only a few percent dry matter

are reduced to 50% moisture and in some cases brought to as low as 10%. Particularly wet

biomass that has undergone an initial size reduction treatment can give a moisture reduction to

about 30% with minor energy demand and material loss.


Filter Press Dewatering - Specific Type: chamber filter press

- Biomass Types: wet green biomass, forages, stems, leaves, etc.

- Input Moisture Content: 50 – 90%

- Output Moisture Content: 20 – 40%, set at 30%

- Material Loss: 2% (main ly sugars and free amino acids)

- Energy Consumption: 10 – 30kWh/tonDW, set 0.23GJ/tonWW

2.6.2.3 Conveyor Belt Drying

In the forage industry reducing the moisture content to below 20% is commonly achieved

through the use of a conveyor belt dryer. This is desired when the material is to be converted

into pellets and/or stored for a considerable length of time. The wet feedstock travels along the

conveyer belt and is exposed to hot air (120 - 200°C), either from below or above, which removes the water in the process. It is a simple yet energy intensive system typically involving a

fuel burner. The energy demand is a direct function of the amount of water removed from the

biomass feedstock. Typically for hot-air belt dryers 4.6 – 7.0GJ/ton water removal is required31.

At temperatures below 150°C driers are considered “low-temp”. These systems have moderately lower energy demand compared to other system; with other modern improvements the energy

consumption can be further reduced37.

Conveyor Belt Drying - Specific Type: hot-air conveyor belt

- Biomass Types: chips, forage, stems, leaves, etc.



- Energy Consumption: 4.5GJ/ton H2O, for 30�20%: 0.56GJ/tonWW

2.6.2.4 Rotary Drum Drying

One of the most straightforward and common dryers for any drying application is the rotary

drum dryer. It works on the exact same principle as the household laundry dryer, rotating the wet

material while injecting a constant flow of warm-air as the drying medium. Industrial rotary drum

dryers for biomass applications use either hot-air (above 130°C) or the direct flue-gas (above 200°C) from the burner. Significant levels of electricity are required to continually rotate the drum but this still represents less than 0.1 – 2.5% of the total energy demand38. Thus electric

contribution can be disregarded. By rotating the wet material in the drum it is brought into direct

contact with the drying medium and promotes a good air particulate contact and fast mass

transfer. These systems are highly effective for initial moisture content reduction. Early

calculation models for bioenergy applications reduce the moisture content from 50% to below

15% and indicate 1.1 – 3.9GJ/ton final product38. As the initial moisture content was set the

energy demand per water removal can be traced back to 1.3 – 4.7GJ/ton H2O. For most biomass

materials flue-gas cannot be used causing the heat energy demand to lean towards the higher end


of the range, relating to a hot-air medium. For particularly wet biomass feedstocks one should

not use the rotary drum dryer, but opt for the filter press/conveyor belt dryer combination.

Rotary Drum Drying - Specific Type: hot-air d rum dryer

- Biomass Types: any

- Input Moisture Content: 20 – 90%, set below 50%



2.6.2.5 Silo/In-Bin Drying

Grains and other biomass material stored in silos are frequently treated with a drying system to

simultaneously dry and store the product ensuring a safe long-term storage. The most popular

type is the continuous flow system. It works by injecting large volumes of warm-air (60 - 80°C or 120°C) from below or at different layers along the height of the silo. Considering the large air flows involved and the low temperatures used, the electric power demand of the circulation fan

cannot be neglected. Depending on the layout 5 – 10% of the total energy demand is electric,

which when translated into primary energy requirements can exceed 20%. Yet, compared to the

other drying systems in-bin drying has moderate energy demands ranging from 2.3 – 3.5GJ/ton

H2O31. It is however only suitable for low-moisture drying. A typical feedstock is shelled corn,

requiring around 1.0GJ/ton WW primary energy to reduce the moisture level from 25% to

15%31. Older values from 1978, indicate similar values for shelled corn brought from 24 to 16%

moisture at 0.94GJ/ton WW. This suggests that for the conventional system, little extra energy

savings can be foreseen.

Silo/In-Bin Drying - Specific Type: hot-air continuous flow dryer

- Biomass Types: grains, low moisture content biomass




2.6.2.6 Exergy and Energy Efficiency

Drying procedures are energy intensive, 1 – 3GJ/ton DW correspond to 5 – 15% of the resulting

calorific value of the feedstock. It is suggested that with adequate heat recovery systems up to

65% of the energy could be recovered and used in either a heat recycling system or in other heat

demanding processes. Similarly high energy efficiencies are present with contemporary multistage

cascading evaporators which can reach as low as 1.0GJ/ton water removed. Conversely nearly all

modern dryers are also capable of utilising off-heat and/or district heat from other thermal

sources. Furthermore, in terms of exergy direct drying system are highly inefficient. The exergy

content of hot air (100°C) is below 100kJ/m³, whereas the energy content is around 2500kJ/m³. A near complete transfer of the fuel energy content to hot air is present suggesting a highly


efficient system, yet the exergy efficiency is closer to 0. This presents ample options to increase

the energy efficiency with better heat integration by using other sources of heat. However, as

beneficial as the mentioned improvement options are, on the rural small-scale they are limited or

completely unfeasible. Since drying operations are best performed in the immediate proximity of

the biomass field to maximize the logistical energy savings, little can be done about the

energy/exergy intense drying options. Only in regions that can properly capitalise on favourable

climate conditions can the external fossil fuel demand for drying be minimized. The energy

required for size and moisture reduction systems must be carefully balanced for the specific

logistical system involved.

2.6.3 Compaction

Currently most biomass is still used for combustion and gasification processes. For these systems

it is common to compact the sized and dried (10% moisture) biomass into pellets. Creating dry

pellets has two advantages for the bioenergy sector; lower logistical costs and a higher heating

value of the feedstock. As this work pertains to biomass as a chemical feedstock pelletization is

not required or even advisable. Additional energy would be involved in opening up the pellet

structure to expose the biomass to the pretreatment steps of a biorefinery.

2.7 Manufacture, Transport and Repairs (MTR)

Large scale cultivation and distribution of non-food biomass requires a considerable amount of

dedicated machinery, both new and old. As they form an integral part of the feedstock

acquisition process the so-called “MTR” for the dedicated machinery must be taken into account.

MTR stands for and connotes the amount of energy sequestered in the manufacturing, delivery

and maintenance of the machinery. Substantial amounts of MTR energy are involved in the

production and continued operation of the machinery involved in the biomass sector. First an

overview, description and general energy requirements of the three components to MTR will be

conducted. This will be followed by considerations and calculations to the dedicated machinery

involved in biomass production and logistical chains.

2.7.1 Manufacturing Energy

Manufacturing of machinery requires vast amounts of the basic raw materials and is associated

with high energy inputs. Despite the advent of high-grade plastics, ceramics and other non-metal

materials steel production and moulding still represents the bulk of the manufacturing cost. As

early as 1973 a simple LCA determined the primary energy demand of the automobile industry to

be 86.77MJ/kg39. Thus, a standard car weighing in at 2000kg relates to an energy demand of

around 175GJ/car. Put in perspective this relates to the energy content of around 100 petrol

fillings or 30000 – 60000km travelled. Catalyzed by the energy crisis a drastic change in raw

material energy efficiency has occurred since the 1970’s. In 1979 USA steel manufacturing cost

was between 22 – 60MJ/kg39. In 1996, the energy demand in the EU dropped by about half to

range between 20 – 30MJ/kg40. Ten years have since transpired which have certainly promoted a

further lowering of the energy intensity. Similar trends are noticeable throughout the raw material


sector; for example aluminium was 214 – 383MJ/kg in 1979 and dropped to 125 – 186MJ/kg by

1996, signifying again a reduction of around 50%. By comparing other manufacturing LCA

studies 86.77GJ/ton was chosen as representative for the farm machine production energy39. The

figures from that study and MTR overview for farm machinery are frequently referenced to, even

in recent publications. Considering the importance and dependence on the steel industry

reducing the manufacturing cost by 50% seems logical to represent recent times. Thus 43.4MJ/kg

is set as the machinery energy demand.

2.7.2 Transport Energy

A elderly study from 1977 determined the energy costs for the transportation and distribution of

manufactured goods to require an additional 8.8MJ/ton39. In the last 30 years the energy

efficiency of transportation has significantly improved. As mentioned and calculated in the heavy

goods vehicle transport section (2.4.1) a reduction of nearly 25% was achieved over 20 years via

the Euro emission norms. The transportation energy portion will be set at 5.9MJ/kg to

implement the assumption of a 33% efficiency improvement over the course of 30 years.

2.7.3 Repair Energy

All machines require servicing and repairs along their lifetime; maintenance is a relatively energy

intense process because of the replacement parts, liquid changes, actual repairing time and

travelling requirements. The replacement parts represent the largest portion at 67.1% of the total

repair energy. In adhering to the simplest approach used to estimate MTR, the repair energy

input is set as a ratio against the manufacturing energy. On average 55% of the initial

manufacturing energy is required for maintaining machinery. The quality and logistics of service

and repairs have improved vastly since the study. Many problems in the manufacturing sector

(like that of rust) have been resolved or minimized. The following table lists the resulting energy

sequestered in repairs of various machines over the course of their lifetime, assuming 50%

reduction achieved since 198539.

Table 2 Repair energy of various farm machinery

Equipment Ratio:

repair-to-manufacturing, old Ratio:

repair-to-manufacturing, new Tractors 0.49 0.25 Combines 0.24 0.12 Mouldboard Ploughs 0.97 0.49 Row Planters 0.43 0.22 Row Cultivators 0.58 0.29 Field Cultivators 0.51 0.26 Disc Harrow 0.61 0.31 Corn Pickers 0.35 0.18 Stalk Choppers 0.33 0.17 Cutterbar Mowers 1.44 0.72 Balers 0.39 0.20 Forage Harvester 0.39 0.20 Rotary Hoes 0.59 0.30 Sprayers 0.37 0.19

Average 0.55 0.28


2.7.4 Farm Equipment MTR

Expanding the current agricultural systems to incorporate large-scale biomass production for

non-food purposes will require an investment in new farm machinery. In the industrialized

regions this implies new tractors and implement tools, which correspond to a considerable

amount of new materials and energy demand in the form of MTR. It is foreseeable that the

developing world will receive older and used equipment from the industrialized world. This

makes estimates of MTR energy values difficult as the allocation must be performed over the

entire operational lifetime. Placing an MTR cost on older machinery which has not been

dedicated to the production of non-food biomass throughout its entire operational lifetime is

questionable and challenging. However, in many areas of the world older models and smaller

implements are still manufactured. And as biomass propagation will be a long-term activity it will

be assumed that even in the developing world machinery will be strictly dedicated over its

lifetime.

The above text box provides a guideline to the methodology used in calculating the MTR energy

demand for farming procedures. As can be seen it is based on the parameters of the tractor and

field implement (weight and operational lifetime) and brought into relation with the field

capacity. Relating it to the field capacity (ha/h) allows the MTR energy demand to be presented

as a function of time (MJ/h) and regarded as a component of the total energy requirement of the

farming operations. The calculations for the resulting MTR of the different farming operations

are not present but are partially covered in the previous Section 2.3 and the weight and

operational lifetime values12, 39. The resulting farming equipment energy and exergy costs are

presented in the following Section 2.8 which includes the MTR component. Depending on the

region and procedure, MTR costs correspond to 2.5 – 16.0% (7.0% average) of the total farming

operation energy cost.

2.7.5 Transportation and other equipment MTR

MTR should be determined for the transportation machinery for they form an integral part of the

biomass production chains, since they too are dedicated. The MTR will be related to the

transportation distance (MJ/km) and also additionally to the transported tonnage (MJ/t⋅km). These separate values are calculated because as mentioned in the transportation Section 2.4

dedicated modes of transportation return empty, implying zero transported tonnage for half the

Example: Calculation Method for MTR Energy of a Farming Procedure

Farming procedure: chisel plough in an industrialized region w ith a f ield capacity of 1.4ha/h

Tractor Plough

Manufacturing: 43.4MJ/kg ⋅ 6600kg = 286.4GJ 43.4MJ/kg ⋅ 1000kg = 43.4GJ

Transport: 5.9MJ/kg ⋅ 6600kg = 38.9GJ 5.9MJ/kg ⋅ 1000kg = 5.9GJ

Repairs: 286.4GJ ⋅ 0.25 = 71.6GJ 43.4GJ ⋅ 0.49 = 21.3GJ

Total MTR: 396.9GJ 70.6GJ

Operational Life: 12000h 2000h

MTR per time: 33.1MJ/h 35.3MJ/h

MTR per area 33.1MJ/h ÷ 1.4ha/h = 23.6MJ/ha 35.3MJ/h ÷ 1.4ha/h = 16.9MJ/ha

Total MTR for field operation: 40.5MJ/ha


travelled distances. To be able to relate the MTR energy demand to the transportation distance

the operational lifetime is expressed in terms of total travelled distance (km). Transportation

machinery can travel remarkably far distances in their lifetime, for example a modern truck can

cover around 1 million kilometres. Benefiting from near-continuous operation, large and robust

designs, transportation machines require a significantly lower portion of repair energy. The

transportation MTR calculations with the machine weight, lifetime and repair ratio assumptions

have been calculated but due to their small portion are not included in this text. The textbox

below provides a insightful guideline to the methodology used in calculating the MTR energy

demand for transportation operations. The resulting transportation energy and exergy costs is

presented in the following Section 2.8 which includes the MTR component. MTR corresponds to

a rather minor portion of the total transportation operation energy costing being 0.9 – 3.1%

(1.9% average), depending on the region and procedure.

2.8 Overview Input Type Costs

Table 3 Labour costs

Region Type Energy Costs (MJ/day)

Exergy Costs (MJ/day)

Developing Manual Labour 20.7 21.7 Industrialized Mechanized Operation 633 665

Table 4 Main tractor specifications

Region Type Weight (kg)

Nominal Power (kW)

Specific Fuel Consumption

(g/kW⋅h) Developing Massey-Ferguson MF240 1730 32 251 – 262 Industrialized New Holland TM-165 6600 107 273 – 328

Examples: Calculation Method for MTR Energy of a Transportation Procedure

Transportation System: truck and bulker transport in an industrialized region

Truck Bulker

Weight: 8500kg 15% of 45000ton = 6.75⋅106kg

Manufacturing: 43.4MJ/kg ⋅ 8500kg = 368.9GJ 43.4MJ/kg ⋅ 6.8⋅106kg = 0.293PJ

Transport: 5.9MJ/kg ⋅ 8500kg = 50.1GJ 5.9MJ/kg ⋅ 6.8⋅106kg = 0.040PJ

Repairs: 368.9GJ ⋅ 0.25 = 92.2GJ 0.293PJ ⋅ 0.063 = 0.018PJ

Total MTR: 511.2GJ 0.351PJ

Operational Life: 1.0⋅106km 25y ⋅ 25knots ⋅ 8000h/y = 9.3⋅10

6km

MTR per distance: 511.2GJ ÷ 1.0⋅106km = 0.51MJ/km 0.351PJ ÷ 9.3⋅10

6km = 46.8MJ/km

Transported Tonnage: 28ton 45000ton

Total MTR 0.018MJ/t⋅⋅⋅⋅km 0.001MJ/t⋅⋅⋅⋅km


Table 5 Farm equipment costs

Region Tractor Type Implement Field Capacity

(ha/h) Energy Costs (MJ/h)

Exergy Costs (MJ/h)

Chisel Plough 0.37 894.7 883.2 Field Cultivator 1.40 236.1 233.5

Harrow 2.92 119.5 117.0 Grain Drill 2.01 175.9 171.7 Drill 0.92 384.5 375.4

Row Crop Planter 2.49 136.2 134.0 Cuttings Planter 2.47 196.2 195.2 Bulb Planter 0.71 477.1 469.3

Fertilizer Sprayer 15.4 11.7 11.5 Mower 4.40 104.1 102.7 Rake 8.00 18.6 18.3

Forage Harvest 3.25 153.1 152.0 Bailer 5.20 116.1 115.6

MF240

Root Digger 0.67 550.1 539.7

Developing

- Crop Duster 395 85.4 85.4

Chisel Plough 1.41 964.7 955.0 Field Cultivator 5.63 240.0 237.8

Harrow 12.0 116.8 115.0 Grain Drill 9.37 151.6 148.8 Drill 3.95 359.7 353.1

Row Crop Planter 11.73 117.7 116.1 Cuttings Planter 4.94 97.3 95.4 Tuber Planter 2.93 470.7 464.4 Fertilizer Sprayer 22.4 9.0 8.7

Mower 17.6 72.6 71.6 Rake 10.0 20.7 19.7

Forage Harvest 4.65 279.2 276.6

TM165

Bailer 7.45 80.3 78.8 - Crop Duster 395 85.5 85.5

NH - TX63 Combine Harvester 4.23 513.5 504.1 NH – FX40 SP-Forage Harvester 3.03 892.2 878.0

Potato Harvester 1.82 1849.0 1826.6

Industrialized

Grimme SF3000 Beet Harvester 2.64 1274.5 1259.0

Table 6 Transportation costs

Energy Costs Exergy Costs Capacity

Loaded Empty Return Loaded Empty Return Region Method ton MJ/t⋅km MJ/km MJ/t⋅km MJ/t⋅km MJ/km MJ/t⋅km

Tractor 6 2.46 11.1 - 2.45 11.1 - Truck 8 1.69 6.2 - 1.67 13.9 - Developing

Train 800 - - 0.398 - - 0.398

Tractor 16 2.15 26.1 - 2.14 25.9 - Truck 28 0.67 11.7 - 0.66 11.6 - Truck* 35 0.90 14.0 - 0.90 13.9 - Train 800 - - 0.235 - - 0.301

Industrialized

Barge 1750 0.21 312.1 - 0.21 311.4 -

Tanker 75000 - - 0.057 - - 0.057 Both

Bulker 45000 - - 0.115 - - 0.115 *Used also in South America – Developing World


Table 7 Storage/Transfer costs

Table 8 Pre-processing costs

Energy Exergy

Method Conditions GJ/tonWW

Cutting 20mm chipped size 0.075 0.075 Crushing 5mm particle size 0.44 0.66 Shearing 1.5mm particle size 1.09 1.75

Table 9 Drying costs

Moisture Conditions Energy Exergy

Method Input Output GJ/tonH2O Removed

Natural Air <50% 30% 0 0 Filter Press >50% 30% 0.23* 0.35* Conveyor Belt <40% 20% 4.5 4.7 Rotary Drum >20% 20% 4.7 4.9 Silo/In-Bin <30% 15% 3.9 4.3

*filter press energy/exergy terms are in GJ/tonWW: no dependence on initial moisture content

Type Material Material Loss Energy Exergy

Loose 3% 14.5MJ/m³ 14.5MJ/m³ Wheel Loader

Packed or Bagged 3% 7.3MJ/m³ 7.3MJ/m³ Loose, dry 2% 1.8MJ/ton 2.3MJ/ton Loose, wet 2% 0.36MJ/ton 0.46MJ/ton Conveyor

All, ship/train bound 1% 1.2MJ/ton 1.5MJ/ton Stacker/Reclaimer Loose 6% 11.4MJ/ton 14.7MJ/ton

Crane, Gantry Bucket Loose 1% 2.32MJ/m³ 2.98MJ/m³ Crane, Gantry Shovel Loose 1% 3.13MJ/m³ 4.02MJ/m³

General All 2% 5MJ/m³ 6.4MJ/m³


3 Farming Operations The previous section dealt with the collection, investigation and calculation of the core energy

and exergy input costs associated with the operation of the common agricultural machinery for

both the developing world and industrialized world. This section will systematically link those

base calculations to the requirements and typical farming procedures for the selected crops.

3.1 Machinery Employment

3.1.1 Operational Labour Requirements

The energy requirements of an agricultural machine are not defined solely by its diesel

consumption and MTR. To an extent the technology has reached sufficient maturity to enable

fully automated farming machinery, but as public and governmental acceptance is still lacking

humans are required for the operation. This presents a minor but additional factor based on the

labour input and operational hours per cultivated area. By taking the reciprocal value of the field

capacity (ha/h) known for each of the farming procedures, the operational hours per hectare

(h/ha) can be determined. Furthermore, tractor implements must be attached to the tractor and

set-up properly before operated presenting an additional labour hour. Daily field capacity per

shift is thus reduced. Reaping the benefits of intensified and efficient farming practices an

industrialized farmer needs not work more than the standard 8 hours a day whereas it is common

in developing regions that agricultural workers go 12 hours straight.. The total hourly operational

labour input cost is determined by factoring the shift length with the previously listed daily labour

input. The following table lists the total energy/exergy input of farming procedures:

Table 10 Farming procedure energy and exergy cost

Farming Procedure Implement Region Tractor Type Fuel Labour Energy ExergyType Type OECD Model* ha/h ha/shif t l/ha h/ha

Developing MF240 0.4 4.4 22.03 2.93 901.2 890.0

Industrialized TM165 1.4 11.3 24.11 0.80 1027.8 1021.3

Developing MF240 1.4 16.8 5.87 0.77 237.9 235.3


Developing MF240 2.9 35.0 2.82 0.37 120.3 117.9


Developing MF240 2.0 24.1 4.08 0.54 177.1 173.0


Developing MF240 0.9 11.0 8.92 1.18 387.2 378.2


Developing MF240 2.5 29.9 3.29 0.44 137.2 135.0


Developing MF240 2.5 29.6 5.03 0.44 197.1 196.2


Developing MF240 0.7 8.5 11.52 1.53 480.5 472.8


Developing MF240 15.4 184.8 0.29 0.07 11.8 11.7


Developing MF240 395.0 4740.0 2.32 0.00 88.2 88.2


Combine Industrialized TX63 4.2 33.8 12.27 0.27 534.6 526.2

Developing MF240 4.4 52.8 2.56 0.25 104.6 103.3


Developing MF240 8.0 96.0 0.45 0.14 18.9 18.7


Developing MF240 3.3 39.0 3.89 0.33 153.8 152.8


Developing MF240 5.2 62.4 2.98 0.21 116.6 116.0


Forage Harvester Industrialized FX40 3.0 24.2 21.60 0.37 921.6 908.8

Beet Harvester Industrialized SF3000 2.6 21.1 31.50 0.43 1308.2 1294.4

Potato Harvester Industrialized SF3000 1.8 14.6 45.70 0.62 1898.0 1877.9

Root Digger Developing MF240 0.7 8.0 13.10 1.62 553.7 543.5

Harvesting

Crop Duster

Soil Treatment

Mower

Rake

Chopper

Bailer

Fertilization

Tillage

Grain Drill

Planting Row Crop

Cuttings Planter

Tuber Planter

MJ/ha

Capacity

Chisel Plough

Drill

Field Cultivator

Harrow


Despite the shorter working day the larger and more powerful tractors of the industrialized

regions greatly increase field capacity and facilitate less operational working hours per cultivated

land. Not a single farming procedure requires a full labour hour per hectare in the industrialized

regions, whereas many of the same procedures cross the 1h/ha mark in the developing regions.

Although the labour requirements are greatly reduced in the industrialized regions, the energy and

exergy requirements are generally higher, further proving the trend of the agricultural sector

transforming from being labour intensive to being fossil fuel intensive.

3.1.2 Cultivation Practice Factors

Listed in Chapter 4, Section 3.1.3 the cropping systems of the choice crops were presented. The

replanting frequency and the harvest cycle rate being crop dependent are needed to determine the

yearly factor for the farming operations. For instance the oil palm is replanted only every 25 years

meaning that on a yearly basis the tillage procedure is 0.04 times the input rate, while an annual

crop like the sunflower, replanted every year, has a tillage factor of 1. This yearly factor is used

for the calculation of the tillage and planting procedures.

For fertilization and pesticide application, a slightly modified yearly factor is used. Fertilizer and

to a lesser extent pesticides are mixed with the seeds before planting. This single application run

is mitigated for seed-based crops only as this option is not possible with cuttings/setts. Nutrients

and crop protection chemicals are required periodically throughout the growing season for many

crops. Called “dressings”, up to half a dozen separate dosing runs can be required over the course

of the growing duration. The yearly factor used for tillage and planting is therefore not

appropriate for soil treatment procedures. Here the establishment and growth duration will be

used for calculating the total growth period. The yearly growth factor is determined by relating

the total growth period to a single year and is set at 1 for crops with a growth period less than 12

months. Calculation of the soil treatment procedures results from combining the total application

frequency over the course of the total growing duration and the yearly growth factor.

Harvesting and collection operations also necessitate a factor. The harvesting cycle rate indicates

the frequency of the harvesting procedures over the course of the growing season. Several crops

are harvested multiple times throughout the year to achieve high crop yields. A perfect example is

sweet sorghum which needs 5 separate harvests to capitalize on the grass-like yield properties.

The yearly factor for harvesting procedures is simply the harvesting cycle rate.

3.2 Labour Employment

Not all the procedures in the cultivation and harvesting of biomass are performed by the

deployment of agricultural machinery; many steps are still carried out by manual labour. This is

especially true in the developing regions where typically entire harvesting operations are

performed by manual labour. A detailed paper has listed and calculated the labour input (h/ha)

for select main crops in a multitude of regions41. Nearly all of the choice crops in their

corresponding regions are covered by the study. Yet for some crops, like the oil palm42,


assessment must be conducted individually or grouped by the crop type and region. The labour

employment has been split into the different farming procedures categories based on expected

portion of the work distribution. The same cultivation practice factors were taken as with the

machinery employment.



The overview of the farming procedure calculations is found in the accompanying database

spreadsheets. It is broken down into the 4 farming procedure sections; tillage, planting, soil

treatment and harvesting. The above mentioned factors and extra manual labour figures are

incorporated. Total energy and exergy values are accumulated for each of the four categories. The

column “use” is meant to denote the employment of that particular agricultural machinery for the

crop. A “1” implies usage and a “0” means not used. A few crops employ no machinery in some

of the farming procedure categories as can be seen by the series of 0’s and the high value for the

labour. This is especially the case for the harvesting section. The following graph incorporates all

factors for the total farming procedure input in MJ/ha terms:

Figure 1 Resulting farming procedure input

Farming Procedu re Input

0

2500

5000

7500

10000

Cas

sava

Grass

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar c

ane

Sunfl o

wer

Swi

tchg

rass

Toba

cco

Whe

at

Wil low

tree

MJ/ha

Energy

Exergy

Based on 10-year ave rage

Includ ing Labour and Mach inery

Sweet sorghum in Kenya is unique because to obtain the best yield figures from multiple grass-

like cultivation practices, an “industrialized” self-propelled forage harvester must be employed.


Should this not be done the yields will mirror the national average, being less than half at

35ton/ha WW. In the other developing regions harvesting is conducted almost exclusively by

manual labour with no urgent expansion of machinery exploitation needed to obtain high yields.

Developing region crops are then amongst the lowest for farming procedures, averaging around

2.5GJ/ha. The difference to the industrialized region crops is however not always great. Several

of the industrialized crops fair equally well in low energy intensity. An annual harvest using a

single combine harvester and a rake and bailer implement for straw collection proves highly

efficient, averaging around 3.0GJ/ha for these crops. Multiple harvesting is significantly more

energy intensive (tobacco, and other grasses) and as expected tuber crops (potato, sugar beet) are

amongst the most energy intensive.

3.3.2 Efficiency

Precisely as with all the primary energy inputs (Chapter 5) it is misleading to visualise the total

farming procedure input energy in terms of land without relating it to the resulting energy output.

This can be performed because the total resulting energy output (see Chapter 4) is expressed in

terms of land area as well. The two figures combined give the farming efficiency as indicated by

the simple formula:

[ ]haMJInputFarming

haMJOutputEnergeticEfficiencyFarming

/_

]/[__ =

The following graph (Figure 2) displays the resulting farming procedure efficiency for the best

practice yields. As one would expect the developing region crops which rely heavily on manual

labour for harvesting are highly energy efficient. At values well above 15000%, reaching 41000%

for the oil palm a loss of a mere 0.67% to 0.25% is found. Even the maize crop with its high

yields and straightforward combine harvester technique yields 14144% energy efficiency which is

equivalent to less than 0.71% energy loss. Other industrial region crops do not fair as well

hovering around 5000% or a loss of 2%. The worst energy efficient crop in terms of farming

procedure is the potato. Despite the high yields of over 65tonWW/ha an energy efficiency of

2780% is found resulting in an energy loss of 3.6%. This approaches the energy losses associated

with the nutrient application/uptake costs. Yet for all the crops the farming procedures remain

several orders of magnitudes below the fertilizer costs. A transition to larger machinery with

higher engine power and the promotion of an increased quality of life for farmers (chiefly in the

developing regions) will not have a drastic lowering effect on the overall energy efficiency of

biomass propagation. None of the investigated crops have an energy loss higher than 5% (or

lower than 2000% efficiency) for the farming procedures, generally signifying that farming does

not have a detrimental influence on the overall energetics and is actually quite efficient. The

subsequent analysis is based on the relative values between the different crops.


Figure 2 Resulting farming procedure efficiency

Efficiencies

0

5000

10000

15000

20000

25000

Cas

sava

Grass

Luce

rne

Maize

Oil pa

lm

Pot

ato

Rap

esee

d

Sor

ghum

Soy

a be

an

Sugar b

eet

Sug

ar can

e

Sunfl o

wer

Swi

tchg

rass

Tobac

co

Whe

at

Willow

tree


]

Energy

Exergy

Based on Fa rming Procedure Energy

3.8E5

4.1E5

2.5E5

3.3.3 Analysis

Table 11 Comparative farming input overview

Crop Farming Procedure (energy) Farming Procedure (exergy)

Common Name Input Efficiency Input Efficiency

Cassava + + + + Grass O - O - Lucerne O - O - Maize + + + + Oil Palm + + + + Potato - - - - Rapeseed + + + + Sorghum - O - O Soya Beans + O + O Sugar Beet O O O O Sugar Cane + + + + Sunflower O - O - Switchgrass O - O - Tobacco - - - O Wheat + O + O Willow Tree + - + -

Input: + below 5.0GJ/ha, - above 7.5GJ/ha, O between 5.0 – 7.5GJ/ha Efficiency: + above 10000%, - below 5000%, O between 5000 – 10000%



4 Biomass Logistics Location, location, location – the phrase that has become a cliché in the real-estate sector is also

perfectly atoned to the logistics of biomass. Propagation and production of biomass is spread

across great areas of land in diverse and frequently isolated regions of the world. The chemical

industry however, as mentioned in Chapter 1, is concentrated in a select few places of the world.

The top 3 petrochemical cluster areas are Houston (North America), Singapore (Asia) and

Rotterdam (Europe). Being major port cities they have evolved into key distribution and

processing centres of the petrochemical industry and serve the needs of the regional chemical

industries coupled to their hinterland. All biomass that is foreseen as a chemical feedstock must

in one form or another pass through and be treated at such chemical processing hubs. And as the

focus of this entire investigation is on the transition to a biobased chemical industry, above all for

Europe, Rotterdam will be set as the “factory gate”. It is the main location of Europe’s existing

petrochemical sector and it is the best adapted and most logical location for future biomass.

All biomass production and transportation chains will be directed towards reaching the port of

Rotterdam. As the factory gate, no additional transportation considerations need to be made

upon shipment delivery, because the proposed biobased chemicals will match the production and

distribution system of Rotterdam. Logistical planning is required to minimize the energy

requirements of transportation. In this section each of the choice crops in their corresponding

regions will be subjected to the creation of the most fossil fuel energy attractive logistical system.

Location, distances, transportation options, pre-processing and drying options will all be carefully

assessed for each biomass production and transportation chain.

4.1 Rotterdam

Located close to the North Sea on the

banks of the delta created by the merging

Rhine and Maas rivers, Rotterdam is a

world city based on its harbour activities

boasting 0.59 million inhabitants and 1.2

million in the greater metropolitan area. It

is a trading and industrial based economy

forming one of the three pillar cities of the

country. In the Netherlands, there is an

expression illustrating this “Amsterdam to

party, The Hague to live, Rotterdam to work” whereas Rotterdammers prefer a slightly modified

version “In Rotterdam the money is earned, in The Hague it's divided, and in Amsterdam it's spilled”. From

1962 to the late 1990’s the port of Rotterdam was the world’s biggest and busiest harbour. With

the development of containerization and off-shoring practices Rotterdam has fallen to 7th in

containers and 3rd in total cargo. Having a higher portion of general cargo traffic illustrates the

focus on the heavy industries, like the petrochemical sector. The port covers a surface area of

105km² along 40km and 5.1km² is dedicated to industrial terrain. In 2005, 370Mton of cargo


passed through the port of Rotterdam of which 10.7Mton was agricultural bulk. This suggests

that the know-how and facilities to handle biomass is already present to a degree. The graphic

below highlights the hinterland of Rotterdam; the yellow circles being major trading hubs and

industrial areas and the light-yellow object depicts the regions directly linked to the port. The

port of Rotterdam is the ideal location to receive and process biomass for the chemical industry.

4.2 Distance to Rotterdam

The first step in assessing the energy requirements in biomass logistics is to determine the

distance between the cultivation fields and the port of Rotterdam. In most instances the total

transportation distance is covered by a combination of the different modalities. Determining the

portion and relative distance covered by each of the individual modes of transportation is

achieved by using different navigational sources, whereas determining the most energy efficient

combination of transportation modes and location of transfer hubs is slightly more arduous.

Example: Since both tractor and tru ck transport are the most energy intensive forms of transportation, demanding at least twice as much as other forms, their employment must be minimized. Switching to the next larger mode of transportation requires that ample biomass is available to provide for a fully loaded shipment. At full capacity, a train for example can handle 800tons. Considering the average transportable wet weight yield to be around 25tonWW/ha, a cultivated area of at least 32ha (0.32km²) would be needed to satisfy one train load. Using simple geometry that relates to a transportation radius of 0.33km, so even when taking inconstant harvesting dates and multipurpose land utilization the transport distance is easily within the bounds on field tractor delivery. Supplying the larger transportation modalities is thus not restricted by the volumes of produced biomass in the immediate surroundings but by the infrastru cture. Train terminals are not located every 0.66km of track (which is the length of some grand stations), they are positioned by multiples of 10km. In some rural areas intervals of 50km are easily possible between transfer junctions.

4.2.1 Starting Point

In Chapter 4, Section 4.1 the locations chosen to represent the typical regions of cultivation for

the particular biomass crops were listed. Given in global coordinates, the areas covered are vast,

ranging between 100km² and 150km². To assist in the calculation of the total transportation

distance determination a small village/settlement in the region has been selected. This will be

representative of the first stage collection and temporal storage of biomass; a place where the

Port of Rotterdam

Rotterdam is Europe’s main port for incoming and outgoing trade in crude oil, oil products, chemicals,

iron ore, coal, metals, foodstuffs and containers. Companies often choose Rotterdam because of its strategic location in Northwest Europe, the depth of the port (24 metres/75 feet), the many port facilities and the excellent hinterland connections (the Rhine!). Doing business via Rotterdam brings indisputable advantages of scale. That is the reason why the German steel industry , for example, imports the majority of its raw materials – iron ore, coal - via Rotterdam.

Many American and Asian companies use Rotterdam as a base for the distribution of their (consumer)

goods throughout Europe. In the immediate vicinity of the container terminals, there are large European distribution centres. Not only for the efficient delivery of products on the continent, but also for their distribution to destinations overseas, such as Great Britain, Scandinavia and the Baltic region.

Rotterdam is among the top three (petro)chemical clusters in the world, with Houston and Singapore. A

large percentage of (petro)chemical production in the port finds its way to industrial centres in the rest of

Europe and on other continents. The port is connected to an extensive underground pipeline network that cuts right across Western Europe.

www.portofrotterdam.com/en/home


farmers will concentrate their harvest for distribution and in many cases expose the biomass to

initial pre-processing options. Tractors are used at this stage with travelling distances ranging

from 5 – 20km depending on the typical farm sizes, density and infrastructure of the region. For

example, densely clustered European farm land will be set at 5km travelling radius whereas the

scattered vast African farm land will be set at 20km. Pick-up is almost exclusively performed by

trucks which, with a given location, enables the use of navigational programs.

4.2.2 Mode of Transport

This sub-section deals with the source of data and calculation methods for determining the

distances involved in logistics for the different modalities.

4.2.2.1 Road

For most areas in the world online navigational programs can

provide a route plan along existing roadways in the region.

ViaMichelin43 and Google maps44 are two good sources for

determining the distance between the set regional starting

point and the next transfer hub along roads. In some regions,

especially in underdeveloped regions, route planners are

currently unavailable and distance determination must be

judged by reading physical maps and the distance legend.

4.2.2.2 Rail

In many instances railways follow the general path of motorways with the major exception that

they are slightly more direct, implying a straighter and shorter path between hubs. The rail

distance will be determined using the road route planners with a 10% distance reduction to

compensate for the infrastructural difference. The EcoTransit model19 will be used for regions in

Europe as it provides accurate distance calculations along the entire European rail system.

4.2.2.3 Inland Waterways

Motorways also have the tendency to follow major rivers and inland waterways. Like the rail

distance calculations the road route planners will be used to determine the inland waterway

distances. But despite many canals and rivers artificially straightened a 10% extra distance will be

added to compensate for the curvy, non-straight nature of rivers.

4.2.2.4 Ocean

Determining the shipping distance between port

cities is performed with the help of the computer

program NetPas45. The optimal shipping route

between the ports is calculated and plotted using

the online database. It provides ample

information relevant to sea logistics, amongst

them the total distance.


4.2.3 Topography

The world, as famously said, “is not flat”. Topography is the broad study of the Earth’s surface

features with terrain relief characteristics covering a major portion. Flat regions, like the

Netherlands, prove to have positive transportation fuel demand reductions. Mountainous

regions, like Malaysia, prove to have transportation fuel demand increases. For tractor, truck, and

train transportation the terrain topography has a significant effect on the fuel consumption. Since

great distances are covered in the logistics of biomass entire regions will be grouped into one of

three gradient types: flat, hilly, or mountainous. Most populated areas in the world have a slightly

hilly terrain which will form the default landscape. The following table lists the compensation

factors for the modalities energy demand.

Table 12 Topography fuel consumption factors

Terrain Type Tractor Truck Train

Flat -5% -5% -25% Hilly (default) 0% 0% 0% Mountainous +5% +5% +20%

4.2.4 Resulting Distance and Mode of Transportation

Listed in the table below is the resulting distance required to transport each of the harvested

crops from their specific growth region to the Port of Rotterdam. It is broken down into the

different selected modes of transportation.

Table 13 Break down transportation distances

Crop Mode of Transportation

Tractor Truck Train Barge Vessel Total Common Name Distance/km

Cassava 20 100 600 - 4379 5099 Grass 5 23 - 176 - 204 Lucerne 15 95 - 2750 4822 7682 Maize 10 15 65 1050 4822 5962 Oil palm 40 80 - - 8837 8957 Potato 5 23 - 176 - 204 Rapeseed 5 8 178 - - 191 Sorghum 15 100 650 - 6252 7017 Soya bean 10 40 - 1750 4822 6622 Sugar beet 5 20 - 425 - 450 Sugar cane 15 200 - - 5417 5632 Sunflower 5 38 223 - 458 724 Switchgrass 10 15 65 1050 4822 5962 Tobacco 20 40 340 - 10767 11167 Wheat 5 38 223 - 458 724 Willow tree 5 55 - - 902 963

This is a simplified table, for the detailed calculation to derive at the biomass logistical chains

with all the necessary considerations and transfer hubs is not listed. The base energy and exergy

requirements have also been calculated in wet weight, MJ/tonWW.


4.3 Size and Moisture Reduction

For many of the crops there are two harvestable components; the agriculturally relevant crop

component and the residue (or leftovers) like stover. As these crop components have completely

different properties and process options to reduce size and moisture content they will be handled

and shipped separately. The properties of main interest are the moisture content and bulk

density. Typical harvested bulk densities have a natural range of roughly 10%. Sources listing

crop bulk densities are scattered, which implies that several assumptions based on the similarity

of the crop components are required14, 46, 47. For example, tobacco forage harvested will have the

same bulk density as grass at 640kg/m³ and the stover/Leaves of the cassava will match that of

the potato being 520kg/m³. The “wet” bulk density and moisture content are used to determine

the resulting “net” bulk density, being the amount of actual dry biomass present per volume.

Presented below are two tables listing the moisture content and bulk densities for both crop

components prior to and after sizing and moisture reduction treatment. For the vast majority of

the crop components it is noticeable that the harvested net bulk density is below 500kg/m³

meaning, that when left untreated less biomass material would be transported than water and air.

A break down of the crop specific drying and size reduction procedural steps and the calculations

for the energy costs is highly complex and can be traced in the accompanying database

spreadsheets. The resulting moisture content is based on the previously stated desired levels of

15% and 20% to facilitate long-haul transportation. Several of the harvested crop components

have moisture contents lower than the minimum required level negating any moisture reduction

techniques. Aside from the desired net bulk density increase, an increase of the wet bulk density

is also induced through sizing and moisture reduction techniques. It will be assumed that the bulk

density raises by 20% with treatment and for those crop components resulting in a calculated net

bulk density below 500kg/m³ the bulk density will be set at 520kg/m³.

Table 14 Bulk densities of agricultural crop components before and after treatment

Harvested Conditions Post-Processing Conditions

Crop Component Moisture Content

Bulk Density

Net Bulk Density

Moisture Content

Bulk Density

Net Bulk Density

Common Name % kg/m³ % kg/m³

Cassava Tuber 69.9 670 202 20 804 643 Grass Whole 82.5 640 112 50 768 384 Lucerne Whole 75 640 160 50 768 384 Maize Seeds 20.6 600 476 15 720 612 Oil palm Fruit 26 750 555 20 900 720 Potato Tuber 78 670 147 78 804 643 Rapeseed Seeds 10 640 576 10 768 691 Sorghum Whole 50.8 640 315 20 768 614 Soya bean Seeds 10.2 720 647 10.2 864 776 Sugar beet Beet 76.6 700 164 76.6 700 164 Sugar cane Cane 82.5 300 53 20 360 520 Sunflower Seeds 20 600 480 20 720 576 Switchgrass Whole 12 240 106 12 550 484 Tobacco Whole 88 640 77 20 768 614 Wheat Seeds 20 770 616 15 924 785 Willow tree Whole 60 260 104 20 550 520


Table 15 Bulk densities of residue crop components before and after treatment

Harvested Conditions Post-Processing Conditions

Crop Component Moisture Content

Bulk Density

Net Bulk Density

Moisture Content

Bulk Density

Net Bulk Density

Common Name % kg/m³ % kg/m³

Cassava Stover/Leaves 39.8 520 313 20 624 520 Maize Stover 75 300 75 20 360 520 Oil palm Fronds/Truck 64.9 520 183 20 624 520 Potato Stover/Leaves 60 520 208 50 624 312 Rapeseed Stover/Pods 85.9 640 90 20 768 614 Soya bean Stover/Pods 60 640 256 20 768 614 Sugar beet Leaves/Tops 86.4 520 71 50 624 312 Sugar cane Stover/Leaves 77.5 520 117 20 624 520 Sunflower Stover/Husks 60.8 520 204 20 624 520 Wheat Stover 8 300 276 8 360 520

Sizing and moisture reduction procedures are giving in GJ/tonWW and/or GJ/tonH2O

removed. By knowing the input and setting the output moisture content and determining the

relative wet weight yield, the energy demand per unit operation can be calculated in terms of

GJ/ha and when brought in relation to the net dry weight yield, in terms of GJ/tonDW.

4.3.1 Transfer and Storage Systems

Sizing and drying operations are best performed as close to the field as possible. Considering that

most of the machines require a certain size and continuous feed flow to operate efficiently and

effectively, the first transfer hub (not the farm) will be selected as the location for these

operations. This is understood as the selected “starting point” or central location for a cluster of

agricultural fields. Thus transport via tractors will always be used for untreated, wet and bulky

biomass. And much like the sizing and moisture reduction calculations the moisture contents and

bulk densities heavily influence the transfer and storage system calculation, since the transfer

equipment energy demand is also given in MJ/m³ and MJ/tonWW terms. Relating them to the

bulk density, moisture contents and dry weight yield will result in MJ/ha and MJ/tonDW. The

table below lists the transfer equipment involves for the various logistical systems.

Table 16 Transfer system machine employment

Transport Mode or Location Type Transfer Equipment Specific Type Biomass Type

from to name name description

Tractor Storage Wheel Loader Loose All freshly harvested Storage Truck Wheel Loader Packed All freshly harvested Truck Train Conveyor Train/Ship Bound Any Truck Barge Conveyor Train/Ship Bound Any Truck Bulker Stacker/Reclaimer Loose Tropical Train Vessel Conveyor Train/Ship Bound Any Barge Bulker Crane Bucket Any Bulker Shore/Storage Crane Bucket Any *Storage Silo Conveyor Wet Forage/Grains *Silo Truck None - Forage/Grains *Vessel Land Crane Shovel Delicate

*Exceptions


Each transfer and storage operation is coupled to a loss of material ranging for 0.1 – 0.6% per

transfer. Following each of the transfer and storage calculations a total material loss of 0.70 –

1.29% is present over the entire logistical system.

4.3.2 Balancing Size and Moisture Reduction and Transport Energy Costs

It is a prerequisite for long-haul transportation of biomass to use sizing and moisture reduction

procedures to prevent degradation and lower the associated transportation costs. For shorter

distances, the benefits of reducing the size and moisture content becomes less of a prerequisite

and more of an option. In several cases when the distances are not great, it would actually be

more energy efficient to avoid preprocessing steps. Reducing the size and moisture content to

increase the net bulk density is energy intensive; 0.48 – 3.68GJ/tonDW. To warrant the

preprocessing procedures the total logistics energy with transportation, transfer, sizing and

moisture reduction must be lower than the direct (untreated) logistics system. Several of the

choice crops and logistic systems are confronted with such a trade-off decision. Below is an

example of the tuber portion of the sugar beet.

Figure 3 Logistics and preprocessing energy trade-off

Logistics and Preprocessing Relation

0

5

10

15

20

25

30

0 200 400 600 800 1000 1200 1400 1600 1800

Distance Covered with Modality (km)

Primary Energy Demand (GJ/tonDW)

Barge - Treated

Truck - Treated

Barge - Not Treated

Truck - Not Treated

425km

1050km

100km75km

Sugar Beet Tuber

In this particular example 425km is needed to cover the distance from the centralized collection

location in the harvest region to the Port of Rotterdam. Barge transportation has been selected

due to the availability in the region, but for the sake of comparison truck transport is also

included. Preparing the sugar beet tuber for long-haul transport requires 1.26GJ/tonDW. At the


425km marker, untreated barge transport would be the most energy efficient option and only at a

transportation distances beyond 1050km does preprocessing become attractive. The trade-off

distance is much shorter for truck transport at 100km. At distances below 75km untreated truck

transport is even more efficient than treated barge transport. The same can be conducted for the

tops/Leaves of the sugar beet and likewise the untreated barge transportation option is the most

energy efficient. Several other crops in the immediate hinterland of the Port of Rotterdam are

better left untreated before transportation. Furthermore, in the cases of forage and crop residues

components the option of initial natural air drying to reduce the moisture content to 50% is still

possible, advisable and included; being fossil fuel free. The crops and individual crop

components that do not gain from preprocessing are:

• Grass: 176km barge from Raalte, Holland • Potato: 176km barge from Raalte, Holland • Rapeseed: 178km train from Hannut, Belgium • Sugar Beet: 425km barge from Uchte, Germany



The total logistical system and resulting energy demand is determined by combining all the

individual aspects and interrelations of the crops together.

Figure 4 Resulting logistical input energy

Log istical Cost Overview

0

50000

100000

150000

Cas

sava

Gra

ss

Lucerne

Maize

Oil pa

lm

Potato

Rapes

eed

Sorghum

Soya

bean

Sug

ar beet

Sugar cane

Sunf

lower

Switc

hgras

s

Tobacc

o

Whea

t

Wil lo

w tr

ee

Primary Energy Cost (M

J/ha)

Transfer/Handling

Sizing and Drying

Transportation


The above graph presents the total logistical energy demand separated into the three main

categories; transportation, sizing/drying, and transfer/storage costs. The exergy-base graph is not

presented as there is little noticeable difference. Both represent the total crop as the individually

assessed agricultural and residue components are combined using the common denominator of

land area (MJ/ha). There is clearly a wide variation between the regionally selected crops resulting

in a primary energy input range of 6.1 – 149.2GJ/ha. A generalisation can be made; regional

crops have a low logistical energy intensity and globally distant crops have a high logistical energy

intensity. Long-haul bulker transportation is the least energy intensive transportation mode, but

when required to travel thousands of kilometres becomes a significant factor. Oil palm, tobacco,

sorghum and sugar cane being cultivated halfway around the world (>5000km sea travel) have

very high transportation costs with the greatest portion of the energy demand linked to ocean

transportation. It is also noticeable that the transfer and storage costs are minor, contributing

only a few percent to the total logistical input. Sizing and drying on the other hand, can for some

crops be the largest factor in the entire logistical chain. Rapeseed, wheat and the willow tree all

require sizing and drying to promote an efficient transport which is evident in the relatively high

sizing/drying input and low transportation input.

4.4.2 Efficiency

Precisely as with all the other energy inputs (e.g. farming in Section 3.3.2) it is misleading to

visualise the total logistical systems in terms of land without relating it to the resulting energy

output. As before the same simple formula will be used related the two terms:

[ ]haMJInputLogistic

haMJOutputEnergeticEfficiencyLogistical

/_

]/[__ =

The graph below visualises the resulting energy and exergy efficiency of the crop logistical

systems. This is the section and aspect of the agricultural feedstock (primary + secondary) input

energy cost where regional crops gain in competitiveness over their more lucrative foreign

counterparts. All of the tropical high-yielding crops that have previously ranked amongst the

most efficient in the other sections are now amongst the bottom. A key marker in the graph is

the 500% line corresponding to a 20% crop energy content loss due to the logistical system.

Several of the crops are even below this line. Lucerne, maize, sorghum, sugar cane and tobacco

are 5 examples of high yielding crops that loss more than 20% of their energy content due to the

required long-haul transportation distances to satisfy the European chemical industry. The potato

and grass, both cultivated in Holland, can be transported without the need of preprocessing or

long-haul transportation. As a result they are the most efficient crops in this section.


Figure 5 Resulting logistical efficiency

Efficiencies

0

500

1000

1500

2000

2500

Cas

sava

Gra

ss

Luce

rne

Maize

Oi l pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar can

e

Sunfl o

wer

Switc

hgra

ss

Toba

cco

Whe

at

Willow

tree


]

Energy

Exergy

Based on the Logistical Systems

3.4E3

4.0E3

2.8E3

4.4.3 Analysis

Table 17 Comparative logistical input overview

Crop Logistical System (energy) Logistical System (exergy)

Common Name Input Efficiency Input Efficiency

Cassava - O - O Grass + + + + Lucerne O - O - Maize - - - - Oil Palm - O - O Potato + + + + Rapeseed + O + O Sorghum - - - - Soya Beans O - O O Sugar Beet O O O + Sugar Cane - - - - Sunflower + + + O Switchgrass O O O O Tobacco - - - - Wheat + O + O Willow Tree O - O -

Input: + below 25.0GJ/ha, - above 75.0GJ/ha, O between 25 – 75GJ/ha Efficiency: + above 1500%, - below 500%, O between 500 – 1500%


5 Results and Discussion The top 3 choice crops for each category (farming and logistics) will be discussed separately

along with the total result for the entire group “secondary energy input” in terms of energy to

material production.

Modern farming is highly energy intensive due to the heavy reliance on diesel powered machinery

employed in the tillage, planting, soil treatment and harvesting operations. However, in many

regions of the world, manual labour is still common place especially for the harvesting

operations. The energy requirements “to feed an army” (of harvesters) is much less than the energy

requirements “to fuel a combine” (harvester). This can be seen in the following table listing the top 3

crops with the lowest energy input demand for the farming operations.

Table 18 Top 3 crops on low farming demand

Energy Exergy Farming Efficiency (Output/Input)


1. Oil Palm: 2.19 Oil Palm: 2.23 Oil Palm: 38051 Oil Palm: 41486 2. Cassava: 2.49 Cassava: 2.23 Cassava: 21656 Cassava: 25266 3. Sugar Cane: 2.94 Sugar Cane: 3.02 Sugar Cane: 16616 Sugar Cane: 19364

Between 350 – 750 man-hours are required to harvest one hectare of the top 3 crops in their

respective regions. Even at only ~1 operational hour per hectare for the fully mechanized

operations, the energy intensity is significantly higher. However, it is foreseeable that with an

increased interest and investment in these manually harvested biomass crops the local farmers

may quickly adopt fully mechanized operation practices. This will undoubtedly support the

development of the regions but will negatively influence the energy intensity of the farming

procedures. The following table lists the top 3 crops based on full mechanization.

Table 19 Top 3 crops on low farming demand (fully mechanized)

Energy Exergy Farming Efficiency (Output/Input)


1. Soya Bean: 3.01 Soya Bean: 3.02 Maize: 14144 Maize: 16611 2. Willow Tree: 3.13 Willow Tree: 3.18 Rapeseed: 9629 Rapeseed: 11079 3. Rapeseed: 3.22 Rapeseed: 3.24 Wheat: 7036 Wheat: 8279

Despite being cultivated using fully mechanized operations the maize crop approaches the

efficiencies (85%) achieved by the manually harvested sugar cane fairly closely. This illustrates the

true extent of the cultivation efficiency of the maize crop. The top 3 most efficient crops (in

terms of farming procedures when full mechanization) are all currently employed on a large scale

for bioenergy purposes, suggesting a correlation and not a coincidence.

Yet no matter how energy intense modern farming procedures are, it must be realised that when

brought into the perspective of the yielded crop output energy content, its contribution is in fact


quite low. For all the crops under investigation, the fraction of the potentially yielded output

energy required for farming is 0.26 – 3.53%. It is a mere 0.26 – 0.60% for the top 3 crops.

In retrospect it was determined in Section 4.3.1 that 0.70 – 1.29% material loss occurs over the

storage and transfer operations encountered during the logistical systems. Even when excluding

the material loss the logistical systems are the most energy intensive in the group of secondary

energy input. For many of the chosen crops the requirements for logistics can be several orders

of magnitudes higher than the requirement for farming procedures. As the following table

depicts, the top 3 crops with the lowest logistical input energy cost are in the same (slightly

higher) range than the most intensive farming procedures.

Table 20 Top 3 crops on low logistics demand

Energy Exergy Logistics Efficiency (Output/Input)


1. Grass: 6.13 Grass: 6.15 Grass: 3378 Grass: 4015 2. Potato: 10.3 Potato: 10.4 Potato: 2306 Potato: 2765 3. Sunflower: 12.0 Sunflower: 14.7 Sunflower: 1549 Sugar Beet: 1556

As expected and already mentioned in the previous section, local crops perform best. The shorter

the travel distance the less intense the logistical operations. An other major additional benefit of

local biomass cultivation and collection is the possibility to transport the feedstock without any

sizing or moisture reduction considerations. Local biomass is best! Locally cultivated grass with

the option of partial air drying is by far the most advantageous crop to feed the Port of

Rotterdam. At 3378% logistical efficiency, less than 3% of the collected energy content is

required (and lost) for the logistics. The sunflower, though transported over a seemingly far

distance of 724km, is the 3rd best crop. The reason is twofold. Firstly, the transportation does not

rely heavily on truck/tractor transport and secondly, the harvested seeds require no drying

preparation before transportation. Wheat has also been set to be cultivated and transported using

the same means as the sunflower yet has a logistics efficiency 70% that of the sunflower. The key

difference between the two crops is the pretreatment of the seeds; it is considerably more energy

intensive to grind wheat into flour than sunflower into an oily slurry. This stresses the fact that

each crop in each region is unique and by being handled differently results in regionally crop

specific logistical systems and respective energy demands.

Although it will be covered in the following chapter, it must already be mentioned that as alluring

as local biomass may appear it cannot satisfy the chemical feedstock demands of the Rotterdam

production facilities both continually over the entire year and in total volume flows. Imported

biomass is inherently necessary. Determining the best combination between the domestic and

foreign sources of biomass in respects to energy/exergy efficiency is paramount.

In the previous two chapters the term land use efficiency was employed to indicate the relationship

between the yield and input energy type; effectively compiling the land requirements for material


production. The same procedure can be performed with regards to the secondary energy inputs.

By relating the dry weight yields and total secondary energy input an “energy use efficiency” is created

with the same unit, g/GJ. This indicates the energy requirements for material production.

Figure 6 Secondary energy use efficiency

Energy Use Figures

0.0E+00

2.5E+05

5.0E+05

7.5E+05

1.0E+06

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar can

e

Sunf lo

wer

Switc

hgra

ss

Toba

cco

Whe

at

Willow

tree

g/GJ

Energy

Exergy

Based on Dry Weight Figures and Secondary Energy and Exergy

1.1E6

1.0E6

Three crops clearly stand out as producing vastly more biomass material per energy input than

the others; namely grass, potato and sugar beet making the top 3 crop selection straightforward.


Energy Exergy

Top Crops g/GJ

1. Grass: 1.05⋅106 Grass: 1.04⋅106 2. Potato: 9.27⋅105 Potato: 9.20⋅105 3. Sugar Beet: 8.18⋅105 Sugar Beet: 8.13⋅105

These three particular crops are rated amongst the lowest in farming procedure efficiency being

heavily reliant on intensive machinery, yet still yield the most material per secondary energy input.

Although this cannot be ignored, the farming procedure energy input is overshadowed by the

significantly higher energy input associated with the logistical systems. Thus transportation and

preprocessing are the most influential aspect for the secondary energy input. This presents

benefits for even the lower yielding crops in temperate regions supplying local chemical industry.



6 Total Agricultural Energy Input Combining the primary (chapter 5) and secondary (this chapter, 6) energy input results in the

total energy input required to supply the chemical industry (or any other industry) with the

respective biomass feedstock. This summation will be dubbed as “total agricultural energy input”. By

relating the terms once again to the potential crop output figures (chapter 4) and by additionally

including the material lost during the storage and transfer operations (section 4.3.1) the overall

energy and material propagation efficiencies can be determined. This section will be broken

down into three parts. The first part will give a compilation of key graphs, the second will show

the results and the discussion listing the top 3 and bottom 3 choice crops per category, and the

third part will give an individual assessment and suggestions options for the regionally set crops.

Exergy results are only present in the tabular results, not in graphical form.

6.1 Graphical Overview

Four graphs are presented in this section. The first, figure 7, is the total agricultural energy input

brought into relation to the productive land area, MJ/ha. For better clarity the total absolute

value has been broken down into the individual input categories. As repeatedly stressed, the

figures are better presented in relation to the crop yield output figures. Although based on the

same resulting relationships, the second graph is slightly different than the commonly presented

efficiency graphs. Figure 8 depicts the percentage of the potentially yielded crop energy lost,

broken down for each of the major input categories, to create a biomass feedstock. The

subsequent two graphs (figures 9 & 10) present the energy use efficiency for the total material

production and the individual biocomponents of the crops, present in the terms g/GJ.

Figure 7 Total agricultural energy input

Total Energy Input

0.0E+00

2.0E+04

4.0E+04

6.0E+04

8.0E+04

1.0E+05

1.2E+05

1.4E+05

1.6E+05

1.8E+05

2.0E+05

Cassa

va

Gra

ss

Luce

rne

Maize

Oil p

alm

Potato

Rapes

eed

Sorghum

Soy

a bean

Sugar

beet

Sugar c

ane

Sunflo

wer

Switc

hgra

ss

Toba

cco

Whea

t

Willow

tree

MJ/ha

Storage

Transportation

Sizing/Drying

Farming

Irrigation

Pesticides

Fertilizer


Figure 8 Total yielded energy lost through agricultural input

Total Energy Loss

0

10

20

30

40

50

60

70

Cassav

a

Gra

ss

Lucern

e

Mai

ze

Oil

palm

Potato

Rape

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Sorghum

Soya b

ean

Sug

ar bee

t

Sugar

cane

Sunflo

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Switc

hgra

ss

Toba

cco

Whe

at

Willow

tree

% Lost Energy

Logistic Layou t

Farming

Irrigation

Pesticides

Fertilize r

Figure 9 Agricultural energy use efficiency

Energy Use Figures

0.0E+00

1.0E+05

2.0E+05

3.0E+05

4.0E+05

5.0E+05

Cas

sava

Gra

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Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sor

ghum

Soy

a be

an

Suga

r bee

t

Sug

ar can

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Sunf lo

wer

Switc

hgra

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Toba

cco

Whe

at

Willow

tree

g/GJ

Energy

Exe rgy

Based on Dry W eight Figures and Total Agricult ural Energy and Exergy Input


Figure 10 Agricultural energy use efficiency per crop component

Land Use Figures

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

Cas

sava

Gra

ss

Luce

rne

Maize

Oil pa

lm

Potat

o

Rap

esee

d

Sorgh

um

Soy

a be

an

Suga

r bee

t

Sug

ar can

e

Sunflo

wer

Switc

hgra

ss

Tobac

co

Whe

at

Willow

tree

g/GJ

Simple CHComplex C6Complex C5LigninProteinFatSum CH

3.1E5

Based on Dry Weight Figures and Total Agricultural Energy Input

3.8E52.9E5

2.3E5

3.5E52.8E5

6.2 Results and Discussion

The following table lists the top 3 crops corresponding to the graphs figure 8 & 9.

Table 22 Top 3 crops on low total agricultural energy demand

Energy Exergy Agricultural Loss Efficiency

Top Crops GJ/ha Energy % Exergy %

1. Grass: 28.4 Grass: 30.2 Grass: 14.7 Grass: 13.1 2. Potato: 36.0 Potato: 37.7 Potato: 16.2 Potato: 14.1 3. Sunflower: 45.4 Sunflower: 53.3 Rapeseed: 17.0 Rapeseed: 16.9

For many of the crops the logistic layout is the largest factor in determining the total agricultural

input energy. Following this, as expected and already mentioned in the previous section, the local

crops perform the best. Grass comes out as the clear leader with less than 15% of the yielded

energy gone into supply the feedstock. On the other scale are the bottom 3 crops, listed in the

following table.

Table 23 Bottom 3 crops on low total agricultural energy demand

Energy Exergy Agricultural Loss Efficiency Bottom

Crops GJ/ha Energy % Exergy %

1. Tobacco: 181 Tobacco: 192 Lucerne: 61.7 Lucerne: 55.4 2. Sorghum: 175 Sorghum: 188 Tobacco: 48.9 Tobacco: 43.6 3. Oil Palm: 163 Oil Palm: 157 Willow Tree: 47.0 Willow Tree: 42.8


Lucerne at an energy loss of 61.7% is a poor crop choice for supplying Rotterdam. Although the

loss is less than 100% suggesting a mitigation potential is possible, it is expected that for most

biomass applications more fossil fuel energy is required than is delivered. Lucerne owes its poor

performance to the high reliance on truck transport, the long overall transportation distance and

local irrigation practices while only yielding a moderate amount of biomass. However judged

solely per land area (GJ/ha) does indicates a high trend, but part of the bottom 3. It is mainly the

relatively low energy-to-material yield that places it well below the other crops. The oil palm, for

instance, is 3rd in intensive agricultural energy input based on land area but ends up in the middle

of the group (<20% loss) in terms of agricultural loss efficiency. Thus, to compete with a local

crop an imported crop must have a respectable yield potential.

For supplying the chemical industry with a biobased material feedstock it is important to look

into the different components and their respective fossil energy use for material propagation. The

following table lists the 4 most important aspects relevant to the industry; total biomass, total

carbohydrates, protein and fatty acids.


Total Biomass Total Carbohydrates Proteins Fatty Acids

Energy Exergy Energy Exergy Energy Exergy Energy Exergy Top Crops

g/GJ g/GJ g/GJ g/GJ

1. Grass:

4.96⋅105

4.66⋅105 Potato:

3.8⋅105

3.6⋅105 Grass:

9.6⋅104

9.0⋅104 Oil Palm:

8.1⋅104

8.3⋅104

2. Potato:

4.87⋅105

4.65⋅105 Grass:

3.1⋅105

2.9⋅105 Rapeseed:

8.7⋅104

7.6⋅104 Rapeseed:

5.4⋅104

4.7⋅104

3. Sugar Beet:

4.38⋅105

4.13⋅105 Sugar Beet:

3.5⋅105

3.3⋅105 Potato:

6.5⋅104

6.2⋅104 Sunflower:

5.3⋅104

4.5⋅104

Each category corresponds to a different focus on the biorefinery layout. Grass, potato, sugar

beet, rapeseed and the sunflower all score well over all the categories suggesting that they can

become an integral part of any biorefinery dedicated for the European chemical industry. Despite

the high logistic energy demand due to the vast transportation distance, the oil palm is still the

most energy efficient crop for fatty acids production.

6.3 Individual Regional Crop Explanations and Recommendations

The selected crops are regionally based. They may therefore be preferable in one area but not a

good option in another. Several considerations, explanations and recommendations can be made

regarding each of the crops to their respectively selected regions. Cassava

Cultivated in Nigeria the feedstock must overcome a large transportation input energy cost. The

high yields, especially of simple carbohydrates, overcome this hurdle. It therefore become a

competitive overseas option and is a good option to supply the industry with feedstock during

off-season months. But due to the lack of infrastructure and know-how, intermediary

biorefineries are probably not a feasible option to help reduce the associated transport cost.


Grass

Judging solely from the agricultural input energy it is the most advantageous crop to supply a

feedstock for the set chemical industry. Furthermore, harvested on several separate occasions

over the course of the growing season provides ample feedstock for a good portion of the

operational year. And vast landscapes of grasslands are less intrusive than other crop options. Lucerne

Of all the investigated crops lucerne shows the poorest performance. Firstly, being cultivated in a

non-rainfed area with irrigation supplied from a deep aquifer is the not very efficient. Locating

the crop in a rainfed area would improve the situation, but would still not make it a viable option

as other crops perform better on such arable lands. Nevertheless the largest factor is the

transportation cost. Seeing that the yield is only marginal, overseas transport is not advisable

being situated so far from a seaport. The lucerne can be competitive in the domestic market

should the irrigation issues be resolved. Even local, small-scale production of half products, like

ethanol and DDGS, with subsequent distribution could not overcome the transport issue. Maize

Transportation input requirements aside, the maize crop is one of the most advantageous crops

being highly productive relative to its agricultural energy input. Even with the high transportation

cost it can compete with other imported feedstocks. Since it is only grown in the Northern

Hemisphere, its effectiveness is limited: the harvest and deliverable dates coincide with the other

local crop production. The locally existing primitive biorefineries are a practical option to create

half products, lowering the logistical systems input by at least half. Considering the existing

ethanol market and predicted demand increase, the waste from the ethanol plants (distillers

grains) will most certainly be the feedstock coming from the maize in America for the European

chemical industry. Oil Palm

The total agricultural energy input demand of the oil palm is almost entirely related to the

overseas transportation. Local preprocessing can reduce the demand only marginally and may

even raise the overall energy costs due to the foreseeable lack of process integration and

efficiency in the region in the coming years Potato

Behind grass the locally cultivated potato is the 2nd best feedstock option. The only area of

foreseeable improvement would be the promotion of better crop breeding or rotational schemes

to reduce the disproportional high pesticide usage. Rapeseed

Rapeseed performs rather well overall. The high figure for the agricultural energy input is

associated with the artificial fertilizer requirements. To achieve the high yields significant levels of

nitrogen are needed. A reduction option would be a leguminous cover crop. Sorghum

Cultivated in Kenya, the feedstock must overcome a high transportation input energy

requirements. The high yields, especially of simple carbohydrates, overcome the hurdle.

Therefore it is a competitive overseas option. It can supply the industry with a feedstock during


off-season months. But due to the lack of infrastructure and know-how, intermediary

biorefineries are probably not a feasible option to help reduce the associated transport cost. Soya Bean

Transportation input requirements aside, the soya bean crop is one of the most advantageous

crops being highly productive with its agricultural energy input. Even with the high

transportation cost it can still compete with other imported feedstocks, however being situated in

Illinois limits its effectiveness having a harvest and deliverable dates coinciding with other local

crop production. Yet unlike the starch-based maize crop, local processing into half products will

have less of an effect on the oily-based crop. A reduction in transportation costs will be present

but not at the same magnitude. An further option would be to lower the irrigation dependence. Sugar Beet

Sugar beet performs rather well overall. The agricultural energy input is split between the

associated artificial fertilizer requirements and the logistical system. To achieve the high yields

significant levels of nitrogen are needed. Reduction options would be to use a leguminous cover

crop during the winter months and to locate the cultivation areas closer to the inland waterways. Sugar Cane

Excluding the large transportation costs, the sugar cane has the lowest agricultural input per

yielded biomass. Using the ethanol production facilities and other local production facilities will

greatly reduce the transportation costs. Considering the existing ethanol market and predicted

demand increase, the waste from the ethanol plants (begasse + stover) will most certainly be an

important feedstock coming from the sugar cane in Brazil for the European chemical industry. Sunflower

The biggest reduction potential of the French grown sunflower is to better control the irrigation

systems. Integrating a drip system to keep to the bare minimum water demand should bring

down the energy losses. Switchgrass

Compared to the other American grown crops, switchgrass has the lowest relative logistic system

energy cost which is primarily due to the exclusion of a drying procedure. Yet, its intensive

farming practice and nutrient requirements influence the overall results negatively. Even with

local processing into half products it is unlikely that it can compete to other more efficient local

feedstocks. Tobacco

Tobacco grown in Australia is simply too far away to efficiently supply the European market,

even with its remarkable yields. Cultivation in a closer region with a suitable climate adapted to

year-round production could be an option. Wheat

To obtain the high yields associated with best practice conditions, wheat requires vast amounts of

artificial fertilizer. Compared to the other regional simple carbohydrate-based feedstock options,

it is the least efficient. Nitrogen demand can slightly be lowered using a summertime cover crop.

However, its forte is providing an earlier local feedstock source. Willow Tree

Regardless of the common notion that the willow tree is a fast grower, the actual yields are simply

too low to warrant the sizing and drying procedures for export, let alone for domestic use.


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Chapter 7 Process Energy Input

Required energy and exergy involved in processing of biomass within a biorefinery concept

Ben Brehmer

Dissertation Report


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Title Chapter 7 – Process Energy Input Author(s) Ben Brehmer A&F number - ISBN-number - Date of publication 1. April, 2008 Confidentiality No OPD code - Approved by - Agrotechnology & Food Sciences Group B.V. P.O. Box 17 NL-6700 AA Wageningen Tel: +31 (0)317 480 150 E-mail: [email protected] Internet: www.afsg.wur.nl © Agrotechnology & Food Sciences Group B.V. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch, hetzij mechanisch, door fotokopieën, opnamen of enige andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. De uitgever aanvaardt geen aansprakelijkheid voor eventuele fouten of onvolkomenheden. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher. The publisher does not accept any liability for inaccuracies in this report.


Abstract The conversion of biomass feedstocks into chemical products is performed in a biorefinery. Each

of the biochemical constituents as described in Chapter 4 are subjected to a different processing

route to yield a chemical. All of the potential chemical products investigated exist in the current

petrochemical industry as described in Chapter 1. Seen from the cradle-to-grave each biochemical

processing step within the biorefinery involves internal process energy. The process energy is

separated into thermal energy, electric energy and indirect energy (also exergy). These are related

to external fossil fuel energy input requirements. Each potential bioprocessing routes is assessed

systematically and expressed in GJ/ton product for that particular stage of processing. The best

available technologies, recently developments, currently researched and even hypothetical designs

are included to foresee the production of a chemical product from each biochemical constituent.

In those case where it applies, the current average processing routes are also listed alongside the

lowest energy consuming option. This chapter is sectioned in the same sequence as the proposed

steps of a biorefinery. First, receiving biomass to remove soils and other impurities is covered.

Secondly, carbohydrates which, in respects to their large biomass proportion and various forms,

are broken down into three subsections; simple carbohydrates, complex carbohydrates and

further glucose processing. Fatty acids, proteins and lignin are all assessed following the same

methodology to yield chemical products in regards to the required thermal and electric process

energies and indirect fossil fuel energy. Unreacted and unconverted material is gathered and

combusted to yield internal heat and power. The efficiencies of the energy conversion and

potential products is described. While an overview is presented to the extents of various

biorefinery schemes, this chapter essentially provides the base data needed for further matrix

calculations of the feedstock dependent biorefinery layouts.

Key Words:

Biomass, Biorefinery, Fermentation, Separation, Chemicals Processing, Energy, Exergy



Content

1 Introduction 303


2 Handling Procedure 305

2.1 Locations 305

2.2 Preparation 306

2.2.1 Washing 306

2.2.2 Product Isolation 306

2.2.3 Sizing 306

3 Carbohydrates 307

3.1 Simple Carbohydrates 307

3.1.1 Starch 308

3.1.1.1 Description 308

3.1.1.2 Processing 308

3.1.1.3 Energy Input 309

3.1.2 Sucrose 310




3.1.3 Other sugars 312

3.2 Complex Carbohydrates 312

3.2.1 Cellulose 313



3.2.2 Hemicellulose 320



3.2.3 Other Complex Carbohydrates 320

3.2.4 Energy Input 321

3.3 Glucose Chemistry 328

3.3.1 Ethanol production 328


3.3.1.2 Standard Processing 329

3.3.1.3 Recent Processing Improvements 331


3.4 Overall Ethanol Production Cost 334

3.4.1 1st Generation Bioethanol 334

3.4.2 2nd Generation Bioethanol 335

3.4.3 Combined generation 336


3.4.4 Ethylene Chemistry 336




4 Fatty Acids 339

4.1 Description 339

4.2 Processing 340

4.2.1 Standard Processing 340

4.2.2 Recent Processing Improvements 342

4.3 Energy Input 343

5 Proteins 347

5.1 Description 347

5.2 Processing 348

5.2.1 Animal feed issue 348

5.2.1.1 General Situation 348

5.2.1.2 Fossil Fuel Mitigation 349

5.2.2 Solubilization 350

5.2.2.1 Chemical Extraction 350

5.2.2.2 Protease 351

5.2.3 Isolation and Purification 352

5.2.3.1 Nanofiltration (NF) 353

5.2.3.2 Electrodialysis (ED) 353

5.2.3.3 Chromatography 354

5.2.3.4 Reverse Osmosis (RO) 356

5.2.3.5 Others 356

5.2.4 Potential synthesis routes 358

5.2.4.1 Process Debriefing (Sources) 360

5.2.4.2 General Process Unit Operations 360


5.3.1 Protease Solubilization 363

5.3.2 Separation and Isolation 364

5.3.3 Drying and Product Preparation 365

5.3.4 Reactions 366

5.3.5 Overall 367

6 Lignin 369

6.1 Description 369

6.2 Processing 370

6.2.1 New Product Options 370

6.2.2 Fungal degradation 370


6.2.3 Gasification 371

6.2.4 Fast-pyrolysis 372


7 Ash 377

7.1 Description 377

7.2 Applications 378

7.2.1 Combustion 378

7.2.2 Post-combustion 378

7.2.2.1 Building Material 378

7.2.2.2 Fertilizers 378

7.2.2.3 Ash Upgrading for Fertilizers 379

7.2.2.4 Land Reclamation 380

8 Biorefinery System 381

8.1 Construction of Facilities 381

8.2 Internal Process Energy 381

8.3 Local Production 381

8.4 Results and Discussion 382

References 383



1 Introduction In the previous chapters, the various biomass feedstocks were investigated and assigned a

cumulative imbedded fossil fuel value for their propagation; a total agricultural fossil fuel energy

input. Industrially cultivated biomass provides a carbon-based feedstock which has, for the large

part, a significantly lower fossil fuel cost then the contained calorific value. And despite the low

efficiency currently associated with direct combustion of biomass, heat and power generation

usually does yield a moderate reduction in fossil fuel consumption. Investigation into modern

high-tech solutions are already partially implemented which drastically increases this efficiency of

biomass combustion, yet the practice of burning biomass is as old as man himself; archaic in

principle. There are other industrial sectors of high fossil fuel intensity that can make superior

utilization of the carbon-based biomass feedstock, potentially mitigating vast quantities of fossil

fuel energy. The processing of biomass to yield chemical precursors is accompanied with new

and laboratory scale researched technology; cutting edge in principle. While biomass processing is

not void of additional energy input, the field is developing with energy reduction in mind.

Think of the petrochemical industry and images of densely arranged smoke stacks, soaring oil

crackers, towering distillation and rectification columns appear in the mind. Furthermore, in

recent times images used to promote climate change conveniently use these typical scenes as a

backdrop. Throughout the long history of the traditional petrochemical production industry the

technology has been meticulously improved and fine tuned to the point that any additional

efficiency improvements are minimal. Being based on naphtha entails very high temperatures and

pressures to maximize the conversion rates meaning theoretical minimum process energy levels

will remain considerably high. This is where the biorefinery has the prospect to capitalize.

Think of the biobased chemical industry and ones mouth begins to water with the idea of deep

fried food or fresh bread. Indeed the current, limited, applications of biomass processing are

more related to the food processing industry than the naphtha processing industry. Images of hay

stacks, grain silos, fermentation towers and cooking ovens comes into mind when thinking about

the biomass industry. With the envisioned expansion of the facilities into full-scale biorefineries

producing chemical precursors the scene and thought will undoubtedly change, although the

delicious smell will probably linger for some time to come. Grand imposing thermal separation

units and boilers emitting copious amounts of smoke will cover the factory grounds as they do

today in the traditional petrochemical industry. The major difference will be the scale and

intensity. Biomass process technology will be paralleled with the developments and

advancements made particularly in the biotechnology field.

Steps involved in biomass processing employ a combination between time-tested existing

technologies, recently developed biotechnology and upcoming technologies designed especially

for biomass applications. Each product route will encompass an individual internal process

energy demand, partially offset by the initial processing procedures common for other products


and partially derived by the final product’s unique processing requirements. Combined all the

products and relative process energies contribute to the overall biorefinery process energy input.

The more products desired to be produced, the more complex the biorefinery becomes with an

increased leaning towards higher energy intensity. Providing a numerous array of products to

satisfy the chemical industry feedstock needs is mimicking the conceptual ideals of the existing

petrochemical layout. Whereas producing chemical precursors fit for direct application in the

existing chemical sector is about the only similarity between the two types of refineries.

Water is the main component that sets the fossil fuel-based and bio-based feedstocks apart.

Upon harvest biomass is wet with a crop dependent dry weight and regardless of the moisture

reduction precaution for transportation typically the first step in a biorefinery is to add water.

Most processes in a biorefinery will indisputably be dominated by water and the properties

thereof. There will be natural thermodynamic limitations imposed on operation temperatures and

pressures of the processes, even the envisioned thermal units will adhere to the boundaries. Plus

water is a perfect medium to employ novel biotechnological processes. In general the process

conditions will be milder than those of the traditional petrochemical production routes. The

overall process energy of a biorefinery system should be much smaller.

The processing of chemicals from biomass should be less energy intensive than the processing

derived from naphtha. Should be, however the advantage of water by inducing milder conditions

is also the cause of major disadvantages in separation techniques. In addition to separation

technology, low conversion rates and up-scaling experimental systems will be the limiting factors

in the success of the biorefinery layout. Each bioprocess route will be assessed for the best

practice option to minimize process energy, thus maximizing fossil fuel savings potential.

A systematic approach will be taken to describe the possible production routes as grouped by the

biomass chemical compositions. In Chapter 4, the crops were classified to agricultural and

biomass categories. The exact biorefinery layout and processes involved are dependent on the

biomass classification of the crop to be processed. By the end of the chapter the resulting process

energy for the optimal biorefinery system for each of the selected crops will be determined.

1.1 Chapter Purpose

In the following chapter all the process energy inputs pertaining to the proposed biorefinery

options of biomass will be calculated and expressed based on the biochemical composition

groups contained in the biomass. The values mentioned herein are based on a straightforward

energy/mass balance in excel using the thermodynamic conversions and axioms to obtain the

exergy values. This chapter is the final of three energy inputs categories required for the creation

of chemicals from biomass. The combination of total agricultural energy input (primary and

secondary energy inputs) with the internal process energy will be able determine the total

embedded fossil fuel energy in the proposed biorefinery systems.


2 Handling Procedure Upon receiving biomass at the biorefinery’s “factory gate” the shift from the realms of agriculture

to the realms of engineering is complete; handmade straw hats exchanged for a plastic moulded

hardhats. Biomass material will be treated as any other industrial feedstock and assessed for the

best possible production route to maximize product efficiency. In Chapter 6, Section 4.3, the

procedures to reduce size and moisture content for long-haul biomass transport were covered

with the main motivation of increasing net bulk density. It was based under the pretence that all

process steps concerning the biorefinery would be centralized at the petrochemical cluster areas.

This placed a particularly high logistics energy cost on particular crops located in distant regions.

Some aspects of the biorefinery are technically basic and can be performed closer to the

agricultural production areas, while other processes are not basic and do need the collective

know-how of the cluster. To reduce the logistics portion several aspects of the biorefinery will be

performed close to the feedstock cultivation. Plus stringent criteria to produce final-grade

products are not imperative, so long as they are properly coupled with the clustered biorefineries.

After the detailed explanation of individual biochemical production routes, Section 4.1.1 covers

the aspect of half-products, or semi-processed material designed to optimize logistics and

biorefinery energy efficiency. Yet regardless of the distance, most of the crops will encounter at

least partial onsite processing beyond the sizing and moisture reduction steps. In some

circumstances the sizing and moisture reduction will even be made redundant. Handling and

initial treatment of the biomass material will thus be conducted onsite unless otherwise stipulated.

Handling procedures is understood as the necessary preparation for downstream internal

processing with purification aspects dominating.

2.1 Locations

The most appropriate mood of transportation for each regionally dependent biomass feedstock

has a major influence on the biorefinery upon delivery. Despite being centrally located within the

confides of the petrochemical cluster the feedstocks arrive from all possible corners of the globe

at independent time intervals and quantities. One of the primary success factors for a biorefinery

is to be able to continually operate year-round decoupled from seasonal influences. Locally

cultivated biomass provides the biorefinery with a moderate quantity of feedstock (per truck,

train, barge, etc.) periodically throughout the harvesting season. Cross-continental cultivated

biomass feedstock, although possibly seasonally dependent as well, arrives in enormous quantities

(sea vessel) sporadically during the local off-season period. In addition to continual operation, a

successful biorefinery must also be able to process an acceptable range of similar feedstocks

within the limitations of biomass classifications. This creates a unique cooperation and

integration opportunity for biorefineries based in the petrochemical cluster. Receiving and initial

feedstock handling procedures in particular can be shared or coupled between the different

biorefinery types. The goal being a relatively constant production rate without over-sizing the

equipment. Preprocessing and initial handling close to the agricultural production sites is void

from this benefit, but has the benefit of dedication to one particular feedstock type. This permits


the onsite facilities to operate at optimal levels during periods of harvest. In general, the handling

preparations are identical regardless of location and phase of the refining.

2.2 Preparation

The concept of handling the throughput of biomass feedstock is to prepare it for an efficient

utilization within the biorefinery system. Impurities and unfavourable structures are altered upon

by need. In fact most feedstocks can be directly processed without any preparation requirements,

but for those feedstocks which do require preparation for processing, they are accompanied with

a material loss and minor energy consumption.

2.2.1 Washing

Several of the crop components, especially the agriculturally relevant portions, are impure and

not suitable for direct processing. As a simple precaution the feedstocks are water washed and in

cases of more complex facilities process water is used. Stones, soil, dirt and other minor

impurities are flushed out with minute energy requirements and negligible wastewater treatment.

Even in the extreme cases where more than 3 times water over the biomass feedstock volume the

energy consumption remains minimal: 30MJ heat and 110MJ electricity per ton wet feedstock.

2.2.2 Product Isolation

As will be shortly mentioned in the following section, the effectiveness of processing simple

carbohydrates is dependant on a high feedstock purity. Removal of the outer shell (through

peeling, de-husking, etc.) is performed to isolate to rich core. Existing biomass facilities make

little use of these residues, while recent develops (Section 3.2.1.2) can which greatly lowers the

overall effective biomass loss.

2.2.3 Sizing

Already covered in the previous chapter, the next sequential processing step after washing and

product isolation is size reduction. This justifies the reasoning of handling/preparation occurring

more often onsite then at the biorefinery clusters. Listed in the following table are the feedstocks

which require separate handling before size and (should any be later envisioned) moisture

reduction steps with the resulting loss in biomass material.

Table 1 Initial handling procedures

Crop Component Onsite Processing Initial Handling Steps Biomass loss

Common Name Y/N General classification %

Cassava Tuber Y Soil removal, washing, peeling* 2.0 Maize Seeds Y Silk removal, washing, kernel removal 0.3 Oil palm Fruit Y Fruit bunch separation* 1.0 Potato Tuber N Soil removal, washing, peeling* 2.0 Soya bean Seeds Y Residuals removal, washing, flaking 1.6 Sugar beet Beet N Soil removal, washing, pinch tops* 2.0 Sugar cane Cane Y Dirt and ash removal, washing† 0.7 Sunflower Seeds Y Husk separation*, washing 0.3 Wheat Seeds Y Kernel isolation*, washing 0.3

†Sugar Cane, is special case as currently washed but with best practice system, no field burning thus no need to be washed; directly feed


3 Carbohydrates Carbohydrates are the most abundant biomolecules that form

the basis of life. Defined as sugars (or saccharides) and their

derivates, the “hydrates of carbon” are any organic compound

based on aldehydes or ketones with hydroxyl functional groups.

In plant matter, the carbohydrates are typically present in

polymers forming polysaccharides. They have a general formula

of Cn(H2O)n-1 where n is usually a large number between 200 and

2500. Biologically they fulfil numerous functions such as for energy storage, energy

transportation and form structural components. The simplest carbohydrates are the

monosaccharides with glucose being the most common. Nearly all of the proposed applications

for biomass-to-chemicals use glucose as a starting building block material1. Although pure

glucose is not present in vast or accessible quantities in biomass, several particular types of

carbohydrates are present in large quantities which, given the right processing, can be broken

down to glucose or other workable materials (such as xylose). The degree of functionality,

complexity and abundance of these carbohydrates are quite different and vary between crop

species. In this section, two groups (dubbed simple and complex) with several subgroups will be

investigated for saccharification processing (breakdown to glucose). The technologies involved in

processing these carbohydrates, apart from being partially crop dependent, are many and very

type specific. The conditions needed to calculate the direct energy and exergy will be listed along

with modern measures to lower the processing inputs. Relation to the fossil fuel input

(cumulative process energy) will not be conducted in this section as the energy generation of each

biorefinery system is unique and specifies the type of fossil fuel energy generation, if any. Finally

the goal will describe the existing and potential glucose chemistry based on the different

carbohydrate biomass feedstocks in reference to major portion of the biorefining system.

3.1 Simple Carbohydrates

The terminology “simple”, used to describe these particular

carbohydrates was chosen to correlate with the technology

involved. The oldest known and most cherished (by some)

processing of biomass is the fermentation to alcohol. Particular

biomass contains ample quantities of these carbohydrates (starch,

sucrose, fructose, etc.) that can be easily saccharified for

subsequent ethanol fermentation. The technology is easy,

straightforward and has been practiced for millennia. As simple

as the processing may be the energy intensity is still remarkably

high allowing for improvements. Heavy consumption of the classical product has possibly lead

process innovation to also remain simple; adhering to the traditional methods. Shifting focus on

biomass utilization for sustainable chemical production places energy efficiency and conversion

rates as paramount. There are many carbohydrates that can be classified as simple, but in this

study the focus will remain on starch and sucrose. Biomass crops containing high levels of these

Medieval Monastery Brewery using starch contained in cereals to ferment beer


products are subjected to standard technologies and processing steps, however the specific

conditions vary slightly for each feedstock resulting in minor energy consumption deviations.

3.1.1 Starch

3.1.1.1 Description

Starch is the second most abundant biomolecule in the biosphere. It is used

by plants to store excess energy and is digested upon an energy need. It is

found in high concentrations in the reproductive organs (such as seeds) so

that sufficient energy is available during germination. It consists of two

different α-D-glucose chains configurations; linear chained amylase and highly branched amylopectin. The ratio between the two forms is plant

source dependent while the typical ratio is 20-amylase:80-amylopectin. The technology use to

break starch down into glucose is similar but also crop dependent. From the select crops two

distinct group classifications can be made: cereal and tuberous. Even though wheat and corn are

both cereal grains corn behaves independently from other grains and must be independently

investigated. Potato and cassava are both tuberous crops and the little difference between them

hardly affects the resulting process energy.

3.1.1.2 Processing

Preparation of starch-rich biomass feedstocks to glucose is called the “mashing process”. Physical

mashing is however only one of three distinct steps; (1) mashing, (2) enzymatic liquefaction and

(3) enzymatic saccharification. Physical mashing is designed to break the cellular walls of the

feedstock to release the inner material largely including starch. Prior to mashing the previously

mentioned size reduction procedures are performed optionally or in some cases cover the

mashing step. Dispersion machines work with a rotor and stator sheering the feedstock material

into a fine pulp with near complete cell wall destruction. It is the most effective system and does

require the handling and size reduction procedures to operate efficiently. Earlier systems rely on

either high pressure (above 6bar) or high temperature (above 100°C) or a combination of both. The most common of which is the Henze cooker, but is gradually being phased out due its high

energy consumption2. The dispersion mashing system with partial stillage (see Section 3.3.1)

recycling is the most energy efficient. Coming from the down-stream distillation column the

85°C hot stillage promotes a near optimal mashing step with little additional input energy. Usually following, but also sometimes combined, with the mashing step liquefying enzymes are

added to the reactor under mild temperatures. There exists a wide multitude of enzymes from an

assortment of host bacteria and fungi. Virtually all are α-amylases and are even present to a degree naturally in the feedstock. Classically malts and autoamylolysis were used for both the

liquefaction and saccharification steps but due to the technical availability of industrially prepared

enzymes have been replaced. TBA, thermostable bacterial α-amylase from bacillus licheniformis, is the most common liquefying enzyme, although today it is common to add an enzyme cocktail to

ensure complete conversion. Directly following liquefaction the saccharification enzymes are


added under slightly elevated temperatures. The exact temperature is feedstock related and

directly effects the heat demand of the process. Tuberous crops in particular require higher

cooking temperatures in the order of 90°C plus. Glucoamylase hydrolyzes the main glycosidic linkage (α-1,4;α-1,6;α1,3) between the starch molecules releasing glucose. Like with the other enzymes a wide assortments exists where Glucoamylase from the fungi aspergillus niger (GAA) is

the most common. The resulting wet product stream is called sugar liquor.

3.1.1.3 Energy Input

Glucose is an intermediary product which when originating from starch is almost exclusively

used in consequent ethanol fermentation. Much information is known regarding ethanol

processing as a whole, whereas isolating the mashing process requires more detailed information.

The overall conversion is the first factor in defining starch processing. Listed in table 2 are all the

relevant figures for each investigated crop type. The first row indicates the slight deviation

between conversion rates, and while all being in the high nineties the tuber crops fair best. Next

the saccharification temperatures play an important role in determining the thermal energy costs.

Steam is used to supply the thermal energy and as discussed in Chapter 2 the difference between

energy content and exergy content is large. The results shown in the table per ton of starch dry

weight elude to this. The mashing process is in particular dominated by enzymatic treatment and

the embedded fossil fuel energy cost of enzyme production is actually quite high. An enzyme

manufacture performed a detailed study for the major enzyme categories3. Liquid α-amylase originating from bacteria costs 19.5MJ/kg in ingredients and 3.0MJ/kg in direct energy. Liquid

glucoamylase from fungi costs 69.9MJ/kg in ingredients and 35.9MJ/kg in process energy. The

dosing rates are essentially the same for all crop types; between 2.0 – 4.0kg (mean 2.5) per ton

starch of amylase and 0.2 – 0.6kg (mean 0.5) for glucoamylase. Although further optimization in

reducing the enzyme loading rate is foreseeable, as shown in the resulting table the proportional

indirect energy cost is already quite low.

Table 2 Starch Processing Energy/Exergy Input

Crop Cereal Cereal (corn) Tuberous

Conditions Conversion Rate (%) 96.2 97.7 99.2

Saccharification Temperature (°C) 65 – 75 80 – 85 92 – 94

Direct Energy Electric (GJ/ton starch) 0.256 0.260 0.198 Thermal (GJ/ton starch) 0.52 0.99 2.51 Direct Exergy Electric (GJ/ton starch) 0.256 0.260 0.198 Thermal (GJ/ton starch) 0.02 0.10 0.43 Indirect Energy/Exergy Costs Enzymatic Energy/Exergy* (GJ/ton starch) 0.109 0.109 0.109

*energy=exergy as enzymatic process energy is almost entirely electric based

As a comparison dried granulated corn starch is listed at 34.6GJ/ton in Boustead database4. This

clearly shows the susceptibility of existing biomass and bioprocessing data.


3.1.2 Sucrose

3.1.2.1 Description

Sucrose, sometimes known as saccharose or best as table sugar, is a

disaccharide of glucose and fructose. Held together by the glycoside bond

the resulting molecular formula is C12H22O11. It can only be formed by plant

life and is regarded as the most important sugar in plants; acting as an

energy transport through the phloem sap. Generally produced seasonally, it

is present in all plant life but at high quantities is a limited to a select few

crops. As with the starch-rich crops there are two distinct biomass feedstock types which contain

high enough quantities of sucrose to be consider sugar-rich crops; namely stems-based (e.g. sugar

cane, sorghum, maple tree) and bulb-based (e.g. sugar beet, onions). Being a disaccharide it has a

much lower order of complexity compared to starch. This allows fermenting bacteria to use

sucrose directly, making the preparation even simpler and less energy intensive than the mashing

process of starch. Essentially the sucrose must be extracted or pressed out of the biomass

feedstock and in this sense the form of biomass determines the applicable technology.

3.1.2.2 Processing

The shape of the two sugar-rich biomass categories dictate the processing steps involved in

extracting the sucrose. Shedding, milling and pressing are involved for the stem-based crops

where slicing, diffusing and pressing are involved for bulb-based crops. Both of these sucrose

processing routes are historically coupled to white table sugar production. Traditionally after the

final pressing procedure the sucrose containing stream is subjected to a clarifier and

concentration step to remove trace chemicals and produce a first molasses. For biorefinery

applications, such as when used directly as a fermentation feedstock, the measures for stream

purification and composition need not be so stringent; sugar liquor containing 10 - 15°Bx (Brix: sucrose content) is sufficient making the clarification and concentration steps redundant, which

also positively reduces the energy intensity. As sugar-rich crops are directly coupled with the

sugar industry the equipment and technology used in the initial sugar liquor preparation steps

operate at near optimal efficiency. Due to the type dependent processing differences description

will be covered separately for the two sugar-rich crop types.

Stem-based

After the initial handling procedures (cleaning) the stems are subjected to a crude shedder to

break the feedstock down into smaller, easier to handle sizes. Unlike the starch mashing process

the pieces are large and do not require destruction of the plant cells. This significantly reduces the

energy intensity and also means that the size and moisture reduction procedures are not needed.

The shredded stem material in then introduced into the milling train unit which extracts the sugar

juice through a series of rollers. Usually a half-dozen industrial-sized rollers are used to crush the

stems and simultaneously squeeze the sugar containing liquids out. Counter-current water is

sprayed on the milled stems to wash out the residual traces of sucrose. The resulting sugar liquor

stream has sucrose content of 14 - 16°Bx. A total of 94.9% from the biomass contained sucrose


is extracted with 0.6% losses associated to reducing sugars, 3.8% to the extraction degree and

0.8% in the juice treatment (water spraying) step.

Bulb-based

After the initial handing procedures (including top removal) the bulbs are subjected to a drum

slicer to cut the feedstock into thin, long chips called cossettes. This procedure increases the

surface area and exposes the interior of the bulb making sucrose extraction possible; cell wall

destruction and size and moisture reduction procedures are not needed. The cossettes are then

placed in large agitation tanks with a counter-current flow of hot water extracting the sucrose.

The hot water is used as a diffusion medium to produce a sugar liquor stream of 10 - 15°Bx. Temperature above 80°C additionally extract pectinic material which negatively effect downstream processing while temperatures below 65°C cause microorganism contamination. At the optimal 70°C diffusion temperatures5, the associated sucrose losses are only 4.2%. Following the diffuser step the residual wet solids are placed in a screw presser to extract an extra 1-2%

additional diffusion juices to be added to the sugar liquor stream. In total 95.1% of the sucrose

contained in the biomass feedstock has been extracted.


Sucrose is almost exclusively used for table sugar production with ethanol fermentation gradually

emerging. Much information is known regarding the process energies for both products and

from the various biomass feedstocks types. Without the clarification and concentration steps the

process energy requirements are heavily reduced compared to table sugar production. Sugar cane

processing will be taken as representative for the stem-based crop types6. And for bulb-based

crop types the sugar beet processing is representative5, 7. In the older (and consequently many of

the existing) sugar cane processing plants the use of steam driven machinery is common due to

the high quantities of bagasse (Section 3.6). A modern biorefinery would use electric driven

motors, which relates to the fact that stem-based sucrose has no thermal energy component. Beet

processing on the other hand has several different thermal components; warm water, hot water

and steam. These various thermal sources lead to a considerable difference in direct energy and

exergy consumption as seen in table 3. Energetically the stem-based feedstocks require the least

amount but seen exegetically it is the bulb-based crops that require the least. By comparing table

2 and table 3, in any case sucrose is less energy intensive than starch processing.

Table 3 Starch Processing Energy/Exergy Input

Crop Stem Bulb

Conditions Conversion Rate (%) 94.9 95.1 Direct Energy Electric (GJ/ton sucrose) 0.452 0.069 Thermal (GJ/ton sucrose) 0.0 0.893 Direct Exergy Electric (GJ/ton sucrose) 0.452 0.069 Thermal (GJ/ton sucrose) 0.0 0.149 Indirect Energy/Exergy Costs* 0 0

*there are no external uses of chemicals or other materials aside from water


3.1.3 Other sugars

Fructose is another important and common saccharide in plant matter which is present in

relatively high concentrations in the fruit of several crop species. But, due to the low material

yields, high energy intensity and lucrative food consumption market no fruit producing crops

were included in the selection of relevant biomass crops (Chapter 4). Extraction of fructose

would, however, be suitable for direct fermentation. Fermenting microorganisms can directly use

fructose, much like sucrose, meaning little processing would be needed. It is foreseeable that fruit

processing residues or stall waste could be mixed with other simple carbohydrate feedstocks to

increase the fermentable sugar yield. Both the starch and sucrose rich biomass crops contain it

and other sugars in lower quantities. In fact, practically all crops have traces of various

monosaccharides include dextrose, galactose, xylose, ribose and the already mentioned fructose.

They are all intermediaries in the biochemistry of disaccharide and polysaccharide production. In

a biorefinery these trace, or free, sugars will contribute to the downstream fermentation feedstock.

In case of crops with a low quantity of simple carbohydrates, they will contribute to the glucose

creation following the complex carbohydrate technologies.

3.2 Complex Carbohydrates

The terminology “complex”, used to describe these particular carbohydrates was chosen to

correlate with the technology involved. In plant matter these carbohydrates (cellulose,

hemicellulose, pectin, etc.) form the structural integrity and are designed to withstand

environmental stresses. Initial hydrolysis, saccharification and subsequent breakdown into

glucose or other workable monosaccharides is not simple. The resistant structural nature of the

carbohydrates makes it difficult to process necessitating complicated machinery and procedures.

Mark Twain wrote “the secret of getting ahead is getting

started. The secret of getting started is breaking your complex

overwhelming tasks into small manageable tasks, and then

starting on the first one”. This idea can be extrapolated into

the processing of complex carbohydrates. Breaking the

complex structures into small manageable pieces is

done through a process called pretreatment. The adjacent

illustration depicts the pretreatment principle; to

separate the cellulose from the hemicellulose

entanglement and lignin shielding, the lignocellulosic material must be subjected to a harsh

pretreatment. In the industry the complex carbohydrates feedstocks are called lignocellulosic

material while the pretreatment technology is frequently referred to as cellulose technology. In

plant matter cellulose, hemicellulose and lignin are inheritably coupled with one another meaning

they will share many processing steps and as a result the processing energy costs. Lignin,

although a part of the initial lignocellulosic material, is after pretreatment separated from the

saccharide processing route because of its aromatic ring structure; it will be handled separately

(Section 3.6). Cellulose and hemicellulose are processed in parallel with only minor differences

separating their process specifications. All biomass material contains lignocellulosic material while


the ratio between the individual complex carbohydrates is unique, which will dictate to a small

degree the overall processing energy demand. The pretreatment and saccharification technologies

are not yet fully proven with many companies and research institutes racing to develop the new

commercial standard. Several of the most promising, near large-scale implementation and most

energy efficient processes will be covered. Pretreatment chemicals, organisms, operation

temperature and pressure, but primarily conversion rates control the resulting energy demand.

3.2.1 Cellulose

3.2.1.1 Description

Cellulose is the most abundant biomolecule in the biosphere. On a

global scale scientists estimate that combined over one trillion (1012)

tonnes of cellulose is synthesised by all plant life annually. It is used by

plants as a structural component for the cellular walls. As a

polysaccharide it consists of thousands of linear chained β-D-glucose units with the general formula (C6H10O5)n. The name derives from

combining cellular wall and glucose. Because it forms the cellular wall in all plant life, it is

present in all biomass feedstocks. It is however, highly concentrated in woody biomass and in the

stem/stalks portions of non-woody biomass. Fibre and pulp residues from the simple

carbohydrates also provides a rich stream of cellulose material. In fact, all the selected biomass

feedstocks will incorporate cellulose technology at some stage in the biorefinery.

3.2.1.2 Processing

Feedstock Considerations

Harsh pretreatment processing conditions are required to cleave and solubilize the lignin and

hemicellulose matrix isolating cellulose for subsequent saccharification. The severity levels of the

treatments are controlled by elevated temperatures, increased pressures, large deviations in pH

and longer residence times. Under particularly severe conditions a near complete cleavage of the

hemicellulose and lignin appears but simultaneously promotes further degradation of the sugars

into undesired products. In the field of pretreatment technologies these sugar degradation

products are referred to as inhibitors because once formed they lower the downstream enzymatic

saccharification and microbial fermentation processes. The most common inhibitor produced is

caused by xylose (hemicellulose) degradation, 5-hydroxymethyl furfural (HMF). Partial

breakdown of lignin forms phenolic degradation products such as 4-hydroxybenzoic acid,

vanillin, syringaldehyde, etc. And to a smaller degree cellulose degrades for furfurals. There are

process integration and control technologies (discussed in Section 3.3.1) foreseeable to reduce the

influence of the degradation products upon formation, but the most logical step would be to

select the best pretreatment technology and conditions for the particular feedstock to avoid their

formation. Here the ratio of lignin, hemicellulose and cellulose play a decisive role in assigning

the logical pretreatment technology. Furthermore, the actual conversion rates (fermentable sugar

formation) is also a function of the feedstock composition, pretreatment technology, and


severity. All of the selected biomass feedstocks will undergo, at some stage within their proposed

biorefinery system, the cellulose pretreatment processing step to liberate sugars found in the

complex carbohydrates. And aside from the simple carbohydrate rich and oil containing

feedstocks this stage marks the beginning of the biorefinery. Thus for investigating the

performance of the pretreatment technologies the feedstocks will be grouped into three distinct

categories:

1. Agricultural Waste Characteristic: high proportions of cellulose (30 – 40%) and hemicellulose (20 – 30%) with a slight lean towards cellulose and moderately low lignin content (<15%) Examples: stems, stover, leaves

2. Processing Residues Characteristic: moderate proportions of cellulose (25 – 35%) and hemicellulose (15 – 25%), low lignin content (<5%) and noticeable protein content (20 – 40%) Examples: distillers grains, bagasse, press cake

3. Recalcitrant Material Characteristic: high proportions of cellulose (30 – 50%), moderate levels of hemicellulose (15 – 25%) and a high lignin content (<15%) Examples: woods, grasses

Oil press cakes (Section 3.4.1.2) have a considerably high lignin content above 15% but because

the pressing and extraction procedures accommodates for milder and efficient pretreatment they

will be classified as processing residues instead of recalcitrant material. High lignin content limits

the effectiveness of the pretreatment process as lignin affectively shields cellulose. Typically the

yields are lower for these feedstocks yet is entirely technology and condition dependent.

Pretreatment Types and Descriptions

There exist a wide multitude of pretreatment technologies which have been suggested and

partially developed over the course of the last decades. The Oil Crisis of 1973 sparked the initial

interest in using lignocellulosic material. Five year ago, when a renewed interest after the ensuing

crude oil price hike following the 9/11 attacks emerged, this authors Master Thesis investigated

the then recent pretreatment technologies for lignocellulosic material8. Still today, 35 years after

the initial interest none of those technologies have been industrially constructed or are even

commercially ready. There still exist a wide selection of researched and proposed technologies

ranging from physical, chemical, physiochemical, biological to a combination. Some can already

be ruled out while others illustrate a great potential. But perhaps it is wiser to be realistic about

the commercialisation timeframe than maintaining optimism; at least a decade is still needed.

Physical pretreatment technology is the first that can be disregarded for use in a biorefinery;

grinding or milling the feedstock to low enough particle sizes to reach a decent digestibility

requires inordinately high energy costs. Conversely many other technologies have shown sugar

yields above 90% with relatively low energy requirements. Generally for those below 90% there

exists little interest within the biorefinery layout as its basic goal is to maximize product yields;

plus lower yields will directly effect the resulting product process energy needs. Despite the


previous mention of pretreatment technologies types there are three classifications which the

covered options fall under: acidic, alkaline and near neutral. Within each of the classifications are

several leading and state-of-the-art methods which will be described and assessed. As R&D

continues additional efficiency and conversion rates can be expected while herein a synopsis of

the general procedures, working conditions and currently attainable yields will be handled in

regard to the feedstock categories.

Near Neutral

Near neutral is in reference to the pH of the active ingredient, being held close to pH7. To reach

the severities required to pretreat the material high temperatures, high pressures and long

residence times are used. There are two major successful near neutral pretreatment technologies

involving water; liquid hot water and steam. Water will partly solubilize the hemicellulose

releasing acids (like acetic acid and formic acid) which further promotes conversion to monomer

sugars. The conversion rates are however, generally lower than other pretreatment options

necessitating additional hemicellulases in the subsequent enzymatic hydrolysis step.

Liquid Hot Water (LHW)

Technically called hydrothermolysis, but more commonly referred to as liquid hot water (LHW)

treatment this technology is very straight forward involving high temperature water and no

chemicals. Tested water temperatures range from 160 to 230°C with high pressures in the order of above 30bars necessary to ensure no steam formation. In a plug-flow reactor the biomass

feedstock is subjected to the pressurized hot water stream for a short period of time, typically 2

to 60mins. Tested solids loading are between 10 – 15% meaning there will be a high water

content in the resulting sugar solution which will cause an elevated energy demand in

downstream processing. Within the range of operation temperatures little formation of

degradation products occur as there is no complete hydrolysis to monosaccharides, most stay in

their oligomer form. Temperatures well above 200°C, however, promote a more complete hydrolysis but cause increased xylose degradation at an expensive associated energy cost. For

certain feedstocks it is possible to achieve a total solubilization of hemicellulose and a partial

hydrolysis of lignin to fully expose the cellulose. The pretreatment works best on agricultural

waste feedstocks, like stover9, below 200°C. Processing wastes have not yet been tested using this technology; so far olive tree pruning residues can give an indication as it contains all the

compositional and partial preprocessing aspects10. Its optimal conditions are indeed at lower

temperatures but the maximum achievable conversion rates are noticeable reduced. Alfalfa can

represent the difficult to process feedstocks as is reflected by the increasingly high temperatures

to achieve moderate conversion rates11. In all investigations it is suggested to include a small

concentration of acid (sulphuric) to increase the sugars yields. An extra 10% is obtainable but

degradation production also increase and in any case adding acid mimics the dilute acid

pretreatment technology (later mentioned). It is common to compare results from LHW to other

technology to validate the research.


Steam

Steam pretreatment is the oldest and still one of the most widely accepted, investigated and to a

limited extent employed technology for processing lignocellulosic feedstocks. It is frequently

associated with sugarcane processing to additionally utilize the bagasse by-product due to an

abundance of available steam. In a pressure reactor high-pressure saturated steam at 6 – 34bar

and 160 - 240°C is introduced to the feedstock material with a high solids loading of up to 80%. The steam largely impregnates and swells the material during a short residence time of 5 – 10

minutes. Upon a quick release of pressure into a flash tank an explosive action is created. It was

previously believed that solely the pressure release mechanism rendered the material more

suitable for hydrolysis. It is now known (as with the LHW) that the water additionally hydrolysed

a part of the hemicellulose into acids. The optimal conditions to yield high cellulose conversion

rates often deviates from those for hemicellulose; a compromise to yield the highest total

converted sugars must be taken. As expected steam pretreatment works best for processing

residues (such as bagasse) although cannot reach values above 90% total yield12. Slightly

unexpected is that higher yields are obtainable from the recalcitrant materials over agricultural

wastes13, 14. High yields, above 90% can be obtained from agricultural wastes but is only possible

under very severe conditions 13. It is hypothesised that the elevated cellulose concentration of the

woody materials positively respond to the swelling despite having a lower hemicellulose content.

Recently studies have began experimenting with the addition of a catalysts before the steam

explosion step to achieve higher overall conversion rates at milder conditions.

Steam with Catalyst

There are two types of catalysts currently tested in combination with steam pretreatment, sulphur

dioxide (SO2) and sulphuric acid (H2SO4). In both cases the chemicals are added to the system as

a diluted water soaking step. Low concentrations of between 0.5 – 2.0% are added per feedstock

weight which cannot be recovered and are best neutralized. They act similarly to the dilute acid

process but by being coupled to the steam explosion step greatly reduces the water consumption.

After soaking for several hours the standard steam pretreatment operation is performed. The

catalysts allows for higher conversion rates at lower temperatures and faster residence times, i.e.

milder conditions. As a positive consequence the production of inhibitors are reduced to

practically zero. Like before, the best performances are from the processing residues followed by

woody biomass and trailed by the agricultural wastes14, 15. Minor performance differences is

noticeable between SO2 and H2SO4, but sulphur dioxide being cheaper, energetically less intense

to produce, and a more workable chemical with no neutralizations precautions is preferred.

Acidic

Acidic pretreatment of lignocellulosic material are very affective at destroying the carbohydrate

matrix shielding the cellulose. At low pH-values and high concentrations the process is fast and

efficient with low energy inputs. Acidity greatly influences the conditional severity promoting a

quick release of sugars including degradation products. The oldest acidic pretreatment technology

of using concentrated sulphuric acid has been prone by hurdles preventing wide spread


implementation. Recovery of the high sugar yields, reduction of degradations products, increased

corrosion protection and recycling of the acid catalysts have caused problems. Few institutes

have remained investigating the option of using concentrated acid and even interest in Arkenol’s

process is a mere footnote. Reducing the concentration while increasing the other process

parameters has proven quite affective, although the presence of degradation products still

remains an issue. Recent work has began in studying the affects of organic acids to reduce the

inhibitor production levels, but come at a product yield reduction cost.

Dilute Acid

Of all the pretreatment technologies dilute sulphuric acid (H2SO4) technology is by far the closet

to actual commercialisation. Several pilot-scale facilities have been built around the world as

demonstration plants for corn stover and fast-growing tree feedstocks. Biomass feedstock is fed

into a screw conveyor and exposed to low-pressure steam (3 – 5bar) at a temperature of 150 -

160°C. After the short heating and physical treatment the feedstock is fed into a large reactor to soak in a dilute acid solution for 5 – 60 minutes. High-pressure steam (12 – 14bars) is used to

bring the reactor to temperatures between 140 - 200°C. Low solids loadings of 5% are used. Studies into increase solid loadings above 10% have proven to drastically reduce the sugars

yields16, 17. Inhibitors including the acid itself must be removed before the enzymatic hydrolysis

step. A slight excess of lime is added to the mixture to precipitate the inhibitors and

simultaneously acts as a neutralization step creating gypsum which is later removed by centrifuge.

Most studies focus on corn stover as a material feedstock because NREL has publically provided

detailed process information and simulations18, 19. These promising results at low economic and

energetic demand have since expanded to other feedstocks20. Best results are found at 160°C, 10 minute residence time, and with an acid concentration of 0.5vol%. Oddly the recalcitrant materials

perform better than the other feedstock categories reaching nearly 95% sugar yields. This has

sparked the forestry industry to investigate the ethanol option with very promising preliminary

results, sometimes approaching theoretical values. Stover does have a similar performance and

achieves higher sugar yields than the processing residues. Other studies have attempted to

decrease the energy consumption by lowering temperature and increasing residence time and

solids loading through higher concentration; the intentions were good but yielded poor results17.

Maleic Acid

Despite the impressive sugar yields of sulphuric acid treatment it is thought that the inhibitor

production could reach levels that would have a negative overall effect on the process. Following

the same procedure, but in place of sulphuric acid, maleic acid can significantly reduce the

inhibitor production21. Yet to achieve inhibitor levels below influential levels the severity is

reduced by decreasing the tested temperature range from 140 - 170°C. At 150°C no influential inhibitors are present and the solid loading can be increased to 30% without any detrimental

effect. However, the overall sugar yields are considerably lower than the dilute acid technology.


Alkaline

Alkaline pretreatment works on a different principle than the other categories. By applying and

heating an alkaline solution to the feedstock the pores will swell. Allowed to soak for a sufficient

time or accelerated through pressure changes the swelling will cause an increased internal surface

area and a decrease in the degree of polymerization and crystallinity of the matrix structure. A

rather large fraction of lignin is solubilized along with hemicellulose exposing the cellulose

molecule. Hemicellulose is largely left in tact or recovered as oligomers meaning additional

hemicellulases is required. The quantity of lignin in the feedstock heavily influences the

performance of alkaline pretreatment. Higher lignin levels, as found in the recalcitrant material,

yield low sugar quantities unless the severity of the treatment is increased otherwise. In some

cases of softwoods, which contain large amounts of lignin, no or small effects were observed.

AFEX

Originally dubbed Ammonia Fast EXplosion22, or more recently altered to Ammonia Fibre

EXpansion23 to sound less imposing, it operates analogously to the steam pretreatment process.

The biomass feedstock is placed in a pressurized reactor and ammonia gas or liquid ammonia is

introduced. Over a short residence time of 10 – 60 minutes the temperature is gradually increased

to 80 - 150°C and brought to the corresponding pressures of 5 – 30bars. The material is sent into a flash tank after a quick release in pressure and while no visible change has occurred the material

has been physically altered. As ammonia is naturally in the gaseous phase at room temperature it

will slowly rise in the flash tank. To accommodate an effective ammonia recycling system it was

initially proposed to use a flash and distillation column achieving 97% recovery. AFEX requires

considerable amounts of ammonia having a 0.5 – 1.5 to dry biomass ratio. Following a detailed

process simulation (as the system is paper-theory) is was concluded that ammonia and its flash

recovery resulted in disproportionally high energy costs24. By focusing on ammonia reduction a

more energy efficiency recovery system was envisioned using a cold water quench25. That system

stipulated ammonia hydroxide be used in place of pure ammonia as the catalyst. Feasibility

testing found positive results at a greatly reduced ammonia consumption; down to a ratio of

0.175:1 ammonia to dry biomass26. AFEX works particularly well on agricultural waste and

processing residues yielding well above 90% free sugars27. Extra xylanase and hemicellulases is

however needed as only a minute portion of the C5 sugars are converted to monosaccharides. A

terrible performance is noticed for the recalcitrant material (i.e. high lignin) feedstocks. To

generalize feedstocks with a lignin content above 15% are not suited for AFEX pretreatment.

ARP

Ammonia Recycle Percolation is another type of process utilizing ammonia. Biomass enters a

packed-bed flow reactor (percolation reactor) and is exposed to aqueous ammonia at elevated

temperatures (150 - 170°C) and pressures (20 – 30bar). A lower solid loading of 20 – 30% over the AFEX process is present but does compensate by having a lower ammonia ratio demand as

compared to the original AFEX process. Recycling is envisioned by a conventional

evaporation/condensation unit, which does require a considerable amount of steam24, 28.

Nonetheless, ARP is an effective method to attain acceptable levels of digestibility (~90%) but


generally performs slightly worse than the AFEX process accompanied by an increased energy

demand. One particularity of the ARP systems is it ability to have a near complete delignification.

So far only corn stover has been tested (or published) and it is expected that it would follow a

similar trend as AFEX with the exception of possibility having a positive effect on the

recalcitrant materials due to its delignification properties.

Lime

Calcium hydroxide (CaOH) pretreatment is a straight forward, economically cheap, and easy

process to increase the susceptibility of cellulose. In a large continuously stirred batch reactor the

biomass feedstock is soaked in a 5 - 10vol% lime solution at a solid loading level of 10 – 20%. The

mash temperature is raised slightly to 50 - 60°C and allowed to sit for several days. Under these conditions the severity of the system is rather low meaning one week residence time is a

necessity. As with the other alkaline processes the pretreatment impregnates the biomass swelling

the pores thus increasing the internal surface area without majorly affecting the hemicellulose or

producing inhibitors. A limited number of studies have been conducted using lime. The well

investigated corn stover revealed remarkably high conversion rates when using 7.3mass% lime in

the magnitude of 90%29. Wheat stover has also been tested using a higher 10mass% concentration

of lime, but yielded considerably lower sugar levels30. The large difference places doubt on the

reliability of the stover figures. Regardless, of all the alkaline treatments lime does have the best

performance on the recalcitrant materials, but at best cannot surpass 80%31. Furthermore as lime

remains in the liquid phase a neutralization step with an acid is needed after soaking.

Enzymatic hydrolysis

After the above pretreatment processes, the cellulose contained in

the biomass feedstock is converted into fermentable sugars through

enzymatic attack. Enzymes will further hydrolysis and cause a near

complete saccharification of the available complex carbohydrates.

The hydrolysis reaction process for breaking down cellulose into

smaller polysaccharides (cellodextrins) or completely into glucose

units is called cellulolysis. Cellulolysis consists of three distinct steps:

absorption of the cellulase enzymes onto the surface of the cellulose, the biodegradation of

cellulose to fermentable sugars, and finally the desorption of cellulase. Because cellulose

molecules bind strongly to each other, cellulolysis is relatively difficult compared to the break

down of other polysaccharides. Reasonably high enzymatic activities and enzyme concentration

are required to achieve complete cellulolysis. Activity and concentration of cellulase is typically

expressed in filter paper units (FPU) per mass of glucan (all C6-sugars)32. The FPU of the

cellulase formulation mix vary immensely from the manufacturer, supplier, types, formations and

age but can generally be regarded set at 1FPU/g glucan is equal to 0.39mass%. In the laboratory

and experimental phase of the pretreatment technologies an over-dosage of enzymes is applied in

the order of 15 – 25FPU/g; this converts to 6 – 10 mass percentage. Increasing the dosage of

cellulases in the process can, to a certain extent, enhance the yield and rate of cellulolysis.

Cellulose enzymes are however expensive and their indirect energy production cost is


considerable meaning an industrial system would benefit from lower dosages. A dosage of

10FPU/g can be considered representative for industrial maturity, thus around 4.0mass% of

enzymes is added to the biomass feedstock to promote hydrolysis and saccharification. Most

cellulases is fungi derived with an unspecified formulated mixture of cellobiohydrolases and

endoglucanases supplemented with β-glucosidase (cleaves cellobiose). In a large reactor the pretreated biomass is mixed with the cellulases and brought to a solid loading of 4 – 6% through

water addition. The solution is adjusted to pH4.0 – 5.0, increased to 45 - 55°C and continuously mixed for 24 – 168hours. Off-heat from the pretreatment systems is usually more than sufficient

to cover the additional heating requirement of the enzymatic hydrolysis.

3.2.2 Hemicellulose

3.2.2.1 Description

Cellulose and lignin are bonded together in a matrix by the

unsymmetrical form of hemicellulose. It is used as the adhesive by

plants keeping the cell wall structure intact. It is a mixture of several

short, linear and branched heteropolymers (matrix polysaccharides)

formed by the 5-carbon ring sugars xylose and arabinose and (to a

lesser extent) the 6-carbon sugars glucose, mannose and galactose. Formed at random with an

amorphous structure is readily hydrolysed into its sugar monomers, but despite the wide

assortment of components hemicellulose consists mainly of D-pentose sugars with xylose

contributing to the largest amounts of sugar monomers. Meaning that, although a mixture of

components, the general formula of (C5H10O5)n can be taken.

3.2.2.2 Processing

As already mentioned lignocellulosic material containing cellulose, hemicellulose and lignin share

the same initial pretreatment processing steps. Hemicellulose is broken down into its monomers

(xylose) and oligomers (xylan). Many of the described pretreatment technologies are able to fully

break hemicellulose down to xylose while others continue to degrade it into inhibitors and still

others only provide a partial cleavage. Additional enzymatic hydrolysis is foreseen for those

pretreatment process which have an incomplete hemicellulose depolymerisation (cleavage).

Frequently xylanase or hemicellulases is added to the pretreated biomass feedstock in the same

cellulolysis reactor without any need to alter the conditions. Several cellulase enzyme cocktails

even contain a xylanase activity which can partially lower the addition of separate xylanase

3.2.3 Other Complex Carbohydrates

There are many complex carbohydrates contained lignocellulose feedstocks aside from pure

cellulose (glucose-based) and hemicellulose (xylose-based). Pectin and free sugars contribute to

adding extra trace levels of all the various saccharides. For simplifications 6-carbon based sugars

are allocated to cellulose and 5-sugar based sugars to hemicellulose.


3.2.4 Energy Input

The pretreatment energy input has been broken down into four sections (thermal energy, electric

energy, chemical production energy and enzyme production energy) and individually assessed for

both cellulose (C6-sugars) and hemicellulose (C5-sugars). The reasoning behind assessing C5 and

C6 sugars separately is that each biomass feedstock has a unique compositional ratio which will

lead to different yields and relative process energy costs. And although they have already been

categorized based on their feedstock type the exact compositional ratio will partially influence the

final process energy and exergy result.

Firstly, like with the simple carbohydrates, thermal and electric energy have been kept in their

direct energy form at this stage of assessment. Several of the main pretreatment processes were

simulated using Aspen+ and documented in full detail19, 24. The consumption of low (1.7bar),

medium (4.5bar) and high (13.2bar) pressure steam and net electric demand had been determined

for each process in relation to the total potential ethanol production. The energy and exergy

content of the steam consumption can be calculated by using saturated steam tables (Chapter 2)

and relates to the direct thermal energy/exergy demand. By carefully examining the heat (steam)

and work (electric) streams in the Aspen+ models in relation to the overall sugar yields, inhibitor

production and ethanol production the portion used in the pretreatment stage can be determined.

The values have been set for the standard operation conditions and conversion yield values

(processing residues; corn stover). Listed in the tables (4-6) are all the process conditions and

sugar conversion rates assigned to the pretreatment technologies for three various biomass

feedstocks categories. The listed temperature, pressure, residence time and solids loading directly

influence the process energy streams in the system. They mostly vary for the feedstock materials,

which will affect the steam and electric demand of the process. As the basic procedures remain

consistent for all feedstocks within the pretreatment technology options, it is those conditions

coupled with the conversion efficiency that alter the process energy demand.

Not all the covered processes have been accompanied with a detailed Aspen+ simulation process

file. In these situations new basic simulations must be complied using the known operation

conditions and sugar conversion yields. These are brought in relation to the well documented and

similar functioning procedures and expressed in the corresponding terms. For example, the

consumption level of high steam versus medium steam is dependent on the reactor operating

temperature of the pretreatment. Similar process heat integration options were also taken into

account. In the calculations thermal and electric process energy demand terms are listed as per

ton initial dry feedstock. The sugar conversion rates will thus directly stipulate the associated

product energy requirements; this is true for all systems.

In the tables: AFEX 1= standard flash recycling, AFEX 2 = proposed quench recycling, Lime 1 =

standard procedure, Lime 2 = WUR (Maas) procedure, Dilute 1 = standard sulphuric acid with

low solid loading, Dilute 2 = high solids, Steam 1 = H2SO4 catalysts, Steam 2 = SO2


Table 4 Pretreatment Optimal Conditions and Conversion Rates – Agricultural Waste

Type Temperature Pressure Residence Time

Solids Loading

Glucose Yield

Xylose Yield

Short name °C bar min % % %

AFEX 1 90 30 5 63 96.0 77.7 AFEX 2 100 20 5 55.6 94.1 89.1 ARP 170 23 10 23 88.5 76.4 Lime 1 55 1 40320 17.5 93.2 79.4 Lime 2 50 1 40320 12.4 56.0 67.0 Maleic 150 5 30 30 76.0 90.0 Dilute 1 160 12 20 5 91.6 91.2 Dilute 2 120 12 90 10 54.6 100.0 Steam 210 20 5 11 95.9 93.8 Steam 1 190 20 5 11 83.4 80.6 Steam 2 190 20 5 35 90.0 84.0 LHW 195 30 15 16 85.2 81.7

Table 5 Pretreatment Optimal Conditions and Conversion Rates – Processing Residues


Solids Loading

Glucose Yield

Xylose Yield



Table 6 Pretreatment Optimal Conditions and Conversion Rates – Recalcitrant Material


Solids Loading

Glucose Yield

Xylose Yield




Secondly, the chemicals involved in the various pretreatment technologies are related to their

cumulative fossil fuel energy/exergy demand. To determine the associated energy cost the level

of added chemicals and the recovery levels must be documented. Several of the process

technologies with 0% recovery of the active chemical will require an accompanying additional

neutralization chemical in the order of an equal molar ratio. Listed in table 7 are all the basic

figures needed to calculated the chemical energy/exergy requirements and because the

concentrations are not varied for the biomass feedstocks types it is representative for all. In this

regard though, the associated chemical costs will be related to the sugar conversion yields as was

done with the thermal and electric energy demand. So, although the requirements are equal for all

feedstocks the relative chemical demand varies for the monosaccharide products.

Table 7 Pretreatment Chemical Requirements – All Feedstocks

Type Active Chemical

Concentration Recovery CED CExD Neutralizing Chemical

CED CExD

Short name Formula ton/ton feedstock % GJ/ton Formula GJ/ton

AFEX 1 NH3 0.80 97.0 28.40 29.96 - - - AFEX 2 NH3 0.167 96.0 28.40 29.96 - - - ARP NH3 0.47 95.0 28.40 29.96 - - - Lime 1 Ca(OH)2 0.073 0 7.04 7.39 H2SO4 1.44 3.28 Lime 2 Ca(OH)2 0.10 0 7.04 7.39 H2SO4 1.44 3.28 Maleic C4H4O4 0.047 80.0 26.60 27.93 Ca(OH)2 7.04 7.39 Dilute 1 H2SO4 0.093 0 1.44 3.28 Ca(OH)2 7.04 7.39 Dilute 2 H2SO4 0.45 0 1.44 3.28 Ca(OH)2 7.04 7.39 Steam - - - - - - - - Steam 1 H2SO4 0.055 0 1.44 3.28 Ca(OH)2 7.04 7.39 Steam 2 SO2 0.056 0 13.82 18.16 - - - LHW - - - - - - - -

Thirdly, the cellulase and hemicellulases enzyme requirements are also related to their cumulative

fossil fuel energy/exergy demand. These particular grades of fungi-based enzymes are

extraordinarily energy intensive to produce. Following the same enzyme producer report3, they

require upwards of 230GJ/ton formulated product. During the early financial investigations

surrounding the lignocellulosic material processing it was acknowledged that the cellulase placed

a major strain on the economical feasibility. These high economic costs can be paralleled with

high energetic production costs. Some years back it was resolved to significantly lower the

associated enzymatic hydrolysis step by 10-fold. This initial 10-fold goal has been reached and

new goals have commenced to extend it to a 20 to 30-fold reduction (Genencor, Novozymes).

Cost reduction was reached by improvements on three different aspects in the chain; fungi strain

engineering, more efficient production methods and an increased activity. The increased activity

has already been incorporated by the proposed industrial loading rate of 10FPU/g as opposed to

the laboratory 15FPU/g glucan. To include the other expected improvements for industrial

applications the CED/CExD for the enzymes are lowered 10-fold to 23.5GJ/ton energy and

28.4GJ/ton exergy. The ammonia based pretreatment technologies require an extra 10FPU/g

hemicellulases, the other alkaline processes 5FPU/g as well as the LHW process. Combined they

form the indirect enzyme energy costs, still a considerable portion of the total.


Finally, the four sections of the pretreatment energy input can be combined. Resulting values are

expressed per ton cellulose and ton hemicellulose as well as the total converted sugars. To

determine the associated process energy input for the two products the conversion ratio and

feedstock composition ratios were used. As can be seen in the following graphs and tables,

cellulose has for all technologies a higher associated process energy input than hemicellulose; due

to a typically higher compositional ratio and conversion rate. The following figures illustrate the

proportion of the four direct and indirect energy costs for each feedstock category; C: Cellulose

or C6-sugars, H: Hemicellulose or C5-sugars. It is noticeable that some technologies may

perform well in having low direct thermal and electric consumption but due to their chemical use

(as a measure of severity) results in a higher overall energy input. The tables below lists the total

process energy and exergy input for cellulose, hemicellulose and the sugars combined. The

pretreatment technology with the lowest overall energy input will be selected for that particular

biomass feedstock type for use in the biorefinery system. Its conversion rates, conditions, and

energy/exergy input will form the basis of all subsequent processing within the biorefinery.

Rather surprisingly the selection is different for each biomass feedstock category.


Figure 1 Pretreatment Energy Costs – Agricultural Waste

Pretreatment Energy Costs

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

C H C H C H C H C H C H C H C H C H C H C H C H

AFEX 1 AFEX 2 ARP Lime 1 Lime 2 Maleic Dilute 1 Dilute 2 Steam Steam 1 Steam 2 LHW

GJ/ton product

Enzyme Indirect Energy

Chemical Ind irect Energy

Electric Ene rgy

Thermal Energy

Agricultural Waste

Table 8 Pretreatment Energy/Exergy Costs – Agricultural Waste

Type Total Energy (GJ/ton product) Total Exergy (GJ/ton product) Short name Cellulose Hemicellulose All Sugars Cellulose Hemicellulose All Sugars

AFEX 1 3.42 2.23 5.65 2.24 1.71 3.95 AFEX 2 1.82 1.48 3.65 1.55 1.39 2.94 ARP 3.65 2.45 6.10 2.23 1.74 3.97 Lime 1 3.53 1.89 5.42 2.19 1.15 3.34 Lime 2 4.62 3.32 7.94 2.00 1.24 3.24 Maleic 2.32 1.06 3.38 2.01 0.67 2.68 Dilute 1 2.33 0.90 3.23 2.42 0.83 3.25 Dilute 2 4.14 3.79 7.93 4.36 3.82 8.18 Steam 2.31 0.87 3.17 1.52 0.25 1.77 Steam 1 3.22 1.42 4.64 2.11 0.61 2.72 Steam 2 3.25 1.39 4.64 2.43 0.78 3.22 LHW 3.59 2.11 5.70 1.62 0.87 2.48

The lowest energetic cost for agricultural wastes is steam, at 3.17GJ/ton sugar products.

�� Agricultural waste biomass feedstocks = Steam pretreatment


Figure 2 Pretreatment Energy Costs – Process Residues


0.0

1.0

2.0

3.0

4.0

5.0

6.0



GJ/ton product



Electric Ene rgy

Thermal Energy

Processing Residues

Table 9 Pretreatment Energy/Exergy Costs – Process Residues



The lowest energetic cost for agricultural wastes is AFEX 2, at 3.43GJ/ton sugar products.

�� Process residue biomass feedstocks = AFEX (Quench) pretreatment


Figure 3 Pretreatment Energy Costs – Recalcitrant Material


0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0



GJ/ton product



Electric Ene rgy

Thermal Energy

Recalcitran t Mate rial

Table 10 Pretreatment Energy/Exergy Costs – Recalcitrant Material



The lowest energetic cost for recalcitrant material is dilute acid 1, at 3.53GJ/ton sugar products.

�� Recalcitrant material biomass feedstocks = Dilute sulphuric acid pretreatment


3.3 Glucose Chemistry

Once a solution of sugar liquor has been created the proceeding processing steps for the

conversion into fermentable products (like ethanol) is universal. Sugar liquors from both the

simple and complex carbohydrates could in theory be joined at this stage. Depending on the

biomass source these sugar liquors will either contain C-6 sugars (glucose) or C-5 sugars (xylose).

And the only real difference between these sources is the microorganisms used for fermentation

and the maximum conversion yield. There are a few modern exceptions to this general rule which

are increasing the overall conversion rates and lowering the energy intensity. They will be

discussed after the basic (or standard) processing steps have been described. Glucose chemistry is

essentially a two-step process; fermentation followed by a purification step. The purification step

is typically a thermal liquid-liquid separation unit operation, e.g. a distillation unit. These are

highly energy intensive and research efforts are underway to avoid their use.

Many products deriving from sugars are proposed within the biobased

economy. In a recent EC report 21 different bio-based products, practically

all deriving from glucose chemistry, were investigated in detail33. The entire

basis of investigation was placed on the assessment of only three biomass

sources; dextrose from corn starch, sucrose from sugar cane, and C5/C6

sugars from corn stover. Producing these fermentable sugars has been in part practiced for

centuries in the manufacturing of food-grade syrups with product quantity not energy efficiency

controlling the production method. The most common corn syrup (glucose syrup) is derived

from the wet milling process. As described in Section 3.1.1.2 wet milling not the most energy

efficient method and has no place in the non-food biomass applications. In the BREW project

the non-renewable process energy for the three fermentable sugar sources are based on those

traditional methods and documented as 6.2 – 10.3GJ/ton for dextrose, 1.4 – 1.7GJ/ton sucrose

and 4.9 – 7.6GJ/ton C5/C6 sugars. The documented resulting dry matter content also varies

which makes the evaporation and purification steps difficult to assess. Regardless the sugar liquor

stream does not need to be concentrated for use in fermentation systems, which will reduce

process energy demand. It is however good to note that following this government document

10.3GJ/ton glucose is considered standard for the biochemical sector (from corn). Industrial

improvements and experience over several decades have made ethanol the benchmark for

anaerobic fermentation and will be the only product investigated derived from carbohydrates.

3.3.1 Ethanol production

3.3.1.1 Description

Ethanol is the single most important bio-based chemical product in

the biomass field and forms the basis of any biorefinery concept. It

goes by many names from its scientific term ethyl alcohol to the

common grain ethanol and simply alcohol. At purities above 99.9%,

which is foreseen for downstream utilization in the biorefinery, it is

called absolute ethanol or anhydrous ethanol. Industrial production of


anhydrous ethanol is by far not a new and revolutionary process. Over the last three decades the

ethanol industry has been shaped into a high-tech production process and because industrial

grade ethanol will not follow the time honoured potable alcohol systems it can achieve vast

energy consumption reductions. Industrial ethanol has a few traditional applications in its virgin

state although it would not at all be presumptuous to state that its use as a transportation fuel

replacement option is the most commonly known. Bioethanol use in the transport sector is either

found in its pure form or as a blend with gasoline. The advances made in this sector will be listed

and incorporated in the biorefinery layout. The current standard industrial process layout will be

covered first followed by the recent developments and proposed improvements. Despite the

growing market of bioethanol, within the biorefinery system for chemical replacement ethanol is

regarded as a feedstock for the production of ethylene. In this respect the effective dehydration

step all determining.

3.3.1.2 Standard Processing

Fermentation

In a reactor the sugar liquor is exposed to fermenting enzymes, most commonly contained within

the microorganism yeast. Minute quantities of oxygen will promote the production of carboxylic

acids (like vinegar) and other unwanted by-products which one often associates with cheap

French wine. Anaerobic conditions are imperative and must be upheld to maximize microbial

fermentation yields. Bakers yeast, Saccharomyces cerevisiae, can easily convert the C6-sugars into

ethanol and is employed in nearly all bioethanol facilities worldwide. C5-sugars, however, cannot

be converted very well by standard strains of yeast. As the biorefinery system will incorporate all

sources of carbohydrates, including hemicellulose, standard strains are not acceptable. Modified

yeast strains and other bacterial strains exists that can convert xylose into ethanol, but generally

require a separate fermentation tank as the operating conditions are different; cofermentation

would be preferred. Already in 1994, work began on genetically engineering the Zymomonas mobilis

bacteria organism34. It can effectively ferment both C6 and C5-sugars in one reactor under the

same operation conditions and compared to standard yeast also boosts a 2 – 4% extra conversion

yield. Z. Mobilis is market ready and has an overall sugar conversion rate of 92 – 94%. The

following reactions occur in the fermentation reactor:

Glucose � 2Ethanol + 2Carbon Dioxide (96% conversion) C6H12O6 � 2C2H5OH + 2CO2

1⋅180.16g/mol (180.16g/mol) � 2⋅46.07g/mol (92.14g/mol) + 2⋅44.01g/mol (88.02g/mol)

Stoichiometric Ratio: 92.14 ÷ 180.16 = 0.512g/g

3Xylose � 5Ethanol + 5Carbon Dioxide (90% conversion) 3C5H10O5 � 5C2H5OH + 5CO2

3⋅150.13g/mol (450.39g/mol) � 2⋅46.07g/mol (230.35g/mol) + 5⋅44.01g/mol (220.05g/mol)

Stoichiometric Ratio: 230.35 ÷ 450.39 = 0.512g/g

The conversion of C5-sugars is slightly lower than C6-sugars but does have the same mass

conversion loss of 0.488g/g through the formation of carbon dioxide. The formed carbon

dioxide is vented and scrubbed to recover any trace ethanol that was diffused into the vapour


phase. In older (existing) open-vat systems this portion is lost. Conventional fermentations are a

batch process reaching completion when the ethanol concentration has achieved 7 – 9vol%.

Rather recent advancements in fermentation technology have allowed the critical concentrations

to raise to 12 – 13vol%. This significantly reduces the downstream separation energy intensity. It is

also an exothermic reaction requiring cooling to maintain operation temperatures between 25 -

37°C with 38°C being the upper limit; temperatures above 40°C will kill the bacteria. But, before the microorganisms are even added a sterilization shock is needed to properly prepare the

fermentation medium (broth) to ensure no inhibiting infections and a smooth fermentation.

Nutrients containing nitrogen, phosphorous, potassium and other trace minerals are supplied to

the broth ensuring an optimal bacterial growth. DAP (diammonium phosphate) is employed

industrially and covers the brunt of the nutrient requirements. The final ethanol containing

solution existing the fermentor is called beer.

Separation

During the early industrial applications of ethanol production its separation from the beer stream

was straight forward involving one large standard distillation column. Over the last two decades

thermally integrated distillation technology which encompass separate stripping and rectification

operation units have greatly reduced the energy intensity. Now producing a pure stream of

ethanol from the beer stream involves a multitude of separation steps.

First, the beer is sent to a so-called beer distillation column (type of stripper)

to separate the solid residue partials including microbes and a great deal

of the water. In some layouts the bottoms are partly circulated to the

fermentation reactor or hydrolysis step, but their fate within the

biorefinery will be handled in later sections. This initial distillation step

increases the ethanol concentration from 12.5vol% to 37 – 40wt%. In the

second distillation column, known as the rectifying unit, the ethanol/water

mixture is brought to the azeotropic point. Due to the azeotropic point this ethanol mixture will

always contain a small percentage of water between 4 – 9wt%. Third, a dehydration unit is needed to

obtain anhydrous (or water-free) ethanol. Traditionally benzene was the chemical of choice to

lower the azeotropic point from 78.2°C to the 64.9°C needed to make 99.5vol% pure ethanol. Regulation in many countries has banned the use of benzene in place for cyclohexane.

Nonetheless this azeotropic distillation step is energy and chemically intensive and cannot be

considered standard. Vapour phase pressure swing regeneration systems, or marketed as

molecular sieves, dehydrate the ethanol product to 99.5% through adsorbing water into a fixed

bed of zeolite beads. Desorption is performed at elevated temperatures and under vacuum to

force the water molecules out of the zeolite structural matrix, regenerating it. Praj systems state

energy savings of up to 50% and their EcoMol products dominate the ethanol dehydration

market. All newly constructed and planned bioethanol facilities (in America) include molecular

sieve dehydration units and can be considered the current standard practice. The whole

separation system encounters an ethanol loss of 0.4 – 0.7wt%.


3.3.1.3 Recent Processing Improvements

Fermentation

As previously described hydrolysis requires 24 – 168hours (with 96h being normal) residence

time to achieve a complete conversion to the monosaccharides. The accumulation of these sugars

naturally inhibit the enzyme performance which is overcome by lower solid loadings and longer

residence time. Simultaneous saccharification and fermentation (SSF) offers the potential for reduced

fermentation times, decreased capital costs and a more uniform operation temperature to

decrease process energy demands. It works on the concept of continuously removing the formed

sugars by immediately fermenting them in the same reactor, thus keeping the concentration low

and allowing the enzymes to perform more effectively. The idea was first conceptualized in the

late 1970’s and has been seriously considered for more than two decades and is still being

researched upon to fix the optimum, especially in relation to energy consumption2, 35, 36. The

residence time can be lowered to 72hours but presents other compromises. SSF (as is) is not a

suitable option for converting the simple carbohydrates as the optimal operation temperatures

between the enzymatic hydrolysis (65 – 90°C) and fermentation (37°C) differ too much. Complex carbohydrate enzymatic hydrolysis, on the other hand, operate at lower temperatures

(50°C) and present only minor operational compromises. Furthermore, the resulting ethanol concentration is actually very low rarely exceeding 4wt% (5.1vol%), placing a particularly high

energetic burden on the standard separation techniques. There are two recent developments that

when integrated can remove the temperature difference issue and turn the lower solids loading

compromise into an energy reduction opportunity.

(1) Genetic modified enzymes and microorganisms have the potential to solve many process

engineering problems through specifically tailoring the desired traits. Thermtolerant yeast and

bacteria strains are able to survive at considerably higher temperatures that would otherwise kill

microorganisms. One such organism is Clostridium thermohydrosulfuricum which can ferment both

C5 and C6-sugars at temperatures of around 60°C. Another modified organism which also uses a wide range of sugars, Bacillus stearothermophilus, can handle temperatures in excess of 75°C. Thus, it

is can be expected that continued progress in GMO strains creation will allow fermentations to

be held at optimal hydrolization operating temperatures. Towards the 65°C range the SSF system could convert all carbohydrate sources as effectively as the current best organisms. Plus, at these

temperatures cooling requirements would be reduced, even creating an extra low heat integration

option to mitigate a portion of the steam demand.

(2) At about 14wt% ethanol fermentation will stop because beyond those concentrations it is toxic

to the microorganisms. Actively removing ethanol while it is being produced can maintain safe

and optimum concentration levels in the fermentation broth. Several conceptual process layouts

have been recently conceived and investigated to achieve a steady state operation. Sending the

fermentation mash into a column with carbon dioxide as a stripping agent has been proposed37.

It was developed for corn starch achieving a continuous ethanol concentration of 5 – 8wt% in the


broth and 25 – 27wt% concentration after the stripping. Removing the carbon dioxide from the

stripped vapour is performed by compression or condensation via cryogenics. Both recycling

options utilize a rather large quantity of electricity in the order of 4.1 – 6.5GJ/ton EtOH (internal

report calculations). The energy intensity also increases with lower fermentable material

concentration which would be the case for complex carbohydrate streams. And despite the

distillation energy savings from an elevated concentration starting point, this layout would be

more energy intense than the standard system. Stripping, however, is still a promising option.

Several bioethanol plants have been constructed in the last decades based on Alfa Laval’s Biostil

process. It was initially plagued by operational and process flow hurdles with design concessions

making it a semi-continuous processes. Many of the problems have since been solved and a new

fully continuous system is available, marketed as the Biostil 2000 process (high performance

ethanol production plant)38. It works by using a portion of the hot ethanol/water vapour mixture

to strip ethanol from the fermentation mash. In the mash stripper 90% of the ethanol contained

in the fermentation mash is removed resulting in a 40wt% ethanol/water stream. And an ethanol

concentration of 6.5wt% is upheld in the broth ensuring optimal concentration. Increasing the

SSF system’s resulting ethanol concentration from 4.0wt% to 6.5wt% should be feasible to applied

in this concept. Microorganism propagation levels are also reduced due to recycling and longer

vitality brought forth by the system dynamics.

Separation

Pervaporation has been a topic of much discussion and research for many decades. A large array

membrane materials are being developed and tested from complex composites to straight

silicalite polycrystallines to simple polymers. They all work by the same principle under similar

(low temperature) conditions and should be ready for large-scale industrial applications shortly.

Membrane production is slowly approaching economic feasibility and is considered a realistic

possibility to replace the distillation or even the rectifying unit. Several studies have begun

investigating the option of creating a continuous fermentation with pervaporation. The

fermentation mash is passed over a non-porous membrane with a hydrophobic coating where

ethanol travels through the membrane by being brought into the vapour phase. A vacuum pump

on the permeate side of the unit provides the necessary pressure drop (5 – 10bar) to convert the

ethanol (and a large portion of water) from the liquid stream to vapour phase. A cooler

condenses the 20 – 23wt% rich ethanol/water stream back into the liquid phase. Membrane

fouling (clogging) problems and low product through-puts have not yet been solved. The 40wt%

ethanol/water stream coming from the continuous Biostil-SSF system could benefit from using

pervaporation technology without encountering fouling constraints. As intriguing as this may

appear, pervaporation would not be suitable within the system because a portion of the rectifier’s

hot top stream is used to strip the ethanol from the fermentation broth. To substitute the

rectifier the product stream would have to the heated to specification, effectively removing the

energy reduction benefit. Nonetheless, integrating the rectifier product stream in the mash

distillation column does present minor energy reduction over the standard layout. Again as

ethanol stream leaving the rectifier unit is not 100% pure a dehydration step like in the standard


layout is needed. Molecular sieves are effective and efficient but limited to 99.5% purity, whereas

modern nanoporous dehydration membranes can achieve 99.7% at even slightly reduced energy

costs39. Acting as a filter pore sizes of 0.4nm are only permeable to the smaller water molecules

thus separating the larger ethanol molecules. A pressure gradient of 1.5bar is introduce by

pressurizing the feed flow and creating a vacuum of 0.007bar on the permeate side.


Both the “standard” and “select recent” improvement process energy and exergy input for the

glucose to ethanol production route have been handled. Table 11 lists the resulting direct and

indirect energy as well as the relevant conditions. A fermentation unit requires modest agitation

and aeration electric energy based on the medium volume ranging from 3.1 up to 23kWh/m³;

realistic best practices were chosen33. As the broth concentration is lower for the select recent

process and is recycled, its electric consumption is noticeable higher. Microbial indirect

production energy costs are based on the Simapro LCA database for yeast at 8.4MJ/kg. Recycling

is taking into consideration for the select recent process. The nutrient DAP has an energy/exergy

production demand of 3.73/4.63GJ/ton (based on Chapter 5) with 0.044ton/ton ethanol

requires for both system layouts. Distillation is the most energy intensive step in ethanol

production. Old systems (starting at 7 – 8vol%) required 6.3 – 7.6GJ/ton EtOH. Increasing the

broth concentration to 12.5vol% reduced it to 5.4GJ/ton and combining the beer column and

rectifier unit reduce it further to 3.93GJ/ton40. Using a portion of the rectifiers top product as a

stripping agent reduces the thermal energy consumption even lower to 2.80GJ/ton. Azeotropic

dehydration costs between 2.6 – 3.3GJ/ton while modern molecular sieves are only 0.67GJ/ton.

All separation operation require moderate level of circulation electricity, but the nanoporous

dehydration being based on pressure gradients has a higher electric demand explaining the

difference in thermal and electric for the select recent process.

Table 11 Glucose Processing Energy/Exergy Input – Standard and Select Process

Category Unit Standard Process Select Recent Process

Fermentation Conditions Broth Concentration wt% EtOH 12.5 6.5

Temperature °C 37 65

Direct Energy (Exergy) Electric GJ/ton EtOH 0.136 0.194 Thermal GJ/ton EtOH 0.588 (0.058) 0.362 (0.036) Indirect Energy (Exergy) Microbial GJ/ton EtOH 0.009 0.005 Chemicals GJ/ton EtOH 0.164 (0.204) 0.164 (0.204) Separation Conditions Input Concentration wt% EtOH 12.5 40 Output Concentration wt% EtOH 99.5 99.7 Direct Energy (Exergy) Electric GJ/ton EtOH 0.321 1.462 Thermal GJ/ton EtOH 4.603 (0.932) 2.800 (0.097)

Conversion rates for both system layout is 96.0% C6 and 90.0% C5


3.4 Overall Ethanol Production Cost

The overall ethanol production cost is merely a summation of the glucose/xylose preparation and

the ethanol fermentation and separation process energy input. It will be highly crop dependent as

the final values are based on the conversion rates and individual proportion of the simple and

complex carbohydrates. The general biomass feedstocks as covered in the previous sections will

be used as an indication. So, in the following sub-sections the direct process energy (thermal and

electricity) and indirect process energy (chemicals, microorganisms, etc.) are presented for the 1st

generation and 2nd generation bioethanol technologies. A distinction has been made between the

standard ethanol and the selection of recent improvement process layouts.

3.4.1 1st Generation Bioethanol

Figure 4 1st Generation Bioethanol – Overall Process Energy Input

1st Generation Ethanol Production

0.0

2.5

5.0

7.5

10.0

12.5

Standard Recent

Select

Std. Sel. Std. Sel. Std. Sel. Std. Sel.

Cereals Cereal (Cron) Tuberous Stem-based Bulb-based

GJ/ton Ethanol

Indirect Energy

Electric Energy

Thermal Energy

Table 12 1st Generation Bioethanol Production Costs

Feedstock Type Cereals Cereals (corn) Tuberous Stem-based Bulb-based

Overall Conversion (ton EtOH/ton carbohydrates)

0.473 0.480 0.488 0.466 0.467

Total Energy (GJ/ton) 6.86 7.82 10.76 5.96 7.04 Total Exergy (GJ/ton) 2.81 2.97 3.51 2.97 2.46

Only the recently select improvement ethanol process route, not fully cumulative

As expected the stem-based crops, like sugar cane, have the lowest process energy intensity for

the production of the biofuel. However in terms of exergy it is the bulb-based crops, like sugar


beet, which require the least amount of process exergy. The stark difference between energy and

exergy illustrate the inefficiencies of steam utilization for mild temperature treatments.

3.4.2 2nd Generation Bioethanol

General indication, but not specific as in Chapter 8 the biorefinery will be based per crop. Here

the three types are developed for both the standard and select.

2nd Generation Ethanol Production

0.0

2.5

5.0

7.5

C H C H C H C H C H C H

Standard Recent Select Standard Recent Select Standard Recent Select

Agricultural Wastes Processing Residues Recalcitrant Material

GJ/ton Ethanol

Indirect Energy

Electric Energy

Thermal Energy

Table 13 2nd Generation Bioethanol Production Costs

Feedstock Type Agricultural Wastes Processing Residues Recalcitrant Material

C6 Conversion 0.471 0.449 0.462 C5 Conversion 0.432 0.398 0.438 Overall Conversion (ton EtOH/ton carbohydrates)

0.456 0.428 0.438

Total Energy (GJ/ton) 8.75 9.07 8.27 Total Exergy (GJ/ton) 4.17 5.65 4.45

Only the recently select improvement ethanol process route, not fully cumulative

Conversion of lignocellulosic feedstocks are in the same broad range (5.96 – 10.76GJ/ton) as the

1st generation route, but all have a higher process energy cost than the best biomass feedstock

option. Rather surprisingly the best performance of the 2nd generation feedstock types is for the

recalcitrant materials, like the willow tree. Like the 1st generation technologies, there is large room

for energy efficiency improvements as indicated by the difference in energy and exergy, however

as there is a higher reliance on electricity and indirect inputs it is at a lower magnitude.


3.4.3 Combined generation

At this stage it is not possible to combine the 1st and 2nd generation technology for display

purposes as the results are heavily feedstock dependent. Nearly all biomass feedstocks contain

portions of simple carbohydrates and complex carbohydrates, where several other will first be

processed for their high fatty acid content. In a biorefinery they will be combined into one

system and will be presented in Chapter 8. Besides, ethanol is destined for ethylene production

within the realms of the biorefinery and the above results are more for interest than crucial for

the calculation of the process energy inputs of the biorefinery.

3.4.4 Ethylene Chemistry

3.4.4.1 Description

Originally called olefiant gas its official term is ethene as stipulated by the

1993 IUPAC nomenclature guidelines, but is still most commonly

referred to as ethylene. It is the simplest alkene chemical with the

molecular formula C2H4 and is present in the gaseous phase in its

virgin form at atmospheric conditions. Ethylene is the single most

important primary petrochemical with an annual global production

exceeding 75Mton. It is used in the synthesis of many other chemicals, but especially used as the

base building block for the production of plastics. Polyethylene (PE), Polyethylene Terephthalate

(PET), Polyvinyl Chloride (PVC), and Polystyrene (PS) comprise of at least half the total global

production of plastics and all four derive from ethylene. The conventional production method is

through the thermo-cracking of the naphtha feedstock. Industrial dehydration of ethanol has

been around for more then a century but has only recently, through improved catalysis, achieved

conversions rates that can compete energetically to the highly efficient cracking route.

3.4.4.2 Processing

The dehydration of ethanol into ethylene is an easy and straight forward reaction involving only

moderate energy demands. The basic technological process is well-known and was first proposed

and employed on a limited degree during the early phases of the 1975 Brazilian PróAlcool

program. Typically ethylene production was restrained to solitary ethanol producers and minor

players in the chemical industry but due to the low conversion yields was eventually phased out.

Currently interest in producing ethylene from bioethanol has since re-emerged in Brazil over the

last few years. Braskem and Dow have both announced the construction of full-scale ethylene

factories based on sugar cane ethanol. Anhydrous ethanol is heated to the vapour phase and

passed over a catalyst-lined dehydration column to remove the water The process is a two-step

reaction; firstly, ethylene ion formation by adsorbing the water (H-O-H) side branch of the

ethanol molecule and secondly, proton removal by splitting the hydrogen cation off creating the

double bonded carbon ethylene molecule. The entire reaction occurs at elevated temperatures

(180 - 500°C) and atmospheric pressures with no presence of water vapour. The intermediate ethylene cation product is highly reactive and will immediately reform into ethanol under the


presence of water molecules. This is why it is imperative that the anhydrous ethanol product

stream be of a maximum purity, for any trace water will lower the ethylene yield. It is also the

function of the catalysts to adsorb and contain the water molecules during the entire process.

Scores of different catalysts have been investigated to maximize the ethanol dehydration

conversion rates. Metal oxide catalysts (Fe2O3 and Mn2O3) along with various calcined physical

mixtures of ferric and manganese oxide with alumina and silica gel have been tested41. The

selectivity of the catalysts showed a strong correlation to temperature dependence, particularly at

high temperatures approaching 500°C. Regardless, the best metal oxide catalyst could not surpass 80% ethanol to ethylene conversion rate and at those temperatures would entail high associated

energy demands. These systems represents the failed earlier attempts at industrial production.

More recently investigation has shifted to solid acid catalysts such as pure silica-alumina and

other zeolite configurations at a lower temperature range (180 - 300°C)42. A catalyst mixture of 90%-SiO2 and 10%-Al2O3 at a high activity of 25.1g catalyst⋅minute per nmol ethanol can dehydrate 99.9% of the ethanol at 180°C. These adsorbing zeolites help prevent the reformation of ethanol and while it is possible to obtain a conversion rate of almost 100% an ethylene carbon

selectivity of more than 99wt% is difficult. Under the best patented solid acid catalysts process a

loss of 1.5% is present, resulting in a product yield of 98.5%43. Steam is foreseen as the thermal

energy source to elevate the column to the absorptive temperature and for regeneration.


Effective and energy efficient dehydration of ethanol for the production of ethanol is a recent

development with corporate propriety restricting the transparency. Depending on the exact

system and configuration the total energy demand ranges from 0.8 – 2.5GJ/ton ethylene. Reverse

calculations from the confidential Shell data used in the EU-BREW report reveal a total energy

consumption of (0.78 – 1.15GJ/ton) with 0.98GJ/ton ethylene being the mean. To avoid its use

the molecular sieve (zeolite) ethanol dehydration unit was used as a guide to determine the actual

electric and thermal energy consumption by relating to the product flow. Ethylene from ethanol

has a stoichiometric yield of 0.609kg/kg or 1.64ton ethanol per ton ethylene. By including the

trace water levels and conversion efficiency the actual ratio becomes 1.67ton ethanol per ton

ethylene. In addition to this higher material adsorption and regeneration requirements the

operation temperatures demand high pressure steam. Here the resulting total direct energy

consumption has been determined to be 1.47GJ/ton. And despite the heavy reliance of catalysts

material the consumption versus the product throughput is so low that its indirect energy

consumption is negligible.

Table 14 Ethylene Processing Energy/Exergy Input

Category Unit Values

Conditions Temperature °C 180

Overall Conversion Rate ton ethylene/ton ethanol 0.598 Direct Energy (Exergy) Electric GJ/ton ethylene 0.30 Thermal GJ/ton ethylene 1.17 (0.26)



4 Fatty Acids

4.1 Description

Although commonly associated with poor human nutrition through high

consumption of animal fats, there are at least 40 distinct plant species

known to produce fatty acids in large quantities and concentrations which

actually represent the bulk of global production. Fatty acids are defined by

having a carboxylic acid molecule linked with a long unbranched aliphatic

tail. They form a major part of the broader chemical classification lipids,

and when present in plant matter are frequently referred to as organic oils,

vegetable oils or merely oil. They are formed through the biosynthesis involving the coenzyme

acetyl-CoA which by carrying a 2-carbon atom group lead to most natural fatty acids composing

of an even number of carbon atoms. In plant matter, they have at least 8 carbon atoms ranging

up to but rarely 24. Furthermore, fatty acids are sub-classified under two categories; saturated and

unsaturated. Those enclosing a carbon-carbon double bond along the aliphatic tail are said to be

unsaturated, while those composed solely of single carbon bonds are known as saturated. Thus a

wide range of fatty acids exists written as CN:M, with N being the number of carbon atoms and

M being the number of carbon double bonds. Palmitic acid (CH3(CH2)14COOH), the most

widespread saturated fatty acid is written C16:0. Oleic acid (CH3(CH2)7CH=CH(CH2)7COOH),

being one of the most widespread unsaturated fatty acids is written C18:1. Practically all fatty

acids, saturated and unsaturated, in plants have the carboxylic acid group bonded to each other

forming a glycerine end chain. These triglyceride molecules are large, diverse, crop dependent and

have a high molecular weight (850 – 950g/mol) leading to oily properties. Vegetable oils and free

fatty acids serve several particular functions in plant matter; they are essential to build and repair

cell structures like the cell wall, form a small proportion of cell membranes, participate in

signalling pathways, but most importantly are concentrated energy sources. Germinating seeds

restricted in size, regardless of the biological grounds, are usually associated with large

concentrations of fatty acids. They typically range from 40 – 50% with some plant species

containing over 70% in the fruit.

Despite the rising health food craze onset by recent obesity trends, within a biorefinery for the

non-food market there exist only a few product options. Hydrolysis or alcoholysis (hydrolysis

with alcohols) of triglyceride fatty acids will form oleochemicals. They are analogous to chemicals

derived from petroleum including fatty acid methyl esters, fatty alcohols, fatty amines and

gycerols. Applications are generally limited to the pharmaceutical, cosmetic and other speciality

industries with restricted production volumes. The transesterification (specific alcoholysis type)

of triglycerides, however, will produce biodiesel and, under strict formulations, biolubricants that

both have bulk production potential. But while most fatty acid-rich crops are currently cultivated

for biodiesel production, it is not a chemical and also has inferior product properties over

conventional fuel diesel, thus biodiesel production (like bioethanol) will not be included in the

biorefinery system layout. Biolubricants, on the other hand, have equal (or even superior)


properties compared to the petroleum-based lubricants and is a chemical with bulk production

potential, reaching 72.7Mton in 200544. The initial processing steps are practically identical to

biodiesel involving pressing, extraction, transesterification and modern solutions for glycerine

production. The true difference is formulation with the exact free fatty acid composition

determining the application and type of biolubricants products, while biodiesel is an unspecified

mixture. Thus, for simplification only one standard blend for each crop type will be chosen to

assess the process energy. In addition, modern and efficient system developments with recycling

and innovative product developments will be covered.

4.2 Processing

The fatty acids of vegetables oils are present in their triglyceride form in relatively high

concentrations in the seeds or fruits of biomass crops. Processing seeds and fruits to obtain free

fatty acids for biolubricants production involves four basic steps; pressing, extracting,

transesterification and purification. These processing steps are identical to standard biodiesel

production methods with industrial and scientific literature information supplying detailed

reports and processing conditions. After the creation of fatty acid esters further separation,

isolation, mixing and/or supplying additives are required to improve performance characteristics

(such as oxidative stability, pour point and viscosity index) of formulated biolubricants. Many

researchers have even gone directly to the biomass production itself genetically altering the fatty

acid compositional distribution in the plant to produce a higher quantity of the desired fatty

acids45. Plus, like the carbohydrate-rich crops, feedstock type influence the process conditions

and energy demands. In the case of fatty acid-rich crops only two categories will be made; seed-

based (40 – 50%) and fruit-based (70 – 80%). The standard processing will be handled first

followed by the recent processing improvements in light of process energy reductions.

4.2.1 Standard Processing

Pressing and Extracting

As a preliminary step to physically force a large portion of the oils out of the feedstock, a

mechanical press is employed. These electrically driven devices are limited to pressing out

between half and three quarters of the contained oil. By heating the feedstock up to 60 - 70°C (using low pressure steam) the viscosity is lowered increasing the pressing efficiency at a lower

electric demand, but is still limited to 80% maximum yield for the seed-based type feedstocks

while fruits-based types can already achieve 96%46. To maximize the oil yields solvents are used

to extract residual traces of oils and accelerate the entire process. Many types of solvents have

been experimented and tested upon, but none have proved as affective as hexane. Besides, the

main motivation of searching for a suitable substitute for hexane (avoiding toxic levels in the

press cake which are strictly regulated for fodder application) is not of relevance within the

strictly non-food biorefinery. With a large flow of 1.2 – 2.5kg hexane per kg feedstock, 95.4% oil

can be recovered47. At such large material demands recovery methods have been developed and

near perfected to achieve 99.8% recovery for recycling. The hexane in the oil stream is recovered

via a flash column while the hexane in the press cake is sent to a desolventizer to be removed;


using high pressure steam and spread over a large surface area the hexane is boiled off and

collected. Overall a best practice installation requires only 1.0kg fresh hexane solvent per ton

recovered oil. The whole system can be described as a steam heated mechanical presser with

integrated solvent extraction. There are four major types of units available; rotary or deep-bed,

horizontal belt, continuous loop extractors and some miscellaneous like a screw presses. They all

work on the counter-current principle with the extracted oil sent to the next stage of processing.

Press cake will be treated as processing residues and subjected to carbohydrate processing

(Section 3.2) and since is does not need to be dried and prepare as an animal feed a noticeable

portion of process energy will be mitigated.

Transesterification

The general term for hydrolysis with an alcohol is alcoholysis where by in the special case of using

vegetable oils it is known as transesterification. Reacting the triglycerides with an alcohol will split

the molecule apart into free fatty acid esters and a glycerol molecule. The reaction can use any

assortment of alcohols but will result in the formation of functional ester branches at the length

of the alcohol molecule. Methanol will form fatty acid methyl ester; ethanol becomes fatty acid

ethyl ester; propanol, fatty acid propyl ester; butanol, butyl ester; and so forth. At some point the

chain length becomes an obstruction; the most common alcohol currently applied in the industry

is the single carbon methanol derived from natural gas. It is economical cheap but does come at a

high cumulative energy demand as will be highlighted in the next section. The following general

formula depicts the overall reaction with the stoichiometric demand:

Triglyceride + 3Methanol � 3 Fatty Acids Methyl Esters (FAME) + Glycerol C54H104O9 + 3CH3OH � 3C18H32O2 + C3H5(OH)3

1⋅930.27g/mol (930.3) + 3⋅32.04g/mol (96.1) � 3⋅279.39g/mol (934.3) + 1⋅92.09g/mol (92.1)

Stoichiometric Ratio (Methanol Demand): 96.1 ÷ 934.3 = 0.103g/g

Each fatty acid-rich feedstock has a different fatty acid composition which will result in a

different molecular weight of its triglycerides, however differences are only apparent between the

previously mentioned separation between seed-based and fruit-based feedstocks. The following

lists the feedstock based molecular weight and methanol demand:

Table 15 Vegetable Oil Molecular Weight for Methanol (g/mol)

Feedstock Triglyceride Free Fatty Acid FAME Methanol Demand

Seed-based 930.27 279.39 934.3 0.103kg/kg

Fruits based 901.50 269.80 905.5 0.106kg/kg

As a general rule of thumb 10wt% methanol is taken for quick studies and scans; carrying out this

extra calculation step slightly increases the accuracy of the minimum methanol demand for the

feedstock types. In practice the reactive alcohol (methanol) is added in excess, usually at twice the

stoichiometric requirements, to ensure a complete reaction conversion. Transesterification

conversion rates of 98% are systematically achieved48. Over 99.99% of the excess solvent is


recovered and recycled according the purification steps (next sub-section). Commercial facilities

use the well-established alkali-catalysts refining step to catalyze the reaction. And although many

alkali catalyst exist, Na(CH3O) (sodium methoxide), is almost exclusively used at 5mol% compared

to the ester product.

Purification and Recovery

To prepare for the transesterification reaction step a purification process called degumming is

required because some of the fatty acids in plant matter are not bonded as a triglyceride molecule

but are present as free fatty acids which negatively influence the reaction; they and other non-

triglyceride molecules must be removed. Free fatty acids and the so-called “unsaponifiable” matter

contribute to an additional overall yield loss of 4.0%47. A 9.5wt% caustic (NaOH) solution is used

to flush out and separate the molecules by their intrinsic behaviour to foam into soap. Resulting

lime demand is 7.5kg per ton product. The methyl ester product is sent to a cascade of hot water

washes columns (70°C) to strip the water-soluble components (glycerol, methanol, etc.) out. The methyl ester product is then vacuum dried to remove any residual water that entered the aqueous

phase and purified to 98.9%. None of the ester products entered the water wash phase. This

stream is sent to a simple series of evaporator tanks and distillation columns to recovery the

glycerine using thermal steam energy.

4.2.2 Recent Processing Improvements

Pressing and Extracting

Within the pressing and extraction steps little improvements are foreseen aside from general

energy efficiency increases through better steam utilization, production and integration. Minor

decrease in steam usage are already noticed between contemporary European facilities to

conventional American ones. This provides a trend indication for newer plant design49, 50.

Information pertaining to palm oil processing plants are limited and noted as being considerably

inefficient51. Modern steam production and integration options can easily reduce the process

energy intensity by the half or not more.

Transesterification and Recovery

As mentioned earlier any alcohol can be used for the alcoholysis (transesterification) step. It was

also mentioned in Section 3.2.1.2 that oil press cakes will be included as “processing residues” for

ethylene production from complex carbohydrates. A portion of the ethanol could be used as the

transesterification reactant before being converted into ethylene within the biorefinery system.

Fatty acid ethyl ester (FAEE) would be produced in place of fatty acid methyl ester (FAME).

FAEE has slightly different physical and chemical properties, but when applied for the

formulation of biolubricants presents minor, if not negligible, constraints. While in this

biorefinery system the fossil fuel derived methanol is avoided, the calculated stoichiometric ratio

however indicates that more ethanol required. And as with methanol a distinction is made

between the two feedstock types. Following the overall reaction equation for FAEE production

from ethanol the minimum ethanol can be calculated. Presented in the following table are the

corresponding difference in molecular weight of the products.


Triglyceride + 3Ethanol � 3 Fatty Acids Ethyl Esters (FAEE) + Glycerol C54H104O9 + 3C2H5OH � 3C19H34O2 + C3H5(OH)3

1⋅930.27g/mol (930.3) + 3⋅46.07g/mol (138.2) � 3⋅325.46g/mol (976.4) + 1⋅92.09g/mol (92.1)

Stoichiometric Ratio (Ethanol Demand): 138.2 ÷ 976.4 = 0.142g/g

Table 16 Vegetable Oil Molecular Weight for Ethanol (g/mol)

Feedstock Triglyceride Free Fatty Acid FAEE Ethanol Demand

Seed-based 930.27 279.39 976.4 0.142kg/kg

Fruits based 901.50 269.80 947.6 0.146kg/kg

Nearly 40% more ethanol is required than methanol to produce the fatty acids ester products. A

recent biotechnological advancement has allowed enzymes to be used in the degumming

preparation step, effectively eliminating the caustic treatment3. Further studies suggest that this

and other lipase enzymes could also be applied to replace the alkali catalyst in the

transesterification step48. There are several key benefits of enzymatic-catalysis, which all relate to

an increased energy efficiency; the reaction temperature is lowered from 80°C to 35°C, the product yields are marginally increased from 98.0% to 98.5%, the recovery of glycerol is possible

without thermal units, and the water-wash product purification step can be completely removed.

In the early days of biodiesel production, glycerol was considered an economically viable by-

product. Due to the production boom (especially in Europe) in recent years it is now treated as a

waste by-product with ever-increasing disposal costs. In 2007, BioMethanol Chemie Holdings

announced their renovation plans to convert the feedstock of an existing methanol chemical

plant from natural gas to glycerol through an undisclosed gasification process. The great

abundance of glycerol has promoted many other investigations into fermentation products in

order to recreate an economic viability of the by-product50. Producing methanol from glycerol

may not be the most logical product, despite the recycling options, as it makes no use of the

highly reduce nature of the C3-carbon structure. In any case, this biorefinery system sees ethanol

fully replacing the need for methanol as a transesterification agent. Particularly in anaerobic

fermentation metabolism glycerol is of special interest and is a viable feedstock for the

production of 1,3-propanedoil (PDO). While PDO is being hyped as a potential fermentation

product from glucose, maintaining the C3-carbon structural integrity results in higher conversion

rates52. Initial studies have found that with 16.2mM glycerol, 11.2mM PDO can be harnessed

leading to a mass yield of 57wt%. The fermentation conditions were held at 58°C, 6.0-6.5pH for at least 8hours at 10wt% solids loading.

4.3 Energy Input

Both the “standard” and “recent” improvement process energy and exergy input for the fatty

acids to biolubricant production route have been handled. Table 17 lists the resulting direct and

indirect energy as well as the relevant conditions. At the moment there are over 450 different

lubricants on the market with specific compositional formulations for the specific applications.


Biomass derived fatty acid esters offer many replacement opportunities with, in some cases, a

number of performance advantages. Projected biolubricant consists of base fatty acid esters

(usually 75 – 90%) and a fossil based additive package designed to achieve the desired properties.

Hydrogenation and other chemical processes are also proposed to increase the oxidative stability

of fatty acid esters, but are not a necessity. As a simplification, the fatty acid esters will be used at

a 75% formulation mixture with additives. The seed-based standard process is based on a series

of rapeseed and soybean production processes with the lowest energy insensitive figures for each

step chosen to be representative for a new installation. Steam is the primary direct energy source

in all processing steps which can be seen by the large energy and exergy difference. However, in

the standard transesterification process, the fossil-based reactant methanol is the most energy and

exergy intensive component. Using ethanol from the downstream biorefinery streams instead of

methanol from natural gas corresponds to a major reduction in energy intensity. Press cake

derived ethanol costs 9.07GJ/ton and 5.65GJ/ton direct process energy and exergy to produce,

respectively. Although the lipase enzyme requires 105GJ/ton and 173GJ/ton indirect energy and

exergy and ample amounts of citric acid as a growth medium, those extra induced costs are

considerably lower than the mitigated thermal (steam) costs. The large electric consumption in

the transesterification step of the recent improvement process is caused primarily caused by

glycerol fermentation.

Table 17 Fatty Acid Processing Energy/Exergy Input – Standard and Recent Process

Category Unit Standard Process Recent Improvement Process*

Crop Seed-based Fruit-based Seed-based Fruit-based

Pressing & Extracting Conditions Temperature °C 60 70 60 60

Oil Yield (pressing) ton/ton 0.954 0.960 0.954 0.960 Oil Yield (degumming) ton/ton 0.96 0.96 1.00 1.00 Direct Energy (Exergy) Electric GJ/ton esters 0.175 0.364 0.175 0.364 Thermal GJ/ton esters 2.20 (0.22) 8.10 (0.80) 2.18 (0.22) 1.17 (0.40) Indirect Energy (Exergy) Solvent GJ/ton esters 0.059 (0.056) 0.0 0.059 (0.056) 0.0 Transesterification & Recovery Conditions Temperature °C 80 80 35 35

Oil Yield ton/ton 0.980 0.980 0.985 0.985 Direct Energy (Exergy) Electric GJ/ton esters 0.001 0.001 0.251 0.251 Thermal GJ/ton esters 1.21 (0.12) 1.24 (0.12) 0.15 (0.01) 0.16 (0.02) Indirect Energy (Exergy) Reactant GJ/ton esters 3.73 (3.92) 3.84 (4.03) 1.29 (0.80) 1.32 (0.82) Catalysts/Others GJ/ton esters 0.34 (0.33) 0.35 (0.33) 0.85 (1.04) 0.85 (1.04)

*Also produces PDO: 53.9kg/ton for seed-based, 55.5kg/ton for fruit-based

The (electric) energy and exergy demand to emulsify the fatty acid esters with the necessary

additives for the lubricant formulation are negligible and can be disregarded. Considering the

global interest in biofuels, like biodiesel, and the fact that unformulated biolubricants follow the


same production route, presenting the overall process energy input is worthwhile. Just as with the

biofuel ethanol section a graph is used to show the direct process energy (thermal and electric)

and indirect process energy (chemicals, microbes, etc.) in combination.

Figure 5 1st Generation Biodiesel – Overall Process Energy Input

Biolub ricant (o r Biodiesel) Production

0.0

2.5

5.0

7.5

10.0

12.5

15.0

Seed-based Fruit-Based Seed-based Fruit-Based

Standard Recent Improvements

GJ/ton Biolubricant

I ndirect Chemical Ene rgy

Direct Electric Ene rgy

Direct Thermal Energy

Table 18 1st Generation Biodiesel Production Costs

Category Standard Process Recent Improvement Process*

Crop Seed-based Fruit-based Seed-based Fruit-based Overall Conversion (ton esters/ton fatty acids)

0.898 0.903 0.940 0.946

Total Energy (GJ/ton) 7.71 13.89 4.95 7.00 Total Exergy (GJ/ton) 4.82 5.66 2.97 3.67

*Also produces PDO: 53.9kg/ton for seed-based, 55.5kg/ton for fruit-based

Rather unexpectedly the fruit-based feedstocks, which contain a higher concentration of

triglycerides, require more energy to convert into fatty acid esters over the seed-based feedstocks.

The exergetic difference is much less however because the fruit-based feedstocks are heavily

influenced by inefficient thermal energy. A noticeable process energy reduction is attainable by

using the recent improvement process, to the point that the fruit-based crops have a lower energy

consumption then the standard seed-based process. The overall conversion yields are comparable

for both feedstock types with 89.8 – 90.3% reached for the standard process and increased to

94.0 – 94.6% for the recent selection.



5 Proteins

5.1 Description

Of all the various biomolecules forming plant matter, proteins may

not be present in the highest concentration, but as the Greek origin

word προτα “prota” denounces, they are of primary importance. Proteins perform a large multitude of tasks and functions in biological

life. They are responsible for carrying out the duties specified by gene

encoded information and even form a large portion of the genetic

material itself (RNA, DNA, etc.). In response to the duty assignments,

proteins can be enzymes catalyzing metabolism and catabolism or can act as the main molecules

regulating signalling and ligand (see Ash, Section 7) transportation. Proteins also govern the

physical forces needed for movement in cells (e.g. sunflowers aligning their heads towards the

sun) and can be used as secondary sources of energy. Legumes in particular store proteins instead

of starch for seed germination energy as they exchange simple carbohydrates for nitrates and

nitrates (ligands) with the inoculated symbiotic nitrogen fixating bacteria. Proteins comprise of

any possible combination of the 20 amino acids and can form quite large and complex structures.

Peptide bonds between the carboxyl and amine (nitrogen containing) group of the amino acids

hold the structure together, which are often referred to biochemically as a

polypeptides. In biochemistry, the general formula for amino acids is

C3H6O2N with a molecular weight of 88.09g/mol; direct to the adjacent

image for the general structure. The protein content of plant matter is

determined by analysing the nitrogen content and multiplying by the

conversional factor 6.25, but actually relates to the amino acid building blocks. Thus amino acids

and their derived proteins are always associated with a nitrogen component.

Existing applications of plant-based proteins hardly make use of the energy intensive nitrogen

functionalization. Even the recently constructed biorefinery systems are limited using the protein-

rich by-products as a source of combustion energy or moderately processed to be suitable as

animal feed. The latter option of using biomass derived protein-rich streams for animal feed

industry applications will be handled in detail to properly allocate the marginal fossil fuel

reduction potential. While the current animal feed industry is profitable enough to industrially

produce certain free amino acids (from both renewable and non-renewable sources) as additives

on a large scale; those production routes for amino acids are energetically intensive. In the early

developmental phases of a full chemical biorefinery, the initial goal should be the extraction,

isolation and any needed purification to yield those amino acids of particular interest for the

animal feed sector. Utilizing the biomass-derived proteins for amine chemical production is still

in its paper hypothesis and initial laboratory experimental phases without a single production

route ready for series industrial consideration. Yet, the first process steps involve protein

separation and purification from the protein-rich by-products to form free amino acids are

somewhat closer. Only with continued research and development into the biotechnological


processing steps within the field of amine chemistry can the nitrogen functionalization be fully

utilized for chemical production. Here no distinction is made between the biomass feedstock

types as all the protein-rich streams originate after the carbohydrate conversion step of the

proposed biorefinery. Each amino acid will be studied for an exemplary functionalized chemical

production route, one with a high existing production volume and associated process energy cost.

As the process routes are hypothesized, the necessary process energy will be determined by

comparison to general processing equipment operated at foreseen conditions. Envisioned

advances in amine chemistry and biotechnology will facilitate the production of many existing

petrochemicals at relatively low process energy intensities without comprising the nitrogen

functionality structure of the amino acids. Finally, this section will exemplify the grand energy

savings potential of using proteins as a feedstock for chemical production within the biorefinery

concept; possibly making protein chemistry, “prota”: of primary importance.

5.2 Processing

5.2.1 Animal feed issue

5.2.1.1 General Situation

Meat production is big global business consuming tremendous quantities of feeding stuffs for

raising livestock. The EU25 alone consumes in excess of 450Mton annually; while most of the

animal fodder originates from farm grown roughages, 142.1Mton of compound feed was

industrially prepared in the EU and an additional 42.5Mton was imported53. It is broken down

into 4 major categories; pigs (swine), poultry (broiler), cattle (beef) and others, with the three

main livestock’s (swine, broiler, beef) all being fairly equally distributed at about a third. The

desired end product is meat with animal fodder serving as an energetic and nutritional input. One

of the industry’s key criteria for efficient production of meat is expressed by the feed to weight

gain ratio, F:G (kg/kg). This ratio is dependent on several factors from animal type, breed, sex,

fodder type, preparation, additives, to the seasonal climate conditions. In the 1980’s, a large cattle

range with locally grown roughages had required a total of 33kg feed per kg beef54. Supplying the

animals with a good-quality pasture (i.e. high digestibility, high protein content) reduces the F:G

ratio by half. Today, by utilizing better compound feeds the modern beef production industry has

significantly lowered the ratio to 7.8kg/kg. Preliminarily testing on genetically improved feed

propagation has further lowered the feed to weight gain ratio to 6.6kg/kg, a full 5-fold lower then

the open system55. Any preachy moral arguments on biological meat production must take into

account this huge boost in land use efficiency. Beef in particular has the largest F:G ratio while

the other two major livestock classifications require considerably less feed. Pork production

ranges from 2.6 – 3.5kg/kg and broiler production ranges from 1.0 – 1.5kg/kg54. In terms of

total feed energy input in relation to the meat energy content the following was found55: beef

40:1; swine 14:1; broiler 4:1. A common method to increase the weight gain ratio (and lower the

energy relation) is to artificially produce and blend in the limiting amino acids. Ruminant animals,

like cattle and sheep, do not have such limitations while the other livestock animals types do. So


despite its gluttonous nature, pork meat production is heavily limited by certain key amino acids,

frequently referred to as the ileal amino acids. To yield the optimal growth rates for swine,

industrial blending of ileal amino acids is in the order of 1.0 lysine, 0.6 methionine + cystine, 0.65

tryptophan, and 0.19 tyrosine. Isoleucine, leucine, valine and phenylalanine are sometimes also

added, but in considerably lower proportions. By far the most limiting amino acid is lysine which

is frequently added at a minimum level of 6.0g/kg pork feed. The same addition of amino acids is

present for all industrially prepared compound feeds, save for the actual blending ratio.

5.2.1.2 Fossil Fuel Mitigation

Animal feed is a tricky co-product in terms of proper allocation within life cycle assessments and

due to this difficulty it has become common to leave it out all together or merely resort to the

energy content56, 57. This is not the proper method when conducting a comparative cradle-to-

factory gate analysis for a biorefinery’s protein-rich by-products because when used as an animal

feed they substitute (or mitigate) the need of producing dedicated animal feeds. A study has

published detailed information regarding the fossil fuel input to produce various animal feeds58.

In general forage animal feeds cost 1 – 3GJ/ton and “concentrated” (compound) feeds cost 6 –

14MJ/kg. Two notable compound feeds are corn gluten meal at 6.1GJ/ton with a protein

content of 47% and soymeal at 6.8GJ/ton with a protein content of 45%. At this stage in the

biorefinery the residue streams could be able to partially replace these two animal feeds.

“Partially” because the most important attribute within the feed industry are the digestion values

coupled with the protein concentration. Therefore, the feed replacement potential must be based

on the protein content relation. Here the protein concentration is very feedstock dependent, and

while only few can match a protein content as high as 45% most of the selected feedstocks result

in a residue stream containing less than 30%. Thus in most cases, the gross feed replacement

potential results in less than 4.0GJ/ton. The net is even lower as extra process energy is required

for drying and fodder preparation. These values are actually several magnitudes below the

mistakenly allocated grass calorific value. Meaning that even bioenergy propagation at low

combustion efficiency yields a higher fossil fuel mitigation potential, therefore animal fodder

production is an inferior option compared to burning. The industrially prepared and blended

amino acid additives can, however, present a promising first step. Take the example of lysine via

fermentative production routes:

Table 19 Cumulative Process Energy for Lysine (GJ/ton)

System Classical System Improved System

Input Type Quantity Energy Cost* CED Quantity Energy Cost* CED

Molasses 5.3 ton 8.3 44.1 2.7 ton 8.3 22.0 Steep Liquor 0.413 ton 34.6 14.3 0.413 ton 3.5 1.4 Ammonia 0.152 ton 34.5 5.2 0.152 ton 34.5 5.2 Sulphuric Acid 0.182 ton 2.3 0.4 0.182 ton 2.3 0.4 Electricity 4.7 MWh 45% conversion 37.3 2.7 MWh 45% conversion 21.7 Steam (Medium) 4.34 ton 85% conversion 17.7 2.53 ton 85% conversion 10.3

*Based on internal calculations, See accompanying database spreadsheets for more details and exergy calculations


The total cumulative process energy is 119.0GJ/ton for the classical system and can be lowered

to 61.2GJ/ton following the proposed improvements59, 60. Similar situations are present for the

other synthesized ileal amino acids which clearly shows a higher fossil fuel mitigation potential

over compound animal fodder. Preparing separate amino acid streams from the biorefinery

protein-rich by-products will follow the same initial processing steps as suggested for the

chemical production; solubilization, separation, isolation and purification. For the essential amino

acids (lysine, methionine, cystine, tryptophan, tyrosine, isoleucine, leucine, valine and

phenylalanine) isolation is a very reasonable first step in producing chemicals. Although they are

not non-food products, they are feasible during the introduction phase. Besides, when destined

as animal feed additives they could be marketed as a mixture, possibly saving in isolation costs.

5.2.2 Solubilization

After the last beer column, which separates the ethanol produced from the fermentation broth

mixture of simple and complex carbohydrates, the bottom stream will act as a protein-rich source

from many of the investigated biomass feedstocks. A considerable portion of the proteins have

already been denatured, destroyed or cleaved into smaller peptides and introduced into the

soluble fraction. Others tend to oligomerize into densely packed fibre-like molecules when

exposed to the high temperatures along the various biorefinery processing steps. The induced

state of the protein structures is not of any particular importance within a biorefinery while the

efficiency and effective ability to separate and isolate their amino acids building blocks is.

Solubilizing the proteins and derived peptides found in the beer column bottom stream is the

first step of many required to form purified amino acids streams. Here the molecular structure of

the proteins and peptides directly effect the solubilization performance. There are two major

types of techniques used and investigated for solubilizing proteins; chemical extraction and

enzymatic cleavage. Both methods will be described and assessed, however enzymatic cleavage is

vastly more promising within the biorefinery concept and will serve as the primary solubilization

technique. As a substantial proportion of the other chemical components in the bottoms stream

are also present in their soluble state, further downstream isolation and purification steps are

required to properly prepare the amino acids. Solubilization is thus the first purification step to

separate proteins and its derived peptides from insoluble and solid material. At this stage in the

biorefinery no distinction is made between the feedstocks, although the absolute concentration

of the proteins contained in the stream (feedstock) will directly effect the process energy.

5.2.2.1 Chemical Extraction

In practically all industrial preparations of proteins from impure sources the first step of

purification is a chemical extraction or some cases a precipitation step. A wide assortment of

alkalis, acids and salts are applied to bring the proteins into solution; in affect a hydrolysis

procedure. The effectiveness is extraordinarily high nearly reaching full separation. However,

these techniques have the structural integrity of the proteins in mind and might not work as well

with dirty biorefinery streams. In addition, a large quantity of extraction chemicals sometimes as

high as 1 to 1 are also required which when coupled with the downstream neutralizing steps place


an inordinately high indirect process energy cost. An option to overcome these high chemical

production costs is to either lower the required concentration, employ recycling options or better

yet integrate it with chemicals required or produced along any of the other biorefinery processing

steps. Ethanol, ammonia and lime were personally tested on AFEX pretreated (Section 3.1.1.2)

processing residues from a cereal-type simple carbohydrate (Section 3.1.1.2) feedstock as

chemical extraction solvents. Even at elevated temperatures (>80°C) and high solvent concentrations (>50wt%) less than 25% of the total insoluble proteins were brought into solution.

Another option is to use strong organic acids to fully hydrolysis the proteins by chemically

cleaving them into soluble fragmented peptides. Sulphuric acid, which is the desired pretreatment

procedure for recalcitrant materials, can indeed solubilize large quantity of the proteins by

cleaving them into small peptides. However, cleavage into the soluble phase will already occur

within the foreseen pretreatment step, meaning additional post-treatment will hardly promote

additional cleavage and even so would entail extra chemical separation costs. This briefly implies

that using biorefinery chemicals to solubilize the proteins and derivatives is not a feasible option.

5.2.2.2 Protease

Proteolytic enzymes, marketed as protease61, are naturally occurring enzymes

in fungal bacteria that are capable of protein cleavage (degrading

polypeptides) at moderately lower temperatures and concentrations. In

the food and industrial enzyme industry much knowledge has been

accumulated regarding technical applications of proteases. That core

know-how can be transferred to the initial protein separation step

within the biorefinery concept. Preliminary protease digestion experiments have been performed

on several process residue feedstocks as a proof of concept26, 62. Initial solubilization rates are

moderate at 51.7% for corn wet distillers grains and 41.5% for wheat stillage. As those

experiments were an introduction to the novel concept of protease digestion to solubilize

proteins from biorefinery side-streams, the results are clearly sub-optimal. An optimal operation

temperature of 50°C has, however, been determined which is lower than the manufacturers 72°C guidelines for industrial food applications. Heat generally affects protein solubility, but excessive

temperatures also tend to deactivate the enzymes. Many more improvement options are

foreseeable with continued research, investigation and development into the system dynamics. A

plausible (yet untested) improvement is to create a specified proteases cocktail, as was

successfully developed for saccharification processing. It appears that of the cleaved peptides

most are below the protein spectrum detection range of 6kDa. Free amino acids have an average

molecular diameter of 0.15kDa suggesting that many of the proteins could have been reduced to

their amino acid building block. Using a protease cocktail should not only increase the overall

solubility but under the right conditions fully cleave all the peptides down to their compositional

amino acids. Furthermore, it appears from the experiments that the enzyme activity decreases

with time meaning a feed-batch system could increase the solubilization rate. It can be expected

that with further investigation and conditioning of the parameters a near complete digestion is


foreseeable; 95% is assumed for future cases and 60% is taken as current cases. In both cases a

complete conversion to amino acids is taken to facilitate the proceeding separation steps.

5.2.3 Isolation and Purification

Isolating and purifying amino acids after the protein digestion separation step involves a wide

multitude of biotechnological and biochemical technologies; in short bioseparation technology.

Yet, not a single bioseparation technology or processing scheme is currently available to handle a

mixture of amino acids. In fact, most of the purification technologies that will be discussed and

chosen for the now amino acid-rich stream have been designed for waste water treatment,

specialty chemicals or the food market. Desalination procedures, for instance, are common

within the food industry to recover proteins because frequently the solution is not in the optimal

state for consequent processing caused by the wrong buffer,

too much salt, too many impurities, or simply too dilute.

These negative process attributes are analogous with the

amino acid-rich streams. The closest processing route that

can act as a guideline is enzyme preparation from a

fermentation broth; i.e. lysine production. The adjacent

illustration is an overview of the isolation processing steps

generally involved in enzyme preparation63. It is optimized to

remove salts and metallic ions (desalination) and other

biomass broth impurities (proteins), leaving an enzyme rich

stream. Amino acid isolation and purification steps will

adhere to similar a processing scheme, but can in many cases

be left in solution as governed by the downstream chemical

synthesis. Many separation technologies exist which utilize the interaction mechanisms held by

the various physiochemical properties of the amino acids. They have five distinct physiochemical

properties which might help facilitate affective isolation and purification: (1) molecular size

(weight), (2) hydropathy index (hydrophobic & hydrophilic nature), (3) isoelectric point (charge),

(4) acidity and basicity (pH) and (5) polarity. Depicted in Figure 6 is a personally proposed overall

processing scheme to isolate each of the 20 amino acids into purified streams. It is a multistep

procedure playing on the individual physiochemical properties of the amino acids. The final

industrial layout within a biorefinery can deviate significantly from this isolation and purification

proposal, but will nevertheless encapsulate a multistep procedure. It is a current knowledge gap

in the whole biorefinery concept that needs to be closed. On large industrial scales these

individual isolation and purification technologies are selected solely by economic considerations

and not by energetic issues. And seeing that the associated financial costs for membrane

production continues to place the highest proportional cost factor on the membrane-based

technologies, the energy intense process costs are greatly offset meaning hardly any development

has gone into process energy reduction. Furthermore, several of the technologies are confined to

the laboratory analysis scale due to the current process economics. Nonetheless, each of the

technologies will be described in detail with the process condition brought into relation with the


operation energy costs. There will be a vast difference in the resulting process energy demand

between the various feedstocks because the operation conditions and energy intensity are based

on permeate product flow rate, meaning the amino acid concentration is all determining. At this

stage in calculations, however, the process operations will be expressed in product flow rate (m³)

and simplified to (ton) by setting the average density at 1ton/m³ as the stream is primarily

composed of water. A representative amino acid concentration of 6.5wt% will be selected prior to

being expanded into the exact feedstock related calculation matrix of Chapter 8. Furthermore,

the exact amino acid weight proportions will also determine the overall individual isolation

values. Again, later in Chapter 8 the exact feedstock composition will be included, while here a

representative simplification of equal amino acid mass distribution is made for presentation

purposes.

5.2.3.1 Nanofiltration (NF)

Nanofiltration is a pressure driven filtration process to separate finer particle

sizes from an aqueous solution. A selective separation layer is formed by an

organic semi-permeable membrane with the pressure difference between the

feed stream (retentate) and the filtrate (permeate) providing the driving force.

Systems are approaching technological maturity and are ready for full-scale

industrial applications. Industrial configurations are typically in the compact

multi-tube cylinder form (see picture). In the biorefinery system nanofiltration

will be used as the first stage in amino acid purification to remove the large soluble particles.

Here the membrane permeation size is set at 1kDa; large enough to allow most molecules to pass

through including salts and unconverted sugars but small enough to block delignified products

and any residual peptides. In many biochemical processing applications the impurities contained

in the retentate are regarded as waster water with disposal provisions64. Here these large soluble

lignin products will join the insoluble solid residue (primarily lignin) and combined will form a

dilute but nearly pure lignin feedstock (Section 6).

5.2.3.2 Electrodialysis (ED)

Electrodialysis is an electrochemical separation process in which

ion exchange membranes are used to remove ions (charged

molecules) from organic solutions65. It can be configured to

produce three separate product streams; positively charged,

negatively charged and the demineralised neutral streams. The

feed stream is passed through a channel with a pair of electrically

charged bipolar membranes and a centre transfer membrane. A slight temperature increase to

40°C and an overpressure of 0.25bar are needed to promote a good separation. Salts in solutions will act as ions and are attracted to either the cathode or anode. Amino acids also have a

isoelectric point (or charge) and will be separately into one of the three streams. Most are

relatively neutral with an isoelectric range of 5.5 – 7.5 and remain in the demineralised product

stream. Positive (or acidic) amino acids have an isoelectric point below 5.5, while negative (or


basic) amino acids have an isoelectric point above 7.5. ED is a fast and effective process for this

stage of separation. Little investigation have been made on the energy consumption of the

desalination of amino acid containing streams, but some studies will act as guides to the energy

costs66. At moderately high concentrations, starting at above 10wt%, proton leakage is promoted.

Current experiments are typically kept at much lower concentrations67.

5.2.3.3 Chromatography

Chromatography is the separation process based on using differing component affinities within a

mobile phase when passed through a stationary phase fixed in a column. The chromatographic

separation can occur via various interaction mechanisms, including size exclusion

chromatography (SEC), ion exclusion chromatography (IEC), and reverse phase adsorption

chromatography (ADS). Irrespective of the particular mechanism, the engineering basics of the

process are the same, products will be eluted at differing rates thus separating them. This limits

chromatography to be a slow batch process. Much detailed information is written about

chromatographic separation as analytical measurement techniques but very little is known in

regards to its manufacturing process applications. The slow rate of separation, batch process

nature and relatively high economic and energetic operation costs are preventing the wide-scale

implementations. The sugar industry does use ion exclusion chromatography to separate and

purify particular sugars from each other. In addition, this process is used in purifying single

amino acids and various organic acids streams as well as to separate salt from glycerol. Each type

of chromatography that could potentially use the physiochemical properties of amino acids for

separation will be handled individually with a brief explanation to their operation kinetics.

Size Exclusion Chromatography (SEC)

As the name suggests size exclusion chromatography separates

molecules according to their size; or more accurately according to

their hydrodynamic diameter or hydrodynamic volume. In practice,

the molecular weight provides enough insight into the differing

molecular sizes of the amino acids. When an aqueous solution (as is

the case with amino acid-rich streams) acts as the mobile phase, the

technique is known as gel permeation chromatography (GPC). As the image

depicts, smaller molecules are able to enter the pores of the stationary phase and; therefore, take

longer to elute than the larger molecules which pass through the column unretarded. A wide

multitude of inert porous materials with varying pore sizes are employed with plastic beads like

cross-linked polystyrene being rather common. GPC is generally regarded as a low resolution

technique and is often reserved for the final purification step, dubbed “product polishing”.

Frequently, product polishing is used on a single product, but within the amino acid isolation and

purification scheme a arbitrary maximum of four simultaneous amino acid products can be

produced. It is here also assumed that as long as the molecular mass differ by at least 10% a

separation is possible. Due to the previously mentioned fact that amino acid isolation and

purification remain a knowledge gap within the biorefinery concept, the validity of these

statements are unknown. In analytical applications of chromatography high pressures above


15bar are applied to force a uniform solvent flow, in industrial applications the pressure can be

lowered to around 3.5bar. While in both applications, the organic solutions need to be heated to

80 - 85°C. Resulting that thermal energy for heating contributes to the largest proportion of the overall process energy, unlike electrodialysis being 78% electricity.

Ion Exchange Chromatography (IEC)

Technically called an “anion exchange gradient elution column”, the ion exchange

chromatography column is the most widely used industrial chromatographic

separation process. IEC is a rather interesting application because the

negatively charged stationary solid phase is not actually performing ion

exchange. The resin serves as a media separating based on the differing

amphoteric characteristics of the mobile phase, the pH in other words. As the

image depicts, positively charged (acidic) molecules are attracted to the negatively charged beads

of the stationary phase and; therefore, take longer to elute than the negatively (basic) and less

positive to neutral molecules which pass through the column relatively unretarded. A wide

multitude of inert resin materials are being studied and marketed with several major industrial

corporations enter the market. Corresponding to this trend is the ever increasing reliance of ion

exchange columns for enzyme and other protein purification steps. Unlike electrodialysis which

separates the streams into positive, negative, and neutral, IEC uses the isoelectric affinity of

amino acids to separate the molecules based on their relative charge. The process conditions and

thus energy demands are analogous to SEC.

Reverse-Phase Adsorption Chromatography (ADS)

ADS has a few name deviations from dry flash chromatography to

expanded bed adsorption (EBA), but all work on the adsorption

principle68, 69. And although it represent one of the most

promising recent developments in biomolecule separation

technologies, only a handful of applications have been studied.

Reverse-phase adsorption chromatography also functions

slightly differently then the other column-based chromatography procedures, for it is a three step

procedure and requires significantly less process energy. It works on the molecular polarity

adsorption affinity difference. Polarity refers to the dipole-dipole intermolecular forces between

the slightly positively-charged end of one molecule to the negative end of another or the same

molecule. Nonpolar molecules have a high affinity and are adsorbed into the packed bed

(stationary phase) adsorbent while the polar molecules having a low affinity are left in solution.

The separation into the two streams, polar and nonpolar as the image depicts, is a three step

process; (1) loading the adsorbent with the nonpolar molecules, (2) washing the polar molecules

away, and (3) eluting the nonpolar molecules by desorbing them with a solvent. Methanol is an

effective solvent with 25 – 50wt% required to fully elute the nonpolar molecules. An additional

standard evaporation step is needed (like in Section 4.2.1) to remove and recycle the solvent. A

conservative 50wt% will be chosen. The ADS separation operates at room temperature negating

any thermal energy in the column and with an overpressure of 1.25bar reduces electric demand.


5.2.3.4 Reverse Osmosis (RO)

Reverse osmosis is best known for the desalination and

purification of water, RO-Water. At this stage along the amino

acid isolation and purification scheme (Figure 6) the solution does

not contain any salts as they were removed earlier. The polar

amino acids do however possess a physiochemical difference that

could facilitate reverse osmosis; a hydrophobic and hydrophilic difference. Under pressures

between 2 – 15bar the hydrophilic amino acids would be forced through the semi-permeable

membrane while the hydrophobic amino acids, acting like salts, would remain. This in effect

further separates the amino acids into two distinct streams. The operation conditions and design

configuration mirrors the nanofiltration unit. In fact, RO is sometime referred to as ultrafiltration

when purifying exceedingly dirty water streams.

5.2.3.5 Others

As research and development shifts towards closing the knowledge gap of amino acid isolation

and purification many new and potentially radical ideas could emerge. Precipitation in itself is one

such example that when studied from a different angle could prove beneficial. Traditionally salts

or chemicals are added to bond to the side-chain groups of protein changing pH or promoting

crystallization. An additional neutralizing chemical step is required involving other separation

procedures. Using enzymes could operate in a similar way, clinging to the various amino acid

chemical structures thereby changing the physiochemical properties. The interaction mechanisms

of the amino acids could be shifted potential promoting more efficient separation from the above

described technologies. Another option with few current applications is lyophilisation or freeze

drying. At high solid loadings the amino acids would all have different freezing points (natural

crystal forming) calling for standard solid/liquid separation techniques. Cryogenics essentially

under vacuum conditions, however, are incredibly energy intense. On the other scale of

temperature manipulations thermal parameter pumping within an ion-exchange resin seems

promising70. It could take advantage of process waste heat as the driving force of separation

significantly lowering the electric demand. It uses dissociation reaction constants to govern the

movement of amino acid towards high or low temperature reservoirs. Current studies are

restricted two amino acid with limited success. Nonetheless, the idea of using amino acids as

building block for the chemical industry is slowly being acknowledged by the academic world

with efforts dedicated towards assessing the current knowledge gap71. In any case the separating,

purifying and isolating amino acids from a biomass based stream will typically entail cascading

multistep procedures. One deviation from this general rule is possible in situ chemical reactions.

The next section lists plausible chemical reactions deriving from amino acids; it is thought that

those conducted in an aqueous solution could change the chemical structure in such way as to

promote an easier and less energetically intense separation step.


Figure 6 Amino Acid Separation Steps

Nanofiltration(partic le s ize separation)

Solubil ized Dis ti llation Bottoms

Lignin Products

Ion Exchange(pH influence separation)

Gel Chromatography

(particle s ize separation)

Electrodialysis(hydropathy separation)

Reverse-Phase

Chromatography

(Polar ity s eparation)

Polar Amino Acids

Nonpola r Amin o Acids

Acidic Amino Acids

Basi c Amino Acids

Neutra l Amino Acids

Aspartic Acid

Glutamic Acid

Lysine

Arginine

His tidine

Salts/Ash

Reverse Osmosis(hydropathy separation)

Gel Chromatography(particle siz e s eparation)

Hydrophobic Amino Acids

Hydrophil ic Amino Acids

Gel Chromatography(particle s ize separation)

Tyros ine

Glutamine

Tryptophan

Threonine

Serine

Glycine

Asparagine

Proline


pH6<Amino Acids

Cystine

Phenylalanine

Methionine

Gel Chromatography

(partic le size separat ion)

Isoleucine

Leucine

Valine

Alanine

Nanofiltration(partic le s ize separation)

Solubil ized Dis ti llation BottomsSolubil ized Dis ti llation Bottoms

Lignin ProductsLignin Products


Gel Chromatography

(particle s ize separation)

Electrodialysis(hydropathy separation)

Reverse-Phase

Chromatography

(Polar ity s eparation)

Polar Amino AcidsPolar Amino Acids

Nonpola r Amin o AcidsNonpola r Amin o Acids

Acidic Amino AcidsAcidic Amino Acids

Basi c Amino AcidsBasi c Amino Acids

Neutra l Amino AcidsNeutra l Amino Acids

Aspartic AcidAspartic Acid

Glutamic AcidGlutamic Acid

LysineLysine

ArginineArginine

His tidineHis tidine

Salts/AshSalts/Ash

Reverse Osmosis(hydropathy separation)

Gel Chromatography(particle siz e s eparation)

Hydrophobic Amino AcidsHydrophobic Amino Acids

Hydrophil ic Amino AcidsHydrophil ic Amino Acids

Gel Chromatography(particle s ize separation)

Tyros ineTyros ine

GlutamineGlutamine

TryptophanTryptophan

ThreonineThreonine

SerineSerine

GlycineGlycine

AsparagineAsparagine

ProlineProline


pH6<Amino AcidspH6<Amino Acids

CystineCystine

PhenylalaninePhenylalanine

MethionineMethionine

Gel Chromatography

(partic le size separat ion)

IsoleucineIsoleucine

LeucineLeucine

ValineValine

AlanineAlanine


5.2.4 Potential synthesis routes

Mention the words biotechnology and bioengineering to the average laymen and images of

deformed produce caused by failed genetic engineering experiments quickly materialize in their

minds. Public resistance, especially in Europe, is

always directed at health safety (and more recently

monopoly prevention) of genetically alternating

eatable products within the food chain. Yet,

biotechnology spans far beyond the agricultural

scope of maximizing crop production. It

encompasses a much broader range of procedures

and applications of biological organisms, many of

which are already employed on a vast scale within

the food and non-food industries; from bacterial cultures for cheese, industrial enzymes for

detergents, to biocatalysts for pharmaceuticals. And while

bioengineering is a mere subsection of the wider

biotechnology field, it is akin to future improvements,

applications tailoring and optimizing the efficiency of the

operations. Nearly all of the potential amino acid synthesis

routes to chemicals embody biotechnology and can benefit

immensely from bioengineering optimizations. In the

traditional petrochemical industry a premium is placed on low production costs with the

employment of high-temperature and high-pressure reaction systems frequently permitting the

use of relatively inexpensive starting materials at strikingly diminished reaction times. Conversely,

a paradigm shift is needed when adopting biotechnology-based options for the biomass derived

processing of the individually isolated amino acid streams because biotechnological operations

perform best at low temperatures and low pressures at considerably long reaction times. The

premium of low production costs remains but the focus is shifted on finding the optimal trade-

off between using expensive enzymes and fermentation microorganisms over the reduction in

intensive direct process energy. Genetically engineering enzymes and microorganisms to lower

the conversional loading rate while simultaneously decreasing the indirect production costs will

not only facilitate but be imperative to the success of amino acid-based chemical production.

In this section a single potential and speculated process route for each of the individual amino

acids will be investigated. The following Table 20 illustrates an overview of a single chemical

product with in some cases a secondary by-product. There are conceivably a sizeable multitude of

chemical production options available for each amino acid; it is simply a quest of continued and

dedicated research and development. Based on the stoichiometric conversion ratios, the mass

yield (kg/kg) is of key importance to be able to determine the relative process energy. As all of

the process steps are hypothesis, the process description and conditions will be clustered and

generalized.

Biotechnology According to the UN convention on bio logical divers ity , “Biotechnology means “any technological application that uses bio logical systems, living organisms, or derivatives thereof, to make or modify products or processes for specif ic use.”


Table 20 Overview Potential Amino Acid Chemical Derivatives

Nomenclature Symbol Formula Structure Molecular Mass Primary Formula Structure Y ield Secondary Formu la Structure Y ield

Alanine ala C3H7NO2 89.1 e thylamine C2H7N 0.51

Arginine arg C6H14N4O2 174.2 1,4-butandiamine C4H1 2N2 0.46 urea (NH2 )2CO 0.31

Asparagine asn C4H6NO4 132.12 acry lamide C3H5NO 0.54

A spartic acid asp C4H7NO4 133.1 e thylamine C2H7N 0.34

Cysteine cy s C3H6NO2S 121.16 feed grade cyste ine C3H6NO2S 1.00

Glutamine g ln C5H10N2O3 146.15 1,4-butandiamine C4H1 2N2 0.46 ammonia NH3 0.10

Glut amic a cid g lu C5H9NO4 147.13 1,4-butandiamine C4H1 2N2 0.51

Glycine gly C2H5NO2 75.07 oxalic acid C2H2O4 0.65 ammonia NH3 0.12

Hist idine his C6H9N3O2 155.16 ionic liquids C2H5NH3NO3 0.62 ammonia NH3 0.10

Isoleucine ile C6H13NO2 131.18 isoprene C5H8 0.97

Leuc ine leu C6H13NO2 131.18 isoprene C5H8 0.97

Ly sine lys C6H14N2O2 146.188 e thylamine C2H7N 0.62

Methionine met C5H11NO2S 149.21 feed grade methionine C5H11NO2S 1

Pheny la lanine phe C9H11NO2 165.19 styrene C8H8 0.63 ammonia NH3 0.10

Proline pro C5H9NO2 115.13 g-buty rolactum C4H6O2 0.75

Serine se r C3H7NO3 105.09 e thylenediamine C2H8N2 0.45

Threonine thr C4H9NO3 119.12 isopropa nolamine C3H9NO 0.63

Tryptophan trp C11H12N2O2 204.225 adipic acid C6H1 0O4 0.54 ammonia NH3 0.08

Ty rosine tyr C9H11NO3 181.19 styrene C8H8 0.57 ammonia NH3 0.09

Valine val C5H11NO2 117.15 isobut yraldehyde C4H8O 0.62 ammonia NH3 0.15

General AA C3H6O2N 88.085 ammonia NH3 0.19

Amino Acids Products


5.2.4.1 Process Debriefing (Sources)

A general insight into several potential chemical products following the biorefinery concept have

been eluded at, including the impending benefits of incorporating protein-based chemistry72. The

described amino acid chemical synthesis examples were limited and process details were not

sufficiently provided. The basis of the herein chosen amino acid chemical synthesis routes were

taken for a large part from a follow-up mini-review focused on probable process routes73. Here

existing processes and plausible process routes were taken from biochemistry, medical and in

some case metabolic pathways studies. Again details pertaining to the exact processing conditions

are void, it does however provide a good insight into potential research directions and covers

most of the hypothetical synthesis routes. For some of the other hypothetical amino acids

product options, additional studies were taken, namely: arginine to ornithine via enzymatic

hydrolysis74, ornithine to butanediamine via enzymatic decaroxylation75, glutamine to glutamic

acid via enzymatic deamination hydrolysis76, GABA to butanediamine following the reverse

reaction of reductive deamination via standard amination77, histidine to ionic liquids via the idea

of solution dissociation60, leucine and isoleucine to isoprene via the complex biosynthesis

mevalonate pathway and enzymatic synthesis73, 78, lysine to ethylamine via a fermentative

degradation to split the carbon backbone of pentanediamine79, tryptophan to adipic acid via a

hydrogenation step of the intermediary muconic acid product80. Many of these and other

hypothesised process routes are contemplated, internally discussed and partially experimented

upon within the Wageningen UR department chair, valorization of plant production chains.

Nonetheless, consult the database for the exact reference sources adhering to the individually

proposed amino acid chemical synthesis route. At the bottom of both tables is the lowest

chemical product option, for as all amino acids contain a carboxylic acid and amine group they

can always be broken down to yield a single ammonia molecule at 0.19kg/kg.

5.2.4.2 General Process Unit Operations

Decarboxylation

Any chemical reaction involving a carboxyl group being split off in the form of a carbon dioxide

compound, following the general reaction formula, is decarboxylation:

R-COOH �� R-H + CO2

The reaction can be catalyzed either chemically or ever more frequent by specific decarboxylase

enzymes. Today there are so many enzymes specific to substrates containing carboxyl groups that

they are categorized by EC numbers, under EC4.1.1, and consequently named after the base

molecule. The most commonly studied is pyruvate decarboxylase. A temperature dependent

activation energy is needed to promote the reaction with the optimal between 31 - 45°C81, but the reaction is exothermic as an ATP is released during the carboxyl group removal. The generated

access thermal energy is in the order of 20 – 35kJ/mol with a medium of 29kJ/mol. Nonetheless,

a small electrical energy input is required to pressurized the tank/column and pump the contents,

in the order of 44kWh/ton82. Also, consider the indirect production energy of the enzymes,

which have a loading rate between 3 – 30g/kg with 5.0g/kg chosen to be representative.


Hydrolysis

Any chemical reaction involving a chemical compound being broken down in the presence of

water forming two new molecules, following the general reaction formula, is hydrolysis:

R′-R″ + H2O �� R′-OH + R″-H

In biochemical applications an enzyme is used to catalyze the reaction and is very site specific to

direct the exact cleavage position. In this section, there is only one reaction involving enzymatic

hydrolysis; alanine to ornithine with urea as a by-product. The operation conditions are thought

to be similar to the enzymatic saccharification step (section 3.1.12); temperature range 65 - 90°C, but as the stream is purer a lower demand (60°C) should be feasible, enzyme loading of 25g/kg, and due to the lower viscosity a reduced electric demand to 0.150GJ/ton product.

Maillard Reaction

Any chemical reaction involving an amino group reacting with the carbonyl group of a sugar

forming two new products, following the general reaction formula, is the Maillard reaction:

Amino Acid + Sugar �� CO2 + H2O + Product 1 + Product 2

The reactions typically involves high heat and is used extensively within the food industry83. It is

used to produce a variety of odours and flavours, meaning the process conditions also vary. Set

temperatures can range from low (40°C) to high (120°C) and pressures from atmospheric to on occasion as high as 60bars. Conversion rates are positively affected by high process intensities,

thus 120°C and 10bar will be set. Sugars are supplied in access, typically at 1:2 – 1:3 weight ratio; the lower value will be taken. Furthermore, the sugar (glucose) will originate from within the

biorefinery (Section 3.3) and its reactant product will be later combusted (Section 6.2.1) yielding

the calorific value. And, while water is produced via the reaction it is best to hold the reactants at

low aqueous concentrations (>20%).

Amination

Any chemical reaction introducing an amine group (ammonia) into an organic molecule to form

an amine, following the general reaction formula, is reductive amination:

R-COOH + NH3 �� R-CONH2 + H2O

Reductive amination is typically catalyzed with a metallic oxide occasionally in the presence of

addition hydrogen. There are two distinct systems; the well-defined high pressure (>100bar) and

proposed low pressure (~1bar). For the amino acid-based systems, the high pressure options will

be focused upon and it entails slightly elevated temperature of 80 - 95°C without hydrogen. Ammonia is added at a one to one stoichiometric ratio, but the indirect fossil fuel production

costs of ammonia will not be considered as many of the other proposed amino acid routes

release ammonia as a by-product. The amination process will thus reduce the yield of ammonia

form the other routes. Electricity is the main input to maintain the high-pressure.

Electrolysis

Any chemical reaction using electric current energy to split a chemical bonded molecule to form

two new products, following the general reaction formula, is electrolysis:

R′-R″ + Eo �� R′-OH + R″-H

Electrolysis is performed in an aqueous solution, usually only with water, but can be catalyzed by

certain alkaline or acidic mixtures. In many systems a weight ratio of 25% is used. Moderately

elevated temperatures are involved ranging from 30 - 80°C, with 70°C used in splitting larger molecules, like proteins. Of course, the electric component is the most intensive and can reach

up to 140 – 200GJ/ton for hydrogen electrolysis. Vastly lower demands are needed for molecule


degradation in heated aqueous solutions. An electric potential of 6 – 30 volts at 0.01 – 0.2 A/cm²

is suitable for protein splitting84. This relates to a slight over electric capacity of 1.5 – 3.0times;

0.48kWh/mol will be taken.

Fermentative

Fermentation does not follow any general reaction formulas. By splitting the source molecule

into new products these substrate acts as an energy source for microorganisms via the unique

internal biochemical pathway of the organisms. For amino acid-base systems it can be called

fermentative degradation as a portion of the molecule is broken off releasing a new usable product.

Ethanol fermentation can act as a guideline to the reaction kinetics and process conditions, but

because it is highly tailored representing the lower scale of fermentation systems the amino acid

system must be placed on the higher scale of the energy range. In the biochemical pathways

involving amino acid a nitrogen functional group is usually consumed by the organism which

reduces greatly reduced the eternal nutrient requirements in the broth.

Enzymatic Catalysis

As with fermentative degradation, enzymatic catalysis does not follow a general reaction formula.

Otherwise known as biocatalysis, the use of enzymes are designed to lower the process condition

intensity to save on heating and pressurizing energies. A detailed example of this principle was

performed on acrylamide and found a process energy reduction from 1.9GJ/ton to 0.4GJ/ton85.

Enzymatic hydrolysis, decarboxylation and deamination are all classified as biocatalysis, yet here it

is understood as being specific reactions which do not fall under those categories. Evaluation is

thus difficult necessitating some set assumptions; atmospheric conditions, 2.5wt% enzymes, and

reflecting with the acrylamide process.

Deamination

Any chemical reaction in the presence of water which removes an amine group in the form of

ammonia, following the general reaction formula, is deamination:

R-CONH2 + H2O �� R-COOH + NH3

Removing an ammonia molecule is immensely less energy intense then adding a molecule, but

unlike removing a carbon dioxide molecule (decarboxylation) does not release noticeable levels of

energy despite being slightly exothermic. The reaction is catalyzed either chemically or by using

enzymes, however in the field of oxidative deamination enzymes are becoming the norm. The

process conditions are analogous with enzymatic hydrolysis with one minor different, product

allocation. Unlike water, ammonia is a product and will be collected easily using a flash tank

separation. This means an extra 17.03g/mol of product will reduce the energy demand, or on

average


No Action

For the amino acids that contain a sulphur (cystine and methionine) there is currently no

potential production route that can make adequate use of incorporating this functionality.

Leaving them in their purified form for the animal feed market is the superior option. In fact, as

will be discussed in more detail in Chapter 8, amino acids with a chemical product of less than

2.5% of the amino acid distribution are also best left in their purified form for the animal feed

market at this stage of development. The development focus will commence with the higher

production volumes and gradually transition to a more complete use of the streams. This is the

logical step when addressing technological process gap hurdles in practice, but as the biorefinery

is designed to produce non-food chemical products the lowest form of chemistry is preferred;

conversion into ammonia.

Removal of Water

At some stage, before or after, the proposed reactions water must be removed to produce a pure

chemical stream. To facilitate several of the above mentioned reactions it is already required that

the purified amino acid reactants contain 0% moisture content. Others can be reacted directly in

their aqueous solution, namely those using enzyme technology. In these cases the chemical

product must be lastly separated from the aqueous broth. For simplifications purposes the same

process steps to remove water will be handled. As the products all vary to water in density and in

some cases their physical state, a centrifuge will be used to initially lower the moisture content to

20% (set). Afterwards a single stage evaporation system will further reduce the moisture content

to 95% and finally steam-based drier will fully de-watering the products.

5.3 Energy Input

5.3.1 Protease Solubilization

Initial protease digestion experiments were performed as a proof of concept resulting in

moderate solubilization rates of 51.7% for corn wet distillers grains and 41.5% for wheat stillage

(intermediary of distillers grains)26, 62. These values and process conditions form the basis of the

energy and exergy calculations, direct to Chapter 2 for the procedure to use Aspen+ process flow

diagram constructs. However, it is expected that with continued experimentation and

investigation into the operation kinetics that a near complete digestion (95%) can be obtained at

lower residence times (24hours) representing the future “expected” trends. Table 21 lists the

process conditions for the tested and expected values for corn and wheat processing streams and

additionally the projected conditions for all protein-rich biorefinery streams. “All” feedstock

sources, because at this stage within the biorefinery the post-fermentation streams should all have

similar composition and consistency. A protease loading of 0.1 weight percent in respects to the

protein content is set. Bacterial protease needs 22.3MJ/kg worth of ingredients, 19.6MJ/kg for

processing of which most is electricity, totally to 43.1GJ/ton3. Exergetically the value lead to

45.2GJ/ton. The thermal and electric internal process energy were based upon the Aspen+ model

with the entropy and enthalpy figures revealing the exergy flows, see Table 21 for an exemplary

spreadsheet.


Table 21 Protease Internal Process Energy/Exergy Calculations (DDGS example)

Category Unit

Solid Portion %

Biomass Feed kg/hWater Content kg/h

Total Feed kg/h

Feed Temperature °CProtein Content %

Protein Flow ton/batch

Protease Residence Time hProtease Temperature °C 40 50 72 40 50 72 40 50 72 40 50 72

Protein Solubility (1.0%) 12.5% 10.0% 15.0% 25.0% 20.4% 22.5% 60.0% 50.0% 47.5% 80.0% 49.9% 82.6%

Small Peptide Proportion (1.0%) 99.0% 98.0% 98.0% 99.0% 98.0% 98.0% 99.0% 98.1% 97.0% 75.0% 90.0% 89.6%Protein Solubility (0.1%) % 5.0% 4.2% 7.5% 7.5% 5.0% 10.0% 55.0% 49.9% 47.3% 67.8% 57.1% 95.0%

Small Peptide Proportion (0.1%) % 99.0% 97.0% 95.0% 99.0% 98.0% 95.0% 99.0% 98.6% 97.4% 91.6% 89.4% 85.8%

Soluble Protein Yield (1.0%) ton 0.025 0.020 0.030 0.050 0.041 0.045 0.120 0.100 0.095 0.160 0.100 0.165

Soluble Protein Yield (0.1%) ton 0.010 0.008 0.015 0.015 0.010 0.020 0.110 0.099 0.094 0.135 0.114 0.189

Batch R eactor Heat 0.09 0.27 0.69 0.09 0.27 0.69 0.09 0.27 0.69 0.09 0.27 0.69Heat Integrated -0.05 -0.20 -0.56 -0.05 -0.20 -0.56 -0.05 -0.20 -0.56 -0.05 -0.20 -0.56

0.04 0.07 0.13 0.04 0.07 0.13 0.04 0.07 0.13 0.04 0.07 0.13

GJ 0.045 0.073 0.137 0.046 0.075 0.140 0.048 0.078 0.145 0.062 0.101 0.188

MJ/h 0.5047 0.50969 0.5211 0.5047 0.50969 0.5211 0.5047 0.50969 0.5211 0.5047 0.50969 0.5211

GJ 0.0030 0.0031 0.0031 0.0061 0.0061 0.0063 0.0121 0.0122 0.0125 0.0606 0.0612 0.0625Enthalpy In -68538 -68538 -68538 -68538 -68538 -68538 -68538 -68538 -68538 -68538 -68538 -68538

Enthalpy Out -68451 -68273 -67870 -68451 -68273 -67870 -68451 -68273 -67870 -68451 -68273 -67870

Entropy In -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336 -38.336

Entropy Out -38.053 -37.492 -36.281 -38.053 -37.492 -36.281 -38.053 -37.492 -36.281 -38.053 -37.492 -36.281

Ref Temp K 293.15 293.15 293.15 293.15 293.15 293.15 293.15 293.15 293.15 293.15 293.15 293.15kmol/h 246.3 246.3 246.3 246.3 246.3 246.3 246.3 246.3 246.3 246.3 246.3 246.3

mol/s 68.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4

Exergy cal/s 284.8 1177.9 4464.8 284.8 1177.9 4464.8 284.8 1177.9 4464.8 284.8 1177.9 4464.8kJ/s 1.2 4.9 18.7 1.2 4.9 18.7 1.2 4.9 18.7 1.2 4.9 18.7

GJ 0.005 0.021 0.081 0.021 0.085 0.323 0.082 0.341 1.292 0.206 0.852 3.230

Total Energy GJ 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.2 0.3

Total Exergy GJ 0.008 0.024 0.084 0.027 0.091 0.329 0.095 0.353 1.304 0.267 0.913 3.292

Operation Energy (1.0%) GJ/ton 1.9 3.8 4.7 1.0 2.0 3.3 0.5 0.9 1.7 0.8 1.6 1.5

Total Process Energy (0.1%) GJ/ton 4.8 9.1 9.4 3.5 8.1 7.3 0.5 0.9 1.7 0.9 1.4 1.3

Total Process Exergy (1.0%) GJ/ton 0.3 1.2 2.8 0.5 2.2 7.3 0.8 3.5 13.8 1.7 9.2 20.0

Total Process Exergy (0.1%) GJ/ton 0.8 2.9 5.6 1.8 9.2 16.5 0.9 3.6 13.8 2.0 8.0 17.4

GJ/h

0.1994

Mass Flow

12

cal/mol

cal/mol.K

Stirring Electricity

Batch R eactor Heat C ost

24 1206

DDGS48.4%

4844356

484021

4.1

( ) ( )[ ]000 SSTHHMEx iii −−−⋅= &

Furthermore, heating efficiency of the digester was incorporated by including a typical insulted

mantel losing about 8% heat energy/exergy per day or 0.333% per hourly operation interval. In

the mentioned articles, the optimal processing conditions were assessed between the protein

solubilization yield in light of potential fossil fuel saving from the downstream product yields to

the internal process energy costs. This is not needed when presuming an expected solubilization

yield of 95%; here the focus is placed upon lower processing conditions. The following table

provides an overview with the projected “all” derived by combining the expected corn and wheat

values:

Table 22 Protease Solubilization Process Energy/Exergy

Crop Corn Wheat All Phase

Unit Tested Expected Tested Expected Projected

Conditions Solubilization Rate % 51.7 95 41.5 95 95 Protease Loading g/g protein 0.01 0.01 0.01 0.01 0.01 Temperature °C 40 40 50 50 45

Residence Time Hours 120 24 120 24 24 Direct Energy (Exergy) Electric GJ/ton AA 1.97 0.33 1.83 0.45 0.39 Thermal GJ/ton AA 1.31 (0.98) 1.14 (0.12) 3.41 (1.63) 2.52 (1.11) 1.83 (0.62) Indirect Energy (Exergy) Enzymes GJ/ton AA 0.83 (0.87) 0.45 (0.48) 1.04 (1.09) 0.45 (0.48) 0.45 (0.48)

The total projected processing energy and exergy cost for all of the feedstocks from this stage in

the biorefinery are 2.67GJ/ton and 1.48GJ/ton protein.

5.3.2 Separation and Isolation

The separation and isolation steps as depicted in figure 6 are handled individually with a set

separation/isolation efficiency of 97% (being common) for each step33, 65. And seeing that the


amino acids require between 3 and 4 steps, the overall isolation efficiency is 91 – 94%. Table 22

lists the range of thermal and electric energy required to operate the separation units. As the

resulting product process energy are functions of the flux, all the values are presented per

product flow rate (i.e. cubic meter). Thus for representative purposes the listed “product

relation” is based on the continued arbitrary protein concentration of 6.5wt%. Lower

concentrations (which will occur, see Chapter 8) directly increase the isolation and purification

operation energy demands. Despite the large thermal component needed for viscosity adjusting,

these procedures are considered to be electric driven. Listed in the appendix are the resulting

exergy figures with a clearly indicates the low thermal proportion. The selected (or chosen) values

within the range are thought to be characteristic of potential amino acid purification steps:

Table 23 Isolation and Purification Operation Energy/Exergy Demands

Type Thermal Energy Electric Energy Product Relation

Nanofiltration - 1 – 7kWh/m³ (3.5) 0.194 GJ/ton Electrodialysis 24.2 – 74.8kWh/m³ (33.8) 85.8 – 265.2kWh/m³ (119.7) 8.5 GJ/ton Chromatography 42.9 – 123.2kWh/m³ (97.5) 12.1 – 34.8kWh/m³ (27.5) 6.9 GJ/ton Reverse-Phase 36.2 – 37.1kWh/m³ (36.4) 15.2 – 32.3kWh/m³ (19.0) 3.1 GJ/ton Reverse Osmosis - 2.5 – 10kWh/m³ (9.0) 0.498 GJ/ton

value range (brackets chosen): # - # (#)

Figure 7 Amino Acid Purification and Isolation Process Energy

Amino Acid Separation Step Process Energy

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Alanine

Argin

ine

Asp

aragin

e

Asparti

c aci

d

Cys

tine

Gluta

min

e

Gluta

mic

acid

Gly

cine

Hist

idin

e

Isol

eucin

e

Leuc

ine

Lys in

e

Met

hionin

e

Pheny

lala

nine

Prol in

e

Serin

e

Threon

ine

Trypt

ophan

Tyros

ine

Valine

GJ/ton Direct Energy

Electric Energy

Thermal Energy

Portrayal: based on 6.5% feed solids loading and equal amino acid distribution

5.3.3 Drying and Product Preparation

Either before the chemical reactions or afterwards, the purified amino acids streams or final

product entail a dewatering step; envisioned here by a common three step process:

Table 24 Dewatering and Product Preparation Energy Cost

Dewatering Step Unit Value


Centrifuge Initial Product Content % 6.5 Final Product Content % 80 Direct Energy (Exergy) Electric GJ/ton product 0.31 Thermal GJ/ton product 0 (0) Single Evaporation Initial Product Content % 80 Final Product Content % 95 Direct Energy (Exergy) Electric GJ/ton product 0.03 Thermal GJ/ton product 0.81 (0.08) Steam Drying Initial Product Content % 95 Final Product Content % 100 Direct Energy (Exergy) Electric GJ/ton product 0.02 Thermal GJ/ton product 0.27 (0.03) 6.5% moisture is an example for display purpose, will depend on feedstock amino acid content

The three steps involve a transition from the post-fermentation relative weight content (set here

as 6.5wt%) to 80% via centrifugation than to 95wt% by single evaporation and finally dewatered to

100wt% through standard steam drying. There are several other dewatering technologies available;

this particular layout is conventional, straight forward, and can be adapted to all product streams.

And while it may not necessarily represent the single most energy efficient technology it is

amongst the ranks of efficient drying process’s.

5.3.4 Reactions

All the reactions involved in the hypothetical amino acid to chemical product production have

been grouped together. Considering that none of the envisioned reactions have any specific

reactions parameters this grouping generalization is possible and provides a satisfactory

indication of the prospective production routes. The grouped reaction type process energy and

exergy requirements are determined and presented in molar mass terms (i.e. kJ/mol) because

each amino acid and potential chemical product boast unique molecular masses. This also allows

the stoichiometric mass to heavily influence the results, see Appendix 10.6. As seen in the

following figure the process energy requirements differ immensely from each other. The indirect

chemical energy is understood as the enzyme production costs. Being currently rare, site specific

and far from optimized enzymes the most energy intensive route are chosen; namely, 89.3GJ/ton

energy and 136.1GJ/ton exergy. Furthermore, a higher loading in the order of 1.0% is

anticipated.

Figure 8 Process Type Process Energy


Amino Acid Chemical Process Unit Type Energy

-50

50

150

250

350

450

Enzymatic

Decarboxylation

Enzymatic

Hydrolysis

Maillard React ion Reduct ive

Amination

Electro lysis Fermentative Enzymatic

Catalysis

Thermal

Catalysis

Enzymatic

Deamination

kJ/m

ol

Indirect Chemical Energy

Electric Energy

Thermal Energy

465 1991

5.3.5 Overall

Figure 9 Overall Amino Acid Process Energy

Amino Acid Overview Chemistry

0

5

10

15

20

25

30

35

40

Alanin

e

Arg

inin

e

Asp

aragin

e

Asparti c

acid

Cys

tein

e

Gluta

min

e

Glu

tam

i c a

cid

Glyci

ne

Histid

ine

Isoleuc

ine

Leucine

Lysine

Meth

i onin

e

Phenyla

l anin

e

Prolin

e

Serine

Threon

ine

Trypto

phan

Tyrosi

ne

Valine

Process Energy (GJ/ton)

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

Overall Yields

Indirect

Electr ic

Thermal

Protein Relation



Figure 10 Overall Amino Acid Chemical Product Process Energy

Amino Acid Product Process Energy

0

5

10

15

20

25

30

35

40

1,4-b

utandia

min

e

acry

lam

ide

adipic

aci

d

amm

onia

ethyla

min

e

ethyle

nedia

mi n

e

feed g

rade

cyste

ine

feed g

rade

meth

ionin

e

g-buty

rol a

ctum

i onic

liqu

ids

isobuty

rald

ehyde

isop

rene

isopro

panolam

ine

oxalic a

cid

styr

eneur

ea

GJ/ton product

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

Overall Yields

Indirect

Electric

Thermal

Pro tein Relation



6 Lignin

6.1 Description

Lignin is the second most abundant biomolecule in the biosphere after

carbohydrates and is the single most abundant source of aromatics.

And unlike the other biomass components, lignin is exceedingly unique;

every plant species, every plant, every section of the plant and every

molecule of lignin is slightly different. Its individual highly complex

polymeric structural layout of aromatic compounds are bonded

together by two major links types; unconcentrated beta-oxygen-4 links

(β-O-4) and concentrated carbon-carbon links (C-C). Three aromatic monolignol monomers with various degrees of methoxylation form the

basis of lignin formation; p-coumaryl alcohol, coniferyl alcohol, and sinapyl

alcohol. When incorporated into the lignin structure following the two

linkage types they form p-hydroxyphenyl (H), guaiacyl (G), and syringal (S).

The final lignin structure present in biomass material are large cross-linked

recemic macromolecules with a molecular mass exceeding 10000 units, see

the adjacent picture for a likely representation. It can be characterized by

the general empirical formula: C9H8-xO2[H2](<1.0[OCH3]x). This chemical configuration provides

great structural integrity to biomass conferring mechanical strength to the cell wall. In addition to

rigidity, lignin’s structure also reduces digestibility of plant biomass, which aids in the defence

systems against pathogens and pests. Yet lignin, as the derived name lignum (Latin for wood)

suggests, provides structural stability to plants as a whole and being a product of plant aging is

commonly associated with woody biomass. The lignin structure in woody biomass is best broken

down into hardwoods consisting primarily of β-O-4-linkages (>60%) and softwoods consisting primarily of C-C-linkages (upwards of 90%). Non-woody biomass materials (as is case for the

selected crops) are more characteristic of softwoods, consisting mainly of C-C-links.

Lignin as a by-product stream has been around for more than century since lignin is removed

from wood-based pulp to manufacture “woodfree” paper. In both the sulphite and Kraft processes,

sulphur drives the delignification and separation reactions producing a waste stream of

lignosulfonates. The pulp and paper industry have even adopted their own proverb regarding

lignin or in actuality the lignosulfonates, “you can make anything from lignin…expect money”. In fact,

these lignin by-products are used for around 300 different applications varying from binding

agents (adhesives, acting as a glue) to dispersing agents (preventing clumping and settling of

undissolved particles in suspensions). None of these product applications make particularly good

use of lignin’s aromatic functionality and are essentially inferior products, yielding little profit.

Furthermore, despite these existing efforts to produce products and blends the large majority of

lignosulfonates are currently burnt as a fuel source. A good general formula to represent a section

of lignin is C20H23O7 resulting with a relatively high calorific value of 25.6GJ/ton. Lignin

originating from within future biorefinery concepts will be present in vast quantities and due to

market saturation are not suitable for the same product array as with the lignosulfonates. Its high

calorific value is already proving alluring as currently all 1st generation biofuel biorefinery-types

are burning the lignin-rich waste streams for internal heat and power requirements. The lignin-


rich stream originating from within this Chapters’ proposed biorefinery concept is, however,

much purer; essentially composed of lignin, minerals (ash) and traces of un-reacted or separated

biochemical impurities in a water solution. This lignin-rich stream is the last stream that can be

subjected to processing options to yield a chemical product. Plus, to remain dedicated to the

main objective of mitigating the use of fossil fuels from within the petrochemical production

chain, directly burning lignin is not a viable option. New processes are gradually being researched

and developed to make use of its aromatic functionality. Soon lignin will no longer be viewed as a

waste product but as a valuable co-product with the biorefinery concept.

6.2 Processing

6.2.1 New Product Options

To utilize the aromatic functional components of lignin the complex lignin structure must be

degraded to release the so-called oxygenated aromatic compounds (OAC)86. Its unique and

complex structure presents a critical problem to any depolymerisation or degradation process as

the resulting OAC products range in an array of beyond 50 individual chemical products. This

places great difficulties in downstream separation and isolation techniques. Research efforts are

under way to vastly reduce the product array and isolate particularly desirable aromatic products.

Due to the unique structure of lignin and the early stages of investigation, laboratory

experimental testing use simple representative structures to mimic the two types of linkages87.

Phenethyl phenyl ether (PPE) for C-C links and its methoxy derivates for β-O-4 links. Cleavage of the two linkage types will produce several but distinctly different groups of chemicals:

Carbon-carbon cleavage (αααα and ββββ aryl-alky-ether bonds) Yields phenolic compounds: like benzene, p-hydroxyphenyl, phenol hydroxylase, acetophenone monooxygenase, cresol, styrene, paraderivatives of phenol, etc.

ββββ-O-4 cleavage Yields guaiacols and syringols: both can be fractionalized to yield synthons (idealized fragment ions) but are better suited for further degradation into chemical precursors like straight benzenes

The goal of lignin depolymerisation is to cleavage these links yielding high levels of the simple

aromatics from benzene to benzoic acid, those which exist in the petrochemical industry. This

proves advantageous for the selected biomass crops as their lignin structure is primarily based

upon the C-C-link, which form the more desirable phenolic compounds. Three different

emerging technologies (fungal degradation, gasification and fast-pyrolysis) will be handled in this

section with the equal aim set on creating new potential product options for lignin-rich streams.

Although the success is limited and largely hypothetical, the aromatic-based amino acids might

eventually be better suited for lignin processing routes as opposed to the amine chemistry option.

While currently, processing lignin and/or aromatic-based biomass streams to produce OAC’s is

the least investigated technological option within the biorefinery concept. Research is thus in its

infancy with the yield, more so than the actual process conditions, effecting the overall internal

process energy. Therefore, expected yields based on current experimental figures will be handled.

6.2.2 Fungal degradation

In nature decay of the lignin components of wood occurs through a fungal infection of different

types; brown rot, soft rot or white rot fungi. Laboratory investigations pertaining to

delignification processes have almost exclusively focused upon white rot fungi. White rot fungi

cultivated on woody biomass produces several ligninolytic enzymes; extracellular laccases (EC


1.10.3.2), manganese peroxidase (EC 1.11.1.13), lignin peroxidase (EC 1.11.1.14) and H202

producing oxidases. There are dozens of fungi species and sub-species containing ligninolytic

enzymes, while most research on lignin degradation for practical purposes has been performed

using the various strains of the pleurotus species. Investigation to their industrial applications have

been around for several decades88. It has since been determined that manganese peroxidase,

which is excreted from most white rot fungi, plays the crucial role in the delignification

mechanisms by generating oxygen species89. The other enzymes are dependent on incorporating

oxygen in their reaction mechanisms with all the enzymes grouped together and expressed as

containing a total ligninolytic activity, expressed in units per gram wood (IU/g). Typical activities

range from 0.1 – 3.0IU/g with 1.5 being average, which converted, approximates 0.12% gram

enzyme per gram lignin loading rate. The main applications of white rot delignification is for

decreasing the lignin content within the pulping process, known as biopulping. It is an intermediary

step to reduce chemical demand and process energy and the conversion rates are rather low8, 89:

Table 25 Fungal Degradation of Lignin

Enzyme Source P. Eryngii P. Chysosporium P. Ostreatus P. Radiata

Delignification Rate 47% 45% 56% 25%

It is not necessarily suitable as a means to produce and yield aromatic chemicals because the

lignin only needs to be (partly) solubilized, meaning an immense array of possible chemical

combinations are naturally present. Furthermore, within the carbohydrate processing sections the

enzymatic hydrolysis and pretreatment steps already degrade a portion of the lignin, solubilizing a

noticeable amount (~1/3). Ligninolytic enzymes could be added at the lignocellulose treatment

stage to accelerate and improve the glucose conversion of, in particular, the recalcitrant materials

(i.e. those containing high levels of lignin). Perhaps future strains and generations of specially

tailored enzymes can target specific linkage and produce a narrow range of chemical products by

adapting enzyme cocktail combinations. Until those routes are investigated there is no real future

of fungal delignification within a biorefinery concept, regardless of it worthiness to mention.

6.2.3 Gasification

Gasification is widely considered to be a very promising biomass processing route and a realistic

alternative to the traditional fermentative routes. It involves the thermal degradation of any

carbonaceous (carbon-containing) raw material to produce syngas (H2 + CO). At temperatures

above 900°C tar formation begins to negatively influence the product yields while at temperatures below 750°C conversion efficiencies drop. Modern fluidized-bed systems can however, lower the temperature range to 400 - 500°C at no drop in conversion efficiency. Nonetheless, gasification is a high-temperature thermal operation with corresponding pressures

approaching 25bar and residence times commonly exceeding an hour. Syngas is a mixture of

hydrogen, carbon monoxide and carbon dioxide with the basic idea is to produce the fuel

hydrogen. As the level of oxygen is regulated gasification does not follow combustion kinetics

but instead follows three separate reactions kinetics designed to maximize the production of

syngas:

(1) C + H2O → CO + H2 (2) C + O2 → CO2 (3) CO2 + C → 2CO

Conversion efficiencies are documented by two terms when referring to biomass feedstocks; (1)

carbon-to-gasification product ratio (CGR) and (2) hydrogen-to-gasification ratio (HGR). The


overall feedstock-to-product ratio of biomass feedstocks are frequently able to reach 80 – 95%.

Lignin contained in biomass, however, has been found to directly reduce these conversion

efficiencies. Investigation into gasification systems based solely on pure lignin feedstocks found

HGR values in the order of only 9 – 26%. It is understandable because the depolymerisation of

lignin induced by the gasification process reacts (consumes) with a portion of the released

hydrogen product, effectively lowering the overall syngas yield90. Researchers in the field of

biomass gasification technology are aware of this restriction and are even promoting the

development of low-lignin biomass crops as sources of new feedstocks (Choren). In this respect

the overall conversion efficiencies are misleading as they often relate to low-lignin feedstocks or

in some scientific studies to pure cellulose, taken as a biomass “model” feedstock91. At this stage

it might be an idea to treat the lignin containing biomass material with the previously mentioned

fungal delignification step to overcome the negative influence of untreated lignin. Suppose that

the lignin issue were to be solved eventually, syngas (or hydrogen) does not make any use of the

aromatic functionality; the energetics of syngas production should be carefully assessed:

Consider: Hydrogen has a lower heating value of 120GJ/ton and a higher heating value of 142GJ/ton. Syngas being water-free, HHV can be taken. Biomass contains 4.5 – 6.0wt% hydrogen with 5.7% being representative for the lignin stru cture. Therefore at maximum conversion

efficiency the energetic yield is 142GJ/ton ⋅ 0.057 = 8.1GJ/ton. The HHV of lignin is 25.6GJ/ton and even with a conservatively low power efficiency of 35% the yielded energy content is 8.9GJ/ton. And this does not even take into account the energy requirements of gasification or necessary compression of hydrogen for downstream application which must be deducted.

In all fairness though, syngas is envisioned as an intermediate and in the case on biomass

gasification to produce, via Fischer Tropsch, diesel92. FT-diesel is catalyzed and fully utilizes the

off-heat supplied by the high-temperature gasification unit, greatly increasing the overall energetic

efficiency. Yet still, hydrogen nor FT-diesel make efficient use of the aromatic functionality of

the lignin feedstock, meaning these systems are not appropriate for within the biorefinery

concept.

6.2.4 Fast-pyrolysis

Where gasification begins pyrolysis continues and fast-pyrolysis ends. Fast-pyrolysis is similar to

gasification being a thermal-based process acting upon carbonaceous feedstocks. It involves rapid

heat transfer and short residence times for both the substrates and decomposition products. As

water negatively influences heat transfer rates and can cause secondary reactions in the

decomposition product stream, the feedstock must be completely dry. The following table

outlines the main differences between gasification, conventional pyrolysis and fast-pyrolysis:

Table 26 Thermal Degradation Types

Type Pressure Temperature Residence Time Liquids Chars Gases

Gasification 25bar 400 - 900°C Hours 5% 10% 85%

Pyrolysis 10 300-400 Minutes 30 35 35 Fast-Pyrolysis 5 250-450 Seconds 75 12 13

The key difference between gasification and fast-pyrolysis is the decomposition product

distribution; gasification produces mainly gases (syngas) where as fast-pyrolysis yields liquids

(aromatics). Gases from the fast-pyrolysis are the smaller components, broken off as formed

CO2, H2O, etc. The chars are un-reacted and heavy particles, which will form a valuable fuel


source for further combustion, Section 7, and any simple hydrocarbons in the gas stream can also

contribute. Both conventional pyrolysis and fast-pyrolysis are performed with the absence of

oxygen, however inclusion of minor amounts has shown to slightly increase the proportional

yield of phenolic components over other oxygenated aromatics. Some components begin to

cleavage at temperatures as low as 220°C, while require at least 400°C. Table 27 General lignin pyrolysis temperature dependent decomposition production

Temperature Bond Cleavage Type Derivatives

150 - 300°C α- and β- ether Oxygenated Aromatics

300 - 350°C Aliphatic side chains Phenolic Compounds

370 - 400°C Carbon-carbon Guaiacyl, Syringyl

400 - 450°C Rest Various OAC

>450°C All Phenol/Benzene + Gases

Most researchers agree that between 425 – 575°C yields the maximum amount of decomposition products. At moderate temperatures, below 450°C, over 90 different products are detectable from biomass streams. Temperature exceeding 450°C presents a larger proportion of phenols and benzenes and begin to form styrene which oddly originates from the carbon-carbon links93.

At temperatures above 500°C, phenol, styrene, and toluene appear to be the main products. Even on woody biomass phenol production can reach up to 52% of the total product distribution

when temperatures above 600°C are employed94. But generally research and development into lignin pyrolysis is limited and has so far been unsuccessful in producing pure chemical product

streams and are only able to yield a wider assortment of pyrolytic components and their

corresponding radicals. Most studies into lignin decomposition obtain lignin from the traditional

pulping processes (meaning lignosulfonates) while others rely on fresh biomass streams (meaning

lignocellulose). These are not representative for the lignin-rich stream from within the biorefinery

concept. Other investigations are analysing the reaction kinetics of fast-pyrolysis on lignin by

employing lignin model chemicals. A large variety of dimmer and trimmer molecules mimic the

different chemical bonds and links contained in the lignin structure. Initial studies have found

cleavage rates for phenolic dimmers to be 3.6 – 80.5% and 17.8 – 70.1% for p-substituted

phenols95. Fast heat transfer at high temperatures is still the most influential factor. A recent low

temperature fast-pyrolysis experiment on model chemicals found a high cleavage rate but yielded

a wide assortments of phenolic compounds96. Earlier studies on PPE as a model for C-C-linkages

(β-ether) found an increase in styrene and phenol production (at equal molar distributions) at temperatures ranging from 500 to 650°C97.

The exact yields of potential aromatic chemicals from lignin at this stage must be presumed and

set as an expectation. Firstly, on the variety of lignin sources 75% total decomposition yields are

already achievable, 95% should be possible and foreseeable with future developments and

optimizations. Secondly, as alluded in table 25, lignin will naturally endure losses as at least 13%

of the lignin structure is not and will no longer be directly attached to the aromatic rings of the

liquid product. The level is dependent on the final chemical products, set here (thirdly) as an

equal molar mix of styrene, phenol and toluene. The highly branched aromatic cinnamic acid

with a molar mass of 148.2g/mol can represent an initial decomposition product. The expected

product mix has a lower average molar mass of 99.1g/mol, meaning 33.1wt% is unusable product


(i.e. gases). Fourthly and finally, setting the yields of the desirable aromatic product mix. Initial

studies have rarely yielded above 10% of any particular component, yet it is expected that with

additional temperature and process optimizations 90% product yields are achievable.

�� 18.5% phenol, 20.5% styrene, 18.1% toluene of lignin feedstock

Another future potential option to lower the product array to these or other certain select

aromatic chemicals could be to utilize enzymes targeting and cleaving off side branches.

6.3 Energy Input

Gasification systems designed for biomass applications are noted to use 20 – 30wt% of the

supplied feedstock as a source of heat generation. At a calorific value of 25.6GJ/ton for lignin

the gasification unit requires more or less 6.4GJ/ton product. Gasification as mentioned is

designed to produce syngas (hydrogen) and operates at high temperatures (>800°C) for long residence times (>1hour). The fast-pyrolysis unit operates at lower temperatures (<600°C) for much shorter residence times (<1minute). The operation energy intensity will also be lower

because the feedstock stream must first be removed of water. So, before the fast-pyrolysis unit

the lignin-rich stream will be subjected to a multistage evaporation system. Process energy

requirements are vastly lower then the single stage evaporation as described in the amino acid

section (Section 5.3.3), largely due to the streams release temperature from the distillation column

(~70 – 80°C). The electric energy demand is set at 5kWh/ton water removed and the thermal energy and exergy demand is 125kWh/ton and 12.4kWh/ton water removed, respectively. And

analogously to the amino acid-rich stream the initial moisture content of the lignin-rich stream is

feedstock dependent. For representation purposes and being close to the expected values, the

solids loading is set here at 10wt%. To fuel the fast-pyrolysis unit an outside source of process

energy is supplied because the feedstock is destined to maximize aromatic product yields. The

requirements are based on the internal cleaving energies of the various chemical bonds:

Table 28 Lignin Bond Type Energies and Product Relation

Bonding Energy Phenol Relation Benzoic Acid Relation

Bond Type kJ/mol GJ/ton GJ/ton

Aliphatic C-O 245 2.6 2.0 Aromatic C-O (methoxyl) 356 3.8 2.9 Aromatic C-O (hydroxyl) 414 4.4 3.4

α-ether 185 2.0 1.5

β-ether 239 2.5 2.0

Relating the bonding energies with these two example products (large and small molecules)

reveals that the thermal process energy ranges from 1.51 – 4.40GJ/ton with an average cleavage

energy of 2.73GJ/ton. At 600°C the exergy-to-energy ratio is 84%, resulting in 2.3GJ/ton. Both energy and exergy values must be brought into relation with the actual product weight

distribution yields (i.e. 18.5% phenol, 20.5% styrene and 18.1% toluene). Further downstream

separation and isolation of the three main product streams is rather straight forward, relying on

swing adsorption technology. The process energy demand is largely based upon the ethanol

dehydration unit, a swing adsorption type. Combined the overall lignin to several select aromatics

products streams results in the following figure:


Figure 11 Overall Lignin Process Energy

Lignin Product Process Energy

0.0

1.0

2.0

3.0

4.0

Phenol Styrene Toluene

Process Energy GJ/ton

15. 0%

17. 5%

20. 0%

22. 5%

25. 0%

Overall Yields

Electric Energy

Thermal Energy

Lignin Relation



7 Ash

7.1 Description

Ash is the name assigned to all biological components that cannot

be classified as organics. Generally this refers to metal ions and

metal salts, which while contained in living organisms are frequently

referred to as ligands. The term ash is used because these metal

compounds remain after combustion in the form of metal oxides.

As listed in Chapter 4, ash can constitute between 5 to 20% total

plant biomass. While ash is always included in proximate analysis of

biological materials (like biomass), in this section it is not understood as merely the summation of

all non-organic components. In the crop guide overview, it is presented as the summation of all

components that do not fit into the other biochemical classifications; namely carbohydrates, fatty

acids, proteins and lignin. Following this definition ash can also contain undisclosed trace levels

of other organics. The functional role of these ash components was described in full detail for

each major component in the fertilizer section of Chapter 5. As a synopsis, the non-organics are

required for many highly specific biological roles. The exact composition of ash is feedstock

dependent and cultivation practice dependent, but there is a strong relationship between nutrient

uptake requirements and total ash content. Nonetheless, the following table presents an

acceptable generalization that provides an indication to the main resulting metal oxides:

Table 29 Ash Composition Generalization

Metal Oxide SiO2 K2O CaO P2O5 MgO SO3 Na2O Ash Proportion 35 30 15 10 5 2.5 2.5

Ash mainly consists of silicon (oxide), which in the event of large soil removal through harvesting

procedures can lead well over 50%. Explained in the earlier handling procedures (Section 2.2), all

soil contamination will be washed out from the feedstock input stream, meaning the 35% value is

representative of the actual amount contained in the biomass material. This composition

generalization was also employed in Chapter 4 (Appendix 3.1) for determining the energy content

upon combustion, resulting in 2.89GJ/ton and 2.43GJ/ton average energetic and exergetic

output. The energetic output of the metal oxide formation is not particularly high and little

deviation would occur by using the exact feedstock specific composition. However, at this last

stage in the biorefinery concept all the unreacted, unconverted, and unseparated biochemicals

will form the ash-rich stream. Combined they are feed into a combustion unit for the generation

heat and power at much higher calorific values than the ligands alone. The power conversion

efficiencies and process conditions will be handed in the next section. In addition to the

moderate levels of energy that can go towards reducing the internal process energy requirements

of the biorefinery, the residue solid stream will still contain the metal oxides or “ash”. Several

potential applications will be described for the ash that have the possibility to mitigate other fossil

fuel intense production routes, unrelated from those of the petrochemical industry.


7.2 Applications

7.2.1 Combustion

In Section 6.2.4, the fast-pyrolysis unit was described in detail to how the aromatic components

can be yielded from the lignin-rich stream. The char residues (unreacted material) and the vented

gases (small hydrocarbons) will be combined and subjected to combustion. This ash-rich stream

can be directly fired in a furnace yielding the components higher heating value (HHV) because

the stream is completely water-free. The basis for calculating the energetic and exergetic output

of the ash-rich streams is based on the group contribution figures for each component in the

stream as previous determined (Appendix 3.2). Even more so then with the other biochemical

components, this stream is incredibly feedstock dependent. The starting biomass feedstock

biochemical composition in combination with the various biorefinery product yields will present

each ash-rich stream with a very unique chemical composition. The resulting energy output upon

combustion cannot be determined at this stage, see Chapter 8 for the combined biorefinery

results. Here the power production efficiency can be determined. Several biomass power

generation technologies have reached technical maturity. The thermal efficiency range for

modern direct combustion units reveals 75 – 92% with a strong dependency on installation scale.

A similar installation scale factor is present for electric generation with smaller scale units

achieving 30% and 35% for larger operations98. In Europe the state-of-the-art biomass

combustion system can achieve an overall thermal power efficiency of 82%99. A combined heat

and power unit (CHP) is the obvious choice, to produce both a portion of electricity and thermal

energy. The 82% total efficiency can still be maintained, where as a realistic electric efficiency of

33% is possible. At those conditions the exergetic efficiency of the thermal component is 29%.

These efficiencies will from the basis for the internal heat and power production capacities.

7.2.2 Post-combustion

With the rising interest and establishment of biomass gasification and combustion units

worldwide, new solutions and opportunities are being researched to deal with ash100. The ash

from coal combustion has been investigated for many decades with several novel solutions101.

Currently, the fast-paced expansion of coal power plants is leading many sites to simply dump the

ash in a sort landfill or ash pond. The same disposal route should not be performed with ash

originating from biomass.

7.2.2.1 Building Material

The easiest and lowest product option is to blend the ash into the production of building

materials, especially concrete and similar construction materials. They have large production

capacities in the megatons scale and mixing in ash is possible at low blends without any

measurable effects on the structural integrity or physical properties. Ash affectively displaces a

portion of stone mining and production. Concrete as such has a rather low cumulative process

energy (between 1.3 and 1.7GJ/ton) with the portion associated to stone being under 1.0GJ/ton.

This ash product option should be considered the lowest utilization form.

7.2.2.2 Fertilizers

What goes in must come out. In the most ideal situation all the nutrients that were removed by

the biomass crop would be brought back to the field of origin in the form of ash; a closed-loop


system with the eventual input reduction of artificial fertilizers to zero. Sadly this is not possible

nor is it foreseeable in the near future due to the following reasons100, 102:

1. Loss of nitrogen

Nitrogen is the single most important and energy intensive fertilizer. In plant matter it is

fixated as protein and physically removed from the biomass feedstock stream as the

desired functionalized nitrogen-based chemicals. Any residual nitrogen is later emitted as

unusable gas (NOx) from the combustion unit.

2. Insolubility of phosphorous

The second most important and energy intensive fertilizer is rendered ineffective.

Through the thermal combustion process the resulting phosphorous oxide molecule has

a very poor solubility in soil and cannot be effective utilized by crops. Release of the P

nutrient is too slow for dedicated short-rotation bioenergy crops.

3. Heavy metal content

Even when originating from clean, untreated sources of biomass trace levels of heavy

metals like cadmium, lead and zinc are present in the ash. The use of catalysts and the

gradual corrosion of the equipment apparently end up in the ash. And while the

concentrations are fairly low (1-10ppm), these levels have a growth limiting effect on

biomass production.

4. Government legislations

In addition to limiting the biomass yields, the heavy metal content contribute to the

overall level of contaminants and can prevent application approval. Furthermore, while

the EU does permit wood-based ash fertilizers for biological farming, it (and thus the

Netherlands) do not permit the use of other biomass-based ashes for fertilizer

applications in respect to environmental protection.

5. Wealthy Dutch farmers

Situating the biorefineries in the midst of the Rotterdam petrochemical cluster means that

the final ash product stream would enter the local market. Ash has little agronomic value

on the expensive farm lands of Holland and farmers will not accept ash on their fields

unless mandated to do so. Alternatively shipping an ash stream back to the original fields

is economically and energetically ludicrous.

7.2.2.3 Ash Upgrading for Fertilizers

There are several exceptions to the above reasons that can permit ash to be used as a recycled

source of fertilizers. The first generation ethanol biorefineries in Brazil, for example, produce a

co-product stream called vinasse6. Vinasse is the bottoms from the distillations columns and

provide an excellent source of ferti-irrigation water while covering the bulk portion of the

adjacent farms potassium nutrient demand. Although proving effective, it is a temporary solution

as the full chemical biorefinery would no longer produce that particular stream. Still, utilization of

potassium and some of the other nutrients is alluring. Acidic treatment on the ash can be

employed to dissolve and separate out the more useful nutrients and brought directly into the

standard fertilizer production schemes. The downside is the energy intensity, for the operation is

more intense then starting with virgin material. Another option is to simply mix and blend in a

portion of the ash into the complex fertilizer formulations. The level of contaminants would

decrease and blending would contribute to a partial reduction of material and indirect fossil fuel


consumption. As long as the biorefineries are in their introductory phase with limited production

scale fertilizer blending is a feasible short-term option.

7.2.2.4 Land Reclamation

Chemical producing biorefineries for fossil fuel mitigation are a long-term solution for the

sustainable feedstock acquisition within the petrochemical industry. Applications for ash should

be addressed for their long-term solutions. One solution is both long-term and is particularly well

suited to the Rotterdam petrochemical cluster location. Mixed in some soil, sand and Dutch

technology and new land mass (polder) can be created with the eventually large streams of ash.

Managed properly over a 25 year course, the polder will become completely fertile. To keep the

polder stable and provide an organic content to the “soil” a perennial crop species is required. It

has been argued that leguminous species will have specific and beneficial application options

within the biobased economy that make use of their nitrogen fixation properties103. Once the

structural integrity of the polder is stable through adequate root structure of the perennial crop,

leguminous crops could be cultivated at these later stages to naturally fix nitrogen into the soil.

Over a course of several years the eventual nitrogen content of the soil could be brought to the

point where it is considered “fertile”. This land reclamation option would overcome the five

listed drawbacks of immediately and directly using ash for fertilizer applications. Here ash will

eventually be supplied to arable lands as a fertile nutrient-rich soil, a fertilizer replacement option.

It is essentially a large-scale, long-term biorefinery compost hep. The fossil fuel mitigation values

will be taken from Chapter 5 for the nutrients, despite the fact that the energy intensity of the

fertilizer industry will certainly decrease over the next 25 years.


8 Biorefinery System

8.1 Construction of Facilities

Producing chemicals from biomass requires the construction of new biorefinery facilities. The

advantage of producing the same chemicals as already contained in the petrochemical industry is

that the downstream infrastructure will remain unaltered. Nonetheless, the biomass feedstock

processing stages require new facilities and costs indirect fossil fuel energy for their manufacture.

EcoInvent, the LCI database, uses a general construction materials input of 0.11kg/kg product

for chemical production facilities. A biorefinery falls under that category. It requires several key

building materials; concrete, steel and glass. Concrete represents the bulk of the materials

followed by steel and lastly glass. Other construction materials (like paints) are in comparatively

minute quantities.

Table 30 Major construction materials process energy and exergy

Material Proportion CED CExD Energy Exergy

Concrete 95% 1.5 3.2 1.43 3.04 Steel 4.5% 22.5 7.4 1.01 0.33 Glass 0.5% 42.3 28.1 0.21 0.14

The average fossil fuel energy requirements for the construction materials is 2.65GJ/ton4. The

exergy value is estimated to be 3.51GJ/ton, meaning that at 0.11kg/kg an extra 0.27GJ/ton

energy and 0.35GJ/ton exergy must be added to the final biorefinery process energy.

8.2 Internal Process Energy

Throughout this chapter each of the steps along the full chemical biorefinery production route

were assessed for internal process energy and were intentionally expressed in thermal, electric and

indirect energy. In the ash section, the combustion unit was discussed and assessed for the heat

and power conversion efficiency. It will partly displace the internal thermal and electric energy

portion. It is however unlikely that the ash-rich stream will provide enough thermal and electric

energy for the entire biorefinery from any of the biomass feedstocks nor biorefinery layouts.

Furthermore, the high-metal chemical composition of the ash stream can cause internal

combustion problems, therefore co-firing is a likely solution. Coal is the best candidate with the

residual ashes following the same land reclamation route as for the biomass ashes. A coal power

plant has a CHP efficiency of 35% electric and 50% thermal energy (30% exergy). In the case

where more electricity is needed then the coal CHP at 35/50 can provide than electricity from

the grid will be imported via natural gas turbines operating at 45% electric energy efficiency. In

cases where more thermal energy is needed a direct coal furnace operating at 85% thermal

efficiency (50% exergy) will cover the difference. Thus the total internal process energy will be

related to the amount of related by external fossil fuel energy input. The amount produced by the

biorefinery combustion unit will be handled separately as a mitigated fossil fuel product. The

graphics used in Chapter 8 provide the best visual insight to the rational.

8.3 Local Production

In Chapter 6, several of the biomass feedstocks requiring vast transportation distances had

particularly high logistical input energy involved in preparing and shipping fresh biomass over the

long-haul transportation distances. Several aspects of the biorefinery can be performed on-site


(or close to the agricultural lands) essentially on a smaller scale. Figure 12 presents a simplified

overview of the total biorefinery system for a simple carbohydrate-rich feedstock (e.g. sugar

cane); an analogous layout is present with the other feedstocks, such as with fatty acid-rich

biomass. The red dotted line indicates which process steps are better performed locally and those

that are better performed at Rotterdam’s petrochemical cluster on the larger scale. Shipping (in

this case) ethylene and a dehydrated product mixture containing lignin, protein and ashes, will

vastly reduce the logistical input energy and thus the total agricultural energy input. The size and

moisture reduction step can also in several cases be avoided. An additional energy input is

introduced by preparing the dehydrated “half-product” mixture. The best suited dehydration unit

is the filter press and conveyor belt combination as handled in Chapter 6. The resulting impact

on the total agricultural energy input can only be determined once the entire biorefinery system

with the overall biochemical conversion yields has been incorporated, see Chapter 8.

Figure 12 Simplified Total Biorefinery System with Half-Product Separation

Handling

(Si zing/Soi l removal)

Biomass(Simple C arbohydrate Rich)

Soil

Sugar Rich

N-Chemicals

Aromatics

EthyleneEthanol

Separat ion

Processing Residues

Protein Rich

Lignin Rich

Fertilizers

Electricity

Heat

Simple Carbohydrate

Processing

Glucose Processing

Complex

Carbohydrate Processing

Ethylene Processing

S/L

Separat ion

Amino Acid

Separation

Lignin Processing

Aromatics

Separat ion

Ash/Residuals Processing

Protein

Processing

On-site (Small Scale)

Petrochemical Cluster (Large-Scale)

Dehydration Unit

Handling

(Si zing/Soi l removal)



SoilSoil

Sugar RichSugar Rich

N-ChemicalsN-Chemicals

AromaticsAromatics

EthyleneEthyleneEthanol

Separat ion

Processing ResiduesProcessing Residues

Protein RichProtein Rich

Lignin RichLignin Rich

FertilizersFertilizers

ElectricityElectricity

HeatHeat

Simple Carbohydrate

Processing

Glucose Processing

Complex

Carbohydrate Processing

Ethylene Processing

S/L

Separat ion

Amino Acid

Separation

Lignin Processing

Aromatics

Separat ion

Ash/Residuals Processing

Protein

Processing

On-site (Small Scale)

Petrochemical Cluster (Large-Scale)

Dehydration Unit

8.4 Results and Discussion

There are no results to discuss in this chapter, as it was an assessment of the internal and indirect

process energy and exergy required for each stage of the biorefinery for chemical production.


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Chapter 8 Fossil Fuel Savings

Mitigated energy and exergy in producing chemicals via the biorefinery concept

Ben Brehmer

Dissertation Report


Colophon



ISO 9001:2000.

Title Chapter 8 – Fossil Fuel Savings Author(s) Ben Brehmer A&F number - ISBN-number - Date of publication 1. October, 2008 Confidentiality No OPD code - Approved by - Agrotechnology & Food Sciences Group B.V. P.O. Box 17 NL-6700 AA Wageningen Tel: +31 (0)317 480 150 E-mail: [email protected] Internet: www.afsg.wur.nl © Agrotechnology & Food Sciences Group B.V. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd, opgeslagen in een geautomatiseerd gegevensbestand of openbaar gemaakt in enige vorm of op enige wijze, hetzij elektronisch, hetzij mechanisch, door fotokopieën, opnamen of enige andere manier, zonder voorafgaande schriftelijke toestemming van de uitgever. De uitgever aanvaardt geen aansprakelijkheid voor eventuele fouten of onvolkomenheden. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system of any nature, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the publisher. The publisher does not accept any liability for inaccuracies in this report.


Abstract The summation of the previously determined total biomass acquisition energy intensity in combination

with the total bioprocessing energy requirements are used to determine to potential fossil fuel energy and

exergy savings for each chemical biorefinery cropping system. The ultimate purpose is to present

the benefits of employing biomass as a feedstock for chemicals by using illustrative and concrete

results derived from the developed methodology. The results are used to validate the notion that

functionality upheaval is something to strive for in industrial biomass applications. The results are

expressed in graphical from, numerical form and accompanied by tables and descriptions for the

16 selected crops alongside the accompanying crop guide. The most important impact

assessment terms: savings per produced chemicals (production efficiency) and savings per arable

land area (land use efficiency), provide the information necessary to determine the optimal

biorefinery cropping system. No single optimum was determine but many improvement options

are present for the chemical biorefinery cropping systems. The main consideration of this chapter

has been to illustrate that nothing is simple or clear-cut but and that chemicals should present a

more attractive conversion option for biomass than energy or fuels.

Key Words:

Fossil fuel, biomass, replacement, results, chemicals, (bio)refinery



Content

1 Introduction 395


2 Compiling Results 397

2.1 Crop Guide 397

2.2 Results 397

2.2.1 Graphs 397

2.2.1.1 General Concept 397

2.2.1.2 Construct Description 397

2.2.1.3 Calculated Values 399

2.3 Production Figures 399

2.3.1 Description 400

2.3.2 Improvement options 400

3 Crop Guide, Results, and Discussion 401

Beta Vulgaris L – Sugar Beet 402

Brassica Napus – Rapeseed 406

Elaeis Guineensis Jacq. – Oil Palm 410

Glycine Max – Soya Bean 414

Helianthus Annuus – Sunflower 418

Manihot Esculenta – Cassava 422

Medicago Sativa – Lucerne 426

Nicotiana Tabacum L. – Tobacco 430

Lolium Perenne – Grass 434

Panicum Virgatum – Switchgrass 438

Saccharum Officinarum L. – Sugar Cane 442

Salix Alba – Willow Tree 446

Solanum Tuberosum – Potato 450

Sorghum Bicolor – Sweet Sorghum 454

Triticum Aestivum – Wheat 458

Zea mays L – Maize 462

4 Optimal Biorefinery Concept 467

4.1 Overall Results 467

4.2 Overall Comparison 467

4.2.1 Energy 467

4.2.2 Exergy 469

4.2.3 Combined Performance 470

4.3 Discussion 470

5 Conclusion 473

5.1 Ben’s Tips 473



1 Introduction In the previous chapters, information relating to and required for the mass and energy balances

were compiled using the standardized methodology enabling a matrix calculation of energy (and

thereby also exergy) inputs all corresponding to biomass propagation and biomass conversions:

the total biomass acquisition energy intensity and the total bioprocessing energy requirements for the

biorefinery were determined for each potential cropping system. At this stage the various selected

cropping systems can be combined with the appropriate conceptual chemical biorefinery layout.

This chapter is therefore, in effect, the summation of all the previous work to illustrate the

potential fossil fuel energy (and exergy) savings that can be obtained by employing biomass

feedstocks for bulk petrochemical products.

Most industrial biomass application routes focus on the potential calorific values of utilizing the

biomass feedstocks; studying the fossil fuel energy replaced upon combustion. This holds true

for nearly all applications from straight bioenergy to biogas, to biofuels, and even to the most

complex gasification systems. And while an internally combined heat and power combustion

(CHP) unit is envisioned for each of the potential chemical biorefinery layouts, it does not

represent the main goal nor encapsulate the greatest replacement potential. Here the focus has

been on providing an alternative feedstock for existing petrochemicals. True, industrially

cultivated biomass feedstocks yield a carbon-based feedstock which have, for the large part, a

significantly lower fossil fuel energy intensity then the contained calorific value. Yet, in this

chapter the results of the energetic and exergetic cradle-to-factory gate assessment will reveal that vast

enhancements of fossil fuel energy savings potential can, in most cases, be a multiple of several

magnitudes higher when employed for petrochemical production routes.

Naturally chemicals used in our throw away society will eventually end up in land-fills or

increasingly (as is the case in more environmental conscience societies) in incinerators. Heat and

power can be captured upon their combustion, hence expressing their contained potential

calorific value. One cannot include this processing stage along the product’s life cycle because

chemicals originating from biomass and fossil fuels (i.e. naphtha or natural gas) will follow the

same end-of-pipe path. Many previous and current LCA chain-based studies are fixated on the

idea of including calorific values at some stage for the biomass feedstock. In seems the norm is to

allot biomass a calorific value, typically dubbed as biomass energy. This is poor practice and cannot

be performed following the principles of comparative life cycle assessments. In this chapter, the

procedures to assess, visualise, and obtain the resulting fossil fuel energy savings potential should

make it clear that such common practices are contradictory. And while including the traditional

crude oil calorific values must be included, it is not in contradiction. Searching and assessing

potential solutions to replace the fossil fuel component in chemicals must include the fossil fuel

feedstocks. They follow the criteria set by the cradle-to-factory gate (or limited LCA) concepts and

are also included in assessing the total biomass acquisition energy intensity which was determined in

Chapter 6. Additionally calculating a biomass calorific value would be counterproductive and is

just incorrect methodology.

The heart of the results are the chemical biorefinery graphs which are meant to illustrate the

process energy (and in a separate graph, exergy) originating from the traditional feedstock routes


(naphtha and gas) in comparison to the unconventional potential alternative feedstock routes, i.e.

biomass. The busy graphs and scatter of comparative chemical products visualise the cumulative

energy (and exergy) demand of both production routes. It has been chosen to illustrate the logic

and conclusive results of upholding the functionalized groups of biochemicals in biomass.

The graphs are accompanied by numerical results and are separately discussed for the various

biomass cropping system as internal comparisons. Some major conclusions can be drawn

between particular regions and particular types of biomass feedstock streams, in the sense of

advantages and disadvantages. A major aspect of the final objective is to determine the optimal

biorefinery cropping system. Such information can help steer research directions and guide future

development of biomass cropping systems while indicating via strengths and potential weakens

the best chemicals to pursue.

The importance of striving for maximum land use efficiency of biomass employed within the

various alternative energy options has been stressed throughout the previous chapters: energy

consumed (and in this chapter saved) per land area, GJ/ha. Even though this does not solve the

apparent dilemma of the food vs. fuel and additionally vs. chemicals issue, it does provide an

indication of how to best cope with a future of increased land use competition. A portion of the

criteria to assess the optimal biomass cropping system layout relies on land use efficiency as a

indication factor. As important as it is, it is but one aspect, the other being the efficiency or fossil

fuel energy savings potential per chemicals actually being produced. Both resulting factors are

investigated in detail using the compiled and corresponding data.

1.1 Chapter Purpose

In the following chapter, all the previous compiled and calculated data pertaining to energy and

exergy input streams of biomass propagation and biorefinery conversions are brought in relation

to the traditional fossil fuel-based chemical production routes. The total embedded fossil fuel

energy in the proposed biorefinery systems are herein actively compared against the existing

petrochemical refinery to determine the level of potential fossil fuel savings in energy and exergy

terms. The ultimate purpose is to present the benefits of employing biomass as a feedstock for

chemical production by using illustrative and concrete results derived from the developed

methodology. These results validate the notion that functionality upheaval is something to strive

for in industrial biomass applications.


2 Compiling Results

2.1 Crop Guide

In the following section, the crop guide as previously described in full detail within Chapter 4 is

presented. It has been intentionally placed in this section as opposed to Chapter 4 to have the

various results of the biorefinery cropping systems alongside each other. It is insightful having all

the relevant information pertaining to the crop’s agricultural practices and considerations

together with the results and eventual discussion. This is mainly due to the fact that the results

are a direct function of the chosen biomass production systems and location. Any alternation in

the harvesting approach or location will have a direct influence on the results. This implies that

the results are meant as a guide for the crops and their corresponding regions, but are actually

variable and may not represent the best choice in regards to the chemical biorefinery layout for

the maximum potential fossil fuel savings.

2.2 Results

Each of the 16 selected crops in their respective locations have been determined following the

matrix-based calculations for the conceptual biorefinery layout. The results are expressed in

graphical from, numerical form and accompanied by tables and descriptions. Each form of the

results are used to indicate the potential fossil fuel energy and exergy savings of the biomass

cropping system for chemical biorefineries.

2.2.1 Graphs

2.2.1.1 General Concept

Immediately succeeding the crop guide are two pictorial representations illustrating the total

cumulative fossil fuel energy and exergy involved in arriving at an array of chemical products

when considering the various process routes from both the traditional petrochemical and

alternative biomass originating feedstocks. They are meant to visualize the methodological

calculation construct adhering to the work described in the previous chapters. The major results

of the graphs are presented in the brackets: the total CED & CExD (cumulative energy and

exergy demand) involved in processing the resulting array of chemical products from the biomass

feedstock route compared to the equivalent naphtha and gas feedstock route (traditional

petrochemical route). The biomass route is on the right-side and illustrated in green while the

traditional petrochemical route is on the left-side and illustrated in red.

2.2.1.2 Construct Description

With the primary goal focused upon producing chemicals and not

biofuels nor bioenergy there is a noticeable header: “next generation”,

explicitly meant to point out the developmental leap from biofuels

to dedicated chemical biorefineries. Listed below are the main

technologies used to convert the biomass feedstock into the main chemical products. They do

not represent every technology involved in converted biomass, but are the variable technological

options of the biorefinery layout, as described in Chapter 7.


Start with the biomass crop image on the right-hand side. Written beneath are the

regional choice and accompanying best practice yields of the crop in both standard

agricultural terms and total dry weight figures. The first energetic and exergetic

value written below “biomass” is a summation of the agricultural and logistics input

according to Chapter 6 in terms of GJ per ton dry weight, otherwise referred to as

“total biomass acquisition energy and exergy intensity”. Each of the biochemical

constituents is presented as their individually allotted feedstock portion. It is a

calculation functionally related to the original mass proportion and additionally as

the useable mass based on the conversion of the final chemical product. For example, simple

carbohydrates are converted to ethylene: the “GJ/ton” value is

expressed in terms of the final product (ethylene) and not of the

original biochemical constituent (simple carbohydrates). Meaning that

the values do not represent the allotted biochemical constituents

values solely but already as the feedstock proportion of the final

chemical product. For this reason, they are typically several factors

higher than the actual biomass acquisition energy and exergy intensity.

The dotted connecting arrows represent the internal process energy and exergy demand. An

intermediate figure is present for several chemical products routes

which indicate either a chemical product or a feedstock that are in

multiples. For example, ethylene can originate from three different

biochemical constituents: simple-, complex C5- and complex C6-

carbohydrates. Each constituent has an independent process route

with the intermediary indicating their independent process energy and

exergy demand. All the dotted connecting arrows led to a chemical product representing the total

cumulative energy and exergy demand. The resulting cumulative

biorefinery energy demand is determined by a direct mass allocation of

the proportional chemical product yields resulting from the biorefinery.

The same proportional mass ratio was used to determine the

corresponding petrochemical mixture, also indicated by the (red)

parenthesis; following the total cumulative energy and exergy demand of the traditional fossil

fuel-based production routes.

On the biomass chemical product side (left, green) the boiler output is listed

in direct energy and exergy terms. It is used to offset a portion (if not more)

of the internal heat and power processing requirements; this value is already taken into account in

the final biorefinery cumulative fossil fuel energy and exergy value. The offset energy and exergy

potential as described in Chapter 2 is a function of the cumulative fossil fuel energy that would

have otherwise been required. In cases, where the boiler produces more heat than necessary in

the biorefinery, the off-heat could theoretically be used to replace a fuel-oil burner. Similarly for

excess electricity which would replace an energy mix of coal and natural gas at limited production

efficiencies. It is here therefore imperative that any excess energy be brought into the grid – at

this stage this considered to take place.


The production of amine-based chemicals originating from proteins

(and subsequently amino acids) are too many to present individually.

There are 20 independent processing routes leading to 15 unique chemical products. To avoid

the obvious issue of cluttering, the protein processing routes have been grouped together to yield

“amine chemicals”. Ammonia is excluded from this grouping as it is a by-product of the main

amine-based chemicals for it is generally cleaved off as a result of the various chemical reactions.

Therefore, the amine chemicals figure indicated in the pictorial representation is the average of all

the 15 separate products, meaning the potentially heavy deviation of particular chemicals

products cannot be graphical visualized.

2.2.1.3 Calculated Values

Presented in the pictorial representation are several key pieces of information and results

calculated by the biorefinery layout. The following are commonly used in biomass and other

alternative energy production system to express their efficiency.

Net Energy Value & Breeding Factor

Net Energy Value (NEV) is the ratio of the output energy or

replaced energy contained in the products compared to the total

energy invested. It is common in practically all biomass application system to give an indication

of energy in versus energy out. The calculation is straightforward:

( )( )OutputBoilerEnergyyBiorefiner

OuputBoilerEnergyeryPetrorefinNEV

__

__

−

+=

The breeding factor (BF) is the inverse expressed in a percentage form. It is meant to indicate the

percentage of non-renewable energy contained in the alternative feedstock.

Fossil Fuel Energy Savings

NEV and BF may be useful indication factors for bioenergy

and biofuel systems but are poorly adapted at biorefinery

systems. They have been designed for calorific-based

assessment systems; chemicals do not fall into this category,

yet it is nevertheless advisable to present the values for comparison to illustrate their

shortcomings. The most important impact assessment figures for a chemical biorefinery system

are relative fossil fuel energy savings. The savings can be related to many different base terms; to

amount of chemicals produced, to the amount biomass utilized and to land use consumption.

Alongside the oil barrel image is the “fossil fuel energy and exergy savings”: “GJ/ton chemicals” indicates

how much fossil fuel energy is saved per mix of the chemicals produced, “GJ/ton biomass”

indicates how much fossil fuel energy is saved per ton of dry feedstock, and the “GJ/ha”

indicates how much fossil fuel energy is saved per arable land area. These values are used to

determine the optimal biorefinery cropping system.

2.3 Production Figures


Proceeding the pictorial representations is a table listing an overview of the biorefinery system

and the overall savings. Firstly, all the chemicals and their production volumes are presented: in

terms of quantity per biomass feedstock (ton/ton crop), in terms of quantity per land area

(ton/ha), and in relative production terms of the chemical biorefinery mixture (%). Based on the

production mass relation the contribution to the total biorefinery energy and exergy demand is

listed for each chemical produced. This is one of the key differences as opposed to many other

LCA studies in the field of biomass applications, by using thermodynamics as the basis subjective

economic allocation weightings are avoided.

2.3.1 Description

Beneath the table is a short bulleted list describing interesting and unique aspects relevant to the

biorefinery cropping system. It is highly contextualized for the particular crop and helps guide the

reader to aspects which for that specific crop influence the resulting fossil fuel energy savings.

For many of the cropping system large quantities of minerals (or ash) can greatly decrease the

overall energy savings potential. Considering that the most energy intensive nutrient, nitrogen,

cannot be used as a fertilizer in land reclamation steps and for the most part contributes to the

protein molecules the savings potential of the residual nutrients (or ash) is vastly lowered. The

ash or recycled nutrients are a function of the biomass acquisition energy input as it is destined to

be a chemical product, potentially replacing fertilizer production. For this reason fertilizer

production from biomass can be intense but despite the minor to negative replacement potential,

in a world of foreseeable material and energy scarcity it is imperative to include a recycling step

for the nutrients. This step is necessary for long-term biomass schemes meaning those crops with

high ash output may only temporarily improve their overall biorefinery energy savings.

2.3.2 Improvement options

Many improvement options are present for the biorefinery cropping systems. Should any clear

and straightforward alterations in the biorefinery layout or cultivation practices be present to

further increase the fossil fuel energy saving value, they are listed. For several of the crops a

change in location and/or stressing on a certain chemical product by omitting a portion of the

standard (chosen) chemical products mix is frequent.


3 Crop Guide, Results, and Discussion

Crop Guide, Results,

& Discussion


Beta Vulgaris L – Sugar Beet Common Names Sugar beet, beetroot, chad, mangel, spinach beet

Classification Annual or biennial herb, C-3

Appearance Numerous 1.5 – 2m large glabrous dark-green Leaves, oval, tapering to a petiole, 5 - 10 cm thick conically shaped white bulbs

Varieties Many available, to tolerate: Al-ions, disease, frost, fungus, HF, high pH, Mn, salts, nematode, phage, poor soil, slope, smog, SO2 and high disease resistance

Genetically Modified Varieties Stringent restrictions, testing only, none grown in Europe

Brief Description About 1/3 of the world sugar production derives from the sugar beet. Through crop selection the sugar yields have increased from 5 to 20% in the past hundred years.

Growth Details Native Area: Northwest Europe Location: Europe, North America and China Climate: Temperate – cool, best with mild frost periods and good sun exposure

Temperature: 5 - 26°C Rainfall/Irrigation: 550 – 750mm, usually not above 880mm, can tolerate up to 2300 – 3150mm Soil Type: Deep, friable well-drained soil with organic matter, poorly on clay Soil Acidity: 4.2 – 8.2 pH, best between 6.0 – 6.8 pH Plantation: Drilled at 1.5 – 2cm intervals, 30 – 45cm row spacing and 1.3 cm deep Shallow seeding to control weed growth competition Seeding Rate: Existing crops must be cold shock treated to produce a seed 4 – 6 kg/ha, seeds germinate irregularly, seed screening advised 35000 – 90000 plants/ha Companion Crop: No, but rotated Weed Control: Seedling stage poor competitor to weeds Cultivation: Summer plant, May – June, mostly hand work or small tractor cultivators Must be rotated, not with Brassica crops, i.e. kohl Harvesting: In first year of growth, autumn to winter, mechanical beet harvester

Nutrient/Fertilizer Requirement Utilizes nutrients from organic manures (farmyard manure, compost, organic wastes) quite well The plant takes only half of the nutrients up, common practice to leave the foliage on fields Over fertilization will reduce the yield of sucrose in the beet

Yield Dependent Macronutrient Uptake

0

50

100

150

200

250

300

350

400

450

500

0 20 40 60 80 100 120

Tuber Yield (ton/ha)

Total Plant Uptake (kg/ha)

N

P2O 5

K2O

CaO

MgO

SO3

Poly . (N)

Poly . (P2O5)

Poly . (K2O)

Poly . (CaO)

Poly . (MgO)

Poly . (SO3)

Yield Dependent Micronutrient Uptake

0

500

1000

1500

2000

2500

0 20 40 60 80 100 120

Seed Yield (ton/ha)

Total Plant Uptake (g/ha)

Fe

Mn

B

Zn

Mo

Cu

Po ly. (Fe)

Po ly. (Mn)

Po ly. (B)

Po ly. (Zn )

Po ly. (Mo)

Po ly. (Cu)


Yield Normal Conditions: 30 – 60 ton tuber/ha (increase with further hybrids) 47.8 ton tuber/ha (EU-15 average), 57.6ton/ha (Germany : 5-year average) Optimal Conditions: Well beyond 100 ton/ha Worldwide Cultivation: 5.84 million hectares at 41 ton/ha

Chemical Composition* (Based on dry weight)

Constituent Beet Leaves

Moisture Content 76.6% 86.4% Cellulose 3.0 27.1 Hemicellulose 4.0 32.5 Lignin 0.7 3.0 Sucrose 70.0 - Other Sugars 8.6 - Protein 1.8 23.5 Fats 1.2 0.3 Minerals 3.3 2.1 Ash 7.4 4 Others - 7.5

Beet/tuber represents 62% of the total dry weight of the plant *Strongly dependent on all growing factors, location and nutrient levels Lower Heat Value: 16600 kJ/kg (beet only), 19900 kJ/kg (whole plant) Higher Heat Value: 17700 kJ/kg (beet only)

Detailed Information Beet Leaves

Free Amino Acid g/kg % g/kg %

Alanine Unknown Unknown

Isoleucine Trace 19.3 16.86

Leucine 0.58 11.74 16.9 14.76 Methionine 0.43 8.70 3.1 2.71

Phenylalanine 0.40 8.10 14.3 12.49

Proline Unknown Unknown Tryptophan 0.79 15.99 0.5 0.44

Nonpolar & Hydrophobic

Valine 0.49 9.92 14.3 12.49

Asparagine Unknown Unknown Cysteine 0.13 2.63 0.7 0.61

Glutamine Unknown Unknown

Glycine 0.41 8.30 Trace Serine Unknown Unknown

Threonine 0.11 2.23 10.8 9.43

Polar & Hydrophilic

Tyrosine 0.22 4.45 Trace Asparagic Acid Unknown Unknown

Acidic Glutamic Acid Unknown Unknown

Arginine 1.2 24.29 15.3 13.36

Histidine 0.13 2.63 4.7 4.10 Basic

Lysine 0.05 1.01 14.6 12.75

Total 4.90 (27.2% of Protein) 114.4 (48.7% of Protein)

Comments The yields appear very high, but what must be realised is that it is a rotational-based crop. This means that the average yields over a longer period of time are significantly lower, yet other crops can be planted in the field, for example legumes, to naturally restore nitrogen nutrients.


Comparative Graph

Energy

Next Generation Phenol: 99.7GJ/tonToluene: 111GJ/tonStyrene: 124GJ/ton

20

10

Crude Oil 44.9GJ/ton

CRACKER

Traditional Petrochemical Route

Potential Chemical Biorefinery Route0GJ/ton

45.1

60

Styrene: 83.9GJ/tonAmine Chemicals: 83.2GJ/ton80

70

- Chemical vs. Biomass CED

- Raw Fossil Fuel Input

Net Energy Value (NEV): 2.3Breeding Factor: 43%

Ammonia: 31.0GJ/ton

Fertilizers: 42.3GJ/ton

Amine Chemicals: 25.1GJ/ton

Biomass

1.97GJ/ton

Sugar BeetGermany

100ton/ha beets

29.2tota lDW/ha

42.8

40

50

30Complex C6

Carbohydrates: 29.3GJ/ton

Complex C5 Carbohydrates: 26.6GJ/ton

Lignin: 298GJ/ton

Protein:

45.8GJ/tonAsh: 42.3GJ/ton

112

Ammonia: 28.5GJ/ton

Ethylene: 67.0GJ/ton

Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton



32.3GJ/ton chemicals

10.0GJ/ton biomass

292GJ/ha

26.7GJ/ton

59.1GJ/ton

Boi ler: 6.2GJ/ton

17.2


Un-utilizedBiochemicals:

0GJ/ton

Simple Carbohydrates: 3.5GJ/ton

Sugar-to-Bioethanol (Mi lli ng)

Lignocellulose-to-Bioethanol (AFEX)

Protein Extraction (Protease )

Lignin Aromatics (Fast-Pyrolysis)

Next Generation Phenol: 99.7GJ/tonToluene: 111GJ/tonStyrene: 124GJ/ton

20

10


CRACKER



45.1

60


70




Ammonia: 31.0GJ/ton



Biomass

1.97GJ/ton

Sugar BeetGermany

100ton/ha beets

29.2tota lDW/ha

42.8

40

50

30Complex C6



Lignin: 298GJ/ton

Protein:

45.8GJ/tonAsh: 42.3GJ/ton

112

Ammonia: 28.5GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




10.0GJ/ton biomass

292GJ/ha

26.7GJ/ton

59.1GJ/ton

Boi ler: 6.2GJ/ton

17.2



0GJ/ton






Exergy

Next Generation Phenol: 108GJ/tonToluene: 113GJ/tonStyrene: 126GJ/ton


0GJ/ton

20

10


CRACKER



40.5

60


70

- Chemical vs. Biomass CExD


Net Exergy Value (NExV): 3.0Breeding Factor: 34%

Ammonia: 23.0GJ/ton



Biomass

2.17GJ/ton

Sugar BeetGermany

100ton/ha beets

29.2tota lDW/ha

37.9

40

50

30

Complex C6


Complex C5


Lignin: 328GJ/ton

Protein:50.4GJ/ton

Ash: 46.6GJ/ton

116

Ammonia: 16.4GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton


Fossil Fuel Exergy Savings


20.9GJ/ton biomass

610GJ/ha

-7.7GJ/ton

59.9GJ/ton

Boi ler: 5.1GJ/tonSimple Carbohydrates: 3.8GJ/ton

8.9








0GJ/ton

20

10


CRACKER



40.5

60


70




Ammonia: 23.0GJ/ton



Biomass

2.17GJ/ton

Sugar BeetGermany

100ton/ha beets

29.2tota lDW/ha

37.9

40

50

30

Complex C6


Complex C5


Lignin: 328GJ/ton

Protein:50.4GJ/ton

Ash: 46.6GJ/ton

116

Ammonia: 16.4GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton




20.9GJ/ton biomass

610GJ/ha

-7.7GJ/ton

59.9GJ/ton


8.9







Overview Savings

Chemicals Biorefinery Production Total Biorefinery

Name ton/ton crop ton/ha % Energy Exergy

Ethylene 0.216 6.32 70.1% 18.72 -5.38

Phenol 0.002 0.06 0.7% 0.19 -0.05

Styrene 0.002 0.07 0.8% 0.21 -0.06

Toluene 0.002 0.06 0.7% 0.18 -0.05

1,4-butandiamine 0.005 0.14 1.6% 0.43 -0.12

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.001 0.04 0.4% 0.10 -0.03

Ammonia 0.002 0.07 0.8% 0.20 -0.06

ε-caprolactum 0.002 0.06 0.7% 0.19 -0.06

Ethylamine 0.003 0.09 1.0% 0.27 -0.08

Ethylenediamine 0.001 0.02 0.2% 0.06 -0.02

Feed grade cystine 0.001 0.02 0.2% 0.05 -0.01

Feed grade methionine 0.002 0.07 0.7% 0.20 -0.06

γ-butyrolactum 0.001 0.04 0.5% 0.13 -0.04

Ionic liquids 0.001 0.03 0.3% 0.09 -0.03

Isobutyraldehyde 0.004 0.11 1.3% 0.34 -0.10

Isoprene 0.009 0.26 2.9% 0.76 -0.22

Isopropanolamine 0.003 0.08 0.9% 0.23 -0.07

Oxalic acid 0.001 0.04 0.4% 0.12 -0.03

Urea 0.003 0.07 0.8% 0.22 -0.06

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.047 1.36 15.1% 4.04 -1.16

Description

- The biomass acquitistion energy input is in middle range with farming procudes and

logistic operations having the highest contribution. As diesel is the main source, little can

be done about exergy in relation to energy input, explaining the similar figures.

- The lignin-based components (aromatics) cost significantly more cumultaive energy and

exergy demand than the standard fossil fuel-based production routes. The chemical

composition of lignin is far too low in sugar beet even when including the tops.

- Several products which rely heavily on thermal processes (such as ethylene) have a large

difference between energy and exergy demand.

- Overall a considerable performance increase for exergy vs. energy as the boiler contributes

to a large offset of steam (internal heat demand) otherwise supplied by a coal power

plant.

Improvement Options

- Further decrease lignin content by earlier harvesting and/or do not include its processing

steps therby adding additional fuel to the interal heat and power combustion unit. Earlier

harvests could also have the propitious effect of raising protein content.

- A high soil content in harvested product (due to bulb) is present which results in energy

intense ash/fertilizer. Sacrife a portion of the yield to remove soil from skin.


Brassica Napus – Rapeseed Common Names Rape, Canola, Rapeseed, Oilseed Rape, Rapa, Rapaseed

Classification Annual or biennial, C-3

Appearance Green with purple-tint base, 1.0 - 1.5meter tall, branched, long, slender stem, 10-30cm long petioles, horizontal toward base, pale yellow open flowers, 1.2-1.5cm long petals,

Varieties Several: Summer and winter, erucic acid free (Canola) and enriched, high oil

Genetically Modified Varieties Yes, but none in Europe as used as non-GMO feed.

Brief Description It is widely cultivated for erucic acid, 2nd largest source of animal (mainly cows) feed, primary source of vegetable oil and the main source for European biodiesel production.

Growth Details Native Area: Western Europe Location: Europe, North America, Australia, China and India (13% total cropped land) Climate: Cool Temperate

Temperature: 5 – 27°C (sensitive to temperatures above 30°C) Rainfall/Irrigation: 100 – 830mm (average 250mm), can tolerate up to 2800mm Soil Type: Fertile, sandy loams to light soils, well drained, low water table Soil Acidity: 4.2 – 8.2pH (6.2pH best) Plantation: Possible broadcasting or firm seedbed, 2.5mm deep grain drill, 30 – 40cm row spacing (common practice at 17 – 35cm apart) Seeding Rate: Fertilizer dependent, 10 – 30kg/ha (5 – 6kg/ha little fertilizer use), 50/50 mix with cracked grains to mitigate the small seeds, 350000 - 700000plants/ha Companion Crop: None Weed Control: Yes, for early protection Treflan, Roundup ready Cultivation: Winter type (high yielding in Europe): mid-September sowing, fall ploughing, Must be rotated with non-oil based plant Harvesting: Before fruit/seed ripens to protect damage, combine seed harvesting, July Plant residue is re-ploughed in soil

Nutrient/Fertilizer Requirement Sensitive to high levels of fertilizers at time of sowing


0

100

200

300

400

500

600

0 1 2 3 4 5 6

Seed Yield (ton /ha)


N

P2O 5

K2O

CaO

MgO

SO3

Poly . (N)

Poly . (P2O5)

Poly . (K2O)

Poly . (CaO)

Poly . (MgO)

Poly . (SO3)


0

500

1000

1500

2000

2500

0 1 2 3 4 5 6

Seed Yield (ton/ha)


Fe

Mn

B

Zn

Mo

Cu

Poly. (Fe)

Poly. (Mn)

Poly. (B)

Poly. (Zn)

Poly. (Mo)

Poly. (Cu )


Yield Normal Conditions: 0.9 – 3.0ton/ha (seeds, total WW: 15 – 48ton/ha) 3.06ton/ha (EU-15 average), 3.8ton/ha (Belgium: 5-year average) Optimal Conditions: 4.12– 5.5ton/ha (Belgium, seeds, total WW: 88ton/ha) Worldwide Cultivation: 26.4million hectares at 1.75ton/ha (seeds)


Constituent Seeds Pod Stem/Stover

Moisture Content 10% 87.4% 83.3% Cellulose 7.1 30.5 36.3 Hemicellulose 4.7 20.3 24.2 Lignin 8.6 - 9.7 Starch 0.4 - - Sucrose 4.1 - - Other Sugars 2.0 - - Protein 25.7 34.1 15.7 Fats 41.5 3.2 9.2 Minerals 0.46 - - Ash 5.0 11.9 4.9 Others 0.44 - -

Seeds, pods and stem represent 30%, 40% and 30% of the total dry weight respectively *Strongly dependent on all growing factors, location and nutrient levels Lower Heat Value: 18040kJ/kg (seeds), 20170kJ/kg (whole crop) Higher Heat Value: 19330kJ/kg (seeds), 21550kJ/kg (whole crop)

Detailed Information Rapeseed is known for the high concentration of erucic acid (C22:1) there is however a variety that has been altered to contain no erucic acid, so-called “00” or Canola:

Fatty Acid Carbon Chain Normal Rape Oil “00” Rape Oil (fraction percent)

Palmitic 16:0 3.8 4 Stearic 18:0 1.6 2 Oleic 18:1 39.2 62 Linoleic 18:2 20.5 22 Linolenic 18:3 9.2 10 Eicosenoic 20:1 11.7 - Erucic 22:1 14.9 -

Low erucic acid variety is mainly used for animal consumption, is lower yielding and has no benefit for bio-diesel production

Amino Acid Composition of Seed Protein

Seeds %

Isoleucine 17.94 Leucine 7.47

Methionine 8.65

Phenylalanine 9.38 Tryptophan 10.47


Valine 8.01

Polar & Hydrophilic

Threonine 10.29

Basic Arginine 17.94

Histidine 12.57 Acidic

Lysine 7.65 Total (100%)

Comments The seeds are 30% of the total dry weight, the rest has a large potential of being used as well.


Comparative Graph

Energy


0GJ/ton

Ethylene: 29.6GJ/to n

20

10


CRACKER


Potential Chemical Biorefinery Route

Next Generation

0GJ/ton

26.7

60

Styren e: 83.9GJ/ton

Amine Chemicals: 83.2GJ/ton80

70



Net Energy Value (NEV): 2.9

Breeding Factor: 35%

Boiler: 6.0GJ/ton

F ertilizers: 37.7GJ/to n

Amine Ch em icals: 9.3GJ/to n

Biomass

2.45GJ/ton

RapeseedBelgium

5 .5ton/ha seeds

16.4to ta lDW/ha

34.5

40

50

30


Lignin: 95.1GJ/ton

Protein: 14.3GJ/ton

Ash: 37.7GJ/ton

44.2

Phenol: 33.9GJ/ton

Styrene: 50.9GJ/ton

Ammonia: 15.4GJ/ton


Tolu en e: 72.7GJ/ton

Phenol: 76.5GJ/ton




21.5GJ/ton biomass

353GJ/ha

58.4GJ/ton

Fatty Acids: 16.0GJ/ton

Ammonia: 31.0GJ/ton

FAEE/PDO: 20.9GJ/to n

Lubricants: 45.5GJ/ton

Fatty Acids-to-Biolubricants (FAEE)




16.4GJ/tonComplex C5 Carbohydrates: 18.3GJ/ton

Toluene: 47.0GJ/ton


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

26.7

60



70





Boiler: 6.0GJ/ton



Biomass

2.45GJ/ton

RapeseedBelgium

5 .5ton/ha seeds

16.4to ta lDW/ha

34.5

40

50

30


Lignin: 95.1GJ/ton

Protein: 14.3GJ/ton

Ash: 37.7GJ/ton

44.2

Phenol: 33.9GJ/ton

Styrene: 50.9GJ/ton

Ammonia: 15.4GJ/ton



Phenol: 76.5GJ/ton




21.5GJ/ton biomass

353GJ/ha

58.4GJ/ton


Ammonia: 31.0GJ/ton







16.4GJ/tonComplex C5 Carbohydrates: 18.3GJ/ton

Toluene: 47.0GJ/ton

Exergy


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

20.2

60



70



Net Exergy Value (NExV): 3.1


Boiler: 4.9GJ/ton


Biomass

2.69GJ/ton

RapeseedBelgium

5 .5ton/ha seeds

16.4to ta lDW/ha

28.7

40

50

30


Lignin: 105GJ/ton

Protein: 17.6GJ/ton

Ash:

41.4GJ/ton41.1

Phenol: 35.4GJ/ton

Ammonia: 11.8GJ/ton



Phenol: 75.8GJ/ton




22.9GJ/ton biomass

377GJ/ha

58.0GJ/ton


Ammonia: 23.0GJ/ton







13.3GJ/ton


Toluene: 41.5GJ/ton

Styrene: 45.9GJ/ton



0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

20.2

60



70





Boiler: 4.9GJ/ton


Biomass

2.69GJ/ton

RapeseedBelgium

5 .5ton/ha seeds

16.4to ta lDW/ha

28.7

40

50

30


Lignin: 105GJ/ton

Protein: 17.6GJ/ton

Ash:

41.4GJ/ton41.1

Phenol: 35.4GJ/ton

Ammonia: 11.8GJ/ton



Phenol: 75.8GJ/ton




22.9GJ/ton biomass

377GJ/ha

58.0GJ/ton


Ammonia: 23.0GJ/ton







13.3GJ/ton


Toluene: 41.5GJ/ton

Styrene: 45.9GJ/ton



Overview Savings



Ethylene 0.110 1.81 21.5% 3.53 2.85

Phenol 0.008 0.14 1.6% 0.27 0.22

Styrene 0.009 0.15 1.8% 0.30 0.24

Toluene 0.008 0.13 1.6% 0.26 0.21

1,4-butandiamine 0.021 0.35 4.2% 0.69 0.55

Acrylamide 0.001 0.02 0.2% 0.03 0.03

Adipic acid 0.004 0.06 0.7% 0.12 0.10

Ammonia 0.008 0.13 1.5% 0.25 0.20

ε-caprolactum 0.011 0.18 2.2% 0.36 0.29

Ethylamine 0.020 0.33 3.9% 0.65 0.52

Ethylenediamine 0.005 0.08 1.0% 0.16 0.13

Feed grade cystine 0.001 0.01 0.2% 0.03 0.02

Feed grade methionine 0.010 0.16 1.9% 0.31 0.25

γ-butyrolactum 0.007 0.11 1.4% 0.22 0.18

Ionic liquids 0.004 0.07 0.9% 0.14 0.11

Isobutyraldehyde 0.009 0.16 1.9% 0.30 0.25

Isoprene 0.031 0.51 6.0% 0.99 0.80

Isopropanolamine 0.010 0.17 2.0% 0.32 0.26

Oxalic acid 0.009 0.14 1.7% 0.28 0.23

Urea 0.007 0.12 1.4% 0.23 0.19

Biolubricants 0.153 2.51 29.9% 4.91 3.96

Fertilizers 0.065 1.07 12.7% 2.08 1.68

Description

- Sufficient lignin content/concentration to lead to a positive contribution of the convertion

to aromatics

- Relatively low protein content, but due to the high conversion of the other components

the risidual concentration are converted efficiently.

- Judging from the exergy graph alone, rapeseed should be one of the best performers but

due to the high product conversion rates the boiler output is lower and cannot overcome

the relatively high indirect energy/exergy cost associated with fatty acid conversion

(despite ethanol being cheaper than methanol)

- Conversion to FAEE is automatically disadvantaged as the traditional petrochemical

production route is only 45GJ/ton (i.e. calorifc value) wheras functional chemicals are

above the mid-70’s range.

Improvement Options

- Possible GMO tailering to increase protein content and lower oil content.

- Burn the pure plant oil onsite for power generation, increasing boiler output and releaving

need for energy intensive purification, extraction and conversion. Rapeseed is a

protenious crop in any case; use oil crops for oil (biolubricant) processing.


Elaeis Guineensis Jacq. – Oil Palm Common Names African palm tree, African oil palm, oil palms

Classification Perennial, C-3

Appearance Single stemmed erect tree up to 8 - 20 meters high, 20 – 30 pinnate Leaves, long 3-5 meter, dense clusters 100 – 200 of fruit with fleshy pericarp, 2 x 3.5cm, maturity every 6 month, weigh 40 – 50kg

Varieties Three: Psifera, Dura, Tenera (classified by fruit)

Genetically Modified Varieties None, but Dura/Tenera hybrids for higher yield with lower canopies

Brief Description Palm has many applications, primarily for the commercial production of oil: palm oil and kernel oil. It can also be used for nutritious, cosmetic and other trade purposes. Grown in many countries outside its native home in large plantations it has caused some environmental concern.

Growth Details Native Area: West Africa, between Angola and Gambia Location: All throughout the tropics, mainly in South East Asia Climate: Tropical Rainforest, high sunlight required

Temperature: 22 - 32°C, cannot tolerate major variations Rainfall/Irrigation: 1750 – 2300mm, good annual distribution of rainfall Soil Type: Wide range of tropical soils, adequate water transport required Soil Acidity: 4 – 6pH, must be acidic, average 5.7pH Plantation: Seed nursery production of young palms, one year before field planting 9 x 9 meter grid planting Seeding Rate: Best: 75 – 150 plants/hectare, yield decreases with higher rates Average: 143 plant/ha Companion Crop: Legumes suggested for ground cover, erosion prevention and nutrients Weed Control: Required for seeding (i.e. at nursery) as slow establishment Cultivation: 1 year nursery production, 2-3 year additional establishment, after 25 years tree become to high for production, 5-10 peak yield Harvesting: Manual cutting of fresh fruit bunches when ripe (highest oil content), twice a year 100-150 bunches/man, after 25 years tree becomes to high, removed

Nutrient/Fertilizer Requirement Highly variable, depending mainly on the yield potential determined by the genetic make-up of the planting material and on the yield limit set by climatic factors.


0

50

100

150

200

250

300

350

0 5 10 15 20 25 30

Fruit Yield (ton/ha)


N

P2O5

K2O

CaO

MgO

SO3

Poly. (N)

Poly. (P2O5)

Poly. (K2O)

Poly. (CaO)

Poly. (MgO )

Poly. (SO 3)


0

100

200

300

400

500

600

0 5 10 15 20 25 30

Fruit Y ield (ton/ha)


Fe

Mn

B

Zn

Mo

Cu

Po ly. (Fe)

Po ly. (Mn)

Po ly. (B)

Po ly. (Zn )

Po ly. (Mo)

Po ly. (Cu)


Yield Normal Conditions: 10 – 25 ton/ha (fruit, yield 3 – 7.5 ton of oil/ha) 19.5ton/ha (Malaysia: 5-year average) Optimal Conditions: Malaysian good fresh wet: 25 ton/ha + 9.8(fronds) + 5.6(trunk) Highest recorded: 46 ton/ha (fruits) Worldwide Cultivation: 7.3 million hectares at 12.6 ton/ha fruits


Constituent Fruit Leaves Trunk Moisture Content 26% 69.9% 50%

Cellulose 10.1 47.5 45 Hemicellulose 6.4 9.3 25 Lignin 4.7 16.4 18 Protein 2.6 6.7 - Oils - -

Fats 74.5

- - Minerals 0.3 - 2 Ash 1.4 8.3 - Others - 11.8 10

*Strongly dependent on all growing factors, location and nutrient levels Fruits represent 1/3, fronds (leaves) represent ½ and the trunk represent 1/6 the total annual wet weight After 25 years the tree trunks can be harvested at around 4 - 7.5 ton/ha WW Lower Heat Value: 39330 kJ/kg (oil), 22100 kJ/kg (fruit residue), 17000 kJ/kg (trunk), 7100 kJ/kg (fronds, wet) Higher Heat Value: 39385 kJ/kg (oil), 20650 kJ/kg (fruit residue), 17800 kJ/kg (trunk), 17500 kJ/kg (fronds)

Detailed Information Palm oil is known for the high concentration of palmitic (hence the name) oleic, and stearic acids

Fatty Acid Carbon Chain Palm Oil (fraction percent)

Myristic 14:0 0.5 - 5.9 Palmitic 16:0 32.3 - 47.0 Stearic 18:0 1.0 - 8.5 Oleic 18:1 39.8 - 52.4 Linoleic 18:2 2.0 - 11.3

Normal Grade Palm Oil: 44.0% Palmitic, 4% Stearic, 40.0% Oleic, 10.0% Linoleic, 2.0% Other Oleic Grade Palm Oil: 40.0% Palmitic, 4.0% Stearic, 43.0% Oleic, 11.0% Linoleic, 2.0% Other Stearic Grade Palm Oil: 58.0% Palmitic, >5.0% Stearic, 29.0% Oleic, 6.5% Linoleic, 1.5% Other Palm kernel oil is a side extractive from the processing of the seeds. It is produced at rate roughly 10-20% of that of the palm oil production, thus 0.25 – 0.75 ton/ha (normal conditions). The composition is however entirely based on medium chain fatty acids:

Fatty Acid Carbon Chain Palm Oil (fraction percent)

Caprylic 8:0 4 Capric 10:0 4 Lauric 12:0 45 Myristic 14:0 18 Palmitic 16:0 9 Stearic 18:0 3 Oleic 18:1 15 Linoleic 18:2 2

Comments Deli Palms (Dura variety) are low-growing and thick-stemmed hybrids with very high yields in Asia but perform poorly in other areas.


Comparative Graph

Energy



0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

26.0

60



70





Boiler: 7.0GJ/ton


Amin e Ch em icals: 39.1GJ/to n

Biomass

2.50GJ/ton

Oil PalmMalaysia

25 .0ton/ha fru its

34.5to ta lDW/ha

46.5

40

50

30


Lignin: 46.4GJ/ton

Protein: 119GJ/ton

Ash: 92.2GJ/ton

27.9

Phenol: 18.1GJ/ton

Styrene: 33.4GJ/ton

Toluene: 31.5GJ/ton



Phenol: 76.5GJ/ton




20.9GJ/ton biomass

721GJ/ha

51.9GJ/ton


Ammonia: 31.0GJ/ton



14.9GJ/ton


Ammonia: 22.6GJ/ton







0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

26.0

60



70





Boiler: 7.0GJ/ton



Biomass

2.50GJ/ton

Oil PalmMalaysia

25 .0ton/ha fru its

34.5to ta lDW/ha

46.5

40

50

30


Lignin: 46.4GJ/ton

Protein: 119GJ/ton

Ash: 92.2GJ/ton

27.9

Phenol: 18.1GJ/ton

Styrene: 33.4GJ/ton

Toluene: 31.5GJ/ton



Phenol: 76.5GJ/ton




20.9GJ/ton biomass

721GJ/ha

51.9GJ/ton


Ammonia: 31.0GJ/ton



14.9GJ/ton


Ammonia: 22.6GJ/ton





Exergy



0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

18.9

60



70





Boiler: 5.6GJ/ton



Biomass

2.61GJ/ton

Oil PalmMalaysia

25 .0ton/ha fru its

34.5to ta lDW/ha

40.140

50

30


Lignin:

48.4GJ/ton

Protein: 120GJ/ton

Ash: 96.2GJ/ton

22.3

Phenol: 17.2GJ/ton

Styrene: 25.7GJ/ton

Toluene: 23.7GJ/tonAmmonia: 22.2GJ/ton



Phenol: 75.8GJ/ton




24.0GJ/ton biomass

830GJ/ha

51.9GJ/ton


Ammonia: 23.0GJ/ton



9.6GJ/ton








0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

18.9

60



70





Boiler: 5.6GJ/ton



Biomass

2.61GJ/ton

Oil PalmMalaysia

25 .0ton/ha fru its

34.5to ta lDW/ha

40.140

50

30


Lignin:

48.4GJ/ton

Protein: 120GJ/ton

Ash: 96.2GJ/ton

22.3

Phenol: 17.2GJ/ton

Styrene: 25.7GJ/ton

Toluene: 23.7GJ/tonAmmonia: 22.2GJ/ton



Phenol: 75.8GJ/ton




24.0GJ/ton biomass

830GJ/ha

51.9GJ/ton


Ammonia: 23.0GJ/ton



9.6GJ/ton







Overview Savings



Ethylene 0.100 3.47 17.8% 2.65 1.72

Phenol 0.017 0.60 3.1% 0.46 0.30

Styrene 0.019 0.67 3.4% 0.51 0.33

Toluene 0.017 0.59 3.0% 0.45 0.29

1,4-butandiamine 0.005 0.19 1.0% 0.14 0.09

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.000 0.00 0.0% 0.00 0.00

Ammonia 0.001 0.03 0.1% 0.02 0.01

ε-caprolactum 0.001 0.02 0.1% 0.02 0.01

Ethylamine 0.002 0.07 0.3% 0.05 0.03


Feed grade cysteine 0.000 0.02 0.1% 0.01 0.01


γ-butyrolactum 0.001 0.03 0.2% 0.03 0.02

Ionic liquids 0.000 0.02 0.1% 0.01 0.01


Isoprene 0.003 0.12 0.6% 0.09 0.06


Oxalic acid 0.001 0.04 0.2% 0.03 0.02

Urea 0.001 0.05 0.3% 0.04 0.02

Biolubricants 0.363 12.54 64.3% 9.57 6.20

Fertilizers 0.027 0.94 4.8% 0.71 0.46

Description

- Has the best overall performance; extraordinarily high yield and relatively low energy

intensity in acquisition and conversion.

- Very high oil concentration facilitates the conversion to biolubricants at energetically

positive rates. Asian production methods are based on drudgery which inherently has a

low energy intensity. Little improvement is foreseeable using current techniques as exergy

demand for FAEE production is similar to energy.

Improvement Options

- Focus on improving extraction techniques, possibly new systems to reduce energy and

potential exergy demand in oil conversion steps.

- Has no possibility to be mechanized which can prevent the industrial and social

development of Malaysia (and other countries in the region). Else yield and production

costs will be heavily sacrificed leading to more of a loss as opposed to a gain by

improving the cropping system. It is foreseeable that through stronger international

development issues oil palm could loss it top position.


Glycine Max – Soya Bean Common Names USA: Soybeans, UK: Soya Beans, Edamame, Japan: shoyu, bean sprout, Asia: Great Treasure, Brings Happiness, Yellow Jewel

Classification Annual, Legume, Papilionaceous, C-3

Appearance Erect hairy stem with trifoliate Leaves, small white or purple flowers, short pods with 1-4 seeds/beans, Height of 0.6 – 1.5 meters with tapped roots up to 2 meters in length

Varieties Thousands, named by bean/pod colour

Genetically Modified Varieties Nearly all, 80% of all commercially sold, leader in research Monsanto

Brief Description Planted in several large areas of the world, the seeds have become an important substitute of meat (complete) protein and other minerals. There are many industrial applications and possibilities of soya beans like soap, resins, plastics, solvents and more recently biodiesel.

Growth Details Native Area: Southeast Asia Location: Major producers are USA, China, India, Brazil and Argentina Climate: Warm – subtropical, full sun to partial shade, wet, cannot tolerate drought

Temperature: 20 - 35°C optimal, breaded varieties for temperate areas Rainfall/Irrigation: 450 – 700mm (average 600mm), tolerate up to 4100mm Soil Type: Deep, free draining, sandy or medium loam Soil Acidity: 5.8 – 6.5 pH must be slightly acidic and not exceed 7.0 Plantation: 2.5 – 4 cm, deeper exposes soil-based pathogens, vary row spacing 18 –76cm Seeding Rate: 30kg/ha for plant density of 100,000 – 133,333 plant/ha 60 kg/ha for plant density of up to 300,000 plants/ha 50 - 100cm between rows and 15-30cm between plants Companion Crop: No, but rotated Weed Control: Weed competition is serious, and may reduce yields by 50%, early cultivation Cultivation: Summer plant, May-June start, 3 – 4 month establishment duration, 2-3 year rotation

and not with all crops for disease control reasons Harvesting: Single harvesting after leaf abscission, fall months, cylinder speed threshes

Nutrient/Fertilizer Requirement Seed or soil applied granular inoculation, soil temperature 25 - 30°C for symbiosis to occur Inoculation bacteria strain: Bradyrhizobium Japonicum (100% N uptake)


0

50

100

150

200

250

300

350

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Seed Yield (ton/ha)


N

P2O5

K2O

CaO

MgO

SO 3

Po ly. (N)

Po ly. (P2O 5)

Po ly. (K2O )

Po ly. (CaO )

Po ly. (MgO)

Po ly. (SO3)


0

200

400

600

800

1000

1200

1400

1600

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Seed Yield (ton/ha)


Fe

Mn

B

Zn

Mo

Cu

Poly. (Fe)

Poly. (Mn)

Poly. (B)

Poly. (Zn)

Poly. (Mo)

Poly. (Cu )


Yield Normal Conditions: 1.7 – 3.4 ton/ha (seeds), ~5 ton/ha (hay, rest of plant) 2.6ton/ha seeds (USA: 5-year average) Optimal Conditions: 4 ton/ha (seeds), 6 ton/ha (hay) Worldwide Cultivation: 91 million hectares at 2.2 ton/ha of seeds


Constituent Seeds‡ Leaf/Stem†

Moisture Content 10.2% 60.0% Cellulose 17

Hemicellulose 4 65

Sugars 7 - Lignin 1 20 Protein 40.8 10 Oils 17.9 - Fats 2.1 - Minerals 2.8 - Ash 6 - Others 1.4 5

Seeds represent about 1/3 of the total dry plant mass, †estimate for leafy matter (hay) ‡Green seeds (or raw seeds) have a moisture content of 68.2%, yellow seeds (or dry seeds) are harvested *Strongly dependent on all growing factors, location and nutrient levels Lower Heat Value: 26000 kJ/kg (seed, estimate), 17000 kJ/kg (stover) Higher Heat Value: 27000 kJ/kg (seed, estimate), 17500 kJ/kg (stover)

Detailed Information The globular protein, Glycine, account for 80 – 90% of the protein with:

Seeds Amino Acid Composition for Glycine Protein g/kg %

Alanine 5.8 1.71

Isoleucine 8.2 2.41 Leucine 31.3 9.20

Methionine 6.1 1.79

Phenylalanine 14.6 4.29 Proline 14.6 4.29

Tryptophan 5.8 1.71


Valine 5.4 1.59 Asparagine 19.4 5.70

Cysteine 3.7 1.09

Glutamine 64.6 18.99 Glycine 2.4 0.71

Serine Unknown

Threonine 7.1 2.09

Polar & Hydrophilic

Tyrosine 13.3 3.91

Asparagic Acid 21.1 6.20 Acidic

Glutamic Acid 62.6 18.41

Arginine 28.2 8.29 Histidine 7.5 2.21 Basic

Lysine 18.4 5.41

Total 340 (85% of Protein)

Comments Nearly all information regarding the soybean is toward the seed and possible residues after processing the seed. A possibility for multiple biorefinery to utilize the hull, also the rest of the plant matter is most likely completely carbohydrate based.


Comparative Graph

Energy


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

25.8

60



70





Boiler: 7.8GJ/ton



Biomass

2.77GJ/ton

SoybeanIllinois

4 .0ton/ha seeds

10.8to ta lDW/ha

36.3

40

50

30


Lignin: 35.5GJ/ton

Protein: 22.6GJ/ton

Ash:

42.7GJ/ton

24.2

Phenol: 14.6GJ/ton

Styrene: 29.5GJ/to n

Ammonia: 14.1GJ/ton



Phenol: 76.5GJ/ton




18.1GJ/ton biomass

196GJ/ha

Fatty Acids:

46.6GJ/ton

Ammonia: 31.0GJ/ton


Lub ricants: 45.5GJ/ton





22.0GJ/tonComplex C5


Toluene: 28.1GJ/ton

Simple Carbohydrates: 132GJ/ton

62.4GJ/ton


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

25.8

60



70





Boiler: 7.8GJ/ton



Biomass

2.77GJ/ton

SoybeanIllinois

4 .0ton/ha seeds

10.8to ta lDW/ha

36.3

40

50

30


Lignin: 35.5GJ/ton

Protein: 22.6GJ/ton

Ash:

42.7GJ/ton

24.2

Phenol: 14.6GJ/ton

Styrene: 29.5GJ/to n

Ammonia: 14.1GJ/ton



Phenol: 76.5GJ/ton




18.1GJ/ton biomass

196GJ/ha

Fatty Acids:

46.6GJ/ton

Ammonia: 31.0GJ/ton







22.0GJ/tonComplex C5


Toluene: 28.1GJ/ton


62.4GJ/ton

Exergy


0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

20.1

60



70





Boiler: 6.4GJ/ton


Biomass

3.26GJ/ton

SoybeanIllinois

4 .0ton/ha seeds

10.8to ta lDW/ha

32.3

40

50

30


Lignin:

41.8GJ/ton

Protein: 26.6GJ/ton

Ash: 50.2GJ/ton

20.0

Phenol: 15.1GJ/ton

Ammonia: 9.8GJ/to n



Phenol: 75.8GJ/ton




19.1GJ/ton biomass

206GJ/ha

62.7GJ/ton


Ammonia: 23.0GJ/ton







20.2GJ/ton

Complex C5

Carbohydrates: 23.7GJ/tonToluene: 21.6GJ/to n

Styrene: 23.4GJ/ton





0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

20.1

60



70





Boiler: 6.4GJ/ton


Biomass

3.26GJ/ton

SoybeanIllinois

4 .0ton/ha seeds

10.8to ta lDW/ha

32.3

40

50

30


Lignin:

41.8GJ/ton

Protein: 26.6GJ/ton

Ash: 50.2GJ/ton

20.0

Phenol: 15.1GJ/ton

Ammonia: 9.8GJ/to n



Phenol: 75.8GJ/ton




19.1GJ/ton biomass

206GJ/ha

62.7GJ/ton


Ammonia: 23.0GJ/ton







20.2GJ/ton

Complex C5

Carbohydrates: 23.7GJ/tonToluene: 21.6GJ/to n

Styrene: 23.4GJ/ton





Overview Savings



Ethylene 0.134 1.44 29.8% 6.56 6.01

Phenol 0.025 0.27 5.6% 1.24 1.14

Styrene 0.028 0.30 6.2% 1.37 1.26

Toluene 0.025 0.27 5.5% 1.21 1.11

1,4-butandiamine 0.032 0.35 7.1% 1.57 1.44

Acrylamide 0.005 0.05 1.1% 0.25 0.23

Adipic acid 0.001 0.01 0.3% 0.06 0.06

Ammonia 0.004 0.04 0.8% 0.17 0.16

ε-caprolactum 0.006 0.07 1.4% 0.31 0.29

Ethylamine 0.013 0.14 2.9% 0.65 0.59




γ-butyrolactum 0.008 0.08 1.7% 0.37 0.34

Ionic liquids 0.002 0.03 0.5% 0.12 0.11


Isoprene 0.021 0.22 4.6% 1.00 0.92


Oxalic acid 0.003 0.03 0.6% 0.13 0.12

Urea 0.004 0.04 0.9% 0.20 0.18

Biolubricants 0.059 0.64 13.2% 2.91 2.67

Fertilizers 0.065 0.70 14.4% 3.18 2.91

Description

- It is a very energy intense crop to cultivate despite its leguminous nature as the total dry

weight yield is far too low to offset cultivation practices. Noticeable increase in exergy

demand in biomass acquisition demand is due chiefly to required sizing and drying

operation in feedstock preparation.

- Production of FAEE is more energy and exergy intense than the traditional production

method; soya bean is not a suitable crop for oil production.

- Regardless of the low biolubricant CED the effect of amine chemistry in the biorefinery

layout can be seen by the high equivalent petrorefinery cost, being above 60GJ/ton.

- The conversion of protein to the amine chemicals is very beneficial and efficient; right

concentration and right composition.

Improvement Options

- Abolish ideas of saving nitrogen fertilizer, instead promote drastic increases of yields

through heavy fertilization.

- Possible GMO tailering to increase protein content and lower oil content.

- Might consider to burn straw/stover directly and not convert as it is low yeilding.


Helianthus Annuus – Sunflower Common Names Sunflower

Classification Annual herb, C-3

Appearance 0.7 – 3.5m erect unbranched stem, alternating ovate Leaves, bright yellow to orange round flower head 10 – 40cm across, clusters of seeds/fruits from achenes, 3m deep, broad taproot system

Varieties Several, new species transgenic, others with drooping heads

Genetically Modified Varieties Yes, mainly for resistance, however non-GMO very popular

Brief Description The world’s second most important source for oil. The seeds have many applications along with human consumption. Considered one of the possible energy crops for bio-diesel production.

Growth Details Native Area: Western North America Location: Wide spread with North America, Europe and Russia leading Climate: Temperate – subtropical, intolerant of shade, tolerates drought and frost

Temperature: 18 - 25°C, yearly average around 20°C Rainfall/Irrigation: 600 – 1000mm (average 900mm), can tolerate up to 4000mm Soil Type: Wide variety, poor to fertile, moist to dry but must be deep and well drained Soil Acidity: 4.5 – 8.7pH, can tolerate both extremes, prefers 6.6pH Plantation: 2.5 – 7.5cm deep, 20cm spacing, 60 – 90cm row distancing, Seeding Rate: 4 – 10kg/ha for plant density of 62500 plants/ha Companion Crop: Not recommended Weed Control: Minor problem, as it is a weed itself Cultivation: Planted in early spring, frost is not a problem, 4 year rotation break and not to be

rotated with potatoes, 70 – 120days maturity Harvesting: 120 – 160 days after sown when seeds become lose but before shedding occurs,

mechanized head removal, drying and threshing

Nutrient/Fertilizer Requirement Respond well to a balanced fertilization, 1-2-3 NPK is best ratio The potassium (K2O) demand is extraordinarily high


0

100

200

300

400

500

600

700

0 1 2 3 4 5 6

Seed Yield (ton/ha)


N

P2O5

K2O

CaO

MgO

SO3

Po ly. (N)

Po ly. (P2O5)

Po ly. (K2O)

Po ly. (CaO)

Po ly. (MgO)

Po ly. (SO3)


0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6

Seed Yield (ton /ha)


Fe

Mn

B

Zn

Mo

Cu

Poly. (Fe)

Poly. (Mn)

Poly. (B)

Poly. (Zn)

Poly. (Mo)

Poly. (Cu )


Yield Normal Conditions: 1 – 3.5 ton/ha (seeds), 2.3ton/ha (France: 5-year average) 5 – 8 ton/ha (straw, factor of two) Optimal Conditions: 5 – 6 ton/ha (seeds) Worldwide Cultivation: 21.4 million hectares at 4.1 ton/ha (1.23 ton/ha seeds)


Constituent Seeds Husk/Flower Foliage

Moisture Content 20% 30% 70% Cellulose 9.0 31.4 38.2 Hemicellulose 6.0 21.9 25.9 Lignin 4.0 11.0 12.3 Protein 25.2 12.7 12.5 Oils -

Fats 49.7 13.7

- Minerals 1.5 - - Ash 4.2 9.3 11.1 Others 0.4 - -

*Strongly dependent on all growing factors, location and nutrient levels Seeds + flower head represent 1/2 of total wet weight Seed consist of 20 – 35% DW husk/shell (30% taken as average) Higher Heat Value: 26000 kJ/kg (seed), 19300 kJ/kg (husk), 16290 kJ/kg (straw) Lower Heat Value: 24350 kJ/kg (seed), 20400 kJ/kg (husk), 17410 kJ/kg (straw)

Detailed Information Seed oil is known for the high concentration of linoleic acid and low palmitic and stearic acids

Fatty Acid Carbon Chain Seed Oil (fraction percent)

Palmitic 16:0 3-8 Stearic 18:0 4-7 Oleic 18:1 15-30 Linoleic 18:2 45-75

Commercial Grade Seed Oil: 6.0% Palmitic, 4.6% Stearic, 17.8% Oleic, 69.2% Linoleic High Oleic Hybrid Seed Oil: 3.6% Palmitic, 4.8% Stearic, 78.9% Oleic, 10.2% Linoleic

Amino Acid Composition of Seed Protein

Seed (protein fraction)

Alanine Unknown


Methionine 1.5

Phenylalanine 4.6 Proline Unknown

Tryptophan -


Valine 4.0 Asparagine Unknown

Cysteine 1.7

Glutamine Unknown Glycine 5.6

Serine Unknown

Threonine 3.4

Polar & Hydrophilic

Tyrosine 1.6

Asparagic Acid Unknown Acidic

Glutamic Acid Unknown

Arginine 10.0 Histidine 2.3 Basic

Lysine 3.6

Total 47.9% of Protein The protein concentration can range from 13 to 26% of seed dry weight, quality worse than soya


Comparative Graph

Energy

Lignin: 129GJ/ton


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

41.2

60



70





Boiler: 4.1GJ/ton

Fert ilizers: 28.3GJ/ton


SunflowerFrance

5 .5ton/ha seeds

8.4to talDW/ha

58.1

40

50

30

Complex C6


Protein:

42.4GJ/ton

Ash: 28.3GJ/ton

55.6

Styrene: 63.2GJ/ton

Ammonia: 17.5GJ/ton



Phenol: 76.5GJ/ton




15.3GJ/ton biomass

128GJ/ha


Ammonia: 31.0GJ/ton

FAEE/PDO: 22.5GJ/ton






23.9GJ/ton

Complex C5


Toluene: 57.9GJ/ton

46.1GJ/tonBiomass

4.85GJ/ton

Phenol: 45.0GJ/ton

Lignin: 129GJ/ton


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

41.2

60



70





Boiler: 4.1GJ/ton



SunflowerFrance

5 .5ton/ha seeds

8.4to talDW/ha

58.1

40

50

30

Complex C6


Protein:

42.4GJ/ton

Ash: 28.3GJ/ton

55.6

Styrene: 63.2GJ/ton

Ammonia: 17.5GJ/ton



Phenol: 76.5GJ/ton




15.3GJ/ton biomass

128GJ/ha


Ammonia: 31.0GJ/ton

FAEE/PDO: 22.5GJ/ton






23.9GJ/ton

Complex C5


Toluene: 57.9GJ/ton

46.1GJ/tonBiomass

4.85GJ/ton

Phenol: 45.0GJ/ton

Exergy

Complex C5 Carbohydrates:

48.5GJ/ton

Lignin: 150GJ/ton


0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

56.2

60



70





Boiler: 3.4GJ/ton


Biomass

5.60GJ/ton

SunflowerFrance

5 .5ton/ha seeds

8.4to talDW/ha

57.0

40

50

30 Complex C6 Carbohydrates: 29.3GJ/ton

Protein: 49.0GJ/ton

Ash: 32.7GJ/ton

37.6

Phenol: 50.0GJ/ton

Ammonia: 14.1GJ/ton



Phenol: 75.8GJ/ton




15.5GJ/ton biomass

130GJ/ha








23.8GJ/ton

Toluene: 55.8GJ/to n

Styrene: 62.0GJ/ton



Ammonia: 23.0GJ/ton

46.3GJ/ton Complex C5 Carbohydrates:

48.5GJ/ton

Lignin: 150GJ/ton


0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

56.2

60



70





Boiler: 3.4GJ/ton


Biomass

5.60GJ/ton

SunflowerFrance

5 .5ton/ha seeds

8.4to talDW/ha

57.0

40

50

30 Complex C6 Carbohydrates: 29.3GJ/ton

Protein: 49.0GJ/ton

Ash: 32.7GJ/ton

37.6

Phenol: 50.0GJ/ton

Ammonia: 14.1GJ/ton



Phenol: 75.8GJ/ton




15.5GJ/ton biomass

130GJ/ha








23.8GJ/ton

Toluene: 55.8GJ/to n

Styrene: 62.0GJ/ton



Ammonia: 23.0GJ/ton

46.3GJ/ton


Overview Savings



Ethylene 0.094 0.79 13.7% 3.27 3.25

Phenol 0.012 0.10 1.8% 0.42 0.42

Styrene 0.013 0.11 2.0% 0.47 0.46

Toluene 0.012 0.10 1.7% 0.41 0.41

1,4-butandiamine 0.030 0.25 4.4% 1.05 1.04

Acrylamide 0.002 0.02 0.3% 0.08 0.08

Adipic acid 0.003 0.02 0.4% 0.10 0.10

Ammonia 0.005 0.04 0.7% 0.16 0.16

ε-caprolactum 0.004 0.04 0.6% 0.15 0.15

Ethylamine 0.010 0.08 1.4% 0.33 0.33




γ-butyrolactum 0.004 0.04 0.6% 0.15 0.15

Ionic liquids 0.002 0.02 0.3% 0.08 0.08


Isoprene 0.016 0.14 2.4% 0.57 0.57


Oxalic acid 0.006 0.05 0.9% 0.21 0.21

Urea 0.006 0.05 0.9% 0.21 0.21

Biolubricants 0.276 2.32 40.2% 9.61 9.56

Fertilizers 0.172 1.44 25.0% 5.97 5.93

Description

- A very expensive crop to cultivate with a meagre yield, i.e. high GJ/ton.

- Nonetheless, oil concentration is sufficient to promote an efficient conversion to FAEE.

- Practically no difference between resulting energy and exergy as oil production represents

over 40% biorefinery chemical product mixture

- Its exergy improvement is offset by higher exergetic biomass acquisition production costs

and large ash/fertilizer product mixture, being 25%.

- Residual protein content and concentration perfectly suited for downstream processing to

amine-based chemicals despite high associated feedstock costs.

- Carbohydrates conversion has a limited positive factor, ethylene close to break-even point.

Improvement Options

- Search for better cultivation location with significantly lower energy demand in irrigation.

- As it has low yields screen for possibilities to cultivate on exhausted or marginal lands.

- GMO tailoring to infuse bacterial symbiosis as fertilizers are a major input component and

overall yields are nonetheless low.

- Considering that oil is the best product from sunflower, it may be best to cess cultivation

of this cropping system as it is highly unlikely to ever be able to compete with oil palm.


Manihot Esculenta – Cassava Common Names Cassava, Manioc, Yucca, Mandioca, Tapioca

Classification Perennial woody shrub, planted as annual crop, C-3

Appearance Palmate Leaves on stubby fibrous stems, 5 – 10 root tubers, Clumps of tapered tubers, 50 – 80 cm long, 5 –10 cm thick, roots reaches 2 meters long, 1mm thick brown skin, white/yellow flesh

Varieties Cultigens, limited, pest and disease resistant, cyanide reduction

Genetically Modified Varieties None

Brief Description Similar to a potato the main purpose is for starchy food. In Africa and Latin America cassava is mostly used for human consumption but is growing on other starch industries.

Growth Details Native Area: South America Location: Latin America and Africa Climate: Tropical – Subtropical, humid but can tolerate drought

Temperature: At least 25°C, heat loving Rainfall/Irrigation: Less than 150mm Soil Type: Possible to grow in marginal lands with low nutrients Soil Acidity: 4.0 – 8.0 pH, grows in nearly all soil Plantation: 7 – 30cm of mature stem, 1m by 1m spacing, vertical 5 - 10cm in soil Mechanical planers are present in Brazil Seeding Rate: Does not occur Companion Crop: Often rice, maize and grain legumes for sufficient nitrogen Weed Control: Necessary in first few months, slow early growth Pest and Disease: In Africa, combined with poor practice yields can reduce by more than 80% Cultivation: Stem cuttings for propagation (cloning), start of rainy season, 1.5 – 3 months establishment and 6 - 18 months for crop Harvesting: Roots can be left in ground up to 24 – 36 months in poor soil conditions Longer left in ground tubers become more woody, less starchy Root extraction, labour intensive, highly perishable within days

Nutrient/Fertilizer Requirement


0

50

100

150

200

250

300

350

400

0 10 20 30 40 50 60


Total P

lant Uptake (kg/ha)

N

P2O5

K2O

CaO

MgO

SO3

Poly. (N)

Po ly. (P2O5)

Po ly. (K2O)

Po ly. (CaO)

Po ly. (MgO)

Po ly. (SO3)

Yield Dependent Micronu trientUptake

0

200

400

600

800

1000

1200

1400

1600

0 10 20 30 40 50 60


Total Plant Uptake (g

/ha)

Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe)

Poly . (Mn)

Poly . (B)

Poly . (Zn)

Poly . (Mo)

Poly . (Cu)


Yield Normal Conditions: 2 – 12 ton/ha tuber (poor) 9.4 ton/ha (Nigeria, 5-year average) Optimal Conditions: 25 – 40 ton/ha tuber (good commercial yield), 50ton/ha tuber (best) 90 ton/ha (speculated at utmost favourable conditions) Worldwide Cultivation: 16.2 million hectares at 10.2 ton/ha

Chemical Composition* (Based on dry weight and sweet cassava, harvested yearly)

Constituent Tuber Leaves Stem† Moisture Content 69.9% 81.0% 15%

Cellulose Hemicellulose

11.7 48.4 65

Lignin 2.7 11.1 20 Sucrose 15.3 - - Starch 63 - - Protein 2.8 36.3 10 Fats 0.6 6.8 - Minerals 1.3 2.9 - Ash 2.5 8.4 5 Others 0.1 - -

*Strongly dependent on all growing factors, location and nutrient levels The root is 50 – 70% of the total plant wet weight (60% taken), †estimate and 25% of wet weight Lower Heat Value: 15500 kJ/kg (tuber alone) Higher Heat Value: 16500 kJ/kg (tuber, estimate)

Detailed Information Root Leaves

Free Amino Acid g/kg % g/kg %

Alanine 0.35 5.69 12 5.94

Isoleucine 0.20 3.25 9 4.46

Leucine 0.40 6.50 19 9.41 Methionine 0.05 0.81 5 2.48

Phenylalanine 0.20 3.25 12 5.94

Proline 0.20 3.25 10 4.95 Tryptophan Trace Trace


Valine 0.25 4.07 12 5.94

Asparagine Unknown Unknown Cysteine 0.05 0.81 2 0.99

Glutamine Unknown Unknown

Glycine 0.35 5.69 11 5.45 Serine 0.35 11 5.45

Threonine 0.30 4.88 11 5.45

Polar & Hydrophilic

Tyrosine 0.10 1.63 7 3.47 Asparagic Acid 1.05 17.07 22 10.89

Acidic Glutamic Acid 1.60 26.02 27 13.37

Arginine 0.15 2.44 13 6.44

Histidine 0.40 6.50 5 2.48 Basic

Lysine 0.15 2.44 14 6.93

Total 6.15 (22%) 202 (55.6%)

Comments The longer the growth period and exposure to the surface will create a bitter cassava tuber. This is due to the partial degradation by naturally occurring enzymes creating HCN, 0.3 – 0.5%DW. Its rooting system is particularly good at mining the soil to extract even trace nutrients.


Comparative Graph

Energy

Ash: 57.9GJ/ton

Next Generation

Phenol: 16.0GJ/ton

Toluene: 29.4GJ/ton

20

10


CRACKER



45.1

60

Styrene: 83.9GJ/ton


70





Amine Chem icals: 26.2GJ/ton

Biomass

1.92GJ/ton

CassavaNigeria

50 ton /ha tube r

35.1to ta lDW/ha

42.8

40

50

30



Lignin: 40.0GJ/ton

Protein:

39.4GJ/ton

25.6Ammonia: 28.6GJ/ton


Tolu ene: 72.7GJ/ton

Phenol: 76.5GJ/ton




12.5GJ/ton biomass

438GJ/ha

27.7GJ/ton

64.7GJ/ton

Boiler: 7.7GJ/ton

17.2Ethylene: 25.0GJ/ton


0GJ/ton

Simple Carbohydrates : 5.8GJ/ton

Styrene: 31.1GJ/ton Ammonia: 31.0GJ/ton

Sugar-to-Bioethanol (Mash ing)




Ash: 57.9GJ/ton

Next Generation

Phenol: 16.0GJ/ton

Toluene: 29.4GJ/ton

20

10


CRACKER



45.1

60

Styrene: 83.9GJ/ton


70






Biomass

1.92GJ/ton

CassavaNigeria

50 ton /ha tube r

35.1to ta lDW/ha

42.8

40

50

30



Lignin: 40.0GJ/ton

Protein:

39.4GJ/ton




Phenol: 76.5GJ/ton




12.5GJ/ton biomass

438GJ/ha

27.7GJ/ton

64.7GJ/ton

Boiler: 7.7GJ/ton



0GJ/ton


Styrene: 31.1GJ/ton Ammonia: 31.0GJ/ton





Exergy

Ash: 61.7GJ/ton


Next Generation

Styrene: 15.3GJ/ton


0GJ/ton

20

10


CRACKER



18.0

60

Styrene: 84.5GJ/ton


70






Biomass

2.04GJ/ton

CassavaNigeria

50 ton /ha tube r

35.1to ta lDW/ha

22.8

40

50

30



Lignin:

42.3GJ/ton

Protein:

42.0GJ/ton




Phenol: 75.8GJ/ton



23.3GJ/ton biomass

817GJ/ha

-3.9GJ/ton

65.3GJ/ton

Boi ler: 6.3GJ/ton Simple Carbohydrates: 6.2GJ/ton

12.3


Toluene: 21.8GJ/tonAmmonia: 23.0GJ/tonPhenol: 23.6GJ/ton





Ash: 61.7GJ/ton


Next Generation

Styrene: 15.3GJ/ton


0GJ/ton

20

10


CRACKER



18.0

60

Styrene: 84.5GJ/ton


70






Biomass

2.04GJ/ton

CassavaNigeria

50 ton /ha tube r

35.1to ta lDW/ha

22.8

40

50

30



Lignin:

42.3GJ/ton

Protein:

42.0GJ/ton




Phenol: 75.8GJ/ton



23.3GJ/ton biomass

817GJ/ha

-3.9GJ/ton

65.3GJ/ton

Boi ler: 6.3GJ/ton Simple Carbohydrates: 6.2GJ/ton

12.3


Toluene: 21.8GJ/tonAmmonia: 23.0GJ/tonPhenol: 23.6GJ/ton






Overview Savings



Ethylene 0.210 7.38 62.4% 17.27 -2.41

Phenol 0.016 0.55 4.7% 1.29 -0.18

Styrene 0.017 0.61 5.1% 1.42 -0.20

Toluene 0.015 0.54 4.6% 1.26 -0.18

1,4-butandiamine 0.007 0.25 2.1% 0.59 -0.08

Acrylamide 0.001 0.04 0.3% 0.08 -0.01

Adipic acid 0.000 0.01 0.0% 0.01 0.00

Ammonia 0.002 0.07 0.6% 0.15 -0.02

ε-caprolactum 0.002 0.09 0.7% 0.20 -0.03

Ethylamine 0.007 0.24 2.0% 0.56 -0.08


Feed grade cysteine 0.001 0.04 0.3% 0.09 -0.01


γ-butyrolactum 0.004 0.12 1.0% 0.29 -0.04

Ionic liquids 0.001 0.04 0.4% 0.10 -0.01


Isoprene 0.008 0.30 2.5% 0.69 -0.10


Oxalic acid 0.002 0.09 0.7% 0.20 -0.03

Urea 0.001 0.04 0.3% 0.09 -0.01

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.033 1.16 9.8% 2.72 -0.38

Description

- An inexpensive cropping system with its major component being logistics; Africa location.

- Has a very high fossil fuel replacement potential based primarily on ethylene production

and to a degree on ash/fertilizer meaning that the system does not make good use out of

biochemical functionality.

- Large unconverted streams feed to boiler which contribute to a large deviation in energy

and exergy to the point of a negative exergy demand.

- And a large efficiency increase potential in exergy over energy is foreseeable in ethylene

production; here 25 down to 16GJ/ton. Improvement Options

- Best practices conditions must be upheld calling for major improvements on current

cropping systems.

- Better sizing and drying techniques to further reduce the logistics input component.

- Focus solely on ethylene production; burn the rest.

- Has the potential to be the #1 cropping system, but must ensure that the produced off-

heat and energy production are utilized locally.


Medicago Sativa – Lucerne Common Names EU: Lucerne, USA: Alfalfa, Medic, Purple Medic, Medick, Barrelclover, Burclover and Trefoil

Classification Perennial, Legume, C-3

Appearance Clusters of clover-like leaves with purple flowers Height of 0.5 – 1.0 meter with roots up to 4.5meters in length

Varieties Over 200

Genetically Modified Varieties Additional tolerance to herbicide, tolerance to arid climates

Brief Description Planted all over the world and being high in minerals, vitamins and protein it is one of the most nutritious crops that can be utilized in any forage situation. It is the highest yielding forage plant.

Growth Details Native Area: Presumably Iran, Northern Middle East Location: All around the globe Climate: Cool - Temperate, dry, cannot survive with high heat and humidity

Temperature: 10 - 30°C Rainfall/Irrigation: 800 – 1600mm (average 1030mm) Soil Type: Wide variety, preferably dry lands Soil Acidity: 6.2 – 7.8 pH, grows poorly below pH 6 Plantation: 1 – 3cm, small seedlings require good seed-to-soil contact Press or air drill machinery, ploughed or rotated before reseeding Seeding Rate: Best: 6.5 – 11 kg/ha (favourable and ploughed in rows\ridges) Worst: 18 – 22 kg/ha (unfavourable and broadcast) Average: 13 – 17 kg/ha Companion Crop: Not advised as yield is strongly reduced Weed Control: Required for seeding; slow establishment and uncompetitive crop Cultivation: Year-round, with spring most successful, 2 – 3-month establishment duration Multiple cuttings, 3 – 5 per year, 6 – 8 years before rotation or replanting Harvesting: Easy and straightforward, upon budding for maximum protein levels

Nutrient/Fertilizer Requirement The best time to apply nutrients is before flowering and if possible with seeding, seed inoculation Inoculation bacteria strain: Rhizobium Meliloti (80% N uptake)


0

100

200

300

400

500

600

700

0 2 4 6 8 10 12 14 16

Dry Hay Yield (ton/ha)

Total P

lant Uptake (kg/ha)

N

P2O5

K2O

CaO

MgO

SO3

Poly. (N)

Po ly. (P2O5)

Po ly. (K2O)

Po ly. (CaO)

Po ly. (MgO)

Po ly. (SO3)


0

100

200

300

400

500

600

700

800

900

1000

0 2 4 6 8 10 12 14 16


Total Plant Uptake (g

/ha)

Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe)

Poly . (Mn)

Poly . (B)

Poly . (Zn)

Poly . (Mo)

Poly . (Cu)


Yield Normal Conditions: 4 – 14 ton (1.0 – 3.5 ton/ha dry) (with no conditioning) 12 – 24 ton/ha (with bacterial and fertilizer conditioning) Optimal Conditions: 40 – 60 ton/ha (with bacterial and fertilizer conditioning) 80 – 120 ton/ha (experimental figures) Worldwide Cultivation: 33 million hectares at 4 ton/ha (or 1 ton/ha dry)

Chemical Composition*

(Based on dry weight) Constituent Stem/Tuber Leaves Whole Plant

Moisture Content 69.5% 82.7% 75%

Cellulose 34 28 31 Hemicellulose 12 8 10 Lignin 9 5 7 Protein 11 31 21 Oils - - - Fats - - - Minerals - - - Ash 7 - - Others 26 28 27

*Strongly dependent on all growing factors, location and nutrient levels Lower Heat Value: 17691 kJ/kg Higher Heat Value: 18978 kJ/kg

Detailed Information Whole Plant

Free Amino Acid g/kg %

Alanine 2.37 6.33

Isoleucine 1.63 4.36 Leucine 2.93 7.83

Methionine 0.32 0.86

Phenylalanine 1.76 4.70 Proline 3.53 9.43

Tryptophan Unknown


Valine 2.37 6.33 Asparagine Unknown

Cysteine Unknown

Glutamine Unknown Glycine 1.82 4.86

Serine 2.04 5.45

Threonine 1.99 5.32

Polar & Hydrophilic

Tyrosine Unknown

Asparagic Acid 7.53 20.12 Acidic

Glutamic Acid 3.68 9.83

Arginine 1.90 5.08 Histidine 1.22 3.26 Basic

Lysine 2.33 6.23

Total 39.23 (18% of Protein)

Comments Most information regarding alfalfa is aimed towards the production of fodder in the form of hay and pellets. USA is the largest producer with 23 million ton per year at 1.25 DW ton/ha.


Comparative Graph

Energy

Fert ilizers: 3.4GJ/ton Un-utilizedBiochemicals:

0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

33.8

60

Styrene: 83.9GJ/ton


70

Lignocellulose-to-Bioethanol (Dilu te)



- Chemical vs. Biomass Cumulative

Process Energy Demand





Biomass

5.17GJ/ton

LucerneSouth Dakota

15.0ton/ha dry hay

15.0to ta lDW/ha

67.2

40

50

30


Complex C5


Lignin: 112GJ/ton

Protein: 35.6GJ/ton

Ash: 46.5GJ/ton

49.7

Phenol: 39.3GJ/ton

Toluene: 52.3GJ/ton

Styrene: 56.9GJ/ton

Ammonia: 18.9GJ/ton



Phenol: 76.5GJ/ton



12.4GJ/ton biomass

186GJ/ha

27.7GJ/ton

Boiler: 7.1GJ/ton


Ammonia: 31.0GJ/ton

56.9GJ/ton

Fert ilizers: 3.4GJ/ton Un-utilizedBiochemicals:

0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

33.8

60

Styrene: 83.9GJ/ton


70










Biomass

5.17GJ/ton

LucerneSouth Dakota

15.0ton/ha dry hay

15.0to ta lDW/ha

67.2

40

50

30


Complex C5


Lignin: 112GJ/ton

Protein: 35.6GJ/ton

Ash: 46.5GJ/ton

49.7

Phenol: 39.3GJ/ton

Toluene: 52.3GJ/ton

Styrene: 56.9GJ/ton

Ammonia: 18.9GJ/ton



Phenol: 76.5GJ/ton



12.4GJ/ton biomass

186GJ/ha

27.7GJ/ton

Boiler: 7.1GJ/ton


Ammonia: 31.0GJ/ton

56.9GJ/ton

Exergy

Lignin: 127GJ/ton

Ash: 52.8GJ/ton


Next Generation

Phenol: 53.8GJ/ton

Styrene: 42.6GJ/ton


0GJ/ton

20

10


CRACKER



48.5

60

Styrene: 84.5GJ/ton


70







Ammonia: 23.0GJ/ton



Biomass

5.86GJ/ton

LucerneSouth Dakota

15.0ton/ha dry hay

15.0to ta lDW/ha

66.8

40

50

30



Protein:40.4GJ/ton

29.2

Ammonia: 15.1GJ/ton



Phenol: 75.8GJ/ton



13.0GJ/ton biomass

195GJ/ha

26.2GJ/ton

57.0GJ/ton


Toluene: 48.6GJ/ton

Boi ler: 5.9GJ/ton

Lignin: 127GJ/ton

Ash: 52.8GJ/ton


Next Generation

Phenol: 53.8GJ/ton

Styrene: 42.6GJ/ton


0GJ/ton

20

10


CRACKER



48.5

60

Styrene: 84.5GJ/ton


70







Ammonia: 23.0GJ/ton



Biomass

5.86GJ/ton

LucerneSouth Dakota

15.0ton/ha dry hay

15.0to ta lDW/ha

66.8

40

50

30



Protein:40.4GJ/ton

29.2

Ammonia: 15.1GJ/ton



Phenol: 75.8GJ/ton



13.0GJ/ton biomass

195GJ/ha

26.2GJ/ton

57.0GJ/ton


Toluene: 48.6GJ/ton

Boi ler: 5.9GJ/ton


Overview Savings



Ethylene 0.127 1.91 30.1% 8.33 7.89

Phenol 0.015 0.23 3.5% 0.98 0.93

Styrene 0.017 0.25 3.9% 1.09 1.03

Toluene 0.015 0.22 3.5% 0.96 0.91

1,4-butandiamine 0.016 0.24 3.8% 1.05 0.99

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.000 0.00 0.0% 0.00 0.00

Ammonia 0.005 0.07 1.2% 0.33 0.31

ε-caprolactum 0.009 0.14 2.2% 0.60 0.57

Ethylamine 0.031 0.46 7.3% 2.01 1.90




γ-butyrolactum 0.015 0.23 3.6% 1.00 0.95

Ionic liquids 0.004 0.07 1.0% 0.29 0.27


Isoprene 0.025 0.38 5.9% 1.64 1.55


Oxalic acid 0.007 0.10 1.6% 0.45 0.43

Urea 0.003 0.05 0.8% 0.23 0.21

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.111 1.67 26.2% 7.27 6.88

Description

- It is the most expensive crop to cultivate and harvest. Biomass acquisition energy intensity

is mainly associated with irrigation and logistics.

- The ash content is also abnormally high which greatly reduces the fossil fuel energy and

exergy replacement potential and presents a minimal increase of exergy versus energy in

the overall savings potential.

- The resulting cumulative energy and exergy to produce ethylene is still safely below the

break-even point therfore contributing to a positive savings potential.

- Residual protein content and concentration are perfectly suited for downstream processing

to amine-based chemicals despite the high associated feedstock costs.

Improvement Options

Problem is not processing or biomass composition but solely biomass acquisition energy:

- Relocate to a region without heavy use of aquifer-based irrigation and closer to cluster port

for half-product processing; for example, Eastern Europe (i.e. Poland).

- A harvesting or washing technique with less soil take up and without a yield loss.


Nicotiana Tabacum L. – Tobacco Common Names Tobacco, flue-cured tobacco, Virginia tobacco

Classification Perennial, harvested as annual, nightshade family, C-3

Appearance 0.9 – 2m tall, thick-stemmed shrub, white to purple cluster of flowers, 30 – 40cm long, 15 – 20cm thick spiralling Leaves

Varieties Several, major types divided by colour and curing methods: Brightleave, White Burley, Shade, Perique, etc.

Genetically Modified Varieties Yes, against diseases and for high protein and amino-acid content make it an ideal plant to develop as a source of limited and specialized nutrients.

Brief Description Known to natives of the Americas for thousands of years, it was used in various forms to release the hallucinogenic stimulant nicotine alkaloid. Upon colonization of America major cultivation efforts began with the success of European introduction and subsequent demand.

Growth Details Native Area: South and Central America Location: Worldwide, almost chiefly in the Southern United States Climate: Currently a wide variety, although mainly warm subtropical, frost-free

Temperature: 20 - 30°C Rainfall/Irrigation: 400 – 600mm, can withstand 1 month drought, sensitive to over irrigation Soil Type: Light sands – thick loam, sandy soil best, must be well aerated and drained Soil Acidity: 5 – 6.5pH, preferable 5.7 – 6.0pH Plantation: Sown in seedbeds, grown for 40 – 60 days under cover, transplanted to fields at 15cm

tall, field spacing 1.2-0.9m x 0.9-0.6m, pre-dug holes Seeding Rate: 0.125 – 0.175t/ha, 1800 – 2200seeds/m² of seedbed Companion Crop: No, rotated every 1-2 years with non eelworm susceptible crops (e.g. maize) Pest and Disease: Yes (i.e. tobacco beetle), some GMO’s act against Weed Control: Not problems as plants are transplanted and can compete Cultivation: Early April seeding, automated late June transplanting, hand suckering (only

important for nicotine uses) end August – early September harvesting Harvesting: Manual cutting of individual Leaves, several at a time with sickle or mechanical whole

crop pulling operations

Nutrient/Fertilizer Requirement Based on published data of the American flue-cured species and Australian biomass species:


0

50

100

150

200

250

300

350

0 5 10 15 20 25 30

Dry Hay Yield (ton /ha)


N

P2O5

K2O

CaO

MgO

SO3

Log. (N)

Log. (P2O5)

Log. (K2O)

Log. (CaO)

Log. (MgO)

Log. (SO3)


0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 5 10 15 20 25 30


Total Plant U

ptake (g/ha)

Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe )

Poly . (Mn)

Poly . (B)

Poly . (Zn)

Poly . (Mo)

Poly . (Cu)


Yield Normal Conditions: 10 – 20 ton/ha (Leaves, relates to 1.5 – 4.0 ton/ha traditionally cured leaves) 16 – 33.2 ton/ha (total plant) Optimal Conditions: 200 – 240 ton/ha (year-round, 5 harvests, treated like grass, .au) 24 – 30 ton/ha (dry leafy material, no stalk growth) Worldwide Cultivation: 4.0 million hectares at 18 ton/ha (1.6 ton/ha of cured leaves)


Constituent Leaves Stalk Whole Plant (for nicotine)

Whole Plant (for biomass)

Moisture Content 88% 35% 65% 88%

Cellulose 36.3 42.4 29.1 36.3 Hemicellulose 34.4 28.2 33.0 34.4 Lignin 12.1 27.0 14.8 12.1 Starch - - 3.0 - Protein 12.0 - 14.8 12.0 Oils - - - - Fats - - - - Minerals - - 1.8 - Ash 5.2 2.4 - 5.2 Others - - 3.5 -

*Strongly dependent on all growing factors, location and nutrient levels In air-cured variety leaves represent about 3/5 of the total wet plant mass Higher Heat Value: 19370 kJ/kg (leaf), 19375 kJ/kg (stalk) Lower Heat Value: 16035 kJ/kg (leaf), 18910 kJ/kg (stalk)

Detailed Information The protein of tobacco can be easily fractionated. Between 30 and 50% of the soluble proteins are of a high nutritional value that can be crystallized and easily extracted, only 1% of amino acids are free. The rest of the proteins are group in a second fraction.

Amino Acid Composition of Plant Protein

Whole Plant (Protein Fraction 1)

Whole Plant (Protein Fraction 2)

Alanine 7.0 5.1

Isoleucine 4.3 3.7

Leucine 8.8 4.1 Methionine 1.6 4.1

Phenylalanine 4.4 8.4

Proline 4.6 8.2 Tryptophan 4.9 8.8


Valine 7.2 10.4

Asparagine Trace Trace Cysteine 3.0 0.8

Glutamine Trace Trace

Glycine 9.2 3.5 Serine 3.3 4.0

Threonine 5.2 4.6

Polar & Hydrophilic

Tyrosine 1.5 Trace Asparagic Acid 8.5 6.1

Acidic Glutamic Acid 11.2 8.9

Arginine 6.1 10.3

Histidine 2.2 5.0 Basic

Lysine 5.8 3.9

Total 98.9% of Protein 99.9% of Protein Tobacco is of course cultivated for its nicotine levels. They can vary from 1.5 – 2.5DW% depending on the crop age, GMO’s up to 4%. 65% is present in the Leaves, rest in the stalk.

Comments It has been mentioned that 4-5 times more proteins can be harnessed from tobacco than from corn and even soya beans using existing technology and yields.


Comparative Graph

Energy

Fertilizers: 3.0GJ/ton Un-utilizedBiochemicals:

0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

28.2

60



70





Fertilizers: 85.6GJ/to n

Amin e Chem icals: 17.1GJ/to n

Biomass

3.43GJ/ton

TobaccoAustralia

200ton/ha wet hay

26.5to ta lDW/ha25.9

40

50

30



Lignin: 49.6GJ/ton

Protein:

44.5GJ/ton

Ash: 85.6GJ/ton

28.9

Phenol: 19.2GJ/ton

Toluene: 34.6GJ/ton

Styrene: 32.5GJ/ton

Ammonia: 19.4GJ/ton



Phenol: 76.5GJ/ton



13.1GJ/ton biomass

347GJ/ha

29.2GJ/ton

Boiler: 7.6GJ/ton


Ammonia: 31.0GJ/ton

64.7GJ/ton




Fertilizers: 3.0GJ/ton Un-utilizedBiochemicals:

0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

28.2

60



70







Biomass

3.43GJ/ton

TobaccoAustralia

200ton/ha wet hay

26.5to ta lDW/ha25.9

40

50

30



Lignin: 49.6GJ/ton

Protein:

44.5GJ/ton

Ash: 85.6GJ/ton

28.9

Phenol: 19.2GJ/ton

Toluene: 34.6GJ/ton

Styrene: 32.5GJ/ton

Ammonia: 19.4GJ/ton



Phenol: 76.5GJ/ton



13.1GJ/ton biomass

347GJ/ha

29.2GJ/ton

Boiler: 7.6GJ/ton


Ammonia: 31.0GJ/ton

64.7GJ/ton




Exergy

Lignin: 52.2GJ/ton

Ash: 90.1GJ/ton


Next Generation

Phenol: 27.1GJ/ton

Styrene: 18.5GJ/ton


0GJ/ton

20

10


CRACKER



22.0

60



70






Biomass

3.61GJ/ton

TobaccoAustralia

200ton/ha wet hay

26.5to ta lDW/ha

19.1

40

50

30

Complex C6 Carbohydrates: 11.2GJ/tonComplex C5 Carbohydrates: 12.5GJ/ton

Protein:

46.8GJ/ton

23.6

Ammonia: 12.7GJ/ton



Phenol: 75.8GJ/ton



21.9GJ/ton biomass

582GJ/ha

5.31GJ/ton

65.0GJ/ton

Boi ler: 6.2GJ/ton


Toluene: 24.9GJ/ton




Ammonia: 23.0GJ/ton

Lignin: 52.2GJ/ton

Ash: 90.1GJ/ton


Next Generation

Phenol: 27.1GJ/ton

Styrene: 18.5GJ/ton


0GJ/ton

20

10


CRACKER



22.0

60



70






Biomass

3.61GJ/ton

TobaccoAustralia

200ton/ha wet hay

26.5to ta lDW/ha

19.1

40

50

30


Protein:

46.8GJ/ton

23.6

Ammonia: 12.7GJ/ton



Phenol: 75.8GJ/ton



21.9GJ/ton biomass

582GJ/ha

5.31GJ/ton

65.0GJ/ton

Boi ler: 6.2GJ/ton


Toluene: 24.9GJ/ton




Ammonia: 23.0GJ/ton


Overview Savings



Ethylene 0.187 4.97 50.9% 14.84 2.70

Phenol 0.022 0.59 6.1% 1.77 0.32

Styrene 0.025 0.66 6.7% 1.96 0.36

Toluene 0.022 0.58 6.0% 1.74 0.32

1,4-butandiamine 0.010 0.26 2.7% 0.79 0.14

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.005 0.13 1.4% 0.40 0.07

Ammonia 0.005 0.13 1.4% 0.40 0.07

ε-caprolactum 0.003 0.08 0.8% 0.22 0.04

Ethylamine 0.008 0.21 2.1% 0.61 0.11




γ-butyrolactum 0.007 0.17 1.8% 0.52 0.09

Ionic liquids 0.003 0.09 0.9% 0.27 0.05


Isoprene 0.008 0.21 2.1% 0.63 0.11


Oxalic acid 0.002 0.06 0.7% 0.19 0.04

Urea 0.003 0.09 0.9% 0.27 0.05

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.040 1.06 10.9% 3.17 0.58

Description

- The very high dry biomass yield can offset to a large degree the biomass acquisition energy

intensity including the hefty logistics costs.

- Main biomass component is lignocellulose resulting in a large quantity of ethylene and at a

relatively low process energy intensity.

- Aromatics are also produced in significant quantities at vastly lower cumulative energy as

compared to traditional process routes.

- Those products (ethylene & aromatics) which rely heavily on thermal processes have a

large difference between energy and exergy demand while supplying the boiler with large

unconverted material streams.

Improvement Options

- Relocated to closer location, such as Southern Europe (i.e. Spain), could vastly decrease the

feedstock energy cost and promote tobacco as one of the best cropping system options.

Should be able, with the right conditions, to outperform Dutch ryegrass.

- Focus on lignin separation and conversion techniques.

- Promote an increase in lignin content by allowing the crop to age; propitiously decrease

harvesting costs and inadvertent soil contamination.


Lolium Perenne – Grass Common Names Ryegrass, grass, green grass, European grass

Classification Perennial, tufted grass, C-3

Appearance 8 – 90cm tall green stems, loosely to densely tufted, shinny folded Leaves, 2 – 6mm narrow, 3 – 20cm long, 3 – 31 cm long spikelets, deep rooting system, 1 – 1.5 meters, most 15cm below topsoil

Varieties Practically infinite, many natural hybrids

Genetically Modified Varieties Countless amounts, developed for application purpose type, highly regulated

Brief Description Grass grows nearly year round, spreads and tills naturally. It has many purposes when manually tilled including: natural grasslands, lawns, pastures, grazing, hay production, soil erosion prevention and possibly as a source of biomass.

Growth Details Native Area: Eurasia and Northern Africa Location: Eurasia and has spread to the rest of the world in various subspecies Climate: Temperate, mild and humid (oceanic/rainy)

Temperature: 4.3 – 23.7°C, sensitive to frost and high temperatures Rainfall/Irrigation: 210 – 820mm, 500mm good yields, <400mm poor yields. Tolerate up to 1760mm. More important than nutrients, cannot tolerate drought or floods Soil Type: Heavy, nutrient rich, moist soils; dry and wet soils not suitable Soil Acidity: 4.5 – 8.2pH tolerance, average 6.3 – 6.7pH, slightly acidic Plantation: Grid drilling or broadcast, 20 – 60cm row spacing, long-lived pasture strains, sown

perennials 10 – 30% higher yielding Seeding Rate: EU: 10 – 20kg/ha drilling, 6 – 20kg/ha broadcast, combined with 12 – 28 kg/ha clover seeds, 440 – 585 kseeds/kg, 20 – 50 kplants/ha (tillers) Companion Crop: Yes, usually the leguminous clover Pest and Disease: No, highly resistant Weed Control: Can become a problem during long-term rotations, reseeding prevents (yearly) Cultivation: Sown in early spring, fast and peak growth during late spring/early summer Harvesting: Growth decreases in late autumn, 7-8 months growth period, multiple cuttings

possible, increase shout growth and yield

Nutrient/Fertilizer Requirement Sown with clovers, inoculation bacteria strain: Rhizobium Trifolii (59% N uptake) Legume sowing is not sufficient to supply all nitrogen, additional fertilizer added


0

50

100

150

200

250

300

350

400

0 2 4 6 8 10 12 14



N

P2O5

K2O

CaO

MgO

SO 3

Po ly. (N)

Po ly. (P2O 5)

Po ly. (K2O )

Po ly. (CaO )

Po ly. (MgO)

Po ly. (SO3)


0

500

1000

1500

2000

2500

0 2 4 6 8 10 12 14 16



Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe )

Poly . (Mn)

Poly . (B)

Poly . (Zn)

Poly . (Mo)

Poly . (Cu)


Yield Normal Conditions: 18 – 30 ton/ha (5 – 8 ton/ha dry hay) Optimal Conditions: 55 – 80 ton/ha (10 – 14 ton/ha dry hay, 2-3 cuttings) European average: 47 ton/ha (12.5 ton/ha dry hay) (2-3 cuttings) Best Practice NL: 14.1 ton/ha dry hay 60 – 100+ ton/ha fresh weight, GMO tests (8-9 cuttings) Worldwide Cultivation: 3.5 billion hectares grazing land at less than 10 ton/ha (2.5 ton/ha dry)

Chemical Composition* (Based on dry weight, common European species)

Constituent Grass White Clover Mix†

Moisture Content 82.4% 82.7% 82.5 Cellulose 30.6 28.3 29.7 Hemicellulose 21.8 20.6 21.3 Lignin 3.1 2.5 2.9 Protein 17.9 22.1 19.4 Sugars 10.5 12.0 11.1 Oils Fats

4.9 2.9 4.2

Ash 11.3 11.6 11.4

*Strongly dependent on all growing factors, location and nutrient levels †typical mix is 37% clover cover over the course of the growing season Higher Heat Value: 19430 kJ/kg Lower Heat Value: 17800 kJ/kg

Detailed Information The amino acid concentration and constituents are very similar to that of wheat. This can be expected as they are very closely related within the same botanical species. Higher mixtures of legumes (i.e. clover) reduce protein content and amino acid concentration. Ryegrass/clover mix herbage composition of essential amino acids:

Whole Plant Amino Acid Composition of Protein g/kg %

Isoleucine 5.92 4.46

Leucine 10.05 7.58

Methionine 1.82 1.37 Phenylalanine 6.13 4.62

Tryptophan Trace


Valine 7.81 5.89 Polar & Hydrophilic

Threonine 6.09 4.59

Arginine 7.78 5.87

Histidine 6.24 4.71 Basic

Lysine 8.72 6.58

Other amino acids

72.03 54.33

Total 132.6 g (79.0% of Protein) Grass is a good source of carotene (4.8 mg/100 g). It contains free fructose, fructosan, mannitol, a complex mixture of oligosaccharides; oxalic-, citric-, malic-, and shikimic- acids, glycerides, and a wax containing hexacosanol.

Comments It has been researched that between 15 – 40% of grown biomass is present in rooting system. Natural ryegrass is a diploid and no polyploids occur, however, in The Netherlands a tetraploid variety (2n=28) was developed and employed in the 60’s. These species have a high tiller density, water solubility for carbohydrates, better yields and are best for large-scale animal production. These properties would be equally advantageous for biomass production applications.


Comparative Graph

Energy


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

26.9

60



70








Ammonia: 31.0GJ/tonF ertilizers: 30.4GJ/to n


Biomass

2.45GJ/ton

GrassThe Netherlands

80.5ton/ha wet hay

14.1to ta lDW/ha

27.8

40

50

30



Lignin: 148GJ/ton

Protein: 21.3GJ/ton

Ash: 30.4GJ/ton

61.8

Phenol: 51.1GJ/ton

Toluene: 63.8GJ/ton

Styrene: 69.9GJ/ton

Ammonia: 15.0GJ/ton



Phenol: 76.5GJ/ton




17.6GJ/ton biomass

249GJ/ha

7.13GJ/ton 58.0GJ/ton

Boiler: 14.1GJ/ton


0GJ/ton


20

10


CRACKER



Next Generation

0GJ/ton

26.9

60



70








Ammonia: 31.0GJ/tonF ertilizers: 30.4GJ/to n


Biomass

2.45GJ/ton


80.5ton/ha wet hay

14.1to ta lDW/ha

27.8

40

50

30



Lignin: 148GJ/ton

Protein: 21.3GJ/ton

Ash: 30.4GJ/ton

61.8

Phenol: 51.1GJ/ton

Toluene: 63.8GJ/ton

Styrene: 69.9GJ/ton

Ammonia: 15.0GJ/ton



Phenol: 76.5GJ/ton




17.6GJ/ton biomass

249GJ/ha

7.13GJ/ton 58.0GJ/ton

Boiler: 14.1GJ/ton

Exergy

Lignin: 163GJ/ton

Ash: 33.5GJ/ton


Next Generation

Phenol: 66.7GJ/ton

Styrene: 54.3GJ/ton


0GJ/ton

20

10


CRACKER



21.1

60



70







Ammonia: 23.0GJ/ton


Biomass

2.70GJ/ton


80.5ton/ha wet hay

14.1tota lDW/ha21.7

40

50

30



Protein: 19.9GJ/ton

60.6



Phenol: 75.8GJ/to n



19.3GJ/ton biomass

272GJ/ha

2.5GJ/ton

58.1GJ/ton

Boiler: 11.0GJ/ton


Toluene: 60.0GJ/ton

Ammonia: 10.6GJ/to n


Lignin: 163GJ/ton

Ash: 33.5GJ/ton


Next Generation

Phenol: 66.7GJ/ton

Styrene: 54.3GJ/ton


0GJ/ton

20

10


CRACKER



21.1

60



70







Ammonia: 23.0GJ/ton


Biomass

2.70GJ/ton


80.5ton/ha wet hay

14.1tota lDW/ha21.7

40

50

30



Protein: 19.9GJ/ton

60.6



Phenol: 75.8GJ/to n



19.3GJ/ton biomass

272GJ/ha

2.5GJ/ton

58.1GJ/ton

Boiler: 11.0GJ/ton


Toluene: 60.0GJ/ton




Overview Savings



Ethylene 0.136 1.91 39.1% 2.79 0.98

Phenol 0.005 0.08 1.5% 0.11 0.04

Styrene 0.006 0.08 1.7% 0.12 0.04

Toluene 0.005 0.07 1.5% 0.11 0.04

1,4-butandiamine 0.016 0.22 4.5% 0.32 0.11

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.003 0.05 1.0% 0.07 0.02

Ammonia 0.006 0.08 1.7% 0.12 0.04

ε-caprolactum 0.007 0.09 1.9% 0.14 0.05

Ethylamine 0.017 0.24 5.0% 0.36 0.13




γ-butyrolactum 0.009 0.13 2.6% 0.19 0.07

Ionic liquids 0.003 0.05 1.0% 0.07 0.02


Isoprene 0.020 0.28 5.8% 0.41 0.15


Oxalic acid 0.005 0.06 1.3% 0.09 0.03

Urea 0.004 0.06 1.3% 0.09 0.03

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.081 1.13 23.2% 1.65 0.58

Description

- By focusing on local production with a multi-year harvest the biomass acquisition energy

intensity is low providing a good starting point for many of the biomass components.

- Multiple harvests also renders protein at the ideal content and concentration promoting

effective and efficient amine chemistry conversions.

- Large unconverted waste streams are used to generate significant amounts of internal

process energy, however not quite sufficient to achieve a negative exergy value.

- Ash content is simply too high which reduces the potential effectiveness, albeit not as

severe as some of the other grasses, like lucerne. Improvement Options

- Increase yield; achieving dry weight yield in excess of 20ton/ha should be possible without

placing large increase in energy demand.

- A harvesting technique or washing technique with less soil take up and without yield losses.

- Since amines and ethylene are produced efficiently and effectively the lignin content may

be utilized to increase the internal heat and power generation, especially considering the

ease of incorporating it in the grid.


Panicum Virgatum – Switchgrass Common Names Switchgrass, Tall Panic Grass

Classification Tall-grass prairie, summer rhizomatous perennial, C-4

Appearance Up to 0.5 - 2.5 meter tall, round stem, reddish tint. Purple flowers, borne singly at the end of branches, root system up to 3m deep

Varieties Several wild varieties, two main types: upland and lowland

Genetically Modified Varieties None thus far

Brief Description Eating by all grazing animals, many framers plant it as means for forage or erosion control and more recently thoughts are given toward biomass applications. It is noted for its heavy growth in late spring and early summer.

Growth Details Native Area: North America Location: Various locations, mainly North America, parts of Europe & South America Climate: Temperate, can tolerate frost and snow cover

Temperature: 5 - 25°C, growth initiated at temperatures above 10°C Rainfall/Irrigation: 300 – 400mm, varies from type Soil Type: Moderately deep – deep, dry – poorly drained, sandy – clay loam, Soil Acidity: 4.9 – 7.6pH, neutrality is optimum Plantation: 2.5 – 10mm depth, mechanized with airflow, drill or no-till drills in rowed rolled

seedbed of 15 – 20cm width Seeding Rate: 5 – 10kg/ha, very small seeds, 500 – 1000seeds/g, reseeding at 4 – 5kg/h necessary

for frost application or with poor establishment Companion Crop: None, but clovers are a possibility Pest and Disease: Resistant to most, grasshoppers and leafhoppers, nothing serious Weed Control: Controlled by moving lawn when 10cm height reached, not essential Cultivation: Frost or spring seeding, possible growth cycle more than 10 years, 75% of mass

produced in summer upon flowering Harvesting: After second year, delayed until winter/early spring for re-growth reasons

Nutrient/Fertilizer Requirement Arbuscalar Mycorrhizal Fungi (AMF) symbiosis in Midwest. European soils do not contain the inoculating strain, yet investigation is underway for others. Inoculation bacteria strain: Mycorrhizae, more specifically Glomus etunicatum (30% N Uptake) First year growth will not incorporate nitrogen as to prevent weed growth stimulation


0

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300

400

500

600

700

0 2 4 6 8 10 12 14 16

Dry Hay Yield ( ton/ha)


N

P2O5

K2O

CaO

MgO

SO3

Poly. (N)

Poly. (P2O5)

Poly. (K2O)

Poly. (CaO)

Poly. (MgO )

Poly. (SO 3)


0

200

400

600

800

1000

1200

1400

0 2 4 6 8 10 12 14 16



Fe

Mn

B

Zn

Mo

Cu

Poly. (Fe)

Poly. (Mn)

Poly. (B)

Poly. (Zn)

Poly. (Mo)

Poly. (Cu)


Yield Normal Conditions: 3.5 – 14 ton/ha (dry, native area of the Midwest) 8 – 10 ton/ha (dry, average, also in Europe) Optimal Conditions: 6 – 25 ton/ha (dry, Southern European test sties) Worldwide Cultivation: Unknown as wild species (in excess of 25 million hectares at 5 ton/ha)

Chemical Composition* (Based on dry weight and the Alamo species)

Constituent Whole Plant

Moisture Content 12% Cellulose 31.0 Hemicellulose 24.4 Lignin 17.6 Pectin 1.2 Protein 9.0 Oils - Fats - Minerals 8.0 Ash 5.8 Others 4.0

*Strongly dependent on all growing factors, location and nutrient levels Higher Heat Value: 18560 kJ/kg Lower Heat Value: 17290 kJ/kg

Detailed Information Very little investigation is available for the amino acid content of Switchgrass. Generally speaking the protein (crude protein) content of the crop can reach up to 20% during the summer growth months and drop to below 4% during the winter senescence. 9.0% is upon biomass harvesting. Sugar extractives: 32.2 C-6 sugars 0.3% Mannan 0.9% Galactan 31.0% Glucan 23.2 C-5 sugars 2.8% Arabinan 20.4% Xylan

Comments Alamo species is more directed at warmer temperatures and wetter soil conditions. As a result is continues to grow longer and has an average yield of 14 t/ha. It should be noted that the moisture content is remarkably low and in addition to the low nutrient demands makes it the “cheapest energy crop”.


Comparative Graph

Energy


0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

28.9

60



70










Biomass

3.11GJ/ton

SwitchgrassIowa

15.9ton/ha wet hay

14.0to ta lDW/ha

28.5

40

50

30



Lignin: 31.0GJ/ton

Protein: 57.8GJ/ton

Ash: 37.0GJ/ton

22.7

Phenol: 13.1GJ/ton

Toluene: 27.9GJ/to nStyren e: 26.6GJ/ton

Ammonia: 19.9GJ/ton



Phenol: 76.5GJ/ton




14.8GJ/ton biomass

208GJ/ha

19.9GJ/ton

Boiler: 8.1GJ/ton


Ammonia: 31.0GJ/ton

58.4GJ/ton


0GJ/ton

20

10


CRACKER



Next Generation

0GJ/ton

28.9

60



70










Biomass

3.11GJ/ton

SwitchgrassIowa

15.9ton/ha wet hay

14.0to ta lDW/ha

28.5

40

50

30



Lignin: 31.0GJ/ton

Protein: 57.8GJ/ton

Ash: 37.0GJ/ton

22.7

Phenol: 13.1GJ/ton

Toluene: 27.9GJ/to nStyren e: 26.6GJ/ton

Ammonia: 19.9GJ/ton



Phenol: 76.5GJ/ton




14.8GJ/ton biomass

208GJ/ha

19.9GJ/ton

Boiler: 8.1GJ/ton


Ammonia: 31.0GJ/ton

58.4GJ/ton

Exergy

Ash: 40.0GJ/ton

Next Generation


0GJ/ton

20

10


CRACKER



23.1

60



70







Am in e Chemicals: 15.3GJ/to n

Biomass

3.37GJ/ton

SwitchgrassIowa

15.9ton/ha wet hay

14.0tota lDW/ha22.3

40

50

30

17.4




Phenol: 75.8GJ/to n



16.9GJ/ton biomass

236GJ/ha

15.3GJ/ton

59.1GJ/ton

Boi ler: 6.6GJ/ton


Toluene: 19.0GJ/ton

Protein: 62.6GJ/ton

Lignin: 33.5GJ/ton



Ammonia: 23.0GJ/ton

Styrene: 12.4GJ/ton

Phenol: 20.4GJ/ton



Ash: 40.0GJ/ton

Next Generation


0GJ/ton

20

10


CRACKER



23.1

60



70







Am in e Chemicals: 15.3GJ/to n

Biomass

3.37GJ/ton

SwitchgrassIowa

15.9ton/ha wet hay

14.0tota lDW/ha22.3

40

50

30

17.4




Phenol: 75.8GJ/to n



16.9GJ/ton biomass

236GJ/ha

15.3GJ/ton

59.1GJ/ton

Boi ler: 6.6GJ/ton


Toluene: 19.0GJ/ton

Protein: 62.6GJ/ton

Lignin: 33.5GJ/ton



Ammonia: 23.0GJ/ton

Styrene: 12.4GJ/ton

Phenol: 20.4GJ/ton




Overview Savings



Ethylene 0.150 2.10 39.0% 7.75 5.98

Phenol 0.033 0.46 8.4% 1.68 1.30

Styrene 0.036 0.50 9.3% 1.86 1.43

Toluene 0.032 0.45 8.3% 1.64 1.27

1,4-butandiamine 0.008 0.12 2.2% 0.44 0.34

Acrylamide 0.000 0.00 0.0% 0.00 0.00

Adipic acid 0.004 0.05 1.0% 0.20 0.15

Ammonia 0.003 0.04 0.7% 0.14 0.11

ε-caprolactum 0.002 0.03 0.6% 0.11 0.09

Ethylamine 0.008 0.11 2.1% 0.42 0.32




γ-butyrolactum 0.005 0.07 1.2% 0.25 0.19

Ionic liquids 0.001 0.01 0.3% 0.05 0.04


Isoprene 0.007 0.10 1.8% 0.35 0.27


Oxalic acid 0.002 0.03 0.5% 0.10 0.08

Urea 0.002 0.02 0.4% 0.09 0.07

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.084 1.18 21.8% 4.34 3.35

Description

- Regardless of being located in America (Iowa) the overall biomass acquisition energy is low

enough because the crop has sufficient yields.

- Due to the unique composition all the potential chemical products are in the same

generally low range of energy/exergy intensity.

- The lignin conversion to aromatics is particularly effective and efficient and is in large

quantities; combined reach more than a quarter of products.

- As with other grasses the ash/fertilizer in considerable and decreases the overall savings. Improvement Options

- Is no major improvement options foreseeable: will remain a middle-range cropping system.

- Relocated to closer location


Saccharum Officinarum L. – Sugar Cane Common Names Sugar cane, sugarcane, noblecane

Classification Asian perennial grass, legume, C-4

Appearance 3-5m height, 2-3cm thick panicle stem, tapering from bottom to top. Silky spikelets. Thin 4-6cm, 20-60cm long, nodule-sprouting green Leaves, roots span 30 cm at 2 meters depth.

Varieties 6 species origins: S. spontaneum, S. robustum, S. officinarum, S. barberi, S. sinense and S. edule. Cultivated versions are hybrids! Genetically Modified Varieties None, but plant breeding hybrids usually tri- or quadrispecific

Brief Description The major source of sugar production. With the advent of the European policy changes the market will must likely collapse and shift to industrial applications, like ethanol. The by-products, bagasse is also used in the paper industry and energy sector. Sugarcane is the world's largest crop.

Growth Details Native Area: South Pacific Islands Location: Throughout the southern tropics, Brazil and India being large producers Climate: Tropics – subtropics, rainforest areas, hot and humid

Temperature: Above 30°C, growth cesses at temperature below 19°C Rainfall/Irrigation: 1500mm is a minimum; average is 1675mm, partially drought resistant High water efficiency, 250 parts water for each part of dry matter Soil Type: Wide variety with drainage a basic requirement Soil Acidity: 4.3 – 8.4pH, average 6.3 Plantation: Stalk furrowing (stem cuttings), two node length, mechanized with chopper-planter, 15-30cm deep, 1.3 – 1.4 meters distance Seeding Rate: 6000 – 7000kg planted stalks/ha create 90 000-150 000 plants/ha. Companion Crop: Leguminous manure and smaller crops Weed Control: Heavy use of herbicides, upon proper canopy development no more Pest and Disease: Susceptible to many viruses and fungi Cultivation: Deep ploughing and ridging necessary, no rotation required, 3-4 years continuous growth up to 8, year round plantation possible Harvesting: Upon stem discolouration, 12 – 20 months upon plantation, cooler periods

Nutrient/Fertilizer Requirement Not exactly a leguminous crop but can harness legumes growth, leguminous manure and side field crops can cover 70% of the nitrogen demand


0

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40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160

Green Biomass Y ield (ton/ha)


N

P2O5

K2O

CaO

Mg O

SO3

Poly. (N)

Poly. (P2 O5)

Poly. (K2 O)

Poly. (Ca O)

Poly. (MgO )

Poly. (SO 3)


0

100

200

300

400

500

600

700

800

900

0 20 40 60 80 100 120 140 160

Green Biomass Y ield (ton/ha)


Fe

Mn

B

Zn

Mo

Cu

Po ly. (Fe )

Po ly. (Mn )

Po ly. (B)

Po ly. (Zn)

Po ly. (Mo )

Po ly. (Cu)


Yield Normal Conditions: 15 – 100ton/ha, 72.3ton/ha cane (Brazil: 5-year average) Best Brazilian practice: 140ton/ha green biomass (35ton/ha dry) Optimal Conditions: The theoretical maximum yield (PAR) is 280 ton/ha/y wet weight Worldwide Cultivation: 20 million hectares at 65.5 ton/ha

Chemical Composition* (Based on dry weight: multiple year average)

Constituent Cane/Stem Leaves

Moisture Content 82.5% 77.5% Cellulose 22.3 38.7 Hemicellulose 18.5 32.4 Lignin 3.9 7.1 Sucrose 46.2 - Other Sugars 2.0 - Protein 0.6 8.0 Fats 0.6 3.6 Oil - - Minerals 1.4 1.1 Ash 1.7 8.9 Others 2.8 -

*Strongly dependent on all growing factors, location and nutrient levels Stalk represents ¾ of the total wet weight It is common practice in Brazil to burn the leaves before harvesting canes, loss of ¼ wet weight Lower Heat Value: 18990kJ/kg (bagasse), 21500 kJ/kg (cane juice), 16000 kJ/kg (leaves) Higher Heat Value: 17710kJ/kg (bagasse), 21000 kJ/kg (cane juice), 16500 kJ/kg (leaves)

Detailed Information Sugar cane itself provides negligible amounts of protein, and supplements are needed when used as a fodder. Stem contains only 0.62 percent in the dry matter. It is the lowest of all other biomass fodder options on amino acid usage. Bagasse (the waste of the sugar processing) is usually burned to harness the contained energy. The industry is autonomous, meaning the bagasse supplied all the heat, steam and electricity to run the sugar plant.

Comments Experimental figures can produce yields of over 35 ton/ha cane of dry weight, which is amazingly high. As the sugar market will shift, investigation should be made on utilizing the existing infrastructure to produce something else.


Comparative Graph

Energy

Protein: 216GJ/ton

Ash: 163GJ/ton


0GJ/ton

Next Generation

Toluene: 34.8GJ/tonStyrene: 37.2GJ/ton

20

10


CRACKER



22.4

60

Styrene: 83.9GJ/ton


70




Fertilizers: 163GJ/tonAmine Chemicals: 144GJ/ton

Biomass

1.34GJ/ton

Sugar CaneBrazil

125ton/ha cane

43.5to ta lDW/ha

25.2

40

50

30


Lignin: 56.8GJ/ton

31.4

Ammonia: 126GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




11.3GJ/ton biomass

490GJ/ha

24.4GJ/ton

66.4GJ/ton

Boiler: 8.2GJ/ton



Phenol: 21.5GJ/ton

Ammonia: 31.0GJ/ton





Protein: 216GJ/ton

Ash: 163GJ/ton


0GJ/ton

Next Generation


20

10


CRACKER



22.4

60

Styrene: 83.9GJ/ton


70




Fertilizers: 163GJ/tonAmine Chemicals: 144GJ/ton

Biomass

1.34GJ/ton

Sugar CaneBrazil

125ton/ha cane

43.5to ta lDW/ha

25.2

40

50

30


Lignin: 56.8GJ/ton

31.4

Ammonia: 126GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




11.3GJ/ton biomass

490GJ/ha

24.4GJ/ton

66.4GJ/ton

Boiler: 8.2GJ/ton



Phenol: 21.5GJ/ton

Ammonia: 31.0GJ/ton





Exergy

Ash: 172GJ/ton

Next Generation

Toluene: 27.4GJ/ton


0GJ/ton

20

10


CRACKER



18.0

60

80

70




Fertilizers: 172GJ/ton

Biomass

1.41GJ/ton

Sugar CaneBrazil

125ton/ha cane

43.5to ta lDW/ha

15.2

40

50

30


Lignin: 59.9GJ/ton

Protein:227GJ/ton

26.2

Ammonia: 64.7GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



22.6GJ/ton biomass

985GJ/ha

67.3GJ/ton

Boi ler: 6.7GJ/ton

Simple Carbohydrates: 3.5GJ/ton9.1



Styrene: 29.9GJ/ton

Phenol: 21.0GJ/ton

Styrene: 84.5GJ/ton


-17.0GJ/ton





Ammonia: 23.0GJ/ton


Ash: 172GJ/ton

Next Generation

Toluene: 27.4GJ/ton


0GJ/ton

20

10


CRACKER



18.0

60

80

70





Biomass

1.41GJ/ton

Sugar CaneBrazil

125ton/ha cane

43.5to ta lDW/ha

15.2

40

50

30


Lignin: 59.9GJ/ton

Protein:227GJ/ton

26.2

Ammonia: 64.7GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



22.6GJ/ton biomass

985GJ/ha

67.3GJ/ton

Boi ler: 6.7GJ/ton

Simple Carbohydrates: 3.5GJ/ton9.1



Styrene: 29.9GJ/ton

Phenol: 21.0GJ/ton

Styrene: 84.5GJ/ton


-17.0GJ/ton





Ammonia: 23.0GJ/ton



Overview Savings



Ethylene 0.231 10.05 86.0% 20.98 -14.59

Phenol 0.008 0.33 2.8% 0.69 -0.48

Styrene 0.008 0.37 3.1% 0.77 -0.53

Toluene 0.007 0.32 2.8% 0.68 -0.47

1,4-butandiamine 0.001 0.05 0.5% 0.11 -0.08

Acrylamide 0.001 0.04 0.3% 0.08 -0.06

Adipic acid 0.000 0.00 0.0% 0.01 -0.01

Ammonia 0.000 0.01 0.1% 0.02 -0.01

ε-caprolactum 0.000 0.01 0.1% 0.02 -0.02

Ethylamine 0.001 0.04 0.3% 0.08 -0.06




γ-butyrolactum 0.000 0.01 0.1% 0.02 -0.02

Ionic liquids 0.000 0.01 0.1% 0.02 -0.01


Isoprene 0.001 0.03 0.2% 0.06 -0.04


Oxalic acid 0.000 0.01 0.1% 0.01 -0.01

Urea 0.000 0.01 0.1% 0.02 -0.01

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.008 0.36 3.1% 0.75 -0.52

Description

- Practically unbeatable; in terms of energy and exergy it performs extraordinarily well.

- It has a very low biomass acquisition energy intensity and simultaneously produces

extraordinarily high yields.

- Ethylene dominates the chemical mix, representing more than 85% and is produced very

efficiently with the residuals contributing to the internal CHP.

- Hardly any ash/fertilizers is produced meaning the difference between energy and exergy is

very large when in combination with an efficient boiler. Improvement Options

- To maintain its top position one must ensure that the produced off-heat and energy

production are utilized locally, which can be an issue in rural Brazil.

- Make only ethylene, nothing else. The amine chemistry and aromatic chemistry are best

directed at contribution to a highly efficient heat and power generation stream.

- It is the best cropping/biorefinery system. (period). Any improvements on yield or

conversion system will only strengthen its position.


Salix Alba – Willow Tree Common Names Willow Tree, White willow, Irish Sailach

Classification Deciduous hardwood tree, C-3

Appearance 20 – 30meters tall, vertical shoots, 5-10cm long, 1-1.5cm wide elongate and serrate leave, green with silky white hairs

Varieties Roughly 350 varieties of willow; for alba the difference is between cultivated and uncultivated, e.g. cricket-bat willow is an English variety (slightly larger) grown as a specialists timber crop

Genetically Modified Varieties None, but several hybrids

Brief Description Native to northern Europe, the willow has been used for timber production for centuries. The fast-growing nature has put it on the top of lingo-cellulosic biomass applications option list.

Growth Details Native Area: Europe and Western Asia Location: Cooler zones of the Northern Hemisphere Climate: Cool - Temperate

Temperature: 10 - 25°C, above 30 is detrimental, tolerates frost Rainfall/Irrigation: 500 – 2000mm, tolerates floods Soil Type: Nearly all types, preferably moist, deep loams Soil Acidity: 5.5 – 8.0pH, can tolerate practically anything, neutrality best Plantation: 18 – 20cm long stems cuttings, near complete cover 2 – 3meter grid spacing (<5 year), 3 – 5meter grid spacing (>15 year) Seeding Rate: Propagation from seedlings is not useful in energy silviculture 500 – 1000 plant/ha for long-term rotation (>15 years) 15000 – 35000 plants/ha for short-term rotation (<5 years) Companion Crop: Legumes highly recommended, grass or mixed with other trees Weed Control: None, except possibility 1st and 2nd year Cultivation: Growth period 25 – 30 years, 1st year whip production to stimulate height growth, also increases yield 10 – 20%, 3 – 4 year harvesting or cutting rotations, can re-sprout from trunk although not implemented Harvesting: Immature retrofitted machines, cuttings or logging with direct chipping, after senescence, later autumn/early winter

Nutrient/Fertilizer Requirement The routing systems are capable of leeching traces of nutrients from deep and sometimes far away water reservoirs, runoffs from other fields and various other sources. This is why deep soils are imperative. The mentioned average yields (next page) are based on no additional nutrient levels. Information regarding nutrient uptake is scarce or unavailable: as being not yet truly considered a crop. However, it is suggested to add sewage sludge to fields as a source of the various nutrients. Results have shown an increase in yields. On unfertile or exhausted lands, a highly concentrated band of fertilizer is suggested (at max 100kg/ha, 3 source average: 85kg/ha) for lifetime source of nitrogen and potassium. Over fertilizing does not affect growth. Assume 7.5kg/tonneWW N, K2O and P2O5, 0.1 for other macronutrients, 0.001 for all micronutrients.


Yield Normal Conditions: 3 – 10 ton/ha (oven dry, upon 3-4th year harvesting 10 – 30ton/ha) 4 – 5 ton/ha (oven dry, Swedish test sites) Optimal Conditions: 8 – 10 ton/ha (oven dry, lower latitudes and with fertilization) Worldwide Cultivation: Wide spread, chiefly wild or planned forest areas, low harvesting


Constituent Trunk Leaves

Moisture Content 60% - Cellulose 49.6 - Hemicellulose 22.9 - Lignin 22.7 - Protein 2.0 - Oils - - Fats - - Minerals 1.3 - Ash 1.5 - Others - -

*Strongly dependent on all growing factors, location and nutrient levels The Leaves are not harnessed but left to provide a nutrient cycle Lower Heat Value: 19200 kJ/kg (whole tree), 18500 (trunk) Higher Heat Value: 19750 kJ/kg (whole tree), 19790 (trunk)

Detailed Information Initial/current practice of harvesting and processing methods is implemented upon leave senescence and thus only trunk and branches are present. The lignocellulosic material is used for processing (should it be for burning or fermentation) the rest, residual constituents are at trace levels and practically unusable and do not need to be mentioned.

Comments Popular is a common willow hybrid derivate used for the same possible application in warmer climates. There is a slight difference, harvesting should be held every 4 – 5 years, it has a lower cellulose concentration and although the yield is comparable due to the warmer climate the actual photosynthetic conversion is marginally reduced. An added environmental advantage: provide a year-round habit for forest wildlife.


Comparative Graph

Energy

Ash: 153GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



Next Generation

0GJ/ton

29.6

60

80

70

- Chemical vs. Biomass Cumulative Process Energy Demand






Biomass

2.98GJ/ton

Willow TreeSweden

20.0ton/ha lumber

8.0tota lDW/ha

24.3

40

50

30



Lignin: 23.0GJ/ton

Protein: 239GJ/ton

20.1


Ammonia: 69.1GJ/tonEthylene: 67.0GJ/ton

Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




15.6GJ/ton biomass

125GJ/ha

24.2GJ/ton

Boi ler: 9.1GJ/ton


Ammonia: 31.0GJ/ton

Phenol: 10.6GJ/ton

Styrene: 83.9GJ/tonAmine Chemicals: 83.2GJ/ton

68.1GJ/ton




Ash: 153GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



Next Generation

0GJ/ton

29.6

60

80

70

- Chemical vs. Biomass Cumulative Process Energy Demand






Biomass

2.98GJ/ton

Willow TreeSweden

20.0ton/ha lumber

8.0tota lDW/ha

24.3

40

50

30



Lignin: 23.0GJ/ton

Protein: 239GJ/ton

20.1


Ammonia: 69.1GJ/tonEthylene: 67.0GJ/ton

Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




15.6GJ/ton biomass

125GJ/ha

24.2GJ/ton

Boi ler: 9.1GJ/ton


Ammonia: 31.0GJ/ton

Phenol: 10.6GJ/ton


68.1GJ/ton




Exergy

Ash: 169GJ/ton

Next Generation

Phenol: 17.5GJ/ton

Styrene: 9.8GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



18.3

60


70






Biomass

3.30GJ/ton

Willow TreeSweden

15.0ton/ha dry hay

15.0tota lDW/ha

23.7

40

50

30



Protein:264GJ/ton

14.7

Ammonia: 51.0GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



17.9GJ/ton biomass

143GJ/ha

68.9GJ/ton

Boi ler: 7.3GJ/ton


Toluene: 16.5GJ/ton

Lignin: 25.5GJ/ton



Ammonia: 23.0GJ/ton

18.4GJ/ton




Ash: 169GJ/ton

Next Generation

Phenol: 17.5GJ/ton

Styrene: 9.8GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



18.3

60


70






Biomass

3.30GJ/ton

Willow TreeSweden

15.0ton/ha dry hay

15.0tota lDW/ha

23.7

40

50

30



Protein:264GJ/ton

14.7

Ammonia: 51.0GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



17.9GJ/ton biomass

143GJ/ha

68.9GJ/ton

Boi ler: 7.3GJ/ton


Toluene: 16.5GJ/ton

Lignin: 25.5GJ/ton



Ammonia: 23.0GJ/ton

18.4GJ/ton





Overview Savings



Ethylene 0.231 10.05 86.0% 20.98 -14.59

Phenol 0.008 0.33 2.8% 0.69 -0.48

Styrene 0.008 0.37 3.1% 0.77 -0.53

Toluene 0.007 0.32 2.8% 0.68 -0.47

1,4-butandiamine 0.001 0.05 0.5% 0.11 -0.08

Acrylamide 0.001 0.04 0.3% 0.08 -0.06

Adipic acid 0.000 0.00 0.0% 0.01 -0.01

Ammonia 0.000 0.01 0.1% 0.02 -0.01

ε-caprolactum 0.000 0.01 0.1% 0.02 -0.02

Ethylamine 0.001 0.04 0.3% 0.08 -0.06




γ-butyrolactum 0.000 0.01 0.1% 0.02 -0.02

Ionic liquids 0.000 0.01 0.1% 0.02 -0.01


Isoprene 0.001 0.03 0.2% 0.06 -0.04


Oxalic acid 0.000 0.01 0.1% 0.01 -0.01

Urea 0.000 0.01 0.1% 0.02 -0.01

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.008 0.36 3.1% 0.75 -0.52

Description

- The overall dry weight yield is merely too low to compensate for the high biomass

acquisition energy intensity making it a poor starting biomass feedstock. Chipping (sizing)

and fertilizer demand round out the major portion.

- It scores mediocre in its conversion to ethylene compared to other carbohydrate (both

simple and complex) rich crops.

- Due to the high lignin content the conversion to the aromatic components is actually

highly efficient and effective being significantly lower than the traditional process routes.

- There is a minor efficiency improvement noticeable due to the thermally reliant processes

(ethylene and aromatics) but is not nearly adequate to be competitive. Improvement Options

- Plant in regions without a large demand on fertilizers and allow growth beyond 3-years to

promote a higher lignin content; best to plant in low-value inland areas.

- Do not convert the proteins but use them to contribute to the boiler output.


Solanum Tuberosum – Potato Common Names Potato, Irish Potato

Classification Perennial, harvested as annual, C-3

Appearance Low-growing herb, 1m, white flowers with yellow stamens, Petiolulate Leaves, 10–30 cm long, 5–15 cm wide, oval-oblong tubers, 10–20 cm long, 5–15 cm wide covered with spots, eyes,

Varieties Thousands: brown, yellow, pink, red, purple, blue, etc

Genetically Modified Varieties Under research, much public pressure

Brief Description The world’s most important non-cereal crop. Grown for the starchy tuber it produces more food energy than any other European crop per hectare.

Growth Details Native Area: Andes, South America Location: Worldwide Climate: Cool – temperate, lots of precipitation

Temperature: 15 – 20°C, can tolerate 3.6 – 27.8°C, year round mean around 12°C Rainfall/Irrigation: 500 – 700mm, around 930mm common, can tolerate up to 4100mm Soil Type: Most soils, for mechanical harvesting light to medium bodied soils Soil Acidity: 5.5 – 7.0, preferred alkaline, below 4.8 impairs growth, mineral soils 6 – 7 pH Plantation: Seeds 4 – 5cm diameter, rows, 40 – 120cm spacing, 10 – 20cm deep holes Seeding Rate: Common varieties are sterile, planted by existing tubers, with 1-2 eyes 1.2 – 1.5 t/ha, as high as 2.5 - 3 t/ha 30000 – 100000 tubers/ha (normal range 30 – 60k tubers/ha, for bulb size) Companion Crop: No, but can be used as a companion crop for other crops Weed Control: Field must be root-weed free, up to 3 ploughings needed Cultivation: Spring to early summer, early maturity 80-100 days, medium maturity 100 – 120days, late maturity over 120 days, up to 3-4 year rotation break Harvesting: Large mechanized farms usually defoliate chemically, autumn months

Nutrient/Fertilizer Requirement Fertilizers are applied before seedbed preparation and ploughed or cultivated into the soil


0

100

200

300

400

500

600

0 20 40 60 80 100 120



N

P2O 5

K2O

CaO

MgO

SO3

Lo g. (N)

Poly . (P2O5 )

Lo g. (K2O )

Poly . (CaO)

Poly . (Mg O)

Poly . (SO3)


0

500

1000

1500

2000

2500

0 20 40 60 80 100 120



Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe )

Poly . (Mn )

Poly . (B)

Poly . (Zn)

Poly . (Mo )

Poly . (Cu)


Yield Normal Conditions: 20 - 40ton/ha (tubers, native areas of Western Europe) 43.5ton/ha (Holland: 5-year average), 65ton/ha tuber (best practice) Optimal Conditions: above 100 ton/ha (experimental findings) Worldwide Cultivation: 19.1 million hectares at 17.1 ton/ha


Constituent Bud/Tuber Leaf/Stem†

Moisture Content 78.0% 60.0% Cellulose 65

Hemicellulose 7.7

Lignin - - Starch 72.5 20 Protein 10.6 10 Oils - - Fats 0.7 - Minerals 0.5 - Ash 5.4 - Others 2.6 5

*Strongly dependent on all growing factors, location and nutrient levels, †Estimate, Tuber represent 60% of total wet weight during growth and upon harvest 89% Lower Heat Value: 19000 kJ/kg (tuber alone) Higher Heat Value: 19500 kJ/kg (tuber, estimate)

Detailed Information Starch (70 – 75DW%): 78% amylopectin 22% amylose Pectin (1.8 – 3.3DW%): 51% Anhydrogalacturonic acid 49% Polysaccharides

- 6% Rhamnose

- 0.6% Fucose - 5.6% Arobinose

- 1.8% Xylose - 86% Galactose

Minerals (0.4 – 0.6DW%): rich in K nearly 95% of minerals, poor in Na less than 1% of minerals Total Amino Acid Tuber

(fraction percent) Alanine 9.6


Methionine 2.3

Phenylalanine 6.6 Proline 4.0

Tryptophan 1.6


Valine 6.1 Asparagine 8.9

Cysteine 2.1

Glutamine 11.0 Glycine 0.2

Serine 2.7

Threonine 5.9

Polar & Hydrophilic

Tyrosine 6.9

Asparagic Acid 4.3 Acidic

Glutamic Acid 4.3


Lysine 7.7

Comments Deficient in sulphur amino acids and probably also histidine. It is relatively rich in lysine


Comparative Graph

Energy


20

10


CRACKER



44.9

60


70




Ammonia: 31.0GJ/ton



Biomass

2.04GJ/ton

PotatoThe Netherlands

65 ton /ha tube r

17.5to ta lDW/ha

42.5

40

50

30

Complex C6

Carbohydrates : 26.7GJ/ton

Complex C5


Lignin: 390GJ/ton

Protein: 24.8GJ/ton

Ash: 55.5GJ/ton

112

Ammonia: 17.1GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




11.4GJ/ton biomass

200GJ/ha

29.5GJ/ton

63.9GJ/ton

Boiler: 5.9GJ/ton

21.1



0GJ/ton







20

10


CRACKER



44.9

60


70




Ammonia: 31.0GJ/ton



Biomass

2.04GJ/ton


65 ton /ha tube r

17.5to ta lDW/ha

42.5

40

50

30

Complex C6

Carbohydrates : 26.7GJ/ton

Complex C5


Lignin: 390GJ/ton

Protein: 24.8GJ/ton

Ash: 55.5GJ/ton

112

Ammonia: 17.1GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




11.4GJ/ton biomass

200GJ/ha

29.5GJ/ton

63.9GJ/ton

Boiler: 5.9GJ/ton

21.1



0GJ/ton






Exergy

Lignin: 421GJ/ton



0GJ/ton

20

10


CRACKER



39.5

60


70




Ammonia: 23.0GJ/ton



Biomass

2.21GJ/ton


65 ton /ha tube r

17.5to ta lDW/ha

37.0

40

50

30

Complex C6


Protein:26.7GJ/ton

Ash: 59.8GJ/ton

147

Ammonia: 10.0GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton




23.1GJ/ton biomass

405GJ/ha

-5.6GJ/ton

64.2GJ/ton


10.1


Complex C5






Lignin: 421GJ/ton



0GJ/ton

20

10


CRACKER



39.5

60


70




Ammonia: 23.0GJ/ton



Biomass

2.21GJ/ton


65 ton /ha tube r

17.5to ta lDW/ha

37.0

40

50

30

Complex C6


Protein:26.7GJ/ton

Ash: 59.8GJ/ton

147

Ammonia: 10.0GJ/ton


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton




23.1GJ/ton biomass

405GJ/ha

-5.6GJ/ton

64.2GJ/ton


10.1


Complex C5







Overview Savings



Ethylene 0.215 3.77 65.0% 19.13 -3.61

Phenol 0.002 0.03 0.5% 0.15 -0.03

Styrene 0.002 0.03 0.6% 0.17 -0.03

Toluene 0.002 0.03 0.5% 0.15 -0.03

1,4-butandiamine 0.011 0.20 3.5% 1.02 -0.19

Acrylamide 0.005 0.08 1.4% 0.41 -0.08

Adipic acid 0.001 0.01 0.2% 0.07 -0.01

Ammonia 0.003 0.06 1.0% 0.28 -0.05

ε-caprolactum 0.005 0.09 1.6% 0.48 -0.09

Ethylamine 0.012 0.22 3.7% 1.10 -0.21




γ-butyrolactum 0.005 0.09 1.5% 0.43 -0.08

Ionic liquids 0.002 0.03 0.5% 0.14 -0.03


Isoprene 0.010 0.18 3.2% 0.93 -0.18


Oxalic acid 0.001 0.03 0.5% 0.13 -0.03

Urea 0.002 0.04 0.6% 0.19 -0.03

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.037 0.65 11.1% 3.28 -0.62

Description

- The yield is high enough in relation to the biomass acquisition energy intensity to bring the

overall cropping system in the middle performance range.

- Although the conversion to ethylene via simple carbohydrates is one of most energy

intensive routes there are many efficiency improvement foreseeable as expensed by the

drastic reduction in exergy demand.

- After the carbohydrate conversion the proteins in the residual stream are easily and

efficiently converted, being one of the least energy intensive options.

- The lignin-based components (aromatics) cost significantly more cumultaive energy and

exergy demand than the standard fossil fuel-based production routes. The chemical

composition of lignin is far too low in potato even when including the tops and skins.

Improvement Options

- Little major improvement options foreseeable; an excellent regional choice.

- Do not include lignin’s processing steps and therby add it as additional fuel to the interal

heat and power combustion unit.

- A high soil content in harvested product (due to tuber) and high nutrient uptake is present

which results in energy intense ash/fertilizer. Sacrife a portion of the yield to remove soil

from skin and lower extreme nutrient uptake demands.


Sorghum Bicolor – Sweet Sorghum Common Names Sorghum, Sweet Sorghum, Durra, Milo, Shattercane

Classification Annual (or semi-perennial) grass, C-4

Appearance 0.6 – 5 meter tall, erect, single stemmed, 5 – 30 mm diameter, panicle 8 – 40cm long, bicolor sorghums are characterized by long, clasping glumes at least ¾ as long as the broadly elliptical grain

Varieties >4000, with sorghum types: broom corn, grain, grass and sweet

Genetically Modified Varieties Several cultivated and hybrid varieties for specific climate conditions. Reduced lignin composition, easier digestibility and harvesting.

Brief Description It is the 5th largest cereal crop in the world; major food source in Africa and India. It was extensively used as a source for sweeteners, however due to heavily labour intensive requirements it has practically been removed from industrialized worlds. Thrives in arid areas where other cereals do not. Stalks considered as a bioenergy option.

Growth Details Native Area: Ethiopia, Eastern Africa Location: Drier regions of the Southern Hemisphere Climate: Hot and arid – semiarid, does not do well in shade

Temperature: 20 – 35°C, 30°C optimal for growth period Rainfall/Irrigation: 400 – 650mm, 200mm min, >750mm not economical. Dormant in drought Soil Type: Wide range, must be deep with good drainage Soil Acidity: 5.0 – 8.5pH, average 6.7pH Plantation: 4 – 5cm deep, seedbeds, 75 – 100cm spacing, depends on rainfall/irrigation levels, developing countries use hand hoe, industrialized maize drills Seeding Rate: 2 – 12 kg/ha (7 – 8 kg/ha normal conditions), 21800 – 61000 seeds/kg 50000 – 100000 plants/ha normal (extremely dry 5000 – 10000 plants/ha) Companion Crop: Generally grown as pure crop; forage use legume (cowpea) is advantageous Weed Control: Spraying of pre-emergence weed killer only at seeding, competes well Cultivation: May – mid-July, after rain period, 50 – 60 days boot stage, 60 – 70 days flowering, more than 120 days for maturity Harvesting: 2 – 5 harvestings per year, first at stem height of 80 – 120cm, 3 – 4 months after sowing, every 1 – 2 months, 10 – 15 cm stubble left over for re-growth

Nutrient/Fertilizer Requirement Deep rooting system can easily leech trace nutrients. Organic fertilizer not recommended.


0

50

100

150

200

250

300

350

0 10 20 30 40 50 60 70 80

Green Biomass Yield (ton/ha)


N

P2O5

K2O

CaO

MgO

SO3

Log. (N )

Po ly. (P2O5)

Log. (K 2O)

Po ly. (CaO)

Po ly. (MgO)

Po ly. (SO3)


0

20

40

60

80

100

120

0 10 20 30 40 50 60 70 80

Green Biomass Yield (ton/ha)

Total Plant U

ptake (g/ha)

Fe

Mn

B

Zn

Mo

Cu

Po ly. (Fe)

Po ly. (Mn)

Po ly. (B)

Po ly. (Zn)

Po ly. (Mo)

Po ly. (Cu)


Yield Poor Conditions: 1 – 6 ton/ha (poor in every aspect, developing African nations) 0.7ton/ha Grain (Kenya: 5-year average = 35ton/ha total green matter) Normal Conditions: 25 – 40 ton/ha (green matter) 30 – 50 ton/ha (good practices, developed nations) Optimal Conditions: 75 ton/ha (green matter, commercial African yields) 100 – 140 ton/ha (EU demonstration sites) Worldwide Cultivation: 44.3 million hectares at 1.3 ton/ha


Constituent Seed/Panicle Stalk Whole Crop† Moisture Content 12.5% 50.0% 75.5%

Cellulose 22.5 Hemicellulose

5.4 13.8

34.6

Lignin - 11.3 8.7 Starch 74.5 - - Sucrose - 39.5 Other Sugars - 4.7

45.2

Protein 8.6 3.3 4.0 Oils - - Fats

3.4 - -

Minerals 0.4 - - Ash 1.7 4.9 2.8 Others 6.0 - 5.0

*Strongly dependent on all growing factors, location and nutrient levels †Based on EU demonstration practices, harvested just before panicle development Distribution of dry weight: - Stalk: 75% (82%) - Leaves: 12.5% (17%)

- Panicle: 7.5% (1%) - Roots: 10%

Higher Heat Value: 18300 kJ/kg (whole plant) Lower Heat Value: 17250 kJ/kg (whole plant)

Detailed Information Hardly any additional information of value is available. However, the proteins contains no Glucan

Comments Sorghum is considered a possible replacement for maize. It is possible to cultivate in drier, less desirable conditions and requires less water/irrigation than all other cereals. Some test sites have presented a higher yield than corn/maize. It has the added advantage of having sucrose, starch and usable bagasse, so can be classified as a grass, cereal and sugar-yielding crop. For these reasons it is among the leader contenders for a biobased economy. Sweet sorghum is similar to normal sorghum but cultivated before the panicle properly develops, sorghum dry weight figures are based on the yield of the panicle.


Comparative Graph

Energy

Protein: 58.9GJ/ton

Ash: 104GJ/ton


0GJ/ton

Next Generation

Toluene: 31.9GJ/ton

Styrene: 33.9GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



27.0

60


70






Biomass 2.05GJ/ton

SorghumKenya

75ton/ha cane

36.9to ta lDW/ha

44.7

40

50

30 Complex C6



Lignin: 47.7GJ/ton

28.3

Ammonia: 33.5GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




12.3GJ/ton biomass

455GJ/ha

27.3GJ/ton

66.4GJ/ton

Boiler: 6.9GJ/ton

13.5



Phenol: 18.6GJ/ton

Ammonia: 31.0GJ/ton


Lignocellulose-to-Bioethanol (Steam)



Protein: 58.9GJ/ton

Ash: 104GJ/ton


0GJ/ton

Next Generation

Toluene: 31.9GJ/ton

Styrene: 33.9GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



27.0

60


70






Biomass 2.05GJ/ton

SorghumKenya

75ton/ha cane

36.9to ta lDW/ha

44.7

40

50

30 Complex C6



Lignin: 47.7GJ/ton

28.3

Ammonia: 33.5GJ/ton


Toluene: 72.7GJ/ton

Phenol: 76.5GJ/ton




12.3GJ/ton biomass

455GJ/ha

27.3GJ/ton

66.4GJ/ton

Boiler: 6.9GJ/ton

13.5



Phenol: 18.6GJ/ton

Ammonia: 31.0GJ/ton





Exergy

Ash: 109GJ/ton

Next Generation

Toluene: 24.3GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



37.4

60

80

70





Biomass 2.16GJ/ton

SorghumKenya

75ton/ha cane

36.9tota lDW/ha

18.9

40

50

30


Complex C5


Lignin: 50.2GJ/ton

Protein:62.0GJ/ton

22.9


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



23.0GJ/ton biomass

851GJ/ha

-5.9GJ/ton

67.1GJ/ton

Boile r: 5.6GJ/ton Simple Carbohydrates: 4.7GJ/ton5.4



Styrene: 26.4GJ/ton

Amine Chemicals: 20.5GJ/tonPhenol: 17.8GJ/ton


Ammonia: 23.0GJ/tonAmmonia: 20.6GJ/ton





Ash: 109GJ/ton

Next Generation

Toluene: 24.3GJ/ton


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



37.4

60

80

70





Biomass 2.16GJ/ton

SorghumKenya

75ton/ha cane

36.9tota lDW/ha

18.9

40

50

30


Complex C5


Lignin: 50.2GJ/ton

Protein:62.0GJ/ton

22.9


Toluene: 73.7GJ/ton

Phenol: 75.8GJ/ton



23.0GJ/ton biomass

851GJ/ha

-5.9GJ/ton

67.1GJ/ton

Boile r: 5.6GJ/ton Simple Carbohydrates: 4.7GJ/ton5.4



Styrene: 26.4GJ/ton

Amine Chemicals: 20.5GJ/tonPhenol: 17.8GJ/ton


Ammonia: 23.0GJ/tonAmmonia: 20.6GJ/ton






Overview Savings



Ethylene 0.221 8.16 69.9% 19.12 -4.14

Phenol 0.014 0.51 4.4% 1.21 -0.26

Styrene 0.015 0.57 4.9% 1.33 -0.29

Toluene 0.014 0.50 4.3% 1.18 -0.26

1,4-butandiamine 0.005 0.20 1.7% 0.46 -0.10

Acrylamide 0.001 0.02 0.2% 0.04 -0.01

Adipic acid 0.000 0.01 0.1% 0.03 -0.01

Ammonia 0.001 0.05 0.4% 0.12 -0.03

ε-caprolactum 0.001 0.05 0.5% 0.13 -0.03

Ethylamine 0.004 0.16 1.4% 0.39 -0.08




γ-butyrolactum 0.003 0.11 0.9% 0.25 -0.05

Ionic liquids 0.001 0.03 0.2% 0.06 -0.01


Isoprene 0.007 0.24 2.1% 0.57 -0.12


Oxalic acid 0.002 0.06 0.5% 0.13 -0.03

Urea 0.001 0.03 0.3% 0.07 -0.02

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.020 0.73 6.3% 1.71 -0.37

Description

- A very successful crop when cultivated as sweet sorghum with extraordinarily high yields.

Cultivation as standard (grain) sorghum would jeopardize benefit.

- Major chemical in the biorefinery mixture is ethylene deriving from the three rich sources

of carbohydrates, nearly 70%.

- Behaves very similar to sugar cane in Brazil and could be dubbed as Africa’s wonder-plant.

The slightly lower yield, however, is replaced by higher amounts of protein which here is

efficiently and effectively converted to amine-based chemicals. Improvement Options

- Best practices conditions must be upheld calling for major improvements on current

systems.

- Must ensure that the produced off-heat and energy production are utilized locally.

- All chemical conversions can be pursued.


Triticum Aestivum – Wheat Common Names Wheat, spring wheat, winter wheat, common wheat, bread wheat Classification Annual grass, autumn or spring sown, C-3 Appearance 0.6 – 1.2 m tall erect and hollow grass, 1.3cm narrow 20-38cm long flat hairy Leaves, thin clumped spikelets, containing the grain

Varieties Countless: classified by growing season and composition.

Genetically Modified Varieties Yes, countless amounts

Brief Description Wheat is the world's most important cereal crop in terms of both area cultivated and amount of grain produced. It is widely grown throughout the world. It is a food staple for flour production, livestock feed and more importantly for the brewing of beer. Residue for fodder or biomass use.

Growth Details Native Area: Middle East, Fertile Crescent Location: Worldwide, mainly in China, Europe and North America Climate: Temperate zones (up to 60 °N), tropical/sub-tropical areas at higher altitudes

Temperature: 4.9 – 27.8°C, growth average 13.4°C Rainfall/Irrigation: 450 – 650mm with 550mm average, toleration between 150 – 2500mm Soil Type: Fertile dark soils rich in nitrogen, prairies with good water retention Soil Acidity: 4.5 – 8.3pH, worldwide mean 6.5pH

Plantation: (Winter wheat) late summer seed propagation, best when 18°C afternoon temp, no-till drilled 2.5 – 5cm deep (moisture dependent) 13 – 20cm spacing Seeding Rate: 90% winter survival rate, limited tilling operations to prevent soil damage, 22 – 100 kg/ha, 33 kg/ha optimum, 5400000 ears/ha at 2.0 – 2.25 ears/plant 2150000 – 2700000 plants/ha Companion Crop: No, but a 3-year rotation cycle, not to be rotated winter-spring wheat Weed Control: Agents added to seeds, rare problems because of minimum tillage operations Pest and Disease: Very susceptible to disease, can suffer from heavy yield losses Cultivation: Attention to soil hardness, balance between root growth and water retention, sprouting in early spring, utilizes the most amount of available solar energy Harvesting: Mid-July, easy, fully mechanized with combiners, drying required for grains above 14% moisture, average is 20%, one year storage

Nutrient/Fertilizer Requirement (Winter wheat) Many added during sowing, however more than 60% used in last shooting phase


0

50

100

150

200

250

300

350

400

450

500

0 2 4 6 8 10 12

Grain Yield (ton/ha)

Total Plant U

ptake (kg/ha)

N

P2O5

K2O

CaO

MgO

SO 3

Po ly. (N)

Po ly. (P2O 5)

Po ly. (K2O )

Po ly. (CaO )

Po ly. (MgO)

Po ly. (SO3)


0

100

200

300

400

500

600

700

0 2 4 6 8 10 12



Fe

Mn

B

Zn

Mo

Cu

Poly . (Fe )

Poly . (Mn )

Poly . (B)

Poly . (Zn)

Poly . (Mo )

Poly . (Cu)


Yield Normal Conditions: 4.7 – 7.0 ton/ha (dry grain), 8.5 – 12.7ton/ha (whole crop wet) 7.0ton/ha (French: 5-year average) Optimal Conditions: 9.0 – 14.8 ton/ha (dry grain), testing average 10.3 ton/ha Correlates to 16.4 – 26.9ton/ha whole crop Worldwide Cultivation: 217 million hectares at 2.86 ton/ha (dry grain)

Chemical Composition* (Based on dry weight and winter wheat)

Constituent Grain Stem/Leaves Moisture Content 20% 8%


22.3 22.6

Lignin 2.4 16.9 Sugars 1.2 - Starch 56.0 - Protein 13.4 - Oils -

Fats 2.5

- Minerals 0.4 - Ash 1.9 10.2 Others - 17.7

Grains represent a little over ½ of the total wet plant mass (55% taken) *Strongly dependent on all growing factors, location and nutrient levels Lower Heat Value: 18600 kJ/kg (straw), 16220 kJ/kg (grain) Higher Heat Value: 19925 kJ/kg (straw), 17529 kJ/kg (grain)

Detailed Information Wheat germ oil is contained at 8 - 12% in the wheat germ, which is 2% of total grain weight. It is known for having a high linoleic fatty acid concentration.

Fatty Acid Carbon Chain Germ Oil (fraction percent)

Palmitic 16:0 11-20 Stearic 18:0 1-6 Oleic 18:1 13-30 Linoleic 18:2 44-65 Alpha Linoleic 18:3 2-13

A large portion of the protein is in the complex water-insoluble form of gluten, around 40% Free Amino Acid Grain

(fraction percent) Isoleucine 6.97

Leucine 8.27 Methionine 1.32

Phenylalanine 3.68

Tryptophan 1.03


Valine 4.0

Polar & Hydrophilic

Threonine 2.78


Lysine 2.80

Total 36.1% of Protein

Comments In the yield figures, water demand and retention is far more influential than nutrient use. (T. aestivum) Hexaploid species, most widely cultivated in the world and highest yielding, common wheat.


Comparative Graph

Energy

Ash:

41.6GJ/ton

Next Generation

Phenol: 15.4GJ/ton

Toluene: 28.8GJ/ton

20

10


CRACKER



34.2

60



70




Biomass

2.04GJ/ton

WheatFrance

10.3ton/ha grain

18.6to ta lDW/ha

25.9

40

50

30



Protein: 21.1GJ/ton

Lignin:

37.8GJ/ton

25.0

Ammonia: 19.0GJ/ton



Phenol: 76.5GJ/ton




18.2GJ/ton biomass

337GJ/ha

65.7GJ/ton

Boiler: 8.6GJ/ton

21.1



0GJ/ton


Styrene: 30.4GJ/to n Ammonia: 31.0GJ/ton



16.6GJ/ton





Ash:

41.6GJ/ton

Next Generation

Phenol: 15.4GJ/ton

Toluene: 28.8GJ/ton

20

10


CRACKER



34.2

60



70




Biomass

2.04GJ/ton

WheatFrance

10.3ton/ha grain

18.6to ta lDW/ha

25.9

40

50

30



Protein: 21.1GJ/ton

Lignin:

37.8GJ/ton

25.0

Ammonia: 19.0GJ/ton



Phenol: 76.5GJ/ton




18.2GJ/ton biomass

337GJ/ha

65.7GJ/ton

Boiler: 8.6GJ/ton

21.1



0GJ/ton


Styrene: 30.4GJ/to n Ammonia: 31.0GJ/ton



16.6GJ/ton





Exergy

Ash: 46.4GJ/ton


Next Generation


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



19.5

60



70






Biomass 2.27GJ/ton

WheatFrance

10.3ton/ha grain

18.6to ta lDW/ha

28.7

40

50

30


Complex C5


Protein: 23.5GJ/ton

Lignin:

42.2GJ/ton

20.3

Ammonia: 13.4GJ/ton



Phenol: 75.8GJ/ton



20.4GJ/ton biomass

378GJ/ha

11.0GJ/ton

66.0GJ/ton

Boi ler: 7.0GJ/ton


13.9


Toluene: 21.8GJ/ton

Styrene: 15.2GJ/ton

Phenol: 23.5GJ/ton Ammonia: 23.0GJ/ton





Ash: 46.4GJ/ton


Next Generation


0GJ/ton

20

10

Crude Oil

44.9GJ/ton

CRACKER



19.5

60



70






Biomass 2.27GJ/ton

WheatFrance

10.3ton/ha grain

18.6to ta lDW/ha

28.7

40

50

30


Complex C5


Protein: 23.5GJ/ton

Lignin:

42.2GJ/ton

20.3

Ammonia: 13.4GJ/ton



Phenol: 75.8GJ/ton



20.4GJ/ton biomass

378GJ/ha

11.0GJ/ton

66.0GJ/ton

Boi ler: 7.0GJ/ton


13.9


Toluene: 21.8GJ/ton

Styrene: 15.2GJ/ton

Phenol: 23.5GJ/ton Ammonia: 23.0GJ/ton






Overview Savings



Ethylene 0.179 3.31 48.2% 8.01 5.30

Phenol 0.017 0.32 4.7% 0.78 0.52

Styrene 0.019 0.36 5.2% 0.87 0.57

Toluene 0.017 0.32 4.6% 0.77 0.51

1,4-butandiamine 0.018 0.33 4.9% 0.81 0.54

Acrylamide 0.002 0.03 0.4% 0.07 0.05

Adipic acid 0.001 0.02 0.2% 0.04 0.02

Ammonia 0.004 0.07 0.9% 0.16 0.10

ε-caprolactum 0.002 0.04 0.5% 0.09 0.06

Ethylamine 0.006 0.11 1.7% 0.28 0.18




γ-butyrolactum 0.011 0.20 2.9% 0.47 0.31

Ionic liquids 0.002 0.04 0.6% 0.09 0.06


Isoprene 0.015 0.28 4.1% 0.68 0.45


Oxalic acid 0.004 0.07 1.1% 0.18 0.12

Urea 0.002 0.03 0.5% 0.08 0.06

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.049 0.91 13.2% 2.20 1.45

Description

- A remarkably high yielding crop of simple carbohydrates for a temperature crop at low

biomass acquisition energy intensity.



- The lignin conversion to aromatics is particularly effective and efficient.

- As with other grasses the ash/fertilizer in considerable and decreases the overall savings.

Whereas in this case it is not from soil contamination, but from a high nutrient demand.

Improvement Options

- The biomass feedstock energy demand is mainly attributed to fertilizer demand meaning

few improvements are foreseeable; perhaps general yield increases.

- For this cropping/biorefinery system layout, it may be best to focus on protein conversion

to amine-based chemicals and therefore decrease a portion of the carbohydrate

processing to the less intense options and allocate a larger part of the crop to the boiler.


Zea mays L – Maize Common Names EU: Maize, USA: Corn, Mealie, Indian Corn

Classification Annual grass, C-4

Appearance 2.5m tall, cane-like stem, joints every 30-45cm, 30-90cm long, thin drooping green Leaves, ears under Leaves covered in sedgy leave coverings, 15-25cm long, 4-8cm thick, 200-400 kernels/ear

Varieties 6 major types: Flour (soft), Popcorn, Dent, Flint, Pod, Sweetcorn

Genetically Modified Varieties Practically all, common type BtCorn (against Bt toxin)

Brief Description The term corn broadly applies to any staple food grain and was originally the term for any crop kernel. It is primary used for livestock fodder and with an increasingly large portion for ethanol production. Human consumption is almost negligible.

Growth Details Native Area: Mexican peninsula, domesticated from the teosinte Zea mays ssp. parviglumis Location: Worldwide; USA roughly half of harvest Climate: Subtropical – temperate, frost will destroy crop

Temperature: 21 - 28°C, warm weather crop Rainfall/Irrigation: 500 – 800mm (average 750mm), can tolerate up to 2590mm – 4100mm Soil Type: Large variety. Prefers deep, naturally rich and easily tilled Soil Acidity: 4.3 – 8.7pH, average is slightly acidic Plantation: Only seed propagation, 2.5 – 5cm deep, 3-4 seeds per hill machine drilled, Spacing 0.8x0.8m – 1.0x1.0m on checker formed rows Seeding Rate: 11.5 – 16kg/ha for plant density of 40,000 – 50,000 plants/ha Companion Crop: Dual legume crop (i.e. soybeans) rotation and sometime also 3rd winter wheat Mixing different variations, i.e. early, medium and late growth Weed Control: None needed, systematic cultivation and rotation enough Cultivation: Ploughed before plantation, planted 2 weeks after last winter frost, early spring, sometimes planted in autumn – early winter and left over the winter Harvesting: Food consumption usually handpicked, other completely mechanized sorting husk and ear from stover. Around late-autumn, 80-120 days for maturity and ears 50-75days after ear development

Nutrient/Fertilizer Requirement Yields strongly react with organic nutrient sources, companion legumes usually enough


0

50

100

150

200

250

300

350

400

450

0 2 4 6 8 10 12 14 16



N

P2O5

K2O

CaO

MgO

SO 3

Po ly. (N)

Po ly. (P2O 5)

Po ly. (K2O )

Po ly. (CaO )

Po ly. (MgO)

Po ly. (SO3)


0

500

1000

1500

2000

2500

0 2 4 6 8 10 12 14 16

Grain Y ield (ton/ha)


Fe

Mn

B

Zn

Mo

Cu

Po ly. (Fe)

Po ly. (Mn)

Po ly. (B)

Po ly. (Zn )

Po ly. (Mo)

Po ly. (Cu)


Yield Normal Conditions: 3.5 – 11 ton/ha (ear/grain), 9.0 ton/ha (USA: 5-year average) 10 – 50 ton/ha (whole crop), 32.5 ton/ha USA average Optimal Conditions: 13.8 ton/ha (grain, best practice) 12 – 20 ton/ha (ear, experimental hybrids of grain maize) Worldwide Cultivation: 145 million hectares at 4.8 ton/ha


Constituent Ear/Cob Stover Moisture Content 20.6%† 75%


9.5 24.1

Lignin - 17.5 Sugars 2.6 - Starch 71.7 - Protein 9.5 11.2 Oils -

Fats 4.3

- Minerals 1.6 1.8 Ash 1.4 6.1 Others - 2.0

Grain (ears/cob) represents about 1/5 of the total wet plant mass *Strongly dependent on all growing factors, location and nutrient levels †20.6% is mature seedling (upon harvesting), green seeds are 62.5% Lower Heat Value: 17000 kJ/kg (corncob), 16850 kJ/kg (stover) Higher Heat Value: 18790 kJ/kg (corncob), 18100 kJ/kg (stover)

Detailed Information There are a number of genetically modified specialty corn varieties that offer several characteristics and produce value-added properties to the grain:

- Waxy corn: high amylopectin starch content (90-100% of starches) - High Amylose corn: high amylose starch content (50-94% of starches)

- High lysine corn: increased levels glutelin, i.e. lysine and tryptophan (0.26 - 0.30 up to 0.34 - 0.37%)

- High oil corn: increase oil content to 7-8% DW and increase protein quantity and quality The globular protein amino acid, Glycine, account for 80 – 90% of the protein. The other amino acids are at such low levels it is not worth mentioning.

Comments Corn supplies 75% of the starch industry and not the potato as could be assumed. Additionally the altitude is greatly confining on the yield, it fairs poorly about 150m. Flat, low lands are ideal. Due to the small root systems the crop requires large amounts of nutrients in the beginning phases of growth. Generally speaking the entire crop does need a lot of nutrients and quite a bit more than the actual uptake. Investigation work is underway in trying to introduce specially designed enzyme to couple with corn, i.e. like a forced legume feature. So far experiments can achieve 70% of nitrogen requirements.


Comparative Graph

Energy

Next Generation

Phenol: 16.3GJ/to n

Toluene: 29.7GJ/ton

20

10


CRACKER



35.9

60



70




Biomass

2.26GJ/ton

MaizeIowa

13.8ton/ha grain

24.8tota lDW/ha

27.0

40

50

30



Protein: 35.0GJ/ton

Lignin:

40.7GJ/ton

26.0Ammonia: 23.3GJ/to n



Phenol: 76.5GJ/to n

Fertilizers: 3.0J/ton



15.4GJ/ton biomass

382GJ/ha

65.3GJ/ton

Boi ler: 9.4GJ/ton

21.9



0GJ/ton


Styrene: 31.4GJ/to n Ammonia: 31.0GJ/to n


Am in e Ch emicals: 19.1GJ/to n

Ash: 63.5GJ/ton





19.9GJ/ton

Next Generation

Phenol: 16.3GJ/to n

Toluene: 29.7GJ/ton

20

10


CRACKER



35.9

60



70




Biomass

2.26GJ/ton

MaizeIowa

13.8ton/ha grain

24.8tota lDW/ha

27.0

40

50

30



Protein: 35.0GJ/ton

Lignin:

40.7GJ/ton

26.0Ammonia: 23.3GJ/to n



Phenol: 76.5GJ/to n

Fertilizers: 3.0J/ton



15.4GJ/ton biomass

382GJ/ha

65.3GJ/ton

Boi ler: 9.4GJ/ton

21.9



0GJ/ton


Styrene: 31.4GJ/to n Ammonia: 31.0GJ/to n


Am in e Ch emicals: 19.1GJ/to n

Ash: 63.5GJ/ton





19.9GJ/ton

Exergy

Ash: 69.0GJ/ton


Next Generation


0GJ/ton

20

10


CRACKER



20.5

60



70






Biomass

2.46GJ/ton

MaizeIowa

13.8ton/ha grain

24.8to ta lDW/ha

30.0

40

50

30


Complex C5


Protein: 37.9GJ/ton

Lignin:

44.2GJ/ton

20.9

Ammonia: 15.9GJ/ton



Phenol: 75.8GJ/ton



17.9GJ/ton biomass

444GJ/ha

65.7GJ/ton


13.7


Toluene: 22.4GJ/ton

Styrene: 15.9GJ/ton

Phenol: 24.2GJ/tonAmmonia: 23.0GJ/ton





13.1GJ/ton

Ash: 69.0GJ/ton


Next Generation


0GJ/ton

20

10


CRACKER



20.5

60



70






Biomass

2.46GJ/ton

MaizeIowa

13.8ton/ha grain

24.8to ta lDW/ha

30.0

40

50

30


Complex C5


Protein: 37.9GJ/ton

Lignin:

44.2GJ/ton

20.9

Ammonia: 15.9GJ/ton



Phenol: 75.8GJ/ton



17.9GJ/ton biomass

444GJ/ha

65.7GJ/ton


13.7


Toluene: 22.4GJ/ton

Styrene: 15.9GJ/ton

Phenol: 24.2GJ/tonAmmonia: 23.0GJ/ton





13.1GJ/ton


Overview Savings



Ethylene 0.190 4.70 55.8% 11.11 7.29

Phenol 0.018 0.45 5.3% 1.06 0.69

Styrene 0.020 0.49 5.9% 1.17 0.77

Toluene 0.018 0.44 5.2% 1.03 0.68

1,4-butandiamine 0.009 0.22 2.6% 0.52 0.34

Acrylamide 0.002 0.05 0.6% 0.12 0.08

Adipic acid 0.000 0.00 0.1% 0.01 0.01

Ammonia 0.002 0.06 0.7% 0.14 0.10

ε-caprolactum 0.003 0.07 0.8% 0.15 0.10

Ethylamine 0.007 0.18 2.2% 0.44 0.29




γ-butyrolactum 0.006 0.14 1.6% 0.32 0.21

Ionic liquids 0.001 0.03 0.4% 0.08 0.05


Isoprene 0.012 0.30 3.6% 0.72 0.47


Oxalic acid 0.003 0.08 0.9% 0.18 0.12

Urea 0.001 0.03 0.4% 0.08 0.05

Biolubricants 0.000 0.00 0.0% 0.00 0.00

Fertilizers 0.036 0.88 10.5% 2.08 1.37

Description

- A remarkably high yielding crop of simple carbohydrates for a temperature crop at low

biomass acquisition energy intensity. Actually slightly better than wheat, but not in this

layout due to the logistics penalty of the location, meaning for Europe (i.e. France) corn

would most likely outperform wheat.



- The lignin conversion to aromatics is particularly effective and efficient.

- As with other grasses the ash/fertilizer in considerable and decreases the overall savings.

Whereas in this case it is not from soil contamination but from a high nutrient demand. Improvement Options

- No major improvement options foreseeable: will remain a middle-range cropping system.



4 Optimal Biorefinery Concept

4.1 Overall Results

Table 1 presents the resulting fossil fuels saving (energetically and exergetically) for the select

crops within the calculation matrix:

Table 1 Resulting Overall Fossil Fuels Savings

Location Fossil Fuel Savings (energy) Fossil Fuel Savings (exergy)

Crop Region /chemical /biomass /ha /chemical /biomass /ha

Cassava Nigeria 37.1 12.5 438 69.1 23.3 817

Grass Holland 50.8 17.6 249 55.6 19.3 272

Lucerne South Dakota 29.2 12.4 186 30.7 13.0 195

Maize Iowa 45.4 15.4 382 52.6 17.9 444

Oil palm Malaysia 37.0 20.9 721 42.6 24.0 830

Potato Holland 34.5 11.4 200 69.8 23.1 405

Rapeseed Belgium 41.9 21.5 353 44.8 22.9 377

Sorghum Kenya 39.0 12.3 455 73.0 23.0 851

Soya bean Illinois 40.3 18.1 196 42.5 19.1 206

Sugar beet Germany 32.3 10.0 292 67.6 20.9 610

Sugar cane Brazil 42.0 11.3 490 84.3 22.6 985

Sunflower France 22.2 15.3 128 22.5 15.5 130

Switchgrass Iowa 38.5 14.8 208 43.7 16.9 236 Tobacco Australia 35.5 13.1 346 59.6 21.9 582

Wheat France 49.6 18.5 343 55.5 20.7 383

Willow tree Sweden 44.0 15.6 125 50.5 17.9 143 - /chemical: GJ per ton biorefinery chemical mixture - /biomass: GJ per ton total dry weight harvested biomass processes - /ha: GJ per arable cultivated land in hectare

4.2 Overall Comparison

4.2.1 Energy

The most important impact assessment terms: savings per produced chemicals (production

efficiency) and savings per arable land area (land use efficiency), provide the information

necessary to determine the optimal biorefinery cropping system. Their combined results, based

on energy savings, are nominalised and expressed in a single chart, Figure 1. The biorefinery

cropping system option closest to the upper right-hand (green) corner has the “best” overall

performance, whereas the option closet to the lower left-hand (red) corner has the “worst”

overall performance. The blue centre diagonal line separates the (nominally) “good” and “bad”

cropping systems. Grass with the highest per chemical mixture savings is located at the top of the

graph but towards the left due to its lower land use efficiency. Oil palm with the best per land

savings is located at the right of the graph but towards the centre due to its lower chemical

production efficiency. Nevertheless, Malaysian oil palm land use efficiency is so high that it still

scores as the optimal biorefinery cropping system overall from those assessed. Generally those

cropping system located in the “good” area can be regarded as optimal considering their diverse

regions, biomass type and chemicals produced.


Figure 1 Graphical Determination of Optimal Biorefinery Cropping System

Malaysian palm oil and the Dutch ryegrass are two significantly different crops; tropical vs.

temperate, oil-rich vs. protein-rich, half-product processing vs. fresh/direct processing, etc. Of

the selected biorefinery cropping systems, grass has the best energy savings in chemicals terms

(GJ/tonchemical) while oil palm is best in land savings (GJ/ha). They perfectly illustrate the contrast

between generally high yielding crops and those lower yielding crops while still well suited for

chemical biorefineries. It is not surprising that oil palm with its 25.0 tonfruits/ha yield can achieve

the highest savings per arable land. Surprisingly however, grass, at only 40% the total biomass

yield (14.1 tonhay/ha), achieves 1.4-fold more energy savings per chemicals produced than oil

palm (50.8 vs. 37.0GJ/ton). Thus, the overall performance is a combination of yield, biochemical

composition and concentration for downstream processing.


4.2.2 Exergy

A distinctly different pattern emerges with the plotted exergy values (Figure 2). The previous

energy-based savings graph depicts the current situation, i.e. what use is made of the resources.

The exergy based figures depicts the thermodynamic situation, i.e. what use could be made of the

resources. Indicating a possible technologies and integration options for a more efficient use of

the current resources (material and energy) following the outlined biorefinery processes. The

latter graph is therefore a projection of the potential; the former of the current state-of-the-art.

This explains why the exergy-based savings (Table 1) are always noticeably higher than the

energy-based savings.

Figure 2 Graphical Determination of Optimal Biorefinery Cropping System (Exergy)


4.2.3 Combined Performance

The top 5 performing biorefinery cropping systems are listed in Table 2 for both energy and

exergy savings. Exergetically, many other crops outperform palm oil: (German grown) sugar beet,

(Nigerian grown) cassava, (Kenyan grown) sorghum, with (Brazilian grown) sugar cane as the

most optimal in respects to production and land use efficiencies. The influence of the recycled

nutrients (ash) stream become more apparent in exergy terms because the cumulative exergy

demand of the fertilizer chemicals are a function of the acquisition biomass exergy which is

systematically higher than the energy intensity. Furthermore, oil-based crops loss their overall

position as biolubricant (biodiesel) processing is mature with only minor foreseeable work

efficiency improvements on current technologies; completely new processes and technologies are

required to improve their overall performance. Oil palm remains, nonetheless, a major contender

due to it high yields.

Table 2 Top 5 Cropping and Biorefinery System of Energy and Exergy Fossil Fuel Savings

Top 5 Crop/Biorefinery Nominal Energy Savings Nominal Exergy Savings

1 Oil Palm, MY Sugar Cane, BR 2 Sugar Cane, BR Sorghum, KE 3 Wheat, FR Cassava, NG 4 Maize, US Sugar Beet, DE 5 Grass, NL Oil Palm, MY

4.3 Discussion

In exergy terms the top 4 crops are carbohydrate-based cropping systems producing vast

amounts of ethylene. Should ethanol and not ethylene was produced, practically all the oily and

protein-based crops would outperform. The savings potential from ethylene is very high with the

production costs to break even with savings from ethanol at 47.9GJ/ton ethylene. None of the

crops has such a high production cost for ethylene, which really stresses to benefit.

In both the energy and exergy optimal biorefinery cropping system graphs the French oil-based

crop, sunflower, is consistently indicated as the “worst” performer. The low yield and high

biomass acquisition energy intensity drives the performance of sunflower to be “less good”. In

tune with biofuels as comparison it still, nonetheless has a replacement potential of

21.9GJenergy/tonproduct and 126GJenergy/ha. This is comparable to, if not slightly better than the

current average 1st generation bioethanol production in Brazil, which mitigates 23.5GJ/ton and

104GJ/ha following the same methodology. As a result even the so-called “worst” biorefinery

cropping system aimed at producing chemicals can be competitive with the “best” system aimed

at producing biofuels.

As a rule of thumb to improve the biorefinery cropping system even further higher the dry

weight yields are desirable, especially with regards to land use efficiency component. Dutch

potato and French wheat are both comparably mid-range yielding crops but are cultivated with a

fairly low agricultural intensity in relation to their total dry weight yield. Wheat therefore

performs high in the energy savings per chemical mixture and overall as did the potato, albeit on

the exergy side. Therefore, even as these are temperate crops, they can approach the overall

savings values of their higher yielding tropical counterparts. There are other some desirable


properties that can steer a cropping system to better performance: like the high yields with an

offset agricultural energy intensity, but also irrigation that is not based on the use of aquifers (as

is the case for lucerne-US), low lignin and high protein content (i.e. frequent harvesting & best

bioprocessing), low harvestable moisture content, cultivation of a crop with minor nutrient

uptake in proportion to total dry weight yield, a convenient location close to a port or waterway,

and so on.

Genetic modification (GM) of crops might assist in increasing the fossil fuel replacement

potential. It could provide incremental yield gains promoting a greater land use efficiency

increase or it could also regulate the biochemical composition promoting a greater production

efficiency increase. GM technology might ultimately drive the cropping systems further into the

upper-right hand corner (green) of the optimal biorefinery cropping system graphs to become

“better”. The crops deemed suitable for genetic modification are those already partially modified

(e.g. soya bean and maize) will naturally have the quickest market entry. More research time is

necessary for the other crops. Conversely, modification is often associated with a sacrifice of

yield or a decrease of many biochemical constituents for the gain of one. The overall balance

could also shift in the wrong direction, consequently it remains to be seen whether these new

GM-crops do indeed contribute positively. In many respects traditional crop breeding systems

along with an altered approach to cultivation and harvesting techniques may have a quicker and

largest beneficial effect in increasing a cropping systems performance. As mentioned in the crop

guide and results, many cropping systems could improve by a simple location change.

One of the bottom-line goals was to determine a singular optimal biorefinery cropping system. If

at this stage a choice must be drawn, it is for the Brazilian sugar cane. Its strength lies solely in

the manufacturing of ethylene and as described the crop guide its only future chemical is

ethylene. That system does not make good use of the functionality of the biochemicals and is

only capable of replacing a single bulk chemical. This approach may face difficulties and hurdles

for market entrance without the help of a full palate of other chemical products. In this sense,

there is no single optimal cropping system currently foreseeable.

Furthermore, biomass is typically harvested at specific time intervals with an irregular production

over the year. Meanwhile it is imperative for the successful forward integration of the large-scale

centralized biorefinery to operate like any other production plant within the petrochemical

cluster. Therefore, it must be able to process biomass constantly throughout the year. Here sugar

cane and other high ethylene dominated cropping systems would not make a contribution, for

example, being dedicated to local production. An overall biorefinery cropping system

combination is consequently only optimal when it has the flexibility to process a variety of

feedstocks (half-products). In this sense, local crops from the hinterland and other temperate

crops can make a contribution, especially during periods of unexpected delays or production

losses of the more favourable variants. Feedstock freedom for continuous operation is imperative

for the success of a chemical biorefinery.



5 Conclusion Technology is constantly driven to increase efficiency and generate profit in what is coined as

value creation. The first industrial uses of coal (and similar bituminous rocks) were used to

primarily produce steam for motion generation. Its chemical calorific value was converted to

mechanical energy. Later during the industrial revolution coal was being used in the coking

process to produce steel. It become a feedstock for a high value added product. When crude oil

began to flood to market its prime market was to produce kerosene again for motion generation.

Its chemical calorific value was converted to mechanical energy. Later as the industry developed

the field of petro-chemistry saw the emergence of an industry produce a wide range of chemical

products. It become a feedstock for high value added products. The first uses of biomass spread

through the ages of human civilization, it was primarily used to create heat. Its chemical calorific

value was converted to thermal and later mechanical energy for electric generation. Biomass is an

alternative to fossil fuels (like coal and oil), why not already focus higher value added products.

This report merely tried to foresee the eventual change to feedstock applications and provide the

grounds to avoid investing in intermediate technologies.

Currently however, there is no single biomass cropping system nor biorefinery that can be

considered as optimum or the best. They all contribute to fossil fuel energy savings and have up

to several magnitudes saving potential than standard application such as bioenergy or biofuel

conversion, based on calorific values. Employing a biomass crop in a particular region has many

aspects to consider, but the main consideration of this report has been attempted at illustrating

that nothing is simple and that chemicals should present a more attractive conversion option for

biomass than energy or fuels.

Regardless, all biomass and conceptual biorefineries layouts are not equal. In certain situations

conventional applications may outperform the chemical biorefinery concept. The trend

differences between energetic and exergetic results for the chemical biorefinery cropping system

in addition to considerations for a continuous feedstock supply reveal that there is not a single

optimum but a combination. Even with a combination these crop-biorefinery systems should be

able to outperform the conventional applications of biomass concluding that dedicated chemical

biorefineries represent a developmental leap towards achieving maximum fossil fuel replacement.

5.1 Ben’s Tips

Firstly, invest in Brazilian sugar cane while promoting the (bio)ethylene market to maturity.

Secondly, invest in Malaysia palm oil. Potentially sell the oil for biodiesel or cosmetics, but focus

on R&D on upgrading press cakes. Once protein extraction possibilities have been worked out

and some amine-based chemicals can be produced efficiently and cheaply invest in regional

ryegrass cultivations. Thirdly, mix feedstocks by expanding to sweet sorghum in stable regions of

sub-Saharan Africa. Adding additional ethylene and half-product imports. Sugar cane production

should provide a structure for success.

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