Perennial energy crops for semiarid lands in the Mediterranean: Elytrigia elongata, a C3 grass with summer dormancy to produce electricity in constraint

environments

Emiliano Maletta*1, Carlos Martin-Sastre

2, Pilar Ciria

1, Aranzazu del Val

1, Annabel Salvado4,

Laura Rovira4, Rebeca Díez3, Joan Serra4, Yolanda González-Arechavala2 and Juan Carrasco

1

1 CEDER-CIEMAT. Energy Department. Biomass Unit. Autovía de Navarra A-15, salida 56. 42290 Lubia

(Soria). Phone: +34 975281013 2 Institute for Research in Technology (IIT) - ICAI School of Engineering - Comillas Pontifical University - E-

28015, Madrid (SPAIN) 3 ITACyL. Biofuels and Bioproducts Resarch Centre, Pol. Agroindustrial Par.2-6 (24358), Leon, Spain. Phone/fax:

+34-987374554 4 IRTA, Mas Badia (17134) Girona, Spain. Phone: +34- 972780275, Fax: +34-972780517

* Corresponding author: emiliano.maletta@ciemat.es

The aim of this report is to demonstrate and evaluate the potential of tall wheatgrass (Elytrigia elongata) to avoid

GHG emissions and obtain lower economic costs in marginal areas of Spain. Our research built scenarios based on

experimental plots (2 and 3 years growth) in 3 locations of Spain with completely different climate conditions

(provinces of Girona, Soria and Palencia). In our experiences, we achieved an adequate establishment and biomass

production, and assumed a rank of biomass yields until the end of the life cycle that is usually accepted to be about

15 years in many other studies in United States, Argentina and Eastern Europe where tall wheatgrass is extensively

cultivated in marginal areas for sheep livestock production. Using our experimental plots and statistical information

for economic inputs costs, we built 5 different scenarios per region considering a large range of biomass yields of tall

wheatgrass. The analysis included a comparison with annual grasses economic costs calculated for a wide range of

biomass yields of a previous study. We estimated GHG emissions savings for tall wheatgrasses and used our previous

study (which had GHG emissions savings as well). Savings were calculated replacing natural gas electricity with

electricity from biomass combustion in real power plants in Spain. In a wide range of yields, the results suggest that

marginal areas might present a better performance with tall wheatgrass compared to annual winter grasses (cereals

whole plant cuttings), thus producing biomass yields with higher GHG savings and lower economic costs at the farm

level.

1 INTRODUCTION

In Spain, a country with more than 4M ha with potential

for energy crops as a consequence of liberalization and

Common Agricultural Policy reforms [1], the

development of energy crops to produce biomass for

heating or electric applications represents a major

challenge. The extensive semiarid rainfed areas of the

Mediterranean require species that tolerate severe

frequent droughts during late spring and summer and

produce sufficiently high yields to obtain biomass with

low costs and high environmental benefits in relation

with the used inputs and fossil energy.

Economic constraints affecting renewable energies

are usually cited as important barriers when developing

new activities in rural areas. Moreover, biomass

production marginal costs in Spain are still a major

constraint limiting the expansion of new facilities at the

time that recent measures have cut subsidies and financial

aid for private companies [2].

During the last decade, in Spain some new power

energy plants started to produce electricity from solid

agricultural residues [3]. Biomass bales from herbaceous

crops are currently used for co-firing to produce

electricity in power energy plants. The first raw materials

considered were agricultural residues (mostly cereal straw

in square bales with less than 11% humidity) and biomass

from energy crops were then also included. Winter

annual crops like triticale (triticosecale sp.), oats (Avena

sativa), peas (Pisum sativum) and rye (Secale cereale)

but also warm annual grasses like fodder maize (Zea

maize) and fibre sorghum (sorghum bicolor), are now

typical solid biofuels involved in private contracts

between farmers and energy companies. These contracts

often establish biomass prices as high as 85€/odt for

square bales from these annual crops [4]. Therefore many

stakeholders are developing a strong interest in new

perennial energy crops that could produce lower biomass

costs in both irrigated and rain fed areas. Biomass yields

per hectare are closely linked to biomass costs since

many areas have low yields as most Mediterranean

extensive rain fed areas have low competitive lands

(unfertile soils, scares rains in spring and summer, etc.).

This consideration would be fundamental in order to

allow the economic feasibility of biomass power energy

plants in Spain.

Despite of economic considerations, energy crops

producing liquid or solid biofuels require to produce

environmental benefits regarding global warming

potentials (GWP) and greenhouse gases emissions (GHG)

among many other impact categories often studied in Life

cycle assessments (LCA) of energy crops and bioenergy

chains [5, 6]. Several studies have encouraged the

research and development of perennial species as energy

crops for marginal areas in order to produce biomass

yields with high energy balances and low environmental

impact regarding water, nitrogen use, erosion,

biodiversity and GHG emissions [7, 8].

In 2009, the Renewable Energy Directive (RED)

established increasingly restrictive minimum GHG

emissions savings for biofuels replacing fossil reference

fuels for transport. This minimums savings are 35%

(from 2009) and will become in 50% in 2017 and 60%

from 1stJanurary of 2018 [9]. Since then, several studies

have provided evidences that marginal areas might

produce also marginal biomass yields or have logistics

implications producing low or none environmental

benefits from feedstock, residues and energy crops [5, 8,

10]. The RED also established a methodological

approach for LCA for biofuels, nevertheless solid

biomass standards and a sustainability criteria for them

have not been addressed sufficiently at the time that many

debates, recommendations on methods and discussions

on land use changes effects on GHG calculations are

currently taking place [11]. Recent significant

advancements have added new principles such as those

from the Roundtable on Sustainable Biofuels (RSB) for

certification schemes. The RSB included a new

certification scheme for most biomass and biofuel

feedstock and established a calculation method for GHG

emissions from agriculture considering CO2, NOx, N2O,

nitrates and Ammonia derived from fertilizers

production, application and dynamics in the soil [12].

In Spain electricity from lignocellulosic energy crops

may replace electricity from natural gas, the cleanest

substituted fossil source as suggested by RSB and RED.

In Spain only few publications on LCA have addressed

lignocellulosic energy crops [13, 14] and there is a lack

of information on C3 or C4 perennial grasses scenarios

producing energy. In a previous study [13], we analysed

GHG emissions from triticale, oats and rye cultivated in

continental rain fed areas in Spain in a wide range of

biomass yields from different species and varieties. Our

results suggested that cereal bales (grain+straw) have to

outreach a yield of about 8 odt/ha in order to accomplish

similar sustainability criteria established for liquid

biofuels in the RED (from 2018, 60% of GHG savings

compared to the fossil substituted reference). Therefore,

those results suggested to condition sustainability of

biomass in most agricultural arable lands in Spain that

have semiarid climate conditions and produce an average

national grain yield of 1,8 t/ha; whole plant biomass

yields of 4 odt/ha considering local harvest indexes

reported from experimental networks [15].

Additionally, many reports strongly suggest that

Common Agricultural Reforms (CAP) for 2014 health

check, should encourage perennial grasses and renewable

energy alternatives at the time cereals and dairy milk

quota would have shorten subsidies for farmers [16].

Spain as one of the member countries with more

abandoned and low competitive cereal lands of Europe

might require new alternative crops to be cultivated under

rain fed conditions and produce biomass. There is a

current need for additional plots and LCA with perennial

species suited for marginal lands or in those areas where

traditional agriculture and livestock production have low

and very low competitiveness [17].

Among several alternative crops, many perennial

grasses have been studied as energy crops and may

produce high environmental benefits and low biomass

costs at the farm level that are relevant for their

consideration on bioenergy chains [4, 5, 6, 7].

Nevertheless, early autumn and spring rains in the

Mediterranean regions are very scarce and in most

regions they limit the adequate establishment and annual

productivity of best suited energy crops like Panicum

virgatum, Arundo donax or Miscanthus giganteum. As

many other C4 grasses (four carbon photosynthetic

metabolism pathway, usually known as “warm grasses”)

these crops have yields reported to be higher than 20

odt/ha per year during their lifetime [4, ]. Nevertheless

most of them require irrigation for rhizome propagation

or event direct sowings in most agricultural lands at least

during the establishment (spring) when drought events

are very frequent in Spain limiting their viability to the

irrigation arable surface. Additionally, even when they

produce much more biomass yields, in some cases have a

higher establishment cost reported to be as high as

2000€/ha in Miscanthus [19, 20].

Perennial C3 grasses (three-carbon photosynthetic

metabolism pathway) also called “cool grasses” can be

established without irrigation during autumn or early

spring and may produce forage in successive years with

harvests during late summer when less precipitation

occur in the Mediterranean. Forage traditional crops like

reed canary grass (Phalaris sp), tall fescue (Festuca

arundinacea) or perennial ryegrass (Lolium perenne)

have been extensively used in Europe for livestock

production and also as new energy crops [21].

Nevertheless, in Mediterranean and semiarid areas most

species produce too low yields or do not re-grow after the

extreme summer drought events. Other best suited C3

energy grass is giant reed (Arundo donax) with very high

yields but require rhizomes or shoots for propagation and

even irrigation or some rains during establishment [20].

Then most of these grasses are best suited for sub-humid

areas in northern regions of Spain, not allowing most rain

fed low competitive cereal regions to produce biomass

from perennial species.

Elytrigia elongata (Host) which common name is

“Tall wheatgrass”, is also known as Thinopyrum

ponticum (Podp), Agropyron elongatum (Host); Elymus

elongatus (Host) var.ponticum. It is a summer dormant

cool season perennial grass native from Eurasia and has

been cultivated in constraints environments all over the

world [22]. Among many other similar wheatgrasses such

as Elymus lancelolatus, Pascopyron smithii, Agropyron

cristatum, A. intermedium and A. sibericum, tall

wheatgrass is probably the latest-maturing wheatgrass

adapted to the temperate areas of North America and

Europe and probably the most productive of all [22]. The

species is adapted to range sites receiving at least 300mm

of annual precipitation and is particularly noted for its

capacity to produce forage and persist in areas that are

too alkaline or saline for other productive crops [22, 23].

Thus, it is a good source of pasture and hay during the

late summer, when forage often is in short supply. It also

has been used successfully as a silage crop. Tall

wheatgrass has large seed that is easy to harvest and

plant. It has good seedling vigour, and established plants

have an exceptionally deep root system, which

contributes to its resistance to drought [23]. Its

palatability for livestock is low at the same time that it

could have acceptable characteristics to use for

combustion in industrial boilers to produce electricity

power. Some recent European studies have analysed Tall

wheatgrass and encourage its consideration for semiarid

areas as a novel energy crop [24].

The aim of this report, is to use current experimental

plots in three regions of Spain established two (2010) and

three years (2009) ago for building scenarios considering

their expected lifetime. We compared tall wheatgrass and

previously reported annual grasses performance on GHG

emissions savings when producing electricity in existing

Spanish power energy plants and their economic costs at

the farm level in a wide assumed range of yields in the

three study regions.

2 MATERIALS AND METHODS

2.1 Location, climate and soil of the experimental plots

used for scenarios building

Two groups of parcels were established with tall

wheatgrass in the provinces of Girona (located in the

region of Catalonia), and Soria and Palencia (in the

region of Castilla y Leon). All plots were cultivated

under rain fed conditions in 2009 and 2010 (Figure 1).

Figure 1: Plots with Tall Wheatgrass (Elytrigia

elongata) in the three study regions in Spain

The experimental plots took place in very different

soils (Table 1). The plots in Soria were on a loam sandy

texture soil (sand 75-85%, lime less than 10% and clay

less than 15%) with organic matter about 0.6% and pH of

6.8. This soil is light, with good drainage. The deeper

texture is sandy or sandy loam. The soil in the plots of

Palencia was the richest in P with moderately high

organic matter (1.37) and the highest pH (8.5). The plots

in the province of Girona have highest organic matter

contents (1.65%).

Table I: Soil characteristics in 0-30 cm layer of the three

sites used for scenario building in this study

pH N (%)P

(mg/kg)

K

(mg/kg)

Organic

Matter (%)Texture

Girona 8,2 0,11 28 192 1,65 loam

Palencia 8,5 0,09 50,4 0,22 1,37 Franc

Soria 6,8 0,03 6,6 61,2 0,6 sandy

Regarding climate conditions, the region of Soria is

characterized by fairly hot summers, with temperatures

sometimes reaching 30 ºC, and cold winters, with

temperatures falling below 0 ºC and frequent frosts; in

2010 the first autumn frost occurred on September 27th (–

0.4 ºC), whereas the last spring frost in 2011 took place

on March 22nd (–0.4 ºC).

The province of Girona is characterized by a Coastal

Mediterranean climate. These characteristics give to this

location more moderate temperatures with no prolonged

periods of extremely high or low temperatures. The

average annual temperature is between 15-16° C, the

minimum annual average is 7°C and the

highest is 23ºC. Extreme temperatures rarely are below

0ºC or exceed 40°C. There are generally soft winters and

hot-drought summers, which generates a lot of

accumulation of water vapor in the atmosphere which

produce “cold drop” in autumn (weather phenomenon

associated with the Mediterranean area characterized by

heavy rains, hail and electrical storms). The average

rainfall values are between 600-750mm. May occur

torrential rains in spring, but especially in autumn. This

location has less dry months than other locations of these

climate characteristics. The province of Palencia, is

characterized by a Continental Mediterranean climate.

Rainfalls range between 350 and 600 mm, the maximum

is in spring and autumn (minimum in winter and

summer). The monthly mean temperature is between 7ºC

and 19 °C with cold winters (between 5 and -10 ° C), and

dry and hot summers (between 20 and 27 ° C average

temperature). Figure 2 shows Ombrothermic diagram –

average temperature (ºC) against precipitation (mm)-

from September 2010 to August 2011.

Soria

0

10

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Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

Months

Tem

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Average Temperature (ºC) Precipitation (mm)

Girona

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Girona

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Figure 2: Ombrothermic diagram for the period

September 2010-August 2011 in all three sites

2.2 Experimental plots used for scenario building

The experimental parcels were established in autumn

2009 and 2010, and in both cases they had no harvests

during the establishment year.

Table II: Experimental plots from different trials (established in 2009 and 2010) in the three study regions

Palencia Soria

Girona

Regions

Management and inputs 2009 2010 2009 2010 2009 2010

Experimental plot Strips Strips small plots Strips small plots small plots

Plot size (total in m2) 5000 4500 225 135 90 90

Tillage operations

Base (NPK in kg/ha)

1st year

Succesive years 0 250

Sowing rate 40 20 30 20 20

Sowing date Nov.2009 Nov.2010 Oct.2009 Oct.2010 Oct.2009 Oct.2010

pre-emergence none Glifosate none

post-emergence none 2-4D 2-4D and MCPA

Weed control mowings 2010 2010 2009 and 2010 2010 and 2011

Cut numbers 1 1 1 1 2 (june - Oct) 1

Biomass yield range (odt/ha) 2.5 - 6 4 - 10 5 - 12 5 - 12 12 - 39 10 - 40

300

GironaPalenciaSoria

350 500 none

Chisel, harrowing, rotary tiller

Herbicides

Top fertilizers NAC27% (kg/ha)

nonenonenone

250

Note: Yields from 2012 were estimated before harvest (June 2012). Maximum and minimum values correspond to the

extreme values of replicates in the first and second year, and in the third year in the case of trials established in 2009

Both trials (2009 and 2010) followed similar

management techniques. Operations for tillage soil

preparation were similar to those usually implemented

with cereals and annual grasses in Spain, including two

passes of chisel, one with harrow disks, rotary tiller and

ring roller. Then, a base fertilization was usually utilized

before sowing in autumn except in Girona were soils are

richer enough and typical management considers weed

competition as favoured when nitrogen fertilizers are

applied during crop establishment (table II). Sowing rates

were adjusted in relation to the germination rates and

seed viability from previous tests (data not shown).

Herbicides and weed control operations (mowing) during

establishment were followed when needed.

Figure 3: Trials plots in Soria (2009) with tall

wheatgrass during bailing in the second year

Sampling methods were used to evaluate the

production in each replicate when trials were cultivated

as small plots (Girona and Palencia). Biomass yields

including harvest losses evaluation were registered in the

grass strips of Soria by mowing and baling operations

(Figure 2). Biomass yields reported considered the

variation among trials and repetitions or replicates as well

as an estimation of the expected biomass yield to be

achieved in summer 2012. Biomass yields assumed for

the third years were based on observations and height in

June 2012.

2.3. Scenarios definition

Management, machinery operations and raw materials

Scenarios definition followed several assumptions for

the total expected lifetime of tall wheatgrass. There are

very few studies with evaluations of tall wheatgrass in a

long period of time especially without grazing

management (only grass cuttings). Many evaluations on

tall wheatgrass were intended for forage production under

extreme alkaline soil conditions that are very different

from the areas under study (mostly arable lands with low

cereal yields). Based on specific studies in other

countries, lifetime of tall wheatgrass in this assessment

was assumed to be 15 years [24]. Following this report

and our experimental plots, we assumed no harvest in the

first year, as well as a maximum yield after the third year

to be maintained for 7 years and a progressive decrease

starting after the crops has 10 years old.

Before establishment, machinery labour included

tillage operations and base broadcasting fertilizations

with NPK fertilizer in Palencia (500kg/ha). Considering

our plots in Soria, Palencia and Girona, once tall

wheatgrass was established we assumed mowing

operations during next spring in order to avoid weed

competition which is also a recommended management to

avoid excessive evapotranspiration during summer in the

first year [22]. Thus, by letting the biomass on the ground

in the first year no baling was considered.

Machinery equipment and tractors weights and

lifetime as well as diesel consumptions were taken from

the Spanish Ministry of Agriculture [25]. This

information was taken into account for the LCA and

economic costs analysis considering the number of times

of all operations during the assumed lifetime.

Fertilization during spring was also different among

the defined scenarios. Based on our experience in Soria,

no top fertilization in spring was done in the

establishment year. Fertilization with Calcium Ammonia

Nitrate (CAN) 27% doses were assumed to be 300, 250

and 150 kg/ha for Palencia, Girona and Soria based on

the soil characteristics and yield expectancy considering

climate conditions. Additionally, a nutrient restitution to

the soil with NPK was assumed to be 50kg/ha in Palencia

and Girona, and 80kg/ha in Soria 6 times in the 15 years

lifetime of tall wheatgrass.

Other inputs like herbicides where assumed based on

the plots of the three study regions as well. Thus, the

scenario considers a pre-emergence glyphosate (1 l/ha) in

Palencia, and broadleaf herbicides 2-4D and dicamba (1

l/ha) in Soria and Palencia during the first year. A final

herbicide spreading (two passes) was also assumed for

the end of the lifetime to allow a new crop establishment

(glyphosate, 1 l/ha).

Table III: Machinery equipment and number of

operations involved in the lifetime (15years) of tall

wheatgrass Weight Lifetime Palencia Girona Soria

Machinery operations for lifetime (kg) (h)

Chisel ploughing (50cm) 750 1200 1

Harrowing by disks 1800 1200 2 2

Ring roller 1500 400 1

Chisel ploughing (25cm) 750 1200 1

Rotary tiller 1400 1200 2 2

Base fertilizer application (establishment) 700 400 1 0 0

Restitution NPK fertilizer (spreader) 700 400 6 6 6

Sowing 810 750 1 1 1

Herbicides spreader (pre-emergence) 600 500 1 0 0

Top fertilizer application (spring) 700 400 15 15 14

Herbicides spreader (post-emergence) 600 500 1 1 1

Mowing 2400 667 15 16 15

Baling (250kg bales) 9000 2308 14 14 14

Bales loading 2500 1333 14 14 14

Last herbicide (End-life application) 600 500 2 2 2

Tractor 1 (120HP) 4320 12000

Tractor 2 (150HP) 5400 10000

(times)

Yields

In order to build scenarios assuming normal large-sized

plots with tall wheatgrass in the study regions, we used

the information from our management techniques and

results in small and medium sized (strips) plots. Based on

similar practices and yields in other reports from

Argentina [26], United States [27] and Hungary [24] we

defined five yield scenarios for each region: very low,

low, middle, high and very high (Table IV). These

different yields assumed no substantial changes in

fertilization or cultivation techniques. Therefore we

assumed that variation in yields is mostly caused by soil

and climate variability among years and specific site

(parcels) of each region. Yields defined in scenarios for

large plots considered the typical differences that small

plots have because of border effects (usually large plots

present 25-50% lower yields compared to small plots

depending on boarders and plot shape).

Table IV: Yield scenarios for the three study regions

Regions Very low Low Middle High Very High

Palencia (odt/ha) 4,1 5,8 7,0 8,2 10,2

Girona (odt/ha) 6,2 8,1 9,5 10,9 12,8

Soria (odt/ha) 2,4 3,9 5,0 6,1 7,0

Yield scenarios (mean value for lifetime)

The three agronomic management patterns (one per

region) and five yield levels of our three regions reported

then a total of 15 scenarios for which economic and LCA

was carried out. The five yield levels reflect variations

assumed to be linked with soil and climate variations

(climatic year and site dependent).

2.4 Life Cycle Assessment methodologies

Life Cycle Assessment (LCA) is the environmental

tool we selected to determine the energetic and

environmental performance of Tall wheatgrass to produce

lignocellulosic biomass for electricity generation.

LCA is a systematic set of procedures for compiling

and examining the inputs and outputs of materials and

energy and the associated environmental impacts directly

attributable to the functioning of a product or service

system throughout its life cycle [28]. This environmental

assessment tool is regulated by ISO 14040 [28] and ISO

14044 [29] standards, and according to this, LCAs

should follow four steps: (1) goal and definition, (2)

inventory analysis, (3) impact assessment and (4)

interpretation.

Simapro 7.2 [30,31] software tool and Ecoinvent 2.2

[32,33] European database have been selected for the

LCAs.

Also a rough nitrogen balance was made considering

nitrogen supply by fertilizers and measuring the amount

of nitrogen contended in the crops as the nitrogen

extracted.

2.4.1 Goal and Scope definition

The aim of this study is to evaluate the energy

balance and environmental impacts of the 15 scenarios

defined in the above sections for growing tall wheatgrass

as energy crop in Spain for electricity generation and

compare them with electricity generation from natural

gas, as a reference for generation from non-renewable

fossil sources.

2.4.2. Functional unit

The functional unit chosen is 1 TJ of electrical energy

generated from biomass for the studied system and from

natural gas for the reference system. This amount of

electrical energy is a round number corresponding to 12

hours of functioning of the 25Mw power plant selected

for this study (see 2.4.5).

The electricity production per hectare of tall

wheatgrass trials is the product of the crop yield (see

Table IV) at 12 % humidity by the net calorific value at

12 % humidity [27] and by the efficiency of the biomass

conversion process into electricity (29.5 % for this case

study).

2.4.3 Systems description

The bioenergy systems analyzed includes three

subsystems: agricultural biomass production, electricity

generation and the transport of products and raw

materials.

Agricultural system

The agricultural system could be described by the

crop schemes followed, the machinery used and the

inputs consumed.

Biomass power plant system

All the data considered to model the biomass power

plant system are real data from a 25 MW biomass plant

located in northern Spain. This plant consumes biomass

at an average humidity of 12% and produces electricity

with a conversion efficiency of 29.5%. The plant

consumes natural gas for maintenance operations and

pre-heating and produces ashes and slag from biomass as

residues. The average consumption of natural gas and the

productions of ashes and slag per kilogram of burned

biomass are shown in Table V.

Table V: Biomass power plant consumptions and

residues produced Consumed or produced

substances Amount

Natural gas consumption

(MJ Kg-1 Wet Biomass Burned)

0.0342

Slag production

(g Kg-1 Wet Biomass Burned) 82.47

Ashes production

(g Kg-1 Wet Biomass Burned)

8.25

The emissions of the plant into the air are submitted

regularly to the local government. The emissions

accounted are only those which affect the global warming

potential (GWP). In the power plant studied these

emissions come from gas natural combustion (see Table

VI). Carbon dioxide emitted from biomass combustion

was not considered because it was previously fixed from

the air by the crop.

Table VI: Biomass power plant aerial emissions Substance Origin Amount

(g Kg-1 Wet Biomass

Burned)

Fossil carbon

dioxide Natural gas 1.94

Table VII: Transport system summary Material From To Distance Vehicle

Seed Field Processing

center 30 km

Lorry

20-28t

Processing

center

Regional

storehouse 100 km

Lorry

20-28t

Regional

storehouse

Demonstratio

n parcel 10 km

Lorry

16-32t

Fertilizers

and

herbicides

Manufacturer Regional

storehouse 600 km Train

100 km Lorry

>16t

Regional

storehouse

Demonstratio

n parcel 10 km

Lorry

16-32t

Biomass Demonstratio

n parcel Biomass plant 60 km

Lorry

16-32t

Ash and

slag Biomass plant Disposal 37 km

Lorry

16-32t

Transport system

The transport system is summarized in Table VII.

This table shows all modes of transport used and the

distances between origin and destination points for every

transport in the LCAs carried out.

The transportation means and distances for the

transport of agricultural inputs until the regional

storehouse are taken from the Ecoinvent database [34].

The distance from the regional store house to plots was

10 km approximately. The transport of workers to the

parcel has not been considered because of the highly

variability of transport distances depending on cases.

Biomass, ash and slag means of transport and distances

were provided by company in charge of the biomass

power plant.

Natural gas system

The natural gas system includes the gas field

operations for extraction, the losses, the emissions and

the purification of the main exporter counties of natural

gas to Spain (Algeria 73 % and Norway 27 %). Also

includes the long distance and local transport of gas to

the power plant in Spain, considering the energy

consumption, loses and emissions for distribution.

Finally the substances needed and the average efficiency

of Spanish natural gas power plants to produce electricity

are taken into account [35].

2.4.4 Life cycle inventory analysis

The inventories used to consider natural gas

consumption [35] of the biomass power plant, transports

[36] of agricultural inputs, and biomass and power plant

residues are taken from Ecoinvent.

The methods used for the inventory analysis of the

agricultural system mainly follow that proposed on Life

cycle inventories of agricultural production systems [34].

To consider N2O emissions we follow the formula

proposed by de RSB GHG Calculation Methodology v

2.0 [12]. This formula is basically based on the formula

proposed in the Ecoinvent Agricultural Report [34], that

considers the new IPCC guidelines [37]. Also we

consider the nitrate emissions affecting to Global

Warning Potential as the RSB purposes [12], making and

estimation of them by means of nitrogen balance, the soil

and crop characteristics and the rainfall of the zone.

Fertilizers productions

The fertilizer inventories consider the different steps

of the production processes, such as the use of raw

materials and semi-finished products, the energy used in

the process, the transport of raw materials and

intermediate products, and the relevant emissions [34].

The production of calcium ammonium nitrate starts

with the production of the ammonium nitrate by the

neutralization of ammonia with nitric acid. The final

product is then obtained by adding dolomite or limestone

to the solution before drying and granulation [38].

No inventories are given in Ecoivent for multinutrient

fertilizers due to the amount different possible ways to

mix nitrogen, phosphorous and potassium compounds to

produce NPK fertilizers [38]. The modeling of NPK

fertilizer inventories has been approximated by

combining inventories of single fertilizers according to

multinutrient fertilizer specific contents of N, P2O5 and

K2O, as well as the form of the nitrogen provided

(ammonium, nitrate or urea) [38].

Herbicides production

The data related to emissions, energy and substance

consumption in the production of the herbicides sprayed

is taken from Ecoinvent [39]. The quantities of active

matters considered are taken from the formulations of the

commercial fertilizers used.

Seed production

Tall wheatgrass seeds can be produced in Spain under

similar conditions compared to the operations of fertilizer

and management practices used for forage cultivation.

Tall wheatgrass seeds are frequently produced under

irrigation in high quality soils under contract with real

farmers, thus their normal operations and yield

production were assumed to be similar to that of the local

common management practices considered in this study.

Then, a grain production yield of 0.8 odt ha-1 was

considered as suggested by other studies [25,26,27].

The energy consumption for cleaning, drying, seed

dressing, and bag filling of the Tall wheatgrass seed in

the processing plant has been estimated in 32.8 kWh t-

1[40].

Diesel consumption and combustion emissions of

agricultural machinery

The diesel consumption of agricultural machinery

was obtained from the Spanish Ministry of Agriculture

[25]. The inventories for the extraction, transport of

petrol, the transformation into diesel and its distribution

are taken from Ecoinvent [41]. The exhaust emissions of

diesel in agricultural machinery engines are also

considered [41].

Agricultural machinery manufacture

The inventories for agricultural machinery

manufacture are specific to the different types of

machinery (tractors, harvesters, tillage implements or

general implements).

The amount of machinery (AM) needed for a specific

process was calculated multiplying the weight (W) of the

machinery by the operation time (OT) and dividing the

result by the lifetime of the machinery (LT) [34]:

AM (kg FU-1) = W (kg) OT (h FU-1) LT-1(h);

Where FU (See 2.4.2) is the functional unit of the

LCA. The life time was obtained from the Spanish

Ministery of Agriculture (see Table III) [25].

Nitrous oxide emissions

The calculation of the N2O emissions [12] is based

on the formula in Nemecek et Kägi [34] and adopts the

new IPCC guidelines [37]:

N2O=

44/28∙(EF1∙(Ntot+Ncr)+EF4∙14/17∙NH3+EF5∙14/62∙NO3-)

With:

N2O = emissions of N2O [kg N2O ha-1]

EF1 = 0.01 (IPCC proposed factor [37])

Ntot = total nitrogen input [kg N ha-1]

Ncr = nitrogen contained in the crop residues [kg N ha-1]

EF4 = 0.01 (IPCC proposed factor [37])

NH3 = losses of nitrogen in the form of ammonia [kg

NH3 ha-1]. Calculated as proposed in the RSB [12] and

Nemecek et Kägi [34] methodologies.

14/17= conversion of kg NH3 in kg NH3-N

EF5 = 0.0075 (IPCC proposed factor [37])

NO3- = losses of nitrogen in the form of nitrate [kg NO3

ha-1]. They were estimated through the RSB formula [12]

which considers nitrogen supply, the nitrogen uptake, the

soil and crop characteristics and the local rainfall.

14/62= conversion of kg NO3- in kg NO3-N.

Land use changes

Direct land used change does not take place because

the parcel selected was previously a winter cereal crop

land. Indirect land use change is a complex process that

is not fully understood by the scientific community and

so is not included in this study [43].

2.4.5 Life cycle impact assessment

Life Cycle Impact Assessment (LCIA) is the phase in

an LCA where the inputs and outputs of elementary flows

that have been collected and reported in the inventory are

translated into impact indicator results [44].

LCIA is composed of mandatory and optional steps.

Mandatory steps of classification and characterization

have been carried out and optional steps normalization

and weighting have been avoided in order to make results

more comparable and to avoid introducing value choices.

In the classification steps elementary flows shall be

assigned to those one or more impact categories to which

they contribute. In the characterization steps each

quantitative characterization factor shall be assigned to

all elementary flows of the inventory for the categories

that have been included in the classification [44].

Environmental impact assessment method

We have selected the software tool Simapro 7.2 [45]

and the impact assessment method of the IPCC 2007 [46]

to assess the 100 years’ period horizon Global Warming

Potential (GWP).

Energy assessment method

In order to assess the energy consumed to generate

electricity from tall wheatgrass biomass and from natural

gas, we have selected the software tool Simapro 7.2 [45]

and the Cumulative Energy Requirement Analysis

(CERA) [48]. This method aims to investigate the energy

use throughout the life cycle of a good or service. The

primary fossil energy (FOSE) has been obtained using

this method.

2.5. Comparison between tall wheatgrass and winter

cereals from previous studies

A previous study data and results from two

experimental plots with triticale (Triticosecale sp.), oats

(Avena sativa), lopsided oats (Avena strigosa L.) and rye

(Secale cereale) was utilized in order to make

comparisons with tall wheatgrass scenarios performance.

The 15 scenarios of tall wheatgrass were based in a

similar range of biomass yields compared to the cited

research in which GHG emissions savings when

substituting natural gas electricity by combusting biomass

in a 25MW boiler. The mentioned study considered two

sites with experimental plots located in two Spanish

provinces in Castilla y León (Soria and León). The power

energy plant and transport systems cited in tables V and

VI, were the same for both studies [13].

2.6 Economic costs at the farm level

In order to calculate costs for biomass production at

the farm level, the 15 scenarios defined for tall

wheatgrass in above sections were analysed together with

the winter cereal trials analysed in previous studies [13].

Winter cereals costs included two regions as defined in

our previous study (Soria and León) which were assumed

to explore enough yield and be management

representative for typical cereal areas in central Spain.

Rental land costs in Soria were assumed to be 90€/ha per

year when cropping Tall wheatgrass. Winter cereals

rental land costs were assumed to be an average value for

the region of Castilla y León (119€/ha.year). Both tall

wheatgrass and winter cereals used economic data from

MARM (2012)[25] and local information for fertilizer,

herbicides and tall wheatgrass seeds prices.

2.7. Nitrogen balances

A rough nitrogen balance was made. This estimation

considers nitrogen supplied in base and top fertilizations

as the entrance of the system and total nitrogen content of

rye aerial biomass trials as exit of the system. The total

amount of nitrogen extracted and exported by the crop

harvest is calculated by multiplying the yield of each

scenario (see Table IV) by its respective biomass

nitrogen content [27]. As roots remain into the soil we

assumed that all nitrogen from roots return to the soil.

Therefore we did not take into account any proportion of

root nitrogen content as extracted nitrogen.

3 RESULTS AND DISCUSSION

3.1 Economic assessment

Costs at the farm level resulted to be much higher for

biomass production from winter cereals compared to Tall

wheatgrass (Figure 4).

0

20

40

60

80

100

120

140

160

180

200

220

240

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Me

an

bio

ma

ss

co

st

(€/o

dt)

Biomass yield (odt/ha.year)

Tall wheatgrass Palencia

Tall wheatgrass Soria

Tall wheatgrass Girona

Triticale

Rye

Oat

Lopsided Oat

Figure 4: Biomass costs production at the farm level in

Tall wheatgrass and winter cereals

Table VIII: main costs for biomass from three scenarios

of Tall wheatgrass and for winter cereals considered in

this study Winter cereals

€/ha.y-1

Regions/inputs Palencia Girona Soria (Soria and León)

Field works 19 18 16 164

base fertilization 13 0 0 157

Top fertilization 70 54 35 70

Pre emergence herbicides 1 8 13 0

Reposition fertilization 8 2 0 0

Post emergence herbicides 1 2 1 51

Final herbicides 2 2 2 0

Rental land 119 174 90 119

Mowing, baling and loading 156 153 153 163

Seeds 5 5 5 114

Total 393,58 418,53 314,18 838,00

Tall wheatgrass (€/ha.y-1)

Considering the biomass yields explored range in our

scenarios, Tall wheatgrass produced lower costs at all

yields but differences were higher (as much as 124€/odt)

when biomass yield was lower (below 4odt/ha). Highest

yields showed a lower cost for Tall wheatgrass (around

36€/odt) suggesting that more productive areas may be

also better suited for the perennial grass.

Total mean costs per hectare considering 15 years

lifetime of Tall wheatrgrass, were much higher that

winter cereals in all scenarios (Table VIII). The higher

costs of winter cereals might be explained mainly because

of a higher contribution of establishment (machinery

operations, base fertilization and sowing). Rental lands

contribution, top fertilization and harvest operations

(mowing, baling and loading) are major costs affecting

Tall wheatgrass.

3.2. Global warming potential

Increasing yields reflect a remarkable reduction in

GHG emissions when producing electricity in a power

energy plant. Nevertheless, winter cereals had higher

GWP at similar yields at the farm level compared to Tall

wheatgrass. As reflected with mean production costs,

lower yields achieved higher GWP per TJ in winter

annual grasses compared to Tall wheatgrass (Figure 5).

0

20

40

60

80

100

120

2000 4000 6000 8000 10000 12000 14000

GW

P (

Mg

CO

2 e

q T

J e

lect

rcit

y-1

)

Yield (kg d.m. ha-1)

Oat

Lopsided Oat

Rye

Triticale

Tall wheatgrass

(Soria)

Tall wheatgrass

(Palencia)

Tall wheatgrass

(Gerona)

Figure 5: Global warming potentials as function of

biomass yields per hectare in winter cereals and Tall

wheatgrass scenarios.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

2000 4000 6000 8000 10000 12000 14000

GH

G S

avin

gs

(%)

Bio

ma

ss C

om

pa

red

to

el

ectr

icit

y

from

Na

tura

l G

as

as

foss

il r

efer

ence

Yield (kg d.m. ha-1)

Oat

Lopsided Oat

Rye

Triticale

Tall wheatgrass

(Soria)

Tall wheatgrass

(Palencia)

Tall wheatgrass

(Gerona)

Tall wheatgrass

Figure 6: GHG emissions savings of Tall wheatgrass and

winter cereals producing electricity from biomass as a

function of biomass yield.

0,2

0,6%

14,5

40,8%

13,4

37,6%

4,6

12,9%

2,3

6,4%

0,6

1,8%

Seed and Pesticides Fertilizers

Nitrous Oxide Field Works

Biomass transport Power Plant Operation

0,2

0,4%

21,7

50,2%

15,0

34,7%

3,5

8,0%

2,3

5,2%

0,6

1,5%

Seed and Pesticides Fertilizers

Nitrous Oxide Field Works

Biomass transport Power Plant Operation

0,1

0,4%

12,8

45,3%

10,0

35,4%

2,4

8,6%

2,3

8,0%

0,6

2,3%

Seed and Pesticides Fertilizers

Nitrous Oxide Field Works

Biomass transport Power Plant Operation

Soria

Palencia

Girona

Figure 7: Different contributions to the global warming

potentials for tall electric production (TJe) from biomass

of wheatgrass in the three study regions

Higher yields produced a higher emission reduction

when comparing GWP of electricity from biomass in the

25MW power energy plant, with natural gas electricity in

Spain (figure 6). As suggested in previous studies, winter

cereals low biomass yields at the farm level determine

higher GWP and lower emissions reductions replacing

the fossil reference. Even under extremely low yield

scenarios (below 4odt/ha) calculated GHG emissions

savings were always higher than 50% and low and

medium yields scenarios in both Palencia and Soria, were

always above 60%. These results suggest that Tall

wheatgrass biomass used for electricity might be suitable

for areas with lower potential yields achieving similar

limitations stated in the sustainability criteria established

for biofuels in the RED.

As shown in Figure 7, most important inputs causing

GWP are fertilizer production and those derived from

fertilizer use (nitrous oxide), accounting in total for

89.9% in Palencia, 78.4% in Soria and 80.7% in Girona.

Differences are linked to the nitrogen fertilizer doses for

each case (see table II).

3.3. Energy balances

Energy yields increased significantly with biomass

production per hectare as most inputs variation is lower

than outputs, suggesting that specific conditions could be

(yearly climate differences or soil variability) could

generate different energy balance scenarios. Therefore,

climate and soil conditions determining yields might

cause large variations on energy balances as well. Tall

wheatgrass originate a similar response compared to

winter cereals, but with a parallel higher response when

correlating energy yields at the power energy plant with

biomass yields in the field (figure 9).

0,0

1,0

2,0

3,0

4,0

5,0

6,0

7,0

8,0

2000 4000 6000 8000 10000 12000 14000

En

erg

y o

utp

ut

per

fo

ssil

en

erg

y i

np

uts

(T

J e

lect

rict

y

TJ

fo

ssil

en

erg

y-1

)

Yield (kg d.m. ha-1)

Oat

Lopsided Oat

Rye

Triticale

Tall wheatgrass

(Soria)

Tall wheatgrass

(Palencia)

Tall wheatgrass

(Gerona)

Figure 9: Energy ratios for electricity production from

biomass of Tall wheatgrass and winter cereals scenarios

as a function of biomass yield

The scenario for the region of Soria clearly has a

higher energy yield at similar biomass yields in the farm

probably explained by lower fertilizer uses (figure 10).

Most important fossil input contributions were

fertilizers. Fossil energy inputs were mostly caused by

fertilizers: 46%, 59.8 and 50.7 in Soria, Palencia and

Girona respectively. Secondly, machinery fossil inputs

and raw materials (pesticides and seeds) were affecting

energy ratios as well.

3.4. Soil nitrogen balance

Nitrogen balances in the soil changed dramatically in

the scenarios assumed for tall wheatgrass as a function of

biomass yield (Figure 11). A clear negative relationship

between soil nitrogen balance and biomass yield seems to

be explained as nitrogen fertilizer uptakes are higher to

nitrogen applications then suggesting a necessarily soil

nitrogen extraction from the soil nitrogen stock. As

management scenarios defined in this study considered

same nitrogen doses for five different biomass yields,

higher biomass yields imply a higher nitrogen uptake

compared to lower yields (figure 12). This result suggest

that yields between 6 and 8 odt/ha resulted in assumed no

changes in soil nitrogen.

0,002

1,0%

0,098

46,0%

0,067

31,5%

0,035

16,5%

0,011

5,0%

Seed and Pesticides Fertilizers

Field Works Biomass transport

Power Plant Operation

Soria

0,002

0,8%

0,146

59,8%

0,051

20,7%

0,035

14,4%

0,011

4,4%

Seed and Pesticides Fertilizers

Field Works Biomass transport

Power Plant Operation

Palencia

0,001

0,7%

0,085

50,7%

0,036

21,3%

0,035

21,0%

0,011

6,4%

Seed and Pesticides Fertilizers

Field Works Biomass transport

Power Plant Operation

Girona

Figure 10: Different contribution for energy fossil inputs

per TJe in the three study regions with Tall wheatgrass

-80

-60

-40

-20

0

20

40

60

0 2000 4000 6000 8000 10000 12000 14000

Nit

rog

en B

ala

nce

(k

g N

ha

-1)

Yield (kg d.m. ha-1)

Tall

wheatgrass

(Soria)

Tall

wheatgrass

(Palencia)

Tall

wheatgrass

(Gerona)

Figure 11: Soil nitrogen balances in the three regions

scenarios as a function of its biomass yields.

As mentioned in above sections, obtaining high GHG

emissions savings would probably mean that Tall

wheatgrass had enough high biomass (energy output) and

energy yield, compared to the GHG emissions incurred

for crop and post-harvest transport and processing

producing electricity. Nevertheless, our results indicate

that producing more biomass implies more nitrogen

uptake and a potential excessive soil nitrogen depletion

that should be addressed in a bioenergy sustainable

production. In Girona for instance, only very low yields

extracted less nitrogen than that supplied to the crop.

Highest GHG emission reductions coincide with soil

nitrogen depletion suggesting that an adequate nitrogen

management should be consider (more nitrogen fertilizers

may cause higher fossil inputs and lower emission

reductions but may allow soil nitrogen stability).

40%

45%

50%

55%

60%

65%

70%

75%

80%

85%

90%

-80 -60 -40 -20 0 20 40 60

GH

G S

av

ings

(%)

Co

mp

are

d t

o el

ectr

icit

y f

rom

Na

tura

l G

as

as

foss

il r

efer

ence

)

Nitrogen Balance (kg N ha-1)

Tall

wheatgrass

(Soria)

Tall

wheatgrass

(Palencia)

Tall

wheatgrass

(Gerona)

NITROGEN SURPLUSNITROGEN DEFICIT

Figure 12: GHG emissions savings as a function of soil

nitrogen balances.

4 CONCLUSIONS

From the results obtained under the trial conditions, it

can be concluded that:

Tall wheatgrass has good prospects for energy in

view of the amount of biomass produced in less fertile

areas without too many inputs.

According to the obtained results, the mean

production costs of Tall wheatgrass at the farm level

ranged from 40-60 €/odt for low and medium yield

scenarios (5-7 odt/ha.year). These costs are lower than

those of winter cereals that should have maximum yields

in order to obtain similar biomass costs. Considering a

price of 75-85€/odt for square bales at the farm (loaded

on the truck), wheat grass have a potential profitability at

least for the scenarios defined in this study. This suggests

that Tall wheatgrass could be suitable to supply power

energy plants in Spain.

Considering the explored range of crop yields and

management conditions, GHG emissions savings when

using Tall wheatgrass biomass for producing electricity

are significantly higher (50-90%) of those of winter

cereals (5-70%). Energy yields of electricity production

where clearly higher when biomass was obtained from

perennial grasses (2.5-7.5) compared to those of

electricity from winter cereals biomass (1.5-3).

These results suggest that TW can have a significant

potential as energy crop in marginal lands in Spain.

Nitrogen fertilization have been observed to be the

most important input to be considered when producing

energy from the species under study. This is because

nitrogen fertilizer production requires a large amount of

energy, causing greenhouse gas N2O emissions and

having a significant negative impact on CO2 balance.

Another sustainability indicator considered in this

study was nitrogen balance that was linked with GHG

emissions savings of electricity from biomass in Tall

wheatgrass. As management techniques regarding base

fertilizers (NPK) and top fertilizer applications in spring

(calcium ammonia nitare, 27%) were different in each

site and the production was assumed to vary in five

scenarios, an impact on the soil nitrogen balance suggest

that soil must be considered when looking for

sustainability of perennial grasses. It would be important

to consider no only energy crop fertilizing and its impact

on biomass quality and emissions but also economic and

energy balances. Moreover, the interest lies on obtaining

maximum yields with a minimum emission impact, so it

is recommended to improve the efficiency in the use of

nitrogen by adjusting the dose, the optimal timing of

application, the type of fertilizer, etc., or the inclusion of

alternative crops like nitrogen fixing species (legumes) or

pasture mixes.

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6 ACKNOWLEDGEMENTS

This work has been developed in the framework of

the Spanish National and Strategic Project `On Cultivos’

co-funded by the Spanish Ministry of Economy and

Competitiveness and the European Funds for Regional

Development (ERDF).under the dossier PSE-120000-

2009-15

7 LOGO SPACE