Apresentação do PowerPoint · for P&W reportedand Tissue paper accordingly to ABTCP (2017) and...

A MILP Framework for Forest Systems Evaluat ion

Biorefineries Design

Bruno Theozzo & Moises Teles dos Santos

1. Genera l

Overview

Genera l Over v iew

Conventional Refinery

Crude Oil Refineries

Chemicals

Energy

Genera l Over v iew

Biorefineries

Biomass Biorefineries

Chemicals

Energy

Renewable

Renewable

Genera l Over v iew

Products from Biomass

Biomass Lignocellulosic

Kraft Cooking

Paper PULP

Eletricity

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Combustion

Heat

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Combustion

Heat

Pyrolysis Bio-oil

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Combustion

Heat

Pyrolysis Bio-oil Upgrading

Syn-Gas Aromatics

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Combustion

Heat


Syn-Gas Aromatics Pretreament C5 & C6 Sugars

Genera l Over v iew



Kraft Cooking

Paper PULP

Eletricity

Lignin

Combustion

Heat


Syn-Gas Aromatics Pretreament C5 & C6 Sugars

Genera l Over v iew

Location Dependency

Biomass demands a high amount of Land which may increase the pression on Food Cultivation and Native Forests Lands

Genera l Over v iew

Location Dependency


Available Lands may not present enough Productivity Potential for a Economically feasible Plantation of Biomass

Genera l Over v iew

Location Dependency



Land Availability and Products Demand usually have a Negative Correlation

Genera l Over v iew

Location Dependency




Forest Systems take Several Years for reaching Commercial Maturity

Genera l Over v iew

Location Dependency




Forest Systems take Several Years for reaching Commercial Maturity

Time and Location Dependent Decision-Making

2. Proposed

Framework

Proposed F ramework

4 Layers Approach

Forest Layer • Which Biomass to plant (or buy)

• Where to Plant the Biomass

• When to Plant and When to

Harvest

Proposed F ramework

4 Layers Approach

Production Layer • Which Technological Route to use

• Where to Locate each Facility

• Where to Get Biomass from




Harvest

Proposed F ramework

4 Layers Approach

Market Layer • Which Products to Produce

• Which Locations to Attend







Harvest?

Proposed F ramework

4 Layers Approach

Market Layer • Which Products to Produce?

• Which Locations to Attend?




Storage Layer • Where to keep Stock

• How to Connect Supply and

Demand




Harvest?

3. Layer

Market

Market Layer

Products Demand

Pulp

Pulp Demand estimated

through Installed Capacity

of Main Producers in Brazil

for P&W and Tissue paper

accordingly to ABTCP

(2017) and Prices are taken

from Suzano Investors

Report (2018)

Market Layer

Products Demand

Pulp Electricity








Report (2018)

Electricity Demand are taken

from Statistical Annuary by

EPE (2017) considering 2.9%

of Substitution which

corresponds to the Energy

Generated by Coal and Prices

are taken as the Historical

Mean accordingly to the

same report.

Market Layer

Products Demand

Pulp Electricity Lignin








Report (2018)

Lignin Demand will be

represented by Cement

Capacities in Brazil

reported by SNIC (2018)

considering a 0.2% of

addition reported by

Huang et al (2018) and

Price of 1800 BRL/ton [1]

accordingly to Gosselink

(2011)

Electricity Demand are taken

from Statistical Annuary by

EPE (2017) considering 2.9%

of Substitution which

corresponds to the Energy

Generated by Coal and Prices

are taken as the Historical

Mean accordingly to the

same report.

4. Layer :

Production

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood

Set Q: Chemical Species

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies

𝒎𝒑𝒑,𝑞,𝒕 − 𝒎𝒑𝒑,𝑞,𝒕−1

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies

𝒎𝒑𝒑,𝑞,𝒕 − 𝒎𝒑𝒑,𝑞,𝒕−1 𝑭𝑭𝑷𝒑,𝑞,𝒕 =

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies

𝒎𝒑𝒑,𝑞,𝒕 − 𝒎𝒑𝒑,𝑞,𝒕−1 𝑭𝑭𝑷𝒑,𝑞,𝒕

+ 𝑭𝑻𝑷𝒑′,𝒑,𝑞,𝒕𝒑′∈𝑷

− 𝑭𝑻𝑷𝒑,𝒑′,𝑞,𝒕𝒑′∈𝑷

=

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies


+ 𝑭𝑷𝒁𝒑,𝒛,𝒒,𝒕𝑧∈𝑍

− 𝑭𝒁𝒑,𝒛,𝑞,𝒕𝑧∈𝑍



=

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies



− 𝑭𝑷𝑴𝒑,𝒎,𝑞,𝒕𝒎∈𝑴


− 𝑭𝑷𝑬𝒑,𝒆,𝑞,𝒕𝒆∈𝑬



=

Product ion Layer

Mass Balance

• Lignin

• Bleached Pulp

• Brown Pulp

• Black Liquor

• Wood Chips

• Wood Fines

• Raw Wood


• Wood

Preparation

• Kraft Cooking

• Lignin

Precipitation

• Steam Turbine

• Bleaching

Set Z: Technologies



− 𝑭𝑷𝑴𝒑,𝒎,𝑞,𝒕𝒎∈𝑴


− 𝑭𝑷𝑬𝒑,𝒆,𝑞,𝒕𝒆∈𝑬



=

Product ion Layer

Conversion Technologies

Production of Chemical “Qprod”

𝑭𝑷𝒁𝒑,𝒛,𝒒𝒑𝒓𝒐𝒅,𝒕 = 𝑭𝒁𝒑,𝒛,𝒒,𝒕𝒒∈𝑸

𝑐𝑜𝑛𝑣_𝑞 𝑧,𝑞,𝒒𝒑𝒓𝒐𝒅

Product ion Layer





/WoodPreparation.Wood.Chips 0.95 WoodPreparation.Wood.Fines 0.05/

GAMS Coding

Product ion Layer






GAMS Coding

• Electricity

• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities

Product ion Layer






GAMS Coding

𝑭𝑼𝒑,𝒛,𝒖,𝒕𝒏𝒆𝒆𝒅𝒆𝒅 = 𝑭𝒁𝒑,𝒛,𝒒,𝒕

𝒒∈𝑸

𝑢𝑡𝑙𝑧,𝑞,𝑢 • Electricity

• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities

Product ion Layer






GAMS Coding


𝒒∈𝑸


• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities

𝑭𝑼𝒑,𝒛,𝒖_𝒑𝒓𝒐𝒅,𝒕𝒑𝒓𝒐𝒅𝒖𝒄𝒆𝒅

= 𝑭𝒁𝒑,𝒛,𝒒,𝒕𝒒∈𝑸

𝑐𝑜𝑛𝑣_𝑢 𝑧,𝑞,𝑢_𝑝𝑟𝑜𝑑

Product ion Layer






GAMS Coding


𝒒∈𝑸


• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities




+ 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝑻𝑜 𝑏𝑒 𝑖𝑛𝑡𝑒𝑟𝑐𝑜𝑛𝑣𝑒𝑟𝑡𝑒𝑑

𝒖∈𝑼

𝑐𝑜𝑛𝑣_𝑖𝑛𝑡𝑢 𝑧,𝑢,𝑢_𝑝𝑟𝑜𝑑

Product ion Layer






GAMS Coding


𝒒∈𝑸

𝑢𝑡𝑙𝑧,𝑞,𝑢 + 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝑻𝑜 𝑏𝑒 𝑖𝑛𝑡𝑒𝑟𝑐𝑜𝑛𝑣𝑒𝑟𝑡𝑒𝑑

• Electricity

• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities





𝒖∈𝑼


Product ion Layer






GAMS Coding


𝒒∈𝑸


• Electricity

• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities





𝒖∈𝑼


𝑭𝑼𝒑,𝒖,𝒕𝑩𝑼𝒀 − 𝑭𝑼𝒑,𝒖,𝒕

𝑺𝑬𝑳𝑳 = 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝒏𝒆𝒆𝒅𝒆𝒅

𝒛∈𝒁

− 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝒑𝒓𝒐𝒅𝒖𝒄𝒆𝒅

𝒛∈𝒁

Product ion Layer






GAMS Coding


𝒒∈𝑸


• Electricity

• NaOH

• Chlorine

• Steam

• Wood Fines

• Raw Wood

Set U: Utilities





𝒖∈𝑼


𝑭𝑼𝒑,𝒖,𝒕𝑩𝑼𝒀 − 𝑭𝑼𝒑,𝒖,𝒕

𝑺𝑬𝑳𝑳 = 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝒏𝒆𝒆𝒅𝒆𝒅

𝒛∈𝒁

− 𝑭𝑼𝒑,𝒛,𝒖,𝒕𝒑𝒓𝒐𝒅𝒖𝒄𝒆𝒅

𝒛∈𝒁

Utilities can only be

traded within

Production Unit P

Product ion Layer


Feed Restrictions

𝑭𝒁𝒑,𝒛,𝒒,𝒕 ≤ 𝑀𝑡𝑒𝑐,𝑧,𝑞𝒚𝒑𝒛𝒑,𝒛 ∀(𝑝 ∈ 𝑃, 𝑧 ∈ 𝑍, 𝑞 ∈ 𝑄, 𝑡 ∈ 𝑇

Product ion Layer


Feed Restrictions


𝑭𝒁𝒑,𝒛,𝒒,𝒕 ≤ 𝑀𝑡𝑒𝑐,𝑧,𝑞 𝑐𝑜𝑛𝑣𝑞

𝑧,𝑞,𝑞𝑝𝑟𝑜𝑑

𝑞𝑝𝑟𝑜𝑑

+ 𝑐𝑜𝑛𝑣_𝑢 𝑧,𝑞,𝑢𝑝𝑟𝑜𝑑𝑢_𝑝𝑟𝑜𝑑

Product ion Layer


Feed Restrictions






Investments

𝑭𝒁𝒑,𝒛,𝒒𝒎𝒂𝒙 ≥ 𝑭𝒁𝒑,𝒛,𝒒,𝒕

Product ion Layer


Feed Restrictions






𝐼 = 𝐼𝑟𝑒𝑓𝐹𝑍𝑚𝑎𝑥

𝐹𝑍𝑟𝑒𝑓

𝑛𝑧,𝑞

Investments


Product ion Layer


Feed Restrictions








𝑛𝑧,𝑞

Investments

Piecewise Linear Approximation (Bergamini et al, 2011)


Product ion Layer


Feed Restrictions








𝑛𝑧,𝑞

Investments

Piecewise Linear Approximation (Bergamini et al, 2011)


Investment data taken from

Fibria Investors Report for

Project Horizonte II (2011)

Product ion Layer

Capacity Decisions

• Wood

• Wood Chips

• Fines

• Brown Pulp

• Black Liquor

• Steam

Location & Capacity for Facilities

Product ion Layer

Capacity Decisions

• Wood

• Wood Chips

• Fines

• Brown Pulp

• Black Liquor

• Steam

Location & Capacity for Facilities

Production to Market Flows

5. Layer :

Forest

Fores t Layer

Demand for Biomass

Forest Layer Production Layer

Fores t Layer

Demand for Biomass


Chemical

Chemical Species set

Wood

Chips

Fines

….

Bleached Pulp

Biomass b composition

Wood = 1

Chips = 0

Fines = 0

….

Fores t Layer

Demand for Biomass


Chemical


Wood

Chips

Fines

….

Bleached Pulp


Wood = 1

Chips = 0

Fines = 0

….

Fores t Layer

Demand for Biomass


Chemical Biomass


Wood

Chips

Fines

….

Bleached Pulp


Wood = 1

Chips = 0

Fines = 0

….

Fores t Layer

Demand for Biomass


Chemical Biomass


Wood

Chips

Fines

….

Bleached Pulp

Harvested Area

• Biomass b

• Age i

Cumulative Growth Parameter


Wood = 1

Chips = 0

Fines = 0

….

Fores t Layer

Demand for Biomass


Chemical


Wood

Chips

Fines

….

Bleached Pulp

Biomass

Harvested Area

• Biomass b

• Age i

Cumulative Growth Parameter

𝑭𝑭𝒇,𝒃,𝒕𝒉𝒂𝒓𝒗𝒆𝒔𝒕𝒆𝒅 = 𝜂𝑏

ℎ𝑎𝑟𝑣𝑒𝑠𝑡𝑖𝑛𝑔 𝑮𝒓𝒐𝒘𝒕𝒉𝒇,𝒃,𝒊

𝒄𝒖𝒎𝒖𝒍𝒂𝒕𝒊𝒗𝒆𝑨𝒇,𝒃,𝒊,𝒕𝒉𝒂𝒓𝒗𝒆𝒔𝒕𝒆𝒅

𝑖 ∈ 𝐼

Fores t Layer

Productivity

As forests have a non-linear growth with ageing…

A Cumulative Wood Production parameter is defined for each

Biomass in each Forest Unit in function of its Age.

Fores t Layer

Productivity




Fores t Layer

Productivity


Maximmum Value taken as

7 times the Producticity of

the Clone on year 3 in study

from Blinkey et al (2017)



Fores t Layer

Productivity





from Blinkey et al (2017)



4 years taken as the inflection point

Fores t Layer

Productivity





from Stape et al (2010)



4 years taken as the inflection point

Maximmum Age above which all properties are taken as constant

Fores t Layer

Lands Parameters

Planted Area - Eucalyptus Available Land - Expansion

Source: IBA (2015) Source: Lossau et al (2015)

Fores t Layer

Lands Parameters



The Top 10 States with Eucalyptus Plantation will be taken for

evaluation for the Model added to Goias and Tocantins which are

relevant regarding Available Land.

Fores t Layer

Lands Parameters



The Top 10 States with Eucalyptus Plantation will be taken for

evaluation for the Model added to Goias and Tocantins which are

relevant regarding Available Land.

Set of Potential Forests Units Bahia Espírito Santo Goiás Maranhão Mato Grosso Mato Grosso do Sul Minas Gerais Paraná Rio Grande do Sul Santa Catarina São Paulo Tocantins >95% of Planted Eucalyptus >83% of Available Land

Fores t Layer

Land balances

𝑨𝒇,𝒃,𝒊,𝒕𝑯𝒂𝒓𝒗𝒆𝒔𝒕

Area Available for Harvesting

Fores t Layer

Land balances

𝑨𝒇,𝒃,𝒊−𝟏,𝒕−𝟏𝒑𝒍𝒂𝒏𝒕𝒆𝒅,𝑲𝑬𝑬𝑷

= 𝑨𝒇,𝒃,𝒊,𝒕𝑯𝒂𝒓𝒗𝒆𝒔𝒕


Fores t Layer

Land balances

−𝑨𝒇,𝒃,𝒊,𝒕𝑷𝒍𝒂𝒏𝒕𝒆𝒅,𝑲𝑬𝑬𝑷 𝑨𝒇,𝒃,𝒊−𝟏,𝒕−𝟏

𝒑𝒍𝒂𝒏𝒕𝒆𝒅,𝑲𝑬𝑬𝑷 = 𝑨𝒇,𝒃,𝒊,𝒕

𝑯𝒂𝒓𝒗𝒆𝒔𝒕


Fores t Layer

Land balances





+𝑨𝒇,𝒃,𝒊,𝒕𝑩𝑼𝒀

Fores t Layer

Land balances


=




𝑨𝒇,𝒃,𝒕𝑷𝒍𝒂𝒏𝒕𝒆𝒅

𝑏 ∈ 𝑩


Area Available for Plantation

Fores t Layer

Land balances


=




−𝑨𝒇,𝒕𝑭𝑹𝑬𝑬,𝑲𝒆𝒆𝒑

𝑨𝒇,𝒕−1𝑭𝑹𝑬𝑬,𝑲𝒆𝒆𝒑


𝑏 ∈ 𝑩



Fores t Layer

Land balances


=






+ 𝑨𝒇,𝒃,𝒊,𝒕𝑯𝒂𝒓𝒗𝒆𝒔𝒕

𝑖 ∈ 𝐼 𝑖≠0

𝑏 ∈ 𝑩


𝑏 ∈ 𝑩



Fores t Layer

Land balances


=







𝑖 ∈ 𝐼 𝑖≠0

𝑏 ∈ 𝑩


𝑏 ∈ 𝑩

+𝑨𝒇,𝒕𝑭𝑹𝑬𝑬,𝒃𝒖𝒚



Fores t Layer

Land balances


=

𝑨𝒇,𝒃,𝒊=0,𝒕𝑷𝒍𝒂𝒏𝒕𝒆𝒅,𝑲𝑬𝑬𝑷 = 𝑨𝒇,𝒃,𝒕

𝒑𝒍𝒂𝒏𝒕𝒂𝒅𝒂







𝑖 ∈ 𝐼 𝑖≠0

𝑏 ∈ 𝑩


𝑏 ∈ 𝑩




Recent Planted

Fores t Layer

Land balances


=









𝑖 ∈ 𝐼 𝑖≠0

𝑏 ∈ 𝑩


𝑏 ∈ 𝑩




Recent Planted

Land Acquisition Costs taken from

Bacha et al (2016)

Fores t Layer

Land balances


=









𝑖 ∈ 𝐼 𝑖≠0

𝑏 ∈ 𝑩


𝑏 ∈ 𝑩




Recent Planted

Land Acquisition Costs taken from

Bacha et al (2016)

Operational Costs taken from IMEA

(2013)

Fores t Layer

Forest Decisions

Planted Area to be Kept

Time O Years

12+ Years

Fores t Layer

Forest Decisions


Time

Time

Planted Area to be Bought

O Years

12+ Years

Fores t Layer

Forest Decisions


Time

Time


Planted Area to be Harvested

Time

O Years

12+ Years

7 Years

Fores t Layer

Forest Decisions


Time

Time


Planted Area to be Harvested

Free Area to be Planted

Time

Time

O Years

12+ Years

7 Years

6. Opt imizat ion

Criteria

Opt imiza t ion Cr i te r ia

Present Value

100 bi BRL

NPV of 58 bi BRL

Revenue Chemicals

Revenue Electricity Land Acquisition Investments

Non-Forest Logistics Productive Investments

Production Costs

Forest Operation Costs

7. Concluding

Remarks

Concluding Remarks

Forest Operations presents a relevant

Economic Potential and Land Expansion in

Brazil does not seems to be a Limiting Factor

Concluding Remarks




Market Demand and Prices are the most critical

parameters and their Uncertainty need to be

addressed in a proper way

Concluding Remarks







Consideration of a more diverse Bio-based

Products Portfolio can provide alternatives for

building more Robust Solutions to the volatile

prices of Cellulose

Concluding Remarks







Consideration of a more diverse Bio-based

Products Portfolio can provide alternatives for

building more Robust Solutions to the volatile

prices of Cellulose

Environmental Impacts needs to be properly

assessed and considered into the Decision

Framework

Bruno Theozzo [email protected]

[email protected]

[email protected]

Moises Teles dos Santos [email protected]

Thank you!

Extra Slides

References

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Empresa de Pesquisa Energética. (2017). Anuário Estatístico de Energia Elétrica

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http://www.cbicdados.com.br/menu/materiais-de-construcao/cimento

Eichler, P., Toledo, M., Vilares, M., Gomes, F., Lourega, R., Santos, G., . . . Santos, F. (2017). Potential assessment of eucalyptus grown for

biorefinery processes. Agronomy Science and Biotechnology, Volume 3, pp. 1-11.

Francis, D. W., Towers, M. T., & Browne, T. C. (2002). Energy Cost Reduction in the Pulp and Paper Industry. Pulp and Paper technical association of

Canada.

ANTT (2019) – Resolution 5.820/2018, adjusted by Resolution 5.839/2019, available at

http://www.antt.gov.br/cargas/arquivos_old/Tabelas_de_Precos_Minimos_do_Transporte_Rodoviario_de_Cargas.html

ANTAQ (2019) – Statistical Annuary – Available at http://web.antaq.gov.br/Anuario/

Blinkey, D., Campoe, O. C., Alvares, C., Carneiro, R. L., Cegatta, I., & Stape, J. L. (2017). The interactions of climate, spacing and genetics on

clonal Eucalyptus plantations across Brazil and Uruguay. Forest Ecology and Management 405, pp. 271-283

Fibria (2016) - Corporate Presentation – Investors Relations

Bergamini, M. L., Grossmann, I. E., Scenna, N., & Aguirre, P. (2008). An improved piecewise outer-approximation algorithm for the global

optimization of MINLP models involving concave and bilinear terms. Computers and Chemical Engineering 32, pp. 477-493.

References

Kannangara, M. S. (2015). Development and integration of acid precipitation based lignin biorefineries in kraft pulping mills. Montreal:

Université de montréal

Lian, Z. T., Chua, K. J., & Chou, S. K. (2010). A thermoeconomic analysis of biomass energy for trigeneration. Applied Energy 87 , pp. 84–95.

Mao, H. (2002). Technical evaluation of a hardwood biorefinery using the "near-neutral" hemicellulose extraction process.

Lossau, S., Fischer, G., Tramberend, S., van Velthuizen, H., Kleinschimt, B., & Schomächer, R. (2015). Brazil's current and future land balances: Is

there residual land for bioenergy production? Biomass and Bioenergy 81, pp. 452-461.

Sixta, H., Potthast, A., & Kroyscheck, A. W. (2006). Chemical Pulping Process. Em H. Sixta, Handbook of Pulp. Weinheim: WILEY-VCHVerlag

GmbH&Co.

Suzano Papel e Celulose SA. (2018). Teleconferência de Resultados 4T2018.

Tran, H., & Vakkilainnen, E. K. (2008). The kraft chemcial recovery process. Tappi.

Gosselink, R. J. (2011). Lignin as a renewable aromatic resource for the chemical industry.

Huang, C., Ma, J., Zhang, W., Huang, G., & Yong, Q. (2018). Preparation of Lignosulfonates from Biorefinery Lignins by Sulfomethylation and

Their Application as a Water Reducer for Concrete. Polymers 10.

IBÁ. (2015). Anuário de Estatística Florestal.

Storage Layer

Storage & Ports

The Storage Layer is useful for implementing a Minimum Storage

Policy that within this scope will not be considered

Internal Freights are taken from

Minimum Freight Policy from ANTT

(2019)

External Markets can only be reached

through Ports in Storage layer, whose

operations cost are given by ANTAQ

(2019)

Production Facilities and External

markets can not be Connected due to

Cost Parameter for this direct transfer

Market Layer

Pulp Demand

Print & Write

Tissue Paper

Pulp Demand estimated through Installed Capacity of

Main Producers in Brazil for P&W and Tissue paper

accordingly to ABTCP (2017) and Prices are taken from

Suzano Investors Report (2018)

Market Layer

Electricity Demand

Electricity Demand are taken from Statistical

Annuary by EPE (2017) considering 2.9% of

Substitution which corresponds to the Energy

Generated by Coal and Prices are taken as the

Historical Mean accordingly to the same

report.

Coal-based Electricity

Market Layer

Lignin Demand

Lignin Demand will be represented by Cement Capacities in Brazil reported

by SNIC (2018) considering a 0.2% of addition reported by Huang et al

(2018) and Price of 1800 BRL/ton [1] accordingly to Gosselink (2011)

Lignin as Cement Additive

Fores t Layer

Land Availability Estado

Área Total [kha]

Área Total [%]

Residual I [kha]

Residual I [%]

Residual II [kha]

Residual II [%]

Residual III [kha]

Residual III [%]

Minas Gerais 58,931 6.9% 19,629 22.9% 12,547 30.0% 12,547 33% Bahia 56,683 6.6% 9,003 10.5% 4,271 10.2% 4,271 11% Goias 34,185 4.0% 6,637 7.8% 3,482 8.3% 3,482 9% São Paulo 24,909 2.9% 4,426 5.2% 3,305 7.9% 3,305 9% Tocantins 27,931 3.3% 7,359 8.6% 2,775 6.6% 2,550 7% Maranhão 32,977 3.9% 4,823 5.6% 2,284 5.5% 1,879 5% Mato Grosso 90,853 10.7% 5,064 5.9% 2,362 5.6% 1,835 5% Mato Grosso do Sul 35,859 4.2% 2,347 2.7% 1,427 3.4% 1,427 4% Paraná 19,932 2.3% 1,692 2.0% 1,306 3.1% 1,306 3% Piauí 25,318 3.0% 3,380 3.9% 1,138 2.7% 1,138 3% Rio Grande do Sul 26,896 3.2% 2,080 2.4% 1,112 2.7% 1,112 3% Espírito Santo 4,623 0.5% 1,248 1.5% 794 1.9% 794 2% Rio de Janeiro 4,374 0.5% 1,410 1.6% 779 1.9% 779 2% Santa Catarina 9,523 1.1% 924 1.1% 576 1.4% 576 2% Pernambuco 9,872 1.2% 472 0.6% 236 0.6% 236 1% Ceará 14,984 1.8% 293 0.3% 176 0.4% 176 0% Paraíba 5,682 0.7% 236 0.3% 173 0.4% 173 0% Rio Grande do Norte 5,311 0.6% 230 0.3% 128 0.3% 128 0% Sergipe 2,197 0.3% 101 0.1% 46 0.1% 46 0% Alagoas 2,791 0.3% 49 0.1% 27 0.1% 27 0% Distrito Federal 582 0.1% 221 0.3% 12 0.0% 12 0% Rondônia 23,893 2.8% 681 0.8% 362 0.9% 0 0% Acre 16,512 1.9% 43 0.1% 39 0.1% 0 0% Amazonas 156,935 18.4% 2,315 2.7% 388 0.9% 0 0% Roraima 22,574 2.6% 4,270 5.0% 167 0.4% 0 0% Pará 124,289 14.6% 5,677 6.6% 1,880 4.5% 0 0% Amapá 14,099 1.7% 997 1.2% 49 0.1% 0 0% Total 852,715 85,607 41,841 37,799

Product ion Layer


Sixta (2006)

ABTCP (2011)

Mao (2012)

Kannangara (2015)

Tran & Vakkilainnnen (2008)

Francis et al (2002)

Lin et al (2010)

Eichler et al (2017)

Conversion Data taken from:

Chemical Utilities Costs taken from Brazilian Federal Tax Agency Import Data

Other Operation Costs taken from Suzano Investors Report (2018)

Fores t Layer

Biomass Parameters

The best performer for Tropical Brazil (E. Urohyplla)

and Subtropical Brazil (E. Camadulensis x E. Grandis)

clones on study from Blinkey et al (2017) were choosen.

Biomass Species

Paraná, Santa Catarina and Rio Grande do Sul were taken as fully

populated by E. Camadulensis x E. Grandis and the Rest of Brazil

with E. Urophylla

E. Camadulensis x E. Grandis

E. Urophylla

Fores t Layer

Age Distribution

All Forest Units were taken as having its planted area age with a

Normal Distribution with Mean Value of 5 years and Standard

Deviation of 2 years.

Maximmum Age above which

all properties are taken as constant

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