Greenhouse Gas Emission Reduction by Multi-Product and...

Copernicus InstituteResearch Institute for Sustainable Development and Innovation

Greenhouse Gas Emission Reduction by Multi-Product and Cascading Systems

IEA Bioenergy Task 38 meeting15th September 2004, Victoria

Veronika Dornburg

Rationale

Biomass for GHG emission reduction atlow costs and high efficiency of land use

multi-functional use of biomass resources:•Multi-product use, e.g. Bio-refinery•Cascading

Multi-functional biomass systems

→ Electricity→ Heat → Fuels

Energy use Material use

→ Construction → Food/fodder → Chemicals → Pulp and paper → Other

Both uses from one crop:multi-product use

Land use Production of biomass

→ Wood (short/long term rotation) → Perennial herbaceous crops (e.g. miscanthus) → Other crops (oilseed, sugar, starch)

Other (multi-functional land uses

Waste-to-energy

+ Recycling:

cascading

What is the potential of multi-functional biomass systems to improve the costs and the land use efficiency of saving non-renewable energy consumption and reducing GHG emissions in quantitative terms?

Key factors:1. the set-up and composition of the biomass system, i.e.

by-product use, recycling rates, efficiency of production etc..

2. the markets in which the bio-refinery system is embedded, e.g.. markets for products and agricultural land

Case studies presented:

1. Poly lactic acid (PLA) bio-refinery systems (including multi-product use and cascading)

2. GHG emission mitigation supply curves (comparing energy and material uses of biomass)

I: Biomass productionBiomass

production (wheat or SRC)

agricultural residues (straw )

main component (grain or wood)

transport transport

II: Bioenergy production III: PLA production

Bio-energy generation

(combustion)

by-products (lignin)

Material production

heat and electricity

main product (PLA)

by-products (gyspum,fodder )

V: PLA recycling IV: End product uselactic acid

(LA)End product production

Back-to-monmer

industrial PLA waste

end products: packaging and synthetic fibres

VI: Waste treatment

waste treatment (incineration)

End product use and substitution

electricity waste treatment

(digestion) transport

Biomass: wheat or SR woodBioenergy: heat and electricity By-products: fodder, gypsumProducts: PLA packaging or fibers Substitution: reference applicationsBTM recyclingWaste treatment: incineration or digestion

Case1:

Multi-functionalPLA bio-refinerysystem in Poland

Approach

combination bottom-up analysis and an analysis of elastic markets

amount of agricultural land neededamount of products and by-products produced

Bio-refinery system: Land and commidity markets:

CHAIN ANALYSIS

mass flows production costs

market prices of land and products

savings of non-renewable consumptionsMARKET ANALYSIS

GHG emission reductionsland use costs of biorefinery

costs with elastic markets

Chain analysis

• Performance of every part of biomass system calculated

• Products, by-products and electricity substitute reference products

• Different system configurations compared, e.g. intense agriculture, no recycling

Parameters•Costs, •Savings of non-renewable energy consumption •GHG emission reduction => per kg PLA and per ha biomass production

Market analysis (1)

Quantity (Q)

Q(eq) Q(biom)

Demand

Demand (biom)

Supply

P(biom)P(eq)

Quantity (Q)

Demand

Supply

Q(scale)

P(scale)

demand for land demand for products

Market analysis (2)

• Price of products and land depend on demand curves

• P(Q) = C*Q1/e

P: price per unit, Q: quantity, e: own-price elasticity

• literature estimates of elasticity based on empirical data and economic models

• C depends on empirical market, i.e. actual sold quantity and market price

Results of chain analysis

1 3 5 7 9 112 4 6 8 10 12

20PLA production

from SR woodPLA production from wheat

1 3 5 7 9 112 4 6 8 10 12Ove

6PLA production

from SR woodPLA production from wheat

1 2 3 4 5 6 7 8 9 10 11 12Wheat SR woodBase case

Intense crop

Non-int. crop

prod. Fibre

Recyc-ling

Incine-ration

Base case

Intense crop

Non-int. crop

prod. Fibre

Recyc-ling

Incine-ration

Break-down of chain analysis

1 3 5 7 9 110 2 4 6 8 10 12

1 3 5 7 9 110 2 4 6 8 10 12C

c ro p p ro d u c tio ntra n s p o rt b io -e n e rg y P L A p ro d u c tio n s u b s t.b y -p ro d s u b s titu t io n p e tro c h e m . p o lym e r re c yc lin g w a s te tre a tm e n t

Results of market analysis

range due to range of own-price elasticity (-0.2 to -2.5)range due to historical range of market prices of petrochemical polymersmitigation costs of bio-refinery system calculated with demand curve of PLA (elasticity -0.5)mitigation costs of bio-refinery system calculated with market prices of petrochemical polymers

Scale of PLA production from SR wood(thousand Mg biomass/yr)

200 400 600 800

itigation costs [Euro/M

scale base case

Case 2: GHG mitigation supply curves

Method• Bottom-up (chain) analysis of bio-material and

bioenergy applications Scenario-dependent biomass cost supply curves

• Estimations of market prices of land, bio-materials and bio-energy carriers depending on the scale of biomass use and the market volume of materials and energy carriers

• Current demand of energy carriers can be replaced without increase of prices, afterwards prices increase

Selected Technologies

Criteria• potentially large market volume in the year 2015• reduces a large amount of GHG emissions per unitof biomass used

•rather low initial GHG emission mitigation costs.

Two material and two energy uses (incl. use of residues and waste-to-energy recovery)•PLA•MDF Board•Methanol as transportation fuel•Electricity

Biomass and GHG emission mitigation supply curves for Poland

Col 1 vs Col 2 Col 1 vs Col 3

Amount of biomass production (PJHHV)

Amount of biomass production (Mgdry)

0 20x106 40x106 60x106 80x106 100x106 120x106

Biomass supply curves

g dry)

Biomass supply II

Biomass supply I

GHG emission mitigation supply curves

GHG emission reduction (Mg CO2eq )

0 20x106 40x106 60x106 80x106 100x106

300MDF board

Methanol

Electricity

1000 1500 2000500

Example: V1 Scenario (A1)

'Integral' GHG emission mitigation cost supply curves for the different scenarios

Amount of biomass (Mgdry biomass)

0 20x106 40x106 60x106 80x106 100x106 120x106

Amount of biomass (PJHHV)M

ScenarioV1

ScenarioV4

ScenarioV3

1000 1500 2000500

total supplyV1

total supplyV4

total supplyV3

total supplyV2

ScenarioV2

Conclusions (1)PLA bio-refinery

• Bio-energy use of residues most important multi-functional use

• Net savings of non-renew. energy up to 220 GJ/(ha*yr), 30-60% from multi-functional use

• Net GHG em. reduction of up to 17 Mg CO2eq/(ha*yr),20-60% from multi-functional use

• Most systems lead to net costs, but profits up to 1100 €/(ha*yr), 5-20 % of the revenues from multi-functional use

• Own-price elasticity of material markets crucial for the economic performance of PLA bio-refinery systems

• Decrease of costs of PLA bio-refinery systems due to economies of scale is marginal at large scales if calculated with own-price elasticity

Conclusions (2)

GHG emission mitigation supply curves

• GHG emission mitigation costs from biomass increase considerable with the scale of biomass utilisation

• Biomass supply costs increase between 20-100 €/Mg, while the increase of agricultural land rents adds up to 50 to 100 €/Mg to biomass production costs at large scales.

• Bio-material production covers only a small part of GHG emission mitigation at low costs due to relatively small material markets. Instead bio-energy production is applied for GHG emission mitigation.

• Both supply and demand of materials and energy carriers should be analysed jointly to quantify the amounts that realistically can be used in a country/region.

Conclusions (3)

Overall biomass utilisation strategies

• To use biomass efficiently in terms of GHG emission reduction, (agricultural) land use and total costs of the system, multi-functional biomass systems can be an attractive option if carefully designed, depending on reference systems and land, material and energy markets.

• For the performance of biomass systems at a large scale of biomass use, the interactions of biomass use with land, material and energy markets need to be better understood.

• Further research on optimal biomass systems for GHG emission mitigation should combine bottom-up information of biomass system with knowledge on market mechanisms from top-down analyses.

Finally,

I would like to thank my colleagues:Jinke van Dam, André Faaij and Martin Patel.

The presented case studies (and other studies on multi-functional biomass system) can be found in:

V.Dornburg: Multi-functional biomass systems, PhD-thesis, Utrecht University (forthcoming).

Greenhouse Gas Emission Reduction by Multi-Product and...

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