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

(PLA)

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)

Pric

e (P

)

Q(eq) Q(biom)

Demand

Demand (biom)

Supply

P(biom)P(eq)

Quantity (Q)

Pric

e (P

)

Demand

Q(eq)

P(eq)

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

GH

G e

mis

sion

redu

ctio

n [M

g C

O2e

q/(h

a*yr

)]

0

5

10

15

20PLA production

from SR woodPLA production from wheat

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

rall

cost

s of

bio

-ref

iner

y sy

stem

[k

Euro

/(ha*

yr)]

-2

0

2

4

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

GH

G e

mis

sion

s an

d G

HG

em

issi

on re

duct

ions

[M

g C

O2e

q/M

g bi

omas

s in

put]

-4

-2

0

2

4

6

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

osts

and

reve

nues

[k

Euro

/Mg

biom

ass

inpu

t]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

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

GH

Gm

itigation costs [Euro/M

gCO

2eq]

-400

-200

0

200

400

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

Biom

ass

supp

ly c

osts

(Eu

ro/M

g dry)

0

20

40

60

80

100

120

Biomass supply II

Biomass supply I

GHG emission mitigation supply curves

GHG emission reduction (Mg CO2eq )

0 20x106 40x106 60x106 80x106 100x106

Mar

gina

l GH

G e

mis

sion

mit

igat

ion

cost

s (

Euro

/Mg

CO2e

q)

-300

-200

-100

0

100

200

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

argi

nal G

HG

em

issi

on m

itig

atio

n co

sts

( Eu

ro/M

g CO

2eq)

-100

0

100

200

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).

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