Lifecycle Analyses of GHG Impacts of Biofuels for Transport

Eric D. Larson

Princeton Environmental Institute

Princeton University, Princeton, NJ USA

Presented at

Energy Week, The World Bank

7 March 2006

Washington, DC

Based on E.D. Larson, “A Review of LCA Studies on Liquid Biofuel Systems for the Transport Sector,” manuscript submitted to Energy for Sustainable Development, October 2005, based on presentation to the Workshop on Biofuels for the Transport Sector, organized by the Science and Technology Advisory Panel of the Global Environment Facility, 29 Aug – 1 Sep 2005, New Delhi, India.

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Content of this talk

• Striking features of different LCA results.

• Key variables/uncertainties in LCA results.

• GHG impacts of biomass use for transportation vs. stationary applications

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Striking features of LCA studies reviewed• Wide range of biofuels have been included in different LCAs:

– Biodiesel (fatty acid methyl ester, FAME, or fatty acid ethyl ester, FAEE)• rapeseed (RME), soybeans (SME), sunflowers, coconuts, recycled cooking oil

– Pure plant oil • rapeseed

– Bioethanol (E100, E85, E10, ETBE)• grains or seeds: corn, wheat, potato• sugar crops: sugar beets, sugarcane• lignocellulosic biomass: wheat straw, switchgrass, short rotation woody crops

– Fischer-Tropsch diesel and Dimethyl ether (DME)• lignocellulosic waste wood, short-rotation woody crops (poplar, willow), switchgrass

• LCAs are almost universally set in European or North American context (crops, soil types, agronomic practices, etc.). One prominent exception is an excellent Brazil sugarcane ethanol LCA.

• Extremely wide range reported for LCA results for GHG mitigation– Across different biofuels – Across different LCA studies for same biofuel

• Lack of focus on evaluating per-hectare GHG impacts.– Most analyses report GHG savings per GJ biofuel. – Some report GHG savings per-vkm. – Few focus on understanding what approaches maximize land-use efficiency for GHG mitigation

• All studies are relatively narrow engineering analyses that assume one set of activities replaces another.

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Delucchi’s Suggested Expanded LCA

IssueConventional Approach

Expanded Approach

Aim of LCA

Evaluate impacts of replacing one limited set of “engineering” activities with another.

Evaluate worldwide impacts of one realistic action compared to another.

Scope of LCA

Narrowly defined chain of material production and use activities.

All major production and consumption activities globally.

Method of LCA

Simplified input/output representation of technology.

Input/output representation of technology with dynamic price linkages between all sectors of economy.

I NCLUDED I N CONVENTIONAL LCA?

Generally not – conventional LCAdoes not perform policy analysis,but simply assumes that one set ofactivities replaces another

In most transportation LCAs, fuellifecycle is well represented (~90%),but materials lifecycle,infrastructure, and land-use oftenare not

Not in most LCAs. If included,results might change significantly(more than 10%), especially whencomparing dissimilar alternatives

Generally, 80-90% of the relevantemission sources are covered, butsome omissions are serious

Relationship between emissionsand state of environment treatedvery crudely (e.g., via CEFs, someof which have serious limitations)

REALITY (I DEAL)

PRODUCTION &CONSUMPTION OFENERGY &MATERIALS, LANDUSE

ENVIRONMENTALSYSTEMS

POLICY ACTION

PRICES

EMISSIONS

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Wide range in LCA results (1)

63% GHG savings per v-km

16% GHG savings per v-km

Concawe, et al., 2004.

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Wide range in LCA results (2)

-300 -250 -200 -150 -100 -50 0 50

EtOH sugar cane *

EtOH lignocellulose *

EtOH sugar beets *

EtOH Molasse *

EtOH wheat *

EtOH corn *

EtOH potatoes *

ETBE lignocellulose *

ETBE sugar beets *

ETBE wheat *

ETBE potatoes *

Biodiesel sunflowers

Biodiesel rapeseed

Biodiesel animal grease

Biodiesel canola

Biodiesel soy beans

Biodiesel coconuts

Biodiesel cooking grease and oil

Vegetable oil rapeseed

Vegetable oil sunflowers

Biomethanol lignocellulose *

MTBE lignocellulose *

DME lignocellulose

BTL lignocellulose

Biogas cultivated biomass

Biogas wastes

GH2 gasified lignocellulose

GH2 fermentation wastes

LH2 gasified lignocellulose

MJ saved PE / km

-3 -2,5 -2 -1,5 -1 -0,5 0 0,5

g saved CO2-equiv. / km

?

?

?

?

?

?

Greenhouse effect

Primary energy

****

Quirin, et al., 2004.

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Key Variables in LCA Studies

• Allocation of co-product credits

• Nitrous oxide (N2O) emissions

• Soil carbon sequestration

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Different co-product allocation methods have different pros and cons

• No allocation.• Allocation by co-product weight.• Allocation by co-product energy content.• Allocation by share of process energy consumed to

make co-product.• Allocation by co-product market value.• Allocation by energy displaced by substituting co-product

for conventional (fossil-fuel derived) product.

• Choice of allocation method depends on context – no intrinsically right method.

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Different allocation methods can give widely varying results

Percent savings in lifecycle GHG emissions for corn ethanol production using different co-product allocation methods:

Wang et al. 2005.

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N2O can be large contributor to total GHG emissions due to high GWP (~300xCO2)

Biofuel

GHG Emissions (kg CO2equiv/GJ)

CO2 CH4 N2O Total

Rape Methyl Ester 25 0.69 15 40.7

Sugarbeet Ethanol 34 0.32 5.6 39.9

Wheat Ethanol 24 0.69 3.7 28.4

Wheat straw Ethanol 0 - 0.59 13.3 12.7

Pure Rapeseed Oil 15 0.49 14.3 29.8

Mid-range of values reported by Elsayed et al., 2003.

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GM, et al. 2002 (European study).

Direct N2O from annual crops, Germany N2O from short-rotation willow, NE USA

Heller, et al. 2003.

N2O emissions depend on type of crop (e.g., annual vs. perennial), agronomic practices, climate, and soil type.

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Soil carbon storage depends on soil type and prior land use

McLaughlin, et al, 2002.

• Soil carbon will eventually saturate.

• Re-release possible.• Most LCA studies

assume no soil carbon contribution (+ or -) to GHG emissions.

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Most studies focus on GHG emissions per GJ biofuel or per v-km. Emissions per ha/yr may give different ranking.

Elsayed, et al. 2003.

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However, little disagreement that grain biofuels give less energy services (and more GHG emissions) per ha/yr than lignocellulosic crops – due primarily to lower effective yield per ha.

IPCC, 1996.

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Biomass yield is a key parameter – depends on crop, agronomic practices, soil type, topography, climate...

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GJ/ha/yr

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dry t/ha/yr

Wood, commercial forest USA, low estimate

Wood, commercial forest USA, high estimate

Above-ground maize USA (grain+stover), avg 1985-87

Alamo Switchgrass Texas USA, avg 5 exp. plots, 1993-94

Eucalyptus Aracruz Brazil, 80000 ha avg, 1986-91

Above-ground sugarcane biomass world avg, 1987

Eucalypt Aracruz, max commercial stand, 1986-91

Alamo Switchgrass Alabama USA, avg exp plots, yr 2-6

Above-ground maize Iowa USA (grain+stover), record 1994

Above-ground sugarcane Zambia, 10k ha

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GJ/ha/yr

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dry t/ha/yr

Wood, commercial forest USA, low estimate

Wood, commercial forest USA, high estimate

Above-ground maize USA (grain+stover), avg 1985-87

Alamo Switchgrass Texas USA, avg 5 exp. plots, 1993-94

Eucalyptus Aracruz Brazil, 80000 ha avg, 1986-91

Above-ground sugarcane biomass world avg, 1987

Eucalypt Aracruz, max commercial stand, 1986-91

Alamo Switchgrass Alabama USA, avg exp plots, yr 2-6

Above-ground maize Iowa USA (grain+stover), record 1994

Above-ground sugarcane Zambia, 10k ha

IPCC, 1996.

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Potential for higher yields with lower inputs for lignocellulosic crops offer larger future GHG mitigation potential than grains/sugars

GHG Emission Reductions with Bioethanol

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Biomass yield, metric t/ha/yr

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Corn ethanol, 2005

Woody & herbaceous cellulosic ethanol, 2005/2010

Herbaceous cellulosic ethanol, 2025

Herbaceous cellulosic ethanol, 2050

Brazil sugarcane, best practice 2002 (68.7 t/ha/yr of raw cane stalks)

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GHG mitigation for bio-electricity vs. biofuel depends primarily on:

• What biofuel is being produced.

• How the biofuel is being made (conversion technology).

• Fossil fuel systems being displaced.

CONCAWE et al. 2004.

Lower biomass yields; Otto-cycle engine.

Higher biomass yields (10 t/ha/yr); Diesel-cycle engine.

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Wrap up• Broad range of LCA results for GHG mitigation for any

given biofuel due to different input assumptions (corresponding to different actual practices) and methods.

• But, some broad conclusions are possible– Grain-based biofuels offer less GHG mitigation than lignocellulosic-based fuels

due primarily to lower effective yields.– Among commercial biofuels today, sugarcane ethanol gives highest land use

efficiency for GHG mitigation.

– In longer term, land use efficiency for GHG mitigation is likely to be highest for lignocellulosic plantation biomass (FT or DME in 2010/2015 timeframe, ethanol in 2020/2030 time frame)

• Biomass for biofuels vs. biomass for electricity– Less GHG mitigation per hectare if biomass is used to make biofuels than if it is

used to make electricity displacing coal power. (This is true with existing steam cycle biopower technology and more true with future bio-IGCC.)

– If bio-electricity is displacing NGCC electricity or electricity from any fossil-fuel combined heat and power, then biofuels (from sugarcane or from lignocellulosic crops) may give greater GHG mitigation per hectare.

– Cost of GHG mitigation ($/tCavoided) for stationary versus transport applications has not been examined, but likely would be lower for higher GHG mitigation options.

extra slides

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Ethanol and FT fuels from lignocellulosic biomass in USA (with foreseeable RD&D advances in switchgrass production and conversion). (US corn EtOH and Brazil sugarcane EtOH also shown.)

Electricity from conventional biomass steam cycle (25% swg to electricity HHV).

Avoided GHG emissions for biofuels vs. conventional bio-electricity

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Biomass yield, dry metric t/ha/yr

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PCwFGD

Ultra SC coal

PFBCcoal

IGCC coal

Coal cogen

NGCC

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Herbaceous cellulosic ethanol, 2005/2010

Herbaceous cellulosic ethanol, 2025

Herbaceous cellulosic ethanol, 2050

Herbaceous cellulosic F-T, 2050

Herbaceous cellulosic FT, 2015

HHV efficiency

~ 43%

~ 36%

~ 54%~ 76% FCP

Brazil sugarcane, best practice 2002

Corn ethanol, 2005

Biomass steam cycle, 25% efficiency

Biofuels

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Potential to increase yields of lignocellulosic crops is substantial (unlike potential for grains/sugar yields)

Current and Projected Switchgrass Yields in the USA

2004 Breeding gains Projected Yields (dt/ha/yr)

Region dry t/ha/yr dt/ha/yr 2025 2050

Northeast 10.9 0.164 14.4 18.5

Appalachia 13.1 0.655 26.9 43.3

Corn Belt 13.4 0.402 21.9 31.9

Lake States 10.8 0.162 14.2 18.2

Southeast 12.3 0.617 25.3 40.7

Southern Plains 9.7 0.483 19.8 31.9

Northern Plains 7.79 0.117 10.2 13.2

Average 11.1 19.0 28.2Greene, 2004.

Historical corn yields in USA

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Ethanol and FT fuels from lignocellulosic biomass in USA (with foreseeable RD&D advances in switchgrass production and conversion). (US corn EtOH and Brazil sugarcane EtOH also shown.)

Electricity from biomass-IGCC with foreseeable RD&D advances (by ~2015) in switchgrass production and conversion (45% swg to electricity HHV).

Avoided GHG emissions for biofuels vs. IGCC bio-electricity

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Biomass yield, dry metric t/ha/yr

Net

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PCwFGD

Ultra SC coal

PFBCcoal

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Herbaceous cellulosic ethanol, 2005/2010

Herbaceous cellulosic ethanol, 2025

Herbaceous cellulosic ethanol, 2050

Herbaceous cellulosic F-T, 2050

Herbaceous cellulosic FT, 2015

HHV efficiency

~ 43%

~ 36%

~ 54%~ 76% FCP

Brazil sugarcane, best practice 2002

Corn ethanol, 2005

Biomass IGCC, 45% efficiency

Biofuels

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Grains produce unused residues, which if used for process energy (e.g., as with sugarcane ethanol), would improve GHG performance (but not vkm/ha)..Table 2.1. Residue ratios for first estimates of crop-residue availability.

Crop Residue Residue

ratioa

Residue energy

(MJ/dry kg)b Typical current residue usesc

Barleyd straw 2.3 17.0 Coconut shell 0.1 kg/nut 20.56 household fuel Coconut fibre 0.2 kg/nut 19.24 mattress making, carpets, etc. Coconut pith 0.2 kg/nut Cotton stalks 3.0 18.26 household fuel Cotton gin waste 0.1 16.42 fuel in small industry Groundnut shells 0.3 fuel in industry Groundnut haulms 2.0 household fuel Maize cobs 0.3 18.77 cattle feed Maize stalks 1.5 17.65 cattle feed, household fuel Millet straw 1.2 household fuel Mustard seed stalks 1.8 household fuel Other seeds straws 2.0 household fuel Pulses straws 1.3 household fuel Rapeseed stalks 1.8 household fuel Rice straw 1.5 16.28 cattle feed, roof thatching, field burned Rice husk 0.25 16.14 fuel in small industry, ash used for cement production Soybeanse stalks 1.5 15.91 Sugarcane bagasse 0.15 17.33 fuel at sugar factories, feedstock for paper production Sugarcane tops/leaves 0.15 cattle feed, field burned Tobacco stalks 5.0 heat supply for tobacco processing, household fuel Tuberse straw 0.5 14.24 Wheat straw 1.5 17.51 cattle feed Wood productsf waste wood 0.5 20.0 (a) Unless otherwise noted, the residue ratio is expressed as kilograms of dry residue per kg of crop produced, where the crop

production is given in conventional units, e.g. kg of rice grain or kg of clean fresh sugarcane stalks. The ratios given here are illustrative only: for a given residue, the residue ratio will vary with the agricultural practice (species selected, cultivation practices, etc.). Unless otherwise noted, the ratios given here are from Biomass Power Division (1998).

(b) Unless otherwise noted, these are higher heating values as reported by Jenkins (1989). The lower heating values are about 5% lower. The higher and lower heating values differ by the latent heat of evaporation of water formed during complete combustion of the residue.

(c) The use to which residues are put varies greatly from one region of a country to another and from country to country. The uses listed here are illustrative only. They are typical uses in parts of India.

(d) Source: Taylor, et al. (1982). (e) Estimate for China as given by Li, Bai, and Overend [1998]. Tubers includes crops such as cassava, yams, and potatoes. (f) Wood products refers to lumber or finished wood products such as furniture. The residue ratio is given as a broad average

by Hall, et al. (1993). The ratio will vary considerably depending on the specific product.