bioenergy and biomaterials: biofuels Niels Jungbluth, ESU-services Ltd.,

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1 2 nd International ecoinvent Meeting Lausanne, March 14, 2008 bioenergy and biomaterials: biofuels Niels Jungbluth, ES-services Ltd., 2

2 Topics Goal and scope of the project Life cycle inventories of bioenergy Allocation methodology Specific regional problems Soy beans Plant oils Sugar cane Results of LCIA study Conclusions for inventories of biofuels 3 Problem setting Ökobilanz von Energieprodukten Diverging results for bioenergy and biofuels in separate studies ecoinvent data v1.3 covered only a small part of bioenergy chains. No common database Aims to fully cover the most important bioenergy chains Main issue biofuels in Switzerland or imported Support for energy policy (fuel tax reductions) Examination for GHG reduction potential Investigation of several environmental aspects of biofuels supply chains 4

3 Participating organisations Project leader: Niels Jungbluth, ES-services Ltd. Financing: Swiss for Energy (BFE), Agriculture (BLW) and Environment, Forests and Landscape (SAEFL) Erdöl-Vereinigung, Zurich; Alcosuisse, Berne; Entsorgung und Recycling Zürich Inventory experts: Carbotech AG, Basel Chudacoff Oekoscience, Zürich Doka Ökobilanzen ENERS Energy Concept, Lausanne INFRAS, Bern Swiss Federal Institute of Technology Zürich (ETHZ) ecoinvent manager: Rolf Frischknecht, ecoinvent Centre 5 Goal and Scope Time frame 2005 or new future technologies Investigation from well to Swiss wheel (cradle-to-grave) Products from multi-output processes are investigated with allocation factors that can be varied by the data user All direct co-products are included in the analysis Consistent investigation of energy, food, fodder and material products from biomass Clear differentiation of fossil and organic carbon Publication with ecoinvent data v2.0 late 2007 ( 6

4 Possible classifications of fuels Chemical classification of energy carrier methane, ethanol, methanol, hydrogen, oils, methyl ester, liquids (petrol, diesel), ETBE, MTBE Resources used Non-renewable: crude oil, natural gas, coal, nuclear Renewable: energy crops (edible, non-edible), algae, forest wood, biomass residues, sun, wind Type of conversion process mechanical, chemical reaction, thermal treatment, fermentation, anaerobic digestion, gasification, Fischer-Tropsch synthesis, biotechnical Marketing: Sunfuel, Sundiesel, Ökodiesel, Biodiesel, Naturgas, 1 st, 2 nd, 3 rd generation 7 Resources, conversion techniques and bioenergy products investigated biomass ressources (crops, wood, residues) wood pellets wood chips biogas plant oils ethanol synthetic gas hydrogen fatty acid methyl ester BTL-fuels methanol combined heat and power plant filling station 8 heating electricity transport devices

5 Data contributions Eners / LASEN ES-services Synthetic fuels Plant oils Methyl ethers (XME) Ethanol Carbotech Project organisation Methodology Clear cutting Gas upgrading and distribution Validation Infras Data base v1.3 Agriculture Biogas PSI Transports Transports ETH Doka Waste management 9 Chudacoff Chemicals Biogas Chemicals Agriculture Ethanol Harmonization of data collection Clear definition of product properties Guidelines for allocation Standard assumptions for prices in allocation Standard distances for biomass transports Standard data for regional storage Carbon balance for biogenic fuels has been corrected in allocation according to product properties 10

6 Investigated biofuels 11 Methanol waste wood Industrial wood Ethanol 99.7% wood grass potatoes sugar beets whey sugar cane BR maize rye DE / RER XME Waste cooking oil Rape seed CH/RER soya oil S / BR palm oil MY Methane 96% agriculture biowaste sludge whey grass wood Structuring of life cycles stages Mix of different inputs, e.g. Rape seeds IP and organic used in oil pressing Different biogas processes used as input to grid Mix of different ethanol pathways used as filling for car Modelling of average cases Data can be easily disaggregated if singe pathways are of interest Change of market situation must be considered in each study using the data 12

7 Transport services investigated in this project Passenger cars Compressed natural gas Methane 96% Ethanol 5% Methanol 100% Plant oil methyl ester 5% ETBE 15% ERO 3, 4, 5 for petrol and diesel Trucks Rape seed methyl ester 100% 13 Allocation Multi-output processes are stored in the database BEFORE allocation Input- and output-specific allocation factors, i.e. individual allocation factor allowed per pollutant and input Allocation executed after import of dataset into database -> calculation of allocated unit processes -> matrix becomes invertible NO system expansion, NO credits All products included: fuel, electricity, heat, material, fertilizer, waste management, fodder, food, etc. Cut-off applied for outputs without economic value and wastes for recycling 14

8 Allocation: Example Biogas organic waste, to biogas plant (1 kg) biogas plant biogas (0.1 Nm3) use, digested matter (0.71 kg) disposal, organic waste (1 kg) 15 cleaning, filling station agriculture Raw data biogas Name disposal, digested biowaste, to biogas, from biowaste, Swiss to Centre matter, anaerobic biowaste, at anaerobic For Life application Cycle in digestion storage digestion agriculture Location 0 0 CH CH CH CH InfrastructureProcess nit 0 0 kg Nm3 kg kg biogas, from biowaste, at storage CH Nm3 1.00E disposal, biowaste, to anaerobic digestion CH kg 1.00E digested matter, application in agriculture CH kg 7.12E heat, natural gas, at boiler condensing modulating >100kW RER MJ 5.94E electricity, low voltage, at grid CH kwh 4.00E disposal, municipal solid waste, 22.9% water, to municipal incineration CH kg 1.00E diesel, burned in building machine GLO MJ 1.80E transport, lorry 16t CH tkm 1.50E solid manure loading and spreading, by hydraulic loader and spreader CH kg 1.00E Carbon dioxide, in air - kg 5.95E Location Carbon dioxide, biogenic - kg 7.05E Methane, biogenic - kg 8.53E nit

9 Soybean production and land transformation 17 Soybean (ecological scarcity 2006) 9'000 8'000 Metolachlor Copper ecological scarcity 2006 points per kg 18 7'000 6'000 5'000 4'000 3'000 2'000 1' '000 Fires during clear cutting soybeans BR soybeans S Soy beans, integrated production, CH Important differences in environmental profile Soy beans organic, CH 2,4-D Phosphorus Phosphate Nitrate Particulates, < 2.5 um Dinitrogen monoxide Benzene Occupation, arable, nonirrigated Remaining substances

10 Plant oil production kg CO2-eq per kg oil at plant 0 19 rape oil CH rape oil RER palm oil MY palm kernel oil soybean oil BR soybean oil S Soya oil RER MY fossil, fossil, non-co2 non-co2 CH4, biogenicch4, biogenic CO2 CO2, land CO2trans Production of sugar cane agriculture Harvest manual/ machinery Sugar /Ethanol production 20

11 Sugar production 7.00E E E-07 DALY/kg 4.00E E E E E+00 sugar, from sugar beet CH sugar, from sugarcane BR 21 Remaining substances Nitrogen oxides Ammonia Sulfur dioxide Particulates, > 2.5 um, and < 10um Particulates, < 2.5 um Respiratory effects, inorganic,eco-indicator 99, (H,A) due to burning of residues Sugar production 100% 90% 80% 70% DALY/kg 60% 50% 40% 30% 20% 10% 0% sugar, from sugar beet, at sugar refinery/kg/ch sugar, from sugarcane, at sugar refinery/kg/br Remaining substances kg C2H4 Toluene Air kg C2H4 Ethene Air kg C2H4 Hexane Air kg C2H4 Propane Air kg C2H4 Ethane Air kg C2H4 Butane Air kg C2H4 Pentane Air kg C2H4 Carbon monoxide, biogenic Air kg C2H4 Methane, fossil Air kg C2H4 Carbon monoxide, fossil Air kg C2H4 Sulfur dioxide Air kg C2H4 22 Respiratory effects, organic, Eco-indicator 99, (H,A) due to burning of residues

12 Fossil Methane Alcohol Biodiesel 100% Rape ME CH 100% Rape ME RER 100% Palmoil M E M Y 100% Soy ME S 100% Soy ME BR 100% Recycled plant oil ME CH 100% Recycled plant oil ME FR Methanol fixed bed CH Methanol fluidized bed CH Ethanol grass CH Ethanol potatoes CH Ethanol sugar beets CH Ethanol whey CH Ethanol wood CH Ethanol sweet sorghum CN Ethanol rye RER Ethanol corn S Ethanol sugar cane BR Methane grass biorefinery Methane manure Methane manure+cosubstrate Methane manure, optimized Methane manure+cosubstrate, optimized Methane biowaste Methane sewage sludge Methane wood Diesel, low sulphur ERO3 Petrol, low sulphur ERO3 Natural gas, ERO3 Zah et al., Infrastructure Cultivation Production Transport Operation CO2-eq. [kg/pkm] GWP-Reduction of Biofuels Conclusions: 13 of 26 investigated biofuels ETH domain and reduce Swiss the GWP significant (>50%) 5 of them are from waste Worst biofuel: Brazilian soya oil with more GWP than fossil reference (transformation of rainforest into agriculture) Fossil Methane Alcohol Biodiesel 100% Rape ME CH 100% Rape M E RER 100% Palmoil ME MY 100% Soy M E S 100% Soy ME BR 100% Recycled plant oil M E CH 100% Recycled plant oil M E FR M ethanol fixed bed CH M ethanol fluidized bed CH Ethanol grass CH Ethanol potatoes CH Ethanol sugar beets CH Ethanol whey CH Ethanol wood CH Ethanol sweet sorghum CN Ethanol rye RER Ethanol corn S Ethanol sugar cane BR M ethane grass biorefinery M ethane manure M ethane manure+cosubstrate M ethane manure, optimized M ethane manure+cosubstrate, optimized M ethane biowaste M ethane sewage sludge M ethane wood Diesel, low sulphur ERO3 Petrol, low sulphur ERO3 Natural gas, ERO3 Maximal reduction: 40% Infrastructure Cultivation Production Transport Operation Environmental impacts (BP 06) Conclusion: Most important aspect of biofuels: cultivation About 40% of environmental impacts of transport services are infrastructure-related Maximal reduction has XME from recycled plant oil: 40% Or with other words: driving a car with XME from recycled plant oil still cause 60% of environmental impacts. Zah et al., BP [Pt/pkm]

13 Biofuels comparison GWP 0% 20% 40% 60% 80% 100% 120% Methane manure, optimized Methane manure+cosubstrate, optimized 100% Recycled plant oil ME FR Ethanol whey CH 100% Recycled plant oil ME CH Methanol fixed bed CH Methane w ood Methanol fluidized bed CH Ethanol sugar cane BR Ethanol grass CH Ethanol w ood CH Ethanol sweet sorghum CN Ethanol sugar beets CH Methane sew age sludge Methane grass biorefinery 100% Soy ME S Methane biow aste 100% Palmoil ME MY 100% Rape ME CH Methane manure+cosubstrate Methane manure 100% Rape ME RER Ethanol corn S Ethanol rye RER Ethanol potatoes CH 100% Soy ME BR Natural gas, ERO3 Diesel, low sulphur ERO3 Petrol, low sulphur ERO3 BP 06 0% 100% 200% 300% 400% 500% Eco-indicator 9 0% 100% 200% 300 Zah et al Tax exemption if 40% lower GWP and not higher environmental impacts than gasoline Trade-off of environmental impacts 26 (Zah et al. 2007)

14 Conclusion from biofuels study A broad variety of investigated biofuels have a significant GWP-reducing potential Overall impact is lower in biofuels from waste. - > Step of cultivation is the most important one Transport-related impacts can t be neglected Many biofuels with agricultural biomass have higher overall impacts than fossil fuels 27 Limits of investigation Emerging technologies with status 2005 Different degree of development status No consequential LCA e.g. influence on food and fodder production No limits due to potentials of biomass production 28

15 Conclusions for inventory data Products show environmental Achilles tendon in different areas => Focus of investigation depends on product analysed Biofuels example: - burning of residues - CO2 emissions due to land transformation => acknowledge and model regional differences ecoinvent data provide the necessary information 29 Conclusions (2) Environmental impacts of biofuel pathways are dependent on the raw material No good or bad types of products Differences of biomass origin, type and processing must be taken into account ecoinvent data must be reworked if used in another context Data base provides good basis for such assessments 30

16 Outlook Full LCA based on investigated data published in the framework of the project ( Life cycle inventories of BTL-fuels are published in EcoSpold format in a European project ( Ongoing discussion on guidelines for tax exemption will further increase the need for reliable LCI data Shift of focus from fuel to fuel consumption 31

17 GWP is one environmental effect others serious effects are: photochemical oxidation acidification eutrophication ozone layer depletion human toxicity fresh water toxicity marine aquatic toxicity land competition abiotic depletion All effects can be aggregated: eco-indicator 99 BP 06 german: mweltbelastungspunkte, english: Ecological Scarcity Point 33 Increase of agricultural area This area was cleared by soybean farmers in Novo Progreso. Brazilian Government figures show that the rate of clearing has increased. 34

18 Annual forest loss in Brazilian Amazon nearly km 2 = 600m 2 per second Clear cutting of primary forests Agricultural area is increased by clear cutting Land transformation leads to CO 2 emissions from soil and biomass Burning of residues with further emissions Loss of biodiversity CO 2 from land transformation accounts for about 90% of Brazil CO 2 emissions Particles from residue burning are an important problem in South-East Asia 36

19 Principle of investigation What is the increase in agricultural area for the production in the reference year? What is emitted per m 2 of clear cut land? Allocation of emissions between wood and stubbed land Stubbed land is the main driver New elementary flow CO 2, land transformation as used by IPCC for different possibilities of analysis 37 Inventory Clear Cutting Name Location Infrastructu reprocess nit clear-cutting, primary forest round wood, primary forest, clear-cutting, at forest road provision, stubbed land Location BR BR BR InfrastructureProcess nit ha m3 m2 round wood, primary forest, clear-cutting, at forest road BR 0 m3 5.21E provision, stubbed land BR 0 m2 1.00E Wood, primary forest, standing - - m3 1.82E Transformation, from tropical rain forest - - m2 1.00E Transformation, to forest, intensive, clearcutting - - m2 1.00E power sawing, without catalytic converter RER 0 h 1.24E Carbon dioxide, land transformation - - kg 1.20E Carbon monoxide, fossil - - kg 7.84E Methane, fossil - - kg 5.14E

20 Inventory agricultural product 39 Name Locati on nit soybeans, at farm Location BR InfrastructureProcess 0 nit kg Occupation, arable, non-irrigated m2a 1.97E+0 Transformation, to arable, non-irrigated m2 3.93E+0 Transformation, from forest, intensive, clear-cutting m2 6.22E-2 Transformation, from arable, non-irrigated m2 3.77E+0 Transformation, from shrub land, sclerophyllous m2 1.03E-1 provision, stubbed land BR m2 6.22E-2 Soybean greenhouse gasses kg CO2-eq per kg at field 0 40 soybeans BR soybeans S Soy beans, integrated Soy beans organic, CH production, CH fossil, fossil, non-co2 non-co2 CH4, biogenicch4, biogenic CO2 CO2, land CO2trans