Environmental Sustainability Analysis of Biodiesel Production - A Comparative Analysis of Different Production Schemes. I.T. Herrmann, Hauschild M., and Birkved M. - Technical University of Denmark, Denmark. - Section for Quantitative Sustainability Assessment. May 4, 2009
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I.T. Herrmann, Hauschild M., and Birkved M. - Technical University of Denmark, Denmark.
Environmental Sustainability Analysis of Biodiesel Production - A Comparative Analysis of Different Production Schemes. I.T. Herrmann, Hauschild M., and Birkved M. - Technical University of Denmark, Denmark. - Section for Quantitative Sustainability Assessment. May 4, 2009. Agenda. - PowerPoint PPT Presentation
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Environmental Sustainability Analysis of Biodiesel Production - A Comparative Analysis of Different Production Schemes.
I.T. Herrmann, Hauschild M., and Birkved M. - Technical University of Denmark, Denmark. - Section for Quantitative Sustainability Assessment.
May 4, 2009
4. May 2009Biodiesel2 DTU Management Engineering, Technical University of Denmark
Agenda
1. Introduction - Sustainability2. Environmental Life Cycle Assessment (LCA)3. LCA Model of Biodiesel4. Method5. Results6. Discussion and Outlook
4. May 2009Biodiesel3 DTU Management Engineering, Technical University of Denmark
1. Introduction - Sustainability
• Environmental• Economic• Social
Environmental
Economic Social
Sustainability
4. May 2009Biodiesel4 DTU Management Engineering, Technical University of Denmark
2a. Environmental Life Cycle Assessment
• Stepwise procedure• ISO Standard – 14040 and 14044
1. Build model - process tree/product chain
2. Inventory - Collecting data of physical quantities of input and output from each process
• Person Equivalent (PE). Impact per functional unit divided with “background reference”. E.g. total greenhouse gas emissions in 1994 translated into CO2-equivalents and divided with the global population number in the same year.
4. May 2009Biodiesel6 DTU Management Engineering, Technical University of Denmark
3. LCA Model of Rape Seed Oil Biodiesel Production
Seeds
Pesticide
Fertilisers
Machine Power
Seed pro.
Energy
Biodiesel production
Energy
Fuel
Electricity from Grid
Coal
Water
Fuel
Energy
Minerals
Chemicals
Energy
Rape seed production T
Rape seed
oil
Chemicals (Methanol and
sodiummethylat)
Minerals
Combustion with energy
recovery
T (Transportation)
T
BD
Glycerine (Avoided)
Waste
Natural Gas
Fuel Oil
Diesel Oil
T
TNatural Gas
Coal
4. May 2009Biodiesel7 DTU Management Engineering, Technical University of Denmark
4. Method
•Using “SimaPro” Program.
•For this initial analysis we have used the “Ecoinvent” database and a few data from the our stakeholders.
•For life cycle impact assessment we have used the EDIP97 method with the normalization reference year 1994.
4. May 2009Biodiesel8 DTU Management Engineering, Technical University of Denmark
Comparison of Conventional and Enzymatic Biodiesel Production + FAME vs. FAEE
-0.5 0 0.5 1 1.5 2 2.5
Human toxicity soil
Human toxicity water
Human toxicity air
Ecotoxicity soil chronic
Ecotoxicity water chronic
Photochemical smog
Eutrophication
Acidifi cation
Global warming (GWP 100)
PE
5a. Results
Enzym – FAME
Enzym - FAEE
Conv - FAEE
Conv – FAME
4. May 2009Biodiesel9 DTU Management Engineering, Technical University of Denmark
5b. Results – Where does it originate from?• The overall major source contributing to the “Ecotoxicity Water Chronic” Impact
Category is the Rape Seed Oil production – contributing with 2.4 PE in the conventional rape seed FAEE production.
• The overall major source contributing to the “Human Toxicity Soil” Impact Category is the Rape Seed Oil production – contributing with 2.1 PE in the conventional rape seed FAEE production.
• From the impact assessment results it is possible to track the impacts back to the substances in the inventory list that contribute the most to the two Impact Categories:
Ecotoxicity Water Chronic Human Toxicity SoilHexane 0.89 PE Benzene 0.63 PEStrontium 0.68 PE Iron 0.49 PECadmium, Ion 0.42 PE Chromium 0.25 PECopper, Ion 0.15 PE Arsenic 0.23 PEIron, Ion 0.09 PE
4. May 2009Biodiesel10 DTU Management Engineering, Technical University of Denmark
6. Discussion and Outlook
• Main source of difference• Data uncertainties• Uncertainties of final results
• Improved model• More accurate data• Different methods