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

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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

3. Impact Assessment – e.g.:a. Global Warming

b. Acidification

c. Ecotoxicity, etc.

Emission EmissionCAS.no. to air to w ater

Substance g g

2-hydroxy-ethanacrylate 816-61-0 0,0348

4,4-methylenebis cyclohexylamine1761-71-2 5,9E-02Ammonia 7664-81-7 3,7E-05 4,2E-05

Materials and Components Manufacturing

Use and Maintaining

Recycle and Disposal

0 20 40 60 80 100 120

Hazardous waste

Volume waste

Land use

Ecotoxicity

Human toxicity

Nutrient enrichment

Photochemical ozone formation

Acidification

Global warming

PEweu94

B

A

4. May 2009Biodiesel5 DTU Management Engineering, Technical University of Denmark

2b. Environmental Life Cycle Assessment

• Functional Unit:or

Efficiency of Different Fuels*- Delivered at Shaft

Type of Fuel Energy Unit RelativePetrol 11.5 MJ/Liter 73%

Diesel Oil 15.8 MJ/Liter 100%Biodiesel 15.0 MJ/Liter 95%Ethanol 7.9 MJ/Liter 50%

* Source – Danish Technological Institute, 2006

• 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

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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.

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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

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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

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6. Discussion and Outlook

• Main source of difference• Data uncertainties• Uncertainties of final results

• Improved model• More accurate data• Different methods