Life cycle assessment of bio-based ethanol produced from different agricultural feedstocks
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Bio-based products are often considered sustainable due to their renewable nature. However, the environmental performance of products needs to be assessed considering a life cycle perspective to get a complete picture of potential benefits and trade-offs. We present a life cycle assessment of the global commodity ethanol, produced from different feedstock and geographical origin. The aim is to understand the main drivers for environmental impacts in the production of bio-based ethanol as well as its relative performance compared to a fossil-based alternative.
Ethanol production is assessed from cradle to gate; furthermore, end-of-life emissions are also included in order to allow a full comparison of greenhouse gas (GHG) emissions, assuming degradation of ethanol once emitted to air from household and personal care products. The functional unit is 1 kg ethanol, produced from maize grain in USA, maize stover in USA, sugarcane in North-East of Brazil and Centre-South of Brazil, and sugar beet and wheat in France. As a reference, ethanol produced from fossil ethylene in Western Europe is used. Six impact categories from the ReCiPe assessment method are considered, along with seven novel impact categories on biodiversity and ecosystem services (BES).
Results and discussion
GHG emissions per kilogram bio-based ethanol range from 0.7 to 1.5 kg CO2 eq per kg ethanol and from 1.3 to 2 kg per kg if emissions at end-of-life are included. Fossil-based ethanol involves GHG emissions of 1.3 kg CO2 eq per kg from cradle-to-gate and 3.7 kg CO2 eq per kg if end-of-life is included. Maize stover in USA and sugar beet in France have the lowest impact from a GHG perspective, although when other impact categories are considered trade-offs are encountered. BES impact indicators show a clear preference for fossil-based ethanol. The sensitivity analyses showed how certain methodological choices (allocation rules, land use change accounting, land use biomes), as well as some scenario choices (sugarcane harvest method, maize drying) affect the environmental performance of bio-based ethanol. Also, the uncertainty assessment showed that results for the bio-based alternatives often overlap, making it difficult to tell whether they are significantly different.
Bio-based ethanol appears as a preferable option from a GHG perspective, but when other impacts are considered, especially those related to land use, fossil-based ethanol is preferable. A key methodological aspect that remains to be harmonised is the quantification of land use change, which has an outstanding influence in the results, especially on GHG emissions.
KeywordsBioethanol Bio-based Biogenic feedstock LCA Maize Sugarcane Sugar beet Wheat
- Adami M, Rudorff BFT, Freitas RM, Aguiar DA, Sugawara LM, Mello MP (2012) Remote sensing time series to evaluate land use change of recent expanded sugar cane crop in Brazil. Sustainability, 4(4):574–585Google Scholar
- ADEME (2010) Analyses de Cycle de Vie appliquées aux biocarburants de première génération consommés en France. Direction Production et Energies Durables (DEPD), FranceGoogle Scholar
- Biofuels Platform (2010) Production of biofuels in the world in 2009. Geographic distribution of bioethanol and biodiesel production in the world. http://www.biofuels-platform.ch/en/infos/production.php?id=bioethanol. Accessed 08 June 2012
- BSI (2012) PAS 2050–1: 2012 assessment of life cycle greenhouse gas emissions from horticultural products. Supplementary requirements for the cradle to gate stages of GHG assessments of horticultural products undertaken in accordance with PAS 2050. British Standards Institution, LondonGoogle Scholar
- California EPA (2009) Proposed regulation to implement the low carbon fuel standard, volume I. Staff Report: Initial Statement of Reasons. California Environmental Protection Agency, California Air Resources Board, SacramentoGoogle Scholar
- de Jong E, Higson A, Walsh P, Wellisch M (2012) Bio-based chemicals, value added products from biorefineries. IEA Bioenergy, Task42 BiorefineryGoogle Scholar
- De Klein C, Novoa RSA, Ogle S, Smith KA, Rochette P, Wirth TC, McConkey BG, Mosier A, Rypdal K, Walsh M, Williams SA (2006) N2O emissions from managed soils, and CO2 emissions from lime and urea application. In: Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K. (eds.) IPCC Guidelines for National Greenhouse Gas Inventories. IGES, Japan. Vol 4, chapter 11Google Scholar
- FAO (2010) Bioenergy environmental impact analysis (BIAS). Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
- FAO (2011a) FAOSTAT. http://faostat.fao.org/site/567/default.aspx#ancor. Accessed 13 June 2012
- FAO (2011b) FAOSTAT. http://faostat.fao.org/site/377/default.aspx#ancor. Accessed 13 June 2012
- Flury K, Jungbluth N (2012) Greenhouse gas emissions and water footprint of ethanol from maize, sugar cane, wheat and sugar beet. ESU-services, Uster, SwitzerlandGoogle Scholar
- Flury K, Frischknecht R, Jungbluth N, Muñoz I (2012) Recommendation for life cycle inventory analysis for water use and consumption. Working paper, ESU Services. http://www.esu-services.ch/fileadmin/download/flury-2012-water-LCI-recommendations.pdf. Accessed 8 Aug 2013
- Frischknecht R, Jungbluth N, Althaus H-J, Doka G, Dones R, Hischier R, Hellweg S, Nemecek T, Rebitzer G, Spielmann M (2010) Overview and methodology. Final report ecoinvent data v2.2, No. 1. Swiss Centre for Life Cycle Inventories, DübendorfGoogle Scholar
- Goedkoop M, Heijungs R, Huijbregts M, De Schryver A, Struijs J, van Zelm R (2009) ReCiPe 2008 A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. First edition. Report I: characterisation. Ministry of housing, Spatial Planning and Environment (VROM), The NetherlandsGoogle Scholar
- Jungbluth N, Chudacoff M, Dauriat A, Dinkel F, Doka G, Faist Emmenegger M, Gnansounou E, Kljun N, Schleiss K, Spielmann M, Stettler C, Sutter J (2007) Life cycle inventories of bioenergy. ecoinvent report no. 17, v2.0. ESU-services, UsterGoogle Scholar
- Kosaric N, Duvnjak Z, Farkas A, Sahm H, Binger-Meyer S, Goebel O, Mayer D et al (2001) Ethanol. In: Arpe (ed) Ullmann’s encyclopedia of industrial chemistry: electronic release, 6th edn. Wiley, WeinheimGoogle Scholar
- Laborde D (2011) Assessing the land use change consequences of European biofuel policies, final report. Prepared by the International Food Policy Institute (IFPRI) for the European Commission. Specific Contract No SI2. 580403, implementing Framework Contract No TRADE/07/A2Google Scholar
- Linak E, Janshekar H, Inoguchi Y (2009) Ethanol. Chemical economics handbook research report. SRI Consulting, HoustonGoogle Scholar
- Meyers R (1986) Handbook of chemical production processes. McGraw-Hill, New YorkGoogle Scholar
- Nemecek T, Heil A, Huguenin O, Meier S, Erzinger S, Blaser S, Dux D, Zimmermann A (2007) Life cycle inventories of agricultural production systems. Ecoinvent report no. 15, v2.0. Agroscope FAL Reckenholz and FAT Taenikon, Swiss Centre for Life Cycle Inventories, DübendorfGoogle Scholar
- Pré Consultants (2012) Simapro software. http://www.pre-sustainability.com/content/simapro-lca-software. Accessed 08 June 2012
- Stewart LK, Charlesworth PB, Bristow KL (2003) Estimating nitrate leaching under a sugarcane crop using APSIM-SWIM. Proceedings from: MODSIM 2003 International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand, July 2003Google Scholar
- Sutter J (2007) Life cycle inventories of petrochemical solvents. ecoinvent report No. 22, v2.0. ETH Zürich. Swiss Centre for Life Cycle Inventories, DübendorfGoogle Scholar
- USEPA (2010) Renewable fuel standard program (RFS2) regulatory impact analysis. EPA-420-R-10-006Google Scholar