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Exploring the Use of Ecological Footprint in Life Cycle Impact Assessment
Author(s) -
Lee SeungJin,
Hawkins Troy R.,
Ingwersen Wesley W.,
Young Douglas M.
Publication year - 2015
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12188
Subject(s) - life cycle assessment , greenhouse gas , industrial ecology , context (archaeology) , ecological footprint , environmental resource management , carbon footprint , environmental economics , land use , metric (unit) , environmental impact assessment , environmental science , consumption (sociology) , footprint , product (mathematics) , natural resource economics , land use, land use change and forestry , production (economics) , sustainability , economics , ecology , operations management , engineering , civil engineering , geography , macroeconomics , archaeology , biology , social science , geometry , mathematics , sociology
Summary Ecological footprint (EF) is a metric that estimates human consumption of biological resources and products, along with generation of waste greenhouse gas (GHG) emissions in terms of appropriated productive land. There is an opportunity to better characterize land occupation and effects on the carbon cycle in life cycle assessment (LCA) models using EF concepts. Both LCA and EF may benefit from the merging of approaches commonly used separately by practitioners of these two methods. However, few studies have compared or integrated EF with LCA. The focus of this research was to explore methods for improving the characterization of land occupation within LCA by considering the EF method, either as a complementary tool or impact assessment method. Biofuels provide an interesting subject for application of EF in the LCA context because two of the most important issues surrounding biofuels are land occupation (changes, availability, and so on) and GHG balances, two of the impacts that EF is able to capture. We apply EF to existing fuel LCA land occupation and emissions data and project EF for future scenarios for U.S. transportation fuels. We find that LCA studies can benefit from lessons learned in EF about appropriately modeling productive land occupation and facilitating clear communication of meaningful results, but find limitations to the EF in the LCA context that demand refinement and recommend that EF always be used along with other indicators and metrics in product‐level assessments.