Towards an Application of the Life Cycle Assessment Framework for GHG Emissions of the Dairy System: A Literature Review
Authors: Baker, F.T. and Axon, S.
Journal: Land
Volume: 14
Issue: 6
eISSN: 2073-445X
DOI: 10.3390/land14061207
Abstract:Farm simulation models are a popular form of measuring greenhouse gas emissions (GHGe) from the agricultural industry as they are holistic and cost effective. The simulation models often follow the well-accepted life cycle assessment (LCA) framework to estimate the GHGe from the complete system from cradle to farm-gate. However, several studies have highlighted flaws in the methodology and accuracy of the application of the LCA tool, underestimating emissions based on the scope of the study. GHGe vary considerably across livestock species, with cattle contributing to the highest proportion, from dairy and beef production. An extensive literature review evaluating the application of the LCA tool for measuring and comparing dairy farm GHGe has not been conducted. The current review evaluates the literature on LCAs of the dairy system across the globe, to highlight the flaws in poor scope design, the potential to underestimate emissions, and significant trade-offs disregarding vital variables.
https://eprints.bournemouth.ac.uk/41093/
Source: Scopus
Towards an Application of the Life Cycle Assessment Framework for GHG Emissions of the Dairy System: A Literature Review
Authors: Baker, F.T. and Axon, S.
Journal: LAND
Volume: 14
Issue: 6
eISSN: 2073-445X
DOI: 10.3390/land14061207
https://eprints.bournemouth.ac.uk/41093/
Source: Web of Science (Lite)
Towards an Application of the Life Cycle Assessment Framework for GHG Emissions of the Dairy System: A Literature Review
Authors: Baker, F. and Axon, S.
Journal: Land
Volume: 14
Issue: 6
DOI: 10.3390/land14061207
Abstract:Farm simulation models are a popular form of measuring greenhouse gas emissions (GHGe) from the agricultural industry as they are holistic and cost effective. The simulation models often follow the well-accepted life cycle assessment (LCA) framework to estimate the GHGe from the complete system from cradle to farm-gate. However, several studies have highlighted flaws in the methodology and accuracy of the application of the LCA tool, underestimating emissions based on the scope of the study. GHGe vary considerably across livestock species, with cattle contributing to the highest proportion, from dairy and beef production. An extensive literature review evaluating the application of the LCA tool for measuring and comparing dairy farm GHGe has not been conducted. The current review evaluates the literature on LCAs of the dairy system across the globe, to highlight the flaws in poor scope design, the potential to underestimate emissions, and significant trade-offs disregarding vital variables.
https://eprints.bournemouth.ac.uk/41093/
Source: Manual
Towards an Application of the Life Cycle Assessment Framework for GHG Emissions of the Dairy System: A Literature Review
Authors: Baker, F.T. and Axon, S.
Journal: Land
Volume: 14
Issue: 6
ISSN: 2073-445X
Abstract:Farm simulation models are a popular form of measuring greenhouse gas emissions (GHGe) from the agricultural industry as they are holistic and cost effective. The simulation models often follow the well-accepted life cycle assessment (LCA) framework to estimate the GHGe from the complete system from cradle to farm-gate. However, several studies have highlighted flaws in the methodology and accuracy of the application of the LCA tool, underestimating emissions based on the scope of the study. GHGe vary considerably across livestock species, with cattle contributing to the highest proportion, from dairy and beef production. An extensive literature review evaluating the application of the LCA tool for measuring and comparing dairy farm GHGe has not been conducted. The current review evaluates the literature on LCAs of the dairy system across the globe, to highlight the flaws in poor scope design, the potential to underestimate emissions, and significant trade-offs disregarding vital variables.
https://eprints.bournemouth.ac.uk/41093/
Source: BURO EPrints