TY - JOUR
T1 - Hybrid life cycle assessment (LCA) does not necessarily yield more accurate results than process-based LCA
AU - Yang, Yi
AU - Heijungs, Reinout
AU - Brandão, Miguel
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Hybrid life cycle assessment (LCA), through combining input-output (IO) models and process-based LCA for a complete system boundary, is widely recognized as a more accurate approach than process-based LCA with an incomplete system boundary. Without a complete process model for verification, however, the performance of hybrid LCA remains unclear. Here, using a counterexample we show that hybrid LCA does not necessarily provide more accurate results than process-based LCA, simply because the aggregation of heterogeneous processes in IO models may introduce more errors. In so doing, we prove that only when IO-based LCA and process-based LCA have the same level of detail would they yield the same results. Whether hybrid LCA provides more accurate estimates depends on whether the IO model introduced serves as an adequate proxy for the missing products as opposed to if they were estimated by a complete process model. The use of a highly-aggregated IO model runs the risk of overestimation, and could result in a larger relative error than the truncation error resulting from an incomplete process model. Our study seeks to provide a balanced view of hybrid LCA, and our findings offer important insights for future hybrid LCA studies to improve the accuracy and realm of applicability of the approach.
AB - Hybrid life cycle assessment (LCA), through combining input-output (IO) models and process-based LCA for a complete system boundary, is widely recognized as a more accurate approach than process-based LCA with an incomplete system boundary. Without a complete process model for verification, however, the performance of hybrid LCA remains unclear. Here, using a counterexample we show that hybrid LCA does not necessarily provide more accurate results than process-based LCA, simply because the aggregation of heterogeneous processes in IO models may introduce more errors. In so doing, we prove that only when IO-based LCA and process-based LCA have the same level of detail would they yield the same results. Whether hybrid LCA provides more accurate estimates depends on whether the IO model introduced serves as an adequate proxy for the missing products as opposed to if they were estimated by a complete process model. The use of a highly-aggregated IO model runs the risk of overestimation, and could result in a larger relative error than the truncation error resulting from an incomplete process model. Our study seeks to provide a balanced view of hybrid LCA, and our findings offer important insights for future hybrid LCA studies to improve the accuracy and realm of applicability of the approach.
KW - Aggregation
KW - Hybrid
KW - Input-output
KW - Life cycle assessment
KW - Process
KW - System boundary
KW - Truncation error
UR - http://www.scopus.com/inward/record.url?scp=85016001460&partnerID=8YFLogxK
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U2 - 10.1016/j.jclepro.2017.03.006
DO - 10.1016/j.jclepro.2017.03.006
M3 - Article
AN - SCOPUS:85016001460
SN - 0959-6526
VL - 150
SP - 237
EP - 242
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -