Stoichiometry-Based Estimation of Climate Impacts of Emerging Chemical Processes: Method Benchmarking and Recommendations

Current chemical process development aims to improve
sustainability.
Decision-making thus needs to assess potential environmental benefits.
However, reliable life cycle inventory data is often unavailable at
early design stages. Without process information, life cycle assessment
practitioners usually estimate inventories solely based on the reaction
stoichiometry and proxies for energy and utility demands. However,
the quality of these proxies has not been tested on a comprehensive
data set. In this study, we compare and benchmark stoichiometry-based
estimation methods that employ proxies for the yield and utility demands
from the literature to a new benchmark database of 474 processes.
This benchmark data set is based on industrially validated processes
from the Process Economics Program (PEP) yearbook. Most estimation
methods are shown to underestimate the global warming impact. We found
that the yield range assumed by Geisler et al. (2004) closely reflects
the actual raw material demands, while the average process energy
demands, calculated by Kim and Overcash (2003), perform best as a
proxy for energy demands. Thus, we propose to combine both proxies
to improve predictions of the inventory data and the overall global
warming impact.