Life cycle assessment (LCA) is a method to evaluate the environmental impacts of a product system from its full life cycle including material extraction, processing, manufacturing, use, and end-of-life. LCA has been used widely in industry and academia to understand the environmental impacts of various products and technologies. However, LCA still faces some critical challenges including data quality and availability. The emerging data science can help address some of the data challenges in LCA. This talk will give two examples on the recent development of data science applications in LCA. First, a decision tree model is developed to estimate missing unit process data that are used to develop life cycle inventory. Second, an artificial neural network model is developed to predict ecotoxicity characterization factors of chemicals used in life cycle impact assessment. The findings of these studies shed light on the promising potential of data science to improve the LCA methodology and promote its applications for environmental sustainability.

Use data science to help address data challenges in life cycle assessment

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.