Inter-Individual Variability and Non-linear Dose-Response Relationship in Assessing Human Health Impact From Chemicals in LCA: Addressing Uncertainties in Exposure and Toxicological Susceptibility

Current life cycle impact assessment (LCIA) practices use a characterization factor to linearly scale chemical emission human health assuming homogeneous exposure and toxicological susceptibility for the entire population. However, both may vary within population, making same elicit disproportionate impacts. Here we explore how inter-individual variabilities in interact affect estimated overall impacts on population level. For exemplification, PROTEX model simulate of general American dieldrin heptachlor, two organochlorine pesticides that tend accumulate food items. Using Monte-Carlo analysis, characterize by considering variations anthropometrics dietary patterns between ages, sexes, racial groups. We assess level five scenarios with different combinations assumptions (homogeneous/heterogeneous) dose-response relationship (linear/non-linear, homogeneous/heterogeneous susceptibility). Our results indicate can six among demographic Combined non-linear heterogeneous susceptibility, is substantially higher than using susceptibility. current LCIA practice linear produces even overestimate