Premium
Multimedia modeling of human exposure to chemical substances: The roles of food web biomagnification and biotransformation
Author(s) -
Arnot Jon A.,
Mackay Don,
Parkerton Thomas F.,
Zaleski Rosemary T.,
Warren Christopher S.
Publication year - 2010
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.15
Subject(s) - biotransformation , bioaccumulation , biomagnification , pollutant , environmental chemistry , environmental science , food web , food chain , persistent organic pollutant , ranking (information retrieval) , chemistry , toxicology , biology , ecology , computer science , predation , biochemistry , machine learning , enzyme
The Risk Assessment IDentification And Ranking (RAIDAR) model is refined to calculate relative human exposures as expressed by total intake, intake fraction ( iF ), and total body burden ( TBB ) metrics. The RAIDAR model is applied to three persistent organic pollutants (POPs) and six petrochemicals using four mode‐of‐entry emission scenarios to evaluate the effect of metabolic biotransformation estimates on human exposure calculations. When biotransformation rates are assumed to be negligible, daily intake and iF s for the nine substances ranged over six orders of magnitude and TBB s ranged over 10 orders of magnitude. Including biotransformation estimates for fish, birds, and mammals reduced substance‐specific daily intake and iF by up to 4.5 orders of magnitude and TBB by more than eight orders of magnitude. The RAIDAR iF calculations are compared to the European Union System for the Evaluation of Substances (EUSES) model iF calculations and differences are discussed, especially the treatment of food web bioaccumulation. Model selection and application assumptions result in different rankings of human exposure potential. These results suggest a need to critically consider model selection and to include reliable biotransformation rate estimates when assessing relative human exposure and ranking substances for priority setting. Recommendations for further model evaluations and revisions are discussed. Environ. Toxicol. Chem. 2010;29:45–55. © 2009 SETAC