摘要：a c k g r o u n d: Scientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioriti za tion is challenging because of the large number of chemicals requiring evaluation and limited data and resources.oB j e c t i v e s: We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments.Me t h o d s: We used a multi media mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified.re s u l t s: Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of mag-nitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in esti-mated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients.co n c l u s i o n s: Mechanistic exposure modeling is suitable for screening and prioritizing large num-bers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncer-tainty in human exposure and risk assessment in a systematic manner.
关键词：exposure; high throughput; organic chemicals; risk; uncertainty analysis
