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Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study, chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources–consumer (near-field), dietary, far-field industrial, and far-field pesticide–to the general population. The balanced accuracies of these source-based exposure pathway models range from 73 to 81%, with the error rate for identifying positive chemicals ranging from 17 to 36%. We then used exposure pathways to organize predictions from 13 different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R2of ∼0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479 926 chemicals, mostly with minimal exposure information. This approach identifies 1880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 μg/kg BW/day for 474572 compounds.

Exposure- and risk-based assessments for chemicals used indoors or applied to humans (i.e., in near-field environments) necessitate an aggregate exposure pathway framework that aligns chemical exposure information from use sources to internal dose and eventually to their potential for health effects. Such a source-to-effect continuum is advocated to balance the complexity of human exposure and the insufficiency of relevant data for thousands of existing and emerging chemicals. Here, we introduce the Risk Assessment, IDentification And Ranking-Indoor and Consumer Exposure (RAIDAR-ICE) model, which establishes an integrated framework to evaluate human exposure due to indoor use and direct application of chemicals to humans. As a model evaluation, RAIDAR-ICE faithfully reproduces exposure estimates inferred from biomonitoring data for 37 chemicals with direct and indirect near-field sources. RAIDAR-ICE generates different rankings for 131 chemicals based on different exposure- and risk-based assessment metrics, demonstrating its versatility for diverse chemical screening goals. When coupled with a far-field RAIDAR model, the near-field RAIDAR-ICE model enables assessment of aggregate human exposure. Overall, RAIDAR-ICE is a powerful tool for high-throughput screening and prioritization of human exposure to neutral organic chemicals used indoors.

Environmental context Some long-lived organic contaminants, such as chlorinated organics, brominated flame retardants and polycyclic aromatic hydrocarbons, can undergo transport through the atmosphere to remote regions. A series of measurements of these compounds taken over almost 3 years in the air at a remote location was combined with meteorological data to try to reveal potential source areas. After adjusting several parameters to optimise the method’s ability to identify sources it was found that for most contaminants no definitive sources are revealed. Abstract A suite of brominated flame retardants, chlorinated organic pesticides and some metabolites thereof were analysed in week-long and day-long air samples collected at Little Fox Lake in Canada’s Yukon Territory from 2007 to 2009. Several trajectory-based methods for source region identification were applied to this dataset, as well as to polycyclic aromatic hydrocarbon (PAH) concentrations in those same samples reported previously. A type of concentration weighted trajectory (CWT) analysis, using a modified grid to avoid difficulties near the Earth’s poles, and removing trajectory endpoints at altitudes greater than 700m did not identify distinct source regions for most analytes. Decreasing the spatial resolution of the grid made interpretation simpler but reinforced patterns that may have stemmed from single trajectories. The potential source contribution function (PSCF) is similar to CWT but treats the concentration data categorically, rather than numerically. PSCF provides more distinct results, highlighting the Arctic Ocean as a potential source of para,para′-dichlorodiphenyldichloroethene and both northern Siberia and Canada’s Yukon and Northwest Territories as potential sources of PAHs. To simulate the uncertainty associated with individual trajectories, a set of trajectories was also generated for six points surrounding the sampling station and included in the trajectory analyses. This had the effect of smoothing the CWT and PSCF values for those analytes with no clearly definable sources, and highlighting the source regions for the two that did. For the bulk of the analytes discussed here, Little Fox Lake is well positioned to act as a background monitoring site.