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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.

We used XAD-resin based passive air samplers (PAS) to measure atmospheric levels of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) at five ombrotrophic bogs in Eastern Canada. The aims of our study were to investigate the influence of local roads on contaminant levels in the bogs, to derive the regional pattern of atmospheric concentrations, and to assess the uncertainties of the method. Expanded uncertainties based on the duplicate PAS deployed at 24 sites were good for the PAHs, while the deployment period of approx. 100 days was too short to yield acceptable uncertainties for PCBs. The regional PAH distribution was in good agreement with the calculated source proximity of the sampled bogs. We conclude that XAD-resin based PAS deployed for comparatively short periods are well suited for measuring atmospheric concentrations of volatile PAHs, while in remote regions longer deployment is necessary for less volatile PAHs and for PCBs., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

The distribution of organochlorine pesticides and polychlorinated biphenyls in air along an altitudinal transect on Balang Mountain in western China was measured by deploying XAD-2 resin based passive air samplers in duplicate at seven sites with elevations ranging from 1242 to 4485 m above sea level for five consecutive six-month periods between 2005 and 2008. Analyzed by gas chromatography-high resolution mass spectrometry, concentrations of hexachlorobenzene were highest, followed by hexachlorocyclohexanes, DDT-related compounds and PCB congeners 28 and 52. Except for hexachlorobenzene, which had largely uniform concentrations in space and time, there were clear seasonal variations with concentrations in summer being higher than in winter. With a few exceptions, concentrations that vary little with altitude suggest that the presence of these chemicals in the area is almost entirely due to atmospheric transport, most likely from the Chengdu plain. This is supported by similarities in the relative abundance of different compounds and in the differences between summer and winter concentrations measured in the city of Chengdu and in the mountains. Furthermore, air mass trajectories during the sampling period often originate to the East, passing over the Western part of the Sichuan basin, including the Chengdu plain, prior to arriving at the sampling sites. Higher summer time values in the mountains are due to more contaminated air being blown into the region, presumably due either to higher pesticide usage in summer or due to higher temperatures leading to higher evaporation in source regions. Air and soil from the region are in equilibrium with respect to alpha-HCH, gamma-HCH, and HCB, whereas a situation of net deposition prevails for p,p'-DDE and p,p'-DDT.

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 R2 of ∼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.