Citation:

Eichler, C., Y. Xu, J. Cao, C. Weschler, T. Salthammer, G. Morrison, Y. Zhang, C. Mandin, W. Wei, P. Blondeau, D. Poppendieck, E. Cohen-Hubal, X. Liu, C. Delmaar, A. Koivisto, O. Jolliet, H. Shin, M. Diamond, C. Bi, AND J. Little. Assessing Human Exposure to Chemicals in Materials, Products and Articles:A Modular Mechanistic Framework. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, , NA, (2020). https://doi.org/10.1021/acs.est.0c02329

Impact/Purpose:

Rapid prioritization and evaluation of the large numbers of chemicals used in consumer products has become a major focus of chemical management strategies to protect consumers from potentially harmful exposures. Although a shared understanding of the value of rapid risk-based evaluation appears to be emerging, both nationally and internationally, implementation strategies vary greatly. Key scientific challenges in exposure modeling include selection of the correct model that fits the needs of the assessment, high complexity and/or large parameter needs, inappropriate simplifications, limited parameter and/or data availability, and the lack of model validation. Mechanistic models are especially valuable for addressing these scientific challenges. In contrast to empirical models, mechanistic models are based on well-recognized, physical/chemical mechanisms that can be relatively easily generalized and also varied in their complexity based on the needs of the assessment. Estimations of key parameters by quantitative structure-use and other predictive relationships can be included in mechanistic modeling approaches. The resulting suite of mechanistic exposure models can be used to support the development of predictive relationships for the estimation of emission and transport parameters, evaluate and build confidence in high-throughput exposure estimates, and inform risk-based chemical management decisions.

Description:

This paper describes a modular mechanistic framework for predicting chemical emission from indoor sources, partitioning among indoor compartments and exposure to humans present in the indoor environment focusing on semi-volatile organic compounds (SVOCs). Important assumptions and their impacts, mechanistically-consistent source emission categories, relevant environmental compartments, congruent exposure pathways and their respective modeling approaches are summarized based on the current consensus regarding what is known about SVOC behavior indoors. Sources of uncertainty and limitations of the framework are discussed, emphasizing the need for further research in different areas of the field. The modular structure of the framework aims at subsequent inclusion of new research findings, other chemical classes of indoor pollutants and additional mechanistic processes relevant to human exposure indoors. The framework connects the current state of knowledge of SVOC exposure in indoor environments to advance chemical risk assessment, and as such may serve as the foundation of the development of a large, open-source community model to better understand interdependencies with existing and ongoing research and policies. The combination of exposure estimates derived using this framework with toxicity data for different endpoints and toxicokinetic mechanisms will ensure that the overall goal of rapid and efficient risk ranking, and chemical prioritization is being achieved. It is highlighted that future risk assessments will need to take a more holistic perspective, consider the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that better reflect impacts observed in human populations to protect public health more effectively. In concert with current advances in exposure science, the proposed framework furthers the goal of integrating chemical risk management and population health perspectives.

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