Advancing Chemical Hazard and Risk Assessments: Insights From Chemical Property Prediction and Multimedia Mass-Balance Modeling

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Authors

Zhang, Zhizhen

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2024

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Dissertation

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Chemical Exposure Science , Chemical Fate And Exposure Modeling , Chemical Sorption Onto Soil , Drinking Water Contamination , Persistence And Mobility Chemicals , QSARs

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Abstract

Evaluating the hazards and risks associated with the vast array of chemical substances on the market is essential for protecting human health and environmental integrity. Chemical properties serve as critical determinants of a chemical's potential for hazard, exposure, and risk. By evaluating both the inherent hazards of chemicals and the likelihood and extent of human exposure, risk assessment enables informed decision-making and the implementation of effective risk management strategies to protect human health and the environment. This dissertation addresses chemical assessments from perspectives of chemical properties and multimedia mass-balance modeling. First, the coverage of the applicability domains of commonly used QSARs is explored in terms of predicting chemical partitioning and reactivity properties for chemical assessments. The result shows that the applicability domains of current QSARs have limited coverage of organic chemicals in predicting chemical biodegradability, bioaccumulation, and long atmospheric transport potential. In addition, using persistence and mobility attributes as an example, prioritization efforts made by hazard-based assessment and exposure-based assessment of chemicals with such attributes in different drinking water sources are compared. The result showed that hazard-based assessment is not sufficient for characterizing the actual risks of chemical substances, and there is a need for multimedia fate and exposure models in support of chemical exposure and risk assessments. To address this issue, a comprehensive mechanistic model to predict the fate, transport, and exposure levels of chemicals in drinking water sources is developed. This model successfully integrates considerations of both surface and subsurface compartments, the hydrogeological cycle, sorption onto various geosorbents, and the partitioning behavior of ionizable chemicals, supporting a more thorough understanding of chemical behavior and associated risks.

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