@article {21384,
	title = {Global environmental fate of short-chain chlorinated paraffins: Modeling with a single vs. multiple sets of physicochemical properties},
	journal = {Science of The Total Environment},
	volume = {666},
	year = {2019},
	pages = {423-430},
	abstract = {\&nbsp; \&nbsp; While short-chain chlorinated\&nbsp;paraffins\&nbsp;(SCCPs) comprise a myriad of components whose\&nbsp;physicochemical properties\&nbsp;are extremely diverse, many previous studies characterized the SCCP mixtures collectively using a single set of physicochemical properties when modeling the global\&nbsp;environmental fate and risk. In this work, we explore whether a discrepancy exists between simulations based on a single set of physicochemical properties and multiple component-specific ones in global fate and risk modeling, and the environmental condition (e.g., proximity to\&nbsp;emission source\&nbsp;vs. temperature) in which such a discrepancy is most notable. We simulated the environmental concentrations and compartmental distribution of SCCPs, using a mechanistic fugacity-based multimedia BETR-Global model. We observed a discrepancy between modeled concentrations based on a single and multiple sets of properties, which is more notable in regions with a low temperature and negligible emissions, e.g., the remote and cold background Arctic region. The modeled compartmental distribution differs slightly between simulations based on different sets of physicochemical properties. While using a single set of properties minimizes input data required for model-based evaluation of the risk of SCCPs, it tends to underestimate the environmental occurrence and risk in remote and cold regions, which are vulnerable and hence deserve a more conservative evaluation conclusion, and prevents us from drawing conclusions on which SCCP component is of greatest concern. The current work can be a relevant step towards improving the methodology for global environmental modeling and risk assessment of SCCPs and other complex halogenated chemical mixtures.},
	url = {https://www.sciencedirect.com/science/article/pii/S0048969719306461},
	author = {C. Chen and Li Li and Liu, Jianguo* and Junzhou Liu}
}
