Confronting new challenges in chemical assessment : emerging contaminants and climate change

University dissertation from Stockholm : Department of Applied Environmental Science (ITM), Stockholm Univeristy

Abstract: Both chemical-specific (e.g. physical-chemical properties) and environmental (e.g. climate) properties are required for model-based chemical exposure assessment. The physical-chemical property data for large numbers of “emerging chemicals” of concern are scarce and uncertain and their unusual structures and behaviour hinder the creation of hazard profiles. Climate change (CC) is expected to alter the transport and fate of chemicals in the environment, so from a long-term perspective it must be accounted for in chemical risk assessment. This thesis tackles the challenges (i) in developing hazard profiles for halogen-free flame retardants (HFFRs), which are emerging chemicals that are often ionogenic and can contain metallic and organic components in the same chemical structure, and (ii) in quantifying the effects of CC on the transport and fate of organic chemicals with a wide range of physical-chemical properties. The findings in Paper I suggest that the hazard profiles of HFFRs can be constructed, though they may be incomplete and associated with uncertainty as a result of data gaps and difficulties in developing models to describe their unique environmental chemistry. Paper II shows that the large uncertainties in physical-chemical properties dominate the variance in future forecasts of chemical concentrations and are far more important than variations in climate parameters due to CC. Paper III derives the CC/baseline scenario ratios of chemical concentrations, which vary widely with physical-chemical properties. Concentrations in the Baltic region are projected to change by factors of up to 3.0. Paper IV identifies significantly decreasing trends in measured atmospheric concentrations of many persistent organic pollutants, implying effectiveness of control actions. There is no evidence that CC has altered the temporal trends in long-term time series of chemicals based on the statistical analyses of the monitoring data.

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