Development of regionalized multimedia chemical fate models for China
To balance the economic development with environmental safety and human health, China has released chemicals management legislation for which chemical prioritization and risk assessment are key issues. To support these ambitions two versions of an environmental fate and behaviour model SESAMe (Sino Evaluative Simplebox-MAMI models), have been developed with different resolutions and structures in this thesis. SESAMe is applied to hypothetical chemicals to investigate the influence of environmental parameters on chemical persistence and long-range transport potential. The environmental distribution of benzo[a]pyrene (BaP) in the base year of 2007 and future scenario in 2030 in China has been predicted using SESAMe v3.0. The efficiency of different technical improvements on reducing emissions and environmental concentrations is discussed using the future scenario. Six organic chemicals, triclosan (TCS), triclocarban (TCC), climbazole, benzophenone-3(BP-3), octocrylene (OC) and octyl methoxycinnamate (OMC), have also been modelled by SESAMe v3.3 to account for the chemical ionisation and the effect of environmental pH to chemical partitioning. The emission inventories of the six chemicals were estimated for 2012. TCS is used as an example chemical to explore the pH dependent environmental risk assessment for ionisable chemicals. Only limited freshwater areas in China were found to be in exceedance of TCS threshold levels. The influence of projected population, infrastructure,and environmental conditions on the use, emission and environmental distribution of the same six chemicals in 2030 was investigated. Infrastructure development, such as wastewater treatment plants (WWTPs) was shown to be the most important factor that will reduce the chemical emission and environmental concentrations into the future. SESAMe models have been successfully applied to a chemical released to air and other types of chemicals released to water that are subject to potential ionisation. Model estimation is demonstrated to be good by comparison with the monitoring data collected from the literature.The application of current and future scenarios demonstrates SESAMe models are potentially useful to support chemical management in China and to identify key gaps for chemical screening and risk assessment.