Application of a spatially resolved model to contextualise monitoring data for risk assessment of down-the-drain chemicals over large scales.

Many regulatory screening level exposure assessments are based on simple large scale conceptual scenarios. However, exposure, and therefore risks associated with chemicals, are characterised by high spatial variability. The Scenario assembly tool (ScenAT) is a global screening level model to enable spatially resolved local predictions of environmental concentrations of home and personal care chemicals. It uses the European Union Technical Guidance Document (TGD) equation to predict local scale freshwater concentrations (predicted environmental concentrations - PECs) of chemicals discharged via wastewater. ScenAT uses Geographic Information System (GIS) layers for the underlying socio-economic (population) and environmental parameters (per capita water use, sewage treatment plant connectivity, dilution factor). Using a probabilistic approach, we incorporate sources of uncertainty in the input data (tonnage estimation, removal in sewage treatment plants and seasonal variability in dilution factors) for two case-study chemicals: the antimicrobial triclosan (TCS) and the anionic surfactant linear alkylbenzene sulphonate (LAS). We then compare model estimates of wastewater and freshwater concentrations of TCS and LAS to UK monitoring data. Comparison showed that modeled PECs were on average higher than mean measured data for TCS and LAS by a factor 1.8 and 1.4, respectively. Considering the uncertainty associated with both model and monitoring data, the use of a probabilistic approach using the ScenAT model for screening assessment is reasonable. The combination of modelled and monitoring data enables the contextualisation of monitoring data. Spatial PECs can be used to identify areas of elevated concentration for further refined assessment.

Prioritising chemicals used in personal care products in China for environmental risk assessment: application of the RAIDAR model.

China represents a significant market for the sale of personal care products (PCPs). Given the continuous emission of hundreds of chemicals used in PCPs to waste water and the aquatic environment after regular use, methods for prioritising the environmental risk assessment for China are needed. In an effort to assess the prioritisation of chemicals used in PCPs in China, we have identified the chemical ingredients used in 2500 PCPs released to the Chinese market in 2009, and estimated the annual emission of these chemicals. The physical-chemical property data for these substances have been estimated and used as model inputs in the RAIDAR model. In general, the RAIDAR model provides an overall assessment of the multimedia fate of chemicals, and provides a holistic approach for prioritising chemical ingredients. The prioritisation exercise conducted in this study is shown to be strongly influenced by loss processes, such as the removal efficiencies of WWT plants and biotransformation.