Estimating chemical emissions from home and personal care products in China

China's economy has grown significantly and concomitantly so has the demand for home and personal care (HPC) products. The detection of chemicals used in HPC products is increasing in profile as China strives to improve its environmental management. China is developing robust exposure models for use in regulatory risk-based assessments of chemicals, including those chemicals used in HPC products. Accurate estimates of chemical emissions play an important role within this. A methodology is presented to derive spatially refined emissions from demographic and economic indicators with large variations in emissions calculated, showing product usage being higher in East and South China. The less affordable a product, the greater the influence per capita Gross Domestic Product has on the product distribution. Lastly, more spatially resolved input data highlights greater variation of product use. Linking product sales data with population density increased the observed variability in absolute usage distribution of HPC products at the county > province > regional > country scale.

Estimating surface water concentrations of "down-the-drain" chemicals in China using a global model

Predictions of surface water exposure to "down-the-drain" chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit "unit-world" approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to "down-the-drain" chemicals in China for different levels of sewage treatment provision. Predicted spatial patterns of concentration were consistent with observed water quality classes for China.