A Multimedia Fate Model to Support Chemical Management in China: A Case Study for Selected Trace Organics

Abstract

SESAMe v3.3, a spatially explicit multimedia fate model for China, is a tool suggested to support quantitative risk assessment for national scale chemical management. The key advantage over the previous version SESAMe v3.0 is consideration of spatially varied environmental pH. We evaluate the model performance using estimates of emission from total industry usage of three UV filters (benzophenone-3, octocrylene, and octyl methoxycinnamate) and three antimicrobials (triclosan, triclocarban, and climbazole). The model generally performs well for the six case study chemicals as shown by the comparison between predictions and measurements. The importance of accounting for chemical ionization is demonstrated with the fate and partitioning of both triclosan and climbazole sensitivity to environmental pH. The model predicts ionizable chemicals (triclosan, climbazole, benzophenone-3) to primarily partition into soils at steady state, despite hypothetically only being released to freshwaters, as a result of agricultural irrigation by freshwater. However, further model calibration is needed when more field data becomes available for soils and sediments and for larger areas of water. As an example, accounting for the effect of pH in the environmental risk assessment of triclosan, limited freshwater areas (0.03% or ca. 55 km(2)) in mainland China are modeled to exceed its conservative environmental no-effect threshold. SESAMe v3.3 can be used to support the development of chemical risk assessment methodologies with the spatial aspects of the model providing a guide to the identification regions of interest in which to focus monitoring campaigns or develop a refined risk assessment.

Drivers of contaminant levels in surface water of China during 2000–2030: Relative importance for illustrative home and personal care product chemicals

“…The gridded (~1 km) Chinese population count and density were projected by CIESIN for the years 2000, 2005, 2015and 2020(CIESIN 2016ab) and by another study for 2030 (Feng and Qi 2016;Qi et al 2015). For the year 2010, to keep identical to our previous study (Zhu et al 2016), data projected by Landscan (Landscan 2010) was used. The urban population was identified by the population density > 5000 (CIESIN 2011) cap/km 2 for 2030 and >1000 cap/km 2 for the other 5 years.…”

“…Changing discharge flow, linked to environmental and infrastructure changes, also affects the dilution of chemicals in surface water. These factors have changed / are changing in a way that could be strongly impacting the concentrations and distributions of chemicals in surface water and the water quality (Zhu et al 2016;Zhu et al 2014).…”

“…Measurements of pharmaceutical and HPCP ingredients have only become available for a limited number of regions in recent years in China. We chose triclosan as an example ingredient in the calculation as it is well studied and there are more monitoring data available than other ingredients for model validation (Zhu et al 2016). It enters the aquatic environment diffusively, primarily from domestic wastewaters.…”

Diffusive gradients in thin-films (DGT) for in situ sampling of selected endocrine disrupting chemicals (EDCs) in waters

“…Other novel passive water sampling devices are therefore needed for environmental monitoring under conditions of changing aquatic environments, to provide more reliable data. Reliable and accurate data on environmental concentrations is crucial for risk assessment of these chemicals and studying their fate in the environment (Zhu et al 2016). Diffusive gradients in thin-films (DGT), developed by Davison in 1994 (Davison andZhang 1994), has been amply demonstrated to provide quantitative in situ measurements of trace components in aqueous systems (Zhang and Davison 1995).…”

Environmental fate and exposure models: advances and challenges in 21st century chemical risk assessment

“…100,101 The multimedia activity model for ionizable (MAMI) organic chemicals has recently been modied in the development of a multimedia chemical fate model for China (SESAMe), designed using the nested structure of SimpleBox. 102,103 The SimpleTreat model 4.0 104 has been updated to include improved handling of ionizable organics, thus providing a tool for estimating chemical fate and behaviour in domestic sewage and activated sludge systems for down-thedrain chemicals, such as pharmaceuticals. 105…”