Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom.
Safety and Environmental Assurance Centre, Unilever, Sharnbrook MK44 1LQ, United Kingdom.
Environ Int. 2014 Aug;69:18-27. doi: 10.1016/j.envint.2014.03.020. Epub 2014 May 4.
We present a new multimedia chemical fate model (SESAMe) which was developed to assess chemical fate and behaviour across China. We apply the model to quantify the influence of environmental parameters on chemical overall persistence (POV) and long-range transport potential (LRTP) in China, which has extreme diversity in environmental conditions. Sobol sensitivity analysis was used to identify the relative importance of input parameters. Physicochemical properties were identified as more influential than environmental parameters on model output. Interactive effects of environmental parameters on POV and LRTP occur mainly in combination with chemical properties. Hypothetical chemicals and emission data were used to model POV and LRTP for neutral and acidic chemicals with different KOW/DOW, vapour pressure and pKa under different precipitation, wind speed, temperature and soil organic carbon contents (fOC). Generally for POV, precipitation was more influential than the other environmental parameters, whilst temperature and wind speed did not contribute significantly to POV variation; for LRTP, wind speed was more influential than the other environmental parameters, whilst the effects of other environmental parameters relied on specific chemical properties. fOC had a slight effect on POV and LRTP, and higher fOC always increased POV and decreased LRTP. Example case studies were performed on real test chemicals using SESAMe to explore the spatial variability of model output and how environmental properties affect POV and LRTP. Dibenzofuran released to multiple media had higher POV in northwest of Xinjiang, part of Gansu, northeast of Inner Mongolia, Heilongjiang and Jilin. Benzo[a]pyrene released to the air had higher LRTP in south Xinjiang and west Inner Mongolia, whilst acenaphthene had higher LRTP in Tibet and west Inner Mongolia. TCS released into water had higher LRTP in Yellow River and Yangtze River catchments. The initial case studies demonstrated that SESAMe performed well on comparing POV and LRTP of chemicals in different regions across China in order to potentially identify the most sensitive regions. This model should not only be used to estimate POV and LRTP for screening and risk assessments of chemicals, but could potentially be used to help design chemical monitoring programmes across China in the future.
我们提出了一个新的多媒体化学物质归趋模型（SESAMe），旨在评估中国范围内化学物质的归趋和行为。我们应用该模型来量化环境参数对中国化学物质整体持久性（POV）和长距离传输潜力（LRTP）的影响，中国的环境条件具有极端多样性。Sobol 敏感性分析用于确定输入参数的相对重要性。物理化学性质被确定为比环境参数对模型输出更有影响。环境参数对 POV 和 LRTP 的相互作用主要发生在与化学性质相结合的情况下。假设化学品和排放数据被用于模拟具有不同 Kow/Dow、蒸气压和 pKa 的中性和酸性化学品的 POV 和 LRTP，在不同的降水量、风速、温度和土壤有机碳含量（fOC）下。一般来说，对于 POV，降水比其他环境参数更有影响，而温度和风速对 POV 变化没有显著贡献；对于 LRTP，风速比其他环境参数更有影响，而其他环境参数的影响取决于特定的化学性质。fOC 对 POV 和 LRTP 有轻微影响，较高的 fOC 总是增加 POV 并降低 LRTP。使用 SESAMe 对实际测试化学品进行了案例研究，以探索模型输出的空间变异性以及环境特性如何影响 POV 和 LRTP。多介质中释放的二苯并呋喃在新疆西北部、甘肃部分地区、内蒙古东北部、黑龙江和吉林的 POV 较高。空气中释放的苯并[a]芘在新疆南部和内蒙古西部的 LRTP 较高，而苊在西藏和内蒙古西部的 LRTP 较高。水中释放的 TCS 在黄河和长江流域的 LRTP 较高。初步案例研究表明，SESAMe 能够很好地比较中国不同地区化学物质的 POV 和 LRTP，以便潜在地识别最敏感的地区。该模型不仅应该用于估计筛选和风险评估中化学物质的 POV 和 LRTP，而且未来还有可能用于帮助设计中国各地的化学监测计划。
