State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China.
School of Mathematics, East China University of Science and Technology, Shanghai 200237, China.
Sci Total Environ. 2022 Apr 1;815:152783. doi: 10.1016/j.scitotenv.2021.152783. Epub 2022 Jan 4.
Recognizing the main sources of pharmaceutically active compounds (PhACs) found in surface waters has been a challenge to the effective control of PhAC contamination from the sources. In the present study, a novel method based on Characteristic Matrix (ChaMa) model of indicator PhACs to quantitatively identify the contribution of multiple emission sources was developed, verified, and applied in Huangpu River, Shanghai. Carbamazepine (CBZ), caffeine (CF) and sulfadiazine (SDZ) were proposed as indicators. Their occurrence patterns in the corresponding emission sources and the factor analysis of their composition in the surface water samples were employed to construct the ChaMa model and develop the source apportionment method. Samples from typical emission sources were collected and analyzed as hypothetical surface water samples, to verify the method proposed. The results showed that the calculated contribution proportions of emission sources to the corresponding source samples were 45%-85%, proving the feasibility of the method. Finally, the method was applied to different sections in Huangpu River, and the results showed that livestock wastewater was the dominant emission source, accounting for 55%-73% in the upper reach of Huangpu River. Untreated municipal wastewater was dominant in the middle and lower reaches of Huangpu River, accounting for 76%-94%. This novel source apportionment method allows the quantitative identification of the contribution of multiple PhAC emission sources. It can be replicated in other regions where the occurrence of localized indicators was available, and will be helpful to control the contamination of PhACs in the water environment from the major sources.
识别地表水中药物活性化合物(PhACs)的主要来源一直是有效控制源头 PhAC 污染的挑战。本研究提出了一种基于指示性 PhAC 特征矩阵(ChaMa)模型的定量识别多种排放源贡献的新方法,并在上海黄浦江进行了验证和应用。选择卡马西平(CBZ)、咖啡因(CF)和磺胺嘧啶(SDZ)作为指示物。利用它们在相应排放源中的出现模式以及表面水样中组成的因子分析,构建 ChaMa 模型并开发源分配方法。采集并分析典型排放源的样品作为假设的地表水样品,以验证所提出的方法。结果表明,排放源对相应源样品的计算贡献比例为 45%-85%,证明了该方法的可行性。最后,将该方法应用于黄浦江的不同河段,结果表明,畜禽废水是主要的排放源,在上游黄浦江占 55%-73%。未经处理的城市污水是黄浦江中下游的主要排放源,占 76%-94%。这种新型源分配方法可以定量识别多种 PhAC 排放源的贡献。在其他存在局部指示物的地区可以复制该方法,有助于控制水环境中 PhAC 的主要污染源污染。