| Literature DB >> 34990669 |
Xiping Kan1, Shengya Feng2, Xuebing Mei1, Qian Sui3, Wentao Zhao4, Shuguang Lyu5, Shuying Sun1, Ziwei Zhang1, Gang Yu6.
Abstract
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.Entities:
Keywords: Characteristic matrix; Emission sources; PhACs; Source apportionment; Surface water
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Year: 2022 PMID: 34990669 DOI: 10.1016/j.scitotenv.2021.152783
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963