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长江下游快速城市化地区水污染特征及源解析:以秦淮河流域为例
引用本文:马小雪,龚畅,郭加汛,王腊春,徐蕴韵,赵春发.长江下游快速城市化地区水污染特征及源解析:以秦淮河流域为例[J].环境科学,2021,42(7):3291-3303.
作者姓名:马小雪  龚畅  郭加汛  王腊春  徐蕴韵  赵春发
作者单位:江苏第二师范学院城市与资源环境学院,南京 210013;Signal Processing in Earth Observation(SiPEO),Technical University of Munich(TUM),80333 Munich,Germany;江苏省水文水资源勘测局宿迁分局,宿迁223800;南京大学地理与海洋科学学院,南京210093;南京市江宁区水务局,南京 211100
基金项目:江苏省高等学校自然科学研究项目(19KJB170002);江苏第二师范学院引进高层次人才科研启动经费项目(921001);南京市水务科技项目(201806);国家留学基金委项目
摘    要:明晰区域水污染现状及污染物与污染源之间的关系是实施水环境精细化管理和区域水污染治理对策的前提.水质标识指数法(WQI)和聚类分析(CA)被用于研究2015~2019年秦淮河流域29个监测站点的11个水质参数的时空变化特征,并利用PMF模型和SIAR同位素源解析模型解析秦淮河流域的污染物来源及贡献率.结果表明,秦淮河流域河道水体总体为中度污染,TN浓度超标是流域水体污染的主要原因;2015~2019年WQI值呈现下降的趋势;空间聚类和PMF分析结果显示:①高污染区位于秦淮河下游城市化程度较高的城区、溧水主城和江宁大学城内的河道及牛首山河,污染源主要为生活污水、商服业污水(28.88%)及工业废水排放(27.43%);②中污染区位于秦淮河下游的江宁开发区和秣陵街道及中上游的禄口街道内河道,主要污染源为城乡生活废水和商服污水(31.62%)、工业废水(27.25%)和内源污染(24.76%);③低污染区位于秦淮河流域湖熟街道内河道及二、三干河,主要污染源为农村生活污水和生活垃圾(28.79%)及农业非点源污染(24.3%);云台山河子流域内NO3--N是氮污染物在子流域受纳水体中的主要存在形式,SIAR溯源结果显示云台山河子流域的NO3--N主要来源于生活污水(61%)和土壤有机氮(34%).本研究结果可为秦淮河流域水污染治理和水生态保护措施提供科学依据和基础.

关 键 词:水污染  PMF法  SIAR模型  源贡献  秦淮河流域
收稿时间:2020/11/22 0:00:00
修稿时间:2021/1/5 0:00:00

Water Pollution Characteristics and Source Apportionment in Rapid Urbanization Region of the Lower Yangtze River: Considering the Qinhuai River Catchment
MA Xiao-xue,GONG Chang,GUO Jia-xun,WANG La-chun,XU Yun-yun,ZHAO Chun-fa.Water Pollution Characteristics and Source Apportionment in Rapid Urbanization Region of the Lower Yangtze River: Considering the Qinhuai River Catchment[J].Chinese Journal of Environmental Science,2021,42(7):3291-3303.
Authors:MA Xiao-xue  GONG Chang  GUO Jia-xun  WANG La-chun  XU Yun-yun  ZHAO Chun-fa
Institution:College of Urban Resources and Environment, Jiangsu Second Normal University, Nanjing 210013, China;Signal Processing in Earth Observation(SiPEO), Technical University of Munich(TUM), 80333 Munich, Germany;Suqian Hydrological and Water Resources Management Bureau of Jiangsu Province, Suqian 223800, China;School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; Water Affairs Bureau of Jiangning District, Nanjing City, Nainjing 211100, China
Abstract:Clarifying the current situation of regional water pollutants and the relationship between pollutants and pollution sources is considered essential for managing the water environment. Water quality identification index (WQI), cluster analysis (CA), positive matrix factorization (PMF), and stable isotope analysis in R (SIAR) were employed to interpret a large and complex water quality data set of the Qinhuai River catchment generated during 2015 to 2019 to monitor of 11 parameters at 29 different sampling sites. WQI analysis indicated that water quality in Qinhuai River catchment is considered to have "moderate pollution," and an improving trend of water quality was observed at the interannual scale. TN was the most deteriorated of all pollution parameters. CA and PMF results on the spatial scale revealed that sampling sites located at downtown of Nanjing and Lishui District or Jangling University town were highly polluted due to the sewage from domestic sewage and business service sewage (28.88%) as well as industrial wastewater (27.43%), while sampling sites located at Hushu Street Administrative District, Ergan River, and Sangan River were slightly polluted by rural domestic wastewater and garbage (28.79%), and agricultural non-point source pollution (24.3%). The middle-lower reaches (Jiangning Development Zone and Moling Street) and middle reaches (Lukou Street Administrative District) were moderately polluted by industrial wastewater (27.25%), sewage from domestic wastewater and business service wastewater (31.62%) as well as inner sources (24.76%). The SIAR results showed that NO3--N was the main nitrogen form, and the NO3--N mainly originated from sewage (61%) and soil (34%) in the Yuntaishan River sub-catchment. These results will aid in the development of measures required to control water pollution in river catchments.
Keywords:water pollution  PMF method  SIAR method  source contribution  Qinhuai River catchment
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