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文章摘要
城市小流域面源污染输出特征及污染负荷分类核算研究
Research on Non point Source Pollution Output Characteristics and Pollution Load Classification Accounting of Urban Small Watershed
  
DOI:
中文关键词: 面源污染  污染负荷核算  贡献率  上秦淮二横沟
英文关键词: Non point source pollution  Pollutionload accounting  Contribution rate  The Erheng ditchwatershed in the upperstream Qinhuai River
基金项目:国家自然科学基金资助项目(41971137,42001109);江苏省自然科学基金资助项目(BK20201102);中国长江三峡集团有限公司联合基金资助项目(201903145)
作者单位
张明睿 安徽工业大学安徽华骐环保科技股份有限公司 
郑俊 安徽工业大学安徽华骐环保科技股份有限公司 
徐力刚 中国科学院大学中国科学院流域地理学重点实验室 
范宏翔 中国科学院大学中国科学院流域地理学重点实验室 
张德伟 安徽华骐环保科技股份有限公司 
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中文摘要:
      以南京市上秦淮片区二横沟小流域为例,在污染源调查的基础上,采用分类法,利用改进后的污染输出系数模型进行流域污染负荷核算,得到外源污染物入河负荷量及各污染源的贡献率。研究结果表明,上秦淮片区二横沟流域内污染物排放负荷总量为COD 229.9 t/a、TN 25.8 t/a、NH3-N 22.4 t/a、TP 1.7 t/a,入河负荷量为COD 47.1 t/a、TN 5.5 t/a、NH3-N 4.6 t/a、TP 0.36 t/a,主要来自面源污染,点源污染较小。其中,生活面源污染年入河贡献率最高,为44.5%,林地面源污染贡献率最低,为0.1%,水产面源、道路面源、水田面源和旱地面源贡献率分别为31.6%、16.2%、6.2%和1.4%。
英文摘要:
      The load of external pollutants into the river and the contribution rate of each source of pollution were obtained by classification method and calculating the pollution load in the watershed using improved pollution output coefficient model, based on the investigation of pollution source, taking the Erheng ditch watershed in the upstream Qinhuai River in Nanjing as example. The results showed that the total pollutant discharge load in that watershed was: COD 229.9 t/a, TN 25.8 t/a, NH3-N 22.4 t/a, TP 1.7 t/a. The load into the river was: COD 47.1 t/a, TN 5.5 t/a, NH3-N 4.6 t/a, TP 0.36 t/a. Non point source pollution was the main pollution, while point source pollution was relatively weak. The annual contribution rate of domestic non point source pollution into the river was the highest of 44.5%, the annual contribution rate of forest non point source pollution into the river was the lowest of 0.1%. The annual contribution rates of aquaculture non point source, road non point source, paddy field non point source and dry land non point source into the river were 31.6%, 16.2%, 6.2% and 1.4%, respectively.
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