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首页> 外文期刊>Environmental Monitoring and Assessment >Application of positive matrix factorization to source apportionment of surface water quality of the Daliao River basin, northeast China
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Application of positive matrix factorization to source apportionment of surface water quality of the Daliao River basin, northeast China

机译：正矩阵分解在东北大辽河流域地表水水质源解析中的应用

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摘要

Surface water monitoring networks play an important role in the stream water quality management. Since a time series of data is obtained from the monitoring network, multivariate statistical techniques can be used to identify important factors or pollution sources of water system. Positive matrix factorization (PMF) is an improved factor analysis tool that has had limited application to water systems. The objective was to apply PMF to monitoring data to apportion water pollution sources in the Daliao River (DLR) basin. The DLR basin includes the Hun and Taizi River catchments in northeast China. This basin is densely populated and heavily industrialized. Fourteen monitoring stations located on the two rivers were used for monitoring 13 physical and chemical parameters from 1990 to 2002. Results show that five sources/ processes in the Hun River and four in the Taizi River were identified by marker species and spatialtemporal variations of resolved factors, including point and nonpoint sources for both rivers. In addition, the industrial pollution source emission inventory data were used to compare with the resolved industrial sources. Results reveal that chemical transformations have influenced some chemical species. However, this influence is small compared with observed seasonal variations. Therefore, identification of pollution point and nonpoint sources by their seasonal variations is possible, which will also aid in water quality management. The spatial variation of the industrial pollutants typically corresponded with the urban industrial pollution source inventories.
机译：地表水监测网络在溪流水质管理中发挥着重要作用。由于从监控网络获得了时间序列数据，因此可以使用多元统计技术来识别水系统的重要因素或污染源。正矩阵分解（PMF）是一种改进的因子分析工具，在水系统中的应用有限。目的是将PMF应用于监测数据以分摊大辽河（DLR）流域的水污染源。 DLR流域包括中国东北的匈奴河和太子河流域。该盆地人口稠密，工业化程度很高。从1990年到2002年，使用两条河流上的14个监测站监测13个物理和化学参数。结果表明，根据标记物种类和分辨因子的时空变化，确定了浑河的5个源/过程和太子河的4个源/过程。 ，包括两条河流的点源和非点源。另外，使用工业污染源排放清单数据与已解析的工业源进行比较。结果表明，化学转化影响了某些化学物种。但是，与观察到的季节变化相比，这种影响很小。因此，可以通过污染点和非点源的季节变化来识别污染点和非点源，这也将有助于水质管理。工业污染物的空间变化通常与城市工业污染源清单相对应。

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  • 来源
    《Environmental Monitoring and Assessment》 |2015年第3期|80.1-80.12|共12页
  • 作者

    Li Huiying; Hopke Philip K.; Liu Xiande; Du Xiaoming; Li Fasheng;

  • 作者单位

    Beijing Municipal Res Inst Environm Protect, Natl Urban Environm Pollut Control Engn Tech Res, Beijing 100037, Peoples R China;

    Clarkson Univ, Inst Sustainable Environm, Potsdam, NY 13699 USA|Clarkson Univ, Ctr Air Resources Engn & Sci, Potsdam, NY 13699 USA;

    Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China;

    Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China;

    Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Positive matrix factorization (PMF); Monitoring network; Surface water quality; Seasonal variability;

    机译：正矩阵分解（PMF）;监测网络;地表水水质;季节变化;

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