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Water quality of a tributary of the Pearl River, the Beijiang, Southern China: implications from multivariate statistical analyses

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Abstract

Water quality information of Beijiang River, a tributary of Pearl River in Guangdong, China, was analyzed to provide an overview of the hydrochemical functioning of a major agricultural/rural area and an industrial/urban area. Eighteen water quality parameters were surveyed at 13 sites from 2005 to 2006 on a monthly basis. A bivariate correlation analysis was carried out to evaluate the regional correlations of the water quality parameters, while the principal component analysis (PCA) technique was used to extract the most influential variables for regional variations of river water quality. Six principal components were extracted in PCA which explained more than 78% and 84% of the total variance for agricultural/rural and industrial/urban areas, respectively. Physicochemical factor, organic pollution, sewage pollution, geogenic factor, agricultural nonpoint source pollution, and accumulated pesticide usage were identified as potential pollution sources for agricultural/rural area, whereas industrial wastewaters pollution, mineral pollution, geogenic factor, urban sewage pollution, chemical industrial pollution, and water traffic pollution were the latent pollution sources for industrial/urban area. A multivariate linear regression of absolute principal component scores (MLR-APCS) technique was used to estimate contributions of all identified pollution sources to each water quality parameter. High coefficients of determination of the regression equations suggested that the MLR-APCS model was applicable for estimation of sources of most water quality parameters in the Beijiang River Basin.

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Authors and Affiliations

  1. Department of Environmental Science, School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, Guangdong, People’s Republic of China

    Ming W. Song, Ping Huang & Hui Zhang

  2. School of Environmental Science and Engineering, South China University of Technology, Guangzhou, 510006, Guangdong, China

    Feng Li

  3. Soil and Fertilizer Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China

    Kai Z. Xie

  4. Department of Architecture Engineering, Jinan Engineering Vocational Technical College, Jinan, 250200, China

    Xi H. Wang

  5. Qingyuan Municipal Environment Protect Bureau, Qingyuan, 511515, China

    Guo X. He

Authors
  1. Ming W. Song
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  2. Ping Huang
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  3. Feng Li
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  4. Hui Zhang
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  5. Kai Z. Xie
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  6. Xi H. Wang
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  7. Guo X. He
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Correspondence to Ping Huang.

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Song, M.W., Huang, P., Li, F. et al. Water quality of a tributary of the Pearl River, the Beijiang, Southern China: implications from multivariate statistical analyses. Environ Monit Assess 172, 589–603 (2011). https://doi.org/10.1007/s10661-010-1358-y

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  • DOI: https://doi.org/10.1007/s10661-010-1358-y

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