Literature DB >> 30698906

Spatial characteristics and influencing factors of river pollution in China.

Enru Wang1, Qian Li2, Hao Hu3, Fuli Peng2, Peng Zhang2, Jianjun Li2.   

Abstract

Based on recent water quality data collected from 763 monitoring sections nationwide, this study examined the concentration of major pollutants in China's major rivers. A spatial autocorrelation analysis confirmed that river pollution was spatially uneven and clustered. While pollution of surface water was a nationwide concern, most serious water pollution happened in the Huai, Hai, Yellow, and Liao river Basins in Northern China. The results of the spatial regression analysis showed that GDP per capita, surface water stock, population, and economic structure were all significantly correlated with surface water pollution, with population having strongest impact, followed by level of economic development. By investigating the common characteristics shared by the "hotspot" cities where serious water pollution occurred, this study recommended a regional or basin approach to assessing water quality and controlling river pollution that cuts across jurisdiction boundaries. While China has made considerable progress in improving water productivity, there is still enormous potential in water conservation. It is also imperative to restructure local economy and develop water-efficient, less polluting industries and services. PRACTITIONER POINTS: River pollution in China was spatially uneven and clustered. Most serious water pollution happened in the Huai, Hai, Yellow, and Liao river basins in Northern China. GDP per capita, surface water stock, population, and economic structure correlated with surface water pollution, with population having strongest impact. A regional or basin approach was recommended to assess water quality and controlling river pollution across jurisdiction boundaries. It is also imperative to restructure local economy and develop water-efficient, less polluting industries and services.
© 2018 Water Environment Federation.

Entities:  

Keywords:  China; river basins; spatial autocorrelation; spatial regression; water pollution; water quality

Mesh:

Year:  2019        PMID: 30698906     DOI: 10.1002/wer.1044

Source DB:  PubMed          Journal:  Water Environ Res        ISSN: 1061-4303            Impact factor:   1.946


  2 in total

1.  Research on SVR Water Quality Prediction Model Based on Improved Sparrow Search Algorithm.

Authors:  Xuehua Su; Xiaolong He; Gang Zhang; Yuehua Chen; Keyu Li
Journal:  Comput Intell Neurosci       Date:  2022-04-28

2.  Comparing spatial patterns of 11 common cancers in Mainland China.

Authors:  Lin Zhang; Xia Wan; Runhe Shi; Peng Gong; Yali Si
Journal:  BMC Public Health       Date:  2022-08-15       Impact factor: 4.135

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.