Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution

Despite strict government controls on pollutant discharges, heavy metal (HM) levels in China's surface waters remain elevated above background values. Accurate source identification of HM pollution is essential for effective environmental management and public health protection. This study collected and analyzed water samples from the southwestern North China Plain to assess HM contamination levels, sources, and health risks, employing the absolute principal component score-multiple linear regression (APCS-MLR) model for robust source apportionment and quantification of pollution source contributions. Surface water HMs remained at "clean" levels but exceeded background values by 1-50 times. Source apportionment identified three primary sources: livestock/poultry (48.3%) > industrial (31.6%) > hybrid sources (20.1%), demonstrating a transition from point to non-point source (NPS) dominance. Monte Carlo simulation revealed serious carcinogenic risks for 1.1% of children and 19.5% of adults. These findings highlight evolving HM pollution patterns in China's agricultural regions, offering important implications for developing nations.

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Publication Details

Journal
iScience
Published
2025-04-23
DOI
https://doi.org/10.1016/j.isci.2025.112524
Citations
5
Primary Topic
Heavy metals in environment
Type
article
Field-Weighted Citation Impact
2.52
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article

Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution

Shaobo Sui, Wanqi Ma, Mingya Wang, Tong Liu et al.
5 citations
iScience
Heavy metals in environment
2.52
article

Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution

Shaobo Sui, Wanqi Ma, Mingya Wang, Tong Liu, Fan Zhang, Shili Yang, Mingshi Wang, Luhao Jia
article en
5 citations

Abstract

Despite strict government controls on pollutant discharges, heavy metal (HM) levels in China's surface waters remain elevated above background values. Accurate source identification of HM pollution is essential for effective environmental management and public health protection. This study collected and analyzed water samples from the southwestern North China Plain to assess HM contamination levels, sources, and health risks, employing the absolute principal component score-multiple linear regression (APCS-MLR) model for robust source apportionment and quantification of pollution source contributions. Surface water HMs remained at "clean" levels but exceeded background values by 1-50 times. Source apportionment identified three primary sources: livestock/poultry (48.3%) > industrial (31.6%) > hybrid sources (20.1%), demonstrating a transition from point to non-point source (NPS) dominance. Monte Carlo simulation revealed serious carcinogenic risks for 1.1% of children and 19.5% of adults. These findings highlight evolving HM pollution patterns in China's agricultural regions, offering important implications for developing nations.

iScienceVol. 28(5)
Henan Polytechnic University (CN)
Zero hunger
Openalex Percentile: Top 11%
Heavy metals in environment
2.52
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