Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution
Summary: 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...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
|
| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004225007850 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849323414747086848 |
|---|---|
| author | Shaobo Sui Mingshi Wang Mingya Wang Wanqi Ma Shili Yang Fan Zhang Luhao Jia Tong Liu |
| author_facet | Shaobo Sui Mingshi Wang Mingya Wang Wanqi Ma Shili Yang Fan Zhang Luhao Jia Tong Liu |
| author_sort | Shaobo Sui |
| collection | DOAJ |
| description | Summary: 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. |
| format | Article |
| id | doaj-art-8a10051bcb704c9eb4dc8910f618c454 |
| institution | Kabale University |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-8a10051bcb704c9eb4dc8910f618c4542025-08-20T03:49:03ZengElsevieriScience2589-00422025-05-0128511252410.1016/j.isci.2025.112524Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollutionShaobo Sui0Mingshi Wang1Mingya Wang2Wanqi Ma3Shili Yang4Fan Zhang5Luhao Jia6Tong Liu7College of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, China; Corresponding authorCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaCollege of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, ChinaSummary: 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.http://www.sciencedirect.com/science/article/pii/S2589004225007850Environmental sciencePollutionAquatic science |
| spellingShingle | Shaobo Sui Mingshi Wang Mingya Wang Wanqi Ma Shili Yang Fan Zhang Luhao Jia Tong Liu Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution iScience Environmental science Pollution Aquatic science |
| title | Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution |
| title_full | Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution |
| title_fullStr | Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution |
| title_full_unstemmed | Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution |
| title_short | Pronounced transition of heavy metal pollution sources in Chinese agricultural surface waters: The rising prominence of non-point source pollution |
| title_sort | pronounced transition of heavy metal pollution sources in chinese agricultural surface waters the rising prominence of non point source pollution |
| topic | Environmental science Pollution Aquatic science |
| url | http://www.sciencedirect.com/science/article/pii/S2589004225007850 |
| work_keys_str_mv | AT shaobosui pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT mingshiwang pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT mingyawang pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT wanqima pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT shiliyang pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT fanzhang pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT luhaojia pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution AT tongliu pronouncedtransitionofheavymetalpollutionsourcesinchineseagriculturalsurfacewaterstherisingprominenceofnonpointsourcepollution |