Spatiotemporal drivers of urban water pollution : Assessment of 102 cities across the Yangtze River Basin
© 2024 The Authors..
Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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| Enthalten in: |
Environmental science and ecotechnology - 20(2024) vom: 27. Apr., Seite 100412 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhao, Yi-Lin [VerfasserIn] |
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| Links: |
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| Themen: |
Basin management |
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| Anmerkungen: |
Date Revised 03.04.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.ese.2024.100412 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM370502574 |
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| 520 | |a © 2024 The Authors. | ||
| 520 | |a Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Basin management | |
| 650 | 4 | |a Local conditions | |
| 650 | 4 | |a Primary indices | |
| 650 | 4 | |a Urban risk factors | |
| 650 | 4 | |a Yangtze river basin | |
| 700 | 1 | |a Sun, Han-Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Xiao-Dan |e verfasserin |4 aut | |
| 700 | 1 | |a Ding, Jie |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Mei-Yun |e verfasserin |4 aut | |
| 700 | 1 | |a Pang, Ji-Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Da-Peng |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Ming |e verfasserin |4 aut | |
| 700 | 1 | |a Ren, Nan-Qi |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Shan-Shan |e verfasserin |4 aut | |
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