Evaluation and source identification of water pollution

• Published in: Ecotoxicology and environmental safety Vol. 289; p. 117499
• Main Authors: Wei, Huaibin, Qiu, Haojie, Liu, Jing, Li, Wen, Zhao, Chenchen, Xu, Hanfei
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.01.2025; Elsevier
• Subjects: Biological Oxygen Demand Analysis; China; Environmental Monitoring - methods; Nitrogen - analysis; Phosphorus - analysis; Pollution areas identification; Random forest; Source analysis; Spatial clustering pattern; Wastewater - analysis; Water Pollutants, Chemical - analysis; Water Pollution - analysis; Water Quality; China; Random forest; Spatial clustering pattern; Source analysis; Water quality; Pollution areas identification
• ISSN: 0147-6513; 1090-2414; 1090-2414
• DOI: 10.1016/j.ecoenv.2024.117499

Maintaining good surface water quality is essential for protecting ecosystems and human health. Henan Province has long faced challenges related to water scarcity and severe water pollution. To support effective management of water pollution in Henan Province and provide insights for regional water pollution management, we collected extensive water quality monitoring data and applied spatial autocorrelation along with random forest to analyze the sources of heavily polluted areas. Results indicate that the spatial pollution pattern of surface water quality in Henan Province can be generally classified as insignificant pollution in the north, heavy pollution in the central regions, and light pollution in the south. Heavily polluted areas are mainly located in Zhengzhou, Luoyang, and Kaifeng. Key indicators affecting water quality in these regions are chemical oxygen demand (CODMn), dissolved oxygen (DO), ammonia nitrogen (NH3-N), and total phosphorus (TP), with urban sewage and industrial wastewater identified as the main causes of deterioration. These results not only provide a scientific basis for the systematic management of surface water quality pollution in Henan Province but also provide a reference for regional water pollution management. [Display omitted] ●Achieve the overall evaluation of regional water pollution and local refinement of pollution sources.●Intelligent analysis of tpollution sources using random forests.●Provides new ideas for regional water pollution management and filling the gap of similar studies in the region.