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ORIGINAL RESEARCH article
Front. Mar. Sci.
Sec. Marine Pollution
Volume 12 - 2025 | doi: 10.3389/fmars.2025.1527098
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Nitrogen pollution in rivers has long been a significant ecological and environmental concern, and research on nitrogen pollution source tracking serves as the foundation for pollution control, playing a crucial role in quantifying different pollution sources and formulating effective mitigation strategies. This study proposes a technical framework for pollution source resolution based on the export coefficient model and microbial source tracking model. Initially, key environmental factors and their spatiotemporal characteristics were analyzed to preliminarily identify potential nitrogen pollution sources, including wastewater treatment plants, stainless steel plants, electroplating factories, chemical plants, pig farms, poultry farms, rice fields, vegetable farms, and tea plantations. Subsequently, hydrochemical and microbial metagenomic analyses were conducted to further refine the identification of nitrogen pollution sources. NMDS analysis revealed significant differences in microbial community structures among different pollution sources, facilitating effective discrimination. Additionally, co-occurrence network analysis was employed to construct microbial fingerprint maps specific to each pollution source. Finally, aBayesian community-wide non-culture microbial source tracking method (SourceTracker) was used for quantitative pollution source apportionment. The export coefficient model estimated that point-source nitrogen loads were primarily derived from domestic wastewater, whereas non-point source nitrogen loads predominantly originated from rural domestic wastewater and agricultural cultivation. By integrating the microbial source tracking model, the primary sources of nitrogen pollution were accurately identified. During the dry season, domestic wastewater (47.3%) was the dominant contributor, including wastewater treatment plants, rural domestic sewage, stainless steel plants, and electroplating factories, with fecal and agricultural sources mainly stemming from pig farms and rice fields. In contrast, during the wet season, agricultural cultivation (20.5%) and natural soil (27.8%) were the predominant contributors, encompassing rice fields, vegetable farms, and tea plantations. This source-tracking approach provides a valuable tool for guiding precise regional pollution control and is particularly applicable in complex pollution environments.
Keywords: nitrogen pollution, Export coefficient models, Microbial source tracking, Nitrogen Source Analysis, Source Tracker Model
Received: 13 Nov 2024; Accepted: 25 Feb 2025.
Copyright: © 2025 Qianhang, Li, Zhou, Jiang and Lei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Weijun Jiang, Lishui Ecological and Environmental Monitoring Center of Zhejiang Province, Lishui, China, Lishui, China
Kun Lei, College of Environmental Science and Engineering, Ocean University of China, Qingdao, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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