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Non-point source pollution has become an important factor affecting the aquatic ecological environment and human health, and the analysis of spatial-temporal variations in non-point source pollution risks is an important prerequisite for pollution control. Based on land-use and land-cover data from 1980 to 2020, the potential non-point source pollution index (PNPI) model was applied in the upper Beiyun River Basin using different weighting methods. The results showed that:① The potential risk of non-point source pollution is high in the southeast and low in the northwest of the basin. Between 1980 and 2020, the total area of extremely high-risk and high-risk non-point source pollution regions showed a decreasing trend, and the main types of land use for extremely high-risk and high-risk regions gradually evolved from paddy fields, drylands, and orchards to urban and rural residential land; ② The weighting of the land use index determined by the mean-square deviation decision, entropy, coefficient of variation, and expert scoring methods was largest among the three PNPI indices, with average weightings of 0.46, 0.53, 0.45, and 0.48, respectively. However, the weightings for runoff and distance indices determined by different weighting methods were notably different, and the proportions of regions with different levels of non-point source pollution risk also varied; ③ The exponential function method, which describes the relationship between source factors and transport factors by constructing the exponential functions of land use, runoff, and distance indices, provided results that are more consistent with the spatial distribution characteristics of non-point source pollution risk in the basin. The proportions of extremely low-risk and extremely high-risk regions are 54.22% and 6.23%, respectively. These results provide scientific reference for risk analysis and the control of non-point source pollution in this basin.
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http://dx.doi.org/10.13227/j.hjkx.202010225 | DOI Listing |
Environ Monit Assess
September 2025
School of Materials Engineering, Changzhou Vocational Institute of Industry Technology, Changzhou, 213000, People's Republic of China.
A multi-indicator framework was developed to resolve multi-source pollution in highly urbanized rivers, demonstrated in the Qinhuai River Basin, Nanjing, China. Water quality index (WQI) stratification was integrated with dissolved organic matter (DOM) fluorescence components, hydrochemical ions, and conventional parameters and analyzed using positive matrix factorization (PMF). Correlation analysis further elucidated source compositions and interactions.
View Article and Find Full Text PDFJ Environ Manage
September 2025
Ecological Modelling Laboratory, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, M1C 1A4, Canada. Electronic address:
Agriculture intensification represents an essential strategy to ensure food security for the growing human population, but it also poses considerable environmental concerns. Climate change and associated projections of an increased frequency of extreme precipitation and runoff events may amplify nutrient dynamics along the watershed-lake continuum, and could further exacerbate the poor water quality conditions downstream. Identifying hotspot locations with higher propensity for sediment and nutrient export and designing effective mitigation measures at the source is more critical than ever.
View Article and Find Full Text PDFEnviron Sci Technol
September 2025
Earth Systems and Global Change Group, Wageningen University & Research, Droevendaalsesteeg 4, Wageningen 6708 PB, The Netherlands.
The widespread use of antibiotics in humans and animals raises significant environmental concerns. However, few approaches can simultaneously quantify their transfer from humans and animals and track their fate in soils and rivers. In this study, we developed the MARINA-Antibiotics model (Model to Assess River Inputs of pollutaNts to seAs for Antibiotics) to quantify the sources and concentrations of 30 widely used antibiotics, as well as assess their associated environmental risks, and implemented this model in the Three Gorges Reservoir Area in 2020.
View Article and Find Full Text PDFEnviron Res
September 2025
Ocean College, Zhejiang University, 1 Zheda Road, Zhoushan, 316021, China; Joint Center for Blue Carbon Research, Ocean Academy, Zhejiang University, Zhoushan, 316021, China; Donghai Laboratory, Zhoushan, 316021, China; Key Laboratory of Watershed Non-Point Source Pollution Control and Water Eco-Sec
Spartina alterniflora as a potential algaecide has invaded coastal ecosystems globally. However, the regional heterogeneity and driving factors of the metabolomic fingerprint in S. alterniflora are still unknown.
View Article and Find Full Text PDFEnviron Res
September 2025
Shandong Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Shandong University of Aeronautics, Binzhou Shandong, 256603, China.
Agricultural nonpoint source pollution (NPSP) is a serious environmental problem globally. Soil nitrogen (N) loss can cause eutrophication. Soil microorganisms are the key factor influencing soil N.
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