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Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models

International Journal of Environmental Research and Public Health 2021 8 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 30 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Man Zhang, Xiaolong Chen, Shuihua Yang, Zhen Song, Yonggui Wang, Qing Yu

Summary

This study used a combination of field measurements and computer models to quantify pollutant loads from different sources across a Chinese river basin. Better tools for tracking pollution sources at basin scale can support efforts to reduce microplastic and other contaminant inputs to waterways.

Study Type Environmental

Pollutant source apportionment is of great significance for water environmental protection. However, it is still challenging to accurately quantify pollutant loads at basin-scale. Refined analytical methods combined the pollution discharge coefficient method (PDCM), field observation, and numerical model (Soil & Water Assessment Tool, SWAT) to make quantitative source appointment in the Tuojiang River, a key tributary of the upper Yangtze River. The chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (N-NH4+) were analyzed. Results showed that the urban sewage treatment plant point source has the largest contribution to COD, TN, and N-NH4+, while TP is mostly from the agricultural sources throughout the year. The total inflowing loads of pollution sources are significantly affected by rainfall. The overall pollution characteristics showed that pollutant loads present in different seasons are as follows: wet season > normal season > dry season. The month with the highest levels of pollutants is July in the wet season. Among the nine cities, the city that contributes the most COD, TN and N-NH4+, is Neijiang, accounting for about 25%, and the city that contributes the most TP is Deyang, accounting for 23%. Among the sub-basins, the Fuxi River subbasin and Qiuxihe River subbasin contribute the most pollutant loads. The technical framework adopted in this paper can be used to accurately identify the types, administrative regions and sub-basins of the main pollution sources in the watershed, which is conducive to management and governance of the environment.

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