Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded Environments, School of Ecology and Environmental Sciences, Yunnan University, Kunming, 650091, China.
Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650091, China.
Environ Geochem Health. 2020 Nov;42(11):3795-3810. doi: 10.1007/s10653-020-00641-z. Epub 2020 Jun 27.
As the upper reach of the Yangtze River, the Jinsha River has experienced ecological degradation due to increased anthropogenic activities. The potential pollution sources affecting the Jinsha River watershed from 2016 to 2018 were investigated using an improved method in combination with correlation analysis and the absolute principal component score-multiple linear regression receptor modeling technique. Our results identified 5-7 potential pollution sources in the Jinsha main stream watershed and the Pudu, Niulan, and Yalong River watersheds of the Jinsha River. The water pollutant concentrations of the Jinsha main stream watershed were mainly influenced by environmental, agricultural, and human population factors. In the Pudu River watershed, the primary pollution sources changed to natural and sedimentary pollutant sources. It is necessary to control the sedimentary pollutants. The Niulan River watershed was also influenced by natural environment factors. Among those, mineral, sedimentary pollutant, and meteorological sources contributed the most to water quality. In the case of the Yalong River watershed, the influence of non-point source pollution caused by human activities and sedimentary pollutants was the main reason for the deterioration of the ecological environment. The multivariate statistical techniques presented good adaptability for the analysis of pollution sources in the Jinsha River watershed, and the results may be useful for the protection and management of the watershed eco-environment.
作为长江上游，金沙江流域由于人类活动的增加，经历了生态退化。本研究采用改进的方法，结合相关分析和绝对主成分得分-多元线性回归受体模型技术，调查了 2016 年至 2018 年影响金沙江流域的潜在污染源。结果表明，金沙江干流流域和金沙江支流普渡河、牛栏江、雅砻江流域存在 5-7 个潜在污染源。金沙江干流流域的水污染浓度主要受环境、农业和人口因素的影响。在普渡河流域，主要污染源变为自然和沉积物污染源，有必要控制沉积物污染物。牛栏江流域也受到自然环境因素的影响，其中矿物、沉积物污染物和气象源对水质的贡献最大。在雅砻江流域，人类活动和沉积物污染物引起的非点源污染的影响是生态环境恶化的主要原因。多元统计技术对金沙江流域污染源分析具有良好的适应性，研究结果可为流域生态环境的保护和管理提供参考。
