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京杭运河上游河段磷污染时空分布特征及污染源解析
引用本文:金梦,兰亚琼,丁淼,等.京杭运河上游河段磷污染时空分布特征及污染源解析[J].环境工程技术学报,2024,14(1):43-51 doi: 10.12153/j.issn.1674-991X.20230546
作者姓名:金梦  兰亚琼  丁淼  嵇春红  刘锐
作者单位:1.浙江省水质科学与技术重点实验室, 浙江清华长三角研究院生态环境研究所;;2.嘉兴市桐乡生态环境监测站
基金项目:浙江省科技创新领军人才项目(2020R52039);嘉兴市“创新嘉兴 优才支持计划”项目;长江生态环境保护修复城市驻点跟踪研究(2022-LHYJ-02-0503-02)
摘    要:

为揭示京杭运河上游桐乡段总磷浓度不能稳定达到GB 3838—2002《地表水环境质量标准》Ⅲ类标准的原因,在桐乡段干流布设24个采样点,入河支流布设18个采样点,开展水质加密监测,研究磷污染发生的时空变化规律;基于水质常规指标的主成分分析,以及各主成分因子中强载荷指标与三维荧光组分的相关性分析,对重点河段磷的主要污染源进行解析;并基于绝对主成分—多元线性回归模型,定量评价主要磷污染源的贡献率。结果表明:1)京杭运河上游桐乡段干流入境水总磷浓度为0.14~0.20 mg/L,沿程监测点5~7、9和21~24有明显变差趋势,最高浓度达0.40 mg/L;部分入河支流水质较差,总磷浓度达到0.44 mg/L。2)主成分分析得到3个主因子,因子1以氨氮、溶解态磷为主要载荷,与类蛋白质组分显著相关,代表生产生活污染;因子2以高锰酸盐指数、溶解态磷、颗粒态氮为主要载荷,与类腐殖质组分显著相关,代表农业源;因子3以颗粒态磷、颗粒态氮为主要载荷,与浊度显著相关,代表码头污染与底泥源。3)运河上游河段的磷污染主要发生在干流监测点5~7和9,主要为码头污染与底泥源,其在丰水期和平水期的贡献率分别为65.9%和31.8%;监测点21~24主要为农业源,其在丰水期和平水期的贡献率分别为34.0%和32.1%;此外,生产生活污染在丰水期也有较大影响,其对监测点5~7和9、21~24的贡献率分别为42.6%、31.8%。



关 键 词:磷污染   主成分分析(PCA)   绝对主成分—多元线性回归(APCS-MLR)   污染源解析   平原河网
收稿时间:2023-07-25
修稿时间:2023-08-22

Spatio-temporal distribution of phosphorus pollution in the upper reaches of Beijing-Hangzhou Canal and its source analysis
JIN M,LAN Y Q,DING M,et al.Spatio-temporal distribution of phosphorus pollution in the upper reaches of Beijing-Hangzhou Canal and its source analysis[J].Journal of Environmental Engineering Technology,2024,14(1):43-51 doi: 10.12153/j.issn.1674-991X.20230546
Authors:JIN Meng  LAN Yaqiong  DING Miao  JI Chunhong  LIU Rui
Affiliation:1. Zhejiang Provincial Key Laboratory of Water Science and Technology, Department of Environment in Yangtze Delta Region Institute of Tsinghua University of Zhejiang;;2. Tongxiang Eco-Environmental Monitoring Station of Jiaxing
Abstract:To reveal the reason why total phosphorus failed to consistently meet the Class Ⅲ standard of Environmental Quality Standards for Surface Water (GB 3838-2002) in Tongxiang segment of Beijing-Hangzhou Canal, 24 sampling sites were set up in Tongxiang section of the mainstream and 18 sampling sites were set up in the tributaries to carry out water quality monitoring and study the spatio-temporal changes of phosphorus pollution. The main sources of phosphorus pollution in key river segments were analyzed by the principal component analysis based on routine water quality indexes, and the correlation analysis of strong load index in each principal component factor and three-dimensional fluorescence component. The quantitative evaluation of the contribution of major pollution sources was conducted using the absolute principal component-multiple linear regression model. The research results revealed that the total phosphorus concentration originating from Tongxiang segment of Beijing-Hangzhou Canal's upper reaches was 0.14-0.20 mg/L, while the water quality along the monitoring sites 5-7, 9 and 21-24 tended to deteriorate significantly, with the highest concentration reaching 0.40 mg/L. Certain tributaries into the mainstream exhibited poor water quality, and the total phosphorus concentration reached 0.44 mg/L. Three main factors were obtained by the principal component analysis. Factor 1 was mainly loaded with ammonia nitrogen and dissolved phosphorus, and was significantly correlated with protein-like component, representing production and domestic pollution. Factor 2, with permanganate index, dissolved phosphorus and particulate nitrogen as the main loads, was significantly correlated with humic-like component, representing agricultural sources. Factor 3, with particulate phosphorus and nitrogen as the main loads, was significantly correlated with turbidity, representing the dock and sediment source. The phosphorus pollution in the upper reaches of the canal mainly occurred at the monitoring sites 5-7 and 9, mainly from the dock and sediment sources, with contribution rates of 65.9% and 31.8% during the high and flat water periods, respectively. At monitoring sites 21-24, agriculture was the primary source of phosphorus pollution, contributing at rates of 34.0% and 32.1% during the high and flat water periods, respectively. Furthermore, the production and domestic pollution exhibited a significant influence during the high water periods. The contribution rates of the prodution and domestic to the monitoring sites 5-7, 9 and 21-24 were 42.6% and 31.8%.
Keywords:phosphorus pollution  principal component analysis(PCA)  absolute principal component-multiple linear regression(APCS-MLR)  pollution source analysis  plain river network
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