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暴雨期间秦淮河水质特征及其污染源解析

Water quality characteristics and pollution source analysis of Qinhuai River during rainstorm events

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为深入探究暴雨前后秦淮河的水质变化,对造成河道污染的污染源进行识别,对秦淮河 5个监测断面在无雨期和暴雨期的水质进行统计分析.文章利用箱线图和相关性分析对不同时期秦淮河水质指标的变化进行了分析;利用APCS-MLR和PMF模型对不同污染源的贡献率进行计算.结果表明,暴雨期,秦淮河的CODMn、NH4+-N和TN的浓度高于无雨期,其中NH4+-N的变化率最大,DO低于无雨期;相比无雨期,暴雨期下DO与CODMn、NH4+-N和TN的负相关性增加.APCS-MLR结果显示,暴雨期时,河道内源污染、城市面源污染、点源污染及未识别污染对秦淮河水质变化的贡献率分别为 61.239%、27.287%、7.739%及 3.735%;PMF模型结果显示,暴雨期时,河道内源污染、城市面源污染及点源污染对秦淮河水质变化的贡献率分别为 62.934%、23.489%及 13.577%.2种模型的结果相近,具有较高的准确性.该结果可为秦淮河暴雨期污染控制提供对策.
To investigate the change of water quality of Qinhuai River before and after rainstorm,identify the pollution source of river,and make statistical analysis of water quality of 5 monitoring sections of Qinhuai River in rainless period and rainstorm period.Box Plot and correlation analysis were used to compare the water quality indicators between no-rain periods and stormy periods.The APCS-MLR and PMF models were applied to estimate the absolute contribution rates of different pollution sources.The results of this research showed that during stormy periods,the concentrations of CODMn,NH4+-N and TN in Qinhuai River were higher than those in no-rain periods,among which NH4+-N had the largest change rate,increasing by 97.78%,while DO concentration was lower than that no-rain periods,decreasing by 40.49%.Compared with no-rain periods,the negative correlation between DO and CODMn,NH4+-N and TN increased during stormy periods,at the meantime the positive correlation between CODMn and NH4+-N and TN were even stronger.Moreover,APCS-MLR and PMF models were used to identify the sources of water pollution in the Qinhuai River during the stormy periods.The results of APCS-MLR showed that the main sources of pollution were internal sources(61.239%),urban runoff(27.287%),point sources(7.739%),and unidentified sources(3.735%).The results of PMF model showed that the contribution rates of river internal pollution,urban non-point pollution and point pollution to the water quality of Qinhuai River were 62.934%,23.489%and 13.577%,respectively.The results of the two models were similar and had high accuracy.The results could provide countermeasures for pollution control of Qinhuai River during rainstorm..

stormQinhuai RiverAPCS-MLRPMFpollutant sources

金辉、梁文伯、陈鸣、吕婷、金哲、杨小丽

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南京市生态环境保护科学研究院,南京 210023

东南大学土木工程学院,南京 211189

暴雨 秦淮河 绝对主成分-多元线性回归 正定矩阵因子分解 污染源

国家重点研发计划项目

2019YFD1100205

2024

环境保护科学
沈阳环境科学研究院

环境保护科学

CSTPCD
影响因子:0.469
ISSN:1004-6216
年,卷(期):2024.50(4)