基于水质分组和水化学特征对秦淮河污染源的分析

Analysis of pollution sources in Qinhuai River based on water quality grouping and hydrochemical characteristics

摘要

【目的】为识别高度城市化流域中典型河段的主要污染来源，提升城市河流水质管理的科学性与精准性，以秦淮河流域为研究对象，结合溶解性有机物(DOM)荧光光谱特征和水化学参数，构建污染源解析与水质关联评价框架。【方法】对秦淮河干支流典型断面的水样采用三维荧光光谱平行因子分析提取DOM荧光组分，并结合SUVA₂₅₄、光谱斜率(S_R)等光谱指数解析其来源特征。同时测定样品中钾、钙、钠、镁等阳离子及其余水质指标，与水质综合指数(WQI)关联分析，以探讨多源污染驱动下河流水质演变规律。【结果】结果表明：荧光组分C1—C4分别与地表径流、污水排放和沉积物释放相关联，其中C3在污水排放点附近显著升高，C4反映沉积物内源释放，C2则呈现多源复合特征。DOM光谱指数间相关性不显著，反映内源DOM对荧光信号干扰强烈，限制其独立用于污染源识别的能力。水化学分析显示，阳离子浓度与水质状况呈负相关，四种离子浓度在WQI较低区域同步升高，表明污水浓缩效应主导其分布。钠离子与硝氮呈显著正相关，结合污水厂排放监测数据，表明污水处理厂尾水为流域总氮的主要来源。【结论】DOM光谱特征与水化学指标联合分析有助于识别城市河流的主要污染类型和驱动因子，可为城市河流精细化污染治理和分区施策提供技术支撑。

Abstract

[Objective] To identify the major pollution sources in typical river sections within highly urbanized watersheds and enhance the scientific and precise management of urban river water quality, the Qinhuai River Basin in Nanjing was selected as a case study. By integrating the fluorescence characteristics of dissolved organic matter(DOM) with hydrochemical parameters, an evaluation framework is developed for pollution source analysis and water quality correlation.[Methods] Water samples from typical cross-sections of the main and tributary channels of the Qinhuai River were analyzed using three-dimensional excitation-emission matrix(EEM) fluorescence spectroscopy combined with parallel factor analysis(PARAFAC) to extract DOM fluorescent components. Fluorescence indices such as SUVA254 and spectral slope(S_R) were used to further interpret their source characteristics. Meanwhile, cations(K⁺, Ca²⁺, Na⁺, Mg²⁺) and other water quality indicators were measured, and the correlation analysis with the water quality index(WQI) was conducted to explore the evolution patterns of river water quality under multi-source pollution.[Results] The result showed that the fluorescent components C1—C4 were associated with surface runoff, sewage discharge, and sediment release, respectively. Among them, C3 was significantly elevated near sewage discharge points, C4 indicated endogenous release from sediments, and C2 showed composite characteristics of multiple sources. No significant correlations were observed among DOM spectral indices, suggesting strong interference from endogenous DOM on fluorescence signals, which limited their ability to be used independently for pollution source identification. Hydrochemical analysis revealed a negative correlation between cation concentrations and water quality conditions. The concentrations of the four ions synchronously increased in regions with low WQI, indicating that sewage concentration effects dominated their distribution. A significant positive correlation was observed between Na⁺ and NO^-₃-N. Combined with effluent monitoring data from sewage treatment plants, this indicated that the tailwater of sewage treatment plants was the primary source of total nitrogen in the watershed.[Conclusion] The combined analysis of DOM spectral characteristics and hydrochemical indicators helps identify key pollution types and driving factors in urban rivers, providing technical support for refined pollution control and zoned management strategies in urban river systems.

关键词

城市河流 / 污染物来源 / 水质综合指数 / 溶解性有机物 / 阳离子浓度 / 三维荧光光谱 / 污染源解析 / 城市水治理

Key words

urban rivers / pollution source / water quality composite index / dissolved organic matter / cation concentration / three-dimensional fluorescence spectroscopy / source apportionment / urban water governance

基金资助

国家自然科学基金青年项目(32301373)

常州工业职业技术学院博士基金项目(BS202313101004)