西安市典型景观湖泊沉积物中溶解性有机物和重金属的分布特征及其源解析

Distribution characteristics and source apportionment of dissolved organic matter and heavy metals in sediment from typical landscape lakes in Xi’an

关键词:  沉积物  溶解性有机物  重金属  荧光特性  源解析  PMF模型

Key words:  sediment  dissolved organic matter  heavy metals  fluorescent characteristic  source apportionment  PMF model

摘要:

城市中典型水体的有机物和重金属污染与人类活动息息相关，开展来源解析研究有助于水体综合治理和提升生态景观服务功能。文章以西安市15个典型公园景观湖泊为研究对象，分析了湖泊沉积物中溶解性有机物（DOM）光谱及重金属含量分布特征，利用正定矩阵因子（PMF）和平行因子分析进行了源解析。结果显示，沉积物中Zn、Cu、As和Hg都有明显的富集，这3种DOM荧光组分分别对应于陆源类腐殖酸 （C1）、类色氨酸类物质 （C2） 和内源产生的类酪氨酸类物质 （C3）。所有湖泊沉积物中，C2 和C3的占比均明显高于C1，其中浐灞水系公园组A3 （雁鸣湖、桃花潭、西安世博园和浐灞湿地公园） 水体中C3最多，城市公园组A4（丰庆公园、长乐公园、莲湖公园和革命公园）中C2最多。PMF分析获得4个污染来源因子，分别表征内生污水源、大气源、陆源和混合源。城市公园组A1 （大明宫太液池、 兴庆公园、大唐芙蓉园和曲江池）内生污水源和陆源贡献均较大，沣潏水系公园组A2（汉城湖、长安公园和樊川公园）主要污染为陆源和内生污水源，浐灞水系公园组A3的内生污水源贡献较大，城市公园组 A4以陆源污染为主。研究结果明晰了西安市典型景观水体污染现状和污染物来源，为进一步开展水体污染综合治理提供了关键数据。

Abstract:

Background, aim, and scope Organic matter and heavy metal pollution in typical urban water bodies are closely associated with anthropogenic activities. Sediments act as an important sink for various pollutants in urban aquatic systems. Source apportionment studies of sediments contribute to the comprehensive management of urban water quality and help enhance the ecological service functions of aquatic landscapes. Positive Matrix Factorization (PMF) is an important method for the source apportionment of heavy metals in sediments; however, relying solely on individual metal elements to infer pollution sources involves considerable uncertainty. The spectral characteristics of dissolved organic matter (DOM) are commonly used to distinguish between nonpoint and point sources of pollution. Integrating heavy metal concentrations with DOM spectral characteristics in PMF analysis is expected to improve the reliability of source apportionment. Materials and methods Fifteen typical park lakes in Xi’an were selected for this study. Based on their water supply sources, the lakes were divided into four groups: Urban Park Group A1 (Daming Palace Taiye Pool, Xingqing Park, Tang Paradise, and Qujiang Pool); Fengyu Water System Park Group A2 (Hancheng Lake, Chang’an Park, and Fanchuan Park); Chanba Water System Park Group A3 (Yanming Lake, Taohua Pool, Xi’an Expo Park, and Chanba Wetland Park); and Urban Park Group A4 (Fengqing Park, Changle Park, Lianhu Park, and Revolution Park). Water and sediment samples were collected from each sampling site in the park lakes in January 2023. Sampling locations were arranged along the direction of water flow within each lake. Specifically, two sampling sites were established in Yanming Lake and Changle Park, while three sites per lake were established in the remaining lakes. The spectral characteristics of DOM and the distribution patterns of heavy metals in lake sediments were investigated using UV-Vis spectroscopy and excitation-emission matrix spectroscopy combined with parallel factor analysis (EEM-PARAFAC). Furthermore, source apportionment was conducted using the PMF model by integrating fluorescence components, spectral parameters, and heavy metal concentrations. Results The enrichment of heavy metals, particularly Zn, Cu, As, and Hg, was observed in the studied sediments. PARAFAC identified three fluorescence components: terrestrial humic-like substances (C1), tryptophan-like substances (C2), and tyrosinelike substances (C3), which are associated with sewage inputs and endogenous sources. Ultraviolet spectral parameters and EEM parameters indicated that sediment DOM was mainly influenced by terrestrial inputs and endogenous sources. Discussion The PMF analysis resolved four pollution source factors. In all lakes, the proportions of C2 and C3 were higher than that of C1. C3 was the dominant component in the Group A3, whereas C2 was the largest component in the Group A4. Factors 1—4 represent endogenous and sewage sources, atmospheric deposition sources, terrestrial sources, and mixed sources, respectively. Specifically, the Group A1 shows significant contributions from endogenous/sewage and terrestrial sources. The Group A2 is mainly influenced by non-point and sewage sources. The contributions of sewage and endogenous sources are prominent in the Group A3, while the Group A4 is primarily characterized by terrestrial sources. Conclusions This study elucidates the pollution status and source characteristics of typical landscape lakes in Xi’an and provides important data for integrated water pollution management. Furthermore, the results indicate that coupling DOM fluorescence characteristics with heavy metal concentrations in PMF analysis can improve the reliability of pollution source apportionment. Recommendations and perspectives The PMF model is applied to analyze the contributions of DOM characteristics, heavy metals, and pollution sources in sediments from typical landscape lakes in Xi’an. The results are consistent with the environmental conditions of each lake. This integrated approach can be applied to other water bodies to improve the accuracy of PMF-based source apportionment.