Evaluation and estimation of water quality based on EEMs-PARAFAC and optical indices in the Bohai Rim

文献类型： 外文期刊

第一作者： Liu, Shukai

作者： Liu, Shukai;Su, Rongguo;Liu, Ke;Zheng, Nan;Zhao, Wenkui;Zhang, Haibo;Wu, Jinpeng;Sun, Peng;Bai, Ying;Zhang, Haibo

作者机构：

关键词： Nutrient; Bohai Sea; Optical indices; Water quality; Dissolved organic matter

期刊名称：JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING （ 影响因子：7.2； 五年影响因子：7.6 ）

ISSN： 2213-2929

年卷期： 2025 年 13 卷 4 期

页码：

收录情况： SCI

摘要： The input of dissolved organic matter (DOM) from rivers significantly influences the water quality of marine aquatic ecosystems, making DOM a valuable indicator of water pollution. The Bohai Sea (BS), an enclosed inland sea, lacks comprehensive studies on the relationship between DOM optical characteristics and water quality. This study investigates DOM distribution and nutrient concentrations in the BS and its four basins, which include 32 inflow rivers. The relationship among DOM and water quality was analyzed using partial least squares regression (PLSR) and support vector machine (SVM) models. The results revealed relatively high total nitrogen and total phosphorus pollutant content in the Yellow River Basin (YRB) and Liaohe Rivers Basin (LIRB), indicating that YRB transports more nitrogen and phosphorus pollutants to BS. Excitation-emission matrix spectroscopy combined with parallel factor analysis (EEMs-PARFAC) identified two terrestrial humic-like substances (C1, C3) and one protein-like substance (C2). Pearson correlation analysis revealed significant correlations between fluorescent components, optical indices, including humification index (HIX), absorption coefficient at 350 nm (a350), molecular weight (E2/E3), biological index (BIX) and fluorescence index (FI) with water quality parameters. PLSR and SVM further confirmed that a350, C1 and HIX were excellent parameters for predicting water quality, particularly NO3--N, dissolved inorganic nitrogen (DIN), TN, and TP, with fitting coefficients greater than 0.83. This study connects various DOM optical indices with water quality parameters, emphasizing the considerable potential of DOM in monitoring and predicting water quality. The results contribute to understanding the biogeochemical role of DOM and provide an effective method for water quality monitoring.

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