College of Environmental & Resource Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang Province, China.
Agriculture Ministry Key Laboratory of Healthy Freshwater Aquaculture, Key Laboratory of Fish Health and Nutrition of Zhejiang Province, Zhejiang Institute of Freshwater Fisheries, Huzhou, 313001, China.
Environ Sci Pollut Res Int. 2022 Nov;29(55):82903-82916. doi: 10.1007/s11356-022-21116-x. Epub 2022 Jun 27.
Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes ([Formula: see text] and [Formula: see text]) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine [Formula: see text] in the Cao'e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.
沿海河流向近岸海域输送了大部分人为氮（N）负荷，往往导致富营养化和缺氧区的形成。准确识别氮源对于优化沿海河流氮污染控制策略至关重要。本研究基于两年的双稳定同位素（[Formula: see text]和[Formula: see text]）季节记录和水质参数，结合双稳定同位素混合稳定同位素示踪模型（MixSIAR）和绝对主成分得分-多元线性回归（APCS-MLR）模型，阐明了杭州湾两条沿海河流的氮动态和氮源。水质/营养水平指数表明，所研究河流处于轻度至中度富营养化状态。水质的时空变异性与季节性农业、水产养殖和生活污水活动以及季节性降水模式有关。APCS-MLR 模型确定土壤+生活污水（69.5%）和水产养殖尾水（22.2%）为主要氮污染源。双稳定同位素混合稳定同位素示踪模型确定土壤氮、水产养殖尾水、生活污水和大气沉降氮对曹娥河（CER）[Formula: see text]的贡献分别为 35.3±21.1%、29.7±17.2%、27.9±14.5%和 7.2±11.4%，对尖塘河（JTR）的贡献分别为 34.4±21.3%、29.5±17.2%、27.4±14.7%和 8.7±12.8%。APCS-MLR 模型和双稳定同位素混合稳定同位素示踪模型在河流氮源识别方面的结果一致。将这两种方法结合起来进行河流氮源识别，可以有效地将 APCS-MLR 方法中的混合源成分区分开来，并减轻稳定同位素分析的高成本，从而以较低的水质采样和同位素分析成本提供可靠的氮源分配结果。本研究强调了土壤氮管理和水产养殖尾水处理在沿海河流氮污染控制中的重要性。
