Cao Meixian, Hu Anyi, Gad Mahmoud, Adyari Bob, Qin Dan, Zhang Lanping, Sun Qian, Yu Chang-Ping
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Sci Total Environ. 2022 Jun 1;823:153680. doi: 10.1016/j.scitotenv.2022.153680. Epub 2022 Feb 10.
Excessive quantities of nitrates in the aquatic environment can cause eutrophication and raise water safety concerns. Therefore, identification of the sources of nitrate is crucial to mitigate nitrate pollution and for better management of the water resources. Here, the spatiotemporal variations and sources of nitrate were investigated by stable isotopes (δN and δO), hydrogeochemical variables (e.g., NO and Cl), and exogenous microbial signals (i.e., sediments, soils, domestic and swine sewage) in an agricultural watershed (Changle River watershed) in China. The concentration ranges of δN- and δO-NO between 3.03‰-18.97‰ and -1.55‰-16.47‰, respectively, suggested that soil nitrogen, chemical fertilizers, and manure and sewage (M&S) were the primary nitrate sources. Bayesian isotopic mixing model suggested that the major proportion of nitrate within the watershed (53.12 ± 10.40% and 63.81 ± 15.08%) and tributaries (64.43 ± 5.03% and 76.20 ± 4.34%) were contributed by M&S in dry and wet seasons, respectively. Community-based microbial source tracking (MST) showed that untreated and treated domestic wastewater was the major source (>70%) of river microbiota. Redundancy analysis with the incorporation of land use, hydrogeochemical variables, dual stable isotope, and exogenous microbial signals revealed domestic wastewater as the dominant cause of nitrate pollution. Altogether, this study not only identifies and quantifies the spatiotemporal variations in nitrate sources in the study area but also provides a new analytical framework by combining nitrate isotopic signatures and community-based MST approaches for source appointment of nitrate in other polluted watersheds.
水环境中过量的硝酸盐会导致富营养化，并引发对水安全的担忧。因此，识别硝酸盐的来源对于减轻硝酸盐污染和更好地管理水资源至关重要。在此，通过稳定同位素（δN和δO）、水文地球化学变量（如NO和Cl）以及外源微生物信号（即沉积物、土壤、生活污水和猪粪污水），对中国一个农业流域（长乐河流域）的硝酸盐时空变化和来源进行了调查。δN-NO和δO-NO的浓度范围分别在3.03‰-18.97‰和-1.55‰-16.47‰之间，这表明土壤氮、化肥以及粪肥和污水（M&S）是主要的硝酸盐来源。贝叶斯同位素混合模型表明，流域内（分别为53.12±10.40%和63.81±15.08%）和支流中（分别为64.43±5.03%和76.20±4.34%）硝酸盐的主要比例在旱季和雨季分别由M&S贡献。基于群落的微生物源追踪（MST）表明，未经处理和处理后的生活污水是河流微生物群的主要来源（>70%）。结合土地利用、水文地球化学变量、双稳定同位素和外源微生物信号进行的冗余分析表明，生活污水是硝酸盐污染的主要原因。总之，本研究不仅识别并量化了研究区域内硝酸盐来源的时空变化，还通过结合硝酸盐同位素特征和基于群落的MST方法，为其他污染流域的硝酸盐源确定提供了一个新的分析框架。
