硝酸盐
环境化学
环境科学
分摊
污染
灵敏度(控制系统)
同位素分析
环境工程
化学
生态学
工程类
地质学
海洋学
有机化学
法学
生物
电子工程
政治学
作者
Xiaoliang Ji,Lielin Shu,Wenli Chen,Zheng Chen,Xu Shang,Yue Yang,Randy Alan Dahlgren,Minghua Zhang
标识
DOI:10.1016/j.jhazmat.2022.129480
摘要
Nitrate pollution is of considerable global concern as a threat to human health and aquatic ecosystems. Nowadays, δ15N/δ18O-NO3- combined with a Bayesian-based SIAR model are widely used to identify riverine nitrate sources. However, little is known regarding the effect of variations in pollution source isotopic composition on nitrate source contributions. Herein, we used δ15N/δ18O-NO3-, SIAR modeling, probability statistical analysis and a perturbing method to quantify the contributions and uncertainties of riverine nitrate sources in the Wen-Rui Tang River of China and to further investigate the model sensitivity of each nitrate source. The SIAR model confirmed municipal sewage (MS) as the major nitrate source (58.5-75.7%). Nitrogen fertilizer (NF, 8.6-20.9%) and soil nitrogen (SN, 7.8-20.1%) were also identified as secondary nitrate sources, while atmospheric deposition (AD, <0.1-7.9%) was a minor source. Uncertainties associated with NF (UI90 = 0.32) and SN (UI90 = 0.30) were high, whereas those associated with MS (UI90 = 0.14) were moderate and AD low (UI90 = 0.0087). A sensitivity analysis was performed for the SIAR modeling and indicated that the isotopic composition of the predominant source (i.e., MS in this study) had the strongest effect on the overall riverine nitrate source apportionment results.
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