School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu province 210023, China; Center for Water and Ecology, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu province 210023, China.
Sci Total Environ. 2022 Sep 10;838(Pt 1):155680. doi: 10.1016/j.scitotenv.2022.155680. Epub 2022 May 4.
Urban storm runoff, as the primary transport medium for nutrients entering urban rivers, contributes to urban water contamination. Accurate source identification is critical for controlling water pollution. Although some studies have used nitrate isotopic composition (δN-NO and δO-NO) to identify nitrate (NO-N) in urban storm runoff, the relatively low frequency of collecting samples in surface runoff within a single functional area hinders the understanding of spatial variations and dynamic process of NO-N sources over the runoff process. This study investigated the nitrogen (N) concentrations and analyzed dynamic changes of NO-N sources in surface runoff in different urban functional areas, drainage pipeline runoff, and channels during the complete runoff process in Wuxi, east China. The results showed that N concentrations in pipeline runoff and channels were higher than those in surface runoff, indicating that high concentration of N pollutants were accumulated in drainage pipelines. Information of δN-NO and δO-NO suggested that the main NO-N source varied between runoff stages. NO-N contribution from atmospheric deposition decreased in the order: surface runoff (57%) > residential pipeline runoff (25%) > channels (14%), while the opposite trend was observed for the contributions from sewage, increasing from 10%, 26% to 39%. In urban storm runoff, more sewage, fertilizers, and soil N were carried into the surface runoff after 30% of cumulative runoff ratio and carried into pipeline runoff in the initial 25% of cumulative runoff ratio in the residential area. As the first attempt to identify nitrate sources over the cumulative runoff in different urban functional areas, this work expands our understanding of the primary nitrate source in urban storm runoff. The findings provide important insights for developing strategies to mitigate non-point source water pollution.
城市暴雨径流作为营养物质进入城市河流的主要输送介质，导致了城市水环境污染。准确的源识别对于控制水污染至关重要。尽管一些研究已经使用硝酸盐同位素组成（δN-NO 和 δO-NO）来识别城市暴雨径流中的硝酸盐（NO-N），但在单个功能区的地表径流中采集样本的频率相对较低，这阻碍了对 NO-N 来源在径流过程中的空间变化和动态过程的理解。本研究调查了氮（N）浓度，并分析了中国东部无锡不同城市功能区地表径流、排水管道径流和河道在整个径流过程中 NO-N 来源的动态变化。结果表明，管道径流和河道中的 N 浓度高于地表径流，表明排水管道中积累了高浓度的 N 污染物。δN-NO 和 δO-NO 的信息表明，主要的 NO-N 源在径流阶段之间有所不同。大气沉降的 NO-N 贡献按地表径流（57%）> 住宅管道径流（25%）> 河道（14%）的顺序减少，而污水的贡献则呈相反趋势，从 10%、26%增加到 39%。在城市暴雨径流中，更多的污水、肥料和土壤 N 在累积径流比达到 30%后被带入地表径流，而在住宅区累积径流比达到 25%的初期则被带入管道径流。作为首次尝试在不同城市功能区的累积径流中识别硝酸盐源，这项工作扩展了我们对城市暴雨径流中主要硝酸盐源的认识。研究结果为制定减轻非点源水污染的策略提供了重要的见解。
