The Institute of Municipal Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
Zhejiang University of Water Resources and Electric Power, Hangzhou, Zhejiang, China.
Environ Res. 2021 Jun;197:111022. doi: 10.1016/j.envres.2021.111022. Epub 2021 Mar 18.
Multiple sources contribute to nitrogen(N) and phosphorus (P) pollution in lowland urban rivers, and apportioning the sources of N and P pollution is essential for improving the ecological health of urban environments. Three urban polders in Jiaxing were selected to investigate the temporal variations of N and P pollutants in lowland urban river waters under dry and wet conditions. Moreover, the main potential sources of N and P pollution were identified through the correlations of pollutants and components of dissolved organic matter (DOM) derived from excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC). The results indicate that the main pollution sources identified with PCA method were consistent with the potential sources revealed by DOM's EEM-PARAFAC components. Furthermore, absolute principal components score combined with multivariate linear regression (APCS-MLR) was conducted. The results illustrated that domestic wastewater contributes more than 70% of N pollution and river-bottom sediments contribute more than 50% of P pollution under dry conditions. On the contrary, discharged water from the stormwater outlets contributes more than 41% of P and 75% of N under wet conditions. Specifically, about 48% of them come from domestic wastewater, and about 38% come from urban surface runoff. This study highlights the effectiveness of DOM components derived from EEM-PARAFAC in identifying the sources of N and P pollution and the PCA-APCS-MLR in apportioning the contributions of each potential pollution source in lowland urban rivers.
多个来源导致了低地城市河流中的氮（N）和磷（P）污染，因此，对 N 和 P 污染的来源进行分配对于改善城市环境的生态健康至关重要。本研究选择嘉兴的三个城市圩区，以调查干旱和湿润条件下低地城市河流水体中 N 和 P 污染物的时间变化。此外，通过污染物与来自激发-发射矩阵（EEM）和并行因子分析（PARAFAC）的溶解有机物质（DOM）成分的相关性，确定了 N 和 P 污染的主要潜在来源。结果表明，PCA 方法识别的主要污染源与 DOM 的 EEM-PARAFAC 成分揭示的潜在来源一致。此外，还进行了绝对主成分得分与多元线性回归（APCS-MLR）的组合分析。结果表明，在干旱条件下，生活污水对 N 污染的贡献超过 70%，而河底沉积物对 P 污染的贡献超过 50%。相反，在湿润条件下，雨水排放口排放的水对 P 的贡献超过 41%，对 N 的贡献超过 75%。具体而言，其中约 48%来自生活污水，约 38%来自城市地表径流。本研究强调了 EEM-PARAFAC 衍生的 DOM 成分在识别 N 和 P 污染来源方面的有效性，以及 PCA-APCS-MLR 在分配每个潜在污染源对低地城市河流的贡献方面的有效性。
