Spatiotemporal variation characteristics and source identification of water pollution: Insights from urban water system

The ongoing expanding urban area had caused multiple sources of water quality degression issues and restrained the green development in many large cities. Identifing the pollution sources of water contamination during no rainy days and rainfall events in the urban-rural marginal catchment efficiently supports regulating and controlling water pollution. In this study, the spatiotemporal variation characteristics of the water pollution were analyzed and the pollution sources during no rainy days and rainfall events were identified based on an integrated framework of the urban water system. A case study was conducted using two receptor models in an ongoing expanding urban-rural marginal catchment in the Qingshan District, Wuhan City, China. Results revealed that the expansion of the urban area significantly varied the water quality. The positive matrix factorization (PMF) model was more convincing and provided more sources than the principal component analysis-multiple linear regressions (PCA-MLR) model. Receptor models also verified that the dominated sources were changed between urban, urban-rural and rural areas although non-point sources were the main pollution source (56.7 ~ 71.9%). The runoff and land surface dusk, with contributions of 39.1 ~ 41.7%, were the prioritized pollution sources for both the urban-rural and urban areas due to the heavily constructive activities and industrial emissions. However, the industrial factor and land surface dusk (42.4%) dominated the pollution sources of rural area. During the rainfall events, the runoff factor and the residential factor (39.3 ~ 45.9%) governed the main pollution sources in both urban and urban-rural areas. The study results provide the scientific basis for supporting the treatment of targeted pollution sources and improving water quality in the urban-rural marginal catchment.

Automated summary

Urban expansion has led to diverse sources of water quality degradation and hindered green development in many major cities. This study efficiently identified pollution sources during no rainy days and rainfall events in an urban-rural marginal catchment, using an integrated framework of the urban water system. The findings revealed significant variations in water quality due to urban area expansion. The positive matrix factorization (PMF) model provided more convincing sources compared to the principal component analysis-multiple linear regressions (PCA-MLR) model. The study emphasized the need to regulate and control pollution sources in order to improve water quality in the urban-rural marginal catchment.