Functional-Area-Based Spatial Variability and Source Apportionment of Urban Rainfall Runoff Pollution: Implications for Sustainable Water Management and Urban Resilience in China

Abstract

Rainfall–runoff pollution poses a major challenge to urban water quality management, particularly in rapidly developing regions. However, its spatial variability and source characteristics remain inadequately understood. This study investigates the types, concentrations, and sources of pollutants in rainfall runoff across different urban land-use settings, with the aim of providing insights for more effective water management strategies. By quantifying pollutant occurrence frequencies, comparing reported event mean concentrations, and summarizing literature-reported pollution sources, we evaluated the spatial heterogeneity of runoff contamination from a descriptive perspective. The compiled literature data showed descriptive differences in reported pollution levels among land-use types, with relatively high pollutant concentrations frequently reported in residential and traffic areas. These differences should be interpreted as functional-area-based patterns rather than continuous geographic spatial distributions. Pollutants such as chemical oxygen demand (COD), suspended solids (SS), and total nitrogen (TN) frequently exceeded China’s Class V surface water quality standards. Atmospheric deposition and surface litter were the most frequently reported pollution sources, while traffic-related activities were frequently associated with elevated heavy metal concentrations in the reviewed studies. These findings underscore the urgent need for targeted, land-use-specific pollution control strategies that not only reduce runoff pollution but also improve source-control efficiency for sustainable urban water management. This study offers valuable insights that may be transferable to other urban environments worldwide, with important implications for policy development and urban resilience in the face of increasing environmental pressures.