Urban non-point source pollution is becoming a serious issue under the context of rapid urbanization and its impacts on surface hydrologic processes. The identification of non-point source risk areas and the effectiveness of source-control measures provides important first steps to improve the degrading aquatic environment but is challenged by the complex dynamics and variabilities of surface pollutants in urban environments. In this study, we investigate the spatial and temporal variabilities of non-point source pollution in a small urban catchment based on numerical simulations and in-situ samplings. Our results show that residential, industrial, and commercial land contribute to the most pollutant loadings and are the main constituents of the pollution risk area. Rainfall duration and intensity are the main factors in determining the temporal variations of urban non-point source pollution. There is no correlation between early drought days and pollution load. Numerical simulations show that it is more effective to increase urban vegetation coverage than to enhance road cleaning for effective non-surface pollution control. For enhanced road cleaning, it is more effective to improve the frequency of road cleaning than its efficiency. Our results provide important guidance for effective controls of non-point source pollution as well as the establishment of long-term surface pollutant monitoring network in complex urban environments.

Excessive nutrient input to surface water, including nitrate, exacerbates water eutrophication. Clarifying the proportions of different nitrate sources in the aquatic environment is critical for improving the polluted water. However, nitrate sources in river basins are very complex and not clearly understood. In this study, nitrogen concentrations and nitrate isotopic compositions were determined to estimate the spatiotemporal variation in nitrate sources in the Yuntaishan River basin, Nanjing, East China, from March 2019 to January 2020. The results showed that the concentrations of total nitrogen (TN), ammonium (NH₄⁺-N), and nitrate (NO₃⁻-N) changed in the ranges of 0.53–18.0 mg/L, 0.01–15.4 mg/L, and 0.06–9.3 mg/L, respectively, wherein NO₃⁻-N was the main nitrogen form. Higher nitrogen concentrations appeared in winter and in the downstream parts of the river. In the entire river basin, the NO₃⁻-N mainly originated from sewage (67%) and soil (26%), with clear spatial variations. NO₃⁻-N in the Yunba sub-watershed was mainly derived from sewage (78%), which was higher than that in other tributaries, i.e., Shengli River (44%) and Yangshan River (49%). This was due to the fact that that Shengli and Yangshan sub-watersheds were covered by urban areas and were equipped with a complete sewage treatment system. In addition, the contributions of sewage to NO₃⁻-N rose from 60% upstream to 86% downstream, suggesting the increasing influence of the point source of sewage. The results showed that 53% of NO₃⁻-N in the basin outlet originated from the point source of sewage near the M4 site. Sewage contributed 75% of NO₃⁻-N in the rainy season and 67% of NO₃⁻-N in the dry season, suggesting the weakly temporal variation. Our results highlight the spatiotemporal variations in sources of NO₃⁻-N. These results will aid in the development of measures needed to control nitrogen pollution in river basins.

Understanding spatio-temporal differences in nitrogen (N) transformation, transport and reduction rates in water bodies is critical to achieve effective mitigation of river eutrophication. We performed culture experiments in six rivers in the Taihu Basin using a custom made in-situ experimental apparatus. We investigated spatio-temporal differences in reduce processes and rates of different N forms and assessed the contribution of biological processes to dissolved inorganic N (DIN) reduce. Results showed that biological processes played a major role in N reduction in summer, while non-microbial processes were dominant in winter. We observed significant spatial and temporal differences in the studied mechanisms, with reduction rates of different N compounds being significantly higher in summer and autumn than spring and winter. Reduction rates ranged from 105.4 ± 25.3 to 1458.8 ± 98.4 mg·(m³·d)⁻¹ for total N, 33.1 ± 12.3 to 440.9 ± 33.1 mg·(m³·d)⁻¹ for ammonium, 56.3 ± 22.7 to 332.1 ± 61.9 mg·(m³·d)⁻¹ for nitrate and 0.4 ± 0.3 to 31.8 ± 9.0 mg·(m³·d)⁻¹ for nitrite across four seasons. Mean DIN reduction rates with and without microbial activity were 96.0 ± 46.4 mg·(m³·d)⁻¹ and 288.1 ± 67.8 mg·(m³·d)⁻¹, respectively, with microbial activity rates accounting for 29.7% of the DIN load and 2.2% of the N load. Results of correlation and principal component analysis showed that the main factors influencing N processing were the concentrations of different N forms and multiple environmental factors in spring, N concentrations, DO and pH in summer, N concentrations and water velocity in autumn and N concentrations in winter.