High-resolution gridded dataset of sectoral water pollution discharges in China from 2007 to 2022

High-resolution datasets of anthropogenic water pollution discharges are essential for characterizing pollution dynamics and informing targeted water quality management in rapidly developing regions. In China, however, available pollution source data are largely restricted to provincial scales and decadal timeframes from national censuses, limiting their utility for spatiotemporal analyses and policy evaluation. Here, we present the High-resolution Sectoral Water Pollution Discharge Dataset for mainland China, spanning 2007–2022 at annual temporal resolution and 30 arc-second (~1 km) spatial resolution. The dataset quantifies discharges of chemical oxygen demand (COD) and ammonium nitrogen (NH3-N) from five key sectors: urban residential, rural residential, industrial, crop farming, and livestock farming. The dataset is derived by integrating national pollution source statistics with multi-source geospatial data—including land-use maps, nighttime lights, livestock mapping, population distributions, and geocoded industrial enterprises—through a top-down downscaling framework that allocates provincial discharges to grid cells. Validation against city-level census data demonstrates strong agreement, while the resulting spatial and temporal patterns are consistent with observed water quality improvements and documented emission trends. This dataset provides a robust data resource for water quality modeling, pollution source attribution, and environmental policy assessment, enabling new insights into human–environment interactions across China’s river basins.