Over the past two decades, agricultural nitrous oxide (N2O) emissions have increased significantly, further intensifying their impact on global warming. Accurate emission estimates are essential for developing effective N2O-mitigation strategies. However, the high-resolution, dynamic simulations of emissions and comprehensive analysis of their driving mechanisms in China remain unclear. In this study, we constructed a city-level agricultural N2O emission inventory covering 336 cities in China from 2000 to 2022 based on multi-source data and machine learning algorithms. Results demonstrate that China’s cropland N2O emissions averaged 390 Gg year−1 during 2000 and 2022, exhibiting sustained growth until 2016, followed by a 13% reduction driven by the nationwide Fertilizer Reduction Policy implementation. Maize, wheat, and rice are identified as the main sources of cropland N2O emissions. Spatially, higher N2O emission intensities were concentrated in eastern China, and hotspots were identified in the Huang-Huai-Hai Plain (5.23 kg ha−1) and the Middle-Lower Yangtze River Plain (2.95 kg ha−1). These emission patterns are primarily influenced by soil organic carbon, crop type, and fertilizer-management practices. This study provides robust data support and methodological basis for formulating agricultural mitigation policies.
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