Abstract
Agriculture emerges as a prominent contributor to CH(4) and N(2)O emissions in China. However, estimates of these two non-CO(2) greenhouse gases (GHGs) remain poorly constrained, hindering a precise understanding of their spatiotemporal dynamics and the development of effective mitigation strategies. Here, we established a consistent estimation framework that integrates emission-factor approach, data-driven models and process-based biogeochemical models, to identify the magnitudes, spatial variations, and long-term trends of agricultural non-CO(2) GHG emissions in China's mainland from 1980 to 2023. Over the study period, the average total agricultural non-CO(2) GHG emissions amounted to 722.5 ± 102.3 Tg CO(2)-eq yr(-1), with livestock CH(4), cropland CH(4), cropland N(2)O and livestock N(2)O contributing 41% (297.4 ± 64.3 Tg CO(2)-eq yr(-1)), 31% (225.0 ± 69.6 Tg CO(2)-eq yr(-1)), 18% (130.6 ± 9.4 Tg CO(2)-eq yr(-1)) and 10% (69.4 ± 20.2 Tg CO(2)-eq yr(-1)), respectively. Approximately 70% of these emissions were concentrated in the eastern region beyond the Hu Line, with emission hotspots identified in South-central China, East China, and the Sichuan Basin. Our analysis revealed three distinct temporal stages of total emissions during the study period: rapid growth (1980-late 1990s), slow growth (late 1990s-middle 2010s), and a stabilization stage (since the middle 2010s). These stages reflect the evolving trajectory of agriculture in China, from the expansion of agricultural yields, to the transformation of agricultural practices, and ultimately the pursuit of sustainable development. However, the temporal trajectory of emissions varied significantly across different regions, highlighting divergent levels of agricultural development. This study presents a comprehensive, gridded, and consistent estimate of agricultural non-CO(2) GHG emissions in China, offering valuable insights for policymakers to develop tailored strategies that adapt to local conditions, enabling effective emission reduction measures.