Re-quantifying China’s N2O emissions from croplands
Monday, 14 December 2015
Poster Hall (Moscone South)
Reactive nitrogen (Nr) entering agricultural soils from fertilizer applications worldwide results into a 43%~63% of global anthropogenic N2O emissions (EDGAR, 2014; Saikawa et al., 2014; Tian et al., 2014). This contribution is likely to increase in countries with intensive agricultural systems such as China (Zhou et al., 2014). yet the patterns, trends, and the associated causes of Chinese emissions remains subject to large uncertainty; inventories of China’s total agricultural soils N2O emissions at present varied by ~150% (Zhou et al., 2015). The primary sources of this uncertainty are conflicting estimates of emission factors, nitrogen inputs, and the associated environmental conditions, yet none of previous estimates are based upon large-scale measurements and high-resolution activity data. Here, we re-quantify China’s N2O emissions from croplands from 1990 to 2012, including direct and indirect pathways, using updated and harmonized N input data, high-resolution environmental factors data, and a comprehensive dataset of global N2O observation networks. The spatially-variable emission factor, and leaching and runoff rates are derived by empirical upscaling of ground-based observations, but validated by ecosystem models and atmospheric inversions of N2O concentration data. N inputs, such as synthetic fertilizer, manure, crop residues, human excretion applied to croplands, are compiled at county-scale, and atmospheric N depositions are simulated by using LMDZ-OR-INCA atmospheric transport chemistry model that has been calibrated by Asian observation networks. We also develop the high-resolution datasets including landuse dynamics (1-km), SOC changes (0.1-deg), climates (0.1-deg), and irrigation rates (city-scale). Three main tasks have been performed in this study: i) the magnitude and spatiotemporal patterns of N2O emissions over China croplands from 1990 to 2012; ii) the attributions of anthropogenic causes of the spatial variations, interannual variability, temporal trends, and growth rates of China’s N2O emissions from croplands. Overall this study may broaden our knowledge of the nitrogen cycle model for agro-ecosystem, which is important for refining IPCC default values of emission factors and designing China’s N2O mitigation protocols.