Weakened growth of cropland N2O emissions in China associated with nationwide policy interventions

China has experienced rapid agricultural development over recent decades, accompanied by increased fertilizer consumption in croplands; yet, the trend and drivers of the associated nitrous oxide (N2O) emissions remain uncertain. The primary sources of this uncertainty are the coarse spatial variation of activity data and the incomplete model representation of N2O emissions in response to agricultural management. Here, we provide new data‐driven estimates of cropland‐N2O emissions across China in 1990–2014, compiled using a global cropland‐N2O flux observation dataset, nationwide survey‐based reconstruction of N‐fertilization and irrigation, and an updated nonlinear model. In addition, we have evaluated the drivers behind changing cropland‐N2O patterns using an index decomposition analysis approach. We find that China's annual cropland‐N2O emissions increased on average by 11.2 Gg N/year2 ( p < .001) from 1990 to 2003, after which emissions plateaued until 2014 (2.8 Gg N/year2, p = .02), consistent with the output from an ensemble of processbased terrestrial biosphere models. The slowdown of the increase in cropland‐N2O emissions after 2003 was pervasive across two thirds of China's sowing areas. This change was mainly driven by the nationwide reduction in N‐fertilizer applied per area, partially due to the prevalence of nationwide technological adoptions. This reduction has almost offset the N2O emissions induced by policy‐driven expansion of sowing areas, particularly in the Northeast Plain and the lower Yangtze River Basin. Our results underline the importance of high‐resolution activity data and adoption of nonlinear model of N2O emission for capturing cropland‐N2O emission changes. Improving the representation of policy interventions is also recommended for future projections.
Ключові слова
Agricultural management, agricultural soils, emission inventory, flux upscaling, land surface model, nitrous oxide, policy analysis, temporal trend
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