Abstract:  N2O is an important greenhouse gas, and farmland is considered to be one of the major sources of its emission. Exploring the reduction potential of N2O not only provides theoretical and technical support for farmland carbon emission reduction measures, but also provides a scientific basis for the realization of China's "double carbon" goal. In order to reduce N2O emissions in Jilin Province, the denitrification-decomposition (DNDC) model was used for point simulation, result verification and sensitivity analysis based on the data of greenhouse gas emissions from Jilin University Functional Agriculture Base (Hunchun). At the same time, the N2O emissions were simulated from 1991 to 2020 under the conditions of corn planting in Jilin Province, its temporal and spatial characteristics were obtained, and the optimization measures for increasing corn production and reducing N2O emissions were proposed. The result shows that the DNDC model was effective in the simulation of N2O emissions from farmland in Jilin Province. Among all the  factors,  nitrogen fertilizer application rate had the greatest influence on N2O emission, followed by  organic fertilizer application rate, soil organic carbon content  also had a certain infulence on N2O emission,while temperature, rainfall and  proportion of straw returning to field had little influcence on N2O emission. As a result of corn cultivation, N2O emissions are highest in the west, middle in the central region and lowest in the east. In order to reasonably control N2O emissions from farmland in Jilin Province, different field management should be carried out in different regions, and the optimal nitrogen application rates are 400, 330 and 480 kg/hm2 with the best base to topdressing application ratios of 7∶3, 9∶1 and 9∶1 in the west, central and east, respectively. The proportion of straw returned to the field has little effect on N2O emissions. While maintaining production, reducing the mass fraction of organic carbon can decrease N2O emissions from agricultural land.

Key words: Jilin Province, farmland, N2O, reduction potential, corn yield, DNDC prediction, double carbon