Updating and refining the N 2 O emission factors (N 2 O-EFs) are vital to reduce the uncertainty in estimates of direct N 2 O emissions. Based on a database with 1151 field measurements across China, the N 2 O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N 2 O-EFs. The third method had the highest R 2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N 2 O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N 2 O-EFs in maize and wheat seasons than other regions, and the highest N 2 O-EFs of 0.66–0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N 2 O-EFs. Based on the best estimation by the selected method, direct N 2 O emissions from China’s crop cultivation were estimated to be 194 Gg N 2 O–N with a 95% confidence interval of 180–208 Gg N 2 O–N in the year 2016.
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Qian et al. (2019) studied this question.
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