Direct nitrous oxide (N2O) emissions (DNEs) from croplands are required in national inventories of greenhouse gases. The Intergovernmental Panel on Climate Change (IPCC) guidelines provide an approach using direct emission factors (EFds) to estimate DNEs, which are constants for large regions. The goal of this paper is to establish empirical models to account for the temporal and spatial variations of EFds, which, apart from the nitrogen addition rate, also vary with a range of environmental factors, so as to enhance the accuracy of regional/national DNE estimates. Therefore, the seasonal/annual DNEs (n = 71) from upland croplands, which are the differences in N2O emissions between fields with and without fertilizer-nitrogen addition, were used to statistically relate DNEs to regulating factors including the fertilizer-nitrogen addition rate (Fn), and environmental (climate and soil) factors. The multivariate stepwise linear regression results showed positive combined effects of Fn and clay fraction on DNEs (R2 = 0.61, p < 0.001). Furthermore, the nonlinear regression of Fn, precipitation, and clay fraction was also adopted for prediction (R2 = 0.50, p < 0.001). Validation with an independent dataset (n = 31) suggested that both models were better predictors of DNEs than the IPCC model, which only depends on Fn. These empirical models may provide simple but reliable approaches for compiling regional/national, and even global inventories of DNEs from croplands. However, both models were restricted to a limited sample size. Understandably, more field observations are still required to further validate the global applicability of these simple approaches.
N2O是重要的温室气体，IPCC推荐的排放因子法是估算区域农田N2O直接排放（DNE）的主要方法，该方法仅考虑施肥量的影响。本研究利用观测数据，分析DNE与施肥量、气象和土壤等因子的经验关系，构建农田DNE经验模型，旨在更好地描述DNE的时空变异性。逐步线性回归结果显示，除施肥量外，土壤黏粒含量也是影响DNE的关键因子（R2 = 0.61, p < 0.001）。非线性回归结果显示，施肥量、降水量和黏粒含量共同影响DNE（R2 = 0.50, p < 0.001）。与IPCC排放因子法相比，本研究建立的经验回归模型表现出更好的预测能力。