Agricultural soils are the most important anthropogenic source of nitrous oxide (N₂O) emissions. This occurs via two main pathways: (1) from microbial-mediated oxidation of ammonium to nitrite and nitrate; and (2) denitrification. Most agro-ecological models explicitly deal with these two pathways albeit with different degrees of process understanding and empiricism. Models that integrate the impact of multiple environmental factors on N₂O emissions can provide estimates of N₂O fluxes from complex agricultural systems. However, uncertainties in model predictions arise from differences in the algorithms, imperfect quantification of the nitrification and denitrification response to edaphic conditions, and the spatial and temporal variability of N₂O fluxes resulting from variable soil conditions. This study compared N₂O responses to environmental factors in six agro-ecological models. The comparisons showed that environmental factors impact nitrification and denitrification differently in each model. Reasons include the inability to apportion the total N₂O flux to the specific N transformation rates used to validate and calibrate the simplifications represented in the model algorithms, and incomplete understanding of the multiple interactions between processes and modifying factors as these are generally not quantified in field experiments. Rather, N₂O flux data is reported as total or net N₂O emissions without attributing emissions to gross and/or net rates for specific N processes, or considering changes that occur between production and emissions. Additional measurements that quantify all processes understand the multiple interactions that affect N₂O emissions are needed to improve model algorithms and reduce the error associated with predicted emissions.

_{农业土壤是一氧化二氮 (N 2} O) 排放的最重要的人为来源。这通过两个主要途径发生：（1）从微生物介导的铵氧化为亚硝酸盐和硝酸盐；(2)反硝化。大多数农业生态模型明确处理这两种途径，尽管过程理解和经验主义的程度不同。_{综合多种环境因素对 N 2} O 排放的影响的模型可以提供复杂农业系统中N _{2 O 通量的估计值。}然而，模型预测的不确定性源于算法的差异、硝化作用和反硝化作用对土壤条件响应的不完善量化，以及 N 2 的时空变异_性土壤条件变化导致的 O 通量。本研究比较了六种农业生态模型中N _{2 O 对环境因素的响应。}比较表明，环境因素在每个模型中对硝化和反硝化的影响不同。原因包括无法将总 N ₂ O 通量分配给用于验证和校准模型算法中表示的简化的特定 N 转化率，以及对过程和修改因素之间的多重相互作用的不完全理解，因为这些通常没有量化现场实验。相反，N ₂ O 通量数据报告为总 N 2 或净 N ₂O 排放，不将排放归因于特定 N 过程的总排放率和/或净排放率，或考虑生产和排放之间发生的变化。_{量化所有过程的额外测量了解影响 N 2} O 排放的多种相互作用，需要改进模型算法并减少与预测排放相关的误差。