...
首页> 外文期刊>Soil Research >Modelling nitrous oxide emissions: comparing algorithms in six widely used agro-ecological models
【24h】

Modelling nitrous oxide emissions: comparing algorithms in six widely used agro-ecological models

机译:Modelling nitrous oxide emissions: comparing algorithms in six widely used agro-ecological models

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

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.
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号