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Development of marginal emission factors for N losses from agricultural soils with the DNDC-CAPRI meta-model

机译:利用DNDC-CAPRI元模型建立农业土壤氮素损失的边际排放因子

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The article discusses marginal emission factors for N losses from agricultural soils, with rape and wheat as examples, and presents results for EU15 as high-resolution maps and aggregated to Member State level. The results are generated by linking the economic model for the agricultural sector CAPRI (Common Agricultural Policy Regional Impact) with spatial down-scaling, and a statistical meta-model for the bio-physical model DNDC (DeNitrification-DeComposition). For a given agro-economic scenario, CAPRI supplies for each crop the crop share, yield and fertilizer application rate spatially downscaled to clusters of 1kmx1km grid cells. The results from CAPRI are processed by a meta-model of DNDC to estimate the local greenhouse gas emissions from the soil. DNDC is a dynamic process-oriented model, which estimates trace gas fluxes and nutrient turnover in agricultural soils. The fit of the regressions is typically very good (~0.95R po for the majority of the regressions), and all coefficients are significant at 99% probability. The meta-model allows a seamless integration between the economic and the bio-physical models, offering additional benefit such as the site-specific calibration of the bio-physical model ensuring the match between simulated and observed yield at the grid-level. The meta-model is used to calculate marginal emission factors for a 1kghap# increase of mineral N and manure fertilizer rates for rape and wheat, at different levels of fertilization. They show that for Western European farming practice, only a small fraction of extra nitrogen fertilizer would go into increased yields: most of it would be emitted to the environment. The largest spatial variability is observed for NO emissions. The derivation of marginal emission factors is just one of the many possible uses for the linked regionalized agro-economic and soil chemistry model, which exploits to a large extent both geo-referenced and regionally available statistical information at European scale.
机译:本文以油菜和小麦为例,讨论了农业土壤氮素损失的边际排放因子,并以高分辨率地图的形式展示了欧盟15国的结果,并汇总到了成员国层面。通过将农业部门CAPRI(共同农业政策区域影响)的经济模型与空间缩减以及生物物理模型DNDC(反硝化分解)的统计元模型联系起来,得出结果。对于给定的农业经济情景,CAPRI为每种作物提供的作物份额,产量和肥料施用率在空间上缩小为1kmx1km网格单元的集群。 CAPRI的结果由DNDC的元模型处理,以估算土壤中的局部温室气体排放量。 DNDC是一个动态的,面向过程的模型,该模型可以估算农业土壤中的痕量气体通量和养分转化。回归的拟合通常非常好(大多数回归为〜0.95R po),并且所有系数均以99%的概率显着。元模型允许经济模型和生物物理模型之间的无缝集成,从而提供额外的好处,例如生物物理模型的特定于现场的校准,可确保网格级别的模拟产量与观察到的产量之间的匹配。该元模型用于计算在不同施肥水平下,氮素每增加1kghap#对油菜和小麦的肥料氮肥利用率和氮肥的边际排放因子。他们表明,在西欧的农业实践中,只有一小部分额外的氮肥可以提高产量:大部分氮肥会排放到环境中。观察到NO排放的最大空间差异。边际排放因子的推导只是链接的区域化农业经济和土壤化学模型的许多可能用途之一,该模型在很大程度上利用了欧洲范围内的地理参考和区域可用的统计信息。

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