The prediction of nitrous oxide (N₂O) and of dinitrogen (N₂) emissions formed by biotic denitrification in soil is notoriously difficult due to challenges in capturing co-occurring processes at microscopic scales. N₂O production and reduction depend on the spatial extent of anoxic conditions in soil, which in turn are a function of oxygen (O₂) supply through diffusion and O₂ demand by respiration in the presence of an alternative electron acceptor (e.g. nitrate).This study aimed to explore controlling factors of complete denitrification in terms of N₂O and (N₂O + N₂) fluxes in repacked soils by taking micro-environmental conditions directly into account. This was achieved by measuring microscale oxygen saturation and estimating the anaerobic soil volume fraction (ansvf) based on internal air distribution measured with X-ray computed tomography (X-ray CT). O₂ supply and demand were explored systemically in a full factorial design with soil organic matter (SOM; 1.2 % and 4.5 %), aggregate size (2–4 and 4–8 mm), and water saturation (70 %, 83 %, and 95 % water-holding capacity, WHC) as factors. CO₂ and N₂O emissions were monitored with gas chromatography. The ¹⁵N gas flux method was used to estimate the N₂O reduction to N₂.N gas emissions could only be predicted well when explanatory variables for O₂ demand and O₂ supply were considered jointly. Combining CO₂ emission and ansvf as proxies for O₂ demand and supply resulted in 83 % explained variability in (N₂O + N₂) emissions and together with the denitrification product ratio [N₂O $/$ (N₂O + N₂)] (pr) 81 % in N₂O emissions. O₂ concentration measured by microsensors was a poor predictor due to the variability in O₂ over small distances combined with the small measurement volume of the microsensors. The substitution of predictors by independent, readily available proxies for O₂ demand (SOM) and O₂ supply (diffusivity) reduced the predictive power considerably (60 % and 66 % for N₂O and (N₂O+N₂) fluxes, respectively).The new approach of using X-ray CT imaging analysis to directly quantify soil structure in terms of ansvf in combination with N₂O and (N₂O + N₂) flux measurements opens up new perspectives to estimate complete denitrification in soil. This will also contribute to improving N₂O flux models and can help to develop mitigation strategies for N₂O fluxes and improve N use efficiency.

中文翻译：

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土壤中的反硝化作用与微量氧供应的关系

众所周知，由于在微观规模上捕获共生过程的挑战，很难预测由于土壤中生物反硝化而形成的一氧化二氮（N ₂ O）和二氮（N ₂）排放。N ₂ O的产生和还原取决于土壤中缺氧条件的空间范围，而缺氧条件又取决于在存在其他电子受体（例如硝酸盐）的情况下通过扩散提供的氧气（O ₂）和通过呼吸产生的O ₂需求。本研究旨在探讨以N ₂ O和（N ₂ O  +  N ₂）通过直接考虑微环境条件来重新包装土壤中的通量。这是通过测量微量氧饱和度并基于X射线计算机断层扫描（X射线CT）测量的内部空气分布估算厌氧土壤体积分数（ansvf）来实现的。通过全因子设计系统地研究了O _2的供求关系，包括土壤有机质（SOM； 1.2％和4.5％），集料尺寸（2-4和4-8 mm）和水饱和度（70％，83％，和95％的持水量（WHC）作为因素。用气相色谱监测CO ₂和N ₂ O的排放。使用¹⁵ N气体通量法估算N ₂ O还原为N ₂只有同时考虑O ₂需求和O ₂供应的解释变量，才能很好地预测.N气体排放。结合使用CO ₂排放和ansvf作为O ₂需求和供应的代理，可以说明（N ₂ O  +  N ₂）排放以及反硝化产物比率[ N ₂ O $/$ （N ₂ O  +  N ₂）]（pr）N ₂ O排放量的81％。由于微距离内O ₂的可变性以及微传感器的小测量体积，由微传感器测量的O ₂浓度很难预测。O ₂需求（SOM）和O ₂供应（扩散性）的独立，易于获得的代理替代预测变量大大降低了预测能力（N ₂ O和（N ₂ O + N ₂）分别为60％和66％使用X射线CT成像分析直接根据ansvf结合N ₂ O和（N ₂ O  +  N ₂）通量测量对土壤结构进行定量的新方法为估计完全反硝化开辟了新的前景。在土壤中。这也将有助于改善N ₂ O通量模型，并有助于制定N ₂ O通量的缓解策略并提高N的利用效率。