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Using the ecosys mathematical model to simulate temporal variability of nitrous oxide emissions from a fertilized agricultural soil

机译:使用ecosys数学模型模拟施肥农业土壤中一氧化二氮排放的时间变化

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Large temporal variability of N2O emissions complicates calculation of emission factors (EFs) needed for N2O inventories. To contribute towards improving these inventories, a process-based, 3-dimensional mathematical model, ecosys, was used to model N2O emissions from a canola crop. The objective of this study was to test the hypothesis in ecosys that large temporal variability of N2O is due to transition among alternative reduction reactions in nitrification/denitrification caused by small changes in soil water-filled pore space (WFPS) following a threshold response, which controls diffusivity (Dg) and solubility of O2. We simulated emissions at field scale, using a 20 c 20 matrix of 36 m c 36 m grid cells rendered in ArcGIS from a digital elevation model of the fertilized agricultural field. Modelled results were compared to measured N2O fluxes using the flux-gradient technique from a micrometeorological tower equipped with a tunable diode laser, to assess temporal N2O variability. Grid cell simulations were performed using original, earlier and later planting and fertilizer dates, to show the influence of changing precipitation and temperature on EFs. Fertilizer application (112 kg N ha1), precipitation and temperature were the main factors responsible for N2O emissions. Ecosys represented the temporal variation of N2O emissions measured at the tower by modelling significant emissions at WFPS > 60% which reduced the oxygen diffusivity, causing a rising need for alternative electron acceptors, thus greater N2O production via nitrification/denitrification. Small changes in WFPS above a threshold value caused comparatively large changes in N2O flux not directly predictable from soil temperature and WFPS. In ecosys, little N2O production occurred at WFPS < 60% because the oxygen diffusivity was large enough to meet microbial demand. Coefficients of diurnal temporal variation in N2O fluxes were high, ranging from 2551% (modelled) and 2463% (measured), during emission periods (00.8 mg N2ON m2 h1). This variation was shown to rise strongly with temperature during nitrification of N fertilizer so that EFs were affected by timing of fertilizer application. EFs almost quadrupled when fertilizer applications were delayed (average: 1.67% (fertilizer-induced emissions), causing nitrification to occur in warmer soils (18 pC), compared to earlier applications (average: 0.45%) when nitrification occurred in cooler soils (12 pC). Large temporal variation caused biases in seasonal emissions if calculated from infrequent (daily and weekly) measurements. These results show the importance of the use of models that include climate impact on N2O, with appropriate time-steps that capture its temporal variation.
机译:N2O排放的较大时间变化性使N2O清单所需的排放因子(EFs)的计算复杂化。为了改善这些库存,使用了基于过程的3维数学模型ecosys对油菜籽中N2O排放进行建模。这项研究的目的是检验ecosys中的一个假设,即N2O的较大时变性是由于阈值响应后土壤充水孔隙空间(WFPS)的微小变化所引起的硝化/反硝化替代还原反应之间的过渡所致。控制氧气的扩散率(Dg)和溶解度。我们使用来自农业耕地的数字高程模型的ArcGIS中渲染的36 m c 36 m网格单元的20 c 20矩阵模拟了田间尺度的排放。使用通量梯度技术将模拟结果与测量的N2O通量进行比较,该通量梯度技术来自配备了可调二极管激光器的微气象塔,以评估N2O的时间变异性。使用原始,较早和较晚的播种日期和肥料日期进行网格单元模拟,以显示降水和温度变化对EF的影响。施肥量(112 kg N ha1),降水量和温度是造成N2O排放的主要因素。 Ecosys通过对WFPS> 60%时的显着排放进行建模来表示在塔上测得的N2O排放的时间变化,这会降低氧气的扩散率,导致对替代电子受体的需求增加,因此通过硝化/反硝化产生了更多的N2O。高于阈值的WFPS的微小变化会导致N2O通量的较大变化,而N2O通量的变化无法直接从土壤温度和WFPS预测。在ecosys中,WFPS <60%时几乎不会产生N2O,这是因为氧气的扩散能力足以满足微生物的需求。在排放期间(00.8 mg N2ON m2 h1),N2O通量的昼夜时间变化系数很高,介于2551%(模型化)和2463%(实测)之间。在氮肥硝化过程中,这种变化表现为随温度而强烈上升,因此EFs受施肥时间的影响。延迟施用化肥时,EFs几乎翻了四倍(平均:1.67%(肥料诱导的排放),导致较温暖的土壤中发生硝化作用(18 pC),而较凉爽的土壤中早期硝化作用(平均水平:0.45%)发生(12%) pC)。如果从不频繁的(每日和每周)测量中计算出较大的时间变化会导致季节性排放的偏差,这些结果表明使用包含气候对N2O影响的模型的重要性,并采用适当的时间步长来捕获其时间变化。

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