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Multi-layer diffusion model and error analysis applied to chamber-based gas fluxes measurements

机译:多层扩散模型和误差分析应用于基于室的气体通量测量

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Chambers are widely-used for measuring greenhouse gas emission from soil surfaces. Current chamber methods are generally based on constant production within the soil, both before and after the placement of the enclosed chamber, and well-mixed chamber systems. The objective of this study is to present an analytical solution for either perfectly mixed or non-mixed non-steady-state (NSS) chamber systems with a depth-dependent gas production term. Parameters such as the decreasing production rate (k), the distance from soil-atmosphere interface to the water table (l(1)), the height of chamber (l(2) - l(1)), the diffusion coefficient in the chamber (D-2), and the air-filled porosity (epsilon) were included in our model. This was accomplished by using a one-dimensional multi-layer transient diffusion model with a production term. If we know k, l(1), l(2) - l(1), D-2, and epsilon, the pre-deployment flux density f(0) can be obtained by fitting the new solution to experimental concentration curve. The analytical solution can be applied to various case scenarios from pure diffusion to perfectly mixed systems, by adjusting D-2. The widely-used linear and nonlinear regression models are subsets of the solution. The proposed solution indicates the importance of the initial concentration distribution f(x) and production term g(x) in emission rates. Without measuring g(x), a large error in estimated pre-deployment flux density f(0) could result. Without knowing the parameters k, l(1), l(2) - l(1) and D-2, a large error in estimated f(0) could result. If the well-mixed model is used for modeling diffusion in not perfectly mixed chamber headspace, the magnitude of the error in f(0) increases monotonically with the increase in heights of sampling ports above l(1) and can be larger than 60% at x = l(2). The error caused by using the well-stirred approximation increase with decreases in D-2 and can be significant for chambers when there are no external mixing devices. The well-mixed solution could not be fitted well to the pure diffusion concentration curve, and vice versa. The solution may be helpful for better evaluating f(0) of trace gases from soil, carrying out the errors analysis and reducing the uncertainty in measured greenhouse gas emissions from soil. (c) 2008 Elsevier B.V. All rights reserved.
机译:腔室被广泛用于测量土壤表面的温室气体排放量。当前的腔室方法通常基于在封闭腔室和充分混合的腔室系统放置之前和之后土壤中的恒定产量。这项研究的目的是提出一种与深度相关的产气量的完全混合或非混合非稳态(NSS)腔室系统的分析解决方案。诸如降低生产率(k),从土壤-大气界面到地下水位的距离(l(1)),腔室高度(l(2)-l(1)),扩散系数等参数腔室(D-2)和充气孔隙率(epsilon)包括在我们的模型中。这是通过使用带有生产项的一维多层瞬态扩散模型来完成的。如果我们知道k,l(1),l(2)-l(1),D-2和epsilon,则可以通过将新解拟合到实验浓度曲线来获得部署前的通量密度f(0)。通过调整D-2,可以将分析解决方案应用于从纯扩散到完全混合的各种情况。广泛使用的线性和非线性回归模型是解决方案的子集。所提出的解决方案表明了排放速率中初始浓度分布f(x)和生产项g(x)的重要性。如果不测量g(x),可能会导致估计的部署前磁通密度f(0)产生较大误差。在不知道参数k,l(1),l(2)-l(1)和D-2的情况下,可能会导致估计f(0)产生较大误差。如果使用充分混合的模型来模拟不完全混合的腔室顶空中的扩散,则f(0)的误差大小会随着采样端口高度在l(1)以上的增加而单调增加,并且可能大于60%在x = l(2)使用良好搅拌的近似值所引起的误差随D-2的减小而增加,并且在没有外部混合设备的情况下对于腔室而言可能是很大的。混合均匀的溶液不能很好地拟合纯扩散浓度曲线,反之亦然。该解决方案可能有助于更好地评估土壤中痕量气体的f(0),进行误差分析并减少从土壤中测得的温室气体排放量的不确定性。 (c)2008 Elsevier B.V.保留所有权利。

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