Methane Dynamics in Peat: Importance of Shallow Peats and a Novel Reduced‐Complexity Approach for Modeling Ebullition
Methane Dynamics in Peat: Importance of Shallow Peats and a Novel Reduced‐Complexity Approach for Modeling Ebullition
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泥炭中的甲烷动力学：浅层泥炭的重要性和一种新颖的简化沸腾建模方法
DOI：
10.1029/2008gm000811
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
J. Waddington
中科院分区：
文献类型：
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作者：
T. Coulthard;A. Baird;J. A. Ramirez;J. Waddington
北部泥炭地是大气甲烷（ch4）最大的天然来源之一，了解这些泥炭地的ch4损失机制对于预测未来的ch4排放速率具有重要意义。甲烷通过扩散、植物运输和以气泡（沸腾）的形式从泥炭地损失到大气中。我们认为，在许多以前的研究中，无论是在测量方面还是在所涉及的机制的概念化方面，沸腾都没有得到适当的解释。我们提出了一个新的气泡形成和释放的概念模型，强调了近地表泥炭作为大气ch4来源的重要性。我们回顾了两种可能的模拟泥炭土中气泡形成和损失的方法：最近提出的气泡阈值方法和完全计算流体动力学方法。我们认为两者都不能满足泥炭地ch4模型的需要，我们提出了一种新的降低复杂性的方法，将气泡的形成和释放概念化，大致类似于倒置的沙堆。与阈值方法不同，我们的模型允许气泡根据泥炭结构在泥炭剖面内的不同深度积累，但它保留了许多细胞（包括细胞自动机）模型的简单性。我们的模型的一个原型的结果与实验室实验的数据的比较表明，该模型捕捉了一些关键的沸腾动力学，因为它再现了很好地观察到的频率-幅度关系。我们概述了进一步发展该模型以提高其预测能力的方法。
Northern peatlands are one of the largest natural sources of atmospheric methane (CH 4 ), and it is important to understand the mechanisms of CH 4 loss from these peatlands so that future rates of CH 4 emission can be predicted. CH 4 is lost to the atmosphere from peatlands by diffusion, by plant transport, and as bubbles (ebullition). We argue that ebullition has not been accounted for properly in many previous studies, both in terms of measurement and the conceptualization of the mechanisms involved. We present a new conceptual model of bubble buildup and release that emphasizes the importance of near-surface peat as a source of atmospheric CH 4 . We review two possible approaches to modeling bubble buildup and loss within peat soils: the recently proposed bubble threshold approach and a fully computational-fluid-dynamics approach. We suggest that neither satisfies the needs of peatland CH 4 models, and we propose a new reduced-complexity approach that conceptualizes bubble buildup and release as broadly similar to an upside down sandpile. Unlike the threshold approach, our model allows bubbles to accumulate at different depths within the peat profile according to peat structure, yet it retains the simplicity of many cellular (including cellular automata) models. Comparison of the results from one prototype of our model with data from a laboratory experiment suggests that the model captures some of the key dynamics of ebullition in that it reproduces well observed frequency-magnitude relationships. We outline ways in which the model may be further developed to improve its predictive capabilities.