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Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

机译:大气中痕量气体扩散模型的比对:Barnett页岩案例研究

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摘要

Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.
机译:减少温室气体排放需要了解在越来越精细的空间和时间尺度上控制这些微量气体通量的主要过程。可以使用多种方法将痕量气体通量估算出来,这些方法将观测到的大气物种的摩尔分数转化为通量或排放速率,通常还可以确定排放源的时空特征。气象模型通常与示踪剂弥散模型结合使用一种逆方法来估算通量,该方法可优化排放以最适合痕量气体摩尔分数的观测结果。评估大气通量估算方法准确性的一种方法是比较独立方法的结果,包括使用不同的气象和示踪剂扩散模型的方法。在这项工作中,我们使用在一次密集的机载战役中收集的丰富的大气甲烷观测数据集,来比较美国德克萨斯州巴内特页岩油和天然气生产盆地的不同甲烷排放量估算值。我们根据各种不同的气象和扩散模型估算排放量。先前对该地区甲烷排放量的估算依赖于简单模型(质量平衡分析)以及地面测量和统计数据分析(清单)。我们发现,在选择相同的排放场的情况下,除了选择气象模型外,示踪剂扩散模型的选择还对预测的顺风甲烷浓度有重大影响。测试的弥散模型通常会低估所观察到的甲烷增加量,在不同模型之间以及不同日期之间会存在明显的差异性(高达3倍)。我们检查了导致该结果的可能原因,发现模型在垂直扩散模拟中存在差异,这表明需要额外的工作来评估和改善在区域示踪气体通量反演中常用的示踪扩散模型中的垂直混合。

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