Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study
| Autor: | Anna Karion, Ariel F. Stein, K. L. Mueller, James R. Whetstone, Z. Barkley, Colm Sweeney, Wayne M. Angevine, Aijun Deng, Israel Lopez Coto, Thomas Lauvaux, Sharon Gourdji, Arlyn E. Andrews |
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| Přispěvatelé: | National Institute of Standards and Technology [Gaithersburg] (NIST), University of Pennsylvania [Philadelphia], NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), PennState Meteorology Department, Pennsylvania State University (Penn State), Penn State System-Penn State System, NOAA Air Resources Laboratory (ARL) |
| Rok vydání: | 2019 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Astrophysics::High Energy Astrophysical Phenomena 010501 environmental sciences Atmospheric sciences 01 natural sciences Article Methane lcsh:Chemistry chemistry.chemical_compound Flux (metallurgy) Natural gas [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment Astrophysics::Galaxy Astrophysics 0105 earth and related environmental sciences [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere business.industry Atmospheric methane lcsh:QC1-999 Trace gas lcsh:QD1-999 chemistry Greenhouse gas Environmental science business Dispersion (chemistry) Oil shale lcsh:Physics |
| Zdroj: | Atmospheric Chemistry and Physics Atmospheric Chemistry and Physics, European Geosciences Union, 2019, 19 (4), pp.2561-2576. ⟨10.5194/acp-19-2561-2019⟩ Atmospheric chemistry and physics Atmospheric Chemistry and Physics, Vol 19, Pp 2561-2576 (2019) |
| ISSN: | 1680-7324 1680-7316 |
| DOI: | 10.5194/acp-19-2561-2019 |
| Popis: | 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 downwind 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. |
| Databáze: | OpenAIRE |
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