Your browser doesn't support javascript.
loading
Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study.
Karion, Anna; Lauvaux, Thomas; Lopez Coto, Israel; Sweeney, Colm; Mueller, Kimberly; Gourdji, Sharon; Angevine, Wayne; Barkley, Zachary; Deng, Aijun; Andrews, Arlyn; Stein, Ariel; Whetstone, James.
Afiliação
  • Karion A; Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, USA.
  • Lauvaux T; Department of Meteorology, The Pennsylvania State University, University Park, PA, USA.
  • Lopez Coto I; Fire Research Division, National Institute of Standards and Technology, Gaithersburg, MD, USA.
  • Sweeney C; Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA.
  • Mueller K; Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, USA.
  • Gourdji S; Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, USA.
  • Angevine W; Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA.
  • Barkley Z; Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA.
  • Deng A; Department of Meteorology, The Pennsylvania State University, University Park, PA, USA.
  • Andrews A; Utopus Insights, Valhalla, NY, USA.
  • Stein A; Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA.
  • Whetstone J; Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, USA.
Article em En | MEDLINE | ID: mdl-31275365
ABSTRACT
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article