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Methods for Spatial Extrapolation of Methane Measurements in Constructing Regional Estimates from Sample Populations.
Schissel, Colette; Allen, David; Dieter, Howard.
Afiliação
  • Schissel C; Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States.
  • Allen D; Center for Energy and Environmental Resources, University of Texas at Austin, Austin, Texas 78758, United States.
  • Dieter H; Energy Emissions Modeling and Data Lab, Austin, Texas 78712, United States.
Environ Sci Technol ; 58(6): 2739-2749, 2024 Feb 13.
Article em En | MEDLINE | ID: mdl-38303409
ABSTRACT
Methane emission estimates for oil and gas facilities are typically based on estimates at a subpopulation of facilities, and these emission estimates are then extrapolated to a larger region or basin. Basin-level emission estimates are then frequently compared with basin-level observations. Methane emissions from oil and gas systems are inherently variable and intermittent, which make it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work develops a framework for extrapolation of emission estimates using the case study of an operator in the Green River Basin. This work also identifies a new metric, the capture ratio, which quantifies the extent to which sources are represented in the sample population, based on the skewness of emissions for each source. There is a strong correlation between the capture ratio and extrapolation error, which suggests that understanding source-level emissions distributions can mitigate error when sample populations are selected and extrapolating measurements. The framework and results from this work can inform the selection and extrapolation of site measurements when developing methane emission inventories and establishing uncertainty bounds to assess whether inventory estimates are consistent with independent large spatial-scale observations.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Gás Natural Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / Gás Natural Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article