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Evaluating Methods To Estimate Methane Emissions from Oil and Gas Production Facilities Using LES Simulations.
Saide, Pablo E; Steinhoff, Daniel F; Kosovic, Branko; Weil, Jeffrey; Downey, Nicole; Blewitt, Doug; Hanna, Steven R; Delle Monache, Luca.
Afiliación
  • Saide PE; Research Applications Laboratory , National Center for Atmospheric Research , 3090 Center Green Drive , Boulder , Colorado 80301 , United States.
  • Steinhoff DF; Research Applications Laboratory , National Center for Atmospheric Research , 3090 Center Green Drive , Boulder , Colorado 80301 , United States.
  • Kosovic B; Research Applications Laboratory , National Center for Atmospheric Research , 3090 Center Green Drive , Boulder , Colorado 80301 , United States.
  • Weil J; Research Applications Laboratory , National Center for Atmospheric Research , 3090 Center Green Drive , Boulder , Colorado 80301 , United States.
  • Downey N; Earth System Sciences, LLC , 117 Bryn Mawr Drive SE Suite 111 , Albuquerque , New Mexico 87106 , United States.
  • Blewitt D; Earth System Sciences, LLC , 117 Bryn Mawr Drive SE Suite 111 , Albuquerque , New Mexico 87106 , United States.
  • Hanna SR; Hanna Consultants , 7 Crescent Avenue , Kennebunkport , Maine 04046 , United States.
  • Delle Monache L; Research Applications Laboratory , National Center for Atmospheric Research , 3090 Center Green Drive , Boulder , Colorado 80301 , United States.
Environ Sci Technol ; 52(19): 11206-11214, 2018 10 02.
Article en En | MEDLINE | ID: mdl-30153010
ABSTRACT
Large-eddy simulations (LES) coupled to a model that simulates methane emissions from oil and gas production facilities are used to generate realistic distributions of meteorological variables and methane concentrations. These are sampled to obtain simulated observations used to develop and evaluate source term estimation (STE) methods. A widely used EPA STE method (OTM33A) is found to provide emission estimates with little bias when averaged over six time periods and seven well pads. Sixty-four percent of the emissions estimated with OTM33A are within ±30% of the simulated emissions, showing a slightly larger spread than the 72% found previously using controlled release experiments. A newly developed method adopts the OTM33A sampling strategy and uses a variational or a stochastic STE approach coupled to an LES to obtain a better fit to the sampled meteorological conditions and to account for multiple sources within the well pad. This method can considerably reduce the spread of the emissions estimates compared to OTM33A (92-95% within ±30% percent error), but it is associated with a substantial increase in computational cost due to the LES. It thus provides an alternative when the additional costs can be afforded to obtain more precise emission estimates.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Meteorología Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Meteorología Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos