scholarly journals Airborne Ethane Observations in the Barnett Shale: Quantification of Ethane Flux and Attribution of Methane Emissions

2015 ◽  
Vol 49 (13) ◽  
pp. 8158-8166 ◽  
Author(s):  
Mackenzie L. Smith ◽  
Eric A. Kort ◽  
Anna Karion ◽  
Colm Sweeney ◽  
Scott C. Herndon ◽  
...  
2019 ◽  
Vol 19 (4) ◽  
pp. 2561-2576 ◽  
Author(s):  
Anna Karion ◽  
Thomas Lauvaux ◽  
Israel Lopez Coto ◽  
Colm Sweeney ◽  
Kimberly Mueller ◽  
...  

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 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.


2015 ◽  
Vol 49 (13) ◽  
pp. 7889-7895 ◽  
Author(s):  
Tara I. Yacovitch ◽  
Scott C. Herndon ◽  
Gabrielle Pétron ◽  
Jonathan Kofler ◽  
David Lyon ◽  
...  

2015 ◽  
Vol 49 (13) ◽  
pp. 8175-8182 ◽  
Author(s):  
Amy Townsend-Small ◽  
Josette E. Marrero ◽  
David R. Lyon ◽  
Isobel J. Simpson ◽  
Simone Meinardi ◽  
...  

2015 ◽  
Vol 49 (13) ◽  
pp. 8139-8146 ◽  
Author(s):  
Xin Lan ◽  
Robert Talbot ◽  
Patrick Laine ◽  
Azucena Torres

2015 ◽  
Vol 49 (13) ◽  
pp. 8124-8131 ◽  
Author(s):  
Anna Karion ◽  
Colm Sweeney ◽  
Eric A. Kort ◽  
Paul B. Shepson ◽  
Alan Brewer ◽  
...  

2015 ◽  
Vol 49 (13) ◽  
pp. 7904-7913 ◽  
Author(s):  
Tegan N. Lavoie ◽  
Paul B. Shepson ◽  
Maria O. L. Cambaliza ◽  
Brian H. Stirm ◽  
Anna Karion ◽  
...  

2018 ◽  
Vol 18 (11) ◽  
pp. 8265-8278 ◽  
Author(s):  
Alexander J. Turner ◽  
Daniel J. Jacob ◽  
Joshua Benmergui ◽  
Jeremy Brandman ◽  
Laurent White ◽  
...  

Abstract. Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ∼ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ∼ 2–7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.


2018 ◽  
Author(s):  
Alexander J. Turner ◽  
Daniel J. Jacob ◽  
Joshua Benmergui ◽  
Jeremy Brandman ◽  
Laurent White ◽  
...  

Abstract. Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3×1.3 km2 spatial resolution and hourly temporal resolution over a 290×235 km2 domain in the Barnett Shale in Northeast Texas, a major oil/gas field with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7×7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7×3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should effectively provide regional (~100 km) information on temporally invariant emissions but is very limited at finer scales. GeoCARB should provide 4–37 % of the total information available for temporally invariant emissions in the Barnett Shale (~100 pieces of information). Improvements to the instrument precision yield greater increases in information content, compared to improved sampling frequency. A precision better than 6 ppb is an important threshold for achieving fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3×1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on transient sources.


2018 ◽  
Author(s):  
Anna Karion ◽  
Thomas Lauvaux ◽  
Israel Lopez Coto ◽  
Colm Sweeney ◽  
Kimberly Mueller ◽  
...  

Abstract. Greenhouse gas emissions mitigation requires understanding 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 emissions 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, U.S.A. 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 under-predicted the observed methane enhancements with significant variability 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.


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