Inversion Estimates of Lognormally Distributed Methane Emission Rates From the Haynesville-Bossier Oil and Gas Production Region Using Airborne Measurements
Inversion Estimates of Lognormally Distributed Methane Emission Rates From the Haynesville-Bossier Oil and Gas Production Region Using Airborne Measurements
Published Date:
2019
Source:
Journal of Geophysical Research: Atmospheres, 124(6)
Quantifying methane (CH4) emissions from the oil and natural gas (O/NG) production sector is an important regulatory challenge in the United States. In this study, we conduct a set of inversion calculations using different methods to quantify lognormal distributed CH4 surface fluxes in the Haynesville-Bossier O/NG production basin in Texas and Louisiana, combining three statistical cost functions, four meteorological configurations, and two days of aircraft measurements from a 2013 field campaign. We aggregate our posterior flux estimates to derive our best estimate of the basin-wide CH4 emissions, 76 metric tons/hr, with a 95% highest density interval of 51–104 metric tons/hr, in agreement with previous estimates using mass balance and eddy covariance approaches with the same aircraft measurements. Our inversion estimate of basin-wide CH4 emissions is 133% (89%–182%, 95% highest density interval) of a gridded Environmental Protection Agency's inventory for 2012, and the largest discrepancies between our study and this inventory are located in the northeastern quadrant of the basin containing active unconventional O/NG wells. Our inversion approach provides a new spatiotemporal characterization of CH4 emissions in this O/NG production region and shows the usefulness of inverse modeling for improving O/NG CH4 emission estimates.
Spain, E. A.; Johnson, S. C.; Hutton, B.; Whittaker, J. M.; Lucieer, V.; Watson, S. J.; Fox, J. M.; Lupton, J.; Arculus, R.; Bradney, A.; Coffin, M. F.;
Published Date:
2020
Source:
Earth and Space Science, 7(3)
Description:
Bubble emission mechanisms from submerged large igneous provinces remains enigmatic. The Kerguelen Plateau, a large igneous province in the southern Indian Ocean, has a long sustained history of active volcanism and glacial/interglacial cycles of sed...
J. Atmos. Oceanic Technol. (2018) 35 (11): 2169–2187.
Description:
Time series simulation is an important tool for developing and testing new signal processing algorithms for weather radar. The methods for simulating time series data have not changed much over the last few decades, but recent advances in computing t...
Rosenow, Andrew A.; Howard, Kenneth; Meitín, José G.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2469–2481.
Description:
On 24 January 2017, a convective snow squall developed in the San Luis Valley of Colorado. This squall produced rapidly varying winds at San Luis Valley airport in Alamosa, Colorado, with gusts up to 12 m s−1, and an associated visibility drop to 1...
The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physi...
Potvin, Corey K.; Broyles, Chris; Skinner, Patrick S.; Brooks, Harold E.; Rasmussen, Erik;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 15–30.
Description:
The Storm Prediction Center (SPC) tornado database, generated from NCEI’s Storm Data publication, is indispensable for assessing U.S. tornado risk and investigating tornado–climate connections. Maximizing the value of this database, however, requ...
A prototype quantitative precipitation estimate (QPE) algorithm that utilizes specific attenuation A and specific differential phase KDP was developed for inclusion into the Multi-Radar Multi-Sensor (MRMS) system and the Weather Surveillance Radar-19...
Observations from three nights of the Plains Elevated Convection at Night (PECAN) field campaign were used in conjunction with Rapid Refresh model forecasts to find the cause of north–south lines of convection, which initiated away from obvious sur...
Jones, Thomas A.; Skinner, Patrick; Knopfmeier, Kent; Mansell, Edward; Minnis, Patrick; Palikonda, Rabindra; Smith, William Jr.;
Published Date:
2018
Source:
Wea. Forecasting (2018) 33 (6): 1681–1708.
Description:
Forecasts of high-impact weather conditions using convection-allowing numerical weather prediction models have been found to be highly sensitive to the selection of cloud microphysics scheme used within the system. The Warn-on-Forecast (WoF) project ...
Flora, Montgomery L.; Potvin, Corey K.; Wicker, Louis J.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2361–2379.
Description:
As convection-allowing ensembles are routinely used to forecast the evolution of severe thunderstorms, developing an understanding of storm-scale predictability is critical. Using a full-physics numerical weather prediction (NWP) framework, the sensi...
Wade, Andrew R.; Coniglio, Michael C.; Ziegler, Conrad L.;
Published Date:
2018
Source:
Mon. Wea. Rev. (2018) 146 (8): 2403–2415.
Description:
A great deal of research focuses on how the mesoscale environment influences convective storms, but relatively little is known about how supercells modify the nearby environment. Soundings from three field experiments are used to investigate differen...
Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false al...
Adams-Selin, Rebecca D.; Clark, Adam J.; Melick, Christopher J.; Dembek, Scott R.; Jirak, Israel L.; Ziegler, Conrad L.;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 61–79.
Description:
Four different versions of the HAILCAST hail model have been tested as part of the 2014–16 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. HAILCAST was run as part of the National Severe Storms Laboratory (NSSL) WRF Ensemble du...
Cai, C.; Avise, J.; Kaduwela, A.; DaMassa, J.; Warneke, C.; Gilman, J. B.; Kuster, W.; de Gouw, J.; Volkamer, R.; Stevens, P.; Lefer, B.; Holloway, J. S.; Pollack, I. B.; Ryerson, T.; Atlas, E.; Blake, D.; Rappenglueck, B.; Brown, S. S.; Dube, W. P.;
Published Date:
2019
Source:
Journal of Geophysical Research: Atmospheres, 124(6)
Description:
United States Environmental Protection Agency guidance on the use of photochemical models for assessing the efficacy of an emissions control strategy for ozone requires that modeling be used in a relative sense. Consequently, testing a modeling syste...
Journal of the Association of Environmental and Resource Economists,7(3)
Description:
Estimating nonmarket benefits for erosion protection can help inform better decision making and policies for communities to adapt to climate change. We estimate private values for a coastal protection option in an empirical setting subject to irrever...
Koch, Steven E.; Fengler, Martin; Chilson, Philip B., 1963-; Elmore, Kimberly L.; Argrow, Brian M.; Andra, David; Lindley, T. Todd;
Published Date:
2018
Source:
J. Atmos. Oceanic Technol. (2018) 35 (11): 2265–2288.
Description:
The potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addr...
Gallo, Burkely T.; Clark, Adam J.; Smith, Bryan T.; Thompson, Richard L.; Jirak, Israel; Dembek, Scott R.;
Published Date:
2019
Source:
Wea. Forecasting (2019) 34 (1): 151–164.
Description:
Probabilistic ensemble-derived tornado forecasts generated from convection-allowing models often use hourly maximum updraft helicity (UH) alone or in combination with environmental parameters as a proxy for right-moving (RM) supercells. However, when...
Journal of the Air & Waste Management Association, 69(1), 71-88
Description:
Novel aerial methane (CH4) detection technologies were used in this study to identify anomalously high-emitting oil and gas (O&G) facilities and to guide ground-based “leak detection and repair” (LDAR) teams. This approach has the potential to en...
Webster, C. R.; Mahaffy, P. R.; Atreya, S. K.; Moores, J. E.; Flesch, G. J.; Malespin, C.; Mckay, C. P.; Martinez, G.; Smith, C. L.; Martin-Torres, J.; Gomez-Elvira, J.; Zorzano, M. P.; Wong, M. H.; Trainer, M. G.; Steele, A.; Archer, D.; Sutter, B.; Coll, P. J.; Freissinet, C.; Meslin, P.Y.; Gough, R. V.; House, C. H.; Pavlov, A.; Eigenbrode, J. L.; Glavin, D. P.; Pearson, J. C.; Keymeulen, D.; Christensen, L. E.; Schwenzer, S. P.; Navarro-Gonzalez, R.; Pla-Garcia, J.; Rafkin, S. C. R.; Vicente-Retortillo, A.; Kahanpaa, H.; Viudez-Moreiras, D.; Smith, M. D.; Harri, A. M.; Genzer, M.; Hassler, D. M.; Lemmon, M.; Crisp, J.; Sander, S. P.; Zurek, R. W.; Vasavada, A. R.;
Published Date:
2018
Source:
Science 360(6393): 1093-1096, 2018
Description:
Variable levels of methane in the martian atmosphere have eluded explanation partly because the measurements are not repeatable in time or location. We report in situ measurements at Gale crater made over a 5-year period by the Tunable Laser Spectrom...
Gas hydrate is an ice‐like form of water and low molecular weight gas stable at temperatures of roughly −10°C to 25°C and pressures of ~3 to 30 MPa in geologic systems. Natural gas hydrates sequester an estimated one sixth of Earth's methane an...
Zavala-Araiza, D.; Lyon, D. R.; Alvarez, R. A.; Davis, K. J.; Harriss, R.; Herndon, S. C.; Karion, A.; Kort, E. A.; Lamb, B. K.; Lan, X.; Marchese, A. J.; Pacala, S. W.; Robinson, A. L.; Shepson, P. B.; Sweeney, C.; Talbot, R.; Townsend-Small, A.; Yacovitch, T. I.; Zimmerle, D. J.; Hamburg, S. P.;
Published Date:
2015
Source:
Proc Natl Acad Sci U S A. 2015 Dec 22; 112(51): 15597-15602.
Description:
Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petrol...
This paper summarizes current understanding of the processes that determine the dynamics of the subsea permafrost–hydrate system existing in the largest, shallowest shelf in the Arctic Ocean; the East Siberian Arctic Shelf (ESAS). We review key env...
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