scholarly journals 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane

2021 ◽  
Vol 21 (6) ◽  
pp. 4339-4356
Author(s):  
Joannes D. Maasakkers ◽  
Daniel J. Jacob ◽  
Melissa P. Sulprizio ◽  
Tia R. Scarpelli ◽  
Hannah Nesser ◽  
...  

Abstract. We use 2010–2015 Greenhouse Gases Observing Satellite (GOSAT) observations of atmospheric methane columns over North America in a high-resolution inversion of methane emissions, including contributions from different sectors and their trends over the period. The inversion involves an analytical solution to the Bayesian optimization problem for a Gaussian mixture model (GMM) of the emission field with up to 0.5∘×0.625∘ resolution in concentrated source regions. The analytical solution provides a closed-form characterization of the information content from the inversion and facilitates the construction of a large ensemble of solutions exploring the effect of different uncertainties and assumptions in the inverse analysis. Prior estimates for the inversion include a gridded version of the Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) and the WetCHARTs model ensemble for wetlands. Our best estimate for mean 2010–2015 US anthropogenic emissions is 30.6 (range: 29.4–31.3) Tg a−1, slightly higher than the gridded EPA inventory (28.7 (26.4–36.2) Tg a−1). The main discrepancy is for the oil and gas production sectors, where we find higher emissions than the GHGI by 35 % and 22 %, respectively. The most recent version of the EPA GHGI revises downward its estimate of emissions from oil production, and we find that these are lower than our estimate by a factor of 2. Our best estimate of US wetland emissions is 10.2 (5.6–11.1) Tg a−1, on the low end of the prior WetCHARTs inventory uncertainty range (14.2 (3.3–32.4) Tg a−1), which calls for better understanding of these emissions. We find an increasing trend in US anthropogenic emissions over 2010–2015 of 0.4 % a−1, lower than previous GOSAT-based estimates but opposite to the decrease reported by the EPA GHGI. Most of this increase appears driven by unconventional oil and gas production in the eastern US. We also find that oil and gas production emissions in Mexico are higher than in the nationally reported inventory, though there is evidence for a 2010–2015 decrease in emissions from offshore oil production.

2020 ◽  
Author(s):  
Joannes D. Maasakkers ◽  
Daniel J. Jacob ◽  
Melissa P. Sulprizio ◽  
Tia R. Scarpelli ◽  
Hannah Nesser ◽  
...  

Abstract. We use 2010–2015 GOSAT satellite observations of atmospheric methane columns over North America in a high- resolution inversion of methane emissions, including contributions from different sectors and long-term trends. The inversion involves analytical solution to the Bayesian optimization problem for a Gaussian mixture model (GMM) of the emission field with up to 0.5° × 0.625° resolution in concentrated source regions. Analytical solution provides a closed-form characterization of the information content from the inversion and facilitates the construction of a large ensemble of solutions exploring the effect of different uncertainties and assumptions. Prior estimates for the inversion include a gridded version of the EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) and the WetCHARTS model ensemble for wetlands. Our best estimate for mean 2010–2015 US anthropogenic emissions is 30.6 (range: 29.4–31.3) Tg a-1, slightly higher than the gridded EPA inventory (28.7 (26.4–36.2) Tg a-1). The main discrepancy is for the oil and gas production sectors where we find higher emissions than the GHGI by 35 % and 22 % respectively. The most recent version of the EPA GHGI revises downward its estimate of emissions from oil production and we find that these are a factor 2 lower than our estimate. Our best estimate of US wetland emissions is 10.2 (5.6–11.1) Tg a-1, on the low end of the prior WetCHARTS inventory uncertainty range (14.2 (3.3–32.4) Tg a-1) and calling for better understanding of these emissions. We find an increasing trend in US anthropogenic emissions over 2010–2015 of 0.4 % a-1, lower than previous GOSAT-based estimates but opposite to the decrease reported by the EPA GHGI. Most of this increase appears driven by unconventional oil/gas production in the eastern US. We also find that oil/gas production emissions in Mexico are higher than in the nationally reported inventory, though there is evidence for a 2010–2015 decrease in emissions from offshore oil production.


2018 ◽  
Vol 52 (19) ◽  
pp. 11206-11214 ◽  
Author(s):  
Pablo E. Saide ◽  
Daniel F. Steinhoff ◽  
Branko Kosovic ◽  
Jeffrey Weil ◽  
Nicole Downey ◽  
...  

2018 ◽  
Vol 18 (9) ◽  
pp. 6483-6491 ◽  
Author(s):  
Jian-Xiong Sheng ◽  
Daniel J. Jacob ◽  
Alexander J. Turner ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
...  

Abstract. We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US in August–September 2013 to estimate methane emissions in that region through an inverse analysis with up to 0.25∘×0.3125∘ (25×25 km2) resolution and with full error characterization. The Southeast US is a major source region for methane including large contributions from oil and gas production and wetlands. Our inversion uses state-of-the-art emission inventories as prior estimates, including a gridded version of the anthropogenic EPA Greenhouse Gas Inventory and the mean of the WetCHARTs ensemble for wetlands. Inversion results are independently verified by comparison with surface (NOAA∕ESRL) and column (TCCON) methane observations. Our posterior estimates for the Southeast US are 12.8±0.9 Tg a−1 for anthropogenic sources (no significant change from the gridded EPA inventory) and 9.4±0.8 Tg a−1 for wetlands (27 % decrease from the mean in the WetCHARTs ensemble). The largest source of error in the WetCHARTs wetlands ensemble is the land cover map specification of wetland areal extent. Our results support the accuracy of the EPA anthropogenic inventory on a regional scale but there are significant local discrepancies for oil and gas production fields, suggesting that emission factors are more variable than assumed in the EPA inventory.


2016 ◽  
Vol 50 (5) ◽  
pp. 2487-2497 ◽  
Author(s):  
John. D. Albertson ◽  
Tierney Harvey ◽  
Greg Foderaro ◽  
Pingping Zhu ◽  
Xiaochi Zhou ◽  
...  

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Mark Burghardt ◽  
Gage Hart Zobell

Oil and gas production continues to be an important sector of Utah’s economy. Following a 25% loss in production between 2014 and 2015, Utah’s production continues to slowly rebound. Crude oil production in 2019 appears to be slightly ahead of 2018 production. Monthly production averages slightly over three million barrels, placing Utah among the top ten states in crude oil production. Along with the continuing increase in production, the state’s legal framework governing oil and gas continues to develop. This Article examines recent changes in Utah statutes and regulations along with new case law developments involving the oil and gas industry. In particular, this Article discusses a recent federal bankruptcy decision involving midstream agreements, the revision to a Utah statute that now requires mandatory reporting of unclaimed mineral interests, and recent revisions to Utah’s oil and gas regulations.


Author(s):  
A. G. Huseynov ◽  
◽  
E. A. Huseynov ◽  

The article analysis the oil and gas production condition in the Republic on basis of statistical data of many years as well as the level of investment provision. The article estimates the structure of expenses on innovative techniques, the condition of exploitation of oil and gas boreholes, the implementation of geological and technological actions, the ways of exploitation methods as well as the methods of ledge effects and influence on extra oil production. It also shows up the reserves and ways of their rational usage. Keywords: innovative activity; geological and technological actions; oil and gas; well.


2021 ◽  
Author(s):  
Maureen Lackner ◽  
Jonathan Camuzeaux ◽  
Suzi Kerr ◽  
Kristina Mohlin

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