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Title: Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin

Abstract

Methane (CH4) is the primary component of natural gas and has a larger global warming potential than CO2. Some recent top-down studies based on observations showed CH4 emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R2 = 0.5). The emission estimates for CH4 in the posterior, 46.3 ± 9.2 Mg CH4/h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH4 emissions in the SoCAB betweenmore » the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. Furthermore, we estimate that dairies contributed 5.9 ± 1.7 Mg CH4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH4/h in the SoCAB.« less

Authors:
 [1];  [2];  [1];  [1];  [1];  [3];  [4];  [1];  [5];  [6];  [7];  [8];  [8];  [9];  [10];  [7]
+ Show Author Affiliations
  1. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States); Univ. of Colorado Boulder, CO (United States)
  2. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States); Univ. of Colorado Boulder, CO (United States); National Centre for Scientific Research-Mixed Organizations (CNRS-UMR), Paris (France)
  3. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.; Univ. of Colorado Boulder, CO (United States)
  4. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States; Univ. of Colorado Boulder, CO (United States)
  5. Univ. of Colorado, Boulder, CO (United States)
  6. Sandia National Lab. (SNL-CA), Livermore, CA (United States); Now at Ramboll Environ US Corporation, Novato, CA (United States)
  7. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
  8. Harvard Univ., Cambridge, MA (United States)
  9. Univ. of Michigan, Ann Arbor, MI (United States)
  10. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1235292
Report Number(s):
SAND-2015-4909J
Journal ID: ISSN 2169-8996; 594363
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres (Online)
Additional Journal Information:
Journal Name: Journal of Geophysical Research: Atmospheres (Online); Journal Volume: 120; Journal Issue: 13; Journal ID: ISSN 2169-8996
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; methane; emission inventory; inverse modeling; Los Angeles

Citation Formats

Cui, Yu Yan, Brioude, Jerome, McKeen, Stuart A., Angevine, Wayne M., Kim, Si -Wan, Frost, Gregory J., Ahmadov, Ravan, Peischl, Jeff, Bousserez, Nicolas, Liu, Zhen, Ryerson, Thomas B., Wofsy, Steve C., Santoni, Gregory W., Kort, Eric A., Fischer, Marc L., and Trainer, Michael. Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin. United States: N. p., 2015. Web. doi:10.1002/2014JD023002.
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Cui, Yu Yan, Brioude, Jerome, McKeen, Stuart A., Angevine, Wayne M., Kim, Si -Wan, Frost, Gregory J., Ahmadov, Ravan, Peischl, Jeff, Bousserez, Nicolas, Liu, Zhen, Ryerson, Thomas B., Wofsy, Steve C., Santoni, Gregory W., Kort, Eric A., Fischer, Marc L., & Trainer, Michael. Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin. United States. https://doi.org/10.1002/2014JD023002
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Cui, Yu Yan, Brioude, Jerome, McKeen, Stuart A., Angevine, Wayne M., Kim, Si -Wan, Frost, Gregory J., Ahmadov, Ravan, Peischl, Jeff, Bousserez, Nicolas, Liu, Zhen, Ryerson, Thomas B., Wofsy, Steve C., Santoni, Gregory W., Kort, Eric A., Fischer, Marc L., and Trainer, Michael. Tue . "Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin". United States. https://doi.org/10.1002/2014JD023002. https://www.osti.gov/servlets/purl/1235292.
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@article{osti_1235292,
title = {Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin},
author = {Cui, Yu Yan and Brioude, Jerome and McKeen, Stuart A. and Angevine, Wayne M. and Kim, Si -Wan and Frost, Gregory J. and Ahmadov, Ravan and Peischl, Jeff and Bousserez, Nicolas and Liu, Zhen and Ryerson, Thomas B. and Wofsy, Steve C. and Santoni, Gregory W. and Kort, Eric A. and Fischer, Marc L. and Trainer, Michael},
abstractNote = {Methane (CH4) is the primary component of natural gas and has a larger global warming potential than CO2. Some recent top-down studies based on observations showed CH4 emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R2 = 0.5). The emission estimates for CH4 in the posterior, 46.3 ± 9.2 Mg CH4/h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. Furthermore, we estimate that dairies contributed 5.9 ± 1.7 Mg CH4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH4/h in the SoCAB.},
doi = {10.1002/2014JD023002},
journal = {Journal of Geophysical Research: Atmospheres (Online)},
number = 13,
volume = 120,
place = {United States},
year = {Tue Jul 28 00:00:00 EDT 2015},
month = {Tue Jul 28 00:00:00 EDT 2015}
}
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https://doi.org/10.1002/2014JD023002
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    Inversion Estimates of Lognormally Distributed Methane Emission Rates From the Haynesville‐Bossier Oil and Gas Production Region Using Airborne Measurements
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