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Estimating methane emissions in California's urban and rural regions using multitower observations

Jeong, Seongeun and Newman, Sally and Zhang, Jingsong and Andrews, Arlyn E. and Bianco, Laura and Bagley, Justin and Cui, Xinguang and Graven, Heather and Kim, Jooil and Salameh, Peter and LaFranchi, Brian W. and Priest, Chad and Campos-Pineda, Mixtli and Novakovskaia, Elena and Sloop, Christopher D. and Michelsen, Hope A. and Bambha, Ray P. and Weiss, Ray F. and Keeling, Ralph and Fischer, Marc L. (2016) Estimating methane emissions in California's urban and rural regions using multitower observations. Journal of Geophysical Research. Atmospheres, 121 (21). pp. 13031-13049. ISSN 2169-897X. doi:10.1002/2016JD025404.

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We present an analysis of methane (CH_4) emissions using atmospheric observations from 13 sites in California during June 2013 to May 2014. A hierarchical Bayesian inversion method is used to estimate CH_4 emissions for spatial regions (0.3° pixels for major regions) by comparing measured CH_4 mixing ratios with transport model (Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport) predictions based on seasonally varying California-specific CH_4 prior emission models. The transport model is assessed using a combination of meteorological and carbon monoxide (CO) measurements coupled with the gridded California Air Resources Board (CARB) CO emission inventory. The hierarchical Bayesian inversion suggests that state annual anthropogenic CH_4 emissions are 2.42 ± 0.49 Tg CH_4/yr (at 95% confidence), higher (1.2–1.8 times) than the current CARB inventory (1.64 Tg CH_4/yr in 2013). It should be noted that undiagnosed sources of errors or uncaptured errors in the model-measurement mismatch covariance may increase these uncertainty bounds beyond that indicated here. The CH_4 emissions from the Central Valley and urban regions (San Francisco Bay and South Coast Air Basins) account for ~58% and 26% of the total posterior emissions, respectively. This study suggests that the livestock sector is likely the major contributor to the state total CH_4 emissions, in agreement with CARB's inventory. Attribution to source sectors for subregions of California using additional trace gas species would further improve the quantification of California's CH_4 emissions and mitigation efforts toward the California Global Warming Solutions Act of 2006 (Assembly Bill 32).

Item Type:Article
Related URLs:
URLURL TypeDescription
Jeong, Seongeun0000-0003-2032-0127
Newman, Sally0000-0003-0710-995X
Zhang, Jingsong0000-0003-3700-151X
Andrews, Arlyn E.0000-0002-8552-3999
Bianco, Laura0000-0002-4022-7854
Cui, Xinguang0000-0002-0721-3119
Graven, Heather0000-0003-3934-2502
Kim, Jooil0000-0002-2610-4882
Priest, Chad0000-0003-1377-9271
Campos-Pineda, Mixtli0000-0003-3949-0572
Weiss, Ray F.0000-0001-9551-7739
Keeling, Ralph0000-0002-9749-2253
Fischer, Marc L.0000-0001-7956-2361
Additional Information:© 2016 American Geophysical Union. Received 23 MAY 2016; Accepted 15 SEP 2016; Accepted article online 1 OCT 2016; Published online 5 NOV 2016. We thank Dave Field, Dave Bush, Edward Wahl, Ken Reichl, Toby Walpert, and particularly Jon Kofler for the assistance with measurements at WGC and analysis of data from radar wind profiler sites; Christina Harth for the assistance with measurements at THD; John Lin, Christoph Gerbig, Steve Wofsy, Janusz Eluszkiewicz, and Thomas Nehrkorn for sharing the STILT code and advice; Anita Ganesan for the motivation of the HBI approach; Chris Potter and William Salas for sharing the modeled CH_4 emission for use as a priori estimates; Ed Dlugokencky and Colm Sweeney for sharing the data for CH_4 background estimates; Ying-Kuang Hsu, Bart Croes, Jorn Herner, Abhilash Vijayan, Matthias Falk, Richard Bode, Anny Huang, Jessica Charrier, Kevin Eslinger, Larry Hunstaker, Ken Stroud, Mac McDougall, Jim Nyarady, and others for sharing the CARB emissions information and providing valuable review comments; and Krishna Muriki for the assistance running the WRF-STILT models on the LBNL-Lawrencium cluster. The data used in the inversion are in Figures S15 and S16, and the CALGEM prior emission distribution is available at This study was supported by the University of California's Discovery Grant Program and the California Air Resources Board Research Division under U.S. Department of Energy contract DE-AC02-05CH11231.
Funding AgencyGrant Number
University of CaliforniaUNSPECIFIED
California Air Resources BoardUNSPECIFIED
Department of Energy (DOE)DE-AC02-05CH11231
Subject Keywords:methane; greenhouse gas; emission inventory; atmospheric transport; inverse model
Issue or Number:21
Record Number:CaltechAUTHORS:20170103-103638604
Persistent URL:
Official Citation:Jeong, S., et al. (2016), Estimating methane emissions in California’s urban and rural regions using multitower observations, J. Geophys. Res. Atmos., 121, 13,031–13,049, doi:10.1002/2016JD025404
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73172
Deposited By: Tony Diaz
Deposited On:03 Jan 2017 19:16
Last Modified:11 Nov 2021 05:12

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