Title
Estimating methane emissions from biological and fossil-fuel sources in the San Francisco Bay Area
Document Type
Article
Publication Date
January 2017
Publication Title
Geophysical Research Letters
Volume
44
Issue Number
1
First Page
486
Last Page
495
DOI
10.1002/2016GL071794
Disciplines
Atmospheric Sciences | Climate | Meteorology | Other Oceanography and Atmospheric Sciences and Meteorology
Abstract
We present the first sector-specific analysis of methane (CH4) emissions from the San Francisco Bay Area (SFBA) using CH4 and volatile organic compound (VOC) measurements from six sites during September – December 2015. We apply a hierarchical Bayesian inversion to separate the biological from fossil-fuel (natural gas and petroleum) sources using the measurements of CH4 and selected VOCs, a source-specific 1 km CH4 emission model, and an atmospheric transport model. We estimate that SFBA CH4 emissions are 166–289 Gg CH4/yr (at 95% confidence), 1.3–2.3 times higher than a recent inventory with much of the underestimation from landfill. Including the VOCs, 82 ± 27% of total posterior median CH4 emissions are biological and 17 ± 3% fossil fuel, where landfill and natural gas dominate the biological and fossil-fuel CH4 of prior emissions, respectively.
Recommended Citation
Seongeun Jeong, Xinguang Cui, Donald Blake, Ben Miller, Stephen Montzka, Arlyn Andrews, Abhinav Guha, Philip Martien, Ray Bambha, Brian LaFranchi, Hope Michelsen, Craig Clements, Pierre Glaize, and Marc Fischer. "Estimating methane emissions from biological and fossil-fuel sources in the San Francisco Bay Area" Geophysical Research Letters (2017): 486-495. https://doi.org/10.1002/2016GL071794
Included in
Atmospheric Sciences Commons, Climate Commons, Meteorology Commons, Other Oceanography and Atmospheric Sciences and Meteorology Commons
Comments
© Copyright 2016 American Geophysical Union. All rights reserved.
This article was published in Geophysical Research Letters, volume 44, issue 1, 2017, and can be found online at the following link: http://dx.doi.org/10.1002/2016GL071794.