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Estimating methane emissions from biological and fossil‐fuel sources in the San Francisco Bay Area

doi: 10.1002/2016gl071794
AbstractWe 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.
- Earth System Research Laboratory United States
- National Oceanic and Atmospheric Administration United States
- University of California System United States
- Lawrence Berkeley National Laboratory United States
- Lawrence Berkeley National Laboratory United States
571, Climate, methane, atmospheric transport, emission inventory, inverse model, Atmospheric Sciences, Climate Action, natural gas, Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, greenhouse gas, Meteorology & Atmospheric Sciences
571, Climate, methane, atmospheric transport, emission inventory, inverse model, Atmospheric Sciences, Climate Action, natural gas, Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, greenhouse gas, Meteorology & Atmospheric Sciences
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).23 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
