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Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin
Author(s) -
Cui Yu Yan,
Brioude Jerome,
McKeen Stuart A.,
Angevine Wayne M.,
Kim SiWan,
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
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd023002
Subject(s) - mesoscale meteorology , weather research and forecasting model , environmental science , emission inventory , air quality index , atmospheric sciences , meteorology , climatology , methane , population , methane emissions , greenhouse gas , geography , geology , oceanography , ecology , demography , sociology , biology
Methane (CH 4 ) is the primary component of natural gas and has a larger global warming potential than CO 2 . Recent top‐down studies based on observations showed CH 4 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 CH 4 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 CH 4 using a Bayesian least squares method in a four‐dimensional inversion. Simulated CH 4 concentrations with the posterior emission inventory achieve much better correlations with the measurements ( R 2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R 2 = 0.5). The emission estimates for CH 4 in the posterior, 46.3 ± 9.2 Mg CH 4 /h, are consistent with published observation‐based estimates. Changes in the spatial distribution of CH 4 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. We estimate that dairies contributed 5.9 ± 1.7 Mg CH 4 /h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH 4 /h in the SoCAB.