Lawrence Berkeley National Laboratory

We present an analysis of methane (CH4) emissions using atmospheric observations from 36 thirteen sites in California during June 2013 – May 2014. A hierarchical Bayesian inversion 37 method is used to estimate CH4 emissions for spatial regions (0.3° pixels for major regions) by 38 comparing measured CH4 mixing ratios with transport model (WRF-STILT) predictions based 39 on seasonally varying California-specific CH4 prior emission models. The transport model is 40 assessed using a combination of meteorological and carbon monoxide (CO) measurements 41 coupled with the gridded California Air Resources Board (CARB) carbon monoxide (CO) 42 emission inventory. Hierarchical Bayesian inversion suggests that state annual anthropogenic 43 CH4 emissions are 2.42 ± 0.49 Tg CH4/yr (at 95% confidence, including transport bias 44 uncertainty), higher (1.2 - 1.8 times) than the CARB current inventory (1.64 Tg CH4/yr in 2013). 45 We note that the estimated CH4 emissions drop to 1.0 - 1.6 times the CARB inventory if we 46 correct for the 10% median CH4 emissions assuming the bias in CO analysis is applicable to 47 CH4. The CH4 emissions from the Central Valley and urban regions (San Francisco Bay and 48 South Coast Air Basins) account for ~58% and 26% of the total posterior emissions, 49 respectively. This study suggests that the livestock sector is likely the major contributor to the 50 state total CH4 emissions, in agreement with CARB’s inventory. Attribution to source sectors for 51 sub-regions of California using additional trace gas species would further improve the 52 quantification of California’s CH4 emissions and mitigation efforts towards the California Global 53 Warming Solutions Act of 2006 (AB-32).