Investigating seasonal methane emissions in Northern California using airborne measurements and inverse modeling

Seasonal methane (CH₄) emissions in Northern California are evaluated during this study by using airborne measurement data and inverse model simulations. This research applies Alpha Jet Atmospheric eXperiment (AJAX) measurements obtained during January–February 2013, July 2014, and October–November 2014 over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV) in order to constrain seasonal CH₄ emissions in Northern California. The California Greenhouse Gas Emissions Measurement (CALGEM) a priori emission inventory was applied in conjunction with the Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport model and inverse modeling techniques to optimize CH₄ emissions. Comparing model-predicted CH₄ mixing ratios with airborne measurements, we find substantial underestimates suggesting that CH₄ emissions were likely larger than the year 2008 a priori CALGEM emission inventory in Northern California. Using AJAX measurements to optimize a priori emissions resulted in CH₄ flux estimates from the SFBA/SJV of 1.77 ± 0.41, 0.83 ± 0.31, and 1.06 ± 0.39 Tg yr⁻¹ when using winter, summer, and fall flight data, respectively. Averaging seasonal a posteriori emission estimates (weighted by posterior uncertainties) results in SFBA/SJV annual CH₄ emissions of 1.28 ± 0.38 Tg yr⁻¹. A posteriori uncertainties are reduced more effectively in the SFBA/SJV region compared to state-wide values indicating that the airborne measurements are most sensitive to emissions in this region. A posteriori estimates during this study suggest that dairy livestock was the source with the largest increase relative to the a priori CALGEM emission inventory during all seasons.