Dynamics and Magnitude of California’s Dairy Methane Emissions Measured using Ground and Space-based Remote Sensing

Abstract:

California has made reducing methane (CH4) from its dairy industry a key part of its climate change mitigation plan. Dairies account for nearly 50% of California's CH4 emission inventory. However, in situ atmospheric measurement-based estimates suggest that the state-wide dairy source may be underestimated by up to a factor of 2. Furthermore, emissions at spatial scales important to mitigation policy (10-100’s of km) are more uncertain and the dynamics of the dairy methane source are not well studied. Ground-based measurements of atmospheric column averaged methane concentrations (XCH4) can provide useful constraints on regional CH4 fluxes. Additionally, high spatial resolution and temporally continuous XCH4 observations by space-based instruments may provide an excellent opportunity to measure CH4 fluxes at these scales. However, the higher uncertainty of satellite measurements may limit their utility at these scales. We report field measurements of XCH4 gradients across a group of 600 dairies in the Southern San Joaquin Valley (SJV) using EM27/SUN solar spectrometers over 3 field campaigns in 2019 to early 2020. We also use soundings from the GOSAT satellite over the same period to compliment this ground-based dataset. We perform inverse optimizations using WRF-STILT and a state-of-the-art facility level inventory of CH4 emissions in the region. Preliminary analysis of our ground-based data shows that top-down estimates of emissions range from 70-130% of our inventory, depending on the observation season. We explore how seasonally variable factors such as temperature, precipitation and natural gas usage can account for these variations. We also take advantage of the large sensitivity footprint of the XCH4 measurements to investigate how diurnal variability affects emissions from the dairies. Our analysis of the GOSAT soundings shows a persistent 12 ppb gradient across the SJV diaries. An inversion with this data finds that they overlap with the ground-based emission estimates within their uncertainties and the results offer an opportunity to assess inter-day variability in emissions. This work illustrates how ground and space-based measurements can complement each other to improve our understanding of CH4 sources at scales relevant to mitigation policy.

LA-UR-20-25657