Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter. Issue 24 (10th December 2021)

• Record Type: Journal Article
• Authors: Heerah, Sajjan; Frausto‐Vicencio, Isis; Jeong, Seongeun; Marklein, Alison R.; Ding, Yifan; Meyer, Aaron G.; Parker, Harrison A.; Fischer, Marc L.; Franklin, Jonathan E.; Hopkins, Francesca M.; Dubey, Manvendra
• Is Part Of: Journal of geophysical research. Volume 126:Issue 24(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-10
• Subjects: methane -- dairy -- atmospheric transport -- remote sensing; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2021JD034785
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: The dairy industry in the San Joaquin Valley (SJV) is one of California's largest methane (CH4 ) sources. Reducing dairy emissions is a priority for the state's climate change plans. Observations of current dairy CH4 emissions are key to monitoring actions taken toward this goal. To help support this, we present new ground‐based measurements of atmospheric column‐averaged CH4 mixing ratio (XCH4 ) gradients across a group of 600 dairies in the central SJV using EM27/SUN solar spectrometers. We used measurements from the 2019 summer and 2020 winter seasons for a top‐down emission inversion based on the WRF‐STILT model. Our top‐down estimates of the region's dairy emissions range from 90% to 183% of the current CALGEM inventory's emissions of 277 Gg/yr. In contrast to the strong temperature dependence found by earlier dairy CH4 emission studies, we also find that our top‐down emissions during the winter measurement days are comparable to the summer measurement days, possibly due to seasonal changes in dairy management practices and meteorological conditions. Furthermore, we find significant interday variability in our measurements and find that our emission estimates overlap with earlier top‐down studies and bottom‐up inventories in this region. Our study demonstrates how analysis of ground‐based remotely sensed CH4 gradient observations can help improve our understanding of CH4 sources at scales relevant to mitigation policy. It also reflects the need for long‐term monitoring of CH4 emissions in the region and at individual facilities to better understand their emissions. Key Points: We present total column measurements of the San Joaquin Valley's dairy methane emissions using EM27/SUN spectrometers over 6 measurement days Top‐down emission estimates from this data show interday variability and overlap with published San Joaquin Valley emission estimates Our measurements' winter emissions are comparable to summer emissions in contrast to patterns expected due to temperature