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Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter

Heerah, Sajjan and Frausto-Vicencio, Isis and Jeong, Seongeun and Marklein, Alison R. and Ding, Yifan and Meyer, Aaron G. and Parker, Harrison A. and Fischer, Marc L. and Franklin, Jonathan E. and Hopkins, Francesca M. and Dubey, Manvendra (2021) Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter. Journal of Geophysical Research. Atmospheres, 126 (24). Art. No. e2021JD034785. ISSN 2169-897X. doi:10.1029/2021jd034785.

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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.

Item Type:Article
Related URLs:
URLURL TypeDescription ItemEM27/SUN retrievals used in this study and the STILT footprints
Heerah, Sajjan0000-0003-1698-5687
Frausto-Vicencio, Isis0000-0002-2549-7995
Jeong, Seongeun0000-0003-2032-0127
Ding, Yifan0000-0002-6300-0185
Meyer, Aaron G.0000-0001-7388-1345
Parker, Harrison A.0000-0002-0041-2764
Fischer, Marc L.0000-0001-7956-2361
Hopkins, Francesca M.0000-0002-6110-7675
Dubey, Manvendra0000-0002-3492-790X
Additional Information:© 2021. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Issue Online: 10 December 2021. Version of Record online: 10 December 2021. Accepted manuscript online: 05 November 2021. Manuscript accepted: 31 October 2021. Manuscript revised: 26 October 2021. Manuscript received: 19 February 2021. This article also appears in: Carbon Weather: Toward the Next Generation of Regional Greenhouse Gas Inversion Systems. This study was funded by the University of California Office of the President’s Grant LFR-18-548581. Work at Lawrence Berkeley National Laboratory was partially supported by Contractor Supporting Research (CSR) funding from Berkeley Lab, provided by the Director, Office of Science, under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. The authors also thank M. Rodriguez, Z. Zhu, D. Meyer, A. Velasco, I. Vicencio and D. Frausto-Vicencio for their help with facilitating and performing the field measurements; J. Podolske for help with conducting the Armstrong TCCON measurements; Taylor Jones for sharing his code to generate a STILT receptor list for the EM27/SUN; Jacob Hedelius, Nicole Jacobs, Nasrin Pak, Debra Wunch for guidance on using the EM27/SUN’s and their retrievals; Alex Turner for providing the emission map from Turner et al. (2015); I. Lino for constructing cooling enclosures for the EM27/SUN’s and M. Rodriguez, K. Heerah and V. Carranza for proofreading the draft. The authors thank LBNL’s Cluster Computing Program and William Porter for the assistance running the WRF-STILT models on the LBNL-Lawrencium and UCR-Aldo clusters respectively. Data Availability Statement. The EM27/SUN retrievals used in this study and the STILT footprints are available at
Funding AgencyGrant Number
University of CaliforniaLFR-18-548581
Department of Energy (DOE)DE-AC02-05CH11231
Subject Keywords:methane; dairy; atmospheric transport; remote sensing
Issue or Number:24
Record Number:CaltechAUTHORS:20220121-733817000
Persistent URL:
Official Citation:Heerah, S., Frausto-Vicencio, I., Jeong, S., Marklein, A. R., Ding, Y., Meyer, A. G., et al. (2021). Dairy methane emissions in California's San Joaquin Valley inferred with ground-based remote sensing observations in the summer and winter. Journal of Geophysical Research: Atmospheres, 126, e2021JD034785.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113040
Deposited By: George Porter
Deposited On:21 Jan 2022 22:43
Last Modified:21 Jan 2022 22:43

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