4.8 Article

Methane Emissions from Dairy Operations in California's San Joaquin Valley Evaluated Using Airborne Flux Measurements

Journal

ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 57, Issue 48, Pages 19519-19531

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.3c03940

Keywords

methane; dairies; emissions; fluxes; eddy covariance; California

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State inventories may underestimate methane emissions from dairy operations in California. Airborne flux measurements in the southern San Joaquin Valley show higher methane emissions from dairy farms compared to inventory estimates. This highlights the need for accurate emission inventories and further investigation of the meteorological factors influencing these emissions.
State inventories indicate that dairy operations account for nearly half of California's methane budget. Recent analyses suggest, however, that these emissions may be underestimated, complicating efforts to develop emission reduction strategies. Here, we report estimates of dairy methane emissions in the southern San Joaquin Valley (SJV) of California in June 2021 using airborne flux measurements. We find average dairy methane fluxes of 512 +/- 178 mg m(-2) h(-1) from a region of 300+ dairies near Visalia, CA using a combination of eddy covariance and mass balance-based techniques, corresponding to 118 +/- 41 kg dairy(-1) h(-1). These values estimated during our June campaign are 39 +/- 48% larger than annual average estimates from the recently developed VISTA-CA inventory. We observed notable increases in emissions with temperature. Our estimates align well with inventory predictions when parametrizations for the temperature dependence of emissions are applied. Our measurements further demonstrate that the VISTA-CA emission inventory is considerably more accurate than the EPA GHG-I inventory in this region. Source apportionment analyses confirm that dairy operations produce the majority of methane emissions in the southern SJV (similar to 65%). Fugitive oil and gas (O&G) sources account for the remaining similar to 35%. Our results support the accuracy of the process-based models used to develop dairy emission inventories and highlight the need for additional investigation of the meteorological dependence of these emissions.

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