Atmospheric Environment: X (Apr 2022)
Evaluating California dairy methane emission factors using short-term ground-level and airborne measurements
Abstract
Robust air pollutant emission reduction strategies rely on accurate source characterizations. Studies have reported that the methane (CH4) emissions from California’s dairy sector are highly variable, and raised questions regarding the representativeness of the statewide CH4 emission estimates. To address these questions, a multi-tiered field study was conducted to evaluate the dairy CH4 emission factors (EFs) used in the California Air Resources Board (CARB) emission inventory. These EFs for dairy cow enteric fermentation and anaerobic lagoons are 144 and 332 kg of CH4 per animal head per year. CH4 emissions from dairies located within the San Joaquin Valley (SJV) were characterized through the analysis of ground-level mobile measurements collected in the summer and the fall of 2019. We developed a novel dispersion modeling-based approach that uses the ground-level mobile measurements of ambient CH4 levels to generate a metric that evaluates the CARB CH4 EFs. The analysis was further expanded using airborne measurements collected between September 2017 and May 2020. The multi-tiered measurements resulted in 126 whole-farm CH4 emission estimates for 107 dairies, making this study the most comprehensive mobile research study focused on CH4 emissions from California dairies to date. CARB CH4 EFs represented dairy CH4 emissions captured in this study fairly well; emissions observed in ground-level mobile measurements in summer and fall, and airborne measurements were greater than the inventory-reported values by only 8% (95% Confidence Interval [CI95%]: -7%–31%), 3% (CI95%: -11 – 21%), and 10% (CI95%: -7 – 45%), respectively. The results underline the effects of meteorology on dairy emissions and suggest that CH4 EFs from dairies with different ranges of herd sizes did not vary significantly. Future evaluation of the CARB CH4 emission inventory must incorporate facility-level data and leverage mechanistic approaches that capture the temporal variation of emissions from California’s dairy farms. Such improvements would enable research studies to better inform the emission inventory and help track the emissions changes from the implementation of new manure management technologies across California.
