Dairies are an important source of greenhouse gas, such as methane (CH4) and nitrous oxide (N2O), and ammonia (NH3) emissions but remain highly uncertain across spatial and temporal scales. Stable isotope measurements and enhancement ratios between different trace gases can be used to characterize and identify relative magnitudes, trends, and sources of emissions. In the first study, CH4 emissions from enteric fermentation and manure management source areas from dairy farms in California's San Joaquin Valley (SJV) are characterized using isotopic signatures of CH4 (δ13CCH4). Methane from manure lagoons was more enriched in δ13C than CH4 from enteric fermentation across seasons on average by 14 ± 2‰. The second study quantified and characterized seasonal CH4, N2O, and NH3 emissions from SJV dairy farms using enhancement ratios of trace gases (ΔN2O:ΔCH4; ΔNH3:ΔCH4). The average ΔNH3:ΔCH4 from freestall barns and corrals observed across all seasons is 0.58 ± 0.19 ppbv ppbv-1 and 0.48 ± 0.05 ppbv ppbv-1, respectively. Manure lagoons had an average ΔNH3: ΔCH4 of 0.09 ± 0.01 ppbv ppbv-1 , whereas dry bedding had ΔNH3:ΔCH4 of 2.71 ± 0.85 ppbv ppbv-1. ΔN2O:ΔCH4 also show distinct signatures between livestock housing, manure management, cropland, and silage, with the highest enhancement ratios observed in cropland (1.65 ± 0.17 ppbv ppbv-1). The third study estimated seasonal and diurnal CH4 fluxes from dairy manure lagoons in Southern California. Diurnal CH4 fluxes were closely correlated with latent heat fluxes and show a positive relationship with lagoon temperatures and wind speed; however, the temperature relationship differs at seasonal timescales. Methane fluxes decreased over the study period, with the highest CH¬4 fluxes measured during the spring season (6.89 µmol m-2s-1; 95% CI: 6.41 - 7.45 µmol m-2s-1), following precipitation events. These findings highlight how isotopic measurements and enhancement ratios of co-located emissions can be used for source apportionment of dairy emissions. Lastly, it underscores the importance of long-term measurements of CH4 fluxes from dairy manure lagoons to determine the principal environmental factors influencing the magnitude of seasonal and diurnal trends.

Methane (CH4), an important greenhouse gas and pollutant, has been targeted for mitigation. Our recent California airborne survey identified >500 CH4 point sources, which accounted for 34-46% of the statewide CH4 emissions inventory for 2016. Individual plumes were observed in close proximity to expected CH4 emitting infrastructure. In order to systematically attribute these plumes to their sources, we developed Vista-CA a geospatial database, that contains more than 900,000 validated CH4 infrastructure elements in the state of California. In parallel, we developed a complimentary algorithm that attributes any individual CH4 plume observation to high confidence Vista-CA source with 99% accuracy. This research illustrates the capabilities of the Vista-CA CH4 database along with Airborne Visible/Infrared Imaging Spectrometer – Next Generation’s (AVIRIS-NG) airborne CH4 retrievals to locate and attribute CH4 point sources to specific economic sectors. Additionally, this research delivers two emissions products for Kern County: a top-down estimate called the AVIRIS-NG Source Data product and the Vista-CA Bottom-Up emissions dataset. We found general agreement in the source apportionment and magnitudes between these datasets. Moreover, due to current CH4 inventories having large uncertainties in emissions from the energy processing and production sectors where fugitive emissions predominate, we used airborne CH4 imaging survey data to show that CH4 emissions from power plants in California are underestimated by current CH4 inventory approaches. We developed process-based bottom-up emission estimates for over 300 power plants in California using Intergovernmental Panel on Climate Change (IPCC) methods. We used airborne CH4 imaging to attribute CH4 observations to over 250 California power plants and characterize the frequency and persistency of top-down CH4 emissions. We found that fugitive emissions constitute 90% of total observed emissions from power plants with the remainder derived from process-driven activity while bottom-up emissions are 28 – 54 times smaller than top-down observations. Comparing the inventory-based estimates with observations, the data show “super-emitter” behavior with 60% of total power plant emissions coming from a handful of facilities, likely due to fugitive CH4 emissions. Future inventories should take advantage of emission observations to quantify CH4 from these sources to improve the state CH4 budget and identify mitigation targets.

Anthropogenic trace gases such as greenhouse gases and air toxics emitted to the atmosphere contribute to radiative forcing, degradation of air quality, and negative impacts on human health. Quantification and characterization of these important trace gases are required to mitigate the global climate crisis and improve the air quality. My dissertation focuses on constraining methane (CH4) emissions from California’s San Joaquin Valley (SJV) dairy farms and characterizing wildfire emissions using ground-based solar spectroscopy observations. Additionally, I characterize a portable gas chromatograph coupled to a photoionization detector (GC-PID) for measuring concentrations of air toxics at ambient levels. In the first study, I studied the seasonality of CH4 emissions from dairy farms across four seasons from Spring 2019 to Winter 2020 in the SJV to investigate whether emissions varied across time and to discern the environmental factors driving temporal differences. Measurements collected during different seasons provided insight into the meteorological and management factors that drive the time-varying patterns observed during the year. This research showed that seasonal variability exists within dairy farm emissions and mitigation should focus in the summer. Wildfires are increasing in the Western United States making it critical to understand the impacts of greenhouse gases and air pollutants emitted to the atmosphere. I used a ground-based remote sensing technique to measure the amount of greenhouse gases and aerosol present in the atmosphere. I isolated a large smoke plume from the Sequoia Lightning Fire Complex (SQF) and calculated variables to understand the fuel properties. This revealed that a significant amount of CH4 was emitted from the 2020 wildfire season. In the third study, I characterized the performance of a compact GC-PID and optimize the configuration to detect ambient levels of benzene, toluene, ethylbenzene, and xylene isomers (BTEX). With an analysis time of less than 15 minutes, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and easily deployable GC-PID for community monitoring and screening of BTEX.

In California, agriculture contributes about 9% of the state’s greenhouse gas (GHG) and 72% of ammonia (NH3) emissions due to fertilizer application, livestock manure management, and enteric fermentation. California climate legislation seeks to achieve carbon neutrality and reduce GHG emissions by 85% below 1990 levels by 2045. State legislation also emphasizes the importance of increasing carbon sequestration and reducing GHG flux from natural and working lands as well as reducing emissions in the dairy and livestock sector. Ensuring the success of these policies requires further research to determine the impact of management strategies on GHG fluxes. First, I conducted seasonal field measurements of methane (CH4) on the manure storage complex of a dairy farm in the San Joaquin Valley with a mobile platform before and after anaerobic digester installation. Digester implementation strongly reduced CH4 emissions by 45.8 to 91.2% compared to pre-digester levels and show temporal variability due to differences in meteorology, on farm management practices, and digester operation. The next study analyzes soil trace gas emissions from land application of liquid dairy manure and the effect of varying soil properties, manure NH4+, and moisture conditions across California. Nitrous oxide (N2O) and ammonia (NH3) emissions ranged from 0.01 to 1.9 μg N2O-N g soil-1 and 0.3 to 32.9 μg NH3-N g soil-1 respectively and were controlled by variability in soil properties. Soil moisture conditions and manure NH4+ interacted to increase emissions. Finally, I examine greenhouse gas emissions from the soil application of solid dairy manure across soil properties and temperature conditions and compare emissions after manure biochar application and to co-application with liquid manure. Manure biochar application saw 1.9-2.5 times less normalized carbon dioxide (CO2) emissions and 4.0-4.4 times less N2O emissions compared to conventional dried solid manure application while N2O emissions were 1.6-2.2 times greater with co-application with liquid manure anaerobic digestate depending on the soil. These findings indicate how several factors interact to impact trace gas emissions from these systems and the importance of these measurements to quantify the impact of changing management practices set to better air quality and mitigate climate change.