Evaluating California dairy methane emission factors using short-term ground-level and airborne measurements

Amini, Seyedmorteza; Kuwayama, Toshihiro; Gong, Longwen; Falk, Matthias M.; Chen, Yanju; Mitloehner, Qian; Weller, Stephen G.; Patteson, Douglas; Conley, Stephen; Scheehle, E.; FitzGibbon, Michael

doi:10.1016/j.aeaoa.2022.100171

Cited by 3 publications

(18 citation statements)

References 20 publications

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“…Table S3 compares the effective dairy cow methane emission factors inferred from our measurements in the Dairy/MB region with the results of multiple recent observational studies in California and Colorado. ,, All measurements were performed during summer months (June–August), and average diurnal ground-level temperatures varied from 24 to 30 °C. Dairies sampled in the studies conducted in California used similar manure management practices (primarily liquid storage systems), and we suspect the same is true for the Colorado dairies based on satellite imagery.…”

Section: Resultsmentioning

confidence: 99%

“…Higher wind speeds during cooler months have been suggested to account for the lack of seasonality in emissions. 11,12 During RECAP-CA, lower temperatures were not associated with considerably higher wind speeds (average of ∼3.3 m s −1 in the lowest temperature tercile and 2.8 m s −1 in the highest) and therefore, any effect of local temperature variability on methane fluxes was unlikely to be offset by simultaneous changes in local wind speeds. Assumptions regarding the seasonality/meteorological dependence of dairy methane emissions critically influence assessments of annual average inventory predictions using short-term measurements.…”

Section: Comparison With Previous Observational and Inverse Modeling ...mentioning

confidence: 96%

“…11,12,37 Longer-term data sets collected across seasons may allow further development and/or verification of emission parametrizations that incorporate dependencies on temperature, anaerobic lagoon agitation (e.g., through surface winds and/or rainfall), and subtle differences in manure management practices. 9,11,15,38 Additional precise measurements of methane emissions in the southern SJV will likely be needed to assess statewide progress toward dairy methane emission reduction goals. While improvement and expansion of existing long-term measurements networks will be critical for such monitoring, 43 our results suggest that airborne measurements could provide a useful complement to the stationary monitoring network.…”

Section: Atmospheric Implicationsmentioning

confidence: 99%

“…Estimates using inverse modeling techniques applied to both long-term , and short-term , measurements suggest that methane emissions from dairy livestock may be twice as large as the California Air Resources Board (CARB) predicts. However, recent short-term measurements at individual dairy facilities, surveys of multiple dairy facilities using mobile measurement techniques, , and short-term inverse modeling studies have supported the accuracy of CARB emission predictions.…”

Section: Introductionmentioning

confidence: 99%

“…Emissions from dairies may vary on seasonal and daily time scales ,, and may be highly intermittent, driven either by temporal variability in routine operations or spontaneous leaks in emission containment devices . Given this complexity and the relative lack of coordinated observational emissions studies in California, ,,, additional direct measurements of dairy emissions are needed to evaluate the accuracy of the state emission inventory.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Schulze,

Ward,

Pfannerstill

et al. 2023

Environ. Sci. Technol.

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Section: Resultsmentioning

confidence: 99%

Section: Comparison With Previous Observational and Inverse Modeling ...mentioning

confidence: 96%

Section: Atmospheric Implicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Schulze,

Ward,

Pfannerstill

et al. 2023

Environ. Sci. Technol.

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Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Zhu,

González-Rocha,

Ding

et al. 2024

Atmos. Meas. Tech.

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Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s−1 when the wind magnitude is less than 3.5 m s−1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH4 emissions in near real time.

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Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft Aircore system

Zhu

González-Rocha

Ding

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and Aircore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11-m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s-1 when the wind magnitude is less than 3.5 m s-1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over 10 second periods or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAAS have great potential as a low-cost tool for detecting and quantifying CH4 emissions in near real-time.

show abstract

Evaluating California dairy methane emission factors using short-term ground-level and airborne measurements

Cited by 3 publications

References 20 publications

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

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

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft Aircore system

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