Methane emissions from dairies in the Los Angeles Basin
- California Inst. of Technology (CalTech), Pasadena, CA (United States). Division of Geological and Planetary Sciences
- Pennsylvania State Univ., University Park, PA (United States). Dept. of Meteorology
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences
- California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.
We estimate the amount of methane (CH4) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic 13/12CH4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES). The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH4 and CO2 (XCH4 and XCO2) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22ppb (part per billion) and from 0.7 to 3ppm (part per million) for XCH4 and XCO2, respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111m resolution. Our top-down CH4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8ppts-1 are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH4 emissions of 2.2 to 3.5ppts-1 at Chino.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); California Institute of Technology (CalTech), Pasadena, CA (United States); Harvard Univ., Cambridge, MA (United States)
- Sponsoring Organization:
- USDOE; LANL Laboratory Directed Research and Development (LDRD) Program; National Aeronautics and Space Administration (NASA); W. M. Keck Foundation (United States); National Science Foundation (NSF)
- Grant/Contract Number:
- AC52-06NA25396; 1337512
- OSTI ID:
- 1463494
- Report Number(s):
- LA-UR-18-21241
- Journal Information:
- Atmospheric Chemistry and Physics (Online), Vol. 17, Issue 12; ISSN 1680-7324
- Publisher:
- European Geosciences UnionCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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