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Title: Methane emissions from dairies in the Los Angeles Basin

Abstract

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 themore » 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.« less

Authors:
 [1];  [2]; ORCiD logo [1];  [3];  [4];  [4];  [4];  [2];  [2]; ORCiD logo [5];  [5]; ORCiD logo [1];  [1];  [3];  [4];  [1]
  1. California Inst. of Technology (CalTech), Pasadena, CA (United States). Division of Geological and Planetary Sciences
  2. Pennsylvania State Univ., University Park, PA (United States). Dept. of Meteorology
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences
  5. California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.
Publication Date:
Research Org.:
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 Org.:
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)
OSTI Identifier:
1463494
Report Number(s):
LA-UR-18-21241
Journal ID: ISSN 1680-7324
Grant/Contract Number:  
AC52-06NA25396; 1337512
Resource Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 17; Journal Issue: 12; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Viatte, Camille, Lauvaux, Thomas, Hedelius, Jacob K., Parker, Harrison, Chen, Jia, Jones, Taylor, Franklin, Jonathan E., Deng, Aijun J., Gaudet, Brian, Verhulst, Kristal, Duren, Riley, Wunch, Debra, Roehl, Coleen, Dubey, Manvendra K., Wofsy, Steve, and Wennberg, Paul O. Methane emissions from dairies in the Los Angeles Basin. United States: N. p., 2017. Web. doi:10.5194/acp-17-7509-2017.
Viatte, Camille, Lauvaux, Thomas, Hedelius, Jacob K., Parker, Harrison, Chen, Jia, Jones, Taylor, Franklin, Jonathan E., Deng, Aijun J., Gaudet, Brian, Verhulst, Kristal, Duren, Riley, Wunch, Debra, Roehl, Coleen, Dubey, Manvendra K., Wofsy, Steve, & Wennberg, Paul O. Methane emissions from dairies in the Los Angeles Basin. United States. https://doi.org/10.5194/acp-17-7509-2017
Viatte, Camille, Lauvaux, Thomas, Hedelius, Jacob K., Parker, Harrison, Chen, Jia, Jones, Taylor, Franklin, Jonathan E., Deng, Aijun J., Gaudet, Brian, Verhulst, Kristal, Duren, Riley, Wunch, Debra, Roehl, Coleen, Dubey, Manvendra K., Wofsy, Steve, and Wennberg, Paul O. Wed . "Methane emissions from dairies in the Los Angeles Basin". United States. https://doi.org/10.5194/acp-17-7509-2017. https://www.osti.gov/servlets/purl/1463494.
@article{osti_1463494,
title = {Methane emissions from dairies in the Los Angeles Basin},
author = {Viatte, Camille and Lauvaux, Thomas and Hedelius, Jacob K. and Parker, Harrison and Chen, Jia and Jones, Taylor and Franklin, Jonathan E. and Deng, Aijun J. and Gaudet, Brian and Verhulst, Kristal and Duren, Riley and Wunch, Debra and Roehl, Coleen and Dubey, Manvendra K. and Wofsy, Steve and Wennberg, Paul O.},
abstractNote = {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.},
doi = {10.5194/acp-17-7509-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 12,
volume = 17,
place = {United States},
year = {Wed Jun 21 00:00:00 EDT 2017},
month = {Wed Jun 21 00:00:00 EDT 2017}
}

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