A33C-0177
Estimating methane emissions from dairies in the Los Angeles Basin

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Camille Viatte1, Thomas Lauvaux2, Jacob Hedelius1, Harrison Alexander Parker3, Jia Chen4, Taylor Jones4, Jonathan Franklin5, Aijun Deng2, Brian Gaudet2, Riley M Duren6, Kristal R Verhulst6, Debra Wunch1, Coleen Marie Roehl1, Manvendra Krishna Dubey3, Stephen Wofsy4 and Paul O Wennberg7, (1)California Institute of Technology, Pasadena, CA, United States, (2)Pennsylvania State University Main Campus, University Park, PA, United States, (3)Los Alamos National Laboratory, Los Alamos, NM, United States, (4)Harvard University, Cambridge, MA, United States, (5)Dalhousie University, Halifax, Canada, (6)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (7)California Institute of Technology, Division of Engineering and Applied Science, Pasadena, CA, United States
Abstract:
Inventory estimates of methane (CH4) emissions among the individual sources (mainly agriculture, energy production, and waste management) remain highly uncertain at regional and urban scales. Accurate atmospheric measurements can provide independent estimates to evaluate bottom-up inventories, especially in urban region, where many different CH4 sources are often confined in relatively small areas. Among these sources, livestock emissions, which are mainly originating from dairy cows, account for ~55% of the total CH4 emissions in California in 2013.

This study aims to rigorously estimate the amount of CH4 emitted by the largest dairies in the Southern California region by combining measurements from four mobile ground-based spectrometers (EM27/SUN), in situ isotopic methane measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport model (the Weather Research and Forecasting model) in Large-Eddy Simulation mode.

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 about total emissions of the dairies. Gradients measured by the four EM27 ranged from 0.2 to 22 ppb and from 0.7 to 3 ppm for XCH4 and XCO2, respectively. To assess the fluxes of the dairies, measurements of these gradients are used in conjunction with the local atmospheric dynamics simulated at 111 m resolution. Inverse modelling from WRF-LES is employed to resolve the spatial distribution of CH4 emissions in the domain. A Bayesian inversion and a Monte-Carlo approach were used to provide the CH4 emissions over the dairy with their associated uncertainties. The isotopic δ13C sampled at different locations in the area ranges from -40 ‰ to -55 ‰, indicating a mixture of anthropogenic and biogenic sources.

<< Previous Abstract | Next Abstract