ALBERT

Beschreibung: 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 simulations with 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 about total emissions of the dairies at Chino. Gradients measured by the four EM27/SUN 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, these gradient measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111 m resolution. Our top-down CH4 emissions derived using the Fourier Transform Spectrometers (FTS) observations of 1.4 to 4.8 ppt/s are in the low-end of previous top-down estimates, consistent with reductions of the dairy farms with urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by 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 3.2 to 4.7 ppt/s at Chino.