Estimating CO2 fluxes in the Bay Area from a dense surface network: First estimates from the Berkeley Atmospheric CO2 Observation Network (BeACON)

Friday, 19 December 2014: 11:05 AM
Alexander J. Turner1, Brian C Mcdonald2, Virginia E Teige3, Alexis Shusterman3, Holly Maness4, Robert Harley5 and Ronald C Cohen2, (1)Harvard University, Cambridge, MA, United States, (2)University of California Berkeley, Berkeley, CA, United States, (3)UC Berkeley, Berkeley, CA, United States, (4)Univ of California Berkeley, Berkeley, CA, United States, (5)Univ California, Berkeley, CA, United States
The paradigm in ground-based trace gas measurements has been to employ a sparse network of high-precision instruments that can be used to measure atmospheric concentrations. However, the Berkeley Atmospheric CO2 Observation Network (BeACON) project aims to provide a better understanding of the emissions and physical processes governing CO2 by deploying a high density of moderate-precision instruments. Here we present the first estimate of hourly urban carbon dioxide fluxes at 1 km spatial resolution in California's Bay Area using the BeACON network. The CO2 fluxes are estimated in a mesoscale inverse modeling framework using WRF-STILT and a custom state-of-the-science prior inventory. We also present a series of Observing System Simulation Experiments (OSSEs) with synthetic observations derived from our custom 1 km inventory that resolves fine-scale CO2 fluxes such as individual highways and attempt to retrieve them using the EDGARv4.2 and VULCAN inventories, which are too coarse to resolve individual highways. These OSSEs allow us to determine the extent to which a dense network can quantify fine-scale CO2 fluxes from sources such as traffic and provide an estimate of the information content of a dense network. This will allow us to place rigorous error bounds on the CO2 fluxes from California's Bay Area and inform future greenhouse gas measurement strategies.