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

Abstract:

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.