Observing urban CO2 emission changes from the transportation sector: COVID-19 and beyond
Presented by: Alex Turner, UC Berkeley
Summary: We describe application of the Berkeley Environmental Air-quality and CO2 Observation Network (BEACO2N) to quantify trace gas fluxes in an urban area. We quantify decreases CO2 emissions due to mobility restrictions from shelter-in-place orders due to COVID-19. BEACO2N has ~70 nodes on 2km spacing in the SF-Bay Area. Every node in the network observes an enhancement associated with the surrounding region. We couple a weather model with a back trajectory model to determine this region of influence. Following this, we use Bayesian inference to derive emissions before and during shelter-in-place. Additional effects such as the role of vehicle speed will be discussed.