Using Network Observations to Constrain CO and CO ₂ Emissions From an Oil Refinery in the San Francisco Bay Area

Point sources are often major contributors of greenhouse gas and air pollutant emissions in urban areas. Dense air monitoring networks provide a unique avenue for studying point source emissions over long time periods. Here, we use the Berkeley Environmental Air‐quality and CO 2 Network (BEACO 2 N) to study CO 2 and air pollutant emissions from an oil refinery in the city of Richmond, CA. We identify 266 plumes crossing one or more sites in the BEACO 2 N network during 2022–2023 as having a source at the refinery and quantify CO 2 emissions using the Gaussian plume model. The refinery is modeled as two point sources, and total CO 2 emissions are found to be 61.3 ± 6.3 kg s −1 , in close agreement with the EPA Facility Level Information on GreenHouse gases Tool inventory and Carbon Mapper measurements. Additionally, plume composition was found to vary, with CO/CO 2 enhancement ratios ranging from 0 to 5 ppb/ppm. Taking the average CO/CO 2 ratio, CO emissions are estimated to be roughly 3,000 mt, a sizable amount compared to the city's estimated non‐refinery CO emissions of 6,800 mt. In addition, we show that dense monitoring networks provide a unique resource for point source emissions quantification with broad application to plumes of varying size and composition, and recommendations are laid out for future applications.