Abstract. In this study, we present a novel approach for assessing nearshore seepage atmospheric emissions through modeling of air quality station data, specifically, a Gaussian plume inversion model. Three decades of air quality station meteorology and total hydrocarbon concentration, THC, data were analysed to study emissions from the Coal Oil Point marine seep field offshore California. THC in the seep field directions was significantly elevated and Gaussian with respect to wind direction, θ. An inversion model of the seep field anomaly, THC’(θ), derived atmospheric emissions. The model inversion is for the far field, which was satisfied by gridding the sonar seepage and treating each grid cell as a separate Gaussian plume. This assumption was validated by offshore in situ offshore data that showed major seep area plumes were Gaussian. Plume air sample THC was 85 % methane, CH4, and 20 % carbon dioxide, CO2, similar to seabed composition, demonstrating efficient vertical plume transport of dissolved seep gases. Air samples also measured atmospheric alkane plume composition. The inversion model used observed winds and derived the three-decade-average (1990–2021) field-wide atmospheric emissions of 83,500 ± 12,000 m3 THC day−1. Based on a 50:50 air to seawater partitioning, this implies seabed emissions of 167,000 m3 THC dy−1. Based on atmospheric plume composition, C1-C6 alkane emissions were 19, 1.3, 2.5, 2.2, 1.1, and 0.15 Gg yr−1, respectively. The approach can be extended to derive emissions from other dispersed sources such as landfills, industrial sites, or terrestrial seepage if source locations are constrained spatially.