Assimilating Morning, Evening, and Nighttime Greenhouse Gas Observations in Atmospheric Inversions

Abstract Improved urban greenhouse gas (GHG) flux estimates are crucial for informing policy and mitigation efforts. Atmospheric inversion modeling (AIM) is a widely used technique combining atmospheric measurements of trace gas, meteorological modeling, and a prior emission map to infer fluxes. Traditionally, AIM relies on mid‐afternoon observations due to the well‐represented atmospheric boundary layer in meteorological models. However, confining flux assessment to daytime observations is problematic for the urban scale, where air masses typically move over a city in a few hours and AIM therefore cannot provide improved constraints on emissions over the full diurnal cycle. We hypothesized that there are atmospheric conditions beyond the mid‐afternoon under which meteorological models also perform well. We tested this hypothesis using tower‐based measurements of CO 2 and CH 4 , wind speed observations, weather model outputs from INFLUX (Indianapolis Flux Experiment), and a prior emissions map. By categorizing trace gas vertical gradients according to wind speed classes and identifying when the meteorological model satisfactorily simulates boundary layer depth (BLD), we found that non‐afternoon observations can be assimilated when wind speed is >5 m/s. This condition resulted in small modeled BLD biases (<40%) when compared to calmer conditions (>100%). For Indianapolis, 37% of the GHG measurements meet this wind speed criterion, almost tripling the observations retained for AIM. Similar results are expected for windy cities like Auckland, Melbourne, and Boston, potentially allowing AIM to assimilate up to 60% of the total (24‐hr) observations. Incorporating these observations in AIMs should yield a more diurnally comprehensive evaluation of urban GHG emissions.