Constraining NOx Emissions Using Spaceborne and Airborne Remotely Sensed NO2 Observations in the Southeast Texas



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Nitrogen oxides (NOx=NO+NO2) largely contribute to ozone formation which is a criterion air pollutant adversely affecting human health and crop yields. They are emitted by a range of anthropogenic and natural sources. The anthropogenic emissions are commonly estimated from the bottom-up inventories which are complicated by errors in underlying assumptions and county-level statistics. Therefore, the bottom-up NOx emissions could induce large biases and quickly become obsolete, which in turn introduce an obstacle for chemical transport models that heavily rely on this information. NO2 (a proxy for NOx) molecules have strong absorption in the ultra-violent wavelengths which facilitates their retrieval from several remote sensing sensors. We use tropospheric NO2 columns from Ozone Monitoring Instrument (OMI) to provide constraints on the bottom-up emissions using a Bayesian inversion in conjunction with the Community Multiscale Air Quality (CMAQ) model associated with Decoupled Direct Method (DDM) in Southeast Texas during DISCOVER-AQ campaign. Results suggest a reduction in area (44%), mobile (30%), and point sources (60%) in high NOx areas (ENOx> 0.2 mol/s). The top-down estimation largely mitigates the overprediction of the model in reproducing surface NO2 against monitoring sites. However, under-prediction of model NO2 in Houston on 09/25–09/26 potentially resulting from the unprecedented local NOx sources from the Houston Ship Channel (HSC) becomes more evident. To address this, we utilize, for the first time, the NO2 columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain NOx emissions in the Houston‐Galveston‐Brazoria area. To incorporate the observations into an analytical inversion, we convert the slant density columns to vertical columns using a radiative transfer model with i) NO2 profiles from a high‐resolution regional model (1×1 km2) constrained by P‐3B aircraft measurements, ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and iii) high‐resolution surface albedo constrained by ground‐based spectrometers. The modest high-quality observations from this airborne sensor enable us to quantify the unprecedented local emissions. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.



Inverse modeling, Emissions, Remote sensing