First Top‐Down Estimates of Anthropogenic NOx Emissions Using High‐Resolution Airborne Remote Sensing Observations. Issue 6 (25th March 2018)

• Record Type: Journal Article
• Authors: Souri, Amir H.; Choi, Yunsoo; Pan, Shuai; Curci, Gabriele; Nowlan, Caroline R.; Janz, Scott J.; Kowalewski, Matthew G.; Liu, Junjie; Herman, Jay R.; Weinheimer, Andrew J.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 6(2018)
• Page Start: 3269
• Page End: 3284
• Publication Date: 2018-03-25
• Subjects: inverse modeling -- Kalman filter -- GCAS -- remote sensing -- NOx emissions; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2017JD028009
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2 ) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high‐resolution regional model (1 × 1 km 2 ) 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. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation ( r > 0.74) with an uncertainty of 3.5 × 10 15 molecules cm −2 . On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions. Key Points: We constrain anthropogenic NO x emissions by Kalman filter using the NO2 observations from GCAS sensor Constrained emissions counterbalance the well‐documented positive bias of 1 × 1 km 2 regional model against surface observations GCAS provides a unique opportunity to detect and constrain an emission event anomaly in the Houston area