A Conservative Downscaling of Satellite-Detected Chemical Compositions: NO2 Column Densities of OMI, GOME-2, and CMAQ

Abstract

A conservative downscaling technique was applied when comparing nitrogen dioxide (NO 2 ) column densities from space-borne observations and a fine-scale regional model. The conservative downscaling was designed to enhance the spatial resolution of satellite measurements by applying the fine-scale spatial structure from the model, with strict mass conservation at each satellite footprint pixel level. With the downscaling approach, NO 2 column densities from the Ozone Monitoring Instrument (OMI; 13 × 24 km nadir footprint resolution) and the Global Ozone Monitoring Experiment-2 (GOME-2; 40 × 80 km) show excellent agreement with the Community Multiscale Air Quality (CMAQ; 4 × 4 km) NO 2 column densities, with R = 0.96 for OMI and R = 0.97 for GOME-2. We further introduce an approach to reconstruct surface NO 2 concentrations by combining satellite column densities and simulated surface-to-column ratios from the model. Compared with the Environmental Protection Agency's (EPA) Air Quality System (AQS) surface observations, the reconstructed surface concentrations show a good agreement; R = 0.86 for both OMI and GOME-2. This study demonstrates that the conservative downscaling approach is a useful tool to compare coarse-scale satellites with fine-scale models or observations in urban areas for air quality and emissions studies. The reconstructed fine-scale surface concentration field could be used for future epidemiology and urbanization studies.

Evaluating current satellite capability to observe diurnal change in nitrogen oxides in preparation for geostationary satellite missions

“…We find that AQS measurements from earlier time windows show slightly better agreement with OMI (r 2 =0.64 for 12:00 LST versus r 2 =0.59 for 13:00 LST, see table S1), which may be due to the lag between surface and column diurnal cycles (Fishman et al 2008). Our spatial correlation coefficients agree with prior work reporting spatial correlation of OMI with AQS monitors, including a comparison of 208 moni- Kim et al (2018) also found a correlation coefficient of r 2 =0.67 for GOME-2A.…”

“…Different approaches have been used to mitigate the smoothing effect for NO 2 when comparing instruments of different resolution. Methods include the regridding of the finer resolution instrument to larger grids (Boersma et al 2008(Boersma et al , 2009), down-sampling finer pixels by averaging them into larger pixels (Hilboll et al 2013), and 'downscaling' satellite data using a model (Kim et al 2018). We explore the potential and limitations in deriving diurnal change from polar-orbiting satellites at smaller scales, using both a re-gridding approach as well as a down-sampling approach.…”

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

“…To compare satellite models, conducting a fair comparison by matching spatial resolution and vertical sensitivity is crucial [62][63][64]. In this study, we processed satellite data using oversampling based on the conservative spatial regridding method and applied the average kernel to the modeled layers before integrating into the column density.…”

Assessment of NO<sub>2</sub> observations during DISCOVER-AQ and KORUS-AQ field campaigns

“…We apply the method described by Kim et al (2016Kim et al ( , 2018 to downscale OMI NO 2 retrievals, which are then compared with aircraft and Pandora data. This method applies high resolution model-derived spatial-weighting kernels to individual OMI pixels and calculates sub-pixel variability within the pixel.…”