Influence of mixing height and atmospheric stability conditions on correlation of NO2 columns and surface concentrations in a Mexico‐United States border region

Abstract The objective was to analyze how representative tropospheric NO2 column densities are of surface NO2 measurements under different atmospheric stability conditions in the air basin of two border cities: Calexico, United States, and Mexicali, Mexico. NO2 columns were measured by the Ozone Monitoring Instrument (OMI) on the NASA Aura satellite. NO2 concentrations and meteorological parameters were also measured on the surface for comparison. Specifically, the correlations between OMI and surface NO2 concentrations under different atmospheric stability conditions according to the Pasquill‐Gifford (P‐G) and Monin‐Obukhov (M‐O) classification schemes were determined for 2017 and 2018. During the passage of the satellite through the study area (11:00–13:00 UTC−8), unstable conditions were documented in both years. Good correlation was found between the surface NO2 and OMI NO2 column observations in the second semester of each year, particularly under unstable conditions as diagnosed by the P‐G and M‐O schemes applied in the first and second year, respectively. However, a weakening of these conditions occurs during the autumn–winter period. In both cases, the highest determination coefficients were found for Calexico, with values of 0.48 and 0.36 in 2017 and 2018, respectively; for Mexicali, the determination coefficients were 0.23 and 0.35, respectively. Under each atmospheric stability scheme, the mechanical and convective turbulence caused a decreasing trend in wind speed and solar radiation over the course of second semester of 2017 and in friction velocity, temperature, and sensible heat flux over the course of the same period for 2018. The negative trend of these parameters during the analyzed time frames helped to reduce the influence of unstable atmospheric conditions, favoring better correlations between satellite and surface NO2 measurements. The methodology applied and results obtained herein can enable us to better understand the representativeness of OMI NO2 data in arid border zones with extreme meteorological conditions.

Abstract licence: CC BY

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