Evaluating the effects of columnar NO2on the accuracy of aerosol optical properties retrievals

Abstract

Abstract. We aim to evaluate the NO2 absorption effect in aerosol columnar properties, namely the aerosol optical depth (AOD), Ångström exponent (AE), and single scattering albedo (SSA), derived from sun–sky radiometers in addition to the possible retrieval algorithm improvements by using more accurate characterization of NO2 optical depth from co-located or satellite-based real-time measurements. For this purpose, we employ multiannual (2017–2022) records of AOD, AE, and SSA collected by sun photometers at an urban and a suburban site in the Rome area (Italy) in the framework of both the Aerosol Robotic Network (AERONET) and SKYNET networks. The uncertainties introduced in the aerosol retrievals by the NO2 absorption are investigated using high-frequency observations of total NO2 derived from co-located Pandora spectroradiometer systems in addition to spaceborne NO2 products from the Tropospheric Monitoring Instrument (TROPOMI). For both AERONET and SKYNET, the standard network products were found to systematically overestimate AOD and AE. The average AOD bias found for Rome is relatively low for AERONET (∼ 0.002 at 440 nm and ∼ 0.003 at 380 nm) compared to the retrieval uncertainties but quite a bit higher for SKYNET (∼ 0.007). On average, an AE bias of ∼ 0.02 and ∼ 0.05 was estimated for AERONET and SKYNET, respectively. In general, the correction seems to be low for areas with low columnar NO2 concentrations, but it is still useful for low AODs (< 0.3), where the majority of observations are found, especially under high NO2 pollution events. For the cases of relatively high NO2 levels (> 0.7 DU), the mean AOD bias was found within the range 0.009–0.012 for AERONET, depending on wavelength and location, and about 0.018 for SKYNET. The analysis does not reveal any significant impact of the NO2 correction on the derived aerosol temporal trends for the very limited data sets used in this study. However, the effect is expected to become more evident for trends derived from larger data sets and in the case of an important NO2 trend. In addition, the comparisons of the NO2-modified ground-based AOD data with satellite retrievals from the Deep Blue (DB) algorithm of the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) resulted in a slight improvement in the agreement of about 0.003 and 0.006 for AERONET and SKYNET, respectively. Finally, the uncertainty in assumptions on NO2 seems to have a non-negligible impact on the retrieved values of SSA at 440 nm leading to an average positive bias of about 0.02 (2 %) in both locations for high NO2 loadings (> 0.7 DU).