OMI tropospheric NO<sub>2</sub> air mass factors over South America: effects of biomass burning aerosols

Abstract

Abstract. Biomass burning is an important and uncertain source of aerosols and NOx (NO + NO2) to the atmosphere. Satellite observations of tropospheric NO2 are essential for characterizing this emissions source, but inaccuracies in the retrieval of NO2 tropospheric columns due to the radiative effects of aerosols, especially light-absorbing carbonaceous aerosols, are not well understood. It has been shown that the O2–O2 effective cloud fraction and pressure retrieval is sensitive to aerosol optical and physical properties, including aerosol optical depth (AOD). Aerosols implicitly influence the tropospheric air mass factor (AMF) calculations used in the NO2 retrieval through the effective cloud parameters used in the independent pixel approximation. In this work, we explicitly account for the effects of biomass burning aerosols in the Ozone Monitoring Instrument (OMI) tropospheric NO2 AMF calculation for cloud-free scenes. We do so by including collocated aerosol extinction vertical profile observations from the CALIOP instrument, and aerosol optical depth (AOD) and single scattering albedo (SSA) retrieved by the OMI near-UV aerosol algorithm (OMAERUV) in the DISAMAR radiative transfer model. Tropospheric AMFs calculated with DISAMAR were benchmarked against AMFs reported in the Dutch OMI NO2 (DOMINO) retrieval; the mean and standard deviation of the difference was 0.6 ± 8 %. Averaged over three successive South American biomass burning seasons (2006–2008), the spatial correlation in the 500 nm AOD retrieved by OMI and the 532 nm AOD retrieved by CALIOP was 0.6, and 68 % of the daily OMAERUV AOD observations were within 30 % of the CALIOP observations. Overall, tropospheric AMFs calculated with observed aerosol parameters were on average 10 % higher than AMFs calculated with effective cloud parameters. For effective cloud radiance fractions less than 30 %, or effective cloud pressures greater than 800 hPa, the difference between tropospheric AMFs based on implicit and explicit aerosol parameters is on average 6 and 3 %, respectively, which was the case for the majority of the pixels considered in our study; 70 % had cloud radiance fraction below 30 %, and 50 % had effective cloud pressure greater than 800 hPa. Pixels with effective cloud radiance fraction greater than 30 % or effective cloud pressure less than 800 hPa corresponded with stronger shielding in the implicit aerosol correction approach because the assumption of an opaque effective cloud underestimates the altitude-resolved AMF; tropospheric AMFs were on average 30–50 % larger when aerosol parameters were included, and for individual pixels tropospheric AMFs can differ by more than a factor of 2. The observation-based approach to correcting tropospheric AMF calculations for aerosol effects presented in this paper depicts a promising strategy for a globally consistent aerosol correction scheme for clear-sky pixels.

Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

“…For mostly scattering aerosols at high altitudes, the implicit aerosol correction can largely account for the aerosol effect on the TG products . However, in some important cases (for low altitude aerosols with high AOD and small SSA) the implicit correction might even increase the errors of the AMF Castellanos et al (2015).…”

“…But aerosol effects on the satellite retrievals are still not well understood. The aerosol effects can be generally separated into two contributions: (a) the effect of aerosols on the satellite AMF compared to AMFs for a pure Rayleigh atmosphere (explicit aerosol correction), and (b) the effect of aerosols on the retrieval of cloud products (often referred to as "implicit aerosol correction", Boersma et al, 2011;Castellanos et al, 2015;Chimot et al, 2016). These two contributions of aerosols on the satellite retrievals are discussed in this study based on the aerosol and TG profiles derived from the MAX-DOAS observations in Wuxi and by comparing the satellite TG VCDs to the corresponding results from the MAX-DOAS observations.…”

An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach

“…, ALP, τ , the OMI effective cloud pressure and fraction on the other hand Castellanos et al, 2015;Chimot et al, 2016). Therefore, this study only focuses on cloud-free reflectance to avoid this complexity.…”

“…For example, the OMI O 2 −O 2 absorption band at 477 nm has been widely exploited to derive cloud information (Acarreta et al, 2004;Sneep et al, 2008). However, the OMI cloud algorithm is sensitive to aerosols, and thus the retrieved effective cloud parameters are modified in their presence (Boersma et al, 2007;Castellanos et al, 2015;Chimot et al, 2016). The OMI O 2 −O 2 spectral band at 477 nm contains significant information on aerosol properties and height.…”

“…The retrieved effective clouds are then used to correct the computed AMF (de Smedt et al, 2008;Boersma et al, 2011). In spite of these well-considered perturbations, the use of the effective cloud parameters, assuming that the opaque Lambertian cloud model can reproduce the distribution of scattering fine particle effects, does not yet completely correct for the aerosol effects when computing the AMF, in particular for the tropospheric NO 2 columns (Castellanos et al, 2015;Chimot et al, 2016).…”