Impact of aerosols on the OMI tropospheric NO<sub>2</sub> retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

Abstract

Abstract. The Ozone Monitoring Instrument (OMI) has provided daily global measurements of tropospheric NO 2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO 2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current operational OMI tropospheric NO 2 retrieval chain (DOMINO -Derivation of OMI tropospheric NO 2 ) product. Instead, the operational OMI O 2 −O 2 cloud retrieval algorithm is applied both to cloudy and to cloud-free scenes (i.e. clear sky) dominated by the presence of aerosols. This paper describes in detail the complex interplay between the spectral effects of aerosols in the satellite observation and the associated response of the OMI O 2 −O 2 cloud retrieval algorithm. Then, it evaluates the impact on the accuracy of the tropospheric NO 2 retrievals through the computed Air Mass Factor (AMF) with a focus on cloud-free scenes. For that purpose, collocated OMI NO 2 and MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua aerosol products are analysed over the strongly industrialized East China area. In addition, aerosol effects on the tropospheric NO 2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observationbased and the simulation-based approach demonstrate that the retrieved cloud fraction increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT primarily represents the shielding effects of the O 2 −O 2 column located below the aerosol layers. The study cases show that the aerosol correction based on the implemented OMI cloud model results in biases between −20 and −40 % for the DOMINO tropospheric NO 2 product in cases of high aerosol pollution (AOT ≥ 0.6) at elevated altitude. These biases result from a combination of the cloud model error, used in the presence of aerosols, and the limitations of the current OMI cloud Look-Up- Table (LUT). A new LUT with a higher sampling must be designed to remove the complex behaviour between these biases and AOT. In contrast, when aerosols are relatively close to the surface or mixed with NO 2 , aerosol correction based on the cloud model results in an overestimation of the DOMINO tropospheric NO 2 column, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO 2 measurements in the presence of high aerosol pollution and particles located at higher altitudes. This highlights the need to implement an improved aerosol correction in the computation of tropospheric NO 2 AMFs.

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

“…The results indicate a systematic increase of eCF and CTP with increasing AOD, but also a large scatter, especially for AOD < 1. The systematic increase of eCF and CTP with AOD is consistent with the model simulations in Chimot et al (2016). The variability of eCF and CTP can be attributed to different observation geometries as well as uncertainties of the cloud retrievals (e.g.…”

“…Leitão et al (2010) and Chimot et al (2016) found that the influence of aerosols on the satellite retrievals mainly de- Figure 14. Absolute differences (a) and relative differences (b) of tropospheric VCDs of NO 2 , SO 2 and HCHO between individual OMI observations and MAX-DOAS observations plotted against the AODs derived from the MAX-DOAS observations.…”

“…If a Lambertian cloud model is used, the effect of this implicit aerosol correction depends systematically on the aerosol properties Lin et al, 2014;Wang et al, 2015;Chimot et al, 2016). For mostly scattering aerosols at high altitudes, the implicit aerosol correction can largely account for the aerosol effect on the TG products .…”

“…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.…”

Space-based NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; emission estimates over remote regions improved in DECSO

“…In DECSO, the grid NO 2 columns simulated by the CTM are projected via a high-resolution grid onto the footprint of satellite observations, which avoids the bias caused by different resolutions of the CTM and satellite observations. The NO 2 observations can suffer from biases in scenes with high aerosol concentrations (Lin et al, 2014;Kuhlmann et al, 2015;Chimot et al, 2016) or the limited resolution of the a priori information used in the retrieval cases with high NO 2 concentration gradients (Heckel et al, 2011;Russell et al, 2011;Laughner et al, 2016). In China, however, there are few isolated emission sources with large concentration gradients.…”