Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?

Short summary

In this paper, the interplay between aerosols and the OMI O₂–O₂ cloud retrieval algorithm is analysed in detail to evaluate the impacts on the accuracy of the tropospheric NO₂ retrievals over cloud-free scenes. Collocated OMI NO₂ and MODIS Aqua aerosol products are compared over North-East China, in industrialized areas; the OMI O₂–O₂ cloud retrieval algorithm is implemented on synthetic study cases dominated by aerosol particles, in order to evaluate and demonstrate the response of the OMI effective cloud retrievals to the particles. The resulting biases highlight the need for an improved aerosol correction.

Key figures

amt-2015-160-discussions-f02 — Altitude-resolved Air Mass Factor at 439 nm without and with aerosols at different atmospheric layers (AOT = 1)

figurewebsite1 — OMI effective cloud fraction as a function of collocated MODIS-Aqua AOT and OMI surface albedo climatology: 3 years (2005-2007), North-East China, summer.

amt-2015-160-discussions-f13 — O2-O2 slant column density and continuum reflectance (475 nm) as a function of effective cloud and aerosol parameters. The ellipses are the simulation nodes. The background colors result from the interpolation / extrapolation of the fit results: a) effective cloud fracton, b) effective cloud pressure [hPa], c) aerosol optical thickness (AOT), d) atmospheric aerosol pressure [hPa]

amt-2015-160-discussions-f15 — Tropospheric NO2 Air Mass Factor biases for different atmospheric aerosol layers and AOT: a) biases assuming no aerocol correction (i.e. clear sky), b) biases assuming implicit aerosol correction through the OMI cloud algorithm.

Abstract

The Ozone Monitoring Instrument (OMI) has provided daily global measurements of tropospheric NO₂ for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO₂ 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 NO₂ retrieval chain (DOMINO – Derivation of OMI tropospheric NO₂) product. Instead, the operational OMI O₂ − O₂ cloud retrieval algorithm is applied both to cloudy and to cloud-free scenes (i.e. clear sky) dominated by the presence of aerosol. 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 O₂ − O₂ cloud retrieval algorithm. Then, it evaluates the impact on the accuracy of the tropospheric NO₂ retrievals through the computed Air Mass Factor (AMF) with a focus on cloud-free scenes. For that purpose, collocated OMI NO₂ 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 NO₂ AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based 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 O₂ − O₂ 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 NO₂ 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 NO₂, aerosol correction based on the cloud model results in an overestimation of the DOMINO tropospheric NO₂ column, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO₂ 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 NO₂ AMFs.