Technical note: Evaluation of profile retrievals of aerosols and trace gases for MAX-DOAS measurements under different aerosol scenarios based on radiative transfer simulations
Year: 2021
Type: article
Abstract: . Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a state of the art remote sensing technique for deriving vertical profiles of trace gases and aerosols. However, MAX-DOAS profile inversions under aerosol pollution scenarios are challenging because of the complex radiative transfer and limited information content of the measurements. In this study, the performances of two inversion algorithms were evaluated for various aerosol pollution scenarios based on synthetic slant column densities (SCDs) derived from radiative transfer simulations. One inversion algorithm is based on optimal estimation, the other uses a parameterized approach. In this analysis, 3 types of profile shapes for aerosols and NO2 were considered: exponential, Boltzmann, and Gaussian. First, the systematic deviations of the retrieved aerosol profiles from the input profiles were investigated. For most cases, the AODs of the retrieved profiles were found to be systematically lower than the input values, and the deviations increased with increasing AOD. Especially for the optimal estimation algorithm and for high AOD, these findings might explain part of the deviations between the AOD retrieved from MAX-DOAS and sun photometers in previous studies. For the optimal estimation algorithm the agreement with the input values can be improved by optimizing the covariance matrix of the a priori uncertainties. Second, the aerosol effects on the NO2 profile retrieval were tested. Here, especially for the optimal estimation algorithm, a systematic dependence on the NO2 VCD was found with a strong relative overestimation of the retrieved results for low NO2 VCDs and an underestimation for high NO2 VCDs. In contrast, the dependence on the aerosol profiles was found to be rather low. In general, both inversion schemes can well retrieve the near-surface values of aerosol extinction and trace gases concentrations.
Institutions: Anhui University, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, European Organisation for the Exploitation of Meteorological Satellites, Max Planck Institute for Chemistry, University of Science and Technology of China, Institute of Urban Environment, University of Chinese Academy of Sciences
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,725
OpenAlex ID: W3132001309