USTC‐PRM: A Parameterized Approach for Profile Retrieval of Aerosol and Trace Gases

Abstract Profiles of aerosol and trace gases are crucial for assessing air pollution changes, identifying the high‐altitude transport of pollutants, and providing a foundation for tracing pollution sources. This study introduces the USTC Parameterized Retrieval Method (USTC‐PRM), an algorithm for retrieving profiles of aerosol extinction and trace gas concentration from MAX‐DOAS measurements. Using the Radiative Transfer Model (RTM), we evaluate the impact of various observation geometries and profile shapes on the air mass factor (AMF) and establish the look‐up table (LUT). USTC‐PRM overcomes the underestimation of high‐altitude aerosols by optimal estimation method (OEM) since it does not rely on prior profiles. The correlation between the retrieved AOD and AERONET AOD is 0.896, compared to 0.826 for the contrasted OEM. For trace gas retrieval, we propose a real‐time LUT establishment method based on retrieved aerosol profiles, significantly reducing memory requirements by over 90% (7.8 GB) and improving the correlation with in situ measurements from 0.867 to 0.911. Additionally, we introduce the concept of look‐up error table (LET) to quantify the AMF bias by retrieving it from LUT. We establish a quality evaluation system based on fitting results, LUT errors, and parameter statistics. Using synthetic data and long‐term MAX‐DOAS measurements, USTC‐PRM demonstrates high performance in retrieving profiles under various aerosol scenarios across high, medium, and low extinction levels, while also identifying abnormal situations, such as foggy and cloudy conditions. USTC‐PRM provides a robust, accurate and efficient approach for MAX‐DOAS profile retrieval, which can be utilized for studying regional transport and tracing atmospheric pollutants.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-09-18
DOI
https://doi.org/10.1029/2025jd043410
Primary Topic
Atmospheric aerosols and clouds
Type
article
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0.00
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article

USTC‐PRM: A Parameterized Approach for Profile Retrieval of Aerosol and Trace Gases

Guiqian Tang, Q.J. Li, Chengzhi Xing, Xiangguang Ji et al.
Journal of Geophysical Research Atmospheres
Atmospheric aerosols and clouds
article

USTC‐PRM: A Parameterized Approach for Profile Retrieval of Aerosol and Trace Gases

Guiqian Tang, Q.J. Li, Chengzhi Xing, Xiangguang Ji, Z.F. Zhang, Chuan Lu, Cheng Liu, Yanyu Kang, Qihou Hu
article en

Abstract

Abstract Profiles of aerosol and trace gases are crucial for assessing air pollution changes, identifying the high‐altitude transport of pollutants, and providing a foundation for tracing pollution sources. This study introduces the USTC Parameterized Retrieval Method (USTC‐PRM), an algorithm for retrieving profiles of aerosol extinction and trace gas concentration from MAX‐DOAS measurements. Using the Radiative Transfer Model (RTM), we evaluate the impact of various observation geometries and profile shapes on the air mass factor (AMF) and establish the look‐up table (LUT). USTC‐PRM overcomes the underestimation of high‐altitude aerosols by optimal estimation method (OEM) since it does not rely on prior profiles. The correlation between the retrieved AOD and AERONET AOD is 0.896, compared to 0.826 for the contrasted OEM. For trace gas retrieval, we propose a real‐time LUT establishment method based on retrieved aerosol profiles, significantly reducing memory requirements by over 90% (7.8 GB) and improving the correlation with in situ measurements from 0.867 to 0.911. Additionally, we introduce the concept of look‐up error table (LET) to quantify the AMF bias by retrieving it from LUT. We establish a quality evaluation system based on fitting results, LUT errors, and parameter statistics. Using synthetic data and long‐term MAX‐DOAS measurements, USTC‐PRM demonstrates high performance in retrieving profiles under various aerosol scenarios across high, medium, and low extinction levels, while also identifying abnormal situations, such as foggy and cloudy conditions. USTC‐PRM provides a robust, accurate and efficient approach for MAX‐DOAS profile retrieval, which can be utilized for studying regional transport and tracing atmospheric pollutants.

Journal of Geophysical Research AtmospheresVol. 130(18)
University of Science and Technology of China (CN), Anhui University (CN), Chinese Academy of Sciences (CN), Hefei Institutes of Physical Science (CN), Anhui Institute of Optics and Fine Mechanics (CN), National Science Centre (PL), Institute of Atmospheric Physics (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 76%
Atmospheric aerosols and clouds
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