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BASIC: A Boosted Aerosol-Size-Integrated XCO2 Retrieval Algorithm

delete2026-07-04
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PRE
AI
Z
Zhujun Li
S
Siwei Li *
J
Jie Yang
J
Jia Xing
M
Maolin Zhang
J
Jiarui Chen
J
Jiaxin Dong
C
Chunying Fan
S
Shuangliang Li
DOI:10.1029/2025JD045295delete
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Abstract

Abstract

En 中文
Accurate retrieval of dry air mole fraction of CO2 (XCO2) is essential for tracking emissions and supporting mitigation. However, aerosols, especially their particle size distribution (PSD), introduce significant uncertainties via scattering and absorption, yet are often overlooked in current methods. Here we present a boosted aerosol-size-Integrated XCO2 (BASIC) retrieval algorithm that flexibly accounts for aerosol-induced lightpath modifications. Validation at five TCCON sites in East Asia shows that BASIC reduces RMSE by 30% and 13% compared to standard and bias-corrected OCO-2 products, respectively. Moreover, BASIC more accurately reproduces the observed spectra, particularly in the aerosol-sensitive O2 A band, outperforming the ACOS algorithm. These improvements highlight the importance of incorporating variable aerosol PSD in retrievals and demonstrate that BASIC enables a more accurate representation of aerosol effects on radiative transfer. Our results suggest that PSD-aware retrievals can significantly improve the accuracy of satellite-derived XCO2 estimates under heavy aerosol loading conditions.
Keywords:
XCO2
aerosol
PSD

Journal

J
journal of geophysical research: atmospheres
IF:
0
Papers:
437
Citations:
0

Organization

T
The University of Tennessee
Scholars:
69
Papers: 36
Citations: 0
W
wuhan university
Scholars:
7.8W
Papers: 5.7W
Citations: 70
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