Articles | Volume 24, issue 20
https://doi.org/10.5194/acp-24-11565-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-11565-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Randall V. Martin
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Aaron van Donkelaar
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Melanie S. Hammer
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Department of Civil and Environmental Engineering, Washington State University, Pullman, Washington, USA
Christopher R. Oxford
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Yanshun Li
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Dandan Zhang
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Inderjeet Singh
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
Alexei Lyapustin
Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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Cited
16 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al. https://doi.org/10.1021/acs.est.4c14483
- Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine Learning D. Westervelt et al. https://doi.org/10.1021/acsestair.4c00366
- Correcting aerosol extinction coefficient vertical structure biases in GEOS-chem via a physics-informed transformer with physical mechanism diagnosis J. Xiong et al. https://doi.org/10.5194/acp-26-8225-2026
- Analysis of the horizontal and vertical distribution of a dust weather event in the Tarim Basin based on multi-source observational datasets H. Jiang et al. https://doi.org/10.1016/j.apr.2025.102455
- Comprehensive Validation of MODIS-MAIAC Aerosol Products and Long-Term Aerosol Detection over an Urban–Rural Area Around Rome in Central Italy V. Terenzi et al. https://doi.org/10.3390/rs17122051
- Impact of Chemical Composition on Aerosol Scattering: Insights from the Surface Particulate Matter Network and Aerosol Robotic Network S. Eom et al. https://doi.org/10.1021/acs.est.5c09325
- Effects of Fire Plume Height on the Geophysical Estimation of Surface Fine Particulate Matter from Satellite Aerosol Optical Depth during North American Wildfires I. Singh et al. https://doi.org/10.1021/acsestair.5c00035
- Vertical Aerosol Structure Matters: Improving the AOD–PM2.5 Link for Air Quality and Exposure I. Rogozovsky et al. https://doi.org/10.1021/acs.est.6c00095
- Long-term CALIOP observations of vertical aerosol stratification over Shanghai: Meteorological modulation and height-resolved transport F. Wei et al. https://doi.org/10.1016/j.atmosres.2026.109329
- From column to surface: connecting the performance in simulating aerosol optical properties and PM2.5 concentrations in the NASA GEOSCCM C. Mogno et al. https://doi.org/10.5194/acp-26-3025-2026
- Unveiling Atmospheric Layers: Vertical Pollution Patterns and Prospects for High-Resolution Aerosol Retrievals Using the Eastern Mediterranean as a Case Study I. Rogozovsky et al. https://doi.org/10.1021/acs.est.4c14556
- Air Pollution Assessment by Aerosol Optical Depth Mapping (AOD) in the Macro-Metropolitan Region of São Paulo, Brazil V. Vasconcelos https://doi.org/10.26848/rbgf.v19.02.p814-830
- Aerosol vertical distributions determine the seasonal relationships between column AOD and surface PM2.5 over Europe S. Zeng et al. https://doi.org/10.1016/j.atmosenv.2026.122305
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al. https://doi.org/10.1016/j.oneear.2025.101237
- Surface PM2.5 air pollution in 2022 India: emission updates, WRF-Chem model evaluation, and source attribution M. Zhou et al. https://doi.org/10.5194/acp-26-10533-2026
- Suitability Assessment of Remotely Sensed Urban Air Quality Data Z. Zhang et al. https://doi.org/10.3390/rs17111848
16 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al. https://doi.org/10.1021/acs.est.4c14483
- Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine Learning D. Westervelt et al. https://doi.org/10.1021/acsestair.4c00366
- Correcting aerosol extinction coefficient vertical structure biases in GEOS-chem via a physics-informed transformer with physical mechanism diagnosis J. Xiong et al. https://doi.org/10.5194/acp-26-8225-2026
- Analysis of the horizontal and vertical distribution of a dust weather event in the Tarim Basin based on multi-source observational datasets H. Jiang et al. https://doi.org/10.1016/j.apr.2025.102455
- Comprehensive Validation of MODIS-MAIAC Aerosol Products and Long-Term Aerosol Detection over an Urban–Rural Area Around Rome in Central Italy V. Terenzi et al. https://doi.org/10.3390/rs17122051
- Impact of Chemical Composition on Aerosol Scattering: Insights from the Surface Particulate Matter Network and Aerosol Robotic Network S. Eom et al. https://doi.org/10.1021/acs.est.5c09325
- Effects of Fire Plume Height on the Geophysical Estimation of Surface Fine Particulate Matter from Satellite Aerosol Optical Depth during North American Wildfires I. Singh et al. https://doi.org/10.1021/acsestair.5c00035
- Vertical Aerosol Structure Matters: Improving the AOD–PM2.5 Link for Air Quality and Exposure I. Rogozovsky et al. https://doi.org/10.1021/acs.est.6c00095
- Long-term CALIOP observations of vertical aerosol stratification over Shanghai: Meteorological modulation and height-resolved transport F. Wei et al. https://doi.org/10.1016/j.atmosres.2026.109329
- From column to surface: connecting the performance in simulating aerosol optical properties and PM2.5 concentrations in the NASA GEOSCCM C. Mogno et al. https://doi.org/10.5194/acp-26-3025-2026
- Unveiling Atmospheric Layers: Vertical Pollution Patterns and Prospects for High-Resolution Aerosol Retrievals Using the Eastern Mediterranean as a Case Study I. Rogozovsky et al. https://doi.org/10.1021/acs.est.4c14556
- Air Pollution Assessment by Aerosol Optical Depth Mapping (AOD) in the Macro-Metropolitan Region of São Paulo, Brazil V. Vasconcelos https://doi.org/10.26848/rbgf.v19.02.p814-830
- Aerosol vertical distributions determine the seasonal relationships between column AOD and surface PM2.5 over Europe S. Zeng et al. https://doi.org/10.1016/j.atmosenv.2026.122305
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al. https://doi.org/10.1016/j.oneear.2025.101237
- Surface PM2.5 air pollution in 2022 India: emission updates, WRF-Chem model evaluation, and source attribution M. Zhou et al. https://doi.org/10.5194/acp-26-10533-2026
- Suitability Assessment of Remotely Sensed Urban Air Quality Data Z. Zhang et al. https://doi.org/10.3390/rs17111848
Saved (final revised paper)
Latest update: 21 Sep 2026
Short summary
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM2.5–AOD relationship (η), can provide global PM2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year....
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