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.
Research article
| 
16 Oct 2024
Research article |
| 16 Oct 2024
| 16 Oct 2024
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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Total article views: 2,666 (including HTML, PDF, and XML)
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Total article views: 2,202 (including HTML, PDF, and XML)
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Cited
10 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al.
- 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.
- From column to surface: connecting the performance in simulating aerosol optical properties and PM2.5 concentrations in the NASA GEOSCCM C. Mogno et al.
- 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.
- 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.
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al.
- 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.
- Impact of Chemical Composition on Aerosol Scattering: Insights from the Surface Particulate Matter Network and Aerosol Robotic Network S. Eom et al.
- 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.
- Suitability Assessment of Remotely Sensed Urban Air Quality Data Z. Zhang et al.
10 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al.
- 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.
- From column to surface: connecting the performance in simulating aerosol optical properties and PM2.5 concentrations in the NASA GEOSCCM C. Mogno et al.
- 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.
- 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.
- Atmospheric aerosol spatial variability: Impacts on air quality and climate change S. Manavi et al.
- 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.
- Impact of Chemical Composition on Aerosol Scattering: Insights from the Surface Particulate Matter Network and Aerosol Robotic Network S. Eom et al.
- 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.
- Suitability Assessment of Remotely Sensed Urban Air Quality Data Z. Zhang et al.
Saved (final revised paper)
Latest update: 02 May 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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