Articles | Volume 14, issue 4
https://doi.org/10.5194/acp-14-2139-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-2139-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Feb 2014
Research article |
| 26 Feb 2014
Factors that influence surface PM2.5 values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ
S. Crumeyrolle
LOA, UMR8518, CNRS, Université Lille1, Villeneuve d'Ascq, France
NASA Langley Research Center, Hampton, VA 23681, USA
NASA Postdoctoral program, Oak Ridge Associated Universities, Oak Ridge, TN 37831, USA
G. Chen
NASA Langley Research Center, Hampton, VA 23681, USA
L. Ziemba
NASA Langley Research Center, Hampton, VA 23681, USA
A. Beyersdorf
NASA Langley Research Center, Hampton, VA 23681, USA
L. Thornhill
NASA Langley Research Center, Hampton, VA 23681, USA
Science Systems and Applications (SSAI), Hampton, VA 23666, USA
E. Winstead
NASA Langley Research Center, Hampton, VA 23681, USA
Science Systems and Applications (SSAI), Hampton, VA 23666, USA
R. H. Moore
NASA Langley Research Center, Hampton, VA 23681, USA
NASA Postdoctoral program, Oak Ridge Associated Universities, Oak Ridge, TN 37831, USA
M. A. Shook
NASA Langley Research Center, Hampton, VA 23681, USA
Science Systems and Applications (SSAI), Hampton, VA 23666, USA
C. Hudgins
NASA Langley Research Center, Hampton, VA 23681, USA
B. E. Anderson
NASA Langley Research Center, Hampton, VA 23681, USA
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Cited
37 citations as recorded by crossref.
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- A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data K. Miyazaki et al. https://doi.org/10.5194/acp-15-8315-2015
- Sources and composition of PM2.5 in the Colorado Front Range during the DISCOVER‐AQ study M. Valerino et al. https://doi.org/10.1002/2016JD025830
- Natural and anthropogenic contributions to long-term variations of SO2, NO2, CO, and AOD over East China H. Kang et al. https://doi.org/10.1016/j.atmosres.2018.09.012
- An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign W. Hou et al. https://doi.org/10.1016/j.jqsrt.2020.107161
- Spatiotemporal changes in aerosol properties by hygroscopic growth and impacts on radiative forcing and heating rates during DISCOVER-AQ 2011 D. Pérez-Ramírez et al. https://doi.org/10.5194/acp-21-12021-2021
- Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depth X. Jin et al. https://doi.org/10.5194/acp-19-295-2019
- Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al. https://doi.org/10.1029/2019JD031380
- Reconciling satellite aerosol optical thickness and surface fine particle mass through aerosol liquid water T. Nguyen et al. https://doi.org/10.1002/2016GL070994
- Spatial analysis of concentrations of multiple air pollutants using NASA DISCOVER-AQ aircraft measurements: Implications for exposure assessment H. Lee et al. https://doi.org/10.1016/j.envres.2017.10.017
- Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States V. Buchard et al. https://doi.org/10.1016/j.atmosenv.2015.11.004
- AEROCAN, the Canadian sub-network of AERONET: Aerosol monitoring and air quality applications C. Sioris et al. https://doi.org/10.1016/j.atmosenv.2017.08.044
- Satellite Monitoring for Air Quality and Health T. Holloway et al. https://doi.org/10.1146/annurev-biodatasci-110920-093120
- Drying-Induced Evaporation of Secondary Organic Aerosol during Summer M. El-Sayed et al. https://doi.org/10.1021/acs.est.5b06002
- 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
- Neighborhood-Scale O3, NO2, and PM2.5 in Washington, D.C. from a 1 × 1 km2 WRF–SMOKE–CMAQ Framework H. Hallaji et al. https://doi.org/10.1021/acsestair.6c00155
- Adaptive AOD Forecast Model Based on GNSS-Derived PWV and Meteorological Parameters Q. Zhao et al. https://doi.org/10.1109/TGRS.2021.3099155
- A Modified Look-Up Table Based Algorithm with a Self-Posed Scheme for Fine-Mode Aerosol Microphysical Properties Inversion by Multi-Wavelength Lidar Z. Zhou et al. https://doi.org/10.3390/rs16132265
- In situ vertical profiles of aerosol extinction, mass, and composition over the southeast United States during SENEX and SEAC4RS: observations of a modest aerosol enhancement aloft N. Wagner et al. https://doi.org/10.5194/acp-15-7085-2015
- Remote sensing of ground-level PM2.5 combining AOD and backscattering profile S. Li et al. https://doi.org/10.1016/j.rse.2016.05.025
- Assessment of high spectral resolution lidar-derived PM2.5 concentration from SEAC4RS, ACEPOL, and three DISCOVER-AQ campaigns B. Sutherland & N. Meskhidze https://doi.org/10.1039/D4EA00143E
- A methodological framework for estimating ambient PM2.5 particulate matter concentrations in the UK D. Galán-Madruga et al. https://doi.org/10.1016/j.jes.2023.11.019
- Hygrosopicity measurements of aerosol particles in the San Joaquin Valley, CA, Baltimore, MD, and Golden, CO D. Orozco et al. https://doi.org/10.1002/2015JD023971
- Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements E. Andrews et al. https://doi.org/10.5194/acp-17-6041-2017
- Improving satellite aerosol optical Depth-PM2.5 correlations using land use regression with microscale geographic predictors in a high-density urban context Y. Shi et al. https://doi.org/10.1016/j.atmosenv.2018.07.021
- Integration of Diverse Data Sources for Spatial PM2.5 Data Interpolation M. Tang et al. https://doi.org/10.1109/TMM.2016.2613639
- Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018 K. Miyazaki et al. https://doi.org/10.5194/essd-12-2223-2020
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- Observations of rapid aerosol optical depth enhancements in the vicinity of polluted cumulus clouds T. Eck et al. https://doi.org/10.5194/acp-14-11633-2014
- An Analysis of Factors Influencing the Relationship between Satellite-Derived AOD and Ground-Level PM10 R. Stirnberg et al. https://doi.org/10.3390/rs10091353
- Aerosol optical properties in the southeastern United States in summer – Part 2: Sensitivity of aerosol optical depth to relative humidity and aerosol parameters C. Brock et al. https://doi.org/10.5194/acp-16-5009-2016
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. https://doi.org/10.1080/10962247.2019.1668498
- HSRL-2 aerosol optical measurements and microphysical retrievals vs. airborne in situ measurements during DISCOVER-AQ 2013: an intercomparison study P. Sawamura et al. https://doi.org/10.5194/acp-17-7229-2017
- Temporal variations of major air pollutants: case study in India U. Bhimavarapu https://doi.org/10.1007/s13198-025-02973-4
- Significant Climate Impact of Highly Hygroscopic Atmospheric Aerosols in Delhi, India Y. Wang & Y. Chen https://doi.org/10.1029/2019GL082339
- How well do satellite AOD observations represent the spatial and temporal variability of PM 2.5 concentration for the United States? J. Li et al. https://doi.org/10.1016/j.atmosenv.2014.12.010
- Urbanization and regional air pollution across South Asian developing countries – A nationwide land use regression for ambient PM2.5 assessment in Pakistan Y. Shi et al. https://doi.org/10.1016/j.envpol.2020.115145
37 citations as recorded by crossref.
- Aerosol optical properties in the southeastern United States in summer – Part 1: Hygroscopic growth C. Brock et al. https://doi.org/10.5194/acp-16-4987-2016
- A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data K. Miyazaki et al. https://doi.org/10.5194/acp-15-8315-2015
- Sources and composition of PM2.5 in the Colorado Front Range during the DISCOVER‐AQ study M. Valerino et al. https://doi.org/10.1002/2016JD025830
- Natural and anthropogenic contributions to long-term variations of SO2, NO2, CO, and AOD over East China H. Kang et al. https://doi.org/10.1016/j.atmosres.2018.09.012
- An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign W. Hou et al. https://doi.org/10.1016/j.jqsrt.2020.107161
- Spatiotemporal changes in aerosol properties by hygroscopic growth and impacts on radiative forcing and heating rates during DISCOVER-AQ 2011 D. Pérez-Ramírez et al. https://doi.org/10.5194/acp-21-12021-2021
- Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depth X. Jin et al. https://doi.org/10.5194/acp-19-295-2019
- Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al. https://doi.org/10.1029/2019JD031380
- Reconciling satellite aerosol optical thickness and surface fine particle mass through aerosol liquid water T. Nguyen et al. https://doi.org/10.1002/2016GL070994
- Spatial analysis of concentrations of multiple air pollutants using NASA DISCOVER-AQ aircraft measurements: Implications for exposure assessment H. Lee et al. https://doi.org/10.1016/j.envres.2017.10.017
- Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States V. Buchard et al. https://doi.org/10.1016/j.atmosenv.2015.11.004
- AEROCAN, the Canadian sub-network of AERONET: Aerosol monitoring and air quality applications C. Sioris et al. https://doi.org/10.1016/j.atmosenv.2017.08.044
- Satellite Monitoring for Air Quality and Health T. Holloway et al. https://doi.org/10.1146/annurev-biodatasci-110920-093120
- Drying-Induced Evaporation of Secondary Organic Aerosol during Summer M. El-Sayed et al. https://doi.org/10.1021/acs.est.5b06002
- 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
- Neighborhood-Scale O3, NO2, and PM2.5 in Washington, D.C. from a 1 × 1 km2 WRF–SMOKE–CMAQ Framework H. Hallaji et al. https://doi.org/10.1021/acsestair.6c00155
- Adaptive AOD Forecast Model Based on GNSS-Derived PWV and Meteorological Parameters Q. Zhao et al. https://doi.org/10.1109/TGRS.2021.3099155
- A Modified Look-Up Table Based Algorithm with a Self-Posed Scheme for Fine-Mode Aerosol Microphysical Properties Inversion by Multi-Wavelength Lidar Z. Zhou et al. https://doi.org/10.3390/rs16132265
- In situ vertical profiles of aerosol extinction, mass, and composition over the southeast United States during SENEX and SEAC4RS: observations of a modest aerosol enhancement aloft N. Wagner et al. https://doi.org/10.5194/acp-15-7085-2015
- Remote sensing of ground-level PM2.5 combining AOD and backscattering profile S. Li et al. https://doi.org/10.1016/j.rse.2016.05.025
- Assessment of high spectral resolution lidar-derived PM2.5 concentration from SEAC4RS, ACEPOL, and three DISCOVER-AQ campaigns B. Sutherland & N. Meskhidze https://doi.org/10.1039/D4EA00143E
- A methodological framework for estimating ambient PM2.5 particulate matter concentrations in the UK D. Galán-Madruga et al. https://doi.org/10.1016/j.jes.2023.11.019
- Hygrosopicity measurements of aerosol particles in the San Joaquin Valley, CA, Baltimore, MD, and Golden, CO D. Orozco et al. https://doi.org/10.1002/2015JD023971
- Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements E. Andrews et al. https://doi.org/10.5194/acp-17-6041-2017
- Improving satellite aerosol optical Depth-PM2.5 correlations using land use regression with microscale geographic predictors in a high-density urban context Y. Shi et al. https://doi.org/10.1016/j.atmosenv.2018.07.021
- Integration of Diverse Data Sources for Spatial PM2.5 Data Interpolation M. Tang et al. https://doi.org/10.1109/TMM.2016.2613639
- Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018 K. Miyazaki et al. https://doi.org/10.5194/essd-12-2223-2020
- The impacts of aerosol loading, composition, and water uptake on aerosol extinction variability in the Baltimore–Washington, D.C. region A. Beyersdorf et al. https://doi.org/10.5194/acp-16-1003-2016
- Observations of rapid aerosol optical depth enhancements in the vicinity of polluted cumulus clouds T. Eck et al. https://doi.org/10.5194/acp-14-11633-2014
- An Analysis of Factors Influencing the Relationship between Satellite-Derived AOD and Ground-Level PM10 R. Stirnberg et al. https://doi.org/10.3390/rs10091353
- Aerosol optical properties in the southeastern United States in summer – Part 2: Sensitivity of aerosol optical depth to relative humidity and aerosol parameters C. Brock et al. https://doi.org/10.5194/acp-16-5009-2016
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. https://doi.org/10.1080/10962247.2019.1668498
- HSRL-2 aerosol optical measurements and microphysical retrievals vs. airborne in situ measurements during DISCOVER-AQ 2013: an intercomparison study P. Sawamura et al. https://doi.org/10.5194/acp-17-7229-2017
- Temporal variations of major air pollutants: case study in India U. Bhimavarapu https://doi.org/10.1007/s13198-025-02973-4
- Significant Climate Impact of Highly Hygroscopic Atmospheric Aerosols in Delhi, India Y. Wang & Y. Chen https://doi.org/10.1029/2019GL082339
- How well do satellite AOD observations represent the spatial and temporal variability of PM 2.5 concentration for the United States? J. Li et al. https://doi.org/10.1016/j.atmosenv.2014.12.010
- Urbanization and regional air pollution across South Asian developing countries – A nationwide land use regression for ambient PM2.5 assessment in Pakistan Y. Shi et al. https://doi.org/10.1016/j.envpol.2020.115145
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