Articles | Volume 16, issue 5
https://doi.org/10.5194/acp-16-3499-2016
© Author(s) 2016. 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-16-3499-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter
Department of Atmospheric Science, Colorado State
University, Fort Collins, CO, USA
Colette L. Heald
Department of Civil and Environmental Engineering and
Department of Earth, Atmospheric and Planetary Sciences, MIT, Cambridge, MA,
USA
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Cited
34 citations as recorded by crossref.
- Field testing a low-cost passive aerosol sampler for long-term measurement of ambient PM2.5 concentrations and particle composition M. Castillo et al. 10.1016/j.atmosenv.2019.116905
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- Assessing the health estimation capacity of air pollution exposure prediction models J. Krall et al. 10.1186/s12940-022-00844-0
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. 10.1080/10962247.2019.1668498
- Air pollution intervention and life-saving effect in China B. Zou et al. 10.1016/j.envint.2018.10.045
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- Impact of diurnal variability and meteorological factors on the PM2.5 - AOD relationship: Implications for PM2.5 remote sensing J. Guo et al. 10.1016/j.envpol.2016.11.043
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- Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia P. Crippa et al. 10.1038/srep37074
- Analysis of spatial factors, time-activity and infiltration on outdoor generated PM2.5 exposures of school children in five European cities A. Korhonen et al. 10.1016/j.scitotenv.2021.147111
- Review: Strategies for using satellite-based products in modeling PM2.5 and short-term pollution episodes M. Sorek-Hamer et al. 10.1016/j.envint.2020.106057
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- Examining PM2.5 concentrations and exposure using multiple models J. Kelly et al. 10.1016/j.envres.2020.110432
- Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models S. Philip et al. 10.1088/1748-9326/aa65a4
- Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification Q. Pu & E. Yoo 10.1016/j.envpol.2021.116574
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- Extreme Air Pollution in Global Megacities M. Marlier et al. 10.1007/s40641-016-0032-z
30 citations as recorded by crossref.
- Field testing a low-cost passive aerosol sampler for long-term measurement of ambient PM2.5 concentrations and particle composition M. Castillo et al. 10.1016/j.atmosenv.2019.116905
- Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response P. Tarín-Carrasco et al. 10.1016/j.envint.2021.106517
- Assessing the health estimation capacity of air pollution exposure prediction models J. Krall et al. 10.1186/s12940-022-00844-0
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. 10.1080/10962247.2019.1668498
- Air pollution intervention and life-saving effect in China B. Zou et al. 10.1016/j.envint.2018.10.045
- Global burden of mortalities due to chronic exposure to ambient PM 2.5 from open combustion of domestic waste J. Kodros et al. 10.1088/1748-9326/11/12/124022
- Impact of diurnal variability and meteorological factors on the PM2.5 - AOD relationship: Implications for PM2.5 remote sensing J. Guo et al. 10.1016/j.envpol.2016.11.043
- Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depth X. Jin et al. 10.5194/acp-19-295-2019
- Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China P. Giani et al. 10.1088/1748-9326/ab7f0f
- Satellite mapping of PM<sub>2.5</sub> episodes in the wintertime San Joaquin Valley: a “static” model using column water vapor R. Chatfield et al. 10.5194/acp-20-4379-2020
- Using Low-Cost Measurement Systems to Investigate Air Quality: A Case Study in Palapye, Botswana W. Lassman et al. 10.3390/atmos11060583
- Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia P. Crippa et al. 10.1038/srep37074
- Analysis of spatial factors, time-activity and infiltration on outdoor generated PM2.5 exposures of school children in five European cities A. Korhonen et al. 10.1016/j.scitotenv.2021.147111
- Review: Strategies for using satellite-based products in modeling PM2.5 and short-term pollution episodes M. Sorek-Hamer et al. 10.1016/j.envint.2020.106057
- Beyond SOx reductions from shipping: assessing the impact of NOx and carbonaceous-particle controls on human health and climate K. Bilsback et al. 10.1088/1748-9326/abc718
- Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty A. van Donkelaar et al. 10.1021/acs.est.1c05309
- A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado B. Ford et al. 10.5194/amt-12-6385-2019
- Comparing Ground Operation-Measured and Remotely Sensed Fine-Particulate Matter Data: A case to validate the Dalhousie product in China L. Han et al. 10.1109/MGRS.2019.2906237
- Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis N. Waidyatillake et al. 10.3390/ijerph18147655
- An observationally constrained estimate of global dust aerosol optical depth D. Ridley et al. 10.5194/acp-16-15097-2016
- Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USA X. Jin et al. 10.1088/1748-9326/ab2dcb
- Estimating premature mortality attributable to PM2.5 exposure and benefit of air pollution control policies in China for 2020 K. Maji et al. 10.1016/j.scitotenv.2017.08.254
- Spatial and temporal estimates of population exposure to wildfire smoke during the Washington state 2012 wildfire season using blended model, satellite, and in situ data W. Lassman et al. 10.1002/2017GH000049
- Fine Particle Emissions From Tropical Peat Fires Decrease Rapidly With Time Since Ignition C. Roulston et al. 10.1029/2017JD027827
- Transboundary atmospheric pollution in Southeast Asia: current methods, limitations and future developments Q. Chen & D. Taylor 10.1080/10643389.2018.1493337
- Examining PM2.5 concentrations and exposure using multiple models J. Kelly et al. 10.1016/j.envres.2020.110432
- Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models S. Philip et al. 10.1088/1748-9326/aa65a4
- Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification Q. Pu & E. Yoo 10.1016/j.envpol.2021.116574
- Future Fire Impacts on Smoke Concentrations, Visibility, and Health in the Contiguous United States B. Ford et al. 10.1029/2018GH000144
- A low-cost monitor for simultaneous measurement of fine particulate matter and aerosol optical depth – Part 3: Automation and design improvements E. Wendt et al. 10.5194/amt-14-6023-2021
4 citations as recorded by crossref.
- The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition J. Belle et al. 10.3390/ijerph14101244
- Public health issues from crude-oil production in the Ecuadorian Amazon territories G. Coronel Vargas et al. 10.1016/j.scitotenv.2019.134647
- Global and regional trends in particulate air pollution and attributable health burden over the past 50 years E. Butt et al. 10.1088/1748-9326/aa87be
- Extreme Air Pollution in Global Megacities M. Marlier et al. 10.1007/s40641-016-0032-z
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Latest update: 31 May 2023
Short summary
As motivation for air quality research, many studies cite the fact that exposure to particulate matter is associated with premature mortality. Recently, more studies have also tried to quantify this burden; however, there are many data sets that can be used and many different methodological choices to be made. In this paper, we seek to explain the different sources of uncertainty in health impact assessments through the example of using model and satellite-based PM2.5 concentrations.
As motivation for air quality research, many studies cite the fact that exposure to particulate...
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