Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land?

Hidy, George M.; Brook, Jeffrey R.; Chow, Judith C.; Green, Mark; Husar, R.B.; Colin, Lee; Scheffe, Richard D.; Swanson, Aaron L.; Watson, John G.

doi:10.3155/1047-3289.59.10.1130

Cited by 49 publications

(28 citation statements)

References 27 publications

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“…Newer generation satellite instruments measure AOD with increased temporal accuracy and finer spatial resolution [27,[32][33][34][35][36][37]. AOD is a unitless measure of the scattering and absorption of visible light by aerosols (particles) in the atmosphere [38][39][40]. AOD data are, by definition, actual physical measurements, an improvement over CMAQ PM 2.5 model predictions.…”

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confidence: 99%

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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The fine particulate matter baseline (PMB), which includes PM 2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM 2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM 2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km 2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM 2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM 2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.In urban areas, PMB gives more "weight" to PM 2.5 monitor readings than CMAQ PM 2.5 model predictions. In rural areas, CMAQ PM 2.5 model predictions exert more influence than PM 2.5 monitor readings on PMB, since there are fewer monitors or no monitors. Ambient air monitors are usually found in urban areas. In the last 15 years, PMB has turned out to be a more representative PM 2.5 concentration surface, compared to the interpolation of PM 2.5 monitor data, as a method to resolve spatial gaps between ambient air monitors [16,18,22]. CDC subsequently incorporated PMB into its Environmental Public Health Tracking (EPHT) network of state and New York City partners [16,18,22,26]. To date, PMB has been used by federal and state epidemiologists completing EPHT projects in different parts of the US [16,18,22,26].Within this decade, the availability and use of satellite AOD data have become more routine [6,16,[27][28][29][30][31]. Newer generation satellite instruments measure AOD with increased temporal accuracy and finer spatial resolution [27,[32][33][34][35][36][37]. AOD is a unitless measure of the scattering and absorption of visible light by aerosols (particles) in the atmosphere [38][39][40]. AOD data are, by definition, actual physical measurements, an improvement over CMAQ PM 2.5 model predictions. Once AOD unitless measurements have been calibrated with actual PM 2.5 readings from on-the-ground ambient air monitors, it is then possible to utilize the derived AOD-PM 2.5 concentration readings to estimate actual ambient PM 2.5 concentration in areas where there are no on-the-ground air monitors. The relationship between AOD measurements and on-the-ground measurements of PM 2.5 concentration readings has b...

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confidence: 99%

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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“…The number of sample points decreases dramatically when satellite data are included. Hidy et al (2009) note that for MODIS data in Fresno from 2002 to 2008, cloud-free days were available 43%, 61%, 94%, and 81% of the time in winter, spring, summer, and fall, respectively. Table 5 shows how the number of sample points decreases as more parameters are added.…”

Section: Effect Of Parameters Selection On Sample Sizementioning

confidence: 99%

Improving retrievals of regional fine particulate matter concentrations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) multisatellite observations

Strawa

Chatfield

Legg

et al. 2013

Journal of the Air & Waste Management Association

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A combination of multiplatform satellite observations and statistical data analysis are used to improve the correlation between estimates of PM 2.5 (particulate mass with aerodynamic diameter less that 2.5 µm) retrieved from satellite observations and groundlevel measured PM 2.5 . Accurate measurements of PM 2.5 can be used to assess the impact of air pollution levels on human health and the environment and to validate air pollution models. The area under study is California's San Joaquin Valley (SJV) that has a history of poor particulate air quality. Attempts to use simple linear regressions to estimate PM 2.5 from satellite-derived aerosol optical depth ( Particularly noteworthy is the fact that the PM 2.5 retrieved using the GAM captures many of the PM 2.5 exceedances that were not seen in the simple linear regression model. Implications: Particulate Mass (PM) in the air is a concern because of its effect on climate and human health. PM concentrations retrieved from satellite observations of aerosol optical depth can provide broad regional coverage that is not attained by surface sites. The techniques developed in this paper have resulted in greatly improved correlations between PM retrieved from satellite observations and PM from surface measurements in areas where the correlation is typically low. These improved retrievals can be used to fill in the gaps between surface sites and validate air quality models that are used for air quality forecasts and epidemiological studies.

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“…Since the low earth orbit Television Infrared Observation Satellite (TIROS-1) was launched on April 1, 1960, many satellites have been operated to provide earth observing information, which includes the measurement of land, ocean, clouds, radiation, and trace gases (e.g., SO 2 , NO 2 , CO, O 3 and Aerosol optical depth (AOD) derived PM2.5/PM10) [90]. Besides, the natural hazards such as volcanoes can also be observed and monitored through RS images.…”

Section: Reviewmentioning

confidence: 99%

Remote sensing and disease control in China: past, present and future

et al. 2013

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Satellite measurements have distinct advantages over conventional ground measurements because they can collect the information repeatedly and automatically. Since 1970 globally and 1985 in China, the availability of remote sensing (RS) techniques has steadily grown and they are becoming increasingly important to improve our understanding of human health. This paper gives the first detailed overview on the developments of RS applications for disease control in China. The problems, challenges and future directions are also discussed with an aim of guiding prospective studies.

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Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land?

Cited by 49 publications

References 27 publications

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Improving retrievals of regional fine particulate matter concentrations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) multisatellite observations

Remote sensing and disease control in China: past, present and future

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