Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter

Abstract

Background: More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5).Objective: In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments.Methods: We combined three satellite-derived PM2.5 sources to produce global PM2.5 estimates at about 10 km × 10 km from 1998 through 2012. For each source, we related total column retrievals of aerosol optical depth to near-ground PM2.5 using the GEOS–Chem chemical transport model to represent local aerosol optical properties and vertical profiles. We collected 210 global ground-based PM2.5 observations from the literature to evaluate our satellite-based estimates with values measured in areas other than North America and Europe.Results: We estimated that global population-weighted ambient PM2.5 concentrations increased 0.55 μg/m3/year (95% CI: 0.43, 0.67) (2.1%/year; 95% CI: 1.6, 2.6) from 1998 through 2012. Increasing PM2.5 in some developing regions drove this global change, despite decreasing PM2.5 in some developed regions. The estimated proportion of the population of East Asia living above the World Health Organization (WHO) Interim Target-1 of 35 μg/m3 increased from 51% in 1998–2000 to 70% in 2010–2012. In contrast, the North American proportion above the WHO Air Quality Guideline of 10 μg/m3 fell from 62% in 1998–2000 to 19% in 2010–2012. We found significant agreement between satellite-derived estimates and ground-based measurements outside North America and Europe (r = 0.81; n = 210; slope = 0.68). The low bias in satellite-derived estimates suggests that true global concentrations could be even greater.Conclusions: Satellite observations provide insight into global long-term changes in ambient PM2.5 concentrations. Satellite-derived estimates and ground-based PM2.5 observations from this study are available for public use.Citation: van Donkelaar A, Martin RV, Brauer M, Boys BL. 2015. Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ Health Perspect 123:135–143; http://dx.doi.org/10.1289/ehp.1408646

Disentangling the Complex Effects of Socioeconomic, Climatic, and Urban Form Factors on Air Pollution: A Case Study of China

“…High concentrations of PM 2.5 -much higher than the 10 µg/m 3 standard set by World Health Organization (WHO) air quality guidelines-occurred over a vast region of China since 1999, ranging from southern Inner Mongolia to Guangdong latitudinally, and from the east coast to central Sichuan longitudinally, plus the southern part of Xinjiang Province [9,11]. In this study, we selected 69 cities across this region based on data availability ( Figure 1).…”

“…High PM 2.5 concentrations have occurred over a vast region of China since the end of the 20th century [9][10][11]. Increased SO 2 emissions have mainly resulted from human activities, such as industrial emissions [12].…”

Source influence on emission pathways and ambient PM<sub>2.5</sub> pollution over India (2015–2050)

“…The GEOS-Chem model has been previously applied to study PM2.5 over India (e.g., Boys et al 2014;Kharol et al 2013;Philip et al 2014a;Li et al 2017) including relating satellite observations of aerosol optical depth to ground-level PM2.5 for the GBD assessment (Brauer et al 2012van Donkelaar et al 2010van Donkelaar et al , 2015van Donkelaar et al , 2016. The simulations undertaken in this work represent one of the finest resolution efforts to date to both represent India, and global scale processes.…”

Characterization of Subgrid-Scale Variability in Particulate Matter with Respect to Satellite Aerosol Observations

“…Particulate matter exposures used in health effects studies are typically estimated by applying spatio-temporal models to a variety of data including measurements from monitoring stations [7], outputs of numerical models [8,9], or satellite observations of aerosol optical depth (AOD) [10][11][12]. Exposure estimates based on these data are representations of ambient air exposures, but accuracy can be limited by the spatial and temporal detail provided in resolving the variability in PM concentrations [13,14].…”