Satellite-based PM concentrations and their application to COPD in Cleveland, OH

Abstract

A hybrid approach is proposed to estimate exposure to fine particulate matter (PM2.5) at a given location and time. This approach builds on satellite-based aerosol optical depth (AOD), air pollution data from sparsely distributed Environmental Protection Agency (EPA) sites and local time–space Kriging, an optimal interpolation technique. Given the daily global coverage of AOD data, we can develop daily estimate of air quality at any given location and time. This can assure unprecedented spatial coverage, needed for air quality surveillance and management and epidemiological studies. In this paper, we developed an empirical relationship between the 2 km AOD and PM2.5 data from EPA sites. Extrapolating this relationship to the study domain resulted in 2.3 million predictions of PM2.5 between 2000 and 2009 in Cleveland Metropolitan Statistical Area (MSA). We have developed local time–space Kriging to compute exposure at a given location and time using the predicted PM2.5. Daily estimates of PM2.5 were developed for Cleveland MSA between 2000 and 2009 at 2.5 km spatial resolution; 1.7 million (~79.8%) of 2.13 million predictions required for multiyear and geographic domain were robust. In the epidemiological application of the hybrid approach, admissions for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was examined with respect to time–space lagged PM2.5 exposure. Our analysis suggests that the risk of AECOPD increases 2.3% with a unit increase in PM2.5 exposure within 9 days and 0.05° (~5 km) distance lags. In the aggregated analysis, the exposed groups (who experienced exposure to PM2.5 >15.4 μg/m3) were 54% more likely to be admitted for AECOPD than the reference group. The hybrid approach offers greater spatiotemporal coverage and reliable characterization of ambient concentration than conventional in situ monitoring-based approaches. Thus, this approach can potentially reduce exposure misclassification errors in the conventional air pollution epidemiology studies.

A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth

“…(1) Model predictability: MLR was commonly used in early studies [17,20,21,[24][25][26][39][40][41]46,47,49,50,54,75], whereas MEM and CTM gradually became the dominant methods and replaced MLR after 2010. However, GWR has developed at a slower pace with a limited number of studies to data, and had moderate performance [32,74,125,126].…”

“…More recently, in order to improve model performance, some studies have explored covariate factors in the MLR model under different conditions [17,20,21,[24][25][26][39][40][41]46,47,49,50,54,75]. A few covariate factors, such as relative humidity and height of the boundary layer, were regarded as significant enough to affect and even invert the relationships between AOD and PM 2.5 .…”

Characteristics and applications of small, portable gaseous air pollution monitors

“…In order to advance environmental and human health studies, mobile air pollution monitors are increasingly used to obtain more accurate personal exposure estimates. Studies show that personal sampling of air pollution is preferable when attempting to accurately measure human exposure (Good et al, 2015;Steinle et al, 2013;Weichenthal et al, 2011;Zartarian et al, 2007), and that a high spatiotemporal resolution is required to correct for misinterpretation of actual exposure (Baxter et al, 2013;Kumar et al, 2013). Although there is a lack of concrete information on the effective use of such sensors by individuals and communities, specific vulnerable populations in urban areas could benefit from these sensor systems (e.g.…”

Characterization of Particulate Matter Profiling and Alveolar Deposition from Biomass Burning in Northern Thailand: The 7-SEAS Study

“…Surfaces of these carbonaceous particles provide a platform to intermix with various chemicals such as metals and organics, which can increase the toxicity of the particles. Epidemiological evidence shows that particulate matter (PM) at levels typically found in urban areas are considered to have adverse health effects, including exacerbation of pre-existing respiratory diseases (Kumar et al, 2013;Díaz-Robles et al, 2015). For example, Kumar et al (2013) observed that the 2.3% risk of an acute exacerbation of chronic obstructive pulmonary disease (COPD) could be increased by a unit increase in exposure to PM of less than 2.5 µm in aerodynamic diameter (PM 2.5 ).…”

“…Epidemiological evidence shows that particulate matter (PM) at levels typically found in urban areas are considered to have adverse health effects, including exacerbation of pre-existing respiratory diseases (Kumar et al, 2013;Díaz-Robles et al, 2015). For example, Kumar et al (2013) observed that the 2.3% risk of an acute exacerbation of chronic obstructive pulmonary disease (COPD) could be increased by a unit increase in exposure to PM of less than 2.5 µm in aerodynamic diameter (PM 2.5 ). Notably, the prevalence rate of COPD in South Asia was 4.2%-9.4% as reported by Lim et al (2015) in 2015, suggesting that characterization of PM emitted by biomass burning is urgent for public health.…”