Low-Concentration PM _2.5 and Mortality: Estimating Acute and Chronic Effects in a Population-Based Study

Abstract

BackgroundBoth short- and long-term exposures to fine particulate matter (≤ 2.5 μm; PM2.5) are associated with mortality. However, whether the associations exist at levels below the new U.S. Environmental Protection Agency (EPA) standards (12 μg/m3 of annual average PM2.5, 35 μg/m3 daily) is unclear. In addition, it is not clear whether results from previous time series studies (fit in larger cities) and cohort studies (fit in convenience samples) are generalizable.ObjectivesWe estimated the effects of low-concentration PM2.5 on mortality.MethodsHigh resolution (1 km × 1 km) daily PM2.5 predictions, derived from satellite aerosol optical depth retrievals, were used. Poisson regressions were applied to a Medicare population (≥ 65 years of age) in New England to simultaneously estimate the acute and chronic effects of exposure to PM2.5, with mutual adjustment for short- and long-term exposure, as well as for area-based confounders. Models were also restricted to annual concentrations < 10 μg/m3 or daily concentrations < 30 μg/m3.ResultsPM2.5 was associated with increased mortality. In the study cohort, 2.14% (95% CI: 1.38, 2.89%) and 7.52% (95% CI: 1.95, 13.40%) increases were estimated for each 10-μg/m3 increase in short- (2 day) and long-term (1 year) exposure, respectively. The associations held for analyses restricted to low-concentration PM2.5 exposure, and the corresponding estimates were 2.14% (95% CI: 1.34, 2.95%) and 9.28% (95% CI: 0.76, 18.52%). Penalized spline models of long-term exposure indicated a larger effect for mortality in association with exposures ≥ 6 μg/m3 versus those < 6 μg/m3. In contrast, the association between short-term exposure and mortality appeared to be linear across the entire exposure distribution.ConclusionsUsing a mutually adjusted model, we estimated significant acute and chronic effects of PM2.5 exposure below the current U.S. EPA standards. These findings suggest that improving air quality with even lower PM2.5 than currently allowed by U.S. EPA standards may benefit public health.CitationShi L, Zanobetti A, Kloog I, Coull BA, Koutrakis P, Melly SJ, Schwartz JD. 2016. Low-concentration PM2.5 and mortality: estimating acute and chronic effects in a population-based study. Environ Health Perspect 124:46–52; http://dx.doi.org/10.1289/ehp.1409111

Air Pollution and Human Development in Europe: A New Index Using Principal Component Analysis

“…The authors show that there is no threshold for ambient PM2.5 concentration below which it does not affect mortality. This finding is similar to other studies [4,5]. Using a household air pollution exposure index [6], it was found that exposure to Suspended Particulate Matter (atmospheric particulate matter with no limit size) is negatively correlated both with level of income and with level of education.…”

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

“…Included studies showed that R 2 value of MEM was higher than those of the other three models in the same area [17,87,104,136]. Moreover, MAIAC algorithms, which led to a highly accurate of AOD, were mostly used in MEM, significantly improving the R 2 value of the model [7,35,83,120,135]. On the global scale, CTM has been proven to be efficient for the mechanism of completing the prediction from using partial AOD data by AOD component analysis [57]; (2) Adjusting factors: The number of these factors has increased due to the development of prediction models.…”

“…In New England, Alexeeff et al [135] further employed the MEM model with [34,131] Kriging and land use regression to describe an epidemiological relationship between AOD and predicted PM 2.5 in 2003. The following year, Shi et al [120] used MEM to predict PM 2.5 using MODIS AOD data collected between 2003 and 2008, and they obtained consistent results (R 2 value = 0.890) for days with available AOD data and without available AOD data. This method was also successfully applied in studies on the relationship between low PM 2.5 exposure and mortality.…”

Evaluating the Sensitivity of the Mass-Based Particle Removal Calculations for HVAC Filters in ISO 16890 to Assumptions for Aerosol Distributions

“…Removal efficiencies in the three size bins are then used to assign HVAC filters a single efficiency metric, which is the minimum efficiency reporting value (MERV), and is based on the minimum removal efficiency in each of the three bins. Although the vast majority of the epidemiological evidence of adverse health outcomes that are associated with airborne particulate matter to date has been linked to mass-based concentrations of PM 1 , PM 2.5 , and PM 10 [10][11][12][13][14][15][16][17][18][19][20], the ASHRAE Standard 52.2 test method does not explicitly evaluate particle removal efficiency for any of these mass-based measures.…”