Global estimation of exposure to fine particulate matter (PM2.5) from household air pollution. (November 2018)

• Record Type: Journal Article
• Authors: Shupler, Matthew; Godwin, William; Frostad, Joseph; Gustafson, Paul; Arku, Raphael E.; Brauer, Michael
• Is Part Of: Environment international. Volume 120(2018)
• Page Start: 354
• Page End: 363
• Publication Date: 2018-11
• Subjects: Bayesian hierarchical modeling -- Exposure assessment -- Household air pollution -- PM2.5 -- Global Burden of Disease -- WHO Global HAP database; Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2018.08.026
• Languages: English
• ISSNs: 0160-4120

Abstract

Abstract: Background: Exposure to household air pollution (HAP) from cooking with dirty fuels is a leading health risk factor within Asia, Africa and Central/South America. The concentration of particulate matter of diameter ≤ 2.5 μm (PM2.5 ) is an important metric to evaluate HAP risk, however epidemiological studies have demonstrated significant variation in HAP-PM2.5 concentrations at household, community and country levels. To quantify the global risk due to HAP exposure, novel estimation methods are needed, as financial and resource constraints render it difficult to monitor exposures in all relevant areas. Methods: A Bayesian, hierarchical HAP-PM2.5 global exposure model was developed using kitchen and female HAP-PM2.5 exposure data available in peer-reviewed studies from an updated World Health Organization Global HAP database. Cooking environment characteristics were selected using leave-one-out cross validation to predict quantitative HAP-PM2.5 measurements from 44 studies. Twenty-four hour HAP-PM2.5 kitchen concentrations and male, female and child exposures were estimated for 106 countries in Asia, Africa and Latin America. Results: A model incorporating fuel/stove type (traditional wood, improved biomass, coal, dung and gas/electric), urban/rural location, wet/dry season and socio-demographic index resulted in a Bayesian R 2 of 0.57. Relative to rural kitchens using gas or electricity, the mean global 24-hour HAP-PM2.5 concentrations were 290 μg/m 3 higher (range of regional averages: 110, 880) for traditional stoves, 150 μg/m 3 higher (range of regional averages: 50, 290) for improved biomass stoves, 850 μg/m 3 higher (range of regional averages: 310, 2600) for animal dung stoves, and 220 μg/m 3 higher (range of regional averages: 80, 650) for coal stoves. The modeled global average female/kitchen exposure ratio was 0.40. Average modeled female exposures from cooking with traditional wood stoves were 160 μg/m 3 in rural households and 170 μg/m 3 in urban households. Average male and child rural area exposures from traditional wood stoves were 120 μg/m 3 and 140 μg/m 3, respectively; average urban area exposures were identical to average rural exposures among both sub-groups. Conclusions: A Bayesian modeling approach was used to generate unique HAP-PM2.5 kitchen concentrations and personal exposure estimates for all countries, including those with little to no available quantitative HAP-PM2.5 exposure data. The global exposure model incorporating type of fuel-stove combinations can add specificity and reduce exposure misclassification to enable an improved global HAP risk assessment. Highlights: Average 24-hr HAP-PM2.5 male/female/child exposures available for 106 countries Cooking fuel/stove type is an important determinant of HAP-PM2.5 exposure. Large regional variation in exposures among households using same cooking fuel type Bayesian techniques allow for more accurate characterization of exposure uncertainty. Exposure measurements available in World Health Organization Global HAP database