Health assessment of future PM2.5 exposures from indoor, outdoor, and secondhand tobacco smoke concentrations under alternative policy pathways in Ulaanbaatar, Mongolia

Abstract

IntroductionWinter air pollution in Ulaanbaatar, Mongolia is among the worst in the world. The health impacts of policy decisions affecting air pollution exposures in Ulaanbaatar were modeled and evaluated under business as usual and two more-strict alternative emissions pathways through 2024. Previous studies have relied on either outdoor or indoor concentrations to assesses the health risks of air pollution, but the burden is really a function of total exposure. This study combined projections of indoor and outdoor concentrations of PM2.5 with population time-activity estimates to develop trajectories of total age-specific PM2.5 exposure for the Ulaanbaatar population. Indoor PM2.5 contributions from secondhand tobacco smoke (SHS) were estimated in order to fill out total exposures, and changes in population and background disease were modeled. The health impacts were derived using integrated exposure-response curves from the Global Burden of Disease Study.ResultsAnnual average population-weighted PM2.5 exposures at baseline (2014) were estimated at 59 μg/m3. These were dominated by exposures occurring indoors, influenced considerably by infiltrated outdoor pollution. Under current control policies, exposures increased slightly to 60 μg/m3 by 2024; under moderate emissions reductions and under a switch to clean technologies, exposures were reduced from baseline levels by 45% and 80%, respectively. The moderate improvement pathway decreased per capita annual disability-adjusted life year (DALY) and death burdens by approximately 40%. A switch to clean fuels decreased per capita annual DALY and death burdens by about 85% by 2024 with the relative SHS contribution increasing substantially.ConclusionThis study demonstrates a way to combine estimated changes in total exposure, background disease and population levels, and exposure-response functions to project the health impacts of alternative policy pathways. The resulting burden analysis highlights the need for aggressive action, including the elimination of residential coal burning and the reduction of current smoking rates.

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities

“…; to study the trend and characteristics of PM 2.5 ( Chen et al, 2020 ; Fontes et al, 2017 ; Sreekanth et al, 2018 ; Liang et al, 2016 ; Batterman et al, 2016 ; San Martini et al, 2015 ), to compare with other data and model evaluation ( Jiang et al, 2015 ; Li, 2020 ; Matthias et al, 2017 ; Mukherjee and Toohey, 2016 ; Shimadera et al, 2016 ; Uno et al, 2014 ; Wang et al, 2018 ), and to estimate the health impacts ( Han et al, 2020 ; Lowsen and Conway, 2016 ; Luong et al, 2020 ; Nhung et al, 2020 ; Tian et al, 2020 ; Wang et al, 2020 ; You et al, 2016 ; Zhang et al, 2020 ). While most of the studies are carried out in China, few studies have been carried out for other countries including Vietnam ( Hien et al, 2019 ; Luong et al, 2020 ), Japan ( Shimadera et al, 2016 ) Indonesia ( Kusuma et al, 2019 ), Mongolia ( Hill et al, 2017 ), Bangladesh ( Auvee and Bashar, 2019 ), and Singapore ( Liu and Salvo, 2018 ).…”

Systematic Literature Review of Health Impact Assessments in Low and Middle-Income Countries

“…Others performed HIA without claiming or defining it as such [56,102], and the term HIA was not always used in the same sense across studies. The lack of definition and transparency in HIA processes that came from studies in China, Turkey, and Mongolia [70,87,100] were harder to identify and include; they could have been discarded due to close similarities with health risk assessments (HRAs). HRAs are an integral part of HIAs (often conducted in the appraisal stage) but are not HIAs.…”

Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks

“…In order to obtain a more specific estimate for the impact of a behavior change scenario, some studies estimate the local risk exposure with local representative data (including national health surveys and observational studies), while using relative risk estimates from the literature, e.g. [14][15][16], for behavioral risks such as second hand smoke or diet. Others point out that most studies in the literature estimate RR with one single risk factor in isolation and advocate estimating the impact of risk factors jointly on local individual level data [e.g., 17].…”