scholarly journals Deaths Attributable to Air Pollution in Nordic Countries: Disparities in the Estimates

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 467 ◽  
Author(s):  
Heli Lehtomäki ◽  
Camilla Geels ◽  
Jørgen Brandt ◽  
Shilpa Rao ◽  
Katarina Yaramenka ◽  
...  

Particulate matter air pollution is widely considered as the leading environmental cause of premature mortality. However, there are substantial differences in the estimated health burden between the assessments. The aim of this work is to quantify the deaths attributable to ambient air pollution in Nordic countries applying selected assessment tools and approaches, and to identify the main disparities. We quantified and compared the estimated deaths from three health risk assessment tools and from a set of different concentration-response functions. A separate analysis was conducted for the impacts of spatial resolution of the exposure model on the estimated deaths. We found that the death rate (deaths per million) attributable to PM2.5 and O3 were the highest in Denmark and the lowest in Iceland. In the five Nordic countries, the results between the three tools ranged from 8500 to 11,400 for PM2.5 related deaths, and for ozone from 230 to 260 deaths in 2015. Substantially larger differences were found between five concentration-response functions. The shape of concentration-response functions, and applied theoretical thresholds led to substantial differences in the estimated deaths. Nordic countries are especially sensitive to theoretical thresholds due to low exposures. Sensitivity analysis demonstrated that when using spatial exposure assessment methods, high spatial resolution is necessary to avoid underestimation of exposures and health effects.

2014 ◽  
Vol 7 (2) ◽  
pp. 2335-2375
Author(s):  
J. Soares ◽  
A. Kousa ◽  
J. Kukkonen ◽  
L. Matilainen ◽  
L. Kangas ◽  
...  

Abstract. A mathematical model is presented for the determination of human exposure to ambient air pollution in an urban area; the model is a refined version of a previously developed mathematical model EXPAND (EXposure model for Particulate matter And Nitrogen oxiDes). The model combines predicted concentrations, information on people's activities and location of the population to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. The revisions of the modelling system containing the EXPAND model include improvements of the associated urban emission and dispersion modelling system, an improved treatment of the time-use of population, and better treatment for the infiltration coefficients from outdoor to indoor air. The revised model version can also be used for evaluating intake fractions for various pollutants, source categories and population subgroups. We present numerical results on annual spatial concentration, time activity and population exposures to PM2.5 in the Helsinki Metropolitan Area and Helsinki for 2008 and 2009, respectively. Approximately 60% of the total exposure occurred at home, 17% at work, 4% in traffic and 19% in other micro-environments. The population exposure originated from the long range transported background concentrations was responsible for a major fraction, 86%, of the total exposure. The largest local contributors were vehicular emissions (12%) and shipping (2%).


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gabriel Carrasco-Escobar ◽  
Lara Schwarz ◽  
J. Jaime Miranda ◽  
Tarik Benmarhnia

AbstractThis study aims to quantify changes in outdoor (ambient) air pollution exposure from different migration patterns within Peru and quantify its effect on premature mortality. Data on ambient fine particulate matter (PM2.5) was obtained from the National Aeronautics and Space Administration (NASA). Census data was used to calculate rates of within-country migration at the district level. We calculated differences in PM2.5 exposure between “current” (2016–2017) and “origin” (2012) districts for each migration patterns. Using an exposure-response relationship for PM2.5 extracted from a meta-analysis, and mortality rates from the Peruvian Ministry of Health, we quantified premature mortality attributable to each migration pattern. Changes in outdoor PM2.5 exposure were observed between 2012 and 2016 with highest levels of PM2.5 in the Department of Lima. A strong spatial autocorrelation of outdoor PM2.5 values (Moran’s I = 0.847, p-value=0.001) was observed. In Greater Lima, rural-to-urban and urban-to-urban migrants experienced 10-fold increases in outdoor PM2.5 exposure in comparison with non-migrants. Changes in outdoor PM2.5 exposure due to migration drove 185 (95% CI: 2.7, 360) premature deaths related to air pollution, with rural-urban producing the highest risk of mortality from exposure to higher levels of ambient air pollution. Our results demonstrate that the rural-urban and urban-urban migrant groups have higher rates of air pollution-related deaths.


2020 ◽  
Vol 15 (7) ◽  
pp. 074010 ◽  
Author(s):  
Sourangsu Chowdhury ◽  
Andrea Pozzer ◽  
Sagnik Dey ◽  
Klaus Klingmueller ◽  
Jos Lelieveld

Risk Analysis ◽  
2016 ◽  
Vol 36 (9) ◽  
pp. 1718-1736 ◽  
Author(s):  
Susan C. Anenberg ◽  
Anna Belova ◽  
Jørgen Brandt ◽  
Neal Fann ◽  
Sue Greco ◽  
...  

2016 ◽  
Author(s):  
Raquel A. Silva ◽  
J. Jason West ◽  
Jean-François Lamarque ◽  
Drew T. Shindell ◽  
William J. Collins ◽  
...  

Abstract. Ambient air pollution from ground-level ozone and fine particulate matter (PM2.5) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry-climate models simulated future concentrations of ozone and PM2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths/year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from less than 0.4 million deaths/year in 2000 to between 1.09 and 2.36 million deaths/year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. Decreases in PM2.5 concentrations relative to 2000 are associated with avoided premature mortality in all scenarios, particularly in 2100: between −2.39 and −1.31 million deaths/year for the four RCPs due to the reductions in emissions projected in these scenarios. The global mortality burden of PM2.5 is estimated to decrease from 1.7 million deaths/year in 2000 to between 0.95 and 1.55 million deaths/year in 2100 for the four RCPs, due to the combined effect of decreases in PM2.5 concentrations and changes in population and baseline mortality rates. Trends in future air pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry-climate models due to differences in simulated pollutant concentrations, and is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.


2016 ◽  
Vol 16 (15) ◽  
pp. 9847-9862 ◽  
Author(s):  
Raquel A. Silva ◽  
J. Jason West ◽  
Jean-François Lamarque ◽  
Drew T. Shindell ◽  
William J. Collins ◽  
...  

Abstract. Ambient air pollution from ground-level ozone and fine particulate matter (PM2.5) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry–climate models simulated future concentrations of ozone and PM2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air-pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths year−1), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382 000 (121 000 to 728 000) deaths year−1 in 2000 to between 1.09 and 2.36 million deaths year−1 in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM2.5 concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between −2.39 and −1.31 million deaths year−1 for the four RCPs. The global mortality burden of PM2.5 is estimated to decrease from 1.70 (1.30 to 2.10) million deaths year−1 in 2000 to between 0.95 and 1.55 million deaths year−1 in 2100 for the four RCPs due to the combined effect of decreases in PM2.5 concentrations and changes in population and baseline mortality rates. Trends in future air-pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry–climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.


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