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Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios

Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state‐of‐the‐art composition‐climate model simulations to contrast human exposure to fine particulate matter in Africa under a “...

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Autores principales: Shindell, D., Faluvegi, G., Parsons, L., Nagamoto, E., Chang, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077466/
https://www.ncbi.nlm.nih.gov/pubmed/35573486
http://dx.doi.org/10.1029/2022GH000601
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author Shindell, D.
Faluvegi, G.
Parsons, L.
Nagamoto, E.
Chang, J.
author_facet Shindell, D.
Faluvegi, G.
Parsons, L.
Nagamoto, E.
Chang, J.
author_sort Shindell, D.
collection PubMed
description Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state‐of‐the‐art composition‐climate model simulations to contrast human exposure to fine particulate matter in Africa under a “baseline” scenario with high material consumption, population growth, and warming to that projected under a sustainability scenario with lower consumption, population growth, and warming. Evaluating the mortality impacts of these exposures, we find that under the low warming scenario annual premature deaths due to PM(2.5) are reduced by roughly 515,000 by 2050 relative to the high warming scenario (100,000, 175,000, 55,000, 140,000, and 45,000 in Northern, West, Central, East, and Southern Africa, respectively). This reduction rises to ∼800,000 by the 2090s, though by that time much of the difference is attributable to the projected differences in population. By contrast, during the first half of the century benefits are driven predominantly by emissions changes. Depending on the region, we find large intermodel spreads of ∼25%–50% in projected future exposures owing to different physics across the ensemble of 6 global models. The spread of projected deaths attributable to exposure to fine particulate matter, including uncertainty in the exposure‐response function, are reduced in every region to ∼20%–35% by the non‐linear exposure‐response function. Differences between the scenarios have an even narrower spread of ∼5%–25% and are highly statistically significant in all regions for all models. These results provide valuable information for policy‐makers to consider when working toward climate change mitigation and sustainable development goals.
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spelling pubmed-90774662022-05-13 Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios Shindell, D. Faluvegi, G. Parsons, L. Nagamoto, E. Chang, J. Geohealth Research Article Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state‐of‐the‐art composition‐climate model simulations to contrast human exposure to fine particulate matter in Africa under a “baseline” scenario with high material consumption, population growth, and warming to that projected under a sustainability scenario with lower consumption, population growth, and warming. Evaluating the mortality impacts of these exposures, we find that under the low warming scenario annual premature deaths due to PM(2.5) are reduced by roughly 515,000 by 2050 relative to the high warming scenario (100,000, 175,000, 55,000, 140,000, and 45,000 in Northern, West, Central, East, and Southern Africa, respectively). This reduction rises to ∼800,000 by the 2090s, though by that time much of the difference is attributable to the projected differences in population. By contrast, during the first half of the century benefits are driven predominantly by emissions changes. Depending on the region, we find large intermodel spreads of ∼25%–50% in projected future exposures owing to different physics across the ensemble of 6 global models. The spread of projected deaths attributable to exposure to fine particulate matter, including uncertainty in the exposure‐response function, are reduced in every region to ∼20%–35% by the non‐linear exposure‐response function. Differences between the scenarios have an even narrower spread of ∼5%–25% and are highly statistically significant in all regions for all models. These results provide valuable information for policy‐makers to consider when working toward climate change mitigation and sustainable development goals. John Wiley and Sons Inc. 2022-05-01 /pmc/articles/PMC9077466/ /pubmed/35573486 http://dx.doi.org/10.1029/2022GH000601 Text en © 2022 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Article
Shindell, D.
Faluvegi, G.
Parsons, L.
Nagamoto, E.
Chang, J.
Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title_full Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title_fullStr Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title_full_unstemmed Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title_short Premature Deaths in Africa Due To Particulate Matter Under High and Low Warming Scenarios
title_sort premature deaths in africa due to particulate matter under high and low warming scenarios
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077466/
https://www.ncbi.nlm.nih.gov/pubmed/35573486
http://dx.doi.org/10.1029/2022GH000601
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