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Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios
Projections of the magnitude and pattern of possible health risks from climate change should be based on multiple climate and development scenarios to describe the range of uncertainties, to inform effective and efficient policies. For a better understanding of climate change-related risks in seven...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466250/ https://www.ncbi.nlm.nih.gov/pubmed/30901812 http://dx.doi.org/10.3390/ijerph16061026 |
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author | Lee, Jae Young Lee, Woo-Seop Ebi, Kristie L. Kim, Ho |
author_facet | Lee, Jae Young Lee, Woo-Seop Ebi, Kristie L. Kim, Ho |
author_sort | Lee, Jae Young |
collection | PubMed |
description | Projections of the magnitude and pattern of possible health risks from climate change should be based on multiple climate and development scenarios to describe the range of uncertainties, to inform effective and efficient policies. For a better understanding of climate change-related risks in seven metropolitan cities of South Korea, we estimated temperature-related summer (June to August) mortality until 2100 using projected changes in climate, population, and adaptation. In addition, we extracted the variations in the mortality estimates associated with uncertainties in climate, population, and adaptation scenarios using 25 climate models, two Representative Concentration Pathways (RCP 4.5 and 8.5), three population scenarios (high, medium and low variants), and four adaptation scenarios (absolute threshold shift, slope reduction in the temperature-mortality relationship, a combination of slope reduction and threshold shift, and a sigmoid function based on the historical trend). Compared to the baseline period (1991–2015), temperature-attributable mortality in South Korea during summer in the 2090s is projected to increase 5.1 times for RCP 4.5 and 12.9 times for RCP 8.5 due to climate and population changes. Estimated future mortality varies by up to +44%/−55%, −80%, −60%, and +12%/−11% associated with the choice of climate models, adaptation, climate, and population scenarios, respectively, compared to the mortality estimated for the median of the climate models, no adaptation, RCP 8.5, and medium population variant. Health system choices about adaptation are the most important determinants of future mortality after climate projections. The range of possible future mortality underscores the importance of flexible, iterative risk management. |
format | Online Article Text |
id | pubmed-6466250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64662502019-04-22 Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios Lee, Jae Young Lee, Woo-Seop Ebi, Kristie L. Kim, Ho Int J Environ Res Public Health Article Projections of the magnitude and pattern of possible health risks from climate change should be based on multiple climate and development scenarios to describe the range of uncertainties, to inform effective and efficient policies. For a better understanding of climate change-related risks in seven metropolitan cities of South Korea, we estimated temperature-related summer (June to August) mortality until 2100 using projected changes in climate, population, and adaptation. In addition, we extracted the variations in the mortality estimates associated with uncertainties in climate, population, and adaptation scenarios using 25 climate models, two Representative Concentration Pathways (RCP 4.5 and 8.5), three population scenarios (high, medium and low variants), and four adaptation scenarios (absolute threshold shift, slope reduction in the temperature-mortality relationship, a combination of slope reduction and threshold shift, and a sigmoid function based on the historical trend). Compared to the baseline period (1991–2015), temperature-attributable mortality in South Korea during summer in the 2090s is projected to increase 5.1 times for RCP 4.5 and 12.9 times for RCP 8.5 due to climate and population changes. Estimated future mortality varies by up to +44%/−55%, −80%, −60%, and +12%/−11% associated with the choice of climate models, adaptation, climate, and population scenarios, respectively, compared to the mortality estimated for the median of the climate models, no adaptation, RCP 8.5, and medium population variant. Health system choices about adaptation are the most important determinants of future mortality after climate projections. The range of possible future mortality underscores the importance of flexible, iterative risk management. MDPI 2019-03-21 2019-03 /pmc/articles/PMC6466250/ /pubmed/30901812 http://dx.doi.org/10.3390/ijerph16061026 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lee, Jae Young Lee, Woo-Seop Ebi, Kristie L. Kim, Ho Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title | Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title_full | Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title_fullStr | Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title_full_unstemmed | Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title_short | Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios |
title_sort | temperature-related summer mortality under multiple climate, population, and adaptation scenarios |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466250/ https://www.ncbi.nlm.nih.gov/pubmed/30901812 http://dx.doi.org/10.3390/ijerph16061026 |
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