Projection of Mortality Burden Attributable to Nonoptimum Temperature with High Spatial Resolution in China
The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:58 |
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| Enthalten in: |
Environmental science & technology - 58(2024), 14 vom: 09. Apr., Seite 6226-6235 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yin, Peng [VerfasserIn] |
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| Links: |
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| Themen: |
Climate change |
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| Anmerkungen: |
Date Completed 10.04.2024 Date Revised 10.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1021/acs.est.3c09162 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM370465261 |
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| 520 | |a The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming | ||
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| 700 | 1 | |a He, Cheng |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Renjie |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Jianbin |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Yong |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Xuejie |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Ji, John S |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Wenjia |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Yongjie |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Huichu |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Maigeng |e verfasserin |4 aut | |
| 700 | 1 | |a Kan, Haidong |e verfasserin |4 aut | |
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