High-resolution outdoor heat-risk modeling for city central areas with applications to Tokyo and Lyon

IF 10.5 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Alvin C.G. Varquez , Janat Taerakul , Florent Renard , Lucille Alonso , Sunkyung Choi , Ryoga Hiroki , Yasunobu Ashie , Eiko Kumakura , Makoto Okumura , Shinya Hanaoka , Atsushi Inagaki , Manabu Kanda
{"title":"High-resolution outdoor heat-risk modeling for city central areas with applications to Tokyo and Lyon","authors":"Alvin C.G. Varquez ,&nbsp;Janat Taerakul ,&nbsp;Florent Renard ,&nbsp;Lucille Alonso ,&nbsp;Sunkyung Choi ,&nbsp;Ryoga Hiroki ,&nbsp;Yasunobu Ashie ,&nbsp;Eiko Kumakura ,&nbsp;Makoto Okumura ,&nbsp;Shinya Hanaoka ,&nbsp;Atsushi Inagaki ,&nbsp;Manabu Kanda","doi":"10.1016/j.scs.2025.106344","DOIUrl":null,"url":null,"abstract":"<div><div>Owing to climate change, urbanization, and population shifts, heat risks in cities are projected to rise. This work aims to introduce a flexible approach for mapping outdoor heat risks by individually constructing, normalizing, and combining its four key components – hazard, exposure, vulnerability, and adaptive capacity – as recommended by the International Panel on Climate Change. The methodology was demonstrated by constructing 500-m hourly-varying outdoor heat risk maps of elderly population over two city-central areas (Tokyo and Lyon) of distinct geophysical features and demographic conditions during a summer day in 2022. The hazard component was described using a 2-m simulation of heat-stress index (wet-bulb globe temperature), which accounts for urban surface details. Vulnerability, exposure, and adaptive capacity were then defined as functions of hourly 500-m population changes, open-space ratios, and proximity to health centers, respectively. During the selected dates in Tokyo’s and Lyon’s central areas, significant spatiotemporal variations emerged in daytime elderly heat risk due to their unique urban landscapes, local climates, and senior population mobility patterns. Meanwhile, reductions in elderly population movement resulted in low outdoor vulnerability despite the peak heat hazard condition during the noontime. This work highlights the usefulness of the proposed approach, the prevailing complexities of detailed risk mapping over city-central areas, and the utility potential of increasing high-quality geospatial datasets.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"125 ","pages":"Article 106344"},"PeriodicalIF":10.5000,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670725002215","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Owing to climate change, urbanization, and population shifts, heat risks in cities are projected to rise. This work aims to introduce a flexible approach for mapping outdoor heat risks by individually constructing, normalizing, and combining its four key components – hazard, exposure, vulnerability, and adaptive capacity – as recommended by the International Panel on Climate Change. The methodology was demonstrated by constructing 500-m hourly-varying outdoor heat risk maps of elderly population over two city-central areas (Tokyo and Lyon) of distinct geophysical features and demographic conditions during a summer day in 2022. The hazard component was described using a 2-m simulation of heat-stress index (wet-bulb globe temperature), which accounts for urban surface details. Vulnerability, exposure, and adaptive capacity were then defined as functions of hourly 500-m population changes, open-space ratios, and proximity to health centers, respectively. During the selected dates in Tokyo’s and Lyon’s central areas, significant spatiotemporal variations emerged in daytime elderly heat risk due to their unique urban landscapes, local climates, and senior population mobility patterns. Meanwhile, reductions in elderly population movement resulted in low outdoor vulnerability despite the peak heat hazard condition during the noontime. This work highlights the usefulness of the proposed approach, the prevailing complexities of detailed risk mapping over city-central areas, and the utility potential of increasing high-quality geospatial datasets.
城市中心区高分辨率室外热风险建模在东京和里昂的应用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信