Wenhao Hu , Yang Hu , Yifu Ge , Zhongyu He , Yang Ju , Guofang Zhai , Yuwen Lu , Bardia Mashhoodi
{"title":"Thermal exposure across age groups: Social, spatial, and temporal inequalities in Nanjing, China","authors":"Wenhao Hu , Yang Hu , Yifu Ge , Zhongyu He , Yang Ju , Guofang Zhai , Yuwen Lu , Bardia Mashhoodi","doi":"10.1016/j.scs.2025.106282","DOIUrl":null,"url":null,"abstract":"<div><div>As climate change and urban expansion intensify, unequal thermal exposure among different age groups has emerged as a significant health concern. Existing studies on age groups' thermal exposures have notable gaps: (1) the lack of comparison between summer and winter seasons; and (2) insufficient understanding of how metropolitan location (e.g., inner-city, suburban) and built environment characteristics (e.g., land cover, morphology) influence thermal exposure. To bridge these gaps, this study analyzes Land Surface Temperature (LST) exposure of children (0–14 years), adults (15–59 years), and senior citizens (60+ years) across Nanjing's neighborhoods during the summer and winter of 2020. The study shows that variations in metropolitan locations correspond to demographic differences and built environment characteristics such as impervious surfaces, vegetation, and building heights, leading to social, spatial and temporal LST inequalities among age groups. For instance, inner-city areas exhibited higher thermal exposure risk in both summer and winter, particularly affecting senior citizens. In contrast, adults experienced relatively moderate LST exposure, likely due to their suburban residence. Random forest model results indicate that built environment characteristics significantly and seasonally influence LST. In summer, higher proportions of impervious surfaces and lower levels of vegetation contribute to elevated LST in inner-city areas. Conversely, in winter, greater impervious surface areas, taller buildings, and greater distance from industrial zones correlate with lower temperatures in these regions. This study ultimately highlights the need for policy interventions to mitigate thermal exposure inequities among different age groups.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106282"},"PeriodicalIF":10.5000,"publicationDate":"2025-03-18","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/S2210670725001593","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
As climate change and urban expansion intensify, unequal thermal exposure among different age groups has emerged as a significant health concern. Existing studies on age groups' thermal exposures have notable gaps: (1) the lack of comparison between summer and winter seasons; and (2) insufficient understanding of how metropolitan location (e.g., inner-city, suburban) and built environment characteristics (e.g., land cover, morphology) influence thermal exposure. To bridge these gaps, this study analyzes Land Surface Temperature (LST) exposure of children (0–14 years), adults (15–59 years), and senior citizens (60+ years) across Nanjing's neighborhoods during the summer and winter of 2020. The study shows that variations in metropolitan locations correspond to demographic differences and built environment characteristics such as impervious surfaces, vegetation, and building heights, leading to social, spatial and temporal LST inequalities among age groups. For instance, inner-city areas exhibited higher thermal exposure risk in both summer and winter, particularly affecting senior citizens. In contrast, adults experienced relatively moderate LST exposure, likely due to their suburban residence. Random forest model results indicate that built environment characteristics significantly and seasonally influence LST. In summer, higher proportions of impervious surfaces and lower levels of vegetation contribute to elevated LST in inner-city areas. Conversely, in winter, greater impervious surface areas, taller buildings, and greater distance from industrial zones correlate with lower temperatures in these regions. This study ultimately highlights the need for policy interventions to mitigate thermal exposure inequities among different age groups.
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;