{"title":"Heatwaves at work: Typology and spatial distributions of occupations exposed to heatwaves in Korea","authors":"","doi":"10.1016/j.scs.2024.105921","DOIUrl":null,"url":null,"abstract":"<div><div>Adapting to heatwaves and other climate change impacts requires identifying vulnerable demographic segments within regions. However, investigations into the spatial distribution of heatwave-vulnerable workers and its implications for local economies have been limited. This study categorizes occupations exposed to heatwaves into five subgroups and analyzes temporal changes in their spatial distributions via a spatial Markov chain model. The results indicate significant heterogeneity in vulnerability among heatwave-exposed occupations, with variations in income, foreign worker proportions, and job instability. The analysis reveals that heatwave-exposed workers are primarily concentrated outside the capital region. Group 3 (manufacturing) exhibited notable industrial clustering, whereas Group 5 (agriculture and fishery) presented high and stable concentrations in rural areas. Conversely, Group 4 (low-skilled and market-sensitive) demonstrates substantial spatial variability. Spatial Markov chain analysis highlights Group 3′s strong agglomeration tendencies influenced by neighboring cities, whereas Group 5 shows minimal spatial effects. Groups 2 and 4 experience considerable shifts in spatial distribution, with Group 2 showing only a 68.7 % probability of sustaining high concentration and Group 4 showing a 62.7 % probability. Recommendations for adaptation strategies and future research related to the economic impacts of climate change are provided on the basis of these findings.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":null,"pages":null},"PeriodicalIF":10.5000,"publicationDate":"2024-10-19","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/S2210670724007455","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
Adapting to heatwaves and other climate change impacts requires identifying vulnerable demographic segments within regions. However, investigations into the spatial distribution of heatwave-vulnerable workers and its implications for local economies have been limited. This study categorizes occupations exposed to heatwaves into five subgroups and analyzes temporal changes in their spatial distributions via a spatial Markov chain model. The results indicate significant heterogeneity in vulnerability among heatwave-exposed occupations, with variations in income, foreign worker proportions, and job instability. The analysis reveals that heatwave-exposed workers are primarily concentrated outside the capital region. Group 3 (manufacturing) exhibited notable industrial clustering, whereas Group 5 (agriculture and fishery) presented high and stable concentrations in rural areas. Conversely, Group 4 (low-skilled and market-sensitive) demonstrates substantial spatial variability. Spatial Markov chain analysis highlights Group 3′s strong agglomeration tendencies influenced by neighboring cities, whereas Group 5 shows minimal spatial effects. Groups 2 and 4 experience considerable shifts in spatial distribution, with Group 2 showing only a 68.7 % probability of sustaining high concentration and Group 4 showing a 62.7 % probability. Recommendations for adaptation strategies and future research related to the economic impacts of climate change are provided on the basis of these findings.
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;