极端天气
弹性(材料科学)
环境规划
脆弱性(计算)
准备
社区复原力
环境资源管理
弱势群体
气候变化
极热
心理弹性
人口
环境科学
地理
资源(消歧)
环境卫生
计算机科学
政治学
生态学
法学
物理
热力学
心理治疗师
生物
医学
计算机安全
计算机网络
心理学
作者
Paramita Sinha,M. M. Fry,Susan Julius,Robert Truesdale,James Cajka,Michele Eddy,Prakash Doraiswamy,Rosanne Albright,Julie Riemenschneider,Matthew Potzler,Brian Lim,Jennifer Richkus,Maggie O’Neal
标识
DOI:10.1016/j.crm.2024.100586
摘要
The interplay of contaminated sites, climate change, and disadvantaged communities are a growing concern worldwide. Worsening extreme events may result in accidental contaminant releases from sites and waste facilities that may impact nearby communities. If such communities are already suffering from environmental, economic, health, or social burdens, they may face disproportionate impacts. Equitable resilience planning to address effects of extreme events requires information on where the impacts may be, when they may occur, and who might be impacted. Because resources are often scarce for these communities, conducting detailed modeling may be cost-prohibitive. By considering indicators for four sources of vulnerability (changing extreme heat conditions, contaminated sites, contaminant transport via wind, and population sensitivities) in one holistic framework, we provide a scientifically robust approach that can assist planners with prioritizing resources and actions. These indicators can serve as screening measures to identify communities that may be impacted most and isolate the reasons for these impacts. Through a transdisciplinary case study conducted in Maricopa County (Arizona, USA), we demonstrate how the framework and geospatial indicators can be applied to inform plans for preparedness, response, and recovery from the effects of extreme heat on contaminated sites and nearby populations. The indicators employed in this demonstration can be applied to other locations with contaminated sites to build community resilience to future climate impacts.
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