The social and spatial distribution of temperature-related health impacts from urban heat island reduction policies. Issue 66 (December 2016)

• Record Type: Journal Article
• Authors: Vargo, Jason; Stone, Brian; Habeeb, Dana; Liu, Peng; Russell, Armistead
• Is Part Of: Environmental science & policy. Issue 66(2016:Dec.)
• Page Start: 366
• Page End: 374
• Publication Date: 2016-12
• Subjects: Urban heat island -- Climate change -- Urban adaptation -- Green area ratio -- Heat-related mortality -- Climate justice; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2016.08.012
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: People of all ages, races, and income groups benefit from cooler urban landscapes. The health benefits of urban cooling vary between and within regions and populations. Specific populations within metro areas benefit more from urban climate adaptation. Abstract: Cities are developing innovative strategies to combat climate change but there remains little knowledge of the winners and losers from climate-adaptive land use planning and design. We examine the distribution of health benefits associated with land use policies designed to increase vegetation and surface reflectivity in three US metropolitan areas: Atlanta, GA, Philadelphia, PA, and Phoenix, AZ. Projections of population and land cover at the census tract scale were combined with climate models for the year 2050 at 4 km × 4 km resolution to produce future summer temperatures which were input into a comparative risk assessment framework for the temperature-mortality relationship. The findings suggest disparities in the effectiveness of urban heat management strategies by age, income, and race. We conclude that, to be most protective of human health, urban heat management must prioritize areas of greatest population vulnerability.