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Avoided Heat-Related Mortality through Climate Adaptation Strategies in Three US Cities

Overview of attention for article published in PLOS ONE, June 2014
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Title
Avoided Heat-Related Mortality through Climate Adaptation Strategies in Three US Cities
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0100852
Pubmed ID
Authors

Brian Stone, Jason Vargo, Peng Liu, Dana Habeeb, Anthony DeLucia, Marcus Trail, Yongtao Hu, Armistead Russell

Abstract

Heat-related mortality in US cities is expected to more than double by the mid-to-late 21st century. Rising heat exposure in cities is projected to result from: 1) climate forcings from changing global atmospheric composition; and 2) local land surface characteristics responsible for the urban heat island effect. The extent to which heat management strategies designed to lessen the urban heat island effect could offset future heat-related mortality remains unexplored in the literature. Using coupled global and regional climate models with a human health effects model, we estimate changes in the number of heat-related deaths in 2050 resulting from modifications to vegetative cover and surface albedo across three climatically and demographically diverse US metropolitan areas: Atlanta, Georgia, Philadelphia, Pennsylvania, and Phoenix, Arizona. Employing separate health impact functions for average warm season and heat wave conditions in 2050, we find combinations of vegetation and albedo enhancement to offset projected increases in heat-related mortality by 40 to 99% across the three metropolitan regions. These results demonstrate the potential for extensive land surface changes in cities to provide adaptive benefits to urban populations at risk for rising heat exposure with climate change.

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Geographical breakdown

Country Count As %
Canada 2 <1%
United States 2 <1%
United Kingdom 1 <1%
Colombia 1 <1%
Japan 1 <1%
Sweden 1 <1%
Unknown 222 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 21%
Researcher 42 18%
Student > Master 40 17%
Professor 11 5%
Other 10 4%
Other 30 13%
Unknown 48 21%
Readers by discipline Count As %
Environmental Science 55 24%
Engineering 25 11%
Earth and Planetary Sciences 18 8%
Medicine and Dentistry 17 7%
Social Sciences 17 7%
Other 28 12%
Unknown 70 30%