Skip to Content

Urban Climate Student wins ISSR Poster Award!

The ISSR poster contest is hosted by the Institute for Social Science Research (ISSR) and is for graduate students at ASU conducting social science research in any field to present proposed and completed research.  This spring semester, 51 students competed and our own Mary Wright was one of 3 first-place winners!

Title: Indoor Temperature and Air Conditioning Use in Phoenix, AZ: A Household Study

Abstract:

Extreme heat is a climate-sensitive health hazard of concern in many cities around the world. Heat vulnerability is higher in many lower-income neighborhoods where vegetation coverage is lower and land surface temperatures are higher. Future health impacts from long-term stressors like global and urban-scale warming are expected to hit resource-constrained populations the hardest.  Despite knowledge that people in the developed world spend 90% of their time indoors, and that indoor exposure accounts for a sizable fraction of heat-related illnesses and deaths, very little is known about the thermal environment indoors, especially in private residences. Thus, the indoor environment is vital to understanding the thermal experience of individuals.

This poster investigates data collected for a project that aims to improve regional hazard resilience. Funded by an NSF Hazards-SEES grant, an interdisciplinary team of researchers at ASU, Georgia Tech, and University of Michigan are striving to uncover the specific social and environmental mechanisms that determine urban vulnerability when independent or coupled heat and power failure events occur. This poster shares preliminary findings from summer 2016 data collection in Phoenix, which involved household surveys, semi-structured vignette interviews, and indoor, outdoor, and personal temperature sensors. In particular, to address the gap in quantitatively backed literature examining the indoor thermal environment, indoor temperatures are investigated utilizing a two-stage clustering approach incorporating hourly mean, variance, and diurnal range.  Clustering reveals specific quantitative cooling profiles which are then matched with survey responses indicating degree of constraint on resources (such as air conditioning), risk perception, and demographic variable