Virginia Heat Watch: Collaboration to assess climate vulnerability at local to regional scales

被引:0
作者
Lookingbill, Todd R. [1 ]
Warren, Karin P. [2 ]
Haley, J. Christopher [3 ]
Malcolm, Elizabeth G. [3 ]
Powell, Lisa Jordan [4 ]
Starr, Scott M. [5 ]
Witiak, Sarah Melissa [6 ]
Wolyniak, Michael J. [5 ]
Zizzamia, Beth [1 ]
机构
[1] Univ Richmond, Dept Geog Environm & Sustainabil, Richmond, VA 23173 USA
[2] Randolph Coll, Dept Environm Studies & Sci, Lynchburg, VA USA
[3] Virginia Wesleyan Univ, Dept Earth & Environm Sci, Virginia Beach, VA USA
[4] Sweet Briar Coll, Ctr Human & Environm Sustainabil, Sweet Briar, VA USA
[5] Hampden Sydney Coll, Dept Biol, Sydney, VA USA
[6] Virginia State Univ, Dept Biol, Petersburg, VA USA
关键词
Community-based science; Urban heat island; Environmental justice; E[!text type='JS']JS[!/text]creen; Socioeconomic disparities; Urban tree canopy; Food access; HOLC; ISLAND; TEMPERATURE; IMPACTS; WEATHER; ENERGY; WAVE;
D O I
10.1016/j.uclim.2024.102252
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Systematic studies of temperature using consistent, field-validated methods are needed to make inter- and intra-urban heat comparisons and to prioritize resources and mitigation strategies. This study investigated spatial patterns of heat hazard across 10 small- to medium- sized cities in Virginia, USA, using a community science approach. Air temperature data were collected on a high-heat day in July 2021, employing a network of 213 volunteers. Geolocated one-second temperature and humidity measurements were used to create and validate 10-m resolution temperature models for each locality. Results indicate substantial intra-urban temperature differentials even in the smallest localities, averaging 3.2 degrees C for the morning, 5.1 degrees C for the afternoon, and 4.9 degrees C for the evening. The average cooling rate for the region was 0.28 degrees C per 10 % increase in tree cover. Census Block Groups with highest percentages of people of color and historically redlined neighborhoods exhibited elevated temperatures, highlighting environmental justice (EJ) implications. Socioeconomic variables less commonly used in EJ studies, such as educational attainment and employment status, were predictive of high-temperature areas in the smaller localities. Findings underscore the broad range of urban heat drivers and illustrate how community-based data can be used to prioritize policy and actions addressing extreme heat at local and regional scales.
引用
收藏
页数:16
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