The 2011 heat wave in Greater Houston: Effects of land use on temperature

被引:24
作者
Zhou, Weihe [1 ]
Ji, Shuang [1 ]
Chen, Tsun-Hsuan [2 ]
Hou, Yi [3 ]
Zhang, Kai [2 ]
机构
[1] Univ Texas Houston, Sch Publ Hlth, Div Biostat, Houston, TX 77030 USA
[2] Univ Texas Houston, Sch Publ Hlth, Div Epidemiol Human Genet & Environm Sci, Houston, TX 77030 USA
[3] CDM Smith, Dallas, TX USA
关键词
Heat wave; Land use regression; Quantile regression; Temperature; PUBLIC-HEALTH; SURFACE-TEMPERATURE; MORTALITY; DETROIT; CITIES;
D O I
10.1016/j.envres.2014.08.025
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Effects of land use on temperatures during severe heat waves have been rarely studied. This paper examines land use-temperature associations during the 2011 heat wave in Greater Houston. We obtained high resolution of satellite-derived land use data from the US National Land Cover Database, and temperature observations at 138 weather stations from Weather Underground, Inc (WU) during the August of 2011, which was the hottest month in Houston since 1889. Land use regression and quantile regression methods were applied to the monthly averages of daily maximum/mean/minimum temperatures and 114 land use-related predictors. Although selected variables vary with temperature metric, distance to the coastline consistently appears among all models. Other variables are generally related to high developed intensity, open water or wetlands. In addition, our quantile regression analysis shows that distance to the coastline and high developed intensity areas have larger impacts on daily average temperatures at higher quantiles, and open water area has greater impacts on daily minimum temperatures at lower quantiles. By utilizing both land use regression and quantile regression on a recent heat wave in one of the largest US metropolitan areas, this paper provides a new perspective on the impacts of land use on temperatures. Our models can provide estimates of heat exposures for epidemiological studies, and our findings can be combined with demographic variables, air conditioning and relevant diseases information to identify 'hot spots' of population vulnerability for public health interventions to reduce heat-related health effects during heat waves. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:81 / 87
页数:7
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