The urban heat island and its impact on heat waves and human health in Shanghai

Tan, Junlei; Zheng, Yan; Tang, Xiaochao; Guo, Changyi; Zhang, Lipeng; Song, Guang-Jing; Zhen, Xinrong; Dong, Yuan; Kalkstein, Adam J.; Feng, Liang; Chen, Huey tsyh

doi:10.1007/s00484-009-0256-x

Cited by 891 publications

(444 citation statements)

References 47 publications

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“…and Melas, D. (2012) reported a higher UHI intensity in the night time and during the warm period in Thessaloniki and Athens (Greece). Maximum intensity of the daytime UHI in summer was detected in other non-European cities with subtropical or tropical climate, such as Shanghai (Tan, J. et al 2010) or Muscat (Charabi, Y. and Bakhit, A. 2011), while in Szeged (Hungary), during a one-year long measurement campaign, the maximum intensity was found in the night-time (Lelovics, E. et al 2014).…”

Section: Detection Of Atmospheric Urban Heat Island Through Direct Mementioning

confidence: 89%

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

et al. 2016

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In the last decades, cities worldwide have experienced accelerated development, so that continuous urbanization and its impact is presently one of the most important topics in diff erent fi elds of research. The main aim of this study is to identify the intensity of the atmospheric urban heat island in Cluj-Napoca city, through direct observations campaigns by using fi xed points and transect measurements. The data has been collected over a period of 6 months (May-October 2015). The measurements have been performed mainly in anti-cyclonic weather condition, during the night, between 23:00 and 03:00. The profi les trajectories followed the main roads of the city on directions North-South, East-West, and Northwest-Southeast. 8 fi xed points have been chosen in order to highlight best the temperature patt erns in diff erent Local Climate Zones (LCZs). The main fi ndings of the study are the followings: the direct observations performed in three seasons (spring, summer and autumn) revealed the existence of an atmospheric urban heat island in Cluj-Napoca city; the warmest areas are compact high-rise and compact midrise, located in the eastern half of the city, where the temperature increases by more than 2.0 °C, as average value for all campaigns, but the maximum values, recorded in the summer are higher than 3.0 °C; the coolest areas are sparsely built areas and the large low-rise/water areas, where the temperature is quite similar to that recorded in the nearby rural areas (diff erence of 0.0-0.1 °C, as average values); local factors, such as mountain breeze and topography have a great impact on the atmospheric urban heat island confi guration.

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Section: Detection Of Atmospheric Urban Heat Island Through Direct Mementioning

confidence: 89%

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

et al. 2016

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“…The obtained TOA reflectance was then corrected for the Sun's angle, based on Equation (6). The study area was classified into three main categories, vegetation, built-up, and waterbody areas.…”

Section: Landsat Oli Data For 2013mentioning

confidence: 99%

Correlation or Causality between Land Cover Patterns and the Urban Heat Island Effect? Evidence from Brisbane, Australia

2016

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Numerous studies have identified associations between the surface urban heat island (SUHI) effect (i.e., SUHI, hereinafter is referred to as UHI) and urban growth, particularly changes in land cover patterns. This research questions their causal links to answer a key policy question: If cities restrict urban expansion and encourage people to live within existing urban areas, will that help in controlling UHI? The question has been answered by estimating four models using data from Brisbane, Australia: Model 1-cross-sectional ordinary least square (OLS) regression-to examine the association between the UHI effect and land cover patterns in 2013; Model 2-cross-sectional geographically weighted regression (GWR)-to examine whether the outputs generated from Model 1 possess significant spatial variations; Model 3-longitudinal OLS-to examine whether changes in land cover patterns led to changes in UHI effects between 2004 and 2013; and Model 4-longitudinal GWR-to examine whether the outputs generated from Model 3 vary significantly over space. All estimations were controlled for potential confounding effects (e.g., population, employment and dwelling densities). Results from the cross-sectional OLS and GWR models were consistent with previous findings and showed that porosity is negatively associated with the UHI effect in 2013. In contrast, population density has a positive association. Results from the longitudinal OLS and GWR models confirm their causal linkages and showed that an increase in porosity level reduced the UHI effect, whereas an increase in population density increased the UHI effect. The findings suggest that even a containment of population growth within existing urban areas will lead to the UHI effect. However, this can be significantly minimized through proper land use planning, by creating a balance between urban and non-urban uses of existing urban areas.

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“…Urban heat, often quantified as urban heat island (UHI), can locally exacerbate the effects of regional climates on heat, emissions, and air quality [1][2][3][4][5]. The exacerbation has significant ramifications in terms of public health from both heat and air-quality pathways [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

Taha¹

2017

Climate

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Abstract:To further evaluate the factors influencing public heat and air-quality health, a characterization of how urban areas affect the thermal environment, particularly in terms of the air temperature, is necessary. To assist public health agencies in ranking urban areas in terms of heat stress and developing mitigation plans or allocating various resources, this study characterized urban heat in California and quantified an urban heat island index (UHII) at the census-tract level (~1 km 2 ). Multi-scale atmospheric modeling was carried out and a practical UHII definition was developed. The UHII was diagnosed with different metrics and its spatial patterns were characterized for small, large, urban-climate archipelago, inland, and coastal areas. It was found that within each region, wide ranges of urban heat and UHII exist. At the lower end of the scale (in smaller urban areas), the UHII reaches up to 20 degree-hours per day (DH/day; • C.hr/day), whereas at the higher end (in larger areas), it reaches up to 125 DH/day or greater. The average largest temperature difference (urban heat island) within each region ranges from 0.5-1.0 • C in smaller areas to up to 5 • C or more at the higher end, such as in urban-climate archipelagos. Furthermore, urban heat is exacerbated during warmer weather and that, in turn, can worsen the health impacts of heat events presently and in the future, for which it is expected that both the frequency and duration of heat waves will increase.

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The urban heat island and its impact on heat waves and human health in Shanghai

Cited by 891 publications

References 47 publications

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

Correlation or Causality between Land Cover Patterns and the Urban Heat Island Effect? Evidence from Brisbane, Australia

Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

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