Application of Universal Thermal Climate Index (UTCI) for microclimatic analysis in urban thermal environments

Park, Sookuk; Tuller, Stanton E.; Jo, Minseok

doi:10.1016/j.landurbplan.2014.02.014

Cited by 149 publications

(59 citation statements)

References 75 publications

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“…Park et al . examined human thermal sensation on human biological maps in summer, demonstrating that UTCI registered correlation coefficients of 0.983, 0.979 and 0.957 with PET, PMV and SET, respectively (Park et al ., ). Farajzadeh et al .…”

Section: Discussionmentioning

confidence: 97%

“…In previous studies, significant correlations were found between the UTCI with SET (r = 0.97) and the PET index (r = 0.96) (Blazejczyk et al, 2012), in addition to a significant relationship between the UTCI and PET index (r = 0.936) (Matzarakis et al, 2014). Park et al examined human thermal sensation on human biological maps in summer, demonstrating that UTCI registered correlation coefficients of 0.983, 0.979 and 0.957 with PET, PMV and SET, respectively (Park et al, 2014). Farajzadeh et al evaluated the thermal indices in northern Iran from 1986 to 2007; the results demonstrated that UTCI strongly connected with PET and SET with r = 0.9 and r = 0.94, respectively (Farajzadeh et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

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Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

Asghari

Teimori

Abbasinia

et al. 2019

Weather

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Objectives The aim of this study was to analyse the thermal discomfort of outdoor environments in two climates of Iran using physiological equivalent temperature (PET), predicted mean vote (PMV) indices and Universal Thermal Climate Index (UTCI). Methods In this study, the meteorological data recorded by the meteorological organisation in a 15‐year period, including temperature, air velocity, cloudiness, relative humidity and water vapour pressure, in two different climates of Iran were surveyed. According to classification of the Köppen, Arak as a representative of a semi‐arid and cold climate and Bandar Abbas as a representative of a hot and dry climate were used to calculate thermal indices. The PMV index was based on the ASHRAE 7‐point thermal sensation scale, and the values of PMV and PET indices were extracted using Rayman1.2 software. The values of the UTCI were calculated using BioKlima 2.6 software. Results The results showed that the maximum and minimum temperatures in two climates were related to July and January, respectively. In Arak, the means of the UTCI, PET and PMV indices were 14.41 ± 11.5, 15.81 ± 1.23 and −0.77 ± 2.15, respectively. In Bandar Abbas as well, the mean of the UTCI, PET and PMV indices were 22.56 ± 9, 22.73 ± 7.7 and 0.73 ± 7.7, respectively. In Arak, there was moderate heat stress to moderate cold stress in this region, whereas in Bandar Abbas, the days had a strong heat stress to low cold stress. There are very strong correlations between the indices used for two different climates. Conclusion The bioclimatic comfort indices used were able to demonstrate the comfort and discomfort of people during different months of the year in two surveyed climates, and despite trivial differences, they provided relatively uniform representations of climate comfort for surveyed cities. Using thermal comfort indices, high‐risk areas can be identified, and appropriate measures can be adopted to reduce the effects of the changes.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

Asghari

Teimori

Abbasinia

et al. 2019

Weather

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“…For example, on a windy day (i.e., high-speed air flow), people tend to feel the discomfort due to the wind environment. Therefore, other methods could be included, such as mapping human bioclimatic map with human activities in open space [47], sun and wind desirability [48]. Moreover, future work should measure thermal comfort instead of only the mean value of UTCI for the entire environment as a judging standard [40], which is an indispensable premise for the intensive development of performance-driven optimization design.…”

Section: Limitations Of This Studymentioning

confidence: 99%

Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China

Wang

et al. 2019

Build. Simul.

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“…More people are affected by higher temperatures for longer period, higher temperature not only makes life uncomfortable for urban residents it is also adversely affecting people's health [14,16] psychology (body heating, increasing stress due to sweating and blood flow, and normal regulation by sweating and vascular change), and health (circulatory collapse, increasing danger of heat stroke, cardiovascular embarassment and normal health) [16,23]. Those indices will determine the urban heat hazard in our study area.…”

Section: Universal Thermal Climate Index (Utci) and Effective Temperamentioning

confidence: 99%

Spatial temporal analysis of urban heat hazard in Tangerang City

Wibowo

Kuswantoro

Ardiansyah

et al. 2016

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. Urban heat is a natural phenomenon which might caused by human activities. The human activities were represented by various types of land-use such as urban and non-urban area. The aim of this study is to identify the urban heat behavior in Tangerang City as it might threats the urban environment. This study used three types of remote sensing data namely, Landsat TM, Landsat ETM+ and Landsat OLI-TIRS, to capture the urban heat behavior and to analysis the urban heat signature of Tangerang City in 2001, 2012, 2013, 2014, 2015 and 2016. The result showed that urban heat signature change dynamically each month based on the sun radiation. The urban heat island covered only small part of Tangerang City in 2001, but it was significantly increased and reached 50% of the area in 2012. Based on the result on urban heat signature, the threshold for threatening condition is 30 o C which recognized from land surface temperature (LST). The effective temperature (ET) index explains that condition as warm, uncomfortable, increase stress due to sweating and blood flow and may causing cardiovascular disorder.

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Application of Universal Thermal Climate Index (UTCI) for microclimatic analysis in urban thermal environments

Cited by 149 publications

References 75 publications

Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

Thermal discomfort analysis using UTCI and MEMI (PET and PMV) in outdoor environments: case study of two climates in Iran (Arak & Bandar Abbas)

Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China

Spatial temporal analysis of urban heat hazard in Tangerang City

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