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Mapping thermal comfort in Iran based on geostatistical methods and bioclimatic indices

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Abstract

The cognition of thermal comfort plays a pivotal role in human life and activities. Recognizing thermal comfort based on climatic parameters is substantially significant. The main objective of the present study is to map thermal comfort using statistics from 43 meteorological stations, from 1970 to 2013. Initially, according to temperature and relative humidity, annual and seasonal thermal comfort conditions were mapped, and later bioclimatic human thermal comfort conditions in line with spatial factors were zoned based on bioclimatic indexes of Temperature Humidity Index (THI), effective temperature (ET) and Relative Strain Index (RSI). Among geostatistical methods, empirical Bayesian kriging (EBK) method with less RSME is more efficient. The annual distribution of temperature changes according to spatial factors of rugged topography and elevation, and latitude affects relative humidity. Thermal comfort in the northern and western half of Iran is higher than the southern and eastern areas of the country. Spatial factors of latitude and altitude reduce bioclimatic uniformity and create small areas with or without thermal comfort conditions. Bioclimatic indicators based on air temperature and relative humidity range of bioclimatic zones show. The results of ET and THI divide the whole country into six zones, from lack of thermal comfort to having thermal comfort conditions. Areas of southern strip as well as central and southeastern parts of the country do not have any human thermal comfort conditions in most of the year.

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References

  • Attorre F, Alfo M, De Sanctis M, Francesconi F, Brun F (2007) Comparison of interpolation methods for mapping climatic and bioclimatic variables at regional scale. Int J Climatol 27(13):1825–1843

    Article  Google Scholar 

  • Ayoade JO (1978) Spatial and seasonal patterns of physiologic comfort in Nigeria. Arch Meteor Geophy B 26(4):319–337

    Article  Google Scholar 

  • Bhowmik AK, Costa AC (2012) A geostatistical approach to the seasonal precipitation effect on Boro rice production in Bangladesh. Int J Geosci 3(03):443–462

  • Çalişkan O, Türkoğlu N, Matzarakis A (2013) The effects of elevation on thermal bioclimatic conditions in Uludağ (Turkey). Atmosfera 26(1):45–57

    Article  Google Scholar 

  • Cetin M (2015) Determining the bioclimatic comfort in Kastamonu City. Environ Monit Assess 187(10):640

    Article  Google Scholar 

  • Daneshvar MRM, Bagherzadeh A, Tavousi T (2013) Assessment of bioclimatic comfort conditions based on physiologically equivalent temperature (PET) using the RayMan model in Iran. Cent Eur J Geosci 5(1):53-60. doi:10.2478/s13533-012-0118-7

    Google Scholar 

  • De Freitas CR, Grigorieva EA (2015) A comprehensive catalogue and classification of human thermal climate indices. Int J Biometeorol 59(1):109–120

    Article  Google Scholar 

  • Demir M, Dindaroglu T, Guven M (2014) The importance of forest lands in terms of bioclimatic comfort: sample of Aras basin. J Hum Ecol 45(1):7–16

    Google Scholar 

  • Eludoyin OM (2014) A perspective of the diurnal aspect of thermal comfort in Nigeria. Atmos Clim Sci 4(04):696

    Google Scholar 

  • Eludoyin OM, Adelekan IO, Webster R, Eludoyin AO (2014) Air temperature, relative humidity, climate regionalization and thermal comfort of Nigeria. Int J Climatol 34(6):2000–2018

    Article  Google Scholar 

  • Emmanuel R (2005) Thermal comfort implications of urbanization in a warm-humid city: the Colombo Metropolitan Region (CMR), Sri Lanka. Build Environ 40(12):1591–1601

    Article  Google Scholar 

  • Givoni B (1963) Mean climate and architecture. Elsevier Press, Amsterdam

    Google Scholar 

  • Hall MR (2010) Materials for energy efficiency and thermal comfort in buildings, first published. Woodhead Publishing Limited and CRP Press LLC, New York

  • Hossienipak EA (2011) Geostatistic. University of Tehran Publisher, Tehran

  • Ishida T, Kawashima S (1993) Use of Cokriging to estimate surface air temperature from elevation. Theor Appl Climatol 47(3):147–157

    Article  Google Scholar 

  • Krivoruchko K (2005) Introduction to modeling spatial processes using geostatistical Analyst. Environmental Systems Research Institute, Redlands. http://www.esri.com/library/whitepapers/pdfs/intro-modeling.pdf. Site last updated September 6, 2005

  • Lee DHK (1965) Climatic stress indices for domestic animals. Int J Biometeorol 9:29–35

    Article  Google Scholar 

  • Lin TP, Matzarakis A (2008) Tourism climate and thermal comfort in Sun Moon Lake, Taiwan. Int J Biometeorol 52(4):281–290

    Article  Google Scholar 

  • Makokha GL (1998) Variations of the effective temperature index (ET) in Kenya. GeoJournal 44(4):337–343

    Article  Google Scholar 

  • Matzarakis A, Mayer H (1997) Heat stress in Greece. Int J Biometeorol 41(1):34–39

  • Mesquita S, Sousa AJ (2009) Bioclimatic mapping using geostatistical approaches application to mainland Portugal. Int J Climatol 29(14):2156–2170

    Article  Google Scholar 

  • Parsons KC (2003) Human thermal environments, the effects of hot, moderate, and cold environments on human health, comfort and performance. Second edition Published by Taylo and Francis, London

  • Pecelj M (2013) Bioclimatic indices based on the menex model example on Banja Luka. Journal of the Geographical Institute Jovan Cvijic, SASA 63(1):1–10

    Article  Google Scholar 

  • Ruiz MA, Correa EN (2015) Suitability of different comfort indices for the prediction of thermal conditions in tree-covered outdoor spaces in arid cities. Theor Appl Climatol 122(1–2):69–83

    Article  Google Scholar 

  • Thompson RD, Perry AH (1997) Applied climatology: principles and practice. Psychology Press

  • Unger J (1999) Comparisons of urban and rural bioclimatological conditions in the case of a Central-European city. Int J Biometeorol 43(3):139–144

    Article  Google Scholar 

  • Zengin M, Kopar I, Karahan F (2010) Determination of bioclimatic comfort in Erzurum–Rize expressway corridor using GIS. Build Environ 45(1):158–164

    Article  Google Scholar 

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Acknowledgments

The authors of the study thereby express their gratitude and appreciation to the Islamic Republic of Iran Meteorological Organization for sharing the data of the meteorological stations under study.

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Correspondence to Hamzeh Ahmadi.

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Ahmadi, H., Ahmadi, F. Mapping thermal comfort in Iran based on geostatistical methods and bioclimatic indices. Arab J Geosci 10, 342 (2017). https://doi.org/10.1007/s12517-017-3129-3

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  • DOI: https://doi.org/10.1007/s12517-017-3129-3

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