Field study on thermal comfort of naturally ventilated residences in southwest China

Di Mou , Bin Cao , Ying-xin Zhu

Journal of Central South University ›› 2022, Vol. 29 ›› Issue (7) : 2377 -2387.

PDF
Journal of Central South University ›› 2022, Vol. 29 ›› Issue (7) : 2377 -2387. DOI: 10.1007/s11771-022-5109-3
Building Thermal Environment and Energy Conservation

Field study on thermal comfort of naturally ventilated residences in southwest China

Author information +
History +
PDF

Abstract

Kunming, a city in southwest China, has a climate that is different from most of the other places in the world because of its unique geographical characteristics. Due to its temperate climate, most of the residential buildings in this region are naturally ventilated. Accordingly, a winter thermal comfort study was conducted in Kunming to reveal the thermal response of residents. Indoor and outdoor environmental parameters were measured, and participants were investigated about their clothing, thermal sensations, thermal preferences, and thermal acceptance using online questionnaires. Data from 162 valid questionnaires were collected in the survey. Although the climate is referred to as “mild”, the survey showed that the indoor temperature during winter was lower than the typical comfort range. Nevertheless, the participants responded that most of them felt neutral and comfortable. The neutral temperature of participants living in Kunming was determined to be 16.96 °C. The acceptable thermal sensation vote (TSV) range of the residents is −0.72 to 1.52. The acceptable indoor air temperature range is 15.03 °C to 19.55 °C, and the optimum indoor air temperature is 17.2 °C. According to this study, the existing thermal comfort evaluation models can hardly predict residents’ thermal responses in Kunming well.

Keywords

thermal comfort / field study / thermal adaptation / mild climate / natural ventilation

Cite this article

Download citation ▾
Di Mou, Bin Cao, Ying-xin Zhu. Field study on thermal comfort of naturally ventilated residences in southwest China. Journal of Central South University, 2022, 29(7): 2377-2387 DOI:10.1007/s11771-022-5109-3

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

LuoM, JiW, CaoB, et al.. Indoor climate and thermal physiological adaptation: Evidences from migrants with different cold indoor exposures [J]. Building and Environment, 2016, 98: 30-38

[2]

HoytT, ArensE, ZhangH. Extending air temperature setpoints: Simulated energy savings and design considerations for new and retrofit buildings [J]. Building and Environment, 2015, 88: 89-96

[3]

FangerP OThermal comfort. Analysis and applications in environmental engineering [M], 1970, Copenhagen, Danish Technical Press

[4]

YuJ, OuyangQ, ZhuY, et al.. A comparison of the thermal adaptability of people accustomed to air-conditioned environments and naturally ventilated environments [J]. Indoor Air, 2012, 22(2): 110-118

[5]

YuJ, CaoG, CuiW, et al.. People who live in a cold climate: Thermal adaptation differences based on availability of heating [J]. Indoor Air, 2013, 23(4): 303-310

[6]

LuoM, CaoB, OuyangQ, et al.. Indoor human thermal adaptation: Dynamic processes and weighting factors [J]. Indoor Air, 2017, 27(2): 273-281

[7]

LinY, YangL, LuoM. Physiological and subjective thermal responses to heat exposure in northern and southern Chinese people [J]. Building Simulation, 2021, 14(6): 1619-1631

[8]

de DearR, BragerG. Developing an adaptive model of thermal comfort and preference [J]. ASHRAE Transactions, 1998, 1041: 1-18

[9]

Földvary LičinaV F, CheungT, ZhangH, et al.. Development of the ashrae global thermal comfort database II [J]. Building and Environment, 2018, 142: 502-512

[10]

KottekM, GrieserJ, BeckC, et al.. World map of the Köppen-Geiger climate classification updated [J]. Meteorologische Zeitschrift, 2006, 15(3): 259-263

[11]

Survey Office of the National Bureau of Statistics in YunnanYunnan survey yearbook [M], 2020, Beijing, China Statistics Press(in Chinese)

[12]

Department of Household SurveysNational Bureau of Statistics of ChinaChina yearbook of household survey [M], 2020, Beijing, China Statistics Press(in Chinese)

[13]

CaoB, ZhuY, LiM, et al.. Individual and district heating: A comparison of residential heating modes with an analysis of adaptive thermal comfort [J]. Energy and Buildings, 2014, 78: 17-24

[14]

HumphreysM, NicolF, RoafSAdaptive thermal comfort: Foundations and analysis [M], 2015, London, Routledge

[15]

R Core TeamR: A language and environment for statistical computing [M], 2021, Vienna, Austria, R Foundation for Statistical Computing

[16]

VenablesW N, RipleyB DModern applied statistics with S [M], 2002, New York, NY, Springer

[17]

ASHRAEANSI/ASHRAE standard 55-2017. Thermal environmental conditions for human occupancy [S], 2017, Atlanta, G A, USA, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.

[18]

NewshamG R. Clothing as a thermal comfort moderator and the effect on energy consumption [J]. Energy and Buildings, 1997, 26(3): 283-291

[19]

SchweikerM, AndréM, Al-AtrashF, et al.. Evaluating assumptions of scales for subjective assessment of thermal environments—Do laypersons perceive them the way, we researchers believe? [J]. Energy and Buildings, 2020, 211: 109761

[20]

de DearR, BragerG S. The adaptive model of thermal comfort and energy conservation in the built environment [J]. International Journal of Biometeorology, 2001, 45(2): 100-108

[21]

YangL, YangQ, WangL, et al.. Research on adaptive thermal comfort model for temperate area [C]. Building Environment-Science & Technology, 2010, Nanjing, China, Southeast University Press, 213-217

[22]

KumarS, MathurJ, MathurS, et al.. An adaptive approach to define thermal comfort zones on psychrometric chart for naturally ventilated buildings in composite climate of India [J]. Building and Environment, 2016, 109: 135-153

[23]

KumarS, SinghM K, LoftnessV, et al.. Thermal comfort assessment and characteristics of occupant’s behaviour in naturally ventilated buildings in composite climate of India [J]. Energy for Sustainable Development, 2016, 33: 108-121

[24]

SinghM K, MahapatraS, AtreyaS K. Adaptive thermal comfort model for different climatic zones of North-East India [J]. Applied Energy, 2011, 88(7): 2420-2428

[25]

BragerG S, PaliagaG, de DearR, et al.. Operable windows, personal control, and occupant comfort [J]. ASHRAE Transactions, 2004, 110: 17-35

AI Summary AI Mindmap
PDF

163

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/