|Title:||Assessment of human thermal comfort during short-term exposure in hot and humid urban outdoor areas|
|Advisors:||Niu, Jianlei (BEEE)|
Mak, Cheuk-ming (BEEE)
Urban ecology (Sociology) -- China -- Hong Kong
Hong Kong Polytechnic University -- Dissertations
|Department:||Department of Building Environment and Energy Engineering|
|Pages:||xviii, 136 pages : color illustrations|
|Abstract:||City residents have to frequently expose themselves to the outdoor environment. For example, people in a living community need to pass through the outdoor areas from home to groceries, restaurants, or subway stations. In daily life, the outdoor space usually acts as a transition area that people enter when moving from one building to another. This outdoor exposure is inevitable and the duration of the exposure is relatively short. For the improvement of residents' comfort and livability and in the urban transitional outdoor areas, it is crucial to carry out assessments on human thermal perceptions and develop appropriate models to predict thermal comfort in the short-term outdoor exposure. The thesis intends to investigate human thermal comfort during short-term (less than 15 minutes) exposure in the hot and humid urban outdoor areas by conducting on-site experiments, including meteorological monitoring and survey. Data acquired from the experiments were analyzed to develop models to predict human thermal sensation and thermal comfort during short-term exposure. Extra field experiments were performed as verification of the regression quality and predicting accuracy of the predicting models.|
The thesis consists of three main sections: 1) The investigation on research subjects' thermal perceptions, including thermal comfort and thermal sensation conditions after a 15-min exposure in several outdoor sites located at a university campus. The experiments were conducted in 23 days from Mar-2016 to Dec-2016. A total number of 1,107 questionnaires were collected. 2) The investigation on research subjects' thermal perceptions, including thermal comfort, thermal sensation and thermal acceptability conditions during a 10-min exposure in two outdoor sites located at a university campus. The experiments were conducted in 14 days from Feb-2018 to Oct-2018. 197 research subjects participated in the repeat experiments and a total number of 1,182 questionnaires were collected in this experiment. 3) The development of TSV and TCV prediction models incorporating the data acquired from the above-mentioned outdoor experiments. Stepwise regressions were conducted to filter the independent variables in predicting TSV and TCV. Multiple linear regression was adopted to determine the impact coefficient of each selected predictor and obtain the final predicting models.
Results indicate that the major meteorological parameters differences that exist between the shaded sites and the sunlit sites are in solar irradiance and air velocity. Statistical analyses show that during both the 10-min exposure and the 15-min exposure, the shaded area are significantly more comfortable than the sunlit area. It is also revealed that respondent thermal perceptions are closely related to the subjects' perceptions of solar radiation and wind speed. Mean Thermal Sensation Vote fitted well respectively with PET or UTCI in linear regressions. A positive relationship existed between Thermal sensation vote and outdoor-indoor meteorological differences and the second-order polynomial regression is suitable for fitting Thermal comfort vote and Thermal acceptability vote with outdoor/indoor environmental differences. Yet additional considerations on the factors that have impacts on the occupants' actual thermal responses should be covered for the enhancement of the predicting accuracy of human thermal perceptions. To improve the predicting model, stepwise regression was employed and four independent variables were finally selected, including PET (or UTCI), indoor/outdoor PET (or UTCI) difference, subjective sunlight level and wind level. The four variables were correlated with TSV and TCV using multiple linear regression to determine the impact coefficients. Subjective sunlight level and wind level were converted into mean radiant temperature and air velocity, respectively according to the corresponding linear regression formulae. Eventually, the TSV and TCV prediction formulae are obtained including four predictors: PET (or UTCI), indoor/outdoor PET (or UTCI) difference, mean radiant temperature and wind velocity, all of which can either be calculated by the meteorological and surveyed data or directly collected from measurements and subject interviews. Predicting accuracies of the 4 predictor models are acceptable (57.9% ~ 72.7% in accuracy) according to the verifications. It is also found that the inclusion of the 3 extra predictors significantly improves the regression quality (0.1 ~ 0.2 in R2) of the predicting models. The predicting accuracies are increased in most cases (+3.6% ~ +14.1%), except that in the TCV predicting model adopting PET and ΔPET as predictors (-4.2%). Thermal perception predicting models adopting UTCI and ΔUTCI as predictors are better in predicting accuracy (+1.1% ~ +7.8%) compared with models adopting PET and ΔPET as predictors.
This thesis comprehensively characterizes the thermal environment and occupants' thermal perception conditions during transitional short-term exposure in different outdoor building geometries located in a hot and humid subtropical city. The study provides abundant experimental data concerning human transient state thermal perceptions in the outdoor areas in the hot and humid subtropical climate. The output of the research can be used to predict subjective thermal perceptions during short-term outdoor exposure in any combinations of environmental parameters and personal details in the subtropical regions. It is also helpful in the development of advanced design tools concerning urban outdoor microclimate, which is believed to be beneficial for developers, city planners and the government in designing a more comfortable and livable urban environment.
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