Indoor Thermal and Ventilation Indicator on University Students’ Overall Comfort
Autor(en): |
Lin-Rui Jia
Qing-Yun Li Xi Chen Chi-Chung Lee Jie Han |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 27 Oktober 2022, n. 11, v. 12 |
Seite(n): | 1921 |
DOI: | 10.3390/buildings12111921 |
Abstrakt: |
Thermal comfort (TC) and CO2 concentration significantly influence the overall indoor comfort sensations of building occupants. However, few studies have focused on educational buildings regarding both TC and CO2 concentration in tropical regions, and they also lack guidelines for short_term evaluation, which is essential for university classrooms. In this study, a mechanically ventilated university classroom was selected to investigate the 5 min-averaged comfort ranges for indoor parameters and the impacts of TC and variation of CO2 on student overall comfort. The real-time indoor environmental parameters were monitored, including indoor air temperature (Ta), mean radiant temperature (Tm), relative humidity (RH) and CO2 and air velocity (va); the operative temperature (Top) was calculated. Moreover, an online-based questionnaire survey related to thermal sensation (TS) and CO2-related air sensation (AS) was carried out. Linear and nonlinear regression models of comfort sensation predictions were obtained based on the questionnaires and corresponding measured indoor environmental data. The 5 min-averaged comfort ranges for Top, CO2 and RH are 21.5–23.8 °C, <1095 ppm and 47–63.5%, respectively. The comfort range of the TS and AS are 2.3–3.1 and 1–1.55, respectively. The result shows that students prefer a relatively cold indoor environment, as this improves their ability to tolerate bad indoor air quality (IAQ) with high CO2. A regression analysis indicated that AS is the most critical aspect, with a weight of 0.32, followed by TS, with 0.18. Finally, it was also found that individual weighting coefficients were not equivalent and differed across geographical locations and building types. Thus, obtaining the prediction models for a particular building is necessary. The results can give meaningful suggestions to adopt the appropriate operations for HVAC and improve indoor environmental quality in university buildings in tropical regions. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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10700056 - Veröffentlicht am:
10.12.2022 - Geändert am:
10.05.2023