期刊
BUILDING AND ENVIRONMENT
卷 194, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2021.107689
关键词
Climate-based daylight metrics; Daylight satisfaction; Lighting comfort; Tropical climates
资金
- Singapore Building Construction Authority (BCA), Green Building Innovation Cluster (GBIC) Research and Development Grant [GBIC-RD/DCP 05]
The study found that gender, eyewear, and access to exterior views have impacts on subjective lighting assessments. Compared to other climate-based daylight metrics, UDI-fellshort and UDI-supplementary associated with Ev outperform in predicting satisfaction with annual access to daylight in this study.
This paper presents a study that investigates lighting qualities within three computer labs from a long-term perspective. Subjective assessments from 173 participants were collected. Accurately calibrated simulation models of three computer labs were generated to simulate annual lighting quantities based on horizontal illuminance (Eh), vertical illuminance (Ev) and monitor illuminance (Em). Gender, eyewear and access to exterior views have impacts on subjective long-term lighting assessments. Due to the low daylighting distributions, climate-based daylight metrics (CBDM) with the thresholds over 300 lx, including daylight autonomy (DA) 300 lx and 500 lx, Useful Daylight Illuminances (UDI) autonomous (UDI300?3000 lx), UDI-exceeded (UID 3000 lx) and Annual Sunlight Exposure (ASE) over 1000 lx (ASE1000 lx), are inapplicable in the context of this study. UDI-fellshort (UDI <100 lx) and UDI-supplementary (UDI100?300 lx) associated with Ev outperform other CBDMs in terms of predicting subjective satisfaction with annual access to daylight. In addition to Eh- and Ev-based annual lighting predictors, Em-based ones are practically correlated with subjective lighting assessments. However, contradictory correlations and logistic regression models between Em-based lighting predictors and subjective lighting assessments are found across the daylit computer lab and electrically lit computer labs, which emphasizes the importance of differentiating Em-based lighting predictors according to monitor type, lighting sources and classroom arrangement.
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