Impacts of Dynamic LED Lighting on the Well-Being and Experience of Office Occupants
Abstract
:1. Introduction
2. Study Design and Methods
2.1. Overall Study Design
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- 2 static lighting conditions that represent typical lighting settings of Japanese (JP) and U.S. offices (i.e., JP-T and US-T conditions);
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- 2 dynamic lighting conditions with varying lighting CCT and illuminance (i.e., JP-D and US-D conditions);
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- 2 weeks were assigned as the acclimation period at the beginning of this study;
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- 1 additional week was assigned to handle the sleep/wake schedule changes due to daylight savings time.
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- Condition 1 (JP-T) represented typical lighting conditions in Japanese offices, i.e., 500 lux/5000 K at the horizontal desk level.
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- Condition 2 (JP-D) was the dynamic lighting profile for Japanese offices. It varied in reasonable Japanese lighting ranges, i.e., the illuminance falls between 500 and 700 lux and CCT falls between 3500 and 6000 K.
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- Condition 3 (US-T) represented typical lighting conditions in US offices, i.e., 300 lux/4000 K.
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- Condition 4 (US-D) was the dynamic lighting profile for U.S. offices. It varied in reasonable U.S. lighting ranges, i.e., the illuminance falls between 300 and 500 lux and CCT falls between 3000 and 5000 K.
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- Dynamic lighting profiles (i.e., JP-D and US-D) presented increased illuminance and CCT levels in the morning compared to the corresponding static lighting level.
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- Dynamic lighting profiles presented gradually decreased illuminance and CCT levels in the afternoon to mimic the natural daylighting variations
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- JP-D and US-D shared the same magnitude in illuminance variation, i.e., to present a constant shift between them over time
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- JP-D and US-D shared the same CCT variation trends that can create similar recognized color change over time.
2.2. Office Configuration
2.3. Lighting System Design
2.4. Participants
2.4.1. Participant Exclusion Criteria
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- diagnosed sleep disorders,
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- severe vision problems,
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- sensitivity to light resulting in headaches or seizures,
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- cognitive abilities interfering with typical office work,
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- physical disabilities interfering with typical office work,
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- severe mood disorders, and
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- drug or alcohol dependency.
2.4.2. Demographic Information
2.4.3. Chronotype
2.5. Environmental Measurement Methods
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- Lighting environment: wireless real-time sensors (Lux1000 and Color Lux1000, Wovyn LLC, Heber City, UT, USA) were deployed at the horizontal desk surfaces and vertical window surfaces to measure the illuminance and CCT.
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- Thermal environment: wireless real-time sensors (Monnit Corp., South Salt Lake, UT, USA) were deployed at each desk to measure the thermal environmental parameters that may affect occupant performance and satisfaction, including temperature, relative humidity, and radiant temperature.
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- Acoustic environment: a real-time acoustic analyzer (XL2 audio and acoustic analyzer with M2211 microphone, NTi Audio Inc., Schaan, Liechtenstein) was deployed to measure the equivalent sound level for acoustic evaluations.
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- Indoor air quality: measure the module-level ventilation rates for indoor air quality evaluations.
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- Building operations: measure operational parameters of the building system, including the shades operation and electrochromic glass control.
2.6. Behavioral Outcome Measurement Methods
2.6.1. Stress
- Objective physiological measurements
- Daily subjective stress measurement
- Monthly subjective stress measurement
2.6.2. Sleep and Circadian Rhythms
- Objective real-time sleep tracking
- Daily subjective measurement—sleep diary
- Daily subjective measurement—alertness
- Monthly sleep quality measurement
2.6.3. Productivity
2.6.4. Secondary and Exploratory Outcomes
- Satisfaction
- Visual comfort
- Mood
- Naturalness
2.7. Statistical Analysis Method
3. Lighting Configuration and Environmental Data Analysis Results
3.1. Evaluation of the Lighting Settings for This Study
3.2. Analysis of the Actual Lighting Environment during This Study
3.2.1. Temporal Illuminance Variations
3.2.2. Temporal Lighting Correlated Color Temperature Variations
3.3. Theoretical Quantification of the Non-Visual Impact of the Dynamic Lighting
3.3.1. Lighting Property Data Analysis
3.3.2. Non-Visual Impact Estimation and Analysis
3.4. Evaluation of Indoor Non-Lighting Environment and System Operations
4. Behavioral Data Analysis Results
4.1. Mental Stress Analysis
4.1.1. Subjective Stress Analysis
4.1.2. Objective Stress Analysis
4.2. Sleep Analysis
4.2.1. Perceived Sleep Quality
- Daily sleep quality
- Monthly sleep quality
4.2.2. Nighttime Sleep Analysis
- Total sleep time
- Sleep onset
- Time in deep sleep
- Time in light sleep
- Other sleep parameters
4.2.3. Alertness—Perceived Feeling of Sleepiness during Daytime
4.3. Productivity Analysis
4.4. Secondary Measures Analysis
4.4.1. Satisfaction
- Satisfaction with lighting
- Satisfaction with other environmental parameters
4.4.2. Visual Comfort
4.4.3. Mood Analysis
- Positive affect
- Negative affect
4.4.4. Perceived Naturalness of the Light
5. Discussions
5.1. Daytime Impacts
5.2. Nighttime Impacts
5.3. Recommendations for Future Studies
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Race | Number |
White | 12 |
Hispanic or Latino | 2 |
Asian | 1 |
Income | Number |
Less than $10,000 | 1 |
$35,000 to less than $50,000 | 1 |
$50,000 to less than $75,000 | 4 |
$75,000 or more | 7 |
Preferred not to answer | 2 |
Education | Number |
Some college or technical school | 4 |
College graduate | 11 |
Chronotype (Morning–Eveningness Questionnaire) | Number |
Definite morning | 1 |
Moderate morning | 5 |
Intermediate | 8 |
Moderate evening | 1 |
Definite evening | 0 |
Baseline Sleep and Stress Measures | Average (SD) |
Sleep Quality (Pittsburgh Sleep Quality Index) | 5.33 (2.69) |
Perceived Stress Scale | 25.73 (6.94) |
Job Stress Scale | 12.13 (3.78) |
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Share and Cite
Zhang, R.; Campanella, C.; Aristizabal, S.; Jamrozik, A.; Zhao, J.; Porter, P.; Ly, S.; Bauer, B.A. Impacts of Dynamic LED Lighting on the Well-Being and Experience of Office Occupants. Int. J. Environ. Res. Public Health 2020, 17, 7217. https://doi.org/10.3390/ijerph17197217
Zhang R, Campanella C, Aristizabal S, Jamrozik A, Zhao J, Porter P, Ly S, Bauer BA. Impacts of Dynamic LED Lighting on the Well-Being and Experience of Office Occupants. International Journal of Environmental Research and Public Health. 2020; 17(19):7217. https://doi.org/10.3390/ijerph17197217
Chicago/Turabian StyleZhang, Rongpeng, Carolina Campanella, Sara Aristizabal, Anja Jamrozik, Jie Zhao, Paige Porter, Shaun Ly, and Brent A. Bauer. 2020. "Impacts of Dynamic LED Lighting on the Well-Being and Experience of Office Occupants" International Journal of Environmental Research and Public Health 17, no. 19: 7217. https://doi.org/10.3390/ijerph17197217