In a psychophysical forced-choice experiment, observers’ ability to detect illuminance differences was found to be 7.4% of the initial illuminance. When matching the illuminance of one space with another, observers’ acceptance of illuminance differences was 17.8% to 19.1%. Lighting control systems with resolutions between 14.8% and 17.7% were found to have greater usability than others. A new approach to step-dimming leverages knowledge of the detectability and acceptability of illuminance differences, as well as usability, to reduce lighting energy consumption. This method can reduce lighting energy consumption more than continuous dimming.
Lighting consumes significant energy in buildings, but current measurements of lighting efficiency are inadequate in capturing the spatial and temporal effectiveness of light. The most widely used lighting energy efficiency measure, luminous efficacy, quantifies the amount of light generated by individual light sources. While luminous efficacy provides manufacturers and designers with a useful metric for quantifying the energy efficiency of individual lighting devices, it does not fully address the use of lighting in architectural spaces. Instead, application efficacy, the relationship between the electrical power consumed by lighting hardware and the amount of light that contributes to the visual perception of building occupants, must be measured. Here, we propose a framework for calculating lighting application efficacy (LAE) based on the primary pathway of light in architectural settings: the generation and emission of light from a luminaire, the travel of the light throughout the space and into occupants’ eyes, and the process of visual perception. The LAE framework will include the development of computational methods for estimating the proportion of emitted light that is directed to task areas and areas corresponding to occupants’ visual fields using ray-tracing lighting design software. Future modeling and validation work will quantify energy efficiency of buildings.
Light therapy is used to treat sleep and circadian rhythm disorders, yet there are limited studies on whether light therapy impacts electroencephalographic (EEG) activity during sleep. Therefore, we aimed to provide an overview of research studies that examined the effects of light therapy on sleep macro- and micro-architecture in populations with sleep and circadian rhythm disorders. We searched for randomized controlled trials that used light therapy and included EEG sleep measures using MEDLINE, PubMed, CINAHL, PsycINFO and Cochrane Central Register of Controlled Trials databases. Five articles met the inclusion criteria of patients with either insomnia or delayed sleep–wake phase disorder (DSWPD). These trials reported sleep macro-architecture outcomes using EEG or polysomnography. Three insomnia trials showed no effect of the timing or intensity of light therapy on total sleep time, wake after sleep onset, sleep efficiency and sleep stage duration compared to controls. Only one insomnia trial reported significantly higher sleep efficiency after evening light therapy (>4000 lx between 21:00–23:00 h) compared with afternoon light therapy (>4000 lx between 15:00–17:00 h). In the only DSWPD trial, six multiple sleep latency tests were conducted across the day (09:00 and 19:00 h) and bright light (2500 lx) significantly lengthened sleep latency in the morning (09:00 and 11:00 h) compared to control light (300 lx). None of the five trials reported any sleep micro-architecture measures. Overall, there was limited research about the effect of light therapy on EEG sleep measures, and studies were confined to patients with insomnia and DSWPD only. More research is needed to better understand whether lighting interventions in clinical populations affect sleep macro- and micro-architecture and objective sleep timing and quality.
Light that enters humans’ eyes and impacts circadian rhythms may come from various sources, including the sun, electric lighting systems, and self-luminous displays. Occupants’ activities strongly impact the light entering their eyes, which is difficult to predict and not yet well understood. This study investigated the circadian contributions of light from different sources in real building environments to better understand the variables that influence the circadian health of occupants. Spectral irradiance distributions at a position equivalent to the front of an eye of a seated occupant in various interior office spaces were collected. Daylight and electric light were measured separately, and light emitted from displays was measured when a variety of different computer tasks was performed. Circadian stimulus (CS) and α-opic irradiance, defined by CIE DIS026/E:2018, were further calculated, and the circadian effects of light from different sources were compared. The results show that daylight has the greatest circadian effect, while electric light in spaces that were predominantly designed with conventional downward lighting has a very limited impact. The circadian effect of light from screens was considerably high. The outcomes suggest that, to optimise the circadian effects of light, connected lighting systems are needed to control light from different sources.