Simulation methods and data collection for assessing non-image forming light levels and quantifiable impacts on building occupants

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Most lighting building performance analysis focuses on meeting horizontal workplane illuminance standards and reducing the need for electric lighting through daylight. Research in medical and lighting literature has shown that newly discovered photoreceptors in the eye are sensitive to different wavelengths of light than the visual system, and these help entrain our circadian system to a 24-hour period based on light exposure-its timing, duration, and color. The circadian system is responsible for the onset of sleep, alertness throughout the day, key aspects of physiology and metabolism, and the timing of hormone secretion. Poor circadian entrainment can result in increased cancer risk and metabolic problems. The light response of the circadian system and its effects on the human body are therefore referred to as non-image forming (NIF). NIF lighting analysis has spawned new building performance standards, simulation tools, and early research on how building performance analysis can measurably improve the alertness, productivity and health of building occupants. This research seeks to radically advance the science of NIF lighting analysis. Careful analysis of the background architectural performance and medical literature on NIF lighting has identified four shortcomings that will be addressed through new fundamental research in this proposal: (1) material reflection and transmission properties are poorly represented in NIF lighting calculations; (2) occupant NIF light exposure is a complex and unknown combination of outdoor transit, electric lighting, daylighting, and use of screen devices; (3) current simulation tools cannot account for many dynamically varying light sources changing in color and intensity throughout the day; and (4) current NIF lighting analysis does not model the impact of light on occupants directly. Four experimental phases will be carried out to address these identified shortcomings. Statistical analysis of new physical measurements will quantify material properties in NIF lighting simulations. Data collection using new NIF light sensors and survey-based methods will be used to define occupant archetypes regarding sleep quality and light history necessary to calculate the effects of light on human physiology. A new simulation and data management toolkit will be developed to account for interactions of multiple light signals under varying climate, building operational, and occupant circumstances. Finally, new mathematical models of NIF lighting's impacts on physiology will be implemented and validated. Through implementing new NIF lighting analysis methods and software tools in the field of building performance simulation, this research will enable new NIF lighting design methods and metrics that focus on better lighting in buildings and the built environment to improve alertness, productivity and health.