Natural lighting, Lighting systems, Daylight factor, Solar radiation, Sunlighting, Spaced, Illuminance, Formulae (mathematics), Distribution functions, Mathematical calculations, Bibliography

Sunlight profoundly influences the Earth's atmosphere and biosphere. Nature fuels the evolution of all living things, their visual systems, and the manner in which they adapt, accommodate, and habituate. Sun luminance measurements serve as data to calculate typical changes in the daily, monthly, and annual variability characteristics of daylight. Climate-based sky luminance patterns are used as models in predicting daylighting calculation and computer programs applied in architecture and building design. Historically, daylight science and daylighting technology has prioritized photometric methods of measurements, calculation, and graphical tools aimed at predicting or evaluating the daylighting of architectural design alternatives. However, due to a heightened awareness of general health and well-being, sunlight exposure and freedom from visual discomfort while undertaking visual tasks are now equally prioritized. Therefore, in order to assure optimal environmental quality, daylighting technology must be based on sound science. Daylight Science and Daylighting Technology, by Richard Kittler, Miroslav Kocifaj, and Stanislav Darula, sketches the entire evolution of daylight science from atmospheric science through apt visual workplace psychophysics.

The cost of operating a building far exceeds the cost of constructing it, and yet until recently little attention was paid to the impact of solar radiation on the costs of heating, cooling and ventilation. And now that there has been a surge in interest in energy efficiency and solar design, architects and designers need a practical guide to the modelling and application of solar energy data. There are many different models and techniques available for calculating the distribution of solar radiation on and in buildings, and these algorithms vary considerably in scope, accuracy and complexity. This book demonstrates which of these predictive tools gives the best results in different circumstances, including explaining which models can be best used in different parts of the world. The author has had over twenty-five years of experience of dealing with solar energy data from four continents and has used that experience in this book to show the development not just of knowledge but also the growing sophistication of the models available to apply it.