The identification of variables influencing personal lighting conditions of office workers

Author:

van Duijnhoven J1ORCID,Aarts MPJ1ORCID,van den Heuvel ER2,Kort HSM34

Affiliation:

1. Building Lighting Group, Department of the Built Environment, Eindhoven University of Technology, Eindhoven, The Netherlands

2. Stochastics, Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

3. Research Centre Healthy and Sustainable Living, University of Applied Sciences Utrecht, Utrecht, The Netherlands

4. Building Healthy Environments for Future Users Group, Department of the Built Environment, Eindhoven University of Technology, Eindhoven, The Netherlands

Abstract

The main reason lighting control is being applied is to reduce energy consumption. However, there are many more reasons for lighting control to be optimised in buildings. Lighting systems can be controlled to enhance or optimise effects beyond vision. Automatic control of electric lighting systems or daylight systems is one way of adjusting someone’s personal lighting conditions. In addition, it is relevant for office workers to know how they can adjust their personal lighting conditions themselves in order to optimise their effects beyond vision (e.g. alertness). Therefore, this article describes a process of identifying predictors that influence personal lighting conditions. The dataset used in this article is gathered during a field study in the Netherlands in spring 2017. This article describes linear mixed models for daily mean illuminances and correlated colour temperatures both throughout the entire day and only at work. These models demonstrated that weather conditions, fixed and flexible personal conditions, office worker’s daily schedule and workspace characteristics influence personal lighting conditions. Weather conditions and fixed and flexible personal conditions though are difficult or impossible to control by the office workers themselves. However, adjustments in personal lighting conditions can be accomplished by the office workers themselves by changing their daily schedules and the workspace characteristics. The findings show that these two predictor categories may explain 4% to 20% of the variance in personal lighting conditions.

Publisher

SAGE Publications

Subject

Electrical and Electronic Engineering

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