Evaluating the Impact of Indoor Office Environmental Conditions and Occupants' Demographics on Comfort and Productivity Levels

Abstract

Indoor environmental conditions can have a significant impact on occupants' comfort and productivity, motivating recent research efforts on the topic. A review of the current literature, however, highlights important shortcomings including (1) the limited evaluation of combined effects of environmental metrics (e.g., temperature, light, and noise) on overall comfort levels, (2) the lack of integrated approaches such as combination of both subjective and objective assessment methods, (3) the limited number of studies conducted in actual building environments as opposed to controlled settings, and (4) the rare evaluation of occupants' happiness and productivity levels. This thesis presents a comprehensive data collection and analysis framework to evaluate the impact of office building environment on occupants' comfort and performance. The framework combines various data collection sources such as surveys, performance tests and sensors, as well as data analysis techniques including descriptive analysis, inferential analysis, Spearman's rank correlation, and ordinal logistic regression models. The framework is validated through a case study of three energy efficient buildings in Abu Dhabi, UAE, where data was collected from 206 occupants. Results show that both environmental conditions have significant impacts on how occupants perceive their indoor environment, affecting their overall satisfaction, happiness, and productivity levels. For instance, noise level has a significant impact on the time taken to complete a performance test, while radiant temperature explains the reported thermal sensation levels. In parallel, demographic factors such as gender and age are important determinants of comfort levels. In addition, an integrated post occupancy evaluation application, including building energy modeling and occupant based evaluations, illustrated how the proposed methodology can be applied to minimize energy consumption of buildings while optimizing the comfort and productivity of occupants.

Date of Award	Dec 2017
Original language	American English