PNNL

Abstract

Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta-analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision-making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to show the aggregate trends between the selected IEQ metrics and improvement to task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high-performance range, while the regression model for noise level was inconclusive. This novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema. This work contributes to broader literature by producing IEQ-based performance gains that can directly inform cost-benefit analyses of building design and renovation.