Proxy methods for detection of inhalation exposure in simulated office environments

Background Modern health concerns related to air pollutant exposure in buildings have been exacerbated owing to several factors. Methods for assessing inhalation exposures indoors have been restricted to stationary air pollution measurements, typically assuming steady-state conditions. Objective We aimed to examine the feasibility of several proxy methods for estimating inhalation exposure to CO 2 , PM 2.5 , and PM 10 in simulated office environments. Methods In a controlled climate chamber mimicking four different office setups, human participants performed a set of scripted sitting and standing office activities. Three proxy sensing techniques were examined: stationary indoor air quality (IAQ) monitoring, individual monitoring of physiological status by wearable wristband, human presence detection by Passive Infrared (PIR) sensors. A ground-truth of occupancy was obtained from video recordings of network cameras. The results were compared with the concurrent IAQ measurements in the breathing zone of a reference participant by means of multiple linear regression (MLR) analysis with a combination of different input parameters. Results Segregating data onto sitting and standing activities could lead to improved accuracy of exposure estimation model for CO 2 and PM by 9–60% during sitting activities, relative to combined activities. Stationary PM 2.5 and PM 10 monitors positioned at the ceiling-mounted ventilation exhaust in vicinity of the seated reference participant accurately estimated inhalation exposure (adjusted R ² = 0.91 and R ² = 0.87). Measurement at the front edge of the desk near abdomen showed a moderate accuracy (adjusted R ² = 0.58) in estimating exposure to CO 2 . Combining different sensing techniques improved the CO 2 exposure detection by twofold, whereas the improvement for PM exposure detection was small (~10%). Significance This study contributes to broadening the knowledge of proxy methods for personal exposure estimation under dynamic occupancy profiles. The study recommendations on optimal monitor combination and placement could help stakeholders better understand spatial air pollutant gradients indoors which can ultimately improve control of IAQ.