Abstract
Personal exposure to volatile organic compounds (VOCs) from indoor sources including consumer products is an understudied public health concern. To develop and evaluate methods for monitoring personal VOC exposures, we performed a pilot study and examined time-resolved sensor-based measurements of geocoded total VOC (TVOC) exposures across individuals and microenvironments (MEs). We integrated continuous (1 min) data from a personal TVOC sensor and a global positioning system (GPS) logger, with a GPS-based ME classification model, to determine TVOC exposures in four MEs, including indoors at home (Home-In), indoors at other buildings (Other-In), inside vehicles (In-Vehicle), and outdoors (Out), across 45 participant-days for five participants. To help identify places with large emission sources, we identified high-exposure events (HEEs; TVOC > 500 ppb) using geocoded TVOC time-course data overlaid on Google Earth maps. Across the 45 participant-days, the MEs ranked from highest to lowest median TVOC were: Home-In (165 ppb), Other-In (86 ppb), In-Vehicle (52 ppb), and Out (46 ppb). For the two participants living in single-family houses with attached garages, the median exposures for Home-In were substantially higher (209, 416 ppb) than the three participant homes without attached garages: one living in a single-family house (129 ppb), and two living in apartments (38, 60 ppb). The daily average Home-In exposures exceeded the estimated Leadership in Energy and Environmental Design (LEED) building guideline of 108 ppb for 60% of the participant-days. We identified 94 HEEs across all participant-days, and 67% of the corresponding peak levels exceeded 1000 ppb. The MEs ranked from the highest to the lowest number of HEEs were: Home-In (60), Other-In (13), In-Vehicle (12), and Out (9). For Other-In and Out, most HEEs occurred indoors at fast food restaurants and retail stores, and outdoors in parking lots, respectively. For Home-In HEEs, the median TVOC emission and removal rates were 5.4 g h−1 and 1.1 h−1, respectively. Our study demonstrates the ability to determine individual sensor-based time-resolved TVOC exposures in different MEs, in support of identifying potential sources and exposure factors that can inform exposure mitigation strategies.
Highlights
Volatile organic compounds (VOCs) are released to the indoor air from a broad range of building materials, volatile chemical products, and activities; and released to the outdoor air from mobile and stationary sources [1,2,3]
Are medians, whiskers are minimum and maximum values. These results show that homes with attached garages had higher medi els and lower median Air Exchange Rates (AER), as compared to homes without attached garage sistent with previous studies that show homes with attached garages ofte indoor total VOC (TVOC) levels [1]
The TVOC exposures were used to identify ME-specific high-exposure events (HEEs) and estimate TVOC emission and removal rates for Home-In HEEs. These results demonstrate the feasibility of using time-resolved personal air pollution sensor data with geolocation data (e.g., global positioning system (GPS), smartphones) and MicroTrac to determine ME-specific exposures, in support of identifying potential sources and exposure factors to develop and evaluate exposure mitigation strategies
Summary
Volatile organic compounds (VOCs) are released to the indoor air from a broad range of building materials, volatile chemical products (e.g., cleaning agents, personal care products), and activities (e.g., cooking); and released to the outdoor air from mobile and stationary sources (e.g., vehicles, gas stations) [1,2,3]. VOC exposures can occur in various indoor microenvironments (MEs) (e.g., residences, work, stores, restaurants), outdoor locations (e.g., parking lots, gas stations), and inside vehicles. We examined VOC exposures in multiple MEs based on time-resolved personal sensor measurements integrated with global positioning system (GPS) data. Manual processing of geocoded data to determine time spent in different MEs is limited due to several challenges, including large, multidimensional (time, location, speed) data, and difficulty discriminating between different MEs (e.g., indoors and outdoors). To address this limitation, we previously developed and evaluated a GPS-based ME classification model (MicroTrac) [7]. We applied MicroTrac to create time-resolved ME-specific VOC exposures
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