Journal article
Estimating personal exposures from a multi-hazard sensor network
Journal of exposure science & environmental epidemiology, Vol.30(6), pp.1013-1022
11/2020
DOI: 10.1038/s41370-019-0146-1
PMCID: PMC6891140
PMID: 31164703
Abstract
Occupational exposure assessment is almost exclusively accomplished with personal sampling. However, personal sampling can be burdensome and suffers from low sample sizes, resulting in inadequately characterized workplace exposures. Sensor networks offer the opportunity to measure occupational hazards with a high degree of spatiotemporal resolution. Here, we demonstrate an approach to estimate personal exposure to respirable particulate matter (PM), carbon monoxide (CO), ozone (O\n), and noise using hazard data from a sensor network. We simulated stationary and mobile employees that work at the study site, a heavy-vehicle manufacturing facility. Network-derived exposure estimates compared favorably to measurements taken with a suite of personal direct-reading instruments (DRIs) deployed to mimic personal sampling but varied by hazard and type of employee. The root mean square error (RMSE) between network-derived exposure estimates and personal DRI measurements for mobile employees was 0.15 mg/m\n, 1 ppm, 82 ppb, and 3 dBA for PM, CO, O\n, and noise, respectively. Pearson correlation between network-derived exposure estimates and DRI measurements ranged from 0.39 (noise for mobile employees) to 0.75 (noise for stationary employees). Despite the error observed estimating personal exposure to occupational hazards it holds promise as an additional tool to be used with traditional personal sampling due to the ability to frequently and easily collect exposure information on many employees.
Details
- Title: Subtitle
- Estimating personal exposures from a multi-hazard sensor network
- Creators
- Christopher Zuidema - Department of Occupational and Environmental Health Sciences, University of Washington School of Public Health, Seattle, USALarissa V Stebounova - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USASinan Sousan - North Carolina Agromedicine Institute, Greenville, NC, USAAlyson Gray - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USAOliver Stroh - Department of Industrial and Systems Engineering, University of Iowa, Iowa City, IA, USAGeb Thomas - Department of Industrial and Systems Engineering, University of Iowa, Iowa City, IA, USAThomas Peters - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA, USAKirsten Koehler - Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. kirsten.koehler@jhu.edu
- Resource Type
- Journal article
- Publication Details
- Journal of exposure science & environmental epidemiology, Vol.30(6), pp.1013-1022
- DOI
- 10.1038/s41370-019-0146-1
- PMID
- 31164703
- PMCID
- PMC6891140
- NLM abbreviation
- J Expo Sci Environ Epidemiol
- ISSN
- 1559-0631
- eISSN
- 1559-064X
- Publisher
- United States
- Grant note
- T42 OH008428 / NIOSH CDC HHS\nR01 OH010533 / NIOSH CDC HHS\nT32 ES015459 / NIEHS NIH HHS
- Language
- English
- Date published
- 11/2020
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Occupational and Environmental Health; Orthopedics and Rehabilitation; Industrial and Systems Engineering
- Record Identifier
- 9984066107002771
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