AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
A Sensor Network for Multiple Hazards in Heavy-Vehicle Manufacturing
THOMAS PETERS, Sinan Sousan, Alyson Gray, Laura Hallett, Geb Thomas, Xiaoxing Liu, Christopher Zuidema, Kirsten Koehler, University of Iowa
Abstract Number: 580 Working Group: Aerosol Exposure
Abstract Personal exposure sampling is the primary means to ensure that gaseous and aerosol hazards in the workplace are maintained below occupational exposure limits, although few exposures are measured to represent a large working population due to costs and time constraints. A novel sensor network for chemical hazards (aerosols, oxidative gas, and CO) and a physical hazard (noise) was developed and deployed in a heavy-vehicle manufacturing facility over a one-year period. Focusing on aerosol sensing, this presentation reviews development of a wireless monitor that served as individual nodes of the network, laboratory testing of 50 monitors, field validation of monitor performance over time, and spatial and temporal observations from network data. Laboratory tests revealed the need to select aerosol sensors 50 units from 100 based on preliminary data that best matched each other to minimize uncertainties in measurement. Field tests showed that active aerosol sensors (Sharp DN) rapidly became dirty (days to weeks), which caused substantial drift in zero values. Passive samplers (Sharp GP) provided similar information as the active sensors with substantially less zero drift. Comparison of monitor data compared to that from a reference photometer and gravimetric samplers demonstrated the value in performing periodic field verification of sensor performance. Temporal-spatial analysis of network data showed how aerosols move through the facility, enabling identification of key sources and targets for upgrades in controls. This type of network monitoring has potential for dramatically increasing the sample size, even if somewhat less accurate and precise than conventional sampling, upon which important decisions in industrial hygiene practice are made. Such a network may also facilitate medical surveillance and epidemiological study.