Literature DB >> 29683781

Laboratory evaluation of a low-cost, real-time, aerosol multi-sensor.

Robert J Vercellino1, Darrah K Sleeth1, Rodney G Handy1, Kyeong T Min2, Scott C Collingwood3.   

Abstract

Exposure to occupational aerosols are a known hazard in many industry sectors and can be a risk factor for several respiratory diseases. In this study, a laboratory evaluation of low-cost aerosol sensors, the Dylos DC1700 and a modified Dylos known as the Utah Modified Dylos Sensor (UMDS), was performed to assess the sensors' efficiency in sampling respirable and inhalable dust at high concentrations, which are most common in occupational settings. Dust concentrations were measured in a low-speed wind tunnel with 3 UMDSs, collocated with an aerosol spectrometer (Grimm 1.109) and gravimetric respirable and inhalable samplers. A total of 10 tests consisting of 5 different concentrations and 2 test aerosols, Arizona road dust and aluminum oxide, were conducted. For the Arizona road dust, total particle count was strongly related between the spectrometer and the UMDS with a coefficient of determination (R2) between 0.86-0.92. Particle count concentrations measured with the UMDS were converted to mass and also were related with gravimetrically collected inhalable and respirable dust. The UMDS small bin (i.e., all particles) compared to the inhalable sampler yielded an R2 of 0.86-0.92, and the large bin subtracted from the small bin (i.e., only the smallest particles) compared to the respirable sampler yielded an R2 of 0.93-0.997. Tests with the aluminum oxide demonstrated a substantially lower relationship across all comparisons. Furthermore, assessment of intra-instrument variability was consistent for all instruments, but inter-instrument variability indicated that each instrument requires its own calibration equation to yield accurate exposure estimates. Overall, it appears that the UMDS can be used as a low-cost tool to estimate respirable and inhalable concentrations found in many workplaces. Future studies will focus on deployment of a UMDS network in an occupational setting.

Entities:  

Keywords:  Dust; real-time detection systems; sensor technologies

Mesh:

Substances:

Year:  2018        PMID: 29683781      PMCID: PMC6309410          DOI: 10.1080/15459624.2018.1468565

Source DB:  PubMed          Journal:  J Occup Environ Hyg        ISSN: 1545-9624            Impact factor:   2.155


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