Thesis
Performance of low-cost optical particle counters over time in high dust environments
University of Iowa
Master of Science (MS), University of Iowa
Spring 2022
DOI: 10.17077/etd.006386
Abstract
Inhaling occupational aerosols can cause adverse health effects such as asthma, lung cancer, and other lung diseases. It is critical to monitor workplace aerosol concentrations to prevent adverse health effects. Low-cost sensors are a type of direct reading instrument that can be used to measure aerosols. They are inexpensive, lightweight, and provide rapid results. These attributes open many possibilities for rapidly measuring aerosols in the workplace. Higher concentrations of dust sometimes found in the workplace can accumulate within the sensor and lead to inaccurate aerosol readings. Consequently, it is important to understand if and how rapidly dust accumulation affects output from low-cost aerosol sensors so that valid measurements can be obtained in the workplace.
The purpose of this study was to determine (1) if dust accumulation affects the performance of two types of low-cost particulate matter sensors (Plantower PMS7003 and Sensirion SPS30) in simulated occupational environments over time, and (2) whether the automatic fan-cleaning procedure of the Sensirion SPS30 prevents dust accumulation from degrading sensor performance. Four Plantower PMS7003 sensors, four Sensirion SPS30 sensors, and four pDR-1500 photometers were exposed to sodium chloride at concentrations ranging around ~3 mg/m3, and Arizona Road Dust at target concentrations. Coefficients of variation were calculated to assess the precision of low-cost sensors, and bias was calculated to determine how well the low-cost sensors agreed with the reference instrument (pDR-1500). A t-test was completed to determine if mean mass concentrations were significantly different from SPS30 sensors with fan-cleaning features on and fan-cleaning features off.
Study results found that sensor performance did not decrease over time when exposed to target concentrations (3 mg/m3) of Arizona road dust. Although the mean differences between SPS30 sensors with fan-cleaning features on and fan-cleaning features off were statistically significant, p<0.001, the differences between groups was negligible in relation to effect size. There many have not been enough dust accumulation to assess the SPS30 fan-cleaning feature. From these data we conclude low-cost optical particle counters may be an effective instrument to use in occupational environments to measure high aerosol concentrations. Future research should test these low-cost sensors in environments with higher concentrations than those measured in this study, to determine if their performance decreases over time. Future work should also investigate the orientation of sensors when deployed as a means of combating internal dust accumulation.
Details
- Title: Subtitle
- Performance of low-cost optical particle counters over time in high dust environments
- Creators
- Ashley Anderson
- Contributors
- Thomas Peters (Advisor)Patrick O'Shaughnessy (Committee Member)Geb Thomas (Committee Member)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Occupational and Environmental Health
- Date degree season
- Spring 2022
- DOI
- 10.17077/etd.006386
- Publisher
- University of Iowa
- Number of pages
- xi, 67 pages
- Copyright
- Copyright 2022 Ashley Anderson
- Language
- English
- Description illustrations
- illustrations (chiefly color), tables, graphs
- Description bibliographic
- Includes bibliographical references (pages 43-47).
- Public Abstract (ETD)
- Inhaling occupational aerosols can cause adverse health effects such as asthma, lung cancer, and other lung diseases. It is critical to monitor workplace aerosol exposure to prevent these adverse health effects from occurring. Low-cost sensors are a type of direct reading instrument that can be used to measure aerosols. They are inexpensive, lightweight, and provide rapid results. These attributes open many possibilities for rapidly measuring aerosols in the workplace. Higher concentrations of dust sometimes found in the workplace can build-up within the sensor and lead to inaccurate aerosol readings. Consequently, it is important to understand if and how rapidly dust accumulation affects output from low-cost aerosol sensors so that valid measurements can be obtained in the workplace. This study investigated (1) if dust accumulation affects the performance of two types of low- cost particulate matter sensors (Plantower PMS7003 and Sensirion SPS30) in simulated occupational environments over time, and (2) whether the automatic fan-cleaning procedure of the Sensirion SPS30 prevents dust accumulation from degrading sensor performance. Four Plantower PMS7003 sensors, four Sensirion SPS30 sensors, and four pDR-1500 photometers were exposed to sodium chloride at concentrations ranging around ~3 mg/m3, and Arizona Road Dust at target concentrations. Coefficients of variation were calculated to assess the precision of low-cost sensors, and bias was calculated to determine how well the low-cost sensors agreed with the reference instrument (pDR-1500). A t-test was conducted to determine if the SPS30 fan- cleaning procedure prevented dust accumulation from affecting sensor performance. Study results indicate that when these sensors were exposed to target concentrations (3 mg/m3) of Arizona Road Dust their performance stayed consistent over time. These data suggest it may be practical to use low-cost sensors in the workplace to obtain aerosol measurements. It was also found the low-cost sensors with internal cleaning features had no meaningful effect on aerosol concentrations. Future research should test these low-cost sensors in higher concentrations than concentrations completed in this study, to determine if performance decreases over time. In other future work, deploying low-cost sensors with their photodiode facing down may be a way to prevent internal dust accumulation from occurring.
- Academic Unit
- Occupational and Environmental Health
- Record Identifier
- 9984271153302771
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