Abstract No:
1675
Abstract Type:
Student Poster
Authors:
W Call1, J Johnston1
Institutions:
1Brigham Young University, Provo, UT
Presenter:
Willow Call
Brigham Young University
Faculty Advisor:
James Johnston
Brigham Young University
Description:
Studying respirable silica exposures among brick workers in Nepal, we found that ≈11% of samples (25/232) had pump flow rates that drifted beyond ± 5% when post-calibrated. Flow rate directly influences particle sizing when using pre-separators. Sample duration, measured respirable dust concentration, person calibrated, calibrator, and participant job category were examined as possible factors. Samples were collected following NIOSH Method 0600. Understanding this may save time and costs when conducting personal sampling.
Situation/Problem:
Breathing zone respirable dust samples are collected using personal sampling pumps connected to cyclone pre-separators. Common methods, including NIOSH 0600 and 7500, specify cyclones with a 4.0 µm aerodynamic diameter cut point. Changing a flow rate and can influence particle sizing. Hence, ±5.0% deviation from pre- to post-calibration has been recognized as an industry cutoff. Flow rate drift outside of this cutoff may result in the need to resample, with associated financial and time losses. Currently, there is little in the published literature related to factors that may influence flow rate drift. Understanding this may lead to more accurate air exposure data and cost and time savings.
Methods:
An observational study was used to analyze factors associated with flow rate drift when sampling for respirable dust and silica among brick workers in Nepal. The study consisted of 232 participants working various jobs across 4 brick kilns in Kathmandu Valley, Nepal. Samples were collected and analized using NIOSH Methods 0600. SKC AirLite pumps were attached to aluminum cyclones (SKC Inc., Fullerton, CA, USA) holding 37 mm cassettes with matched-weight 5.0 µm PVC filters. Then attached in participants' breathing zones using filter cassette holders (SKC Inc., Fullerton, CA, USA). Pumps were pre-calibrated using Mesa Labs Defender 510 Mid-flow dry calibrators (Mesa Labs, Lakewood, CO, USA) to 2.5 L/m ± 1.0%. Post-calibrated using the same calibrator from pre-calibration. All cassettes were sent to ALS Laboratories in Salt Lake City, UT, USA to be analyzed. R version 4.5.2 was used for data management and statistical analyses. Fisher's exact test with Monte Carlo simulation was used to evaluate relationships between flow rate drift and person who calibrated, calibrator, and worker job category. ANOVA was used to evaluate respirable dust concentration and sample duration. SAS version XX (placeholder ask Greg) was used for data management and statistical analyses. All samples needed to have a percent error difference of less than ± 5.0% to accurately represent particles with a 4.0 µm aerodynamic diameter. A scatter plot showing post over pre-calibrations with linear limits of ± 5.0% was rendered. Of our sample set of 249 participants, 27 were outside ± 5.0%. A linear regrssion model was used to determine the correlation between percentage error withing the pumps flow rates and the filter weights.
Results / Conclusions:
Of 232 samples, 20 (8.6%) were below and 5 (2.2%) exceeded the ± 5.0% drift threshold. There were no significant differences observed for who calibrated (p=0.9), the calibrator used (p=0.1), and participant job category (p=0.54) from the Fisher's exact tests with Monte Carlo simulation. Results of ANOVA also showed no significant differences with respirable dust concentration (p=0.216) or sample duration (p=0.483). With no statistical differences were found (α=0.05 ), drift could not be attributed to any single identifiable factor in this dataset. This study would benefit from a larger sample of pumps that had a drift of ± 5.0%. This sample was limited by field-based variables, rather than pump-specific variables. For example, we did not evaluate pump back pressure, or the dataset for pump serial number. Since our equipment was used on multiple participants, it is possible that one or more pumps were responsible for our findings. We recommend tracking drift data longitudinally for specific pumps.
Core Competencies:
Chemical Sampling and Instrumental Analysis
Secondary Core Competencies:
Laboratory Quality Assurance/Quality Management
Choose at least one (1), and up to five, (5) keywords from the following list. These selections will optimize your presentation's search results for attendees.
Aerosol and airborne particulate monitoring
Equipment rental and repair
Exposure Assessment
Respiratory Protection
Testing, certification, and credentialing
Based on the information that will be presented during your proposed session, please indicate the targeted audience practice level: (select one)
Technician: Technician is a job title given to persons who are trained to assist professionals and practitioners with task-specific assignments. Technicians may collect air samples, operate direct-reading instruments, and provide other services based on specific training received and instructions received from professionals and practitioners.
Was this session organized by an AIHA Technical Committee, Special Interest Group, Working Group, Advisory Group or other AIHA project Team?
No
Are worker exposure data and/or results of worker exposure data analysis presented?
Yes
If yes, i.e., If worker exposure data and/or results of worker exposure data analysis are to be presented please describe the statistical methods and tools (e.g. IHSTAT, Expostats, IHSTAT_Bayes, IHDA-AIHA, or other statistical tool, please specify) used for analysis of the data.
ANOVA, R version 4.5.2. Fisher’s exact test with a Monte Carlo simulation, R version 4.5.2.
How will this help advance the science of IH/OH?
This research may help Industrial Hygienists to understand and find solutions to flow rate drift, increase air sampling accuracy, and reduce sample exclusions. This study examines how exposure assessment accurately addresses pump drift as a source of systematic error in respirable dust sampling that is often over looked. Sampling is time-intensive and can have large financial costs. Our findings suggest that the person who conducted calibration, the calibrator, participant job category, exposure dust concentration, and sample duration did not significantly influence pump drift in this study. Finding solutions to pump drift will maximize equipment efficiency, cut financial costs, and reduce wasted time within organizations. The study establishes a methodological framework and baseline dataset that future researchers can build on, particularly if designed to capture more equipment flow rate drift events.
Have you presented this information before?
No
I have read and agree to these guidelines.
Yes