Facility-wide assessment of occupational exposure to dust, noise, and formaldehyde
7 affiliations
- 1Department of Mechanical Engineering, Colorado State University, Fort Collins, CO USA
- 2Department of Mechanical Engineering, Universidad San Francisco de Quito, Quito, Ecuador
- 3Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO USA
- 4Department of Communication Studies, Colorado State University, Fort Collins, CO USA
- 5Department of Journalism and Media Communication, Colorado State University, Fort Collins, CO USA
- 6Access Sensor Technologies, Fort Collins, CO USA
- 7Department of Statistics, Colorado State University, Fort Collins, CO USA
Abstract
Background: Exposure to particulate matter, hazardous gases, and noise among workers causes millions of deaths, injuries, and disabilities annually. These exposures are not measured frequently, and most workers are never monitored because resources for monitoring are limited globally. Even in high-income countries, just two or three samples per workplace inspection are collected on average. Considerably larger sample sizes are required to estimate measures of central tendency and upper percentiles of common exposure distributions. Therefore, interventions and epidemiological studies often rely on poor estimates of those parameters.
Objective: The objective of this study was to demonstrate that a small team can cost-effectively measure all workers’ exposures to multiple hazards within a facility (~100 workers) in a single day while minimizing participant burden and loss of productivity.
Methods: We deployed novel, compact personal monitors—called AirPens—to measure exposures to total particulates, formaldehyde, and A-weighted noise among workers at a furniture manufacturing facility during one full work shift. AirPens were preloaded with sampling media and preprogrammed to minimize field deployment time. On-board sensor data were used to identify sampling anomalies, confirm that AirPens were worn, and validate sampling results. Valid samples were then used to estimate exposure distribution parameters.
Results: A team of five people deployed 83 AirPens at the facility. After quality assurance screening, 67 PM, 67 noise, and 22 formaldehyde samples remained valid (or 72, 67, and 31, respectively if samples below the limit of detection are counted as valid). PM and noise exposure distribution parameters (e.g., arithmetic and geometric mean, 95th percentile) were estimated with high certainty. Uncertainty (i.e., confidence intervals) grew several fold when smaller sample sizes were analyzed.
Significance: Use of streamlined multi-hazard monitoring technology enables dramatically higher sample throughput for workplace exposure assessment. This approach reduces the uncertainty of workplace risk assessment and facilitates more in-depth analyses of personal exposure.
Impact statement: Comprehensive monitoring of personal exposure to air pollution is lacking due to technological and logistical limitations inherent to established monitoring methods. This lack of monitoring limits occupational health practice and epidemiologic research, which rely on sufficient sample sizes to support expert judgments or statistical inferences. This work demonstrates a new wearable sampler for particle, gas, and noise hazards, designed to overcome typical barriers to personal exposure assessment (e.g., cost, time, participant burden). Results show that this new sampling approach can produce measurements of similar quality, but on a much larger scale, compared to established technology.
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BibTeX
@article{rueda2026facilitywide,
title = {{Facility-wide assessment of occupational exposure to dust, noise, and formaldehyde}},
author = {Emilio Molina Rueda and Ellison Carter and Christian L’Orange and Meghan R. Cosgrove and Elizabeth A. Williams and Ashley A. Anderson and Marie J. Andales and Jessica Tryner and Marilee Long and Ander Wilson and John Volckens},
journal = {Journal of Exposure Science \& Environmental Epidemiology},
year = {2026},
month = may,
doi = {10.1038/s41370-026-00883-6},
url = {https://doi.org/10.1038/s41370-026-00883-6},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Facility-wide assessment of occupational exposure to dust, noise, and formaldehyde
AU - Emilio Molina Rueda
AU - Ellison Carter
AU - Christian L’Orange
AU - Meghan R. Cosgrove
AU - Elizabeth A. Williams
AU - Ashley A. Anderson
AU - Marie J. Andales
AU - Jessica Tryner
AU - Marilee Long
AU - Ander Wilson
AU - John Volckens
PY - 2026
DA - 2026/05/28
JO - Journal of Exposure Science & Environmental Epidemiology
DO - 10.1038/s41370-026-00883-6
UR - https://doi.org/10.1038/s41370-026-00883-6
AB - Background: Exposure to particulate matter, hazardous gases, and noise among workers causes millions of deaths, injuries, and disabilities annually. These exposures are not measured frequently, and most workers are never monitored because resources for monitoring are limited globally. Even in high-income countries, just two or three samples per workplace inspection are collected on average. Considerably larger sample sizes are required to estimate measures of central tendency and upper percentiles of common exposure distributions. Therefore, interventions and epidemiological studies often rely on poor estimates of those parameters. Objective: The objective of this study was to demonstrate that a small team can cost-effectively measure all workers’ exposures to multiple hazards within a facility (~100 workers) in a single day while minimizing participant burden and loss of productivity. Methods: We deployed novel, compact personal monitors—called AirPens—to measure exposures to total particulates, formaldehyde, and A-weighted noise among workers at a furniture manufacturing facility during one full work shift. AirPens were preloaded with sampling media and preprogrammed to minimize field deployment time. On-board sensor data were used to identify sampling anomalies, confirm that AirPens were worn, and validate sampling results. Valid samples were then used to estimate exposure distribution parameters. Results: A team of five people deployed 83 AirPens at the facility. After quality assurance screening, 67 PM, 67 noise, and 22 formaldehyde samples remained valid (or 72, 67, and 31, respectively if samples below the limit of detection are counted as valid). PM and noise exposure distribution parameters (e.g., arithmetic and geometric mean, 95th percentile) were estimated with high certainty. Uncertainty (i.e., confidence intervals) grew several fold when smaller sample sizes were analyzed. Significance: Use of streamlined multi-hazard monitoring technology enables dramatically higher sample throughput for workplace exposure assessment. This approach reduces the uncertainty of workplace risk assessment and facilitates more in-depth analyses of personal exposure. Impact statement: Comprehensive monitoring of personal exposure to air pollution is lacking due to technological and logistical limitations inherent to established monitoring methods. This lack of monitoring limits occupational health practice and epidemiologic research, which rely on sufficient sample sizes to support expert judgments or statistical inferences. This work demonstrates a new wearable sampler for particle, gas, and noise hazards, designed to overcome typical barriers to personal exposure assessment (e.g., cost, time, participant burden). Results show that this new sampling approach can produce measurements of similar quality, but on a much larger scale, compared to established technology.
SN - 1559-0631
SN - 1559-064X
ER -