Occupational Exposure Assessment Models

Occupational exposure assessment models are structured frameworks designed to estimate workers’ exposure to hazardous agents in the workplace. They range from simple, conservative screening tools to sophisticated mechanistic representations that integrate physical, chemical and process parameters. Tier 1 models employ deterministic algorithms with default parameters to provide initial bounding estimates, while Tier 2 and higher-tier models incorporate task-specific variables and statistical calibration to refine predictions. Empirical modifying-factor models adjust base-case exposures through contextual factors such as ventilation, duration of task and use of controls, whereas mass-balance and computational fluid dynamics techniques simulate dynamic dispersion and removal processes. Recent advances have sought to bridge model outputs with real-time monitoring data, enhancing reliability through Bayesian calibration and improved parameterisation. Global harmonisation efforts, notably under regulatory schemes such as REACH and ISES Europe, have underlined the need for transparent validation protocols and shared model repositories. Practical applications span chemical manufacturing, nanomaterial handling, healthcare disinfection and electroplating, facilitating risk management, regulatory compliance and epidemiological research. These models support proactive exposure control, guiding engineering design, personal protective equipment selection and process optimisation to protect worker health on a global scale.

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Occupational Exposure Assessment Models publication trend

The graph below shows the total number of articles in occupational exposure assessment models across all publications each year (not limited to Nature Index journals).

Technical terms

Occupational exposure assessment model: A computational or empirical framework for estimating workers’ exposure concentrations to chemical or physical hazards in occupational settings.

Deterministic model: A method that uses fixed input parameters and mathematical equations to produce a single, conservative exposure estimate.

Modifying-factor model: An empirical approach that adjusts baseline exposure estimates using contextual factors such as task duration, ventilation and control measures.

Two-box model: A compartmental approach dividing the workplace into near-field and far-field zones to simulate contaminant dispersion and worker proximity.

Dustiness index: A measure of the propensity of powdered materials to generate airborne particles under standardised agitation conditions.

Handling energy factor: A parameter reflecting the mechanical energy applied during material handling, used to adjust emission rate estimates.

References

1. Use of the dustiness index in combination with the handling energy factor for exposure modelling of nanomaterials. NanoImpact (2024).
2. Occupational inhalation exposure during surface disinfection—exposure assessment based on exposure models compared with measurement data. Journal of Exposure Science & Environmental Epidemiology (2023).
3. Personal Exposure to Sulfuric Acid in the Electroplating Industry: Development and Validation of a Predictive Model. Toxics (2024).
4. Exposure Models for REACH and Occupational Safety and Health Regulations. International Journal of Environmental Research and Public Health (2020).
5. Theoretical Background of Occupational-Exposure Models—Report of an Expert Workshop of the ISES Europe Working Group “Exposure Models”. International Journal of Environmental Research and Public Health (2022).