Failure analysis is an essential step in semiconductor manufacturing. When a chip fails quality control, engineers must physically section the wafer to locate the defect, often using manual cutting tools at a workbench. Unlike the highly automated cleanrooms that dominate public perceptions of chip fabrication, these analysis stations involve close human contact with the workpiece. The cutting action abrades silicon, resins, and patterned layers, generating airborne dust, while any organic materials in the wafer stack can release volatile compounds. Because operators lean over the bench for extended periods, their breathing zone sits directly above the emission source, making the geometry of airflow around the bench a matter of occupational health.

The research team combined direct field measurements with computational fluid dynamics, or CFD, to characterize exposure conditions during real wafer-cutting operations. They measured total volatile organic compound concentrations during both bare-wafer and patterned-wafer cutting. The results revealed a striking difference: cutting patterned wafers, which carry processed circuit layers, produced TVOC concentrations of 0.12 to 0.15 milligrams per cubic meter, roughly five times higher than the 0.02 to 0.03 milligrams per cubic meter observed when cutting bare silicon. The patterned layers, which include organic resins and dielectric materials, clearly contribute additional chemical emissions that bare wafers do not.

Particulate matter measurements completed the exposure picture, capturing the dust generated as cutting tools grind through the wafer structure. But the researchers recognized that concentration numbers alone tell only half the story. What ultimately determines inhalation exposure is not just how much contaminant is released, but where the air carries it. A plume of dust that rises from the cutting point and drifts toward the operator’s face poses a far greater risk than the same plume drawn immediately into an exhaust duct. That insight drove the team to examine the airflow field itself, using both experimental velocity measurements and steady-state CFD simulations to map how air moved across the workbench.

The centerpiece of the study was the evaluation of a hybrid containment workbench, or HCW, a modified local exhaust ventilation system designed to redirect contaminant-laden air away from the worker. The CFD simulations predicted air velocities that matched experimentally measured values with relative errors ranging from 5.3 to 18.2 percent, a level of agreement that gives the modeling approach real credibility for engineering design work. In industrial ventilation, where small changes in flow direction can determine whether a contaminant reaches the breathing zone, validating simulations against physical measurements is essential, and this study did so systematically.

The airflow analysis showed that the HCW produced a flow directed toward the rear exhaust system, and that recirculation near the worker’s breathing zone was reduced compared with the original configuration. Recirculation zones are the hidden villains of ventilation design: they trap contaminants in slow-moving eddies that can linger near the operator, allowing dust and vapors to accumulate in exactly the region where the worker inhales. By suppressing these recirculating patterns and establishing a coherent sweep toward the exhaust, the redesigned bench created airflow conditions that the authors describe as potentially reducing contaminant movement toward the operator.

To confirm that the simulations reflected physical reality, the team performed qualitative smoke visualization experiments at the workbench. Tracer smoke released at the cutting area followed the same trajectories predicted by the CFD model, streaming toward the rear exhaust rather than pooling around the operator. This convergence of quantitative simulation, measured air velocities, and visual flow tracing provides a three-way verification that is often missing from ventilation assessments, which frequently rely on a single method. It also demonstrates a practical workflow that other semiconductor facilities could adopt: model the airflow, validate with anemometer measurements, and confirm with smoke tests before committing to hardware changes.

The human element of the study came from anonymous worker questionnaires administered before and after the HCW installation. Before the new workbench, 84.2 percent of the surveyed workers, sixteen out of nineteen, reported perceiving process odors during wafer cutting. After the HCW was implemented, worker-rated odor and dust control scores improved, indicating that the operators themselves noticed the difference in their working environment. While subjective perceptions are not a substitute for concentration measurements, they capture the lived experience of exposure, including irritation and discomfort that instruments may miss, and the near-universal odor reporting before the intervention underscores how noticeable the emissions were to the people closest to the work.

Perhaps the most important message of the study is methodological. The authors argue that local airflow should be evaluated together with contaminant concentrations when assessing worker exposure and local exhaust ventilation in semiconductor failure-analysis laboratories. A bench can achieve acceptable average concentration readings while still allowing intermittent contaminant excursions into the breathing zone, particularly during the dynamic, short-duration emissions that manual cutting produces. Time-weighted averages can smooth away these fluctuations, which is why understanding the instantaneous flow field, where eddies form, and which paths contaminants take, adds a layer of protection that concentration monitoring alone cannot provide. The combination of CFD, field measurement, and worker feedback offers a template for a more complete exposure assessment.

The findings arrive at a moment when the semiconductor industry is expanding rapidly and scrutiny of occupational health in high-tech manufacturing is intensifying. Failure-analysis labs are smaller and less automated than fabrication cleanrooms, and their ventilation challenges have received comparatively little attention. This study shows that relatively contained engineering interventions, a redesigned workbench with properly directed exhaust, can meaningfully alter the airflow landscape that governs what workers breathe. For an industry built on controlling contamination at the nanometer scale to protect its products, the study is a reminder that the same precision, applied to protecting the people who dissect failed chips, is both achievable and measurable, one airflow streamline at a time.

Subject of Research: Occupational exposure to particulate matter and volatile organic compounds during semiconductor wafer cutting and the evaluation of local exhaust ventilation using field measurements and computational fluid dynamics

Article Title: Worker exposure to particulate matter and volatile organic compounds during semiconductor failure analysis: assessment of local exhaust ventilation using field measurements and computational fluid dynamics

Article References: Park, Y., Choung, M.-H., Oh, J.-S., Roh, H.-S., & Kang, C. (2026). Worker exposure to particulate matter and volatile organic compounds during semiconductor failure analysis: assessment of local exhaust ventilation using field measurements and computational fluid dynamics. Air Quality, Atmosphere & Health, 19(10), Article 229. https://doi.org/10.1007/s11869-026-02123-0

Image Credits: AI Generated

DOI: 10.1007/s11869-026-02123-0

Keywords: semiconductor failure analysis, worker exposure, particulate matter, volatile organic compounds, local exhaust ventilation, computational fluid dynamics, wafer cutting, hybrid containment workbench, occupational health, airflow simulation, smoke visualization, indoor air quality

The research team, led by Shubham Sharma with Nivedita Kaul and Sumit Khandelwal as co-authors, monitored a working sandstone-carving unit in Rajasthan across three seasons. Rather than relying on a single measurement technique, they combined two complementary approaches. Workers wore personal sampling equipment that captured the respirable fraction of dust, the particles small enough to penetrate deep into the lungs, over their shifts. At the same time, real-time instruments logged concentrations of particulate matter in four size classes: PM10, PM4, PM2.5 and PM1, corresponding to particles with aerodynamic diameters of ten, four, two-and-a-half and one micrometer or less. A 31-channel aerodynamic particle sizer resolved the full size distribution of the airborne dust, while concurrent meteorological measurements recorded the temperature, humidity and wind conditions surrounding each sampling campaign.

The seasonal contrast in fine-particle concentrations was striking. Winter recorded the highest particulate levels of any season, with mean PM2.5 concentrations reaching 109.3 micrograms per cubic meter at the workplace. To put that figure in context, it is roughly an order of magnitude above the annual guideline value recommended by the World Health Organization, and it represents the air in the immediate breathing zone of the artisans rather than a distant ambient monitor. The researchers attribute the winter spike to a combination of factors that converge during the cold months. Temperature inversions and stagnant air suppress the dispersion of dust away from the work area, lower humidity and cooler temperatures alter how particles remain suspended, and the enclosed or semi-enclosed nature of many carving workshops traps emissions close to the source.

Particle size matters as much as particle quantity, and here the study revealed a seasonal fingerprint in the dust itself. During winter, the size distributions showed enhanced accumulation of submicron particles, those smaller than one micrometer, which are the fraction most capable of reaching the deepest regions of the lung and even crossing into the bloodstream. In spring and summer, by contrast, the coarse mode of the distribution grew stronger, reflecting larger fragments that settle more quickly but can still irritate the upper airways. The ratios between size fractions told a consistent story: the contribution of PM1 relative to PM2.5 remained relatively stable across seasons, indicating that once particles are in the fine range, their internal composition shifts little, while the ratio of PM2.5 to PM4 varied more, marking the boundary where seasonal effects reshape the dust cloud.

One of the most technically interesting aspects of the work lies in how the team handled the statistics. The four PM fractions are nested within one another, meaning PM10 includes PM4, which includes PM2.5, which includes PM1. This nesting produces severe multicollinearity: correlations among the fractions exceeded 0.90, making it statistically treacherous to attribute effects to any single size class using ordinary regression. The researchers therefore applied principal component regression, a technique that first compresses the correlated particle-size and meteorological variables into a small set of uncorrelated components and then regresses the outcome on those components. The resulting models explained between 90.4 and 97.7 percent of the variation in PM1 concentrations, an unusually high degree of explanatory power for field exposure data.

The principal component analysis also showed that the drivers of fine-particle concentrations change with the calendar. Associations between PM1 levels and the particle-size and meteorological components varied from season to season, meaning that no single control strategy calibrated in one season can be assumed to work year-round. Strong correlations among all PM fractions pointed to a common source, the mechanical working of the stone itself, but meteorology determines how much of that source ends up in the breathing zone. In winter, the same grinding and chiseling that produces a manageable dust cloud in a breezy spring workshop instead accumulates into a dense, fine-particle haze that lingers around the artisan’s face for hours.

The health stakes of these measurements are not abstract. Sandstone from Rajasthan contains substantial crystalline silica, and inhaling respirable silica dust causes silicosis, a progressive disease for which there is no cure once fibrosis sets in. Studies cited by the authors document high prevalences of silicosis among stone carvers in Brazil, Thailand and Canada’s Nunavut territory, as well as among sandstone mine workers across Rajasthan itself. Indian surveys have reported respiratory symptoms, reduced spirometric readings and radiological abnormalities among stone-cutting workers, and Rajasthan’s own silicosis compensation program has disbursed grants for diagnosed cases and deaths. Previous work by the same research group examined respiratory deposition of particles in stone carving using real-time mass and number concentrations, and the new study extends that line of inquiry by adding the seasonal dimension and the full size-resolved picture.

What makes the findings actionable is their specificity. Because winter emerges as the season of peak exposure, dust-control interventions can be timed and intensified when they matter most. The literature on stone fabrication points to several engineering controls that have proven effective elsewhere: on-tool shrouds and local exhaust ventilation that capture dust at the point of generation, wet methods that suppress dust before it becomes airborne, and enclosure of grinding stations. The study’s seasonal size distributions offer a further clue for control design, since a system tuned to capture coarse particles in summer may underperform against the submicron accumulation mode that dominates in winter. Administrative measures, such as rotating workers away from grinding tasks during high-exposure periods and ensuring proper use of respiratory protection, can also be scheduled around the winter peak.

The authors are careful to frame the scope of their conclusions. The measurements come from a single sandstone-carving workplace monitored over three seasons, and they note that larger multi-site and longer-duration investigations are required to establish how broadly the seasonal patterns apply across the stone-carving sector. Rajasthan’s carving industry is vast and largely informal, ranging from heritage-restoration workshops to small units producing export-quality decorative stonework, and working conditions can differ substantially between sites. Nonetheless, the study provides something the sector has lacked: a seasonally resolved, size-resolved characterization of what carvers actually breathe, grounded in personal sampling rather than area monitors alone.

For the artisans of Rajasthan, the message embedded in the data is quietly urgent. The dust that glitters in a shaft of winter sunlight is not merely a nuisance but a precisely measurable hazard whose finest particles concentrate exactly when the weather conspires to keep them airborne and close. The study’s models, explaining more than ninety percent of the variance in fine-particle concentrations, demonstrate that this hazard is predictable, and what is predictable can be managed. As India’s natural stone industry faces growing scrutiny over labor conditions and occupational disease, research of this kind supplies the evidence base on which targeted regulation, engineering investment and worker protection can finally be built, season by season and micron by micron.

Subject of Research: Seasonal particulate matter exposure and particle size distribution among sandstone-carving workers in Rajasthan, India

Article Title: Seasonal variation in particulate emissions, particle size distribution, and worker exposure at a sandstone-carving workplace in Rajasthan

Article References: Sharma, S., Kaul, N., & Khandelwal, S. (2026). Seasonal variation in particulate emissions, particle size distribution, and worker exposure at a sandstone-carving workplace in Rajasthan. Air Quality, Atmosphere & Health, 19(10), Article 217. https://doi.org/10.1007/s11869-026-02110-5

Image Credits: AI Generated

DOI: 10.1007/s11869-026-02110-5

Keywords: particulate matter, respirable dust, silica exposure, silicosis, sandstone carving, occupational health, Rajasthan, PM2.5, particle size distribution, principal component regression, air quality, worker exposure