Determination of particle concentration rankings by spatial mapping of particle surface area, number, and mass concentrations in a restaurant and a die casting plant

Direct-reading instruments for aerosols: A review for occupational health and safety professionals part 2: Applications

Direct reading instruments (DRIs) for aerosols have been used in industrial hygiene practice for many years, but their potential has not been fully realized by many occupational health and safety professionals. Although some DRIs quantify other metrics, this article will primarily focus on DRIs that measure aerosol number, size, or mass. This review addresses three applications of aerosol DRIs that occupational health and safety professionals can use to discern, characterize, and document exposure conditions and resolve aerosol-related problems in the workplace. The most common application of aerosol DRIs is the evaluation of engineering controls. Examples are provided for many types of workplaces and situations including construction, agriculture, mining, conventional manufacturing, advanced manufacturing (nanoparticle technology and additive manufacturing), and non-industrial sites. Aerosol DRIs can help identify the effectiveness of existing controls and, as needed, develop new strategies to reduce potential aerosol exposures. Aerosol concentration mapping (ACM) using DRI data can focus attention on emission sources in the workplace spatially illustrate the effectiveness of controls and constructively convey concerns to management and workers. Examples and good practices of ACM are included. Video Exposure Monitoring (VEM) is another useful technique in which video photography is synced with the concentration output of an aerosol DRI. This combination allows the occupational health and safety professional to see what tasks, environmental situations, and/or worker actions contribute to aerosol concentration and potential exposure. VEM can help identify factors responsible for temporal variations in concentration. VEM can assist with training, engage workers, convince managers about necessary remedial actions, and provide for continuous improvement of the workplace environment. Although using DRIs for control evaluation, ACM and VEM can be time-consuming, the resulting information can provide useful data to prompt needed action by employers and employees. Other barriers to adoption include privacy and security issues in some worksites. This review seeks to provide information so occupational health and safety professionals can better understand and effectively use these powerful applications of aerosol DRIs.

Estimating personal exposures from a multi-hazard sensor network

Occupational exposure assessment is almost exclusively accomplished with personal sampling. However, personal sampling can be burdensome and suffers from low sample sizes, resulting in inadequately characterized workplace exposures. Sensor networks offer the opportunity to measure occupational hazards with a high degree of spatiotemporal resolution. Here, we demonstrate an approach to estimate personal exposure to respirable particulate matter (PM), carbon monoxide (CO), ozone (O₃), and noise using hazard data from a sensor network. We simulated stationary and mobile employees that work at the study site, a heavy-vehicle manufacturing facility. Network-derived exposure estimates compared favorably to measurements taken with a suite of personal direct-reading instruments (DRIs) deployed to mimic personal sampling but varied by hazard and type of employee. The root mean square error (RMSE) between network-derived exposure estimates and personal DRI measurements for mobile employees was 0.15 mg/m³, 1 ppm, 82 ppb, and 3 dBA for PM, CO, O₃, and noise, respectively. Pearson correlation between network-derived exposure estimates and DRI measurements ranged from 0.39 (noise for mobile employees) to 0.75 (noise for stationary employees). Despite the error observed estimating personal exposure to occupational hazards it holds promise as an additional tool to be used with traditional personal sampling due to the ability to frequently and easily collect exposure information on many employees.

Variability of aerosol mass and number concentrations during taconite mining operations

This study characterized concentration metrics of airborne nanoparticles and their time series across major operations of a taconite mine through monitoring respirable and ultrafine particle concentrations at four major processing departments of the mine: crushing, dry milling, wet milling, and pelletizing (United Taconite Mine, Iron Junction, MN, USA). We used three area stations of direct-reading instruments to estimate concentration metrics including PM₁ (particles with an aerodynamic diameter <1 µm), respirable dust (particles sampled according to the respirable convention with a 50% sampling efficiency at an aerodynamic diameter of 4 µm), PN (total number concentration of particles), and lung-deposited surface area concentrations (LDSA) of particles smaller than 300 nm, on two different days. Results for each station were compared using bivariate correlation analysis to obtain insight into the spatial distribution, and intra-class correlation coefficients (ICCs) to evaluate the between-day repeatability between the measurements. Comparability of the LDSA concentrations measured by two different devices was also investigated using linear regression. Results revealed that the pelletizing operation produced the highest average LDSA concentration on both days (with a maximum concentration of 199 ± 48 µm²/cm³ in pelletizing, 141 ± 52 µm²/cm³ in crushing, 91 ± 9 µm²/cm³ in dry milling, and 85 ± 7 µm²/cm³ in wet milling). Concentrations in all operations showed a fair to excellent between-day repeatability but they were significantly different within stations of each operation. Measured LDSA concentrations did not show a linear correlation between different instruments, except for crushing.

Optimizing a Sensor Network with Data from Hazard Mapping Demonstrated in a Heavy-Vehicle Manufacturing Facility

Objectives

To design a method that uses preliminary hazard mapping data to optimize the number and location of sensors within a network for a long-term assessment of occupational concentrations, while preserving temporal variability, accuracy, and precision of predicted hazards.

Methods

Particle number concentrations (PNCs) and respirable mass concentrations (RMCs) were measured with direct-reading instruments in a large heavy-vehicle manufacturing facility at 80-82 locations during 7 mapping events, stratified by day and season. Using kriged hazard mapping, a statistical approach identified optimal orders for removing locations to capture temporal variability and high prediction precision of PNC and RMC concentrations. We compared optimal-removal, random-removal, and least-optimal-removal orders to bound prediction performance.

Results

The temporal variability of PNC was found to be higher than RMC with low correlation between the two particulate metrics (ρ = 0.30). Optimal-removal orders resulted in more accurate PNC kriged estimates (root mean square error [RMSE] = 49.2) at sample locations compared with random-removal order (RMSE = 55.7). For estimates at locations having concentrations in the upper 10th percentile, the optimal-removal order preserved average estimated concentrations better than random- or least-optimal-removal orders (P < 0.01). However, estimated average concentrations using an optimal-removal were not statistically different than random-removal when averaged over the entire facility. No statistical difference was observed for optimal- and random-removal methods for RMCs that were less variable in time and space than PNCs.

Conclusions

Optimized removal performed better than random-removal in preserving high temporal variability and accuracy of hazard map for PNC, but not for the more spatially homogeneous RMC. These results can be used to reduce the number of locations used in a network of static sensors for long-term monitoring of hazards in the workplace, without sacrificing prediction performance.

Mapping Occupational Hazards with a Multi-sensor Network in a Heavy-Vehicle Manufacturing Facility

Due to their small size, low-power demands, and customizability, low-cost sensors can be deployed in collections that are spatially distributed in the environment, known as sensor networks. The literature contains examples of such networks in the ambient environment; this article describes the development and deployment of a 40-node multi-hazard network, constructed with low-cost sensors for particulate matter (SHARP GP2Y1010AU0F), carbon monoxide (Alphasense CO-B4), oxidizing gases (Alphasense OX-B421), and noise (developed in-house) in a heavy-vehicle manufacturing facility. Network nodes communicated wirelessly with a central database in order to record hazard measurements at 5-min intervals. Here, we report on the temporal and spatial measurements from the network, precision of network measurements, and accuracy of network measurements with respect to field reference instruments through 8 months of continuous deployment. During typical production periods, 1-h mean hazard levels ± standard deviation across all monitors for particulate matter (PM), carbon monoxide (CO), oxidizing gases (OX), and noise were 0.62 ± 0.2 mg m-3, 7 ± 2 ppm, 155 ± 58 ppb, and 82 ± 1 dBA, respectively. We observed clear diurnal and weekly temporal patterns for all hazards and daily, hazard-specific spatial patterns attributable to general manufacturing processes in the facility. Processes associated with the highest hazard levels were machining and welding (PM and noise), staging (CO), and manual and robotic welding (OX). Network sensors exhibited varying degrees of precision with 95% of measurements among three collocated nodes within 0.21 mg m-3 for PM, 0.4 ppm for CO, 9 ppb for OX, and 1 dBA for noise of each other. The median percent bias with reference to direct-reading instruments was 27%, 11%, 45%, and 1%, for PM, CO, OX, and noise, respectively. This study demonstrates the successful long-term deployment of a multi-hazard sensor network in an industrial manufacturing setting and illustrates the high temporal and spatial resolution of hazard data that sensor and monitor networks are capable of. We show that network-derived hazard measurements offer rich datasets to comprehensively assess occupational hazards. Our network sets the stage for the characterization of occupational exposures on the individual level with wireless sensor networks.

Sampling Strategies for Accurate Hazard Mapping of Noise and Other Hazards Using Short-Duration Measurements

Hazard mapping is an effective way to depict spatial variability in hazard intensity obtained with direct-reading instruments on a facility floor plan. However, the extent to which temporal variability affects map accuracy is unknown, and guidance on sampling strategies to minimize map bias is lacking. In this study, we evaluated the accuracy of hazard maps produced for simulated sources and sampling strategies in a hypothetical facility. Hazard maps were produced from sampled data at high, mid, and low spatial resolution and with and without replicates and compared to a reference time-weighted average hazard map using several map comparison metrics. In agreement with 'real-world' mapping datasets, the simulation showed that increasing the number of replicates improved the overall comparability of the hazard map produced from the sampled data with the time-weighted average hazard map more efficiently than increasing the sampling spatial resolution. However, if accurately capturing peak exposures near sources is of interest, increasing the spatial resolution of the measurements, particularly near sources, is needed. From these results, we formulated guidelines to use the preliminary assessment of the temporal variability of large and intermittent sources to inform the spatial resolution and need for replicate measures to minimize the bias in hazard maps.

Relationships between number, surface area, and mass concentrations of different nanoparticles in workplaces

No consistent metric for measuring exposure to nanoparticles has yet been agreed upon internationally. This study seeks to examine the relationship between the number concentration (NC), surface area concentration (SAC), and mass concentration (MC) of nanoparticles in workplaces. Real-time NC20-1000 nm, SAC10-1000 nm, and respirable MC100-1000 nm were determined for different nanoparticles. Concentration ratio (CR, activity: background), exposure ranking (ER), and between-metric correlation coefficients (R) were used to analyze the relationships between the three metrics. The ratio of cumulative percentage by number (APN) and cumulative percentage by mass (APM) was used to analyze whether the nanoparticle number is predominant, as compared with the nanoparticle mass. The CRs of NC20-1000 nm and SAC10-1000 nm for different nanoparticles at the corresponding work sites were higher than those of respirable MC100-1000 nm. The ERs of NC20-1000 nm for nano-Fe2O3 and nano-Al2O3 were the same as those of SAC10-1000 nm, but were inconsistent with those of respirable MC100-1000 nm. The order of correlation coefficients between NC20-1000 nm, SAC10-1000 nm, and respirable MC100-1000 nm was: RSAC and NC > RSAC and MC > RNC and MC. The ratios of APN and APM for nano-Al2O3 and grinding-wheel particles (less than 100 nm) at the same work site were 2.03 and 1.65, respectively. NC and SAC metrics are significantly distinct from the MC in characterizing exposure to airborne nanoparticles. Simultaneous measurements of the NC, SAC, and MC should be conducted as part of nanoparticle exposure assessment strategies and epidemiological studies.

Aerosol Emission Monitoring and Assessment of Potential Exposure to Multi-walled Carbon Nanotubes in the Manufacture of Polymer Nanocomposites

Recent animal studies have shown that carbon nanotubes (CNTs) may pose a significant health risk to those exposed in the workplace. To further understand this potential risk, effort must be taken to measure the occupational exposure to CNTs. Results from an assessment of potential exposure to multi-walled carbon nanotubes (MWCNTs) conducted at an industrial facility where polymer nanocomposites were manufactured by an extrusion process are presented. Exposure to MWCNTs was quantified by the thermal-optical analysis for elemental carbon (EC) of respirable dust collected by personal sampling. All personal respirable samples collected (n = 8) had estimated 8-h time weighted average (TWA) EC concentrations below the limit of detection for the analysis which was about one-half of the recommended exposure limit for CNTs, 1 µg EC/m(3) as an 8-h TWA respirable mass concentration. Potential exposure sources were identified and characterized by direct-reading instruments and area sampling. Area samples analyzed for EC yielded quantifiable mass concentrations inside an enclosure where unbound MWCNTs were handled and near a pelletizer where nanocomposite was cut, while those analyzed by electron microscopy detected the presence of MWCNTs at six locations throughout the facility. Through size selective area sampling it was identified that the airborne MWCNTs present in the workplace were in the form of large agglomerates. This was confirmed by electron microscopy where most of the MWCNT structures observed were in the form of micrometer-sized ropey agglomerates. However, a small fraction of single, free MWCNTs was also observed. It was found that the high number concentrations of nanoparticles, ~200000 particles/cm(3), present in the manufacturing facility were likely attributable to polymer fumes produced in the extrusion process.

Exposure to airborne particles and volatile organic compounds from polyurethane molding, spray painting, lacquering, and gluing in a workshop

Due to the health risk related to occupational air pollution exposure, we assessed concentrations and identified sources of particles and volatile organic compounds (VOCs) in a handcraft workshop producing fishing lures. The work processes in the site included polyurethane molding, spray painting, lacquering, and gluing. We measured total VOC (TVOC) concentrations and particle size distributions at three locations representing the various phases of the manufacturing and assembly process. The mean working-hour TVOC concentrations in three locations studied were 41, 37, and 24 ppm according to photo-ionization detector measurements. The mean working-hour particle number concentration varied between locations from 3000 to 36,000 cm⁻³. Analysis of temporal and spatial variations of TVOC concentrations revealed that there were at least four substantial VOC sources: spray gluing, mold-release agent spraying, continuous evaporation from various lacquer and paint containers, and either spray painting or lacquering (probably both). The mold-release agent spray was indirectly also a major source of ultrafine particles. The workers’ exposure can be reduced by improving the local exhaust ventilation at the known sources and by increasing the ventilation rate in the area with the continuous source.

Ultrafine particle characteristics in a rubber manufacturing factory

BACKGROUND

According to epidemiological research, exposure to rubber fumes can cause various types of cancer and can lead to an increase in death rate because of cardiovascular diseases.

OBJECTIVES

In this study, we have assessed the characteristics of ultrafine particles emitted into the air during the manufacturing of rubber products using waste tires.

METHODS

To assess the aerosol distribution of rubber fumes in the workplace from a product during curing, we have performed particle number concentration mapping using a handheld condensation particle counter. The particle number concentration of each process, count median diameter (CMD), and nanoparticle ratio (<100nm) were determined using an electrical low-pressure impactor (ELPI), and the surface area concentration was determined using a surface area monitor. The shape and composition of the sampled rubber fumes were analyzed using an ELPI-transmission electron microscopy grid method. Further, the rubber fume mass concentration was determined according to the Methods for the Determination of Hazardous Substances 47/2.

RESULTS

The results of particle mapping show that the rubber fumes were distributed throughout the air of the workplace. The concentration was the highest during the final process of the work. The particle number concentration and the surface area concentration were 545 000cm(-3) and 640 µm(2) cm(-3), respectively, approximately 10- and 4-fold higher than those in the outdoor background. During the final process, the CMD and the nanoparticle ratio were 26nm and 94%, respectively. Most of the rubber fume particles had a compact shape because of the coagulation between particles. The main components of these fumes were silicon and sulfur, and heavy metals such as zinc were detected in certain particles. The filter concentration of the rubber fumes was 0.22mg m(-3), lower than the UK workplace exposure limit of 0.6mg m(-3).

CONCLUSIONS

Therefore, the rubber manufacturing process is a potentially dangerous process that produces a high concentration of specific nanoparticles.

Distribution of particle and gas concentrations in Swine gestation confined animal feeding operations

OBJECTIVES

Dust mass concentrations, temperatures, and carbon dioxide concentrations were mapped in a modern, 1048-pen swine gestation barn in winter, spring, and summer.

METHODS

In each season, two technicians measured respirable mass concentrations with an aerosol photometer and temperatures and carbon dioxide concentrations with an indoor air quality monitor at 60 positions in the barn. Stationary photometers were also deployed to measure mass concentrations during mapping at five fixed locations.

RESULTS

In winter when building ventilation rates were low (center-barn mean air velocity=0.34 m s(-1), 68 fpm) to conserve heat within the barn, mass and carbon dioxide concentrations were highest (mass geometric mean, GM=0.50 mg m(-3); CO2 GM=2060 ppm) and fairly uniform over space (mass geometric standard deviation, GSD=1.48; CO2 GSD=1.24). Concentrations were lowest in summer (mass GM=0.13 mg m(-3); CO2 GM=610 ppm) when ventilation rates were high (center-barn mean air velocity=0.99 m s(-1), 196 fpm) to provide cooling. Spatial gradients were greatest in spring (mass GSD=2.11; CO2 GSD=1.50) with low concentrations observed near the building intake, increasing to higher concentrations at the building exhaust.

CONCLUSIONS

Mass concentrations obtained in mapping were generally consistent with those obtained from stationary monitors. A moderately strong linear relationship (R2=0.60) was observed between the log of photometer-measured mass concentration and the log of carbon dioxide concentration, suggesting that carbon dioxide may be an inexpensive alternative to assessing air quality in a swine barn. These results indicate that ventilation can effectively reduce contaminant levels in addition to controlling temperature.

Particulate matter (PM) exposure assessment--horizontal and vertical PM profiles in relation to agricultural activities and environmental factors in farm fields

Reports profiling airborne particulate matter (PM) in farm fields, especially during a Class B biosolids land-injection process, are scarce. Thus, this study characterized PM in such a farm field located in northwest Ohio. For comparison, a control farm field with no biosolids application history was also monitored. During 11 days of varied agricultural activities, the concentrations of particle mass and number (count) and also metal content were monitored in the study field, and their interactions with environmental factors were examined. The monitoring was performed across the farm field at four heights of 0.5, 1.5, 2.5, and 3.5 m from the ground. The overall mean (SD) concentration (μg/m(3)) of respirable suspended particulate matter (RPM) was 30.8 (23.1) with means ranging from 15.9 (3.80) during post-tilling Event 1, 19.9 (12.4) during biosolids application to 56.1 (11.7) during post-harvest (including baling) activity. The maximum concentration of RPM (μg/m(3)) was 43 during biosolids application, 90 during post-harvest, and 183 during post-tilling Event 2 activities. Overall, 93.7% (8.98%) of the total suspended particulate matter (TPM) was respirable. The levels of RPM significantly (p < 0.01) correlated with TPM and particle counts of ultrafine particles (UFP) and 0.3 μm particle size. Ambient temperature showed no effect, whereas wind speed and relative humidity had an inverse effect on RPM concentration. Particle concentrations changed minimally during each set of monitoring across the field, except during major activities or sudden weather changes. For particles with sizes of 2, 5, and 10 μm, the counts decreased with increasing height from the ground and were significantly (p < 0.05) higher at 0.5 m than at other heights. The levels of nine metals within particles monitored were well below current recommended occupational exposure criteria. These results suggest that injection of the biosolids into agricultural land provides significant protection against exposure to biosolids particles.

Assessing potential nanoparticle release during nanocomposite shredding using direct-reading instruments

This study was conducted to determine if engineered nanoparticles are released into the air when nanocomposite parts are shredded for recycling. Test plaques made from polypropylene resin reinforced with either montmorillonite nanoclay or talc and from the same resin with no reinforcing material were shredded by a granulator inside a test apparatus. As the plaques were shredded, an ultrafine condensation particle counter; a diffusion charger; a photometer; an electrical mobility analyzer; and an optical particle counter measured number, lung-deposited surface area, and mass concentrations and size distributions by number in real-time. Overall, the particle levels produced were both stable and lower than found in some occupational environments. Although the lowest particle concentrations were observed when the talc-filled plaques were shredded, fewer nanoparticles were generated from the nanocomposite plaques than when the plain resin plaques were shredded. For example, the average particle number concentrations measured using the ultrafine condensation particle counter were 1300 particles/cm(3) for the talc-reinforced resin, 4280 particles/cm(3) for the nanoclay-reinforced resin, and 12,600 particles/cm(3) for the plain resin. Similarly, the average alveolar-deposited particle surface area concentrations measured using the diffusion charger were 4.0 μm(2)/cm(3) for the talc-reinforced resin, 8.5 μm(2)/cm(3) for the nanoclay-reinforced resin, and 26 μm(2)/cm(3) for the plain resin. For all three materials, count median diameters were near 10 nm during tests, which is smaller than should be found from the reinforcing materials. These findings suggest that recycling of nanoclay-reinforced plastics does not have a strong potential to generate more airborne nanoparticles than recycling of conventional plastics.

A strategy for assessing workplace exposures to nanomaterials

This article describes a highly tailorable exposure assessment strategy for nanomaterials that enables effective and efficient exposure management (i.e., a strategy that can identify jobs or tasks that have clearly unacceptable exposures), while simultaneously requiring only a modest level of resources to conduct. The strategy is based on strategy general framework from AIHA® that is adapted for nanomaterials and seeks to ensure that the risks to workers handling nanomaterials are being managed properly. The strategy relies on a general framework as the basic foundation while building and elaborating on elements essential to an effective and efficient strategy to arrive at decisions based on collecting and interpreting available information. This article provides useful guidance on conducting workplace characterization; understanding exposure potential to nanomaterials; accounting methods for background aerosols; constructing SEGs; and selecting appropriate instrumentation for monitoring, providing appropriate choice of exposure limits, and describing criteria by which exposure management decisions should be made. The article is intended to be a practical guide for industrial hygienists for managing engineered nanomaterial risks in their workplaces.

Prospects and pitfalls of occupational hazard mapping: 'between these lines there be dragons'

Hazard data mapping is a promising new technique that can enhance the process of occupational exposure assessment and risk communication. Hazard maps have the potential to improve worker health by providing key input for the design of hazard intervention and control strategies. Hazard maps are developed with aid from direct-reading instruments, which can collect highly spatially and temporally resolved data in a relatively short period of time. However, quantifying spatial-temporal variability in the occupational environment is not a straightforward process, and our lack of understanding of how to ascertain and model spatial and temporal variability is a limiting factor in the use and interpretation of workplace hazard maps. We provide an example of how sources of and exposures to workplace hazards may be mischaracterized in a hazard map due to a lack of completeness and representativeness of collected measurement data. Based on this example, we believe that a major priority for research in this emerging area should focus on the development of a statistical framework to quantify uncertainty in spatially and temporally varying data. In conjunction with this need is one for the development of guidelines and procedures for the proper sampling, generation, and evaluation of workplace hazard maps.

Quantification of nanoparticle uptake by cells using microscopical and analytical techniques

Quantification of nanoparticles in biological systems (i.e., cells, tissues and organs) is becoming a vital part of nanotoxicological and nanomedical fields. Dose is a key parameter when assessing behavior and any potential risk of nanomaterials. Various techniques for nanoparticle quantification in cells and tissues already exist but will need further development in order to make measurements reliable, reproducible and intercomparable between different techniques. Microscopy allows detection and location of nanoparticles in cells and has been used extensively in recent years to characterize nanoparticles and their pathways in living systems. Besides microscopical techniques (light microscopy and electron microscopy mainly), analytical techniques such as mass spectrometry, an established technique in trace element analysis, have been used in nanoparticle research. Other techniques require ‘labeled’ particles, fluorescently, radioactively or magnetically. However, these techniques lack spatial resolution and subcellular localization is not possible. To date, only electron microscopy offers the resolving power to determine accumulation of nanoparticles in cells due to its ability to image particles individually. So-called super-resolution light microscopy techniques are emerging to provide sufficient resolution on the light microscopy level to image or ‘see’ particles as individual particles. Nevertheless, all microscopy techniques require statistically sound sampling strategies in order to provide quantitative results. Stereology is a well-known sampling technique in various areas and, in combination with electron microscopy, proves highly successful with regard to quantification of nanoparticle uptake by cells.