The Mapping of Fine and Ultrafine Particle Concentrations in an Engine Machining and Assembly Facility

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.

Direct-reading instruments for aerosols: A review for occupational health and safety professionals part 1: Instruments and good practices

With advances in technology, there are an increasing number of direct-reading instruments available to occupational health and safety professionals to evaluate occupational aerosol exposures. Despite the wide array of direct-reading instruments available to professionals, the adoption of direct-reading technology to monitor workplace exposures has been limited, partly due to a lack of knowledge on how the instruments operate, how to select an appropriate instrument, and challenges in data analysis techniques. This paper presents a review of direct-reading aerosol instruments available to occupational health and safety professionals, describes the principles of operation, guides instrument selection based on the workplace and exposure, and discusses data analysis techniques to overcome these barriers to adoption. This paper does not cover all direct-reading instruments for aerosols but only those that an occupational health and safety professional could use in a workplace to evaluate exposures. Therefore, this paper focuses on instruments that have the most potential for workplace use due to their robustness, past workplace use, and price with regard to return on investment. The instruments covered in this paper include those that measure aerosol number concentration, mass concentration, and aerosol size distributions.

Exposure to Ultrafine Particles in the Ferroalloy Industry Using a Logbook Method

Background: It is difficult to assess workers’ exposure to ultrafine particles (UFP) due to the lack of personal sampling equipment available for this particle fraction. The logbook method has been proposed as a general method for exposure assessment. This method measures the time and concentration components of the time-weighted average concentration separately and could be suitable for investigation of UFP exposure. Objectives: In this study, we have assessed workers’ exposure to UFP in a ferrosilicon plant. The main tasks of the furnace workers were identified, and the logbook method was used in combination with stationary measurements of UFP taken as close to the identified task areas as possible. In order to verify the results, respirable particles were collected using stationary sampling in close proximity to the UFP measuring instrument, and personal full-shift sampling of respirable particles was performed simultaneously. Thus, exposure to respirable particles determined using the logbook method could be compared to the results of standard measurement. Methods: The particle number concentration of ultrafine particles was determined using a NanoScan SMPS. Respirable particle concentration and exposure were determined using a sampling train consisting of a pump, filter, filter cassettes, and SKC Cyclone for the respirable fraction. Attendance times for workers at each work location were registered via thorough observations made by the research team. Results: The logbook method for exposure estimation based on stationary sampling equipment made it possible to calculate UFP exposure for workers operating the furnaces at a ferrosilicon plant. The mid-size furnace and the large furnace were evaluated separately. The workers operating the largest furnace were exposed to 1.47 × 10⁴ particles/cm³, while workers operating the mid-size furnace were exposed to 2.06 × 10⁴ particles/cm³, with a mean of 1.74 × 10⁴ particles/cm³. Substantial contributions from the casting area, ladle transport corridor, and both tapping areas were made. Exposure to respirable particles was 2.04 mg/m³ (logbook); 2.26 mg/m³ (personal sampling) for workers operating the large-sized furnace, 3.24 mg/m³ (logbook); 2.44 mg/m³ (personal sampling) for workers operating the medium-sized furnace, and 2.57 mg/m³ (logbook); 2.53 mg/m³(personal sampling) on average of all tappers. The average ratio of these two methods’ results was 1.02, which indicates that the logbook method could be used as a substitute for personal sampling when it is not possible to perform personal sampling, at least within this industry. Conclusions: The logbook method is a useful supplement for exposure assessment of UFP, able to identify the most polluted areas of the workplace and the contribution of different work tasks to the total exposure of workers, enabling companies to take action to reduce exposure.

Sources of error and variability in particulate matter sensor network measurements

The quality of mass concentration estimates from increasingly popular networks of low-cost particulate matter sensors depends on accurate conversion of sensor output (e.g., voltage) into gravimetric-equivalent mass concentration, typically using a calibration procedure. This study evaluates two important sources of variability that lead to error in estimating gravimetric-equivalent mass concentration: the temporal changes in sensor calibration and the spatial and temporal variability in gravimetric correction factors. A 40-node sensor network was deployed in a heavy vehicle manufacturing facility for 8 months. At a central location in the facility, particulate matter was continuously measured with three sensors of the network and a traditional, higher-cost photometer, determining the calibration slope and intercept needed to translate sensor output to photometric-equivalent mass concentration. Throughout the facility, during three intensive sampling campaigns, respirable mass concentrations were measured with gravimetric samplers and photometers to determine correction factors needed to adjust photometric-equivalent to gravimetric-equivalent mass concentration. Both field-determined sensor calibration slopes and intercepts were statistically different than those estimated in the laboratory (α = 0.05), emphasizing the importance of aerosol properties when converting voltage to photometric-equivalent mass concentration and the need for field calibration to determine slope. Evidence suggested the sensors' weekly field calibration slope decreased and intercept increased, indicating the sensors were deteriorating over time. The mean correction factor in the cutting and shot blasting area (2.9) was substantially and statistically lower than that in the machining and welding area (4.6; p = 0.01). Therefore, different correction factors should be determined near different occupational processes to accurately estimate particle mass concentrations.

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.

Occupational Exposure to Fine Particles and Ultrafine Particles in a Steelmaking Foundry

Several studies have shown an increased mortality rate for different types of tumors, respiratory disease and cardiovascular morbidity associated with foundry work. Airborne particles were investigated in a steelmaking foundry using an electric low-pressure impactor (ELPI+™), a Philips Aerasense Nanotracer and traditional sampling equipment. Determination of metallic elements in the collected particles was carried out by inductively coupled plasma mass spectrometry. The median of ultrafine particle (UFP) concentration was between 4.91 × 103 and 2.33 × 105 part/cm3 (max. 9.48 × 106 part/cm3). Background levels ranged from 1.97 × 104 to 3.83 × 104 part/cm3. Alveolar and deposited tracheobronchial surface area doses ranged from 1.3 × 102 to 8.7 × 103 mm2, and 2.6 × 101 to 1.3 × 103 mm2, respectively. Resulting inhalable and respirable fraction and metallic elements were below limit values set by Italian legislation. A variable concentration of metallic elements was detected in the different fractions of UFPs in relation to the sampling site, the emission source and the size range. This data could be useful in order to increase the knowledge about occupational exposure to fine and ultrafine particles and to design studies aimed to investigate early biological effects associated with the exposure to particulate matter in the foundry industries.

Preferred sampler inlet configurations for collection of aerosolized nano-scale materials

BACKGROUND

Due to the lack of standard industrial hygiene sampling protocols for collection of nano-scale materials, sampling inlet device selection is left to individual researchers and professionals.

OBJECTIVE

The objective of this study was to compare nano-scale aspiration efficiency for common inlet configurations with that of an open-ended sampler tube that is a commonly used inlet for direct reading instruments such as a condensation particle counter.

METHODS

A polydisperse aerosol was generated using an electric motor as the aerosol source. Typical aerosols generated by this method produced particles with geometric mean mobility diameters of approximately 30 nm with geometric standard deviations of approximately 2. Comparison of raw particle counts in size ranges measured with a scanning mobility particle analyzer was made by determining the fractional difference between the selected inlet and that of the open-ended tube.

RESULTS

Particle size distributions were nearly identical for all inlet types. The same held true for numbers of particles collected with the exception that the needle inlet was highly variable.

CONCLUSIONS

When completing air monitoring for nano-scale materials, inlets on most collection devices (filters, tubing) do not impact aspiration efficiency. This means that it is not necessary to match inlet configurations when using multiple methods to collect and analyze nano-scale materials.

Composition of Metallic Elements and Size Distribution of Fine and Ultrafine Particles in a Steelmaking Factory

Background: The characteristics of aerosol, in particular particle size and chemical composition, can have an impact on human health. Particle size distribution and chemical composition is a necessary parameter in occupational exposure assessment conducted in order to understand possible health effects. The aim of this study was to characterize workplace airborne particulate matter in a metallurgical setting by synergistically using two different approaches; Methodology: Analysis of inhalable fraction concentrations through traditional sampling equipment and ultrafine particles (UFP) concentrations and size distribution was conducted by an Electric Low-Pressure Impactor (ELPI+™). The determination of metallic elements (ME) in particles was carried out by inductively coupled plasma mass spectrometry; Results: Inhalable fraction and ME concentrations were below the limits set by Italian legislation and the American Conference of Governmental Industrial Hygienists (ACGIH, 2017). The median of UFP was between 4.00 × 10⁴ and 2.92 × 10⁵ particles/cm³. ME concentrations determined in the particles collected by ELPI show differences in size range distribution; Conclusions: The adopted synergistic approach enabled a qualitative and quantitative assessment of the particles in steelmaking factories. The results could lead to a better knowledge of occupational exposure characterization, in turn affording a better understanding of occupational health issues due to metal fumes exposure.

Low-Cost, Distributed Environmental Monitors for Factory Worker Health

An integrated network of environmental monitors was developed to continuously measure several airborne hazards in a manufacturing facility. The monitors integrated low-cost sensors to measure particulate matter, carbon monoxide, ozone and nitrogen dioxide, noise, temperature and humidity. The monitors were developed and tested in situ for three months in several overlapping deployments, before a full cohort of 40 was deployed in a heavy vehicle manufacturing facility for a year of data collection. The monitors collect data from each sensor and report them to a central database every 5 min. The work includes an experimental validation of the particle, gas and noise monitors. The R² for the particle sensor ranges between 0.98 and 0.99 for particle mass densities up to 300 μg/m³. The R² for the carbon monoxide sensor is 0.99 for concentrations up to 15 ppm. The R² for the oxidizing gas sensor is 0.98 over the sensitive range from 20 to 180 ppb. The noise monitor is precise within 1% between 65 and 95 dBA. This work demonstrates the capability of distributed monitoring as a means to examine exposure variability in both space and time, building an important preliminary step towards a new approach for workplace hazard monitoring.

STATIC AND ROVING SENSOR DATA FUSION FOR SPATIO-TEMPORAL HAZARD MAPPING WITH APPLICATION TO OCCUPATIONAL EXPOSURE ASSESSMENT

Rapid technological advances have drastically improved the data collection capacity in occupational exposure assessment. However, advanced statistical methods for analyzing such data and drawing proper inference remain limited. The objectives of this paper are (1) to provide new spatio-temporal methodology that combines data from both roving and static sensors for data processing and hazard mapping across space and over time in an indoor environment, and (2) to compare the new method with the current industry practice, demonstrating the distinct advantages of the new method and the impact on occupational hazard assessment and future policy making in environmental health as well as occupational health. A novel spatio-temporal model with a continuous index in both space and time is proposed, and a profile likelihood-based model fitting procedure is developed that allows fusion of the two types of data. To account for potential differences between the static and roving sensors, we extend the model to have nonhomogenous measurement error variances. Our methodology is applied to a case study conducted in an engine test facility, and dynamic hazard maps are drawn to show features in the data that would have been missed by existing approaches, but are captured by the new method.

Nanoparticle formation in a chemical storage room as a new incidental nanoaerosol source at a nanomaterial workplace

Chemical storage rooms located near engineered nanomaterials (ENMs) workplaces can be a significant source of unintentional nanoaerosol generation. A new incidental nanoparticle source was identified and characterized in a chemical storage room located at an ENMs workplace. Stationary and mobile measurements using on-line instruments and chemical analysis of volatile organic compounds (VOCs) were carried out to identify the source. The number of nanoaerosols emitted from the chemical storage room was found to be several orders of magnitude higher than that existing in the ENMs workplace. VOC analysis showed that the accumulated precursors and oxygenated VOCs in the chemical storage room could be attributed to incidental particle formation via gas-to-particle conversion. We stress the importance of identification of the incidental nanoaerosols to allow characterization of the nanoaerosols at ENMs workplaces, and to estimate additional nanoaerosols exposure, which was previously unknown. Hazardous chemical substances in the workplace have been regulated in many countries; however, most of the regulations are focused on gas-phase or liquid-phase substances. The present study emphasizes the importance of secondary pollutants in particulate form that can be generated from the gas or liquid phase of hazardous chemical substances.

Effect of Carbon Nanotubes Upon Emissions From Cutting and Sanding Carbon Fiber-Epoxy Composites

Carbon nanotubes (CNTs) are being incorporated into structural composites to enhance material strength. During fabrication or repair activities, machining nanocomposites may release CNTs into the workplace air. An experimental study was conducted to evaluate the emissions generated by cutting and sanding on three types of epoxy-composite panels: Panel A containing graphite fibers, Panel B containing graphite fibers and carbon-based mat, and Panel C containing graphite fibers, carbon-based mat, and multi-walled CNTs. Aerosol sampling was conducted with direct-reading instruments, and filter samples were collected for measuring elemental carbon (EC) and fiber concentrations. Our study results showed that cutting Panel C with a band saw did not generate detectable emissions of fibers inspected by transmission electron microscopy but did increase the particle mass, number, and EC emission concentrations by 20% to 80% compared to Panels A and B. Sanding operation performed on two Panel C resulted in fiber emission rates of 1.9×10⁸ and 2.8×10⁶ fibers per second (f/s), while no free aerosol fibers were detected from sanding Panels A and B containing no CNTs. These free CNT fibers may be a health concern. However, the analysis of particle and EC concentrations from these same samples cannot clearly indicate the presence of CNTs, because extraneous aerosol generation from machining the composite epoxy material increased the mass concentrations of the EC.

Workplace Exposure to Titanium Dioxide Nanopowder Released from a Bag Filter System

Many researchers who use laboratory-scale synthesis systems to manufacture nanomaterials could be easily exposed to airborne nanomaterials during the research and development stage. This study used various real-time aerosol detectors to investigate the presence of nanoaerosols in a laboratory used to manufacture titanium dioxide (TiO₂). The TiO₂ nanopowders were produced via flame synthesis and collected by a bag filter system for subsequent harvesting. Highly concentrated nanopowders were released from the outlet of the bag filter system into the laboratory. The fractional particle collection efficiency of the bag filter system was only 20% at particle diameter of 100 nm, which is much lower than the performance of a high-efficiency particulate air (HEPA) filter. Furthermore, the laboratory hood system was inadequate to fully exhaust the air discharged from the bag filter system. Unbalanced air flow rates between bag filter and laboratory hood systems could result in high exposure to nanopowder in laboratory settings. Finally, we simulated behavior of nanopowders released in the laboratory using computational fluid dynamics (CFD).

Copper-based nanoparticles induce high toxicity in leukemic HL60 cells

From the increasing societal use of nanoparticles (NPs) follows the necessity to understand their potential toxic effects. This requires an in-depth understanding of the relationship between their physicochemical properties and their toxicological behavior. The aim of the present work was to study the toxicity of Cu and CuO NPs toward the leukemic cell line HL60. The toxicity was explored in terms of mitochondrial damage, DNA damage, oxidative DNA damage, cell death and reactive oxygen species (ROS) formation. Particle characteristics and copper release were specifically investigated in order to gain an improved understanding of prevailing toxic mechanisms. The Cu NPs revealed higher toxicity compared with both CuO NPs and dissolved copper (CuCl2), as well as a more rapid copper release compared with CuO NPs. Mitochondrial damage was induced by Cu NPs already after 2 h exposure. Cu NPs induced oxidation at high levels in an acellular ROS assay, and a small increase of intracellular ROS was observed. The increase of DNA damage was limited. CuO NPs did not induce any mitochondrial damage up to 6 h of exposure. No acellular ROS was induced by the CuO NPs, and the levels of intracellular ROS and DNA damage were limited after 2 h exposure. Necrosis was the main type of cell death observed after 18 h exposure to CuO NP and dissolved copper.

Effects of data sparsity and spatiotemporal variability on hazard maps of workplace noise

Personal sampling, considered a state-of-the-art technique to assess worker exposures to occupational hazards, is often conducted for the duration of a work shift so that time-weighted average (TWA) exposures may be evaluated relative to published occupational exposure limits (OELs). Such cross-shift measurements, however, provide little information on the spatial variability of exposures, except after a very large number of samples. Hazard maps, contour plots (or similar depiction) of hazard intensity throughout the workplace, have gained popularity as a way to locate sources and to visualize spatial variability of physical and chemical hazards within a facility. However, these maps are often generated from short duration measures and have little ability to assess temporal variability. To assess the potential bias that results from the use of short-duration measurements to represent the TWA in a hazard map, noise intensity measurements were collected at high spatial and temporal resolution in two facilities. Static monitors were distributed throughout the facility and used to capture the temporal variability at these locations. Roving monitors (typical of the hazard mapping process) captured spatial variability over multiple traverses through the facility. The differences in hazards maps generated with different sampling techniques were evaluated. Hazard maps produced from sparse, roving monitor data were in good agreement with the TWA hazard maps at the facility with low temporal variability. Estimated values were within 5 dB of the TWA over approximately 90% of the facility. However, at the facility with higher temporal variability, large differences between hazard maps were observed for different traverses through the facility. On the second day of sampling, estimates were at least 5 dB different than the TWA for more than half of the locations within the facility. The temporal variability of noise was found to have a greater influence on map accuracy than the spatial sampling resolution.

Assessment of two portable real-time particle monitors used in nanomaterial workplace exposure evaluations

Background

Nanoparticle emission assessment technique was developed to semi-quantitatively evaluate nanomaterial exposures and employs a combination of filter based samples and portable real-time particle monitors, including a condensation particle counter (CPC) and an optical particle counter (OPC), to detect nanomaterial releases. This laboratory study evaluated the results from CPC and OPC simultaneously measuring a polydisperse aerosol to assess their variability and accuracy.

Methods and Results

Two CPCs and two OPCs were used to evaluate a polydisperse sodium chloride aerosol within an enclosed chamber. The measurement results for number concentration versus time were compared between paired particle monitors of the same type, and to results from the Scanning Mobility Particle Spectrometer (SMPS) which was widely used to measure concentration of size-specific particles. According to analyses by using the Bland-Altman method, the CPCs displayed a constant mean percent difference of −3.8% (95% agreement limits: −9.1 to 1.6%; range of 95% agreement limit: 10.7%) with the chamber particle concentration below its dynamic upper limit (100,000 particles per cubic centimeter). The mean percent difference increased from −3.4% to −12.0% (range of 95% agreement limits: 7.1%) with increasing particle concentrations that were above the dynamic upper limit. The OPC results showed the percent difference within 15% for measurements in particles with size ranges of 300 to 500 and 500 to 1000 regardless of the particle concentration. Compared with SMPS measurements, the CPC gave a mean percent difference of 22.9% (95% agreement limits: 10.5% to 35.2%); whereas the measurements from OPC were not comparable.

Conclusions

This study demonstrated that CPC and OPC are useful for measuring nanoparticle exposures but the results from an individual monitor should be interpreted based upon the instrument's technical parameters. Future research should challenge these monitors with particles of different sizes, shapes, or composition, to determine measurement comparability and accuracy across various workplace nanomaterials.

Evaluation of a diffusion charger for measuring aerosols in a workplace

The model DC2000CE diffusion charger from EcoChem Analytics (League City, TX, USA) has the potential to be of considerable use to measure airborne surface area concentrations of nanoparticles in the workplace. The detection efficiency of the DC2000CE to reference instruments was determined with monodispersed spherical particles from 54 to 565.7 nm. Surface area concentrations measured by a DC2000CE were then compared to measured and detection efficiency adjusted reference surface area concentrations for polydispersed aerosols (propylene torch exhaust, incense, diesel exhaust, and Arizona road dust) over a range of particle sizes that may be encountered in a workplace. The ratio of surface area concentrations measured by the DC2000CE to that measured with the reference instruments for unimodal and multimodal aerosols ranged from 0.02 to 0.52. The ratios for detection efficiency adjusted unimodal and multimodal surface area concentrations were closer to unity (0.93-1.19) for aerosols where the majority of the surface area was within the size range of particles used to create the correction. A detection efficiency that includes the entire size range of the DC2000CE is needed before a calibration correction for the DC2000CE can be created. For diesel exhaust, the DC2000CE retained a linear response compared to reference instruments up to 2500 mm(2) m(-3), which was greater than the maximum range stated by the manufacturer (1000 mm(2) m(-3)). Physical limitations with regard to DC2000CE orientation, movement, and vibration were identified. Vibrating the DC2000CE while measuring aerosol concentrations may cause an increase of ~35 mm(2) m(-3), whereas moving the DC2000CE may cause concentrations to be inflated by as much as 400 mm(2) m(-3). Depending on the concentration of the aerosol of interest being measured, moving or vibrating a DC2000CE while measuring the aerosol should be avoided.

A novel method for assessing respiratory deposition of welding fume nanoparticles

Welders are exposed to high concentrations of nanoparticles. Compared to larger particles, nanoparticles have been associated with more toxic effects at the cellular level, including the generation of more reactive oxygen species activity. Current methods for welding-fume aerosol exposures do not differentiate between the nano-fraction and the larger particles. The objectives of this work are to establish a method to estimate the respiratory deposition of the nano-fraction of selected metals in welding fumes and test this method in a laboratory setting. Manganese (Mn), Nickel (Ni), Chromium (Cr), and hexavalent chromium (Cr(VI)) are commonly found in welding fume aerosols and have been linked with severe adverse health outcomes. Inductively coupled plasma mass spectrometry (ICP-MS) and ion chromatography (IC) were evaluated as methods for analyzing the content of Mn, Ni, Cr, and Cr(VI) nanoparticles in welding fumes collected with nanoparticle respiratory deposition (NRD) samplers. NRD samplers collect nanoparticles at deposition efficiencies that closely resemble physiological deposition in the respiratory tract. The limits of detection (LODs) and quantitation (LOQs) for ICP-MS and IC were determined analytically. Mild and stainless steel welding fumes generated with a robotic welder were collected with NRD samplers inside a chamber. LODs (LOQs) for Mn, Ni, Cr, and Cr(VI) were 1.3 μg (4.43 μg), 0.4 μg (1.14 μg), 1.1 μg (3.33 μg), and 0.4 μg (1.42 μg), respectively. Recovery of spiked samples and certified welding fume reference material was greater than 95%. When testing the method, the average percentage of total mass concentrations collected by the NRD samplers was ~30% for Mn, ~50% for Cr, and ~60% for Ni, indicating that a large fraction of the metals may lie in the nanoparticle fraction. This knowledge is critical to the development of toxicological studies aimed at finding links between exposure to welding fume nanoparticles and adverse health effects. Future work will involve the validation of the method in workplace settings. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: Digestion, extraction, and analysis procedures for nylon mesh screens.].

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.

Comparison of the DiSCmini aerosol monitor to a handheld condensation particle counter and a scanning mobility particle sizer for submicrometer sodium chloride and metal aerosols

We evaluated the robust, lightweight DiSCmini (DM) aerosol monitor for its ability to measure the concentration and mean diameter of submicrometer aerosols. Tests were conducted with monodispersed and polydispersed aerosols composed of two particle types (sodium chloride [NaCl] and spark-generated metal particles, which simulate particles found in welding fume) at three different steady-state concentration ranges (Low, <10(3); Medium, 10(3)-10(4); and High, >10(4) particles/cm(3)). Particle number concentration, lung deposited surface area (LDSA) concentration, and mean size measured with the DM were compared with those measured with reference instruments, a scanning mobility particle sizer (SMPS), and a handheld condensation particle counter (CPC). Particle number concentrations measured with the DM were within 16% of those measured by the CPC for polydispersed aerosols. Poorer agreement was observed for monodispersed aerosols (±35% for most tests and +101% for 300-nm NaCl). LDSA concentrations measured by the DM were 96% to 155% of those estimated with the SMPS. The geometric mean diameters measured with the DM were within 30% of those measured with the SMPS for monodispersed aerosols and within 25% for polydispersed aerosols (except for the case when the aerosol contained a substantial number of particles larger than 300 nm). The accuracy of the DM is reasonable for particles smaller than 300 nm, but caution should be exercised when particles larger than 300 nm are present. [Supplementary materials are available for this article. Go to the publisher's online edition of the Journal of Occupational and Environmental Hygiene for the following free supplemental resources: manufacturer-reported capabilities of instruments used, and information from the SMPS measurements for polydispersed test particles.].

Case study. Health hazards of automotive repair mechanics: thermal and lighting comfort, particulate matter and noise

An indoor environmental quality survey was conducted in a small private automotive repair shop during May 2009 (hot season) and February 2010 (cold season). It was established that the detached building, which is naturally ventilated and lit, had all the advantages of the temperate local climate. It provided a satisfactory microclimatic working environment, concerning the thermal and the lighting comfort, without excessive energy consumption for air-conditioning or lighting. Indoor number concentrations of particulate matter (PM) were monitored during both seasons. Their size distributions were strongly affected by the indoor activities and the air exchange rate of the building. During working hours, the average indoor/outdoor (I/O) number concentration ratio was 31 for PM0.3-1 in the hot season and 69 for the cold season. However I/O PM1-10 number concentration ratios were similar, 33 and 32 respectively, between the two seasons. The estimated indoor mass concentration of PM10 for the two seasons was on average 0.68 mg m(-3) and 1.19 mg m(-3), i.e., 22 and 36 times higher than outdoors, during the hot and the cold seasons, respectively. This is indicative that indoor air pollution may adversely affect mechanics' health. Noise levels were highly variable and the average LEX, 8 h of 69.3 dB(A) was below the European Union exposure limit value 87db (A). Noise originated from the use of manual hammers, the revving up of engines, and the closing of car doors or hoods. Octave band analysis indicated that the prevailing noise frequencies were in the area of the maximum ear sensitivity.

Influence of analysis methods on interpretation of hazard maps

Exposure or hazard mapping is becoming increasingly popular among industrial hygienists. Direct-reading instruments used for hazard mapping of data collection are steadily increasing in reliability and portability while decreasing in cost. Exposure measurements made with these instruments generally require no laboratory analysis although hazard mapping can be a time-consuming process. To inform decision making by industrial hygienists and management, it is crucial that the maps generated from mapping data are as accurate and representative as possible. Currently, it is unclear how many sampling locations are necessary to produce a representative hazard map. As such, researchers typically collect as many points as can be sampled in several hours and interpolation methods are used to produce higher resolution maps. We have reanalyzed hazard-mapping data sets from three industrial settings to determine which interpolation methods yield the most accurate results. The goal is to provide practicing industrial hygienists with some practical guidelines to generate accurate hazard maps with 'off-the-shelf' mapping software. Visually verifying the fit of the variogram model is crucial for accurate interpolation. Exponential and spherical variogram models performed better than Gaussian models. It was also necessary to diverge from some of the default interpolation parameters such as the number of bins used for the experimental variogram and whether or not to allow for a nugget effect to achieve reasonable accuracy of the interpolation for some data sets.

Evaluation of Airborne Particle Emissions from Commercial Products Containing Carbon Nanotubes

The emission of the airborne particles from epoxy resin test sticks with different CNT loadings and two commercial products were characterized while sanding with three grit sizes and three disc sander speeds. The total number concentrations, respirable mass concentrations, and particle size number/mass distributions of the emitted particles were measured using a condensation particle counter, an optical particle counter, and a scanning mobility particle sizer. The emitted particles were sampled on a polycarbonate filter and analyzed using electron microscopy. The highest number concentrations (arithmetic mean = 4670 particles/cm(3)) were produced with coarse sandpaper, 2% (by weight) CNT test sticks and medium disc sander speed, whereas the lowest number concentrations (arithmetic mean = 92 particles/cm(3)) were produced with medium sandpaper, 2% CNT test sticks and slow disc sander speed. Respirable mass concentrations were highest (arithmetic mean = 1.01 mg/m(3)) for fine sandpaper, 2% CNT test sticks and medium disc sander speed and lowest (arithmetic mean = 0.20 mg/m(3)) for medium sandpaper, 0% CNT test sticks and medium disc sander speed. For CNT-epoxy samples, airborne particles were primarily micrometer-sized epoxy cores with CNT protrusions. No free CNTs were observed in airborne samples, except for tests conducted with 4% CNT epoxy. The number concentration, mass concentration, and size distribution of airborne particles generated when products containing CNTs are sanded depends on the conditions of sanding and the characteristics of the material being sanded.

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.

Investigation of Aerosol Surface Area Estimation from Number and Mass Concentration Measurements: Particle Density Effect

For nanoparticles with nonspherical morphologies, e.g., open agglomerates or fibrous particles, it is expected that the actual density of agglomerates may be significantly different from the bulk material density. It is further expected that using the material density may upset the relationship between surface area and mass when a method for estimating aerosol surface area from number and mass concentrations (referred to as "Maynard's estimation method") is used. Therefore, it is necessary to quantitatively investigate how much the Maynard's estimation method depends on particle morphology and density. In this study, aerosol surface area estimated from number and mass concentration measurements was evaluated and compared with values from two reference methods: a method proposed by Lall and Friedlander for agglomerates and a mobility based method for compact nonspherical particles using well-defined polydisperse aerosols with known particle densities. Polydisperse silver aerosol particles were generated by an aerosol generation facility. Generated aerosols had a range of morphologies, count median diameters (CMD) between 25 and 50 nm, and geometric standard deviations (GSD) between 1.5 and 1.8. The surface area estimates from number and mass concentration measurements correlated well with the two reference values when gravimetric mass was used. The aerosol surface area estimates from the Maynard's estimation method were comparable to the reference method for all particle morphologies within the surface area ratios of 3.31 and 0.19 for assumed GSDs 1.5 and 1.8, respectively, when the bulk material density of silver was used. The difference between the Maynard's estimation method and surface area measured by the reference method for fractal-like agglomerates decreased from 79% to 23% when the measured effective particle density was used, while the difference for nearly spherical particles decreased from 30% to 24%. The results indicate that the use of particle density of agglomerates improves the accuracy of the Maynard's estimation method and that an effective density should be taken into account, when known, when estimating aerosol surface area of nonspherical aerosol such as open agglomerates and fibrous 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.

Developing korean standard for nanomaterial exposure assessment

Nanotechnology is now applied to many industries, resulting in wide range of nanomaterial-containing products, such as electronic components, cosmetic, medicines, vehicles, and home appliances. Nanoparticles can be released throughout the life cycle of nanoproducts, including the manufacture, consumer use, and disposal, thereby involving workers, consumers, and the environment in potential exposure. However, there is no current consensus on the best sampling method for characterizing manufactured-nanoparticle exposure. Therefore, this report aims to provide a standard method for assessing nanoparticle exposure, including the identification of nanoparticle emission, the assessment of worker exposure, and the evaluation of exposure mitigation actions in nanomaterial-handling workplaces or research institutes.

Particle mapping in stables at an American Thoroughbred racetrack

REASONS FOR PERFORMING STUDY

Airway inflammation and mucus in the trachea are common in racehorses. Fine airborne particles can initiate and coarse particles can worsen airway inflammation in man and in animal models of airway disease. The regional and seasonal distribution of particles of different sizes has never been investigated in American racing stables.

OBJECTIVES

To determine the regional and seasonal concentration and number of airborne particles of different sizes in racing stables.

METHODS

Direct reading instruments were used to determine the mass concentration and numbers of particles 3 times daily (early morning, midday and late afternoon) in July, September and November, in 3 different racing stables.

RESULTS

Average particle concentrations were lowest in July and highest in September and November. Early morning concentrations were significantly higher than those measured throughout the rest of the day. The completely enclosed stable with little natural ventilation, had significantly higher particulate concentrations than the open-sided stable. With regard to numbers of particles, those 2-5 µm were greatest in July and least in November; those 0.5-1.0 µm were greatest in September and least in November. Location of stall within stable also affected concentrations and numbers.

CONCLUSIONS

The concentration and number of particles in sizes known to reach the lower airways varies with stable design/management, time of day, season of year and location of the stall within the stable.

POTENTIAL RELEVANCE

Particle mapping is a useful tool in the identification of stables, season, and location of stalls within stables where horses may be at greater risk of exposure to offending particulates.

Airborne nanoparticle concentrations in the manufacturing of polytetrafluoroethylene (PTFE) apparel

One form of waterproof, breathable apparel is manufactured from polytetrafluoroethylene (PTFE) membrane laminated fabric using a specific process to seal seams that have been sewn with traditional techniques. The sealing process involves applying waterproof tape to the seam by feeding the seam through two rollers while applying hot air (600 °C). This study addressed the potential for exposure to particulate matter from this sealing process by characterizing airborne particles in a facility that produces more than 1000 lightweight PTFE rain jackets per day. Aerosol concentrations throughout the facility were mapped, breathing zone concentrations were measured, and hoods used to ventilate the seam sealing operation were evaluated. The geometric mean (GM) particle number concentrations were substantially greater in the sewing and sealing areas (67,000 and 188,000 particles cm⁻³)) compared with that measured in the office area (12,100 particles cm⁻³). Respirable mass concentrations were negligible throughout the facility (GM = 0.002 mg m⁻³) in the sewing and sealing areas). The particles exiting the final discharge of the facility's ventilation system were dominated by nanoparticles (number median diameter = 25 nm; geometric standard deviation of 1.39). The breathing zone particle number concentrations of the workers who sealed the sewn seams were highly variable and significantly greater when sealing seams than when conducting other tasks (p < 0.0001). The sealing workers' breathing zone concentrations ranged from 147,000 particles cm⁻³ to 798,000 particles cm⁻³, and their seam responsibility significantly influenced their breathing zone concentrations (p = 0.03). The finding that particle number concentrations were approximately equal outside the hood and inside the local exhaust duct indicated poor effectiveness of the canopy hoods used to ventilate sealing operations.

Mapping particulate matter at the body weld department in an automobile assembly plant

A respiratory health survey conducted in an assembly plant in 2000-2001 found that welders had elevated rates of self-reported respiratory symptoms compared with painters and assembly workers. Subsequently, the ventilation system was improved at the body weld department. In a follow-up study, particle spatial distributions were analyzed, following a mapping protocol developed specifically for this workplace, to evaluate the effectiveness of the changes. Significant temporal and spatial variations were observed. Temporal variation during a shift was monitored with over-shift stationary sampling at fixed locations. Spatial variation was evaluated with 1-min time-weighted average particle concentrations measured throughout the process areas (212 locations). The arithmetic spatial mean across 212 locations for the respirable particles varied from 305 microg/m(3) to 501 microg/m(3) on 6 sampled days, with a standard deviation of 71 microg/m(3), indicating that the difference between before and after countermeasures must be at least 191 microg/m(3) to be considered statistically significant at the given sample sizes. The available data were not sufficient to evaluate the reduction of the particle concentrations after the countermeasures. The map of particle mass concentration revealed several high concentration areas, requiring further investigation and potentially higher level of controls. Resistance welding needed to be effectively controlled, as it could be the major particle emitting sources in the facility. The map of submicrometer (0.014 microm to 1.0 microm) particle count concentration presented different patterns from that of respirable particle mass concentration, indicating that the submicrometer particles tended to be more evenly distributed over the process areas. Workers not in proximity to intensive welding operations might be exposed to fine particles at levels higher than had traditionally been thought. Mapping was demonstrated to be an effective method to assess particle spatial distributions. A well-designed sampling protocol is critical to achieving the specific aims of a mapping study.

Use of a condensation particle counter and an optical particle counter to assess the number concentration of engineered nanoparticles

There is a need to evaluate nanoparticle (< 100 nm) exposures in occupational settings. However, portable instruments do not size segregate particles in that size range. A proxy method for determining nanoparticle count concentrations involves subtracting counts made with a condensation particle counter (CPC) from those of an optical particle counter/sizer (OPC), resulting in an estimation of "very fine" particles < 300 nm, where 300 nm is the OPC lower detection limit. However, to determine size distributions from which particles < 100 nm may be estimated, the resulting count of particles < 300 nm can be used as an additional channel of count data in addition to those obtained from the OPC. To test these methods, the very fine number concentrations determined using a CPC and OPC were compared with those from SMPS measurements and were used to verify the accuracy of a very fine particle number concentration determined by an OPC and CPC. Two "size-distribution" methods, weighted-average and log-probit, were applied to reproduce particle size distributions from OPC and CPC data and were then evaluated relative to their ability to accurately estimate the nanoparticle number concentrations. Various engineered nanoparticles were used to create test aerosols, including titanium dioxide (TiO(2)), silicon dioxide (SiO(2)), and iron oxide (Fe(2)O(3)). These materials were chosen because of their different refractive indices and therefore may be measured differently by the OPC. The count-difference method was able to estimate very fine particle number concentrations with an error between 10.9 to 58.4%. In estimating nanoparticle number concentrations using the size-distribution methods, the log-probit method resulted in the lowest percent errors that ranged from -42% to 1023%. Percent error was lower than the instrument manufacturer's indicated level of accuracy when the test aerosol refractive index was similar to that used for OPC calibration standards. Accuracy could be increased if there was an increase in the size resolution for number concentrations measured by the CPC of very fine particles and mitigation of optical effects.

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

Measurements using several exposure metrics were carried out in a restaurant and a die casting plant to compare the spatial distributions of particle surface area (SA), number, and mass concentrations and rank exposures in different areas by those metrics. The different exposure metrics for incidental nanoparticle and fine particle exposures were compared using the concentration rankings, statistical differences between areas, and concentration ratios between different areas. In the die casting plant, area concentration rankings and spatial distributions differed by the exposure metrics chosen. Surface area and fine particle number concentrations were greatest near incidental nanoparticle sources and were significantly different between three areas. However, mass and coarse particle number concentrations were similar throughout the facility, and rankings of the work areas based on these metrics were different from those of SA and fine number concentrations. In the restaurant, concentrations in the kitchen for all metrics except respirable mass concentration were significantly greater than in the serving area, although SA and fine particle number concentrations showed larger differences between the two areas than either the mass or coarse particle number concentrations. Thus, the choice of appropriate exposure metric has significant implications for exposure groupings in epidemiologic and occupational exposure studies.

Comparing exposure zones by different exposure metrics using statistical parameters: contrast and precision

Recently, the appropriateness of using the 'mass concentration' metric for ultrafine particles has been questioned and surface area (SA) or number concentration metrics has been proposed as alternatives. To assess the abilities of various exposure metrics to distinguish between different exposure zones in workplaces with nanoparticle aerosols, exposure concentrations were measured in preassigned 'high-' and 'low-'exposure zones in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory using SA, number, and mass concentration metrics. Predetermined exposure classifications were compared by each metric using statistical parameters and concentration ratios that were calculated from the different exposure concentrations. In the restaurant, SA and fine particle number concentrations showed significant differences between the high- and low-exposure zones and they had higher contrast (the ratio of between-zone variance to the sum of the between-zone and within-zone variances) than mass concentrations. Mass concentrations did not show significant differences. In the die cast facility, concentrations of all metrics were significantly greater in the high zone than in the low zone. SA and fine particle number concentrations showed larger concentration ratios between the high and low zones and higher contrast than mass concentrations. None of the metrics were significantly different between the high- and low-exposure zones in the diesel engine laboratory. The SA and fine particle number concentrations appeared to be better at differentiating exposure zones and finding the particle generation sources in workplaces generating nanoparticles. Because the choice of an exposure metric has significant implications for epidemiologic studies and industrial hygiene practice, a multimetric sampling approach is recommended for nanoparticle exposure assessment.

Aerosol monitoring during carbon nanofiber production: mobile direct-reading sampling

Detailed investigations were conducted at a facility that manufactures and processes carbon nanofibers (CNFs). Presented research summarizes the direct-reading monitoring aspects of the study. A mobile aerosol sampling platform, equipped with an aerosol instrument array, was used to characterize emissions at different locations within the facility. Particle number, respirable mass, active surface area, and photoelectric response were monitored with a condensation particle counter (CPC), a photometer, a diffusion charger, and a photoelectric aerosol sensor, respectively. CO and CO₂ were additionally monitored. Combined simultaneous monitoring of these metrics can be utilized to determine source and relative contribution of airborne particles (CNFs and others) within a workplace. Elevated particle number concentrations, up to 1.15 × 10⁶ cm⁻³, were found within the facility but were not due to CNFs. Ultrafine particle emissions, released during thermal treatment of CNFs, were primarily responsible. In contrast, transient increases in respirable particle mass concentration, with a maximum of 1.1 mg m⁻³, were due to CNF release through uncontrolled transfer and bagging. Of the applied metrics, our findings suggest that particle mass was probably the most useful and practical metric for monitoring CNF emissions in this facility. Through chemical means, CNFs may be selectively distinguished from other workplace contaminants (Birch et al., in preparation), and for direct-reading monitoring applications, the photometer was found to provide a reasonable estimate of respirable CNF mass concentration. Particle size distribution measurements were conducted with an electrical low-pressure impactor and a fast particle size spectrometer. Results suggest that the dominant CNF mode by particle number lies between 200 and 250 nm for both aerodynamic and mobility equivalent diameters. Significant emissions of CO were also evident in this facility. Exposure control recommendations were described for processes as required.

Nanoparticle Emission Assessment Technique (NEAT) for the identification and measurement of potential inhalation exposure to engineered nanomaterials--Part B: Results from 12 field studies

The National Institute for Occupational Safety and Health (NIOSH) conducted field studies at 12 sites using the Nanoparticle Emission Assessment Technique (NEAT) to characterize emissions during processes where engineered nanomaterials were produced or used. A description of the NEAT appears in Part A of this issue. Field studies were conducted in research and development laboratories, pilot plants, and manufacturing facilities handling carbon nanotubes (single-walled and multi-walled), carbon nanofibers, fullerenes, carbon nanopearls, metal oxides, electrospun nylon, and quantum dots. The results demonstrated that the NEAT was useful in evaluating emissions and that readily available engineering controls can be applied to minimize nanomaterial emissions.

A comprehensive review of the literature on exposure to metalworking fluids

An extensive literature review was conducted of studies with exposure measurements to metalworking fluids (MWFs). A database of 155 arithmetic means based on 9379 aerosol measurements from published studies was compiled. Weighted arithmetic means (WAMs) and their variance calculated across studies were summarized based on decade (prior to 1970s through 2000s), industry (auto, auto parts, small job shops, and others), operation (grinding and machining), and fluid type (straight, soluble, synthetic, and semisynthetic). Total mass and total extractable mass measurements that were simultaneously collected were compared. Average concentrations by size fractions and mass median aerodynamic diameters (MMADs) were also analyzed. Analysis of the WAMs indicated a reduction in exposure levels over time regardless of industry or type of operation or fluid, with mean levels prior to the 1970s of 5.4 mg/m(3), which dropped to 2.5 mg/m(3) in the 1970s, to 1.2 mg/m(3) in the 1980s, and to 0.5 mg/m(3) in the 1990s. No further reduction was seen in the 2000s. A comparison by industry, operation, and fluid type found no consistent patterns in the measurement results. The percent extractable mass in the total aerosol samples varied by fluid type, with an average 84% in straight fluids, 58% in synthetic fluids, 56% in soluble fluids, and 42% in the semisynthetic fluids. Exposure means from the thoracic fraction (0.3-0.5 mg/m(3)) were slightly less than those for total aerosol for both the 1990s and 2000s, the only decades for which thoracic data were available. Respirable means did not change from the 1980s to the 2000s (generally about 0.2-0.3 mg/m(3)). The MMADs of the MWF aerosols averaged 4-6 microm. These measurement data indicate a clear reduction of exposure levels over time. They will be used for the retrospective assessment of exposure levels to MWFs in a population-based, case-control study of bladder cancer.

Ultrafine particle characteristics in seven industrial plants

Ultrafine particles are considered as a possible cause of some of the adverse health effects caused by airborne particles. In this study, the particle characteristics were measured in seven Swedish industrial plants, with a special focus on the ultrafine particle fraction. Number concentration, size distribution, surface area concentration, and mass concentration were measured at 10 different job activities, including fettling, laser cutting, welding, smelting, core making, moulding, concreting, grinding, sieving powders, and washing machine goods. A thorough particle characterization is necessary in workplaces since it is not clear yet which choice of ultrafine particle metric is the best to measure in relation to health effects. Job activities were given a different order of rank depending on what particle metric was measured. An especially high number concentration (130 x 10(3) cm(-3)) and percentage of ultrafine particles (96%) were found at fettling of aluminium, whereas the highest surface area concentration (up to 3800 mum(2) cm(-3)) as well as high PM10 (up to 1 mg m(-3)) and PM1 (up to 0.8 mg m(-3)) were found at welding and laser cutting of steel. The smallest geometric mean diameter (22 nm) was found at core making (geometric standard deviation: 1.9).

Determinants of exposure to metalworking fluid aerosols: a literature review and analysis of reported measurements

An extensive literature review of published metalworking fluid (MWF) aerosol measurement data was conducted to identify the major determinants that may affect exposure to aerosol fractions (total or inhalable, thoracic and respirable) and mass median diameters (MMDs). The identification of determinants was conducted through published studies and analysis of published measurement levels. For the latter, weighted arithmetic means (WAMs) by number of measurements were calculated and compared using analysis of variance and t-tests. The literature review found that the major factors affecting aerosol exposure levels were, primarily, decade, type of industry, operation and fluid and engineering control measures. Our analysis of total aerosol levels found a significant decline in measured levels from an average of 5.36 mg m(-3) prior to the 1970s and 2.52 mg m(-3) in the 1970s to 1.21 mg m(-3) in the 1980s, 0.50 mg m(-3) in the 1990s and 0.55 mg m(-3) in the 2000s. Significant declines from the 1990s to the 2000s also were found in thoracic fraction levels (0.48 versus 0.40 mg m(-3)), but not for the respirable fraction. The WAMs for the auto (1.47 mg m(-3)) and auto parts manufacturing industry (1.83 mg m(-3)) were significantly higher than that for small-job machine shops (0.68 mg m(-3)). In addition, a significant difference in the thoracic WAM was found between the automotive industry (0.46 mg m(-3)) and small-job machine shops (0.32 mg m(-3)). Operation type, in particular, grinding, was a significant factor affecting the total aerosol fraction [grinding operations (1.75 mg m(-3)) versus other machining (0.95 mg m(-3))], but the levels associated with these operations were not statistically different for either the thoracic or the respirable fractions. Across all decades, the total aerosol fraction for straight oils (1.49 mg m(-3)) was higher than for other fluid types (soluble = 1.08 mg m(-3), synthetic = 0.52 mg m(-3) and semisynthetic = 0.50 mg m(-3)). Fluid type was also found to be partly associated with differences in the respirable fraction level. We found that the total aerosols were measured by a variety of sampling media, devices and analytical methods. This diversity of approaches makes interpretation of the study results difficult. In conclusion, both the literature review and the measurement data analyzed found that decade and type of industry, operation and fluid were important determinants of total aerosol exposure. Industry type and fluid type were associated with differences in exposure to the thoracic and respirable fraction levels, respectively.

Airborne monitoring to distinguish engineered nanomaterials from incidental particles for environmental health and safety

Two methods were used to distinguish airborne engineered nanomaterials from other airborne particles in a facility that produces nano-structured lithium titanate metal oxide powder. The first method involved off-line analysis of filter samples collected with conventional respirable samplers at each of seven locations (six near production processes and one outdoors). Throughout most of the facility and outdoors, respirable mass concentrations were low (<0.050 mg/m(3)) and were attributed to particles other than the nanomaterial (<10% by mass titanium determined with inductively coupled plasma atomic emission spectrometry). In contrast, in a single area with extensive material handling, mass concentrations were greatest (0.118 mg m(-3)) and contained up to 39% +/- 11% lithium titanium, indicating the presence of airborne nanomaterial. Analysis of the filter samples collected in this area by transmission electron microscope and scanning electron microscope revealed that the airborne nanomaterial was associated only with spherical aggregates (clusters of fused 10-80 nm nanoparticles) that were larger than 200 nm. This analysis also showed that nanoparticles in this area were the smallest particles of a larger distribution of submicrometer chain agglomerates likely from welding in an adjacent area of the facility. The second method used two, hand-held, direct-reading, battery-operated instruments to obtain a time series of very fine particle number (<300 nm), respirable mass, and total mass concentration, which were then related to activities within the area of extensive material handling. This activity-based monitoring showed that very fine particle number concentrations (<300 nm) had no apparent correlation to worker activities, but that sharp peaks in the respirable and total mass concentration coincided with loading a hopper and replacing nanomaterial collection bags. These findings were consistent with those from the filter-based method in that they demonstrate that airborne nanoparticles in this facility are dominated by "incidental" sources (e.g., welding or grinding), and that the airborne "engineered" product is predominately composed of particles larger than several hundred nanometers. The methods presented here are applicable to any occupational or environmental setting in which one needs to distinguish incidental sources from engineered product.

Relationships among particle number, surface area, and respirable mass concentrations in automotive engine manufacturing

This study investigated the relationships between particle number, surface area, and respirable mass concentration measured simultaneously in a foundry and an automotive engine machining and assembly center. Aerosol concentrations were measured throughout each plant with a condensation particle counter for number concentration, a diffusion charger for active surface area concentration, and an optical particle counter for respirable mass concentration. At selected locations, particle size distributions were characterized with the optical particle counter and an electrical low pressure impactor. Statistical analyses showed that active surface area concentration was correlated with ultrafine particle number concentration and weakly correlated with respirable mass concentration. Correlation between number and active surface area concentration was stronger during winter (R2 = 0.6 for both plants) than in the summer (R2 = 0.38 and 0.36 for the foundry and engine plant respectively). The stronger correlation in winter was attributed to use of direct-fire gas fired heaters that produced substantial numbers of ultrafine particles with a modal diameter between 0.007 and 0.023 mu m. These correlations support findings obtained through theoretical analysis. Such analysis predicts that active surface area increasingly underestimates geometric surface area with increasing particle size, particularly for particles larger than 100 nm. Thus, a stronger correlation between particle number concentration and active surface area concentration is expected in the presence of high concentrations of ultrafine particles. In general, active surface area concentration may be a concentration metric that is distinct from particle number concentration and respirable mass concentration. For future health effects or toxicological studies involving nano-materials or ultrafine aerosols, this finding needs to be considered, as exposure metrics may influence data interpretation.

Occupational risk management of engineered nanoparticles

The earliest and most extensive societal exposures to engineered nanoparticles are likely to occur in the workplace. Until toxicologic and health effects research moves forward to characterize more broadly the potential hazards of nanoparticles and to provide a scientific basis for appropriate control of nanomaterials in the workplace, current and future workers may be at risk from occupational exposures. This article reviews a conceptual framework for occupational risk management as applied to engineered nanomaterials and describes an associated approach for controlling exposures in the presence of uncertainty. The framework takes into account the potential routes of exposure and factors that may influence biological activity and potential toxicity of nanomaterials; incorporates primary approaches based on the traditional industrial hygiene hierarchy of controls involving elimination or substitution, engineering controls, administrative controls, and use of personal protective equipment; and includes valuable secondary approaches involving health surveillance and medical monitoring.