Samples of the respirable fraction of airborne particles to which workers are exposed are an important component of many health protection programs, especially in those workplaces where there is a risk of health problems from exposure to respirable crystalline silica. The most common technique for size-selection of the respirable dust fraction is to use a miniature cyclone preselector, many of which are based on the "Higgens-Dewell" (HD) design. A variant of the HD cyclone, commonly referred to as the "aluminum (or aluminium) cyclone," was developed in Scandinavia. Early work showed that a flow rate of 2.2 l min-1 would be appropriate to meet the size-separation convention standardized under the International Organization for Standardization (ISO), while a later, non-peer-reviewed study suggested 2.5 l min-1 and this flow rate is currently recommended by the manufacturers. The International Sampler Comparison Group is working on revising the European Standard EN13205 on sampler performance testing for consideration as an ISO standard. In this work, 5 aluminum cyclone units were tested at 2.5 l min-1 and the cyclones were further tested at 2.3 and 2.2 l min-1 to determine the optimal flow rate. While the flow rate of 2.3 l min-1 had the lowest overall mean bias, a flow rate of 2.2 l min-1 gave bias <±10% over the whole area of size distributions of interest. This supports earlier findings and suggests that 2.2 l min-1 is the most accurate flow rate for sampling with the aluminum cyclone. However, 2.3 l min-1 also meets the specification of EN13205 in that the area of bias >±10% is minimal. The consequence of continuing to use the aluminum cyclone at 2.5 l min-1 is an underestimate of respirable particles when compared with the ISO convention.

The quantification of crystalline silica (quartz) in materials helps communicate the potential risk of exposure when the materials are then included in a work process that could generate an aerosol of particulate. Although many analytical laboratories have developed procedures for quantification of quartz in bulk samples, these procedures are not standardized and are generally limited to their individual needs. Therefore, the International Standards Organization (ISO) working group for silica measurement (ISO/TC146/SC2/WG7 Silica) developed an international standard that describes 3 analytical methods for the determination of quartz in bulk samples by X-ray diffraction (XRD): the external standard method for samples prepared on filters, the internal standard method, and the spiking method. This paper describes the results of an interlaboratory measurement comparison in which the 3 XRD standardized methods were evaluated to verify if the 3 methods produce results that agree with each other. Simple analytical systems, represented by 4 binary mixtures of quartz added to another mineral, were prepared. Sub-samples of the 4 test powders were delivered to the 7 participating laboratories from 6 countries that agreed to participate in this study. The precision of each measurement method, calculated as a percentage of quartz weight within the range 10 to 16 wt%, was similar for the 3 XRD methods. The repeatability SDs, sr, ranged between 0.4 and 0.8 (relative SD, RSDr, between 4.3% and 8.7%) for thin specimens on filter, 0.4 to 1.1 (RSDr between 4.2% and 10.6%) for the internal standard method, and 0.3 to 1.2 (RSDr between 3.7% and 11.9%) for the spiking method. The reproducibility SDs, sR, of the results in the studied wt% range were between 1.1 and 2.1 (RSDR between 12.7% and 21.5%) for the method of thin specimen on filter, 1.1 to 1.4 (RSDR between 7.5% and 14.1%) for the internal standard method and 1.1 to 2.6 (RSDR between 9.5% and 23.7%) for the spiking method. These methods obtained equivalent results at 2 concentration levels of 10% and 16% in these binary mixtures. A further step of interlaboratory testing should be implemented to investigate the performance of the 3 methods at the lower quartz concentration values.

Abstract Introduction The aim of this study is to present a step-by-step process that walks through the conceptualization and building of a low-cost (~ $150) monitoring device for airborne fine particulate matter (PM2.5), based on miniaturized sensors and components. Methodology Details on the implementation of the hardware and software are provided which facilitate the data acquisition and analysis. The central components and their setup discussed in what follows include: the sensor device (called “P.ALP” – Ph.D. Air quality Low-cost Project), Arduino IDE (Integrated Development Environment) and R code (open-access software). The devices were tested for accuracy and precision under controlled conditions (type of dust, dust concentrations, temperature, relative humidity) using an aerosol testing chamber (Marple design). Results A monitoring device for PM2.5, based on low-cost sensors and technologies was successfully conceptualized, designed, and implemented. The preliminary tests showed promising results in detecting dust concentration variability and satisfying performances in terms of data storage and operating time. Conclusions The P.ALP monitoring system was designed and developed to be a basic device, which can be further customized and implemented using the wide range of low-cost sensors available on the market.

To improve worker health protection and support engineering applications in underground mines, such as ventilation-on-demand, capabilities are increasingly sought for continuous monitoring of diesel particulate matter (DPM). For near real-time monitoring over periods up to a full workshift, the FLIR Airtec handheld monitor was developed and calibrated to the NIOSH Standard Method 5040 measure of elemental carbon (EC), which is commonly used as an analytical surrogate for DPM. However, needs still exist for autonomous monitoring over longer periods (e.g., weeks to months). To meet those needs, two commercially available instruments are considered here, the Magee Scientific AE33 Aethalometer and the Sunset Laboratory Semi-continuous OC-EC Field Analyzer. Along with a prototyped monitor called the Airwatch, these were tested head-to-head against the Method 5040 EC and the Airtec in a controlled laboratory setting; and against one another in a field study at an underground mine. Key findings include: the OC-EC field analyzer performed well across a wide range of EC concentrations; the AE33 performed well at relatively low concentrations, but modifications or additional data corrections are likely needed at higher concentrations; and the Airwatch showed good potential, though significant improvements will be required if this instrument is to be further developed, including resolution of several mechanical issues and selection of an appropriate filter material and development of robust data corrections. Moreover, the relative advantages and disadvantages associated with each instrument (e.g., in terms of data quality, complexity and maintenance) must be considered in the context of the intended application and sampling environment.

The PDM3600 and PDM3700 are two closely related person-wearable dust monitors manufactured by Thermo Fisher Scientific. Both are based on tapered element oscillating microbalance technology and provide nearly real-time, mass-based readings of respirable dust concentrations. From a monitoring perspective, the primary difference between the models is the PDM3600 has an integrated cap lamp with attached inlet, while the PDM3700 has no cap lamp and a revised inlet attaches to the worker’s lapel. Using coals of varied origin and employing a wide range of concentrations, side-by-side measurements from these instruments were collected under controlled laboratory conditions and then compared. By use of ordinary least squares and weighted least squares regression methods, followed by mixed model analysis, results suggest there is no statistically significant or practical difference in instrument performance. The two monitors are equivalent for the field dust concentration measurements for which they were designed.

A worker’s personal exposure to respirable dust in occupational environments has traditionally been monitored using established methodologies which entail the collection of an 8-h representative sample that is sent away for laboratory analysis. While these methods are very accurate, they only provide information on the average exposure during a specific time period, generally a worker’s shift. The availability of relatively inexpensive aerosol sensors can allow researchers and practitioners to generate real-time data with unprecedented spatial and temporal granularity. Low-cost dust monitors (LCDM) were developed and marketed for air pollution monitoring and are mostly being used to help communities understand their local and even hyper-local air quality. Most of these integrated sensing packages cost less than 300 per unit, in contrast to wearable or area dust monitors specifically built for mining applications which have been around for decades but still average around5000 each. At the National Institute for Occupational Safety and Health (NIOSH), we are leveraging the power of high-volume data collection from networks of LCDM to establish baseline respirable hazard levels and to monitor for changes on a seasonal basis as well as following any application of control technologies. We have seen the effective use and advantages of monitoring live data before, during, and after events like shift changes, operational changes, ventilation upgrades, adverse weather events, and machine maintenance. However, many factors have prevented a systematic adoption of LCDMs for exposure monitoring: concern for their analytical performance, the complexity of use, and lack of understanding of their value are some factors. This contribution outlines a 1-year case study at a mine in Wisconsin, USA, covering the installation, maintenance, data visualizations, and collaboration between NIOSH researchers and the industrial hygiene professionals at the mine.

This study aimed to assess the performance, in terms of precision and accuracy, of a prototype (called “P.ALP”—Ph.D. Air Quality Low-cost Project) developed for monitoring PM2.5 concentration levels. Four prototypes were co-located with reference instrumentation in four different microenvironments simulating real-world and working conditions, namely (i) office, (ii) home, (iii) outdoor, and (iv) occupational environments. The devices were evaluated for a total of 20 monitoring days (approximately 168 h) under a wide range of PM2.5 concentrations. The performances of the prototypes (based on the light-scattering working principle) were tested through different statistical methods. After the data acquisition and data cleaning processes, a linear regression analysis was performed to assess the precision (by comparing all possible pairs of devices) and the accuracy (by comparing the prototypes against the reference instrumentation) of the P.ALP. Moreover, the United States Environmental Protection Agency (US EPA) criteria were applied to assess the possible usage of this instrumentation, and to evaluate the eventual error trends of the P.ALP in the data storage process, Bland–Altman plots were also adopted. The outcomes of this study underlined that the P.ALP performed differently depending on the microenvironment in which it was tested and, consequently, on the PM2.5 concentrations. The device can monitor PM2.5 variations with acceptable results, but the performance cannot be considered satisfactory at extremely low and remarkably high PM2.5 concentrations. Thanks to modular components and open-source software, the tested device has the potential to be customized and adapted to better fit specific study design needs, but it must be implemented with ad hoc calibration factors depending on the application before being used in field.

Abstract The adoption and potential operationalization of aerosol sensors in occupational hygiene entails an understanding of the performance of a specific sensor to measure the aerosol of interest. Often, hygienists intend to monitor the airborne mass concentration of a certain aerosol and most sensor technologies can only provide estimates since they do not measure mass directly. Technological advancements in terms of sensors and algorithms will improve the performance of products in the future. But this might come with an increased cost and indirectly hindered adoption in most environments. Practices such as assessment and evaluation of the performance conducted periodically by the manufacturer and field assessment and calibration of the aerosol sensors can increase the confidence in the data generated. The field practices are not well established and hygienists should consider them as an important step of their activities. This contribution will provide an overview of the performance metrics for aerosol sensors that occupational hygienists should consider during the selection and adoption of the technologies. Most metrics can be applied to both personal and area aerosol monitors and for low-cost and medium-cost devices. For each metric, suggestions will be shared on how to measure it in the field and how hygienists can engage with manufacturers to receive information.

The goal of the present research was to assess, under controlled laboratory conditions, the accuracy and precision of a prototype device (named ‘P.ALP’: Ph.D. Air-quality Low-cost Project) developed for PM2.5 concentration level monitoring. Indeed, this study follows a complementary manuscript (previously published) focusing on the in-field evaluation of the device’s performance. Four P.ALP prototypes were co-located with the reference instrument in a calm-air aerosol chamber at the NIOSH laboratories in Pittsburgh, PA (USA), used by the Center for Direct Reading and Sensor Technologies. The devices were tested for 10 monitoring days under several exposure conditions. To evaluate the performance of the prototypes, different approaches were employed. After the data from the devices were stored and prepared for analysis, to assess the accuracy (comparing the reference instrument with the prototypes) and the precision (comparing all the possible pairs of devices) of the P.ALPs, linear regression analysis was performed. Moreover, to find out the applicability field of this device, the US EPA’s suggested criteria were adopted, and to assess error trends of the prototype in the process of data acquisition, Bland–Altman plots were built. The findings show that, by introducing ad hoc calibration factors, the P.ALP’s performance needs to be further implemented, but the device can monitor the concentration trend variations with satisfying accuracy. Overall, the P.ALP can be involved in and adapted to a wide range of applications because of the inexpensive nature of the components, the small dimensions, and the high data storage capacity.

Abstract Direct-reading, time-resolved devices, such as optical particle counters (OPCs) and photometers, offer a unique insight into the temporal and spatial distribution of airborne particles. They can provide a comprehensive picture of changes in concentration of airborne particles in occupational settings and therefore can be used to investigate failures in engineering control systems as well as identify exposures driven by working procedures and methods. In recent years, new developments have led to the commercialisation of low- cost optical-based sensors, which provide particle matter (PM) mass concentrations including PM2.5 and PM10 for environmental monitoring. TNO, NIOSH, and HSE are investigating their application to occupational settings with the aim to produce guidelines for calibration and use. This study evaluated the performance and accuracy of six commercially available low-cost sensors (Airbeam 2, Airveda, Omni Awair, OPC-N3, OPC-R1 and PATS+), in calm air test chambers, against reference devices including an Aerodynamic Particle Sizer (APS 3320), GK2.69 respirable cyclones, and pDR-1500 photometers. Several factors were considered: type of dust (particles having different size distribution, shape and refractive index), within- and between-device variations and exposure pattern (peak and constant concentrations). The devices were subjected to relatively high respirable concentrations (greater than 1 mg/m3) in addition to low concentrations. This presentation will present the results of the laboratory testing with particular focus on their accuracy, response, and calibration for quantitative exposure measurements. The low-cost sensor devices are also being deployed in the workplace for further evaluation and practicality of use.

This publication aims to disseminate a step-by-step process that walks through the conceptualization and building of a low-cost (~ $150 monitoring device for airborne fine particulate matter (PM2.5), based on miniaturized sensors and components. Details on the implementation of the hardware and software are provided which facilitate the data acquisition, capture and analysis. The central components and their setup discussed in what follows include: the sensor device (called “P.ALP” – Ph.D. Air quality Low-cost Project), Arduino IDE (Integrated Development Environment) and R code (open-access software). A monitoring device for PM2.5, using low-cost sensors and technologies was successfully conceptualized, designed, and implemented. The P.ALP monitoring system was designed and developed to be a basic device, which can be further customized and implemented using the wide range of low-cost sensors available on the market.

Low-cost particulate matter sensors are a up-and-coming technology for monitoring occupational exposure to hazardous substances in high spatial and temporal resolutions. Low costs, small sizes and high measurement frequencies offer the potential to continuously, automatically and remotely measure dust exposure and emission in the workplace. However, much remains unknown about how these devices can be successfully applied in occupational settings. TNO (the Netherlands) has, in collaboration with HSE (UK) and NIOSH (US), performed field studies at seven companies in the bakery, woodworking and welding industry to explore the use of sensors. A total of 145 full / half-shift measurements were collected for 37 workers and 15 static positions. Measurement data was obtained using four types of sensor and conventional respirable gravimetric and high-resolution reference devices. High-resolution contextual information was collected using additional sensors, including an ultrasound-based indoor positioning system, to investigate how these can further characterize exposure situations. Sensor accuracy compared to reference measurements ranged up to R2-values of 0.92, but large variations were observed within and between industries. Overall, stationary measurements showed less variation in performance compared to personal measurements. Different types of sensor seemed more accurate for specific industries. Contextual measurements provided additional information on when and where exposure occurred, for example by dynamic hazard maps based on indoor location and personal sensor measurements. Although performance of sensors remains lower than conventional methods, they may provide accurate measurements in specific situations. Additionally, sensors can provide new types of information that cannot be captured by time-integrated measurements.

Low-cost particulate matter (PM) sensors provide new methods for monitoring occupational exposure to hazardous substances, such as flour dust. These devices have many possible benefits, but much remains unknown about their performance for different exposure monitoring strategies in the workplace. We explored the performance of PM sensors for four different monitoring strategies (time-weighted average and high time resolution, each quantitative and semi-quantitative) for assessing occupational exposure using low-cost PM sensors in a field study in the industrial bakery sector. Measurements were collected using four types of sensor (PATS+, Isensit, Airbeam2, and Munisense) and two reference devices (respirable gravimetric samplers and an established time-resolved device) at two large-scale bakeries, spread over 11 participants and 6 measurement days. Average PM2.5 concentrations of the low-cost sensors were compared with gravimetric respirable concentrations for 8-h shift periods and 1-min PM2.5 concentrations of the low-cost sensors were compared with time-resolved PM2.5 data from the reference device (quantitative monitoring strategy). Low-cost sensors were also ranked in terms of exposure for 8-h shifts and for 15-min periods with a shift (semi-quantitative monitoring strategy). Environmental factors and methodological variables, which can affect sensor performance, were investigated. Semi-quantitative monitoring strategies only showed more accurate results compared with quantitative strategies when these were based on shift-average exposures. The main factors that influenced sensor performance were the type of placement (positioning the devices stationary versus personal) and the company or workstation where measurements were collected. Together, these findings provide an overview of common strengths and drawbacks of low-cost sensors and different ways these can be applied in the workplace. This can be used as a starting point for further investigations and the development of guidance documents and data analysis methods.

In the ever-expanding complexities of the modern-day mining workplace, the continual monitoring of a safe and healthy work environment is a growing challenge. One specific workplace exposure concern is the inhalation of dust containing respirable crystalline silica (RCS) which can lead to silicosis, a potentially fatal lung disease. This is a recognized and regulated health hazard, commonly found in mining. The current methodologies to monitor this type of exposure involve distributed sample collection followed by costly and relatively lengthy follow-up laboratory analysis. To address this concern, we have investigated a data-driven predictive modeling pipeline to predict the amount of silica deposition quickly and accurately on a filter within minutes of sample collection completion. This field-based silica monitoring technique involves the use of small, and easily deployable, Fourier transform infrared (FTIR) spectrometers used for data collection followed by multivariate regression methodologies including Principal Component Analysis (PCA) and Partial Least Squares (PLS). Given the complex nature of respirable dust mixtures, there is an increasing need to account for multiple variables quickly and efficiently during analysis. This analysis consists of several quality control steps including data normalization, PCA and PLS outlier detection, as well as applying correction factors based on the sampler and cassette used for sample collection. While outside the scope of this article to test, these quality control steps will allow for the acceptance of data from many different FTIR instruments and sampling types, thus increasing the overall useability of this method. Additionally, any sample analyzed through the model and validated using a secondary method can be incorporated into the training dataset creating an ever-growing, more robust predictive model. Multivariant predictive modeling has far-reaching implications given its speed, cost, and scalability compared to conventional approaches. This contribution presents the application of PCA and PLS as part of a computational pipeline approach to predict the amount of a deposited mineral of interest using FTIR data. For this specific application, we have developed the model to analyze RCS, although this process can be implemented in the analysis of any IR-active mineral, and this pipeline applied to any FTIR data.

Over the last decade, technological advancements have been made available and applied in a wide range of applications in several work fields, ranging from personal to industrial enforcements. One of the emerging issues concerns occupational safety and health in the Fourth Industrial Revolution and, in more detail, it deals with how industrial hygienists could improve the risk-assessment process. A possible way to achieve these aims is the adoption of new exposure-monitoring tools. In this study, a systematic review of the up-to-date scientific literature has been performed to identify and discuss the most-used sensors that could be useful for occupational risk assessment, with the intent of highlighting their pros and cons. A total of 40 papers have been included in this manuscript. The results show that sensors able to investigate airborne pollutants (i.e., gaseous pollutants and particulate matter), environmental conditions, physical agents, and workers' postures could be usefully adopted in the risk-assessment process, since they could report significant data without significantly interfering with the job activities of the investigated subjects. To date, there are only few "next-generation" monitors and sensors (NGMSs) that could be effectively used on the workplace to preserve human health. Due to this fact, the development and the validation of new NGMSs will be crucial in the upcoming years, to adopt these technologies in occupational-risk assessment.

Research studying the intersection of occupational safety and health (OSH) and direct reading and sensor technologies (DRST) is sparse, with a specific lack of research available that has empirically considered ways that DRST may impact worker well-being. In this paper, the authors examine how organizations could utilize core elements of their health and safety management system (HSMS) to coordinate and execute DRST in the workplace to support worker well-being. National Institute for Occupational Safety and Health (NIOSH) researchers developed a 39-item questionnaire targeting OSH professionals to understand attitudes toward DRST and the current and intended uses of DRST at their place of employment. Eighty-eight OSH professionals completed the questionnaire between August and December 2021. Descriptive results of the study sample are provided but the focus of the study applies the open-ended responses to two questions, which was deductively analyzed. Descriptive results show that reliability and validity of data was a top concern while the open-ended qualitative feedback revealed three primary themes: (1) acceptability and trust in technology; (2) ease of use; and (3) support and guidelines. Results provide an opening to use core HSMS elements (i.e., management commitment and leadership, communication and coordination, and employee involvement) during DRST integration to demonstrate support for workers during times of ambiguity and change.

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.

With the advent of new sensing technologies and robust field-deployable analyzers, monitoring approaches can now generate valuable hazard information directly in the workplace. This is the case for monitoring respirable dust and respirable crystalline silica concentration levels. Estimating the quartz amount of a respirable dust sample by nondestructive analysis can be carried out using portable Fourier transform infrared spectroscopy (FTIR) units. Real-time respirable dust monitors, combined with small video cameras, allow advanced assessments using the Helmet-CAM methodology. These two field-based monitoring approaches, developed by the National Institute for Occupational Safety and Health (NIOSH), have been trialed in a sandstone quarry. Twenty-six Helmet-CAM sessions were conducted, and forty-one dust samples were collected around the quarry and analyzed on-site during two events. The generated data generated were used to characterize concentration levels for the monitored areas and workers, to identify good practices, and to illustrate activities that could be improved with additional engineered control technologies. Laboratory analysis of the collected samples complemented the field finding and provided an assessment of the performance of the field-based techniques. Only a fraction of the real-time respirable dust monitoring sessions data could be corrected with laboratory analysis. The average correction factor ratio was 5.0. Nevertheless, Helmet-CAM results provided valuable information for each session. The field-based quartz monitoring approach overestimated the concentration by a factor of 1.8, but it successfully assessed the quartz concentration trends in the quarry. The data collected could be used for the determination of a quarry calibration factor for future events. The quartz content in the dust was found to vary from 14% to 100%, and this indicates the need for multiple techniques in the characterization of respirable dust and quartz concentration and exposure. Overall, this study reports the importance of the adoption of field-based monitoring techniques when combined with a proper understanding and knowledge of the capabilities and limitations of each technique.

Exposure science is fundamental to the field of occupational safety and health. The measurement of worker exposures to hazardous agents informs effective workplace risk mitigation strategies. The modern era of occupational exposure measurement began with the invention of the personal sampling device, which is still widely used today in the practice of occupational hygiene. Newer direct-reading sensor devices are incorporating recent advances in transducers, nanomaterials, electronics miniaturization, portability, batteries with high-power density, wireless communication, energy-efficient microprocessing, and display technology to usher in a new era in exposure science. Commercial applications of new sensor technologies have led to a variety of health and lifestyle management devices for everyday life. These applications are also being investigated as tools to measure occupational and environmental exposures. As the next-generation placeable, wearable, and implantable sensor technologies move from the research laboratory to the workplace, their role in the future of work will be of increasing importance to employers, workers, and occupational safety and health researchers and practitioners. This commentary discusses some of the benefits and challenges of placeable, wearable, and implantable sensor technologies in the future of work.