Search Results (30)

Respirable crystalline silica is a well-established occupational hazard in construction work. Despite increased awareness, consistent exposure control remains a challenge, particularly in dynamic and resource-constrained environments. Respirable crystalline silica exposure in construction environments challenges the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 8 (Decent Work and Economic Growth). Respirable crystalline silica particles cause severe health complications, including silicosis, lung cancer, cardiovascular diseases, and autoimmune disorders, representing a significant barrier to achieving SDG 3.9’s target of reducing deaths and illnesses from hazardous chemical exposures by 2030. This systematic review evaluates two decades of advancements (2004–2024) in respirable crystalline silica identification, characterisation, and mitigation within construction, synthesising evidence from 143 studies to assess progress toward sustainable occupational health management. This review documents a paradigmatic shift from traditional exposure assessment toward sophisticated monitoring approaches incorporating real-time detection systems, virtual reality–Computational Fluid Dynamics simulations, and wearable sensor technologies. Engineering controls, including local exhaust ventilation, wet suppression methods, and modified tool designs, have achieved exposure reductions exceeding 90%, directly supporting SDG 8.8’s commitment to safe working environments for all workers, including migrants and those in precarious employment. However, substantial barriers persist, including prohibitive costs, inadequate infrastructure, and regional regulatory disparities that particularly disadvantage lower-resourced countries, contradicting the Sustainable Development Goals’ principles of leaving no one behind. The findings advocate holistic approaches integrating technological innovation with context-specific regulations, enhanced international cooperation, and culturally adapted worker education to achieve equitable occupational health protection supporting multiple Sustainable Development Goals’ objectives by 2030 and also highlighting potential areas for future research. Full article

Background: Lithium is an essential commodity; however, its mining and processing can expose miners to airborne contaminants such as inhalable dust, respirable dust and respirable crystalline silica. These exposures may adversely affect respiratory health. To protect the health of miners, exposure assessment and control activities are required, followed by respiratory health monitoring to assess the effect of exposure on respiratory health. This study aimed to investigate the relationship between workgroup exposure to airborne contaminants and respiratory health. To determine group exposure levels, exposure data was collected at the group level, which limits individual-level inference, followed by health monitoring. Methods: Industry health monitoring data were collected from miners in three surface lithium mines in Western Australia for the period between October 2023 and October 2024. Miners from Management Administration & Technical, Crusher/Dry/Wet Plant, and Laboratory Operations participated in a pulmonary function test, completed a health and exposure questionnaire and underwent a low dose high-resolution computed tomography. Multivariable linear and logistic regression models were fitted to identify factors associated with lung function and respiratory symptoms. Results: Older age, smoking and pre-existing respiratory conditions were correlated with poor respiratory airflow. The odds of having a respiratory obstruction or restriction were significantly higher by 3.942 and 2.165 times respectively, for miners who were 40 years old or above, and those who had existing diagnosed respiratory medical conditions. The risk of coughing among current smokers was more than four times higher compared to non-smokers. In addition, working in Crushing and Processing was significantly associated with the risk of experiencing respiratory symptoms compared to working in Management Administration & Technical and Laboratory Operations. Conclusions: The study demonstrated that respiratory health was influenced by non-work-related risk factors. Based on these results, it is recommended that health promotion programs be developed and implemented to empower miners to cease smoking and to manage non-work-related respiratory conditions. Full article

The 6 February 2023 earthquake in Kahramanmaraş, Turkey, caused significant debris accumulation, raising concerns about air quality and public health. This study assessed dust concentrations during debris removal and emergency response efforts over a five-day period. Post-disaster respirable and total dust concentrations were measured using dust monitoring devices and the MDHS-14/3 gravimetric method. Scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) analyses identified fibrous structures and elements associated with asbestos, suggesting potential long-term health risks such as asbestosis and lung cancer. The average respirable dust concentration was 30.84 mg/m³, and the total dust concentration was 33.66 mg/m³. The findings emphasize the urgent need for protective measures to mitigate exposure risks for affected populations and emergency responders. Integrating health risk assessments into disaster management strategies are crucial to reducing long-term public health impacts. Full article

This study investigates the correlations between the wear conditions of conical pick cutters and key variables such as the physical properties (shape, aspect ratio, roughness), explosive potential, health and safety implications, and particle size distribution of coal dust and larger fragments using the linear cutting machine (LCM). This research was conducted within the framework of recent regulatory developments, notably implementing the new silica rule in the mining and construction sectors and climate change consideration. This study reveals critical insights into optimizing operational processes while adhering to stringent health and safety regulations. The findings indicate that as cutting tools wear, there is a significant increase in generated fine particles, including respirable crystalline silica (RCS), which elevates the risk of respiratory diseases and, in the case of coal dust, a higher potential for explosions. The results show that the silica content in respirable dust is a function of rock mineralogy; however, the results showed that the absolute amount of silica-containing dust increased with bit wear in rocks containing pertinent minerals. For the larger fragments, the new bit produced a 1699 fragment count, while the completely worn-out bit produced a 5608 count. The results of the dust concentration show that the new bit produces 89.2 mg/m³ (17.84%); the moderate bit produces 165.1 mg/m³ (33.03%), and the worn-out bit produces 245.6 mg/m³ (49.13%). Moreover, this study highlights the impact of bit wear on the production of larger fragments, which decreases with tool degradation, further contributing to dust generation. These results suggest the necessity for proactive equipment maintenance, enhanced dust control measures, and continuous monitoring of cutting tool wear to ensure compliance with regulatory standards and to protect workers’ health and safety. Full article

Current regulations mandate the monitoring of respirable coal mine dust (RCMD) mass and crystalline silica in underground coal mines to safeguard miner health. However, other RCMD characteristics, such as particle size and chemical composition, may also influence health outcomes. This study collected RCMD samples from two underground coal mines and performed detailed chemical speciation. Source apportionment was used to estimate RCMD and silica contributions from various sources, including intake air, fire suppression limestone dust, coal dust, diesel engine exhaust, and rock strata. The mine dust mass-based size distributions were comparable to those recorded over a decade ago, with a peak around 10 μm and the majority of the mass in the supermicron size range. The current mine conditions and mining practices do not appear to have significantly increased the generation of smaller particles. Limestone rock dust was prevalent in many locations and, along with coal dust, was the main contributor to RCMD at high-concentration locations. Silica accounted for over 10% of RCMD mass at several active mining locations, primarily from limestone and rock strata dust. Reducing the concentration of limestone dust and its silica content could reduce RCMD and silica levels. Further cleaning of the intake air could also improve the overall mine air quality. Full article

In livestock houses, particulate matter (PM) is a critical factor not only for disease and odor spread but also for the work environment. In particular, workers are exposed to high concentrations of organic particulate matter and harmful gases while performing their tasks, and, as they age, they become more vulnerable to respiratory diseases. This study analyzed the PM concentrations in commercial broiler houses, focusing on the differences in ventilation rates according to the season and the type of work, categorized into a static work period (SWP) and dynamic work period (DWP). In the regional monitoring using gravimetric methods, the average PM concentrations were found to be within acceptable limits, with TSP at 1042 µg/m³, PM-10 at 718 µg/m³, and PM-2.5 at 137 µg/m³. These values did not exceed the recommended exposure limits for inhalable dust at 2400 µg/m³ and respirable dust at 160 µg/m³ in chicken farmers. However, in the personal monitoring using a real-time aerosol spectrometer, it was revealed that the aerosol concentrations during DWP exceeded the standards by up to 214%. Specifically, during DWP, the concentrations were 1.74 times higher for TSP, 1.40 times higher for PM-10, and 1.22 times higher for PM-2.5 compared to SWP. It was observed that during the movement of workers, the physical generation of particles around 10 µm, such as feed and bedding, occurred due to the movement of chickens, which influenced the aerosol concentration. Full article

In recent years, the Mineral Liberation Analyser (MLA) has played a pivotal role in analysing respirable and inhalable ambient air samples collected on filters from both underground coal and metalliferous mines. Leveraging backscattered electron (BSE) image analysis and X-ray mineral identification, the MLA offers automated quantitative mineral characterization. The escalating prevalence and severity of mine dust lung diseases, particularly among young miners, have reignited interest in comprehensively understanding the dust’s characterization, encompassing mineralogy, particle size, and shape. Merely measuring total respirable dust exposure and its duration based on gravimetrically determined weight is no longer deemed sufficient in addressing the evolving landscape of occupational health challenges in mining environments. Since the publication of previous studies, efforts have been dedicated to refining the Mineral Liberation Analyser (MLA) methodology for respirable dust sampling. This refinement, discussed in detail in this paper, encompasses various enhancements, such as the implementation of data checks to identify carbon contamination, backscattered electron (BSE) drift, and the misclassification of X-ray spectra. Additionally, an examination of sampling efficiency led to the exploration of using smaller samples as an alternative to the time-intensive analysis of entire filters. Furthermore, this paper presents a reanalysis of paired filter sample sets previously reported using the Sarver Group Methodology. These samples are subjected to analysis using the Mineral Liberation Analyser, providing a more detailed illustration of the outputs derived from the updated methodology and compared to previously published MLA data. Full article

The United States has witnessed a concerning surge in the incidence of diseases like Coal Workers’ Pneumoconiosis (CWP), despite numerous efforts aimed at prevention. This study delves into the realm of respiratory health by investigating the deposition of dust particles within the respiratory tract and lungs. By analyzing particles of varying sizes, shapes, velocities, and aerodynamic diameters, we aim to gain a comprehensive understanding of their impact on deposition patterns. This insight could potentially drive changes in dust exposure protocols within mining environments and improve monitoring practices. The interplay of several critical factors, including particle characteristics and an individual’s breathing patterns, plays a pivotal role in determining whether particles settle in the lungs or are exhaled. This paper provides a comprehensive literature review on Respirable Coal Mine Dust (RCMD), with a specific focus on examining particle deposition across different regions of the airway system and lungs. Additionally, we explore the utility of Computational Fluid Dynamics (CFD) in simulating particle behavior within the respiratory system. Predicting the precise behavior of dust particles within the respiratory airway poses a significant challenge. However, through numerical simulations, we aspire to enhance our understanding of strategies to mitigate total lung deposition by comprehensively modeling particle interactions within the respiratory system. Full article

The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement monitoring of the anthropogenic aerosol spreading is necessary. For indoor aerosol measurements usually standard lab equipment is used. However, these devices are time-consuming, expensive and unwieldy. The idea is to replace this standard laboratory equipment with low-cost sensors widely used for monitoring fine dust (particulate matter—PM). Due to the low acquisition costs, many sensors can be used to determine the aerosol load, even in large rooms. Thus, the aim of this work is to verify the measurement capability of low-cost sensors. For this purpose, two different models of low-cost sensors are compared with established laboratory measuring instruments. The study was performed with artificially prepared NaCl aerosols with a well-defined size and morphology. In addition, the influence of the relative humidity, which can vary significantly indoors, on the measurement capability of the low-cost sensors is investigated. For this purpose, a heating stage was developed and tested. The results show a discrepancy in measurement capability between low-cost sensors and laboratory measuring instruments. This difference can be attributed to the partially different measuring method, as well as the different measuring particle size ranges. The determined measurement accuracy is nevertheless good, considering the compactness and the acquisition price of the low-cost sensors. Full article

Inhalation exposure to cadmium at the workplace has been associated with an increased risk of lung cancer and non-cancer respiratory effects. To ensure levels of cadmium remain below effect levels, air quality is monitored and regulations specifying an air limit value are implemented. The EU Carcinogens and Mutagens Directive of 2019 recommended values for the inhalable fraction and the respirable fraction but the latter only for a transitional period. Cadmium exposure has also been associated with systemic effects, following its storage in the kidneys and due to its long half-life. The accumulation of cadmium occurs via different exposure routes and from different sources, including workplace dust and fumes, food, and smoking. Biomonitoring (in blood, urine) has been identified as the most appropriate method to follow up cumulative exposure and total cadmium body burden, as it conveniently reflects intakes by all routes. However, it is not systematically implemented. This paper has a double objective: first, proposing a possible limit value for the respirable fraction, using an approach integrating epidemiological data. Secondly, demonstrating that the implementation of both air and biological limit values is key to protecting workers’ health in occupational settings. The paper summarizes the current knowledge on cadmium health effects and how biomarkers reflect those. It presents an approach to derive a respirable value, using recent human data, and describes how the combination of air monitoring and biomonitoring is applied by the EU industry to protect the workforce. While a respirable fraction value helps protect workers against local respiratory adverse health effects, air monitoring alone is not sufficient to protect workers against systemic effects of cadmium. Therefore, complementary biomonitoring and the implementation of a biological limit value is recommended. Full article

Chainsaw operation is associated with several hazards, including exposure to wood dust, a risk factor which requires serious attention due to health impacts such as respiratory disease. This study aims to investigate the effect of saw chain type and wood species on the mass concentration of airborne wood dust during chainsaw cross-cutting operations. Real-time inhalable and respirable dust measurements in the breathing zone of the chainsaw operator were carried out using a desktop aerosol monitor. Three types of cutter shape (semi chisel, full chisel, and chamfer chisel) and four types of wood species (oak, beech, spruce, and fir) were used in the experiments. The split-plot ANOVA results showed that both respirable and inhalable mass concentrations of wood dust were affected exclusively by wood species. No statistically significant differences were found among particular levels of cutter shape. The highest average mass concentrations of airborne dust were generated by the combination of oak wood and a full chisel cutter. Full article

Millions of workers are required to wear reusable respirators in several industries worldwide. Reusable respirators include filters that protect workers against harmful dust, smoke, gases, and vapors. These hazards may cause cancer, lung impairment, and diseases. Respiratory protection is prone to failure or misuse, such as wearing respirators with filters out of service life and employees wearing respirators loosely. Currently, there are no commercial systems capable of reliably alerting of misuse of respiratory protective equipment during the workday shifts or provide early information about dangerous clogging levels of filters. This paper proposes a low energy and non-obtrusive functional building block with embedded electronics that enable breathing monitoring inside an industrial reusable respirator. The embedded electronic device collects multidimensional data from an integrated pressure, temperature, and relative humidity sensor inside a reusable industrial respirator in real time and sends it wirelessly to an external platform for further processing. Here, the calculation of instantaneous breathing rate and estimation of the filter’s respirator fitting and clogging level is performed. The device was tested with ten healthy subjects in laboratory trials. The subjects were asked to wear industrial reusable respirator with the embedded electronic device attached inside. The signals measured with the system were compared with airflow signals measured with calibrated transducers for validation purposes. The correlation between the estimated breathing rates using pressure, temperature, and relative humidity with the reference signal (airflow) is 0.987, 0.988 and 0.989 respectively, showing that instantaneous breathing rate can be calculated accurately using the information from the embedded device. Moreover, respirator fitting (well-fitted or loose condition) and filter’s clogging levels (≤60%, 80% and 100% clogging) also can be estimated using features extracted from absolute pressure measurements combined to statistical analysis ANOVA models. These experimental outputs represent promising results for further development of data-driven prediction models using machine learning techniques to determine filters end-of-service life. Furthermore, the proposed system would collect relevant data for real-time monitoring of workers’ breathing conditions and respirator usage, helping to improve occupational safety and health in the workplace. Full article

Particulates from diesel generator operation are a known air pollutant with adverse health effects. In this study, we used low-cost particulate matter (PM) sensors to monitor PM_2.5 in a diesel generator plant. We compared the measurement results from a PM sensor and a reference instrument (DustTrak), and we found a high correlation between them. The data overestimation or underestimation of PM sensors implied the need for data calibration. Hence, we proposed a data calibration algorithm based on a nonlinear support vector machines(SVM )model, and we investigated the effect of three calibration factors on the model: humidity, temperature, and total volatile organic compounds (TVOC). It was found that the TVOC correction coefficient has great influence on the model, which should be considered when calibrating the low-cost PM sensor in diesel generator operation sites. A monitoring network with six low-cost sensors was installed in the diesel generator plant to monitor PM_2.5 concentration. It was found that normal diesel generator work, diesel generator set handling work, and human activity are the most dominant ways of producing particulate matter at the site, and dispersion is the main cause of increased PM_2.5 concentrations in nonworking areas. In this study, PM_2.5 emissions from two different diesel generators were tested, and PM_2.5 concentrations at monitoring points reached 220 μg/m³ and 120 μg/m³, respectively. This further confirms that diesel generators produce many respirable particles when working. Full article

This review considers the use of filters to sample air in mining workplace environments for dust concentration measurement and subsequent analysis of hazardous contaminants, especially respirable crystalline silica (RCS) on filters compatible with wearable personal dust monitors (PDM). The review summarizes filter vendors, sizes, costs, chemical and physical properties, and information available on filter modeling, laboratory testing, and field performance. Filter media testing and selection should consider the characteristics required for mass by gravimetry in addition to RCS quantification by Fourier-transform infrared (FTIR) or Raman spectroscopic analysis. For mass determination, the filters need to have high filtration efficiency (≥99% for the most penetrable particle sizes) and a reasonable pressure drop (up to 16.7 kPa) to accommodate high dust loading. Additional requirements include: negligible uptake of water vapor and gaseous volatile compounds; adequate particle adhesion as a function of particle loading; sufficient particle loading capacity to form a stable particle deposit layer during sampling in wet and dusty environments; mechanical strength to withstand vibrations and pressure drops across the filter; and appropriate filter mass compatible with the tapered element oscillating microbalance. FTIR and Raman measurements require filters to be free of spectral interference. Furthermore, because the irradiated area does not completely cover the sample deposit, particles should be uniformly deposited on the filter. Full article

Exposure monitoring and health surveillance of coal mine workers has been improved in Australia since coal workers’ pneumoconiosis was reidentified in 2015 in Queensland. Regional variations in the prevalence of mine dust lung disease have been observed, prompting a more detailed look into the size, shape, and mineralogical classes of the dust that workers are being exposed to. This study collected respirable samples of ambient air from three operating coal mines in Queensland and New South Wales for characterization analysis using the Mineral Liberation Analyser (MLA), a type of scanning electron microscope (SEM) that uses a combination of the backscattered electron (BSE) image and characteristic X-rays for mineral identification. This research identified 25 different minerals present in the coal samples with varying particle size distributions for the overall samples and the individual mineralogies. While Mine 8 was very consistent in mineralogy with a high carbon content, Mine 6 and 7 were found to differ more significantly by location within the mine. Full article