An analysis on control banding-based methods used for occupational risk assessment of nanomaterials

Despite all benefits of nanomaterials, their unique characteristics made them an emerging hazard in workplaces, which need to be assessed for their potential risks. So, the aim of this study was to review all the studies conducted on the risk assessment of activities involving nanomaterials with CB-based methods.This study is based on a literature review on databases including Web of science, Scopus, PubMed, and SID. After reviewing and screening studies according to PRISMA, the collected data were meta-analyzed by Comprehensive Meta-Analysis Software. Also, Newcastle-Ottawa checklist was used for quality assessment of the studies. To determine similarity of methods, Cohen's Kappa was used. Sensitivity analysis was used to determine the role of each factor in the risk assessment by using the Crystal Ball tool.There are eight validated methods for risk assessment. Also, some authors used a self-deigned tool based on CB approach. The results of meta-analysis showed that the odds ratio for the risk of activities involved with nanomaterials was 0.654 (high risk). Results of simulation for Nanotool showed that the mean risk level of activities involved with nanomaterials, with a certainty of 95.07%, is moderate (RL3). Moreover, sensitivity analysis showed that the risk was depended on "Hazard band" in all methods except ISO method.The obtained results can be useful in improving existing methods and suggesting new methods. Also, there is a need to design and propose specific methods for risk assessment of incidental and natural nanomaterials.

Control Banding and the Global Rise of Qualitative Risk Assessment Strategies

PURPOSE OF REVIEW

Control banding (CB) is a risk assessment strategy that has been applied globally to a variety of occupational hazards. This article describes how this method can be applied, recent developments in the CB literature, an example of how it is utilized for a large, diverse worksite, and where the future of CB is headed.

RECENT FINDINGS

Over the past several years, the applications of CB have widened significantly and have accordingly helped bolster the public and occupational safety, health, and hygiene (OSHH) professionals' understanding of occupational exposure to various hazards. The fields of workplace chemicals, nanomaterials, and airborne pathogens (i.e., COVID-19), specifically have seen remarkable increases in the development of CB tools. Extensive CB tool validation efforts have also lent increasing credibility to this alternative approach. CB is a simplified strategy of assessing occupational exposures and providing commensurate controls and solutions to reduce workplace risks. CB can be used as a primary or tiered risk assessment and risk management approach which can be utilized by both OSHH professionals and nonexperts alike to identify solutions for reducing work-related exposures. The need for health and safety expertise will continue to grow as technological advancements, environmental changes, and economic forces increase workplace hazard complexity, and CB will continue to be a useful tool for those performing risk assessments.

Laboratory activities involving nanomaterials: risk assessment and investigating researchers symptoms

The increasing use of nanomaterials is a threat to human health and environment that has led to the expansion of risk assessment methods. Thus, the aim of this study was to assess the occupational risks of activities involving nanomaterials in nanomedicine research laboratories by Control Banding (CB) NanoTool and Guidance methods. Further, the symptoms of researchers working in these laboratories were investigated. This cross-sectional study was managed in nanomedicine research laboratories. Risk assessment was performed by the CB NanoTool and Guidance methods. Moreover, a questionnaire was used to assess the prevalence of non-specific symptoms. Finally, data were analyzed using the IBM SPSS software. Descriptive statistics were used for data analysis. Many activities are located on the risk level RL2 and category A based on the CB NanoTool and Guidance methods, respectively. Further, the highest severity of exposure to nanomaterials belonged to the preparation of suspension and emulsion and manufacture of metal nanopolymers, but the highest probability of exposure was in the manufacturing of carbon nanocomposites. In addition, there was a significant relationship between the level of risk in the two methods (P = 0.003). Although, cutaneous symptoms were the most common symptoms among laboratory researchers, chi-square test did not confirm any significant relationship between symptoms and risk levels (p-value >0.05) in these two methods. Since the NanoTool method uses more diverse parameters for risk assessment and is more acceptable, choosing control measures based on its results seems more reasonable. Moreover, Guidance can be used as a method for initial assessments and determine the need for further assessments.

Occupational Exposure to Incidental Nanomaterials in Metal Additive Manufacturing: An Innovative Approach for Risk Management

The benefits of metal 3D printing seem unquestionable. However, this additive manufacturing technology brings concerns to occupational safety and health professionals, since recent studies show the existence of airborne nanomaterials in these workplaces. This article explores different approaches to manage the risk of exposure to these incidental nanomaterials, on a case study conducted in a Portuguese organization using Selective Laser Melting (SLM) technology. A monitoring campaign was performed using a condensation particle counter, a canning mobility particle sizer and air sampling for later scanning electron microscopy and energy dispersive X-ray analysis, proving the emission of nano-scale particles and providing insights on number particle concentration, size, shape and chemical composition of airborne matter. Additionally, Control Banding Nanotool v2.0 and Stoffenmanager Nano v1.0 were applied in this case study as qualitative tools, although designed for engineered nanomaterials. This article highlights the limitations of using these quantitative and qualitative approaches when studying metal 3D Printing workstations. As a result, this article proposes the IN Nanotool, a risk management method for incidental nanomaterials designed to overcome the limitations of other existing approaches and to allow non-experts to manage this risk and act preventively to guarantee the safety and health conditions of exposed workers.

Exposure characteristics and risk assessment of air particles in a Chinese hotel kitchen

Background

The hazards of kitchen particles have attracted social attention, but their distribution characteristics and risk assessment are rarely reported.

Objective

To explore the temporal and spatial distribution characteristics of kitchen particles, analyze the variations in characteristics of number concentration (NC), mass concentration (MC), surface area concentration (SAC), and particle size distribution, provide reference indexes for evaluating worker exposure, evaluate the risk of kitchen particles, as well as suggest improvements and control measures.

Patients and methods

Different cooking posts in a Chinese hotel kitchen were selected to monitor exposure to particles, explore the temporal and spatial distribution characteristics of NC, MC, and SAC of particles in the cooking post, analyze changes in the particle size, compare the individual exposure of particles between the cooking and steaming posts, and analyze the correlation between NC, MC, and SAC. Risk assessment of kitchen ultrafine particles was performed using a Nanotool.

Results

The sizes and fluctuation ranges of NC_{10 - 500nm} at cooking posts during lunch preparation and at peak periods were significantly higher than those at the end of the lunch period. The mean values of MC_{10 - 500nm} during the lunch preparation peak and ending periods were 0.149, 0.229, and 0.151 mg m^-3, respectively. The mean values of SAC_{10 - 500nm} were 225, 961, and 466 μm²·cm^-3, respectively. The mode diameter of exposed particles at the cooking post [(34.98 ± 2.33) nm] was higher than that at the steaming post [(30.11 ± 2.17) nm] (P < 0.01). The correlation between SAC_{10 - 500nm} and NC_{10 - 500nm} (r = 0.703) was the strongest. Nanotool gave a hazard rating ratio, exposure rating ratio, and risk ratio of 0.75.

Conclusion

The sizes of the NC, MC, and SAC of the particles at the cooking post were related to the kitchen operations. Since kitchen particles are of high exposure and risk levels, protective measures should be formulated and implemented to deal with them safely.

A Qualitative and Quantitative Occupational Exposure Risk Assessment to Hazardous Substances during Powder-Bed Fusion Processes in Metal-Additive Manufacturing

Metal-additive manufacturing (AM), particularly the powder-bed fusion (PBF) technique, is undergoing a transition from the short-run production of components to higher-volume manufacturing. The industry’s increased production efficiency is paired with a growing awareness of the risks related to the inhalation of very fine metal powders during PBF and AM processes, and there is a pressing need for a ready-to-use approach to assess the risks and the occupational exposure to these very final metal powders. This article presents a study conducted in an AM facility, which was conducted with the aim to propose a solution to monitor incidental airborne particle emissions during metal AM by setting up an analytical network for a tailored approach to risk assessment. Quantitative data about the respirable and inhalable particle and metal content were obtained by gravimetric and ICP-MS analyses. In addition, the concentrations of airborne particles (10–300 nm) were investigated using a direct reading instrument. A qualitative approach for risk assessment was fulfilled using control banding Nanotool v2.0. The results show that the operations in the AM facility are in line with exposure limit levels for both micron-sized and nano-sized particles. The particulate observed in the working area contains metals, such as chromium, cobalt, and nickel; thus, biological monitoring is recommended. To manage the risk level observed for all of the tasks during the AM process, containment and the supervision of an occupational safety expert are recommended to manage the risk. This study represents a useful tool that can be used to carry out a static evaluation of the risk and exposure to potentially harmful very fine metal powders in AM; however, due to the continuous innovations in this field, a dynamic approach could represent an interesting future perspective for occupational safety.

NanoSafe III: A User Friendly Safety Management System for Nanomaterials in Laboratories and Small Facilities

Research in nanoscience continues to bring forward a steady stream of new nanomaterials and processes that are being developed and marketed. While scientific committees and expert groups deal with the harmonization of terminology and legal challenges, risk assessors in research labs continue to have to deal with the gap between regulations and rapidly developing information. The risk assessment of nanomaterial processes is currently slow and tedious because it is performed on a material-by-material basis. Safety data sheets are rarely available for (new) nanomaterials, and even when they are, they often lack nano-specific information. Exposure estimations or measurements are difficult to perform and require sophisticated and expensive equipment and personal expertise. The use of banding-based risk assessment tools for laboratory environments is an efficient way to evaluate the occupational risks associated with nanomaterials. Herein, we present an updated version of our risk assessment tool for working with nanomaterials based on a three-step control banding approach and the precautionary principle. The first step is to determine the hazard band of the nanomaterial. A decision tree allows the assignment of the material to one of three bands based on known or expected effects on human health. In the second step, the work exposure is evaluated and the processes are classified into three "nano" levels for each specific hazard band. The work exposure is estimated using a laboratory exposure model. The result of this calculation in combination with recommended occupational exposure limits (rOEL) for nanomaterials and an additional safety factor gives the final "nano" level. Finally, we update the technical, organizational, and personal protective measures to allow nanomaterial processes to be established in research environments.

Occupational Exposure to Ultrafine Particles in Metal Additive Manufacturing: A Qualitative and Quantitative Risk Assessment

Ultrafine particles (UFPs) can be released unintentionally during metal additive manufacturing (AM). Experts agree on the urgent need to increase the knowledge of the emerging risk of exposure to nanoparticles, although different points of view have arisen on how to do so. This article presents a case study conducted on a metal AM facility, focused on studying the exposure to incidental metallic UFP. It intends to serve as a pilot study on the application of different methodologies to manage this occupational risk, using qualitative and quantitative approaches that have been used to study exposure to engineered nanoparticles. Quantitative data were collected using a condensation particle counter (CPC), showing the maximum particle number concentration in manual cleaning tasks. Additionally, scanning electron microscopy (SEM) and energy dispersive X-ray analyzer (EDS) measurements were performed, showing no significant change in the particles’ chemical composition, size, or surface (rugosity) after printing. A qualitative approach was fulfilled using Control Banding Nanotool 2.0, which revealed different risk bands depending on the tasks performed. This article culminates in a critical analysis regarding the application of these two approaches in order to manage the occupational risk of exposure to incidental nanoparticles, raising the potential of combining both.

Integrative approach in a safe by design context combining risk, life cycle and socio-economic assessment for safer and sustainable nanomaterials

Moving towards safe and sustainable innovations is an international policy ambition. In the on-hand manuscript, a concept combining safe by design and sustainability was implemented through the integration of human and environmental risk assessment, life cycle assessment as well as an assessment of the economic viability. The result is a nested and iterative process in form of a decision tree that integrates these three elements in order to achieve sustainable, safe and competitive materials, products or services. This approach, embedded into the stage-gate-model for safe by design, allows to reduce the uncertainty related to the assessment of risks and impacts by improving the quality of the data collected along each stage. In the second part of the manuscript, the application is shown for a case study dealing with the application of nanoparticles for Li-Ion batteries. One of the general conclusions out of this case study is that data gaps are a key aspect in view of the reliability of the results.

Quantitative Validation of Control Bands Using Bayesian Statistical Analyses

This study presents a quantitative validation of 15 Similar Exposure Groups (SEGs) that were derived via control bands inherent to the Risk Level Based Management System currently being used at the Lawrence Livermore National Laboratory. For 93% of the SEGs that were evaluated, statistical analyses of personal exposure monitoring data, through Bayesian Decision Analysis (BDA), demonstrated that the controls implemented from the initial control bands assigned to these SEGs were at least as protective as the controls from the control band outcomes derived from the quantitative data. The BDA also demonstrated that for 40% of the SEGs, the controls from the initial control bands were overly protective, thus allowing controls to be downgraded, which resulted in a significant saving of environmental safety and health (ES&H) resources. Therefore, as a means to both confirm existing controls and to identify candidate SEGs for downgrading controls, efforts to continuously improve the accuracy of Control Banding (CB) strategies through the routine quantitative validation of SEGs are strongly encouraged. Targeted collaborative efforts across institutions and even countries for both the development of CB strategies and the validation of discreetly defined SEGs of commonly performed tasks will not only optimize limited ES&H resources but will also assist in providing a simplified process for essential risk communication at the worker level to the benefit of billions of workers around the world.

Management of Occupational Risk Prevention of Nanomaterials Manufactured in Construction Sites in the EU

Currently, nanotechnology plays a key role for technological innovation, including the construction sector. An exponential increase is expected in its application, although this has been hampered by the current degree of uncertainty regarding the potential effects of nanomaterials on both human health and the environment. The accidents, illnesses, and disease related to the use of nanoproducts in the construction sector are difficult to identify. For this purpose, this work analyzes in depth the products included in recognized inventories and the safety data sheets of these construction products. Based on this analysis, a review of the recommendations on the use of manufactured nanomaterials at construction sites is performed. Finally, a protocol is proposed with the aim of it serving as a tool for technicians in decision-making management at construction sites related to the use of manufactured nanomaterials. This proposed protocol should be an adaptive and flexible tool while the manufactured nanomaterials-based work continues to be considered as an "emerging risk," despite the expectation that the protocol will be useful for the development of new laws and recommendations for occupational risk prevention management.