TY - JOUR
AU1 - McCord, Tyler, A
AU2 - Legaspi, Matthew, T
AU3 - West, Elaine, A
AU4 - Yung, Priscilla, K
AU5 - Larson, Diana, L
AU6 - Paik, Samuel, Y
AU7 - Zalk, David, M
AB - Abstract 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. Bayesian Decision Analysis, Control Banding, occupational risk management, quantitative validation, risk communication, Risk Level Based Management System, Risk Level Determination Documents Introduction Over 2 million deaths annually are attributed to work-related disease and at least 2.5 billion members of the global workforce lack access to basic occupational health resources (Zalk, 2010; Takala et al., 2014). The resource-limited health and safety industry is therefore tasked with developing simple, efficient, and scalable approaches to delivering environmental safety and health (ES&H) services. Control Banding (CB) is a qualitative risk assessment strategy that categorizes tasks into Risk Levels (RLs) based on severity and probability factors, thereby providing a simple means of determining controls and displaying compliance. Since its initial application in the pharmaceutical industry, CB has proved itself to be an adaptable risk management tool in an increasing number of applications worldwide. CB in Industrial Hygiene Occupational Exposure Limits (OELs) have been the basis for controlling workplace exposures since their development in the latter half of the 19th century. OELs are quantitative, agent-specific maximum exposure values believed to be safe for most healthy workers when exposed over a working lifetime. Their utility is limited by the fact that the number of chemicals used in a given workplace almost always exceeds the number of available OELs, and different organizations publish conflicting OELs for the same substance due to the use of differing methodologies for developing OELs (Deveau et al., 2015). Because OELs alone often fail to provide adequate guidance for controlling all hazards present in a workplace, the pharmaceutical industry, beginning in the late 1980s, developed a chemical categorization scheme that used available toxicological information to determine appropriate control measures. Understandably, characteristics such as physical properties and quantity used were not addressed in these initial models because the substances in question were deliberately highly biologically potent. Succeeding generalizable models, however, incorporated a growing number of relevant properties that made risk assessment increasingly straightforward, such as the European Union (EU) risk phrases (‘R-phrases’, now Hazard Statements), which provided some 60 categorizations according to specific toxicological properties, reactivity, explosivity, and more. The Control of Substances Hazardous to Health (COSHH) Essentials was the first widely adopted and thoroughly studied CB toolkit (HSE, 2003). It built upon the R-phrase framework by adding an exposure potential factor, and thus produced a specific and representative risk assessment with control prescriptions. This was particularly useful to smaller businesses in most industries that lacked a trained health or safety professional, though it did not address common agents like silica dust, wood particulate, and welding fumes. Since then, both general and specialized CB tools for bulk chemicals have proliferated and found use across the world (Zalk and Heussen, 2011). The growth of CB can be attributed to its focus on three ongoing criteria: (i) hazard, exposure, and RLs must be derived using rigorous scientific principles, (ii) elevated risks require increasingly stringent controls, and (iii) when less is known about a hazard, more conservative decision criteria are required. Although there is no single standard for CB processes, the basics of banding hazards, exposures, and controls continues to show tremendous promise for qualitative risk assessment and risk management applications by Occupational Safety, Health and Hygiene (OSHH) experts and nonexperts. The growth of CB has also been tied to the need to identify a simplified path to identify solutions to reduce work-related risks through qualitative risk assessment methods for common workplace hazards that could be readily learned and applied by management and employees alike. CB has most significantly proven itself in the scientific literature as being extremely useful in the absence of information, as in the absence of OELs or in emerging technologies like nanomaterials, and equally as essential in addressing the lack of sufficient ES&H professional expertise in the workplace globally (Zalk et al., 2019, 2020). For example, the CB Nanotool (Paik et al., 2008) has been the primary risk assessment method used at Lawrence Livermore National Laboratory (LLNL) for characterizing Engineered Nanoparticle (ENP) exposures since 2007 and has also become an integral part of controlling ENP exposures at various institutions around the world (IRSST, 2009; Safe Work Australia, 2009, 2010; ISO, 2014; Zalk and Paik, 2016; Canada, 2018). Recent CB expansion of range, beyond Industrial Hygiene (IH) and into other ES&H professions, uses the same basic stratification of practical prevention strategies as used in earlier risk matrices. Examples include barrier banding for industrial safety hazards (Swuste, 2005; NIOSH, 2006; Zalk, 2010; Zalk and Swuste, 2020), CB in ergonomics (Zalk, 2001; Kogi and Caple, 2008), CB for environmental application (Coleman and Zalk, 2014), risk communication for radiation safety (Root et al., 2020), the Construction Toolbox (Zalk et al., 2011), control of infectious diseases (Nelson, 2010; CDC, 2014), the Genius eTool for respiratory protection (OSHA, 2018), and a rapid risk assessment protocol for acute public health events (WHO, 2012). Risk Level Based Management System Throughout this process of expansion, both across the ES&H professions and around the world, CB has also found itself a solid footing in risk management and as a foundation for risk communication (Zalk, 2020). Given the limitations of OELs mentioned above, CB is providing impetus to a shift in the IH profession in the overall occupational exposure paradigm. OELs as a tool for regulatory oversight leaves many professionals seeing their intended use for evaluating compliance as a means for punishing employers that expose their workers to hazardous agents (Cherrie, 2017). In contrast, the simplified, multidisciplinary communication that CB affords to workers and managers can alternatively provide an opportunity to merge CB-based risk language with corporate governance. As important as compliance with regulations may be at our largest institutions, the primary focus of ES&H professionals should always be to identify the right processes to implement the most appropriate solutions for reducing work-related risk, for all workers, everywhere. As a United States Department of Energy (DOE) and National Nuclear Security Administration (NNSA) research facility, LLNL is required to comply with a uniquely complex litany of regulations from multiple entities. Its primary Federal Occupational Safety and Health Administration (OSHA) requirements are augmented by ES&H obligations outlined in the Lawrence Livermore National Security (LLNS) LLC contract, as well as additional DOE ES&H requirements stated in Title 10 of the Code of Federal Regulations that may invoke the adoption of otherwise voluntary standards, such as American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Values (TLVs). Demonstrating compliance to each of these bodies requires a considerable amount of effort beyond what is required in typical IH settings. In addition, LLNL’s focus on research and development (R&D) results in constantly changing work processes that can involve the use of numerous and novel agents. Traditional IH practices that were developed to address repetitive, routine use of limited numbers of agents is not efficient in this type of dynamic work setting. Through a review of their existing processes, the LLNL ES&H organization found that their approach often equally allocated ES&H resources to work activities regardless of the RL of the given work activity. This was problematic because more resources than necessary were focused on lower risk, routine activities and not enough resources were available to focus on higher-risk, dynamic processes. Noting the broadening utility of CB in risk management worldwide, LLNL responded by developing the Risk Level Based Management System (RLBMS), a CB-based approach to controlling risk and demonstrating compliance to each of its regulatory entities (Zalk et al., 2010). In addition to large-scale implementation, the ES&H organization also created smaller-scale ‘toolbox’ applications of CB principles to assess specific types of agents (e.g. nanomaterials) for which little guidance, such as OELs, existed. With the implementation of the RLBMS, LLNL succeeded in reducing the amount of resources needed to produce auditable documentation of work activities. However, as effective and intuitive as this approach has been, the need for empirical, quantitative validation of the qualitative RL outcomes from RLBMS remained. Toward this end, a Bayesian statistical model developed by Hewett et al. (2006) was applied to personal sampling data collected at LLNL and quantitative RLs were determined according to the resulting exposure concentration estimates. This paper describes and reports the quantitative validation of qualitative RLs for 15 Similar Exposure Groups (SEGs) at LLNL using a Bayesian Decision Analysis (BDA) method as a means to evaluate the utility of the CB approach. Materials and methods Risk Assessment & Control database As part of the RLBMS’s initiative to shift resources away from low-risk activities and toward high-risk activities, LLNL developed a database that facilitates and documents risk assessments called the Risk Assessment & Control (RAC) database. This database, developed using a Filemaker Pro application (Claris International, Inc., Santa Clara, CA), functions as a semiautomated workplace innovation platform that provides ES&H professionals with tools and information to conduct their risk assessments in accordance with established hazard-specific Risk Level Determination Documents (RLDDs) developed by internal ES&H subject matter experts. To perform a risk assessment for a given task, information regarding the task’s location, work operation, hazards, exposure characteristics, and other pertinent data are entered into the database. For substances that have established OELs, RLs are generally established based on the substance’s potential to exceed a certain fraction of the OEL, which is based on the ES&H professional’s qualitative assessment of the activity. For example, RL 1 is typically designated for expected exposures between 0 and 10% of the OEL, RL 2 for expected exposures between 10 and 50% of the OEL, RL 3 for expected exposures between 50 and 100% of the OEL, and RL 4 for expected exposures over 100% of the OEL. During the development of the RLDD, example tasks are binned into each RL designation in accordance with the subject matter expert’s professional judgment informed by exposure monitoring and/or modeling data when available. The ES&H professional’s qualitative assessment is thus facilitated by the inclusion of these example tasks in the RLDD. For substances that do not have OELs but are addressed by a sizable body of research and practical tools, the RAC database developers incorporated many of these resources into the database in the form of algorithmic CB-based ‘toolkits’ that quickly convert user input factors to an RL outcome based on severity and probability factors. The first implementation of this strategy was the ‘CB Nanotool’. In the early 2000s, nanoparticles posed a challenge to the IHs at LLNL (and to the greater IH community) due to a lack of centralized toxicological information, the absence of OELs, and limited quantitative methods. However, given that individual factors, such as surface chemistry, shape, diameter, carcinogenicity, mutagenicity, and others, were known to be associated with adverse health effects, mostly through animal research (NIOSH, 2006), Paik et al. created a CB tool that classifies a nanoparticle operation into one of four RLs based on the combined ratings of those individual factors and the ratings of additional probability factors related to the potential for dispersion, amount of handled material, duration of activity, etc. The RL outcome, in turn, determines the control band, thus providing guidance on control measures that are commensurate to the risk (Paik et al., 2008; Zalk et al., 2009, 2019) in the absence of exposure monitoring data. Another toolkit, incorporated into the RAC database as the ‘ChemTool’, uses information such as chemical phase, toxicity, OEL, vapor pressure, and quantity to assign RLs based upon the BAuA EMKG Risk Assessment Tool (BAuA, 2005). This tool is particularly useful for chemicals that do not have established OELs. Another toolkit, the ‘WeldTool’, specifically designed at LLNL to assess risk associated with various types of welding operations, was incorporated into the RAC database to provide an overall RL based on such factors as type of welding, base and filler metal composition, welder’s breathing position, work location, area configuration, arc time, etc. In addition to these tools, the RAC database also includes calculators that perform common operations including mass/volume concentration to mole fraction conversion, temperature/volume conversion, and lower and upper confidence limit calculation. Based on the RL outcome, the RLDD, with or without the use of a CB toolkit, provides a series of controls broken out as engineering, administrative and personal protection equipment (PPE) controls that are required for that specific RL (i.e. control band), which in turn provides the ES&H professional with the minimum information required to customize the controls for that task in a specific work control document. This centralized process ensures that tasks are assessed in a structured and consistent way across the entire laboratory while flowing down regulatory requirements and institutional policies. Quantitative validation of SEGs While the CB-based RLBMS is an effective system in concept, LLNL recognized the necessity of validating this approach both initially and on an ongoing basis through the collection of exposure monitoring data. For the CB Nanotool, in particular, a concerted effort was made to validate the tool quantitatively given its high-profile use by various organizations, both nationally and internationally, since its initial publication in 2008 (Safe Work Australia, 2010; Savolainen et al., 2010; Schulte et al., 2010; Workplace Health and Safety Queensland, 2017). This culminated in the recently published, comprehensive study on the quantitative validation of the CB Nanotool (Zalk et al., 2019), which demonstrated the accuracy of the CB approach for nanomaterials. In a similar fashion, but with the intent to apply this validation broadly across all IH hazards, a procedure was developed at LLNL for validating SEGs using BDA, as alluded to earlier in the description of the RLBMS. According to this procedure, SEGs are defined as ‘Task + Hazard + Risk Level’. The ‘Task’ and ‘Hazard’ components of a given SEG are defined in a work control document, and the ‘Risk Level’ component of the SEG is determined through a qualitative assessment of the task using an RLDD. In defining a SEG, it was important to consider all the factors that would influence the RL of the SEG. For example, when initially developing the plan for assessing manganese exposures during welding activities (SEG #1 in Results section), the SEGs were characterized strictly based on the type of welding activity performed (e.g. MIG versus TIG versus stick, etc.). However, as results were being received, it was clear that the use or nonuse of local exhaust ventilation (LEV) was an important determinant of exposure; thus, SEGs were refined, or in some cases split into separate SEGs even for the same type of welding activity, based on the utilization of LEV. Further attempts were made to include additional parameters that could influence exposure, such as task duration, tools and methods, location description, quantities and concentrations of materials, etc. All of these relevant parameters were included within the SEG description to ensure that any exposure data collected from associated work would be reflective of the SEG. For the SEG validations, previous sampling results from 1999 to present-day were queried and samples taken during work activities matching the SEG descriptions were identified. Each queried sampling report was thoroughly reviewed to ensure data quality objectives were met, including the specification of those workplace factors described above, to determine if the results were appropriate for inclusion in the quantitative validation of the SEG. As part of this process, LLNL IHs were also instructed to query their colleagues across the site to discuss the SEG scope and determine if other tasks that may have initially been missed during the SEG characterization should be included and for assistance refining the scope of the SEG. All the data were evaluated against the data quality objectives defined in LLNL’s internal procedure for quantitative validation of SEGs by LLNL’s Industrial Hygiene Group Leader and either accepted or rejected. As can be expected, not all the data were able to meet these data quality objectives. For example, when gathering air sampling data for the SEG for manual removal of lead-based paint, some older sampling reports lacked corresponding bulk sampling results identifying the concentration of lead in the removed paint. Only those air sampling data connected with confirmed lead-containing bulk sampling results were chosen for inclusion in the data set for this SEG validation (Activity #14 in Table 2). Given the dynamic nature of activities at LLNL as a R&D laboratory, it was not possible to obtain large numbers of samples for most tasks. Most of the work activities performed in this type of setting are not routine and often only occur a few times during the year. With this in mind, a minimum of six exposure monitoring data points were collected before proceeding with the statistical analysis. The selection of six data points as the minimum required sample size was based on the American Industrial Hygiene Association (AIHA) guide for assessing and managing occupational exposures (AIHA, 2015), where it is stated that since 1991, the AIHA Exposure Assessment Strategies (EAS) Committee, who published this guide, has recommended collecting six to ten measurements for a baseline survey. The European Committee for Standardization also established, in 1995, a procedure to demonstrate with a high degree of confidence that workers are not likely to be exposed to concentrations above an established Occupational Exposure Limit Value (OELV) based upon a relatively small number of measurements that can have variability in exposure (CEN, 2019). This strategy statistically tests compliance with the OELVs by initially using a minimum of three representative exposure measurements for each SEG. If the 70% Upper Confidence Level for the 95th percentile reaches 10% of the OELV, additional samples are collected up to a maximum of six exposure measurements. Finally, personal correspondence with the developer of the IHDataAnalyst software, who is also a member of the AIHA EAS Committee, confirmed that a sample size of six gives a reasonable estimate of an exposure population’s Geometric Mean and Geometric Standard Deviation and from there a ‘reasonably accurate’ decision can be made with small sample sizes (Hewett, 2020). Nevertheless, to compensate for the relatively low minimum sample number requirement, a conservative validation criterion was established as follows: when there was at least a 90% probability that the 95th percentile true exposure (X0.95) of a given SEG, based on the BDA, was the same as or lower than the previously assigned RL, it was interpreted as a quantitative validation of the qualitative risk assessment. The establishment of this criterion necessitates the collection of additional samples beyond the minimum of 6 if the goal is to validate a relatively low RL and if there is significant variability in the data and/or the data is approaching the OEL. IHDataAnalyst V1.34 software (EASi, Morgantown, WV) was used to conduct the BDA. As selectable options within the application, a Fillibens goodness-of-fit test (Filliben, 1975) was used to determine if the data represented a lognormal distribution and the Maximum Likelihood Estimate was used for all censored data analyses. Exposure category cutoffs were determined for each BDA based on the RL descriptions in the applicable RLDD. Order, descriptive, and compliance statistics were obtained from each set of data and the probabilities of X0.95 for each RL category were determined in the likelihood decision chart. It should be noted that in the IHDataAnalyst software, 75% probability for the 95th percentile true exposure is considered ‘high certainty’; hence, 90% probability represents a conservative approach even when compared with the default ‘high certainty’ category in the software. In addition, when performing the BDA, while it was recognized that the qualitative RLs could have been used to establish the prior distribution, a decision was made to use a noninformative (i.e. uniform) prior distribution. This was to ensure that the quantitative RL would be based strictly on the exposure monitoring data alone and thus serve as an independent validation of the qualitative RL. The use of noninformative priors is common in BDAs and is used for situations when the final decision probabilities are intended to reflect the analysis of the data alone. However, as described in Hewett et al. (2006), the BDA still provides a final output that is easier to understand and interpret than traditional X0.95 point estimates and confidence intervals. When the statistically determined quantitative RL was determined to be higher than the previously assigned qualitative RL, the RL for the task was elevated, and with it, controls were increased. When the quantitative RL was determined to be lower than that assigned by the previously assigned qualitative RL, the controls were reduced, thereby preserving ES&H resources. The results of the quantitative analyses would also feed into revisions of the RLDDs, enabling a recalibration of example tasks into their respective RL designations. Results The following are examples of four SEGs that were quantitatively validated at LLNL through the BDA approach. The applicable RLDDs for these four SEGs are presented in Supplementary File, available at Annals of Work Exposures and Health online. A summary table of results with descriptive statistics for these SEGs is presented in Table 1. A summary table of results for all 15 SEG validations that have been completed to date, including the BDA graphs, is presented in Table 2. Table 1. Air sampling results for manganese, lead, silica, and beryllium. Sample year . Monitored agent . Sample duration (min) . Sample size . Results (mg·m−3) . 8-h TWA results (mg·m−3) . Mean (mg·m−3) . Standard deviation (mg·m−3) . Geometric Mean (mg·m−3) . Geometric Standard Deviation . Exposure limit (mg·m−3) . 2019 Manganese (inhalable) 60–372 (20–180 arc time) 6 0.00083 to 0.082 0.00058 to 0.016 0.0084 0.0070 0.0032 8.2 0.1 2019 Manganese (respirable) 60–372 (20–180 arc time) 6 <0.00083 to 0.018 <0.00010 to 0.0036 0.0016 0.0013 0.00089 4.2 0.02 2005– 2007 Lead 212–347 7 <0.58 to <0.97 <0.33 to <0.42 <0.37 0.046 <0.37 1.1 0.05 2000– 2004 Crystalline silica (quartz) 44–210 6 0.12 to 1.1 0.011 to 0.32 0.13 0.11 0.083 3.2 0.025 2018 Beryllium 110–256 7 <0.000020 to <0.000045 <0.000010 to <0.000011 0.000011 0.00000018 0.000010 1.0 0.0002 Sample year . Monitored agent . Sample duration (min) . Sample size . Results (mg·m−3) . 8-h TWA results (mg·m−3) . Mean (mg·m−3) . Standard deviation (mg·m−3) . Geometric Mean (mg·m−3) . Geometric Standard Deviation . Exposure limit (mg·m−3) . 2019 Manganese (inhalable) 60–372 (20–180 arc time) 6 0.00083 to 0.082 0.00058 to 0.016 0.0084 0.0070 0.0032 8.2 0.1 2019 Manganese (respirable) 60–372 (20–180 arc time) 6 <0.00083 to 0.018 <0.00010 to 0.0036 0.0016 0.0013 0.00089 4.2 0.02 2005– 2007 Lead 212–347 7 <0.58 to <0.97 <0.33 to <0.42 <0.37 0.046 <0.37 1.1 0.05 2000– 2004 Crystalline silica (quartz) 44–210 6 0.12 to 1.1 0.011 to 0.32 0.13 0.11 0.083 3.2 0.025 2018 Beryllium 110–256 7 <0.000020 to <0.000045 <0.000010 to <0.000011 0.000011 0.00000018 0.000010 1.0 0.0002 Open in new tab Table 1. Air sampling results for manganese, lead, silica, and beryllium. Sample year . Monitored agent . Sample duration (min) . Sample size . Results (mg·m−3) . 8-h TWA results (mg·m−3) . Mean (mg·m−3) . Standard deviation (mg·m−3) . Geometric Mean (mg·m−3) . Geometric Standard Deviation . Exposure limit (mg·m−3) . 2019 Manganese (inhalable) 60–372 (20–180 arc time) 6 0.00083 to 0.082 0.00058 to 0.016 0.0084 0.0070 0.0032 8.2 0.1 2019 Manganese (respirable) 60–372 (20–180 arc time) 6 <0.00083 to 0.018 <0.00010 to 0.0036 0.0016 0.0013 0.00089 4.2 0.02 2005– 2007 Lead 212–347 7 <0.58 to <0.97 <0.33 to <0.42 <0.37 0.046 <0.37 1.1 0.05 2000– 2004 Crystalline silica (quartz) 44–210 6 0.12 to 1.1 0.011 to 0.32 0.13 0.11 0.083 3.2 0.025 2018 Beryllium 110–256 7 <0.000020 to <0.000045 <0.000010 to <0.000011 0.000011 0.00000018 0.000010 1.0 0.0002 Sample year . Monitored agent . Sample duration (min) . Sample size . Results (mg·m−3) . 8-h TWA results (mg·m−3) . Mean (mg·m−3) . Standard deviation (mg·m−3) . Geometric Mean (mg·m−3) . Geometric Standard Deviation . Exposure limit (mg·m−3) . 2019 Manganese (inhalable) 60–372 (20–180 arc time) 6 0.00083 to 0.082 0.00058 to 0.016 0.0084 0.0070 0.0032 8.2 0.1 2019 Manganese (respirable) 60–372 (20–180 arc time) 6 <0.00083 to 0.018 <0.00010 to 0.0036 0.0016 0.0013 0.00089 4.2 0.02 2005– 2007 Lead 212–347 7 <0.58 to <0.97 <0.33 to <0.42 <0.37 0.046 <0.37 1.1 0.05 2000– 2004 Crystalline silica (quartz) 44–210 6 0.12 to 1.1 0.011 to 0.32 0.13 0.11 0.083 3.2 0.025 2018 Beryllium 110–256 7 <0.000020 to <0.000045 <0.000010 to <0.000011 0.000011 0.00000018 0.000010 1.0 0.0002 Open in new tab Table 2. Summary of qualitative and quantitative RLs for 15 SEGs. Activity no. . Task description . Hazard description and sampling/analytical method . Air monitoring results (8-h TWA) summary . Occupational exposure limit . Initial qualitative RL . Validated quantitative RL (BDA result) . Comment . 1 Indoor GMAW with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.00058 to 0.016 mg m−3 Range (respirable): <0.00010 to 0.0036 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 3: Results indicate true exposure population is RL 3. Respiratory protection may be downgraded to half- face air-purifying respirator when using LEV. Controls downgraded to RL 3. 2 Bench-top soldering using electronic solder iron, SnPb solder, without use of LEV Lead fume via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 7 Range: <0.33 to <0.42 µg m−3 Data collected: 2005–2007 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 1: Inhalation exposure less than 10% of the OSHA PEL. RL 1: Results confirm true exposure population is RL 1. Results confirm that LEV or respiratory protection is not required for this task. 3 Concrete jackhammering outdoors RCS via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (quartz only): 0.011 to 0.32 mg m−3 Data collected: 2000–2004 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 91% likelihood of exposure being in excess of ten times the TLV (see Results section). Full-face air-purifying respirator is required. 4 Beryllium contaminated duct removal Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 2 lpm No. of samples: 7 Range: <0.010 to <0.011 µg m−3 Data collected: 2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10% and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. Respiratory protection no longer required. Controls downgraded to RL 1. 5 Indoor Gas Tungsten Arc Welding (GTAW) on stainless steel with use of LEV Hexavalent chromium fumes via OSHA ID-215 Sampler: 37-mm 5 µm polyvinyl chloride (PVC) filter cassette Flow rate: 2 lpm No. of samples: 8 Range: <0.0085 to 0.012 µg m−3 Data collected: 2016–2019 5 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 1: Results indicate true exposure population of RL 1. Results confirm that respiratory protection is not required for this task. Controls downgraded to RL 1. 6 Concrete drilling for seismic anchor installation, installing support brackets for utility pipes, conduits, panels, etc., using HEPA-filtered LEV or wet methods Crystalline silica dust via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 17 Range: <0.0070 to 0.0044 mg m−3 Data collected: 2003–2015 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using LEV or wet methods. 7 Indoor Gas Tungsten Arc Welding (GTAW), grinding and brushing on stainless steel with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): <0.00010 to 0.0050 mg m−3 Range (respirable): <0.00011 to 0.0025 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 3: Inhalation exposure will be between 50 and 100% of PEL. RL 2: Results indicate true exposure population is RL 2. Respiratory protection no longer required when using LEV. Controls downgraded to RL 2. 8 Handling and coating lead shielding Lead particulate via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 9 Range: <0.42 to 11 µg m−3 Data collected: 1992–2003 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not required. 9 Weighing and transfer of dry carbon nanotubes into liquid suspension Nanoparticulates via NIOSH 5040 Sampler: 25-mm quartz fiber filter cassette with GK 2.69 BGI cyclone Flow rate: 4.2 lpm No. of samples: 8 Range: <0.35 to <0.41 µg m−3 Both area and personal breathing zone samples included Data collected: 2016–2017 1 µg m−3 (NIOSH REL) RL 2: Inhalation exposure less than 50% of NIOSH REL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using fume hood. 10 Concrete saw cutting RCS via NIOSH 7500/NIOSH 0600 Sampler: aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (all polymorphs): <0.0080 to 0.083 mg m−3 Data collected: 2005–2009 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 10% likelihood of exposure being in excess of ten times the TLV. Minimum half-face air-purifying respirator is required. 11 Drywall demolition RCS via NIOSH 7500/NIOSH 0600 Samplers: SKC 8 LPM PPIs® with pre-weighed 37-mm 5 µm PVC filter media; aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5–8 lpm No. of samples: 6 Range (all polymorphs): <0.0010 to 0.013 mg m−3 Data collected: 2019 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will be between 10 and 50% of the TLV. RL 4: Results indicate true exposure population is RL 4. Implement respiratory protection requirement. 12 NIF laser test chamber entry— component maintenance and repair Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 4 lpm No. of samples: 20 Range: <0.0046 to <0.0052 µg m−3 Data collected: 2015–2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. However, due to projected increase in target chamber contamination over time, respiratory protection controls are still required (see Results section). 13 NIF laser target and diagnostic equipment handling Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassettes Flow rate: 4 lpm No. of samples: 30 Range: <0.0052 to <0.010 µg m−3 Data collected: 2013–2017 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the AL. RL 1: Results indicate true exposure population is RL 1. Controls downgraded to RL 1. 14 Manual scraping lead- containing paint with HEPA vacuum or wet methods Lead fume via NIOSH 7300 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 1.5–2 lpm No. of samples: 26 Range: <0.40 to 7.3 µg m−3 Data collected 1998–2010 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure potential at an RL 2. Respiratory protection is not required. 15 Indoor GMAW with limited or no use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.017 to 0.26 mg m−3 Range (respirable): 0.011 to 0.15 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 4: Results confirm true exposure population is RL 4. Additional analysis of BDA indicates 34.3% likelihood of exposure being in excess of ten times the respirable TLV. Full-face air-purifying respirator is required. Activity no. . Task description . Hazard description and sampling/analytical method . Air monitoring results (8-h TWA) summary . Occupational exposure limit . Initial qualitative RL . Validated quantitative RL (BDA result) . Comment . 1 Indoor GMAW with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.00058 to 0.016 mg m−3 Range (respirable): <0.00010 to 0.0036 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 3: Results indicate true exposure population is RL 3. Respiratory protection may be downgraded to half- face air-purifying respirator when using LEV. Controls downgraded to RL 3. 2 Bench-top soldering using electronic solder iron, SnPb solder, without use of LEV Lead fume via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 7 Range: <0.33 to <0.42 µg m−3 Data collected: 2005–2007 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 1: Inhalation exposure less than 10% of the OSHA PEL. RL 1: Results confirm true exposure population is RL 1. Results confirm that LEV or respiratory protection is not required for this task. 3 Concrete jackhammering outdoors RCS via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (quartz only): 0.011 to 0.32 mg m−3 Data collected: 2000–2004 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 91% likelihood of exposure being in excess of ten times the TLV (see Results section). Full-face air-purifying respirator is required. 4 Beryllium contaminated duct removal Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 2 lpm No. of samples: 7 Range: <0.010 to <0.011 µg m−3 Data collected: 2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10% and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. Respiratory protection no longer required. Controls downgraded to RL 1. 5 Indoor Gas Tungsten Arc Welding (GTAW) on stainless steel with use of LEV Hexavalent chromium fumes via OSHA ID-215 Sampler: 37-mm 5 µm polyvinyl chloride (PVC) filter cassette Flow rate: 2 lpm No. of samples: 8 Range: <0.0085 to 0.012 µg m−3 Data collected: 2016–2019 5 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 1: Results indicate true exposure population of RL 1. Results confirm that respiratory protection is not required for this task. Controls downgraded to RL 1. 6 Concrete drilling for seismic anchor installation, installing support brackets for utility pipes, conduits, panels, etc., using HEPA-filtered LEV or wet methods Crystalline silica dust via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 17 Range: <0.0070 to 0.0044 mg m−3 Data collected: 2003–2015 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using LEV or wet methods. 7 Indoor Gas Tungsten Arc Welding (GTAW), grinding and brushing on stainless steel with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): <0.00010 to 0.0050 mg m−3 Range (respirable): <0.00011 to 0.0025 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 3: Inhalation exposure will be between 50 and 100% of PEL. RL 2: Results indicate true exposure population is RL 2. Respiratory protection no longer required when using LEV. Controls downgraded to RL 2. 8 Handling and coating lead shielding Lead particulate via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 9 Range: <0.42 to 11 µg m−3 Data collected: 1992–2003 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not required. 9 Weighing and transfer of dry carbon nanotubes into liquid suspension Nanoparticulates via NIOSH 5040 Sampler: 25-mm quartz fiber filter cassette with GK 2.69 BGI cyclone Flow rate: 4.2 lpm No. of samples: 8 Range: <0.35 to <0.41 µg m−3 Both area and personal breathing zone samples included Data collected: 2016–2017 1 µg m−3 (NIOSH REL) RL 2: Inhalation exposure less than 50% of NIOSH REL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using fume hood. 10 Concrete saw cutting RCS via NIOSH 7500/NIOSH 0600 Sampler: aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (all polymorphs): <0.0080 to 0.083 mg m−3 Data collected: 2005–2009 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 10% likelihood of exposure being in excess of ten times the TLV. Minimum half-face air-purifying respirator is required. 11 Drywall demolition RCS via NIOSH 7500/NIOSH 0600 Samplers: SKC 8 LPM PPIs® with pre-weighed 37-mm 5 µm PVC filter media; aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5–8 lpm No. of samples: 6 Range (all polymorphs): <0.0010 to 0.013 mg m−3 Data collected: 2019 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will be between 10 and 50% of the TLV. RL 4: Results indicate true exposure population is RL 4. Implement respiratory protection requirement. 12 NIF laser test chamber entry— component maintenance and repair Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 4 lpm No. of samples: 20 Range: <0.0046 to <0.0052 µg m−3 Data collected: 2015–2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. However, due to projected increase in target chamber contamination over time, respiratory protection controls are still required (see Results section). 13 NIF laser target and diagnostic equipment handling Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassettes Flow rate: 4 lpm No. of samples: 30 Range: <0.0052 to <0.010 µg m−3 Data collected: 2013–2017 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the AL. RL 1: Results indicate true exposure population is RL 1. Controls downgraded to RL 1. 14 Manual scraping lead- containing paint with HEPA vacuum or wet methods Lead fume via NIOSH 7300 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 1.5–2 lpm No. of samples: 26 Range: <0.40 to 7.3 µg m−3 Data collected 1998–2010 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure potential at an RL 2. Respiratory protection is not required. 15 Indoor GMAW with limited or no use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.017 to 0.26 mg m−3 Range (respirable): 0.011 to 0.15 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 4: Results confirm true exposure population is RL 4. Additional analysis of BDA indicates 34.3% likelihood of exposure being in excess of ten times the respirable TLV. Full-face air-purifying respirator is required. Open in new tab Table 2. Summary of qualitative and quantitative RLs for 15 SEGs. Activity no. . Task description . Hazard description and sampling/analytical method . Air monitoring results (8-h TWA) summary . Occupational exposure limit . Initial qualitative RL . Validated quantitative RL (BDA result) . Comment . 1 Indoor GMAW with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.00058 to 0.016 mg m−3 Range (respirable): <0.00010 to 0.0036 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 3: Results indicate true exposure population is RL 3. Respiratory protection may be downgraded to half- face air-purifying respirator when using LEV. Controls downgraded to RL 3. 2 Bench-top soldering using electronic solder iron, SnPb solder, without use of LEV Lead fume via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 7 Range: <0.33 to <0.42 µg m−3 Data collected: 2005–2007 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 1: Inhalation exposure less than 10% of the OSHA PEL. RL 1: Results confirm true exposure population is RL 1. Results confirm that LEV or respiratory protection is not required for this task. 3 Concrete jackhammering outdoors RCS via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (quartz only): 0.011 to 0.32 mg m−3 Data collected: 2000–2004 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 91% likelihood of exposure being in excess of ten times the TLV (see Results section). Full-face air-purifying respirator is required. 4 Beryllium contaminated duct removal Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 2 lpm No. of samples: 7 Range: <0.010 to <0.011 µg m−3 Data collected: 2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10% and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. Respiratory protection no longer required. Controls downgraded to RL 1. 5 Indoor Gas Tungsten Arc Welding (GTAW) on stainless steel with use of LEV Hexavalent chromium fumes via OSHA ID-215 Sampler: 37-mm 5 µm polyvinyl chloride (PVC) filter cassette Flow rate: 2 lpm No. of samples: 8 Range: <0.0085 to 0.012 µg m−3 Data collected: 2016–2019 5 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 1: Results indicate true exposure population of RL 1. Results confirm that respiratory protection is not required for this task. Controls downgraded to RL 1. 6 Concrete drilling for seismic anchor installation, installing support brackets for utility pipes, conduits, panels, etc., using HEPA-filtered LEV or wet methods Crystalline silica dust via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 17 Range: <0.0070 to 0.0044 mg m−3 Data collected: 2003–2015 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using LEV or wet methods. 7 Indoor Gas Tungsten Arc Welding (GTAW), grinding and brushing on stainless steel with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): <0.00010 to 0.0050 mg m−3 Range (respirable): <0.00011 to 0.0025 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 3: Inhalation exposure will be between 50 and 100% of PEL. RL 2: Results indicate true exposure population is RL 2. Respiratory protection no longer required when using LEV. Controls downgraded to RL 2. 8 Handling and coating lead shielding Lead particulate via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 9 Range: <0.42 to 11 µg m−3 Data collected: 1992–2003 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not required. 9 Weighing and transfer of dry carbon nanotubes into liquid suspension Nanoparticulates via NIOSH 5040 Sampler: 25-mm quartz fiber filter cassette with GK 2.69 BGI cyclone Flow rate: 4.2 lpm No. of samples: 8 Range: <0.35 to <0.41 µg m−3 Both area and personal breathing zone samples included Data collected: 2016–2017 1 µg m−3 (NIOSH REL) RL 2: Inhalation exposure less than 50% of NIOSH REL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using fume hood. 10 Concrete saw cutting RCS via NIOSH 7500/NIOSH 0600 Sampler: aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (all polymorphs): <0.0080 to 0.083 mg m−3 Data collected: 2005–2009 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 10% likelihood of exposure being in excess of ten times the TLV. Minimum half-face air-purifying respirator is required. 11 Drywall demolition RCS via NIOSH 7500/NIOSH 0600 Samplers: SKC 8 LPM PPIs® with pre-weighed 37-mm 5 µm PVC filter media; aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5–8 lpm No. of samples: 6 Range (all polymorphs): <0.0010 to 0.013 mg m−3 Data collected: 2019 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will be between 10 and 50% of the TLV. RL 4: Results indicate true exposure population is RL 4. Implement respiratory protection requirement. 12 NIF laser test chamber entry— component maintenance and repair Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 4 lpm No. of samples: 20 Range: <0.0046 to <0.0052 µg m−3 Data collected: 2015–2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. However, due to projected increase in target chamber contamination over time, respiratory protection controls are still required (see Results section). 13 NIF laser target and diagnostic equipment handling Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassettes Flow rate: 4 lpm No. of samples: 30 Range: <0.0052 to <0.010 µg m−3 Data collected: 2013–2017 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the AL. RL 1: Results indicate true exposure population is RL 1. Controls downgraded to RL 1. 14 Manual scraping lead- containing paint with HEPA vacuum or wet methods Lead fume via NIOSH 7300 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 1.5–2 lpm No. of samples: 26 Range: <0.40 to 7.3 µg m−3 Data collected 1998–2010 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure potential at an RL 2. Respiratory protection is not required. 15 Indoor GMAW with limited or no use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.017 to 0.26 mg m−3 Range (respirable): 0.011 to 0.15 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 4: Results confirm true exposure population is RL 4. Additional analysis of BDA indicates 34.3% likelihood of exposure being in excess of ten times the respirable TLV. Full-face air-purifying respirator is required. Activity no. . Task description . Hazard description and sampling/analytical method . Air monitoring results (8-h TWA) summary . Occupational exposure limit . Initial qualitative RL . Validated quantitative RL (BDA result) . Comment . 1 Indoor GMAW with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.00058 to 0.016 mg m−3 Range (respirable): <0.00010 to 0.0036 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 3: Results indicate true exposure population is RL 3. Respiratory protection may be downgraded to half- face air-purifying respirator when using LEV. Controls downgraded to RL 3. 2 Bench-top soldering using electronic solder iron, SnPb solder, without use of LEV Lead fume via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 7 Range: <0.33 to <0.42 µg m−3 Data collected: 2005–2007 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 1: Inhalation exposure less than 10% of the OSHA PEL. RL 1: Results confirm true exposure population is RL 1. Results confirm that LEV or respiratory protection is not required for this task. 3 Concrete jackhammering outdoors RCS via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (quartz only): 0.011 to 0.32 mg m−3 Data collected: 2000–2004 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 91% likelihood of exposure being in excess of ten times the TLV (see Results section). Full-face air-purifying respirator is required. 4 Beryllium contaminated duct removal Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 2 lpm No. of samples: 7 Range: <0.010 to <0.011 µg m−3 Data collected: 2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10% and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. Respiratory protection no longer required. Controls downgraded to RL 1. 5 Indoor Gas Tungsten Arc Welding (GTAW) on stainless steel with use of LEV Hexavalent chromium fumes via OSHA ID-215 Sampler: 37-mm 5 µm polyvinyl chloride (PVC) filter cassette Flow rate: 2 lpm No. of samples: 8 Range: <0.0085 to 0.012 µg m−3 Data collected: 2016–2019 5 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 1: Results indicate true exposure population of RL 1. Results confirm that respiratory protection is not required for this task. Controls downgraded to RL 1. 6 Concrete drilling for seismic anchor installation, installing support brackets for utility pipes, conduits, panels, etc., using HEPA-filtered LEV or wet methods Crystalline silica dust via NIOSH 7500/ NIOSH 0600 Sampler: aluminum cyclone with preweighted 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 17 Range: <0.0070 to 0.0044 mg m−3 Data collected: 2003–2015 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will not exceed 50% of the PEL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using LEV or wet methods. 7 Indoor Gas Tungsten Arc Welding (GTAW), grinding and brushing on stainless steel with use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): <0.00010 to 0.0050 mg m−3 Range (respirable): <0.00011 to 0.0025 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 3: Inhalation exposure will be between 50 and 100% of PEL. RL 2: Results indicate true exposure population is RL 2. Respiratory protection no longer required when using LEV. Controls downgraded to RL 2. 8 Handling and coating lead shielding Lead particulate via NIOSH 7300 Sampler: 37-mm 0.8 µm MCE filter cassette Flow rate: 2.5 lpm No. of samples: 9 Range: <0.42 to 11 µg m−3 Data collected: 1992–2003 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not required. 9 Weighing and transfer of dry carbon nanotubes into liquid suspension Nanoparticulates via NIOSH 5040 Sampler: 25-mm quartz fiber filter cassette with GK 2.69 BGI cyclone Flow rate: 4.2 lpm No. of samples: 8 Range: <0.35 to <0.41 µg m−3 Both area and personal breathing zone samples included Data collected: 2016–2017 1 µg m−3 (NIOSH REL) RL 2: Inhalation exposure less than 50% of NIOSH REL. RL 2: Results confirm true exposure population is RL 2. Respiratory protection is not needed when using fume hood. 10 Concrete saw cutting RCS via NIOSH 7500/NIOSH 0600 Sampler: aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5 lpm No. of samples: 6 Range (all polymorphs): <0.0080 to 0.083 mg m−3 Data collected: 2005–2009 0.025 mg m−3 (ACGIH TLV) RL 4: Inhalation exposure will be at or above 100% of the TLV. RL 4: Results confirm true exposure population is RL 4. Further analysis of BDA indicates 10% likelihood of exposure being in excess of ten times the TLV. Minimum half-face air-purifying respirator is required. 11 Drywall demolition RCS via NIOSH 7500/NIOSH 0600 Samplers: SKC 8 LPM PPIs® with pre-weighed 37-mm 5 µm PVC filter media; aluminum cyclone with pre-weighed 37-mm 5 µm PVC filter cassette Flow rate: 2.5–8 lpm No. of samples: 6 Range (all polymorphs): <0.0010 to 0.013 mg m−3 Data collected: 2019 0.025 mg m−3 (ACGIH TLV) RL 2: Inhalation exposure will be between 10 and 50% of the TLV. RL 4: Results indicate true exposure population is RL 4. Implement respiratory protection requirement. 12 NIF laser test chamber entry— component maintenance and repair Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 4 lpm No. of samples: 20 Range: <0.0046 to <0.0052 µg m−3 Data collected: 2015–2018 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the PEL. RL 1: Results indicate true exposure population is RL 1. However, due to projected increase in target chamber contamination over time, respiratory protection controls are still required (see Results section). 13 NIF laser target and diagnostic equipment handling Beryllium via HCL-I-2050 Sampler: 37-mm, 0.8 µm MCE filter cassettes Flow rate: 4 lpm No. of samples: 30 Range: <0.0052 to <0.010 µg m−3 Data collected: 2013–2017 0.2 µg m−3 (OSHA PEL) RL 2: Inhalation exposure will be between 10 and 50% of the AL. RL 1: Results indicate true exposure population is RL 1. Controls downgraded to RL 1. 14 Manual scraping lead- containing paint with HEPA vacuum or wet methods Lead fume via NIOSH 7300 Sampler: 37-mm, 0.8 µm MCE filter cassette Flow rate: 1.5–2 lpm No. of samples: 26 Range: <0.40 to 7.3 µg m−3 Data collected 1998–2010 30 µg m−3 (OSHA AL) 50 µg m−3 (OSHA PEL, ACGIH TLV) RL 2: Inhalation exposure less than the OSHA AL. RL 2: Results confirm true exposure potential at an RL 2. Respiratory protection is not required. 15 Indoor GMAW with limited or no use of LEV Manganese fumes (inhalable and respirable) via NIOSH 7303/7300 modified Sampler: IOM inhalable aerosol sampler with respirable foam insert Flow rate: 2 lpm No. of samples: 6 Range (inhalable): 0.017 to 0.26 mg m−3 Range (respirable): 0.011 to 0.15 mg m−3 Data collected: 2019 0.1 mg m−3 (inhalable— ACGIH TLV) 0.02 mg m−3 (respirable— ACGIH TLV) RL 4: Inhalation exposure greater than 100% of PEL. RL 4: Results confirm true exposure population is RL 4. Additional analysis of BDA indicates 34.3% likelihood of exposure being in excess of ten times the respirable TLV. Full-face air-purifying respirator is required. Open in new tab SEG #1: Indoor Gas Metal Arc Welding with LEV use Hazard: manganese fumes (inhalable and respirable) Initial RL: 4 (qualitative risk assessment) This task involves the potential for manganese exposure with the use of LEV during Gas Metal Arc Welding (GMAW or ‘MIG’). The primary route of exposure is inhalation of airborne manganese particles. The filler materials and base metals used during GMAW contained roughly 1–2% manganese. While the example tasks in the RLDD suggested a RL of 3, an initial RL of 4 was designated for this task by the IH responsible for providing oversight to this activity given the reduction of the OEL for manganese with DOE’s adoption of the 2016 ACGIH TLVs for inhalable and respirable manganese, a literature review that broadly suggested excess exposures to manganese during various types of welding operations, including GMAW (Flynn and Susi, 2012; Insley et al., 2019), and the uncertainty in the effectiveness of the LEV that was used. The intent of this assessment was to quantitatively determine the RL and potentially downgrade respiratory protection if appropriate. The bounding conditions for this task were GMAW with lead-, cadmium-, arsenic-, mercury-, nickel-, or beryllium-containing base metal, filler or alloy materials, the use of thoriated tungsten electrodes, and welding in a confined space, enclosure, or explosive environment. Post analysis RL: 3 (quantitative validation) Six samples were collected and analyzed for inhalable and respirable manganese to characterize this task. Sampling was performed using an IOM sampler with respirable foam disc (SKC Inc., Eighty-Four, PA) for concurrent collection of both inhalable and respirable particulate mass. Since a powered air-purifying respirator (PAPR) with welding helmet and P100 filters was used during all of these sampling episodes, the IOM samplers were attached to the respirator shroud near the lapel outside the respirator, as specified by an OSHA letter of interpretation (OSHA, 1999). Samples were analyzed using the National Institute for Occupational Safety and Health (NIOSH) 7300 method, modified for particle size-selective sampling. Inhalable samples were compared with the TLV of 0.1 mg m−3 (for inhalable particulate matter) and respirable samples were compared with the TLV of 0.02 mg m−3 (for respirable particulate matter). LEV hoods were qualitatively tested semiannually (i.e. smoke test) and quantitatively tested annually (i.e. capture velocity test) according to LLNL policy. Based on the BDA, the decision probabilities for inhalable and respirable particulate mass were 0.844 and 0.814 for RL 2, respectively. Since the cumulative decision probabilities for both inhalable and respirable manganese for RL 1 and 2 were below 90% certainty and above 90% when combined with the decision probabilities for RL 3, it was determined with more than 90% certainty that the 95th percentile true exposure profile for this SEG is at or below RL 3 for both inhalable and respirable manganese. Based on the BDA analysis result, the minimum respiratory protection requirement was downgraded to half-face air-purifying respirator with P100 filter. SEG #2: bench-top soldering using electric soldering iron Hazard: lead Initial RL: 2 (qualitative risk assessment) This task involves the potential for exposures to lead fumes during bench-top soldering with an electric soldering iron. Routes of exposure include inhalation of airborne lead particulate, dermal absorption from skin contact, and ingestion from eating or drinking with contaminated hands. The work performed under this assessment included up to 6 h of soldering per shift with lead-tin solder with a lead content of 37% at a bench-top soldering station with no LEV present. The bounding conditions for this task were open flame soldering and brazing, use of cadmium-containing solder, use of solder with >37% lead, and soldering at temperatures that exceeded 700°F. Post analysis RL: 1 (quantitative validation) Seven samples for airborne lead collected from 2005 to 2007 were analyzed to characterize this task. Samples were collected in two 120 ft2 rooms with general heating, ventilation, and cooling ventilation but no LEV. Air samples were collected and analyzed in accordance with NIOSH Method 7300 using a 37-mm Closed-Face-Cassette (SKC Inc., Eighty-Four, PA). Based on the BDA, the task received a decision probability of 1 (i.e. 100%) for RL 1. All other RLs had a decision probability of 0, supporting the hypothesis that we can state with more than 90% certainty that the 95th percentile true exposure profile is at or below RL 1. While this would allow a downgrade of controls to RL 1 from an inhalation exposure standpoint, the controls for RL 2 were retained for this SEG given the potential for dermal exposure in accordance with the RLDD for lead. SEG #3: silica exposure during concrete jackhammering Hazard: respirable crystalline silica Initial RL: 4 (qualitative risk assessment) This task involves the potential for exposure to respirable crystalline silica (RCS) during concrete jackhammering activities. The route of exposure is inhalation of RCS particles. The initial RL for this task was determined to be RL 4 and the intent of this assessment was to validate if the correct RL was designated for this activity. The bounding conditions for this task were performing the task without water for dust suppression and working indoors or in other enclosed locations. As part of the DOE’s regulatory policy, the 2016 version of ACGIH TLV of 25 µg m−3 was adopted as the OEL, which is equivalent to the OSHA Action Level (OSHA, 2019). Post analysis RL: 4 (quantitative validation) Six data points from RCS monitoring reports between 2000 and 2004 were used for this SEG. Each sample was collected via the use of a 25-mm aluminum cyclone (SKC Inc., Eighty-Four, PA) and then analyzed in accordance with NIOSH 7500 for quartz, cristobalite, and tridymite. The reports used for this SEG validation did not include data for two of the RCS polymorphs—cristobalite and tridymite—because results were less than the analytical reporting limit. Had these polymorphs been detected, those results would be added to the results for quartz for computing worker exposure to RCS. It should also be noted that while the minimum sample volume (MSV) of 400 L specified by NIOSH 7500 was not collected for four of the six samples, personal monitoring was performed for the entire duration of the jackhammering activity for all of these samples. In determining the 8-h Time-weighted Averages (TWAs) for each of these samples, zero exposure was assumed for the remainder of their shifts after confirming that no other work with potential exposure to silica was performed during those shifts, consistent with a recent proposition to remove the concept of MSVs in IH sampling methods (Paik and Zalk, 2019). In all cases of monitoring, the worker operating the jackhammer was accompanied by another worker using water to suppress the dust being generated. Workers involved in both roles used full-face, tight-fitting PAPRs or loose-fitting hood PAPRs, with P100 filters, in addition to long-sleeve work uniforms and leather gloves for dermal protection. Based on the BDA, the task received a decision probability of 1 (i.e. 100%) for RL 4. All other exposure ratings had a decision probability of 0, supporting the hypothesis that we can state with more than 90% certainty that the 95th percentile true exposure profile is at or below RL 4 (in this context, RL 4 is defined as greater than the OEL, with no upper limit). In addition to validating qualitative RLs, BDA can also be used to verify if the appropriate level of respiratory protection is specified for tasks designated as RL 4. At RL 4, exposures are expected to exceed the OEL; however, the degree of exceedance must be understood in order to prescribe the correct level of respiratory protection. The Assigned Protection Factor (APF) of the respirator must be able to protect wearers from the highest anticipated exposure. Toward this end, an additional BDA was performed from the existing data set. Since the exposure cutoffs for each RL are defined by the user and the BDA software allows for as many as five RLs, RL 5 was introduced for this additional analysis and was defined as being greater than 10 times the OEL, or >250 µg m−3. This value was selected to represent the level of exposure that would not be adequately protected by the use of a half-face air-purifying respirator (APR). The BDA indicated a 91% probability that the true 95th percentile exposure population was RL 5, proving that a half-face air-purifying respirator would not be adequate for this SEG. As a result, a full-face air-purifying respirator was considered the minimum required respirator for this SEG. SEG #4: beryllium contaminated duct removal Hazard: beryllium Initial RL: 2 (qualitative risk assessment) This assessment characterized exposures to beryllium present in contaminated ductwork that needed to be removed as a part of a major building infrastructure project. Routes of exposure to beryllium during this work activity were dermal contact and inhalation. The work included in this assessment consisted of the removal of approximately 300 linear feet of 16″ diameter beryllium contaminated return air ducting. The degree of surface contamination in the ducting was characterized via surface sampling to be no greater than 0.65 µg/100 cm2. The duct work was removed using double cut shears and hand cut shears in conjunction with a high-efficiency particulate air (HEPA) vacuum at the point of cutting. HEPA-equipped negative air machines were also attached to the duct system to maintain negative pressure throughout the system during the removal process. The project took two workers a total of three 8-h days. It should be noted that for DOE sites, the applicable OEL for beryllium is the OSHA Permissible Exposure Limit (PEL) of 0.2 µg m−3. Post analysis RL: 1 (quantitative validation) Six personal exposure samples of airborne beryllium were taken throughout the project. Additional samples were projected to be taken, but these samples were not collected due to the completion of the project. These samples were collected using 37-mm 0.8 mixed cellulose ester (MCE) Filter Closed-Face-Cassettes (SKC Inc., Eighty-Four, PA) and analyzed via HCL-I-2050 (internal modified NIOSH Method 7300 to collect beryllium oxide in addition to elemental beryllium). The result of each sample was below the analytical reporting limit. Based on the BDA, RL 1 had a decision probability of 0.963, supporting the hypothesis that we can state with more than 90% certainty that the 95th percentile true exposure profile is at or below RL 1. This quantitative validation effort led to future iterations of the task being cleared for a lower level of beryllium controls compared with the qualitative RL outcome of RL 2. Summary of SEG validation data In eight of the 15 SEGs reviewed (or 53%), the SEG was validated at the same RL that was assigned during the initial qualitative assessment. These SEGs included: bench-top soldering (lead), concrete jackhammering (silica), drilling into concrete (silica), handling lead shielding (lead), weighing/transferring carbon nanotubes (ENPs), concrete saw cutting (silica), manual scraping lead paint (lead), and GMAW welding with no or limited LEV (manganese). However, for 6 of the 15 SEG validations reviewed (or 40%), the initial RL for the SEG was higher than the final validated RL, suggesting that the prescribed controls were more conservative than they needed to be. This may be perceived as ‘over control’ by some OSHH professionals; however, this is an accepted paradigm of working within CB models and qualitative risk assessment strategies like RLBMS (Zalk and Nelson, 2008). These SEGs included: GMAW welding with LEV (manganese), contaminated duct removal (beryllium), TIG welding (hexavalent chromium), TIG welding (manganese), National Ignition Facility (NIF) Laser Target and Diagnostic Equipment Handling (beryllium), and NIF Laser Target Chamber Entry (beryllium). As a result of the BDA analysis, the controls for five of these tasks were downgraded, which resulted in a significant saving of ES&H resources, including a reduced level of worker training, relaxed use of PPE, and reduction in exposure monitoring frequency. In the case of the SEG for NIF Laser Target Chamber Entry (beryllium), although the quantitative RL outcome was 1 compared with the qualitative RL of 2, the continued use of beryllium as a target material in future shots is expected to result in additional beryllium being deposited on the interior surface of the target chamber. Since it is anticipated that during future maintenance activities, this additional beryllium residue buildup could be encountered resulting in future personnel exposures being higher than what was measured during this initial validation, a management decision was made not to downgrade the controls for this SEG and for the RL to remain at 2. This decision was driven by LLNL’s programmatic goal to minimize worker’s potential exposure to beryllium and prevent future beryllium-related incidents from occurring. NIF Laser Target Chamber Entry and NIF Laser Target/Diagnostic Equipment Handling activities are described in detail in Paik et al. (2017). Only one of the SEGs reviewed had a validated RL that was higher than its initial qualitative assessment. Drywall removal (crystalline silica) using power tools had an initial qualitative RL of 2, which was lower than the statistically determined RL of 4. As a result, additional controls including respiratory protection were prescribed for protecting workers from potential overexposure to RCS during drywall demolition activities. Discussion Validation of CB strategies Work-related exposures to hazards will always be rife with variability and the quantitative measurement and analysis will always be an essential component of the IH profession, especially for CB strategies (Kromhout, 2016). Validation efforts have found CB models to be mostly conservative in their outcomes (Hashimoto et al., 2007; Zalk et al., 2019). A validation of nearly 4000 measurements with four Registration Evaluation, Authorization and Restriction of Chemicals (REACH) Tier 1 CB models found relatively appropriate levels of conservatism at the 90th percentile of outcome at or above quantitatively measured outcomes (van Tongeren et al., 2017). In their assessment of the COSHH model, Tischer and colleagues set forth a three-part framework (Tischer, 2003) that can be applied to similar CB models: First, evaluate the internal strength; is the theory consistent within itself and with reality? Second, evaluate the external performance; do the observations fit the model’s predictions? Third, analyze the operational feasibility; can the strategy realistically be implemented in the work setting? In this study, the first question was addressed by the involvement of hazard-specific subject matter experts in the development of RLDDs and CB toolkits, with these documents and tools being developed through their experience managing these hazards. The second question was addressed using the BDA method, as described, to analyze sampling data and estimate exposure concentrations present during a task. Based on this analysis, an RL was assigned according to concentration ranges delineated in the applicable RLDD. The third question, with respect to feasibility, was addressed through the implementation of this approach to the 15 SEGs that were evaluated in this study. BDA versus conventional statistics As illustrated by Hewett et al. (2006), the BDA approach, while rigorous, is still much more practical than the use of Upper Tolerance Limits (UTLs) in conventional statistics (AIHA, 2006, 2015), which would require many more samples to come to a similar conclusion as the BDA. As a simple illustration, if conventional statistics were applied to the same data set presented in Table 1 for inhalable manganese exposures during welding (using LEV), the 95%, 95% UTL, based on lognormal parametric statistics, would be 8.0 µg m−3, which is well into the range of RL 4, defined as greater than the OEL. In comparison, the BDA yielded a conclusion with 99% confidence (based on the cumulative probabilities of RL 1, 2, and 3; see Table 2) that the 95th percentile true exposure population is RL 3 or below, which corresponds to a range of 0–100% of the OEL. This is possible because the BDA can be constrained to a plausible range of exposure profiles, where, unlike conventional statistics, possible exposure profiles do not extend to infinity. BDA also focuses on decision-making, where the point estimate of the 95th percentile (X0.95) provides a determination of the most likely RL instead of a statistical confidence interval around the point estimate. The decision charts are easy to interpret and can facilitate communication with management and employees. Unlike conventional statistics, the BDA conclusion also passes the ‘sanity test’ if one were to simply look at the data set, the general spread in the data, and the applicable OEL. Taken holistically, this design provides a truly conservative foundation that also embraces the reality of working with the limited data sets that are representative of the modern, dynamic workplace. OSHA Silica Standard (29 CFR 1926.1153), Table 1 As the analysis above concluded that half-face APRs cannot adequately protect workers during concrete demolition activities using a jackhammer, another BDA was conducted to determine if the OSHA Silica Construction Standard’s Table 1 should be considered adequately protective of workers during concrete jackhammering activities. For this analysis, the OSHA PEL of 50 µg m−3 was used instead of the TLV of 25 µg m−3 as a basis for designating 5 RLs, with RL 5 defined as greater than 10 times the OEL, or >500 µg m−3. This is because compared with the ACGIH TLV for crystalline silica, OSHA has a higher exposure limit of 50 µg m−3 and Table 1 only requires a respirator with an APF of 10 when jackhammering for more than 4 h and no respiratory protection is required if jackhammering duration is 4 h or less. LLNL’s data set was again reanalyzed, with RL 5 defined as greater than 10 times the PEL to account for the range where a half-face APR would be considered inadequate per OSHA. Since the 8-h TWAs for the data set were calculated from actual work durations that were less than 4 h, this analysis would only be considered representative of jackhammering that was 4 h or less in duration. The analysis found that there was a 52% probability that the true 95th percentile exposure population was RL 4 and a 48% probability that it was RL 5 (Fig. 1). Based on this analysis, RL 5 represents the RL at which there is at least 90% certainty that the 95th percentile true exposure is at that RL or below. Thus, at minimum, a full-face air-purifying respirator with P100 cartridges, or possibly a PAPR, would be needed to protect workers from silica exposure. This analysis demonstrates that the controls outlined in OSHA’s Table 1 are inadequate when jackhammering is performed for 4 h or less, since no respirator would be required, and also inadequate if performed for more than 4 h a day, since the prescribed half-face APR would not have a high enough of a protection factor. Since 29 CFR 1926.1153(d)(2)(i) exempts employers from performing an exposure assessment if they follow Table 1, potential overexposures to silica would go undetected if employers are fully relying on Table 1. Figure 1. Open in new tabDownload slide Likelihood graph from Bayesian Decision Analyses of RCS sampling results by RL, with additional 5th RL for respirator determination. Figure 1. Open in new tabDownload slide Likelihood graph from Bayesian Decision Analyses of RCS sampling results by RL, with additional 5th RL for respirator determination. While this specific discussion is unique to 1926.1153 Table 1 for jackhammering, the overarching lesson is that controls need to be verified based on a rigorous review and analysis of personal air monitoring data. Whether controls are passed down through regulation, corporate offices, or industry standards, OSHH professionals have the responsibility to verify that the prescribed controls will be adequate to protect workers from overexposure. There are certainly other opportunities for OSHH professionals to use BDA analysis to verify the adequacy of externally sourced controls. The examination of other tasks listed in 1926.1153 Table 1, for example, may also yield similar protection benefits to workers if put through a similar validation process. Additional research is needed to further investigate these opportunities in order to continue advancing the field of occupational health and safety. Continuous improvement of the RLBMS model The SEG validation process is an integral part of the RLBMS model by its routine validation of qualitative RLs using quantitative data. RLDDs are refined through this continuous feedback mechanism that appropriately reflects an essential process improvement cycle. The use of RLBMS streamlines the assessment process and adds consistency and credibility to an IH program. It also provides a process for calibrating IHs within the program, which was an initial goal of RLBMS; helping to ensure the same set of controls are prescribed in different work control documents even when the task is assessed by different IHs having varying degrees of experience with a specific task and the potential hazards it presents. Presenting the minimum set of controls through the RLDD in a statistically validated and concise manner that flows down institutional policies and regulatory requirements leverages the experience and knowledge of subject matter experts. Once the minimum set of controls for a given RL has been established, additional customized controls can be prescribed to account for specific work locations and task variables that would influence an individual’s exposure. At the same time, this process saves IH resources by eliminating the need to reassess the same task except for when the tasks change or when regulation mandates periodic resampling. Conclusion The current RL distribution of completed assessments at LLNL finds that the vast majority of hazards, over 80%, are assessed by the IH at RL 2 or lower. As emphasized in the initial RLBMS process and confirmed in this validation effort, allocating resources equally regardless of the RL focuses resources unnecessarily on lower risk, routine activities when IH attention is needed for the higher-risk processes that carry more serious consequences. This risk profile is not unique to LLNL and is typical for most enterprises (Zalk et al., 2010). Therefore, it is important to consider that lessons learned from this quantitative validation exercise and the beneficial applications and outcomes of RLBMS have the potential to be applied more broadly both nationally and internationally. With approximately 20 000 IH practitioners worldwide, and a large majority of these in the USA, the IH profession needs to be treated as a scarce resource. This is especially true on the global scale in economically transitioning and developing countries, where over 90% of the world’s workers have minimal to no access to any OSHH professionals (Takala et al., 2014). This article describes the LLNL IH program holistically and can be modeled by any IH program, small or large. If RLBMS were to be used more broadly, and its SEGs more synchronized across industries for the vast majority of tasks that are standardized and commonly performed, cumulative data sets could be shared to vastly increase the number of validated SEGs that could be readily available for sharing. The opportunity to harness beneficial outcomes, like the ones presented here, could then be designed to become more universally applicable for the most common trades performed by well over a billion workers globally. As noted above, the occupational exposure paradigm is already shifting and OELs being used in a punitative fashion by regulatory oversight agencies has a decades-long track record of not effectively reducing work-related risks. As an outcome of the increasing efforts to quantitatively validate RLBMS and CB tools, and the already proven effectiveness of CB-based risk communication at the manager and worker levels alike, the need to expand this effort is becoming more essential each passing day. The process is certainly not perfect, but it is proving itself to be really good, especially in the absence of expertise. Therefore, the need to increase the research basis for expanding efforts at large institutions like those presented here will only help to bolster collaborative efforts to provide the most appropriate solutions for achieving prevention of work-related risks where it is most needed in the world. Funding This work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344; Lawrence Livermore National Security, LLC, LLNL-JRNL-807201. Acknowledgements The authors would like to thank Ryan Kamerzell for his role in developing the original RAC database and SEG validation procedure and Jim Branum for his tireless and unwavering support in developing, enhancing, and maintaining the RAC database. The authors would also like to thank Juliana Hall, Matt Fechser, Wes Chase, Geoffrey Won, Onwuka Okorie, Amanda Bewley, Angelica Cobb, and Shelley Zhang for completing several of the SEG validation reports used in this study. Conflict of interest The authors do not declare any conflicts of interest. Disclaimer This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes. References AIHA . 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TI - Quantitative Validation of Control Bands Using Bayesian Statistical Analyses
JF - Annals of Work Exposures and Health (formerly Annals Of Occupational Hygiene)
DO - 10.1093/annweh/wxaa081
DA - 2021-01-14
UR - https://www.deepdyve.com/lp/oxford-university-press/quantitative-validation-of-control-bands-using-bayesian-statistical-BIeTSuft5O
SP - 63
EP - 83
VL - 65
IS - 1
DP - DeepDyve
ER -