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Title: Control Banding and Nanotechnology Synergist

Abstract

The average Industrial Hygienist (IH) loves a challenge, right? Okay, well here is one with more than a few twists. We start by going through the basics of a risk assessment. You have some chemical agents, a few workers, and the makings of your basic exposure characterization. However, you have no occupational exposure limit (OEL), essentially no toxicological basis, and no epidemiology. Now the real handicap is that you cannot use sampling pumps, cassettes, tubes, or any of the media in your toolbox, and the whole concept of mass-to-dose is out the window, even at high exposure levels. Of course, by the title, you knew we were talking about nanomaterials (NM). However, we wonder how many IHs know that this topic takes everything you know about your profession and turns it upside down. It takes the very foundations that you worked so hard in college and in the field to master and pulls it out from underneath you. It even takes the gold standard of our profession, the quantitative science of exposure assessment, and makes it look pretty darn rusty. Now with NM there is the potential to get some aspect of quantitative measurements, but the instruments are generally verymore » expensive and getting an appropriate workplace personal exposure measurement can be very difficult if not impossible. The potential for workers getting exposures, however, is very real, as evidenced by a recent publication reporting worker exposures to polyacrylate nanoparticles in a Chinese factory (Song et al. 2009). With something this complex and challenging, how does a concept as simple as Control Banding (CB) save the day? Although many IHs have heard of CB, most of their knowledge comes from its application in the COSHH Essentials toolkit. While there is conflicting published research on COSHH Essentials and its value for risk assessments, almost all of the experts agree that it can be useful when no OELs are available (Zalk and Nelson 2008). It is this aspect of CB, its utility with uncertainty, that attracted international NM experts to recommend this qualitative risk assessment approach for NM. However, since their CB recommendation was only in theory, we took on the challenge of developing a working toolkit, the CB Nanotool (see Zalk et al. 2009 and Paik et al. 2008), as a means to perform a risk assessment and protect researchers at the Lawrence Livermore National Laboratory. While it's been acknowledged that engineered NM have potentially endless benefits for society, it became clear to us that the very properties that make nanotechnology so useful to industry could also make them dangerous to humans and the environment. Among the uncertainties and unknowns with NM are: the contribution of their physical structure to their toxicity, significant differences in their deposition and clearance in the lungs when compared to their parent material (PM), a lack of agreement on the appropriate indices for exposure to NM, and very little background information on exposure scenarios or populations at risk. Part of this lack of background information can be traced to the lack of risk assessments historically performed in the industry, with a recent survey indicating that 65% of companies working with NM are not doing any kind of NM-specific risk assessment as they focus on traditional PM methods for IH (Helland et al. 2009). The good news is that the amount of peer-reviewed publications that address environmental, health and safety aspects of NM has been increasing over the last few years; however, the percentage of these that address practical methods to reduce exposure and protect workers is orders of magnitude lower. Our intent in developing the CB Nanotool was to create a simplified approach that would protect workers while unraveling the mysteries of NM for experts and non-experts alike. Since such a large part of the toxicological effects of both the physical and chemical properties of NM were unknown, not to mention changing logarithmically as new NM research continues growing, we needed to account for this lack of information as part of the CB Nanotool's risk assessment. We chose a standardized 4 X 4 risk matrix (see figure 1) as our starting point, working with the severity parameters on one axis and the probability parameters on the other. The development of the severity axis was certainly the hardest part of our effort. This required the dissection of NM and its physicochemical properties which are often unknown, adding information on the PM which is far more available, and somehow scoring these input factors in a manner that appropriately weighted each factor. We decided to give unknown input factors a score of 75% of the points for each category, because otherwise the instinct of considering it as extremely dangerous would kick in and the highest level of control would almost always be the outcome.« less

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
978412
Report Number(s):
LLNL-JRNL-421516
TRN: US201010%%82
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Journal Article
Resource Relation:
Journal Name: The Synergist, vol. 21, no. 3, March 1, 2010, pp. 26-29; Journal Volume: 21; Journal Issue: 3
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; CHEMICAL PROPERTIES; CLEARANCE; DEPOSITION; EDUCATIONAL FACILITIES; EPIDEMIOLOGY; GOLD; LAWRENCE LIVERMORE NATIONAL LABORATORY; LUNGS; OCCUPATIONAL EXPOSURE; POLYACRYLATES; PROBABILITY; RECOMMENDATIONS; RISK ASSESSMENT; SAFETY; SAMPLING; TOXICITY

Citation Formats

Zalk, D, and Paik, S. Control Banding and Nanotechnology Synergist. United States: N. p., 2009. Web.
Zalk, D, & Paik, S. Control Banding and Nanotechnology Synergist. United States.
Zalk, D, and Paik, S. 2009. "Control Banding and Nanotechnology Synergist". United States. doi:. https://www.osti.gov/servlets/purl/978412.
@article{osti_978412,
title = {Control Banding and Nanotechnology Synergist},
author = {Zalk, D and Paik, S},
abstractNote = {The average Industrial Hygienist (IH) loves a challenge, right? Okay, well here is one with more than a few twists. We start by going through the basics of a risk assessment. You have some chemical agents, a few workers, and the makings of your basic exposure characterization. However, you have no occupational exposure limit (OEL), essentially no toxicological basis, and no epidemiology. Now the real handicap is that you cannot use sampling pumps, cassettes, tubes, or any of the media in your toolbox, and the whole concept of mass-to-dose is out the window, even at high exposure levels. Of course, by the title, you knew we were talking about nanomaterials (NM). However, we wonder how many IHs know that this topic takes everything you know about your profession and turns it upside down. It takes the very foundations that you worked so hard in college and in the field to master and pulls it out from underneath you. It even takes the gold standard of our profession, the quantitative science of exposure assessment, and makes it look pretty darn rusty. Now with NM there is the potential to get some aspect of quantitative measurements, but the instruments are generally very expensive and getting an appropriate workplace personal exposure measurement can be very difficult if not impossible. The potential for workers getting exposures, however, is very real, as evidenced by a recent publication reporting worker exposures to polyacrylate nanoparticles in a Chinese factory (Song et al. 2009). With something this complex and challenging, how does a concept as simple as Control Banding (CB) save the day? Although many IHs have heard of CB, most of their knowledge comes from its application in the COSHH Essentials toolkit. While there is conflicting published research on COSHH Essentials and its value for risk assessments, almost all of the experts agree that it can be useful when no OELs are available (Zalk and Nelson 2008). It is this aspect of CB, its utility with uncertainty, that attracted international NM experts to recommend this qualitative risk assessment approach for NM. However, since their CB recommendation was only in theory, we took on the challenge of developing a working toolkit, the CB Nanotool (see Zalk et al. 2009 and Paik et al. 2008), as a means to perform a risk assessment and protect researchers at the Lawrence Livermore National Laboratory. While it's been acknowledged that engineered NM have potentially endless benefits for society, it became clear to us that the very properties that make nanotechnology so useful to industry could also make them dangerous to humans and the environment. Among the uncertainties and unknowns with NM are: the contribution of their physical structure to their toxicity, significant differences in their deposition and clearance in the lungs when compared to their parent material (PM), a lack of agreement on the appropriate indices for exposure to NM, and very little background information on exposure scenarios or populations at risk. Part of this lack of background information can be traced to the lack of risk assessments historically performed in the industry, with a recent survey indicating that 65% of companies working with NM are not doing any kind of NM-specific risk assessment as they focus on traditional PM methods for IH (Helland et al. 2009). The good news is that the amount of peer-reviewed publications that address environmental, health and safety aspects of NM has been increasing over the last few years; however, the percentage of these that address practical methods to reduce exposure and protect workers is orders of magnitude lower. Our intent in developing the CB Nanotool was to create a simplified approach that would protect workers while unraveling the mysteries of NM for experts and non-experts alike. Since such a large part of the toxicological effects of both the physical and chemical properties of NM were unknown, not to mention changing logarithmically as new NM research continues growing, we needed to account for this lack of information as part of the CB Nanotool's risk assessment. We chose a standardized 4 X 4 risk matrix (see figure 1) as our starting point, working with the severity parameters on one axis and the probability parameters on the other. The development of the severity axis was certainly the hardest part of our effort. This required the dissection of NM and its physicochemical properties which are often unknown, adding information on the PM which is far more available, and somehow scoring these input factors in a manner that appropriately weighted each factor. We decided to give unknown input factors a score of 75% of the points for each category, because otherwise the instinct of considering it as extremely dangerous would kick in and the highest level of control would almost always be the outcome.},
doi = {},
journal = {The Synergist, vol. 21, no. 3, March 1, 2010, pp. 26-29},
number = 3,
volume = 21,
place = {United States},
year = 2009,
month =
}
  • Control Banding (CB) strategies to prevent work-related illness and injury for 2.5 billion workers without access to health and safety professionals has grown exponentially this last decade. CB originates from the pharmaceutical industry to control active pharmaceutical ingredients without a complete toxicological basis and therefore no occupational exposure limits. CB applications have broadened into chemicals in general - including new emerging risks like nanomaterials and recently into ergonomics and injury prevention. CB is an action-oriented qualitative risk assessment strategy offering solutions and control measures to users through “toolkits”. Chemical CB toolkits are user-friendly approaches used to achieve workplace controls inmore » the absence of firm toxicological and quantitative exposure information. The model (technical) validation of these toolkits is well described, however firm operational analyses (implementation aspects) are lacking. Consequentially, it is often not known if toolkit use leads to successful interventions at individual workplaces. This might lead to virtual safe workplaces without knowing if workers are truly protected. Upcoming international strategies from the World Health Organization Collaborating Centers request assistance in developing and evaluating action-oriented procedures for workplace risk assessment and control. It is expected that to fulfill this strategy’s goals, CB approaches will continue its important growth in protecting workers.« less
  • Control Banding (CB) strategies offer simplified solutions for controlling worker exposures to constituents that are found in the workplace in the absence of firm toxicological and exposure data. These strategies may be particularly useful in nanotechnology applications, considering the overwhelming level of uncertainty over what nanomaterials and nanotechnologies present as potential work-related health risks, what about these materials might lead to adverse toxicological activity, how risk related to these might be assessed, and how to manage these issues in the absence of this information. This study introduces a pilot CB tool or 'CB Nanotool' that was developed specifically for characterizingmore » the health aspects of working with engineered nanoparticles and determining the level of risk and associated controls for five ongoing nanotechnology-related operations being conducted at two Department of Energy (DOE) research laboratories. Based on the application of the CB Nanotool, four of the five operations evaluated in this study were found to have implemented controls consistent with what was recommended by the CB Nanotool, with one operation even exceeding the required controls for that activity. The one remaining operation was determined to require an upgrade in controls. By developing this dynamic CB Nanotool within the realm of the scientific information available, this application of CB appears to be a useful approach for assessing the risk of nanomaterial operations, providing recommendations for appropriate engineering controls, and facilitating the allocation of resources to the activities that most need them.« less
  • Control Banding (CB) strategies offer simplified solutions for controlling worker exposures to constituents often encountered in the workplace. The original CB model was developed within the pharmaceutical industry; however, the modern movement involves models developed for non-experts to input hazard and exposure potential information for bulk chemical processes, receiving control advice as a result. The CB approach utilizes these models for the dissemination of qualitative and semi-quantitative risk assessment tools being developed to complement the traditional industrial hygiene model of air sampling and analysis. It is being applied and tested in small and medium size enterprises (SMEs) within developed countriesmore » and industrially developing countries; however, large enterprises (LEs) have also incorporated these strategies within chemical safety programs. Existing research of the components of the most available CB model, the Control of Substances Hazardous to Health (COSHH) Essentials, has shown that exposure bands do not always provide adequate margins of safety, that there is a high rate of under-control errors, that it works better with dusts than with vapors, that there is an inherent inaccuracy in estimating variability, and that when taken together the outcomes of this model may lead to potentially inappropriate workplace confidence in chemical exposure reduction in some operations. Alternatively, large-scale comparisons of industry exposure data to this CB model's outcomes have indicated more promising results with a high correlation seen internationally. With the accuracy of the toxicological ratings and hazard band classification currently in question, their proper reevaluation will be of great benefit to the reliability of existing and future CB models. The need for a more complete analysis of CB model components and, most importantly, a more comprehensive prospective research process remains and will be important in understanding implications of the model's overall effectiveness. Since the CB approach is now being used worldwide with an even broader implementation in progress, further research toward understanding its strengths and weaknesses will assist in its further refinement and confidence in its ongoing utility.« less
  • The Risk Level Based Management System (RLBMS) is an occupational risk management (ORM) model that focuses occupational safety, hygeiene, and health (OSHH) resources on the highest risk procedures at work. This article demonstrates the model's simplicity through an implementation within a heavily regulated research institution. The model utilizes control banding strategies with a stratification of four risk levels (RLs) for many commonly performed maintenance and support activities, characterizing risk consistently for comparable tasks. RLBMS creates an auditable tracking of activities, maximizes OSHH professional field time, and standardizes documentation and control commensurate to a given task's RL. Validation of RLs andmore » their exposure control effectiveness is collected in a traditional quantitative collection regime for regulatory auditing. However, qualitative risk assessment methods are also used within this validation process. Participatory approaches are used throughout the RLBMS process. Workers are involved in all phases of building, maintaining, and improving this model. This work participation also improves the implementation of established controls.« less
  • An analysis of the data on nanomaterial texturing showed that textures arise even when there are no apparent causes of their formation. It was noted that the texturing problem is particularly urgent for medical and biological applications. The correlation of texturing with nanocrystal shaping was indicated. It was emphasized that the effect of the size factor on nanocrystal morphology is especially pronounced for crystals with linear sizes smaller than 10 nm. It was proposed to control textures of such crystals by the OTED method implemented in the electron microscope column.