# Current Strategies for Engineering Controls in Nanomaterial Production and Downstream Handling Processes/Control Evaluations

​CHAPTER 4
Control Evaluations
The effectiveness of engineering controls for reducing exposures to nanomaterials during manufacturing and handling has not been widely investigated. To evaluate control measures in nanomanufacturing facilities, investigators need to collect both quantitative and qualitative data to describe nanoparticle emissions. Accurate direct-reading instruments allow investigators to identify the source of contamination in real time for various task scenarios. More detailed information about the materials, such as morphology and chemical characteristics, can be obtained by collecting air filter samples for off-line analysis.
4.1 Approaches to Evaluation
Strategies for measuring nanomaterial exposures and emissions in the workplace are being developed and evaluated by a range of researchers [Brouwer et al. 2009; NIOSH 2009a; OECD 2009; Ramachandran et al. 2011]. Because there are currently no exposure limits for engineered nanomaterials in the United States, a multifaceted approach combining qualitative analysis with quantitative means should be used to determine nanoparticle emissions and control effectiveness [Oberdörster et al. 2005]. However, some researchers have suggested using non-mass-based metrics such as surface area or particle number as a reasonable approach to assessing health effects [Wittmaach 2007; Rushton et al. 2010; Oberdörster et al. 2005]. The evaluation procedures include (1) identification of emission sources, (2) background and area monitoring, (3) air concentration measurement by direct-reading instruments and filter-based sampling, and (4) measurement of air velocity and patterns.
4.1.1 Identification of Emission Sources
The main purpose of the initial assessment or walk-through survey is to identify potential sources of emissions and to help researchers prepare a sampling plan for the in-depth evaluation of processes and control measures. Portable direct-reading devices (e.g., handheld CPCs and photometers) are recommended for quick identification. The initial assessment should involve looking at the processes and equipment as well as the general plant environment. To optimize and improve engineering controls, a control checklist is recommended for collecting basic information on methods, manufacturing processes, and existing controls.
4.1.2 Background and Area Monitoring
A plan to assess control effectiveness requires that measurements are first taken of background concentrations in adjacent work areas. This allows the contribution of ​individual processes to be assessed by removing the background component [Brouwer et al. 2004; Demou et al. 2008; Peters et al. 2009]. The background measurement should be repeated after process or task evaluations. High background concentrations need to be addressed before control evaluation. The following factors can affect background data:
Area (or static) monitoring can also be conducted to evaluate the general air quality of workplaces. Instruments such as the CPC and impactors are suitable for this type of monitoring. Ideally, filter samples can be taken at the same location as area monitoring with direct-reading instruments to make a side-by-side comparison.
4.1.3 Air Monitoring and Filter Sampling
The selection of direct-reading instruments (Table 3) for field evaluation must cover a wide range of particle sizes. Particle diffusion occurs rapidly when nanoparticles are released in the workplace. It results in nanomaterial agglomerates because of particle collisions. For example, the average particle size (or size distribution) is larger during product transfer than right after product harvesting. Based on the data collected during initial assessment, characterization of nanomaterial emissions can be conducted with direct-reading instruments to provide higher resolutions of spatial and time variation. To evaluate control efficiency for specific processes or tasks, the sampling ports should be located as close as possible to the suspected emission sources but outside of control measures (or at a worker’s breathing zone). Filter sampling for off-line qualitative analysis must occur in parallel with real-time monitoring. Sampling duration may not be an issue for most direct-reading instruments but should be considered for filter sampling to avoid overloading. The data collected from an initial assessment can be used to determine sampling time and flow rate for filter samples.
​Table 3. Summary of instruments and techniques for monitoring nanoparticle emissions in nanomanufacturing workplaces
| Metric | Instrument | Remarks |
| Aerosol concentration | CPC | Real-time measurement. Typical concentration range of up to 400,000 particles/cm3 for stand-alone models with coincidence correction; 100,000 particles/cm3 for hand-held models. |
| | DMPS | SMPS often uses a radioactive source. FMPS uses electrometer-based sensors. Concentration range from 100−107 particles/cm3 at 5.6 nm and 1−105 particles/cm3 at 560 nm. |
| Surface area | Diffusion charger | Need appropriate inlet pre-separator for nanoparticle measurement. Total active surface area concentration up to 1,000 µm2/cm3. |
| | ELPI | Real-time size-selective detection of active surface area concentration. 2×104–6.9×107 particles/cm3 depending on size range/stage. |
| Mass | Size selective static sampler | Low pressure cascade impactors. Micro-orifice impactors. |
| | TEOM | EPA standard reference equivalent method. |
| Aerosol concentration by calculation | ELPI | |
| Surface area by calculation | DMPS | |
| | DMPS and ELPI used in parallel | Surface area is estimated by difference in measured aerodynamic and mobility diameters. |
| Mass by calculation | ELPI | Calculated by assumed or known particle charge and density. |
| | DMPS | Calculated by assumed or known particle charge and density. |
Abbreviations: CPC=condensation particle counter; DMPS=differential mobility particle sizer; SMPS=scanning mobility particle sizer; FMPS=fast mobility particle sizer; ELPI= electric low pressure impactor; TEOM=tapered element oscillating microbalance
​4.1.4 Assessment of Air Velocities and Patterns
The measurement of air velocity and pattern is important to establish sampling locations, evaluate outdoor contaminant penetration, and assess the performance of existing control measures. Two widely used air fluid velocity measuring devices are the Pitot tube and the hot-wire anemometer. The Pitot tube is useful to measure flow in ducts with high temperatures and/or high particle concentrations, which could damage the thermal anemometer probe. Shown in Figure 20, a Pitot tube is a primary standard that measures total and static pressures, and air velocity is calculated by using the pressure difference (i.e., velocity pressure) based on the Bernoulli equation. The method for conducting a Pitot traverse is described in the ACGIH Industrial Ventilation Manual [ACGIH 2013]. The Pitot traverse is typically used to measure duct air velocity to estimate overall system exhaust flow rate. Occasionally it is difficult to find a suitable location for Pitot tube traverses. Accurate duct velocity can be obtained using this method; however, poor measuring locations will cause inaccurate estimates of exhaust air flow. Sometimes the airflow through a hood can only be determined by measuring the air velocity at the hood face.
The measurement of fume hood face velocity is an important method to assess proper operation and containment. The average hood face velocity can be measured by dividing the opening of the hood into equal area grids of approximately one square foot and logging the velocity at the center of each grid with the thermal anemometer. To measure the velocities at each grid point, the anemometer should be held perpendicular to the direction of air flow. An average face velocity can be calculated while the variation in hood velocity from grid to grid should be assessed and noted [ACGIH 2013; ASHRAE 1995].
Figure 20. Operating principle of a Pitot tube (left) and different types of Pitot tubes (right)
​In addition to Pitot tubes and anemometers for measuring air velocity, smoke generators provide a low-cost method to visualize airflow patterns around control measures. Figure 21 shows an example of a smoke generator. Airflow visualization techniques can be used to help understand the patterns of airflow in and around exhaust hoods and pressure differences between adjacent areas/rooms. Smoke can be released around the edge of, or inside of, a local exhaust hood to visualize the airflow patterns. This will help determine whether airborne particles are being effectively captured and removed by the ventilation system. Recorded observations should concentrate on (1) how much of the smoke is entrained into the LEV, (2) how quickly the exhaust captures the smoke, (3) the direction of air flow, and (4) whether or not any of the smoke visibly enters the worker’s breathing zone. In addition, multiple replications of smoke-release observations should be made at locations where LEV performance is marginal or poor as indicated by reverse airflow, lack of air movement, slow clearance time, and escape of smoke from the hood. Special attention should be paid in subsequent tracer gas testing and air velocity measurements to locations where smoke release observations indicate poor or marginal capture efficiency. In addition, video may be taken of airflow visualization tests to provide feedback information to the company on system performance and factors that negatively affect hood performance.
Another use for airflow visualization is the evaluation of room pressurization status. It is recommended that rooms where nanomaterials are used be kept at an atmospheric pressure that is lower than adjacent areas. This condition helps contain the materials and reduce exposures to workers in other areas of the plant. Smoke should be released at the interfaces (doors or other openings) between any nanomaterial production areas and attached spaces. By releasing smoke at these interfaces, it can be easily observed whether air is moving into or out of the production area and proper remediation approaches may be implemented where necessary.
Photo by NIOSH
Figure 21. Smoke generator to visualize airflow
​To qualitatively assess whether exhaust re-entrainment may be an issue, smoke can be released within each hood in the production room while a researcher observes the emission of the smoke through the exhaust stack. This qualitative test will help to evaluate the potential for re-entrainment of exhaust into any air intakes or roof openings. The behavior of the exhaust plume is dependent on varying environmental conditions such as wind speed and direction; therefore, this test should be repeated to capture the potential for re-entrainment under a variety of conditions. In addition, air velocity measurements should be taken at the center of the exhaust duct opening to evaluate the discharge velocity of the hood exhaust. These readings should be evaluated, along with the physical design and installation of the exhaust stack, against guidance from consensus standards organizations such as ASHRAE, ACGIH, or AIHA.
4.1.5 Facility Sampling and Evaluation Checklist
When evaluating a facility that manufactures or uses nanomaterials, it is important to first assess what engineering controls are in place in the facility. The initial assessment should involve looking at the processes and equipment as well as the general plant environment, the effective use of the engineering control by the operator(s), and the overall performance of the control equipment. Checklists are useful tools for helping to identify the process and facility factors related to nanomaterial production, use, emissions, and exposure. A checklist as shown in Table 4 may help for collecting basic process information (e.g., capacity, location, and usage) and control operation and maintenance parameters to ensure effectiveness of exposure control.
​Table 4. Checklist of controls for nanomaterial manufacturing and handling
| Item | Category | Data |
| Process/task | Category (select all applicable) □ Weighing □ Mixing □ Transferring □ Drying □ Cleaning □ Cutting/sanding □ Harvesting □ Unpacking ENMs □ Maintenance/repair □ Finishing (drilling, sawing, grinding) □ Packaging/shipping □Others: ________________________ Background | Workspace Duration (min) Frequency (times per day) Number of workers involved PPE type Concentration Size distribution: ___________________ Number: __________________________ Mass: _____________________________ |
| Nanomaterial | □ SWCNT □ MWCNT □ Other carbon-based □ Metals □ Oxides □ Quantum dots □ Composite: ____________________ □ Others: ________________________ | Processing rate/volume Primary particle size Concentration at source Number: __________________________ Mass: _____________________________ Concentration at worker breathing zone or area (designate) Number: __________________________ Mass: _____________________________ Breathing zone: ____________________ Area: _____________________________ ​ |
| Control type | □NONE □Local exhaust □General exhaust/dilution □Ventilated enclosure □Fume hood □Dust collector □Laminar room □Glove box □Booth □ Other:_________________________ | Dimensions  Location  Operation □ Hood type □ Face velocity: ___________________ □ Flow rate: _______________________ □ Temp: __________________________ □ Enclosure integrity □ Airflow patterns □ Recirculation  Fan/filtration information □Filter type: _________________________ □Manufacturer: ______________________ □Resistance (pressure drop): __________ □Nominal design flow rate: ___________ □Fan type: __________________________ □Flow rate: __________________________ □Stack position/design: □Visual observation |
| Visual Observation | Workspace  Surface contamination  Housekeeping  Layout ​ | Workspace  Surface contamination  Housekeeping  Layout ​ |
| Industrial Exhaust Ventilation Deficiency Report Worksheet □ Building: □ Room: □ Hood number: □ Date: □ Investigator/reporter: □ Fan number: Notes and sketch  Management Ductwork □ No local cognizant person □ Lack of records □ Lack of up-to-date plans and specifications □ Lack of emergency plan □ Insufficient employee training □ No hood testing mechanism □ No hood-use approval mechanism □ Holes, air leaking □ Dents □ Poor construction □ Plugged □ Corroded □ Leaking □ Dampers improperly set □ Fire dampers □ Doesn’t meet SMACNA qualifications Hood Fan/Motor □ Improper type for operation/chemicals used □ Air leaking from hood (smoke noncontainment) □ Surfaces corroded □ Surfaces dirty □ Hood mechanisms inoperable □ Lack of real-time airflow monitor □ Flammable construction materials □ Slots not open to appropriate size □ Slots blocked by equipment, chemicals □ Worn out or corroded □ Insufficient rpm □ Belts slipping or broken □ Motor burned out □ Undersized fan Hood operations Stack □ Use of hood when hood exhaust off □ Hood not being used □ Inappropriate materials/equipment in hood □ Noisy □ Not attached □ Inappropriate location □ Inadequate height □ Stack exit velocity insufficient □ Aesthetic enclosure hinders dispersion Work practices Exhaust hood □ Untrained personnel □ Rapid movements at hood face □ Placing upper body in hood □ Operating outside hood □ Inadequate exhaust volume □ Inadequate face velocity □ Inadequate face velocity range □ Turbulence in hood face ​ Make-up air System maintenance □ No replacement air □ Insufficient air for dilution of fugitive emissions □ Contaminated by exhaust air □ Supply diffuser blows on hood face □ Supply diffuser blocked □ Temperature inadequate □ Employee complaints (noise, draft) □ Does not meet ASHRAE 62 provisions □ Supply not balanced with exhaust □ Inadequate maintenance (equipment broken) □ Lack of ongoing PM program Worksite Manifold exhaust systems □ Cluttered, housekeeping poor, dirty □ Hood positioned near door, window, walkway, other turbulence □ Fire escape routes blocked □ Aisles blocked □ Likelihood of fire/explosion; mixed chemicals □ Corrosion in manifold □ Condensation in manifold □ One hood goes positive □ Part of system under positive pressure Notes |||
SMACNA: Sheet Metal and Air Conditioning Contractors’ National Association
​4.2 Evaluating Sources of Emissions and Exposures to Nanomaterials
4.2.1 Direct-reading Monitoring
Currently, it is unclear which metrics associated with exposures to engineered nanomaterials are most important from a health and safety perspective. The mass-based metric is traditionally used to characterize toxicological effects of exposure to air contaminants. Animal in vivo exposure studies and cell-culture-based in vitro experiments show that size and shape are the two major factors influencing toxicological effects of engineered nanomaterials. Some of the instruments developed to characterize nanoparticles are capable of real-time measurement [Brouwer et al. 2004; Pui 1996; Ramachandran 2005]. Real-time measurement of aerosolized particles, including primary nanoparticles and agglomerates, play an important role in identifying nanomaterial emissions and evaluating control systems during field surveys. The measuring devices used to evaluate controls in the workplace should be portable and robust. Information about readily available instruments and techniques for nanoparticle monitoring (Table 3) has been summarized and discussed in technical reports [BSI 2007a; EU-OSHA 2009; HSE 2004; ISO 2007, 2008; Mark 2007; Park et al. 2010a, b, 2011].
It is noted that some of the instruments on the list in Table 3 are not suited for monitoring nanomaterial emissions in the workplace. For instance, the tapered element oscillating microbalance (TEOM) is used by the Environmental Protection Agency as a standard reference equivalent method to monitor environmental air quality, but the cut-off particle sizes of 10, 2.5, or 1 µm and dimensions of this instrument limit its use for workplace sampling. Another example is the scanning monitoring particle sizer (SMPS), which uses a radioactive source to bring the sampling aerosol to charge equilibrium. This can make shipping difficult. Sometimes it can be difficult to obtain quantifiable mass concentrations of nanomaterials in the workplace using impactor sampling. Newly developed devices, such as photometers, can detect nanoparticles as small as 50−100 nm with resolution around 1 µg/m$^3$. These instruments can provide continuous monitoring for real-time mass concentrations.
Data from direct-reading instruments only provide a semiquantitative indication of potential nanoparticle emissions. Fluctuating background concentrations may make determination of control efficiency difficult; changes in background concentration may lead the evaluator to think that the controls are performing either better or worse than they are actually performing. In addition, direct-reading instruments cannot distinguish particle source and composition; these can only be determined through off-line microscopic and chemical analysis.
Sampling quality is always an issue for field evaluation. High-quality sampling results can be obtained by following certain steps. The sampling data can only be trusted by using instruments that have been calibrated for nanoparticle sampling before use. Factory calibration for particle counters and sizers typically uses reference materials having a range of particle sizes. If possible, the instruments should be calibrated with the target nanomaterials in the laboratory before using them for field study. The comparison calibration should also be done on identical instruments if they will be used in a field survey. To maintain consistent sampling performance, a zero check for instruments should be performed before daily use and after sampling high-particle emissions. Sampling loss due to particles deposited in sampling tubes can be lowered by using conductive tubing and minimizing tubing length and bends in the tubing. The sampling location should be considered carefully, because nanoparticles diffuse rapidly through the workplace air. The choice of sampling location could have a large influence on the sampling results. The sampling ports must be kept as close as possible to the emission source.
​4.2.2 Off-line Analysis
In addition to direct-reading instrument measurements, nanoparticle emissions can also be characterized using off-line analysis techniques. Off-line analysis methods can determine the physical and chemical properties of airborne nanomaterials, such as particle size, shape, surface area, composition, and agglomeration state. These properties are useful to evaluate exposure and toxicology of nanomaterials in the workplace. Off-line analysis can also be useful in separating background nanomaterials from engineered nanomaterials, based on size, shape, morphology, etc.
NIOSH has developed techniques for off-line analysis using filter samples. NIOSH Method 7402 (Asbestos by TEM) was developed to collect filter samples of materials with large aspect ratios for analysis using transmission electron microscopy (TEM) and can be used to determine particle morphology and geometry. NIOSH Method 5040 (Diesel particulate matter as elemental carbon) can be used to measure elemental carbon (e.g., CNT, CNF). Other nanomaterials (e.g., metals) can be collected on filters and analyzed using NIOSH Method 7300 (Elements by ICP). Using the mass determined by chemical analysis and dividing by the total air flow volume will provide a mass concentration of the nanomaterial of interest. As with real-time instrumentation, background samples are collected to help distinguish nanomaterials from incidental ultrafine aerosols. The optical diameters of single particles and agglomerates can be compared to data from direct-reading instruments discussed above.
Filters overloaded with particles cannot be analyzed by direct-transfer TEM analysis. Therefore, filter sample volume needs to be balanced against the particle emission rate to avoid filter overload. The results of the initial walk-through survey with portable particle counters should provide basic information to help determine appropriate filter sampling volume and collection time.
4.2.3 Video Exposure Monitoring
Video exposure monitoring (VEM) is an exposure assessment technique in which real-time monitoring devices (e.g., nanoparticle and dust monitors) are synchronized with video of the work activity [Beurskens-Comuth et al. 2011]. The product of VEM is a video of the work activity with a graphical presentation of exposure concentrations that corresponds to the job task displayed on the video. VEM aides in the identification of work practices that can contribute significantly to overall exposure patterns by giving a visual display of work activities and the corresponding real-time monitoring values. With this exposure assessment tool, both management and employees can be shown which activities have the highest exposure concentrations and can therefore benefit from a change in work practice, installation of engineering controls to mitigate the exposure, or the use of PPE.
The VEM method was initially developed by NIOSH engineers in the late 1980s to bring together work activity data (video recordings) with direct-reading exposure data. By identifying the critical activities that contribute most to a worker’s exposure, sampling resources can be directed to controlling those job activities that affect exposures. Work activity variables can also be keyed into the exposure database to statistically assess the impact of work activities on exposures. The method permits researchers and safety and health professionals to capitalize on the time element of the direct-reading data by uniting the exposure measurement with the corresponding work activities. The VEM method allows direct-reading monitors to be used as more than simple detectors and have a significant impact on occupational exposures.
​4.3 Evaluating Ventilation Control Systems
Several methodologies are available to evaluate local exhaust systems and other exposure controls. These techniques include indirect approaches, such as the measurement of capture velocity, slot velocities, hood static pressure, and other system performance parameters [Goodfellow and Tahti 2001]. Often these measures are compared with design guidance or standards from organizations such as ASHRAE, ANSI, AIHA, and ACGIH. In general, these tests provide a method of checking system performance without the requirement for expensive instrumentation or a high level of operator experience.
Because these measures do not directly assess system performance, it is often a good idea to use methods that are more specialized than these indirect methods. One method commonly used to evaluate the capture efficiency of the LEV system is the quantitative capture test. Tracer gas release and measurement is a method used to quantitatively estimate the efficiency of industrial exhaust ventilation hoods [Hampl 1984; Hampl et al. 1986; Marzal et al. 2003b]. This method typically involves using a surrogate for the process-generated contaminant and requires the use of special measurement and dispersion equipment to conduct the test. A variety of tracers have been used, including oil mist aerosols, polystyrene latex spheres, and gases [Beamer et al. 2004; Ellenbecker et al. 1983; Hampl 1984].
In addition to the quantitative capture method, qualitative methods, such as smoke release or dry ice tests, are often used to evaluate air movement. Smoke generation and capture is a method often used to qualitatively evaluate the performance of ventilation controls [Marzal et al. 2003a; Woods and Mckarns 1995]. With this method, a source is used to introduce smoke in and around the hood. This allows the researcher to better understand the performance of the hood and evaluate the effect of cross currents on the capture of contaminants. These tests not only give the experimenter a sense of the system performance but provide invaluable information on where other measurements, such as air velocities and tracer gas experiments, should be concentrated. This testing is often conducted while workers are not in the production area, either after the work shift or while workers are on break.
4.3.1 Standard Containment Test Methods for Ventilated Enclosures
Some standard test methods (Table 5) to evaluate fume hoods have been developed: Invent-UK method, DIN 12924, BS 7258, EN 14175:2003, and ANSI/ASHRAE 110-1995. One major difference between ANSI/ASHRAE 110-1995 and other standard test methods is that only one sampling probe is used to detect the test gas concentration near the worker’s breathing zone. Other test methods adopt multiple sampling probes connected to a manifold to obtain the area concentration near the fume hood opening. The test methods of DIN 12924 and ANSI/ASHRAE 110-1995 use a manikin to test the containment effectiveness of fume hoods. Dynamic test conditions are specified in the test methods of EN 14175:2003 and ANSI/ASHRAE 110-1995. The purpose of the dynamic test is to evaluate the hood during typical maneuvers such as raising or lowering the sash and simulating the airflow disturbance related to a person walking in front of the hood.
During field evaluations, ventilated enclosures should also be tested during normal-use conditions. Collecting samples both inside and outside the containment opening and in the worker’s breathing zone is recommended to assess control effectiveness when workers are performing standard tasks.
​Table 5. Comparison of the fume hood performance test methods
| Test method | Invent-UK | DIN 12924 | BS 7258 | EN 14175:2003 | ANSI/ASHRAE 110-1995 |
| Country | United Kingdom | Germany | Great Britain | European Union | United States |
| Test parameters | Face velocity | Tracer gas test | Tracer gas test | Face velocity | Face velocity and cross draft |
| | Tracer gas test | | | Tracer gas test | Smoke visualization |
| | | | | Robustness test (dynamic test by walk-bys and traffic) | Tracer gas test |
| Tracer gas | 10% SF$_6$ + 90% N$_2$ @ 3.0 LPM | 10% SF$_6$ + 90% N$_2$ @ 3.33 LPM | 10% SF$_6$ + 90% N$_2$ @ 2.0 LPM | 10% SF$_6$ + 90% N$_2$ @ 2-4 LPM | 100% SF$_6$ @ 4.0 LPM |
| Tracer gas sampling probes | 9 | 20 | Multi-probes depending on opening size | Multi-probes (inner and outer grids) | 1 in breathing zone |
| Use of manikin | No | Yes | No | No | No |