Abstract
Abstract
Airborne nanomaterials have the potential to impact environmental, public, and occupational health. As such, background and incidental airborne nanomaterials are ubiquitous in both developed and emerging countries. Furthermore, increased application of engineered nanomaterials (ENMs) in consumer goods and research and development markets has led to a corresponding growth of nanomaterial-related manufacturing to meet this demand. As these sources are extremely diverse, opportunities for exposure to airborne nanomaterials are equally diverse. Environmental and occupational exposures to nanomaterials have the potential to occur if the material is not safely handled or the activity is not effectively contained. However, evaluating and assessing potential exposure to airborne nanomaterials pose new challenges due to their small size, their negligible mass, and their high diffusivities. In addition to continuing questions regarding such issues as selection of appropriate dose metrics (mass, surface area, or number) and the identification of physicochemical characteristics of nanomaterials that impact environmental and human health, sampling strategies may be necessary to identify any spatial and temporal changes in nanomaterial concentration and physicochemical characteristics while also differentiating incidental and ENMs from background nanomaterials. Currently, exposure assessment and routine monitoring for airborne nanomaterials are either very minimal or nonexistent. Whenever monitoring efforts occur, they do not generally follow any consistent strategy. However, strategies to conduct exposure assessments have begun to emerge. The goal of this article is to review sampling strategies and instrumentation characteristics needed to carry out industrial hygiene exposure assessments for airborne nanomaterials.
Introduction
Nanomaterials that impact public health are typically ambient aerosols. The public health research community typically refers to these nanomaterials as ultrafine particles with an upper size between 100–200 nm. The variability in the upper size originates from the uncertainty in the transition point from the ultrafine mode to the accumulation mode (∼200 nm to 2.5 μm) (Hinds, 1999). Combustion is the primary source of ultrafine particles that impact localized areas near the source. New particle formation via nucleation and condensation (Stanier et al., 2004) and photochemical reactions that produce secondary organic aerosols (Kulmala et al., 2000) are secondary sources that are more homogeneous and, hence, more regional. Public health impacts of nanomaterials from these sources affect urban and rural areas of both developed and emerging countries. Mobile sources and industrial emissions are the combustion products common in developed countries (Kittelson, 1998). Residential cooking, heating, and lighting using biomass combustion are the source of nanomaterials in developing countries. The nanomaterials formed by combustion are high surface area (SA), low density fractal agglomerates composed of elemental carbon and polycyclic aromatic hydrocarbons (Friedlander, 2000; Eiguren-Fernandez et al., 2003).
Through rapid growth in the past several years, nanotechnology encompasses broad reaching industries, including pharmaceuticals, advanced materials, medicine, agriculture, electronics, and energy (Issues in Science, 2005). An estimated two million workers will be working in nanotechnology manufacturing within the next 15 years (Roco, 2003). These employees have the potential to be at risk to ENM exposure if not properly managed. As an outcome from this industrial interest, consumer products that contain nanomaterials are increasing. Although the current focus for exposure assessment, for industrial hygiene purposes remains, with occupational environments; it is only a matter of time before a significant proportion of the population will use or come into contact with products enabled by nanotechnology. Additionally, it is anticipated that the methods and instrumentation developed for measuring airborne ENMs in occupational environments could be adapted to other environmental situations in the future. From an occupational perspective, industrial scale production of ENMs and subsequent formulation and application in products typically produce high volumes of materials, yet their composition and characteristics are generally more uniform. Research scale applications for ENMs may require lower volumes of materials, but their compositions and characteristics are more diverse in a given occupational area (HSE, 2004; NIOSH, 2012).
Although large investments continue in nanotechnology, the funding for environmental, health, and safety aspects of nanotechnology may be currently insufficient to protect occupational health (Maynard, 2006; NNI, 2011). As there are many fundamental unknowns regarding health risks of nanomaterials, key mechanisms for exposure and toxicity effects of nanomaterials remain poorly understood. Key questions include the following:
1. What is the persistence of airborne nanomaterials? 2. How stable are nanomaterials given atmospheric and occupational conditions? 3. How do physicochemical characteristics influence fate and transport? 4. What are likely exposure routes (e.g., inhalation, dermal, ingestion, and ocular)? 5. What are suitable dose metrics (e.g., particle mass, number, or SA)? 6. How do nanomaterials translocate across the body? 7. What are key mechanisms of toxicity (Kandlikar et al., 2007)?
As exposure is defined as the intensity or concentration of a contaminant over a time interval with biological relevance (e.g., an adverse health outcome), exposure and hazard need to be characterized and understood in the assessment of the overall risk for ENMs. Uncertainty persists regarding the appropriate metric by which intensity should be measured for inhalation exposures (NIOSH, 2006; ISO, 2007). Although mass concentration has been regarded as the most appropriate exposure metric associated with health effects of particle exposures, the appropriateness of the mass concentration metric for nanomaterials remains unclear (McCawley et al., 2001). Particle number and SA concentrations have been proposed as more suitable alternatives for nanomaterials (Oberdörster, 1996). This distinction has important implications for conducting exposure assessment to nanomaterials and for suitable instruments to detect and quantify the presence of airborne nanomaterials. Additionally, this lack of information means that appropriate public health standards (e.g., ambient air quality standards) and occupational exposure limits (OELs) have not been established for nanomaterials. Because most occupational exposure assessment strategies presuppose the existence of OELs, their notable absence for nanomaterials may hinder exposure monitoring efforts. While current exposure monitoring in occupational settings for nanomaterials is either very minimal or nonexistent, when it does exist, it generally does not follow a consistent strategy. Additionally, these efforts are not optimized for cost and efficiency, limiting their widespread use.
Discussion
Airborne nanomaterial exposures
Public exposures
Numerous epidemiological studies link nanomaterial exposure to respiratory and nonrespiratory adverse health outcomes. For example, the public's exposure to nanomaterials is associated with reductions in peak expiratory flow (Pekkanen et al., 1997), cardiovascular mortality (Wichmann et al., 2000), acute lower respiratory infections (Smith et al., 2000), low birth weight (Sram et al., 2005), and nutritional deficiencies (Mishra and Retherford, 2007). The importance of mobile sources and residential biomass combustion to overall nanomaterials emission rates has focused exposure research in these areas.
People who reside near major, high speed roadways or that spend significant time traveling inside vehicles have the highest exposures to mobile source nanomaterials. People that live more than 300 m from a major roadway are not exposed to nanomaterial concentrations above background levels (Barzyk et al., 2009). The nanomaterial concentration rapidly decreases and size distribution shifts toward the accumulation mode as a function of distance from the roadway because of atmospheric dispersion, evaporation of volatile components, and possibly coagulation (Zhu et al., 2002). Nanomaterial penetration into vehicle cabins during commuting is also significant. Personal preferences regarding cabin ventilation via open windows, vents, and air conditioning determine the magnitude of a person's exposure. Given these factors, traveling inside a vehicle contributes 10–50% of a person's nanomaterial exposure (Zhu et al., 2007).
Biomass combustion drives nanomaterial exposure in emerging countries. One-third of the world's population relies on biomass combustion for cooking, heating, and lighting due to poverty or lack of other power sources. The stoves employed to burn the biomass produce elevated nanomaterial emissions because of poor combustion efficiency. The local community infrastructure does not have the materials and economic resources to manufacture and maintain high efficiency stoves that minimize nanomaterial emissions. As a result, indoor air quality in residences burning biomass is very poor with peak particulate matter concentrations often exceeding 20,000 μg/m3 (Ezzati and Kammen, 2001). To date, the contribution of nanomaterials to indoor air pollution produced by biomass combustion has not been quantified. One potential issue is that lack of electrical power and infrastructure at these remote study locations prevents use of the aerosol instrumentation necessary to conduct a detailed investigation of the biomass smoke size distribution.
Occupational exposures
Within workplace environments, various activities and processes have the potential for ENM emissions. Even when operations are conducted within protective environments, such as hoods, glove boxes, and secondary containment, the need for high levels of emissions controls may still exist (Tsai et al., 2008a).
In nanomaterial manufacturing, many processes can be potential sources for airborne nanomaterials, including synthesis and generation (Swihart, 2003; Kuhlbusch and Fissan, 2006; Demou et al., 2008; Park et al., 2009; Wang et al., 2011), handling (Maynard et al., 2004; Tsai et al., 2008b; Bello et al., 2009; Park et al., 2009), and packaging (Demou et al., 2008). The potential for ENM release during any of these processes are often predicated on whether the material is in liquid (i.e., colloid or suspension) or dry form (i.e., powder), with the later often considered to possess the largest potential for airborne nanomaterial release (Kuhlbusch et al., 2004; Peters et al., 2009).
Exposure assessment strategies
Public health
From a public health perspective, nanomaterial exposure assessment is a complex issue. Particulate matter epidemiologic studies in developed countries use concentrations measured at a central site to represent the population's exposure. This approach is not applicable to nanomaterial exposure assessment because of the high spatial and temporal variability in ultrafine particle concentrations as distance from the mobile source increases (Sioutas et al., 2005). The alternatives are to perform microenvironmental or personal level exposure assessments to fully characterize the linkage between nanomaterial exposure and health.
Microenvironmental assessments may be the best approach to characterize population level exposures. A microenvironmental assessment places a stationary nanomaterial monitor at various indoor and outdoor locations, such as playgrounds, residences, and commercial buildings. This approach provides nanomaterial exposure data for a large, spatially diverse population over an extended period of study. However, the capital expense of the instrumentation, operation and maintenance costs for the monitors, and concerns regarding the representativeness of the exposure concentration data to the entire population discourages implementation of this approach. Even if a study were conducted, the analytical costs may prohibit the detailed characterization of the physical and chemical nature of the nanomaterials.
Personal exposure assessments have the potential to capture the dynamics of individual, time-resolved nanomaterial exposure concentration data in the aforementioned microenvironments. However, current commercially available measurement technologies are inappropriate for assessing personal exposure to nanomaterials, especially when metrics other than mass, such as SA, need to be measured. New technologies like a miniaturized disk-type electrostatic precipitator (Qi et al., 2008) and the MicroPEM™ (Rodes et al., 2012) may shift the paradigm for personal level nanomaterial exposure assessment in developed and emerging countries. The size, weight, accuracy, and precision of these instruments increase the representativeness of the exposure assessment by minimizing exposure misclassification (Rodes and Thornburg, 2004).
Occupational environments
Uncertainties in and costs associated with conducting exposure assessments for ENMs have led to the adaptation of a limited number of approaches. In general, these exposure assessments are multi-step processes. Although the following examples involve assessing occupational environments, the same techniques could be adapted to environmental situations as well.
Briefly, control banding approaches have been used to assess risk levels and generate guidance for controls for nanomaterials in workplaces (Maynard and Kuempel, 2005; Paik et al., 2008). Control banding utilizes assumptions around grouping nanomaterials according to their hazard potential. From this, control bands are then developed based on the hazard potential (NIOSH, 2009a, 2009b) with the bands having the highest hazard potential receiving the greatest emphasis and those with lower hazard potential receiving a lower level of analysis. The control banding approach is often hampered by the lack of toxicological data used during hazard assessments (Schulte et al., 2010).
Ramachandran, et al. developed guidance that adapts a strategy from the American Industrial Hygiene Association and provides a generic framework to enable that risks to workers handling ENMs are managed properly (Ignacio and Bullock, 2006; Ramachandran et al., 2012). By leveraging knowledge on similarly exposed groups, which is based on basic characterization information about the workplace, workforce, and work operations for employees with similar roles, responsibilities, and work conditions, efficiency and cost can be minimized in conducting exposure assessments (Ramachandran et al., 2012).
Systematic development of concentration maps can be used to highlight processes and regions of occupational environments that may need additional focus and attention. Concentration mapping is a technique used to determine spatial and temporal variability of aerosol concentration and distribution in a workplace as a function of work processes. This technique can be applied to identify contaminant sources or as a presurvey tool to determine sampling locations for aerosol concentration measurements. Example of concentration mapping include studies in automotive plants (Dasch et al., 2005); for metalworking fluids (O'Brien, 2003); multi-metric assessments (Peters et al., 2006); and detection of incidental nanomaterials (Ramachandran et al., 2005; Heitbrink et al., 2009).
The Nanoparticle Emission Assessment Technique (NEAT) strategy has been developed by the National Institute for Occupational Safety and Health (NIOSH) (Methner et al., 2010a, 2010b). This strategy employs the use of multi-metric direct-read, time-integrated instruments to identify process specific emissions. If a nanomaterial release is detected, filter based sampling is then employed to collect samples for microscopy and mass/elemental concentration analysis. The tiers represent an escalation in the complexity and detail of the exposure assessment. Information collected through NEAT can be combined with metadata (e.g., location of processes) to generate concentration maps.
In 2011, a consortium of German institutions published a strategy document for ENM exposure measurement and assessment in occupational settings (VCI, 2011). The strategy outlines a three tier approach that can be applied by small to large companies. The first tier is information collection using established industrial hygiene practices to determine whether an airborne release of ENMs could occur. If an exposure potentially exists, a basic exposure assessment is conducted as defined by tier two. This assessment uses a limited set of basic instrumentation to determine if the OEL is exceeded and a significant increase in aerosol concentration is detected. At tier 3, the most advanced measurement techniques, such as electrical mobility methods, are used to assess potential workplace exposures to determine if risk management measures need implemented.
No matter the strategy employed, industrial hygienists typically use their professional knowledge and training to assess occupational environments for potential hazards. Yet, due to the significant differences between airborne nanomaterials and larger particulate matter, including negligible mass, higher diffusivity, and having size dimensions less than the visible wavelength of light, the previous experiences of industrial hygienists may not be easily translatable to the nanoscale.
Differentiating between background and engineered airborne nanomaterials
When assessing the potential for workplace exposure to airborne nanomaterials, differentiation between engineered, background, and incidental nanomaterials is a key concern. In sufficiently high concentrations, even incidental particles may be considered a mixed exposure (Evans et al., 2010), as these particles may possess adverse health risks. The resulting exposure misclassification (Rodes and Thornburg, 2004) complicates the linkage between nanoparticle source and health effect. Unfortunately, these nanoparticles can also be difficult to distinguish using common real-time instruments (Dasch et al., 2005; Peters et al., 2006). Although methods still need refinement, differentiation can be estimated or enhanced by utilizing one or more of the following techniques (Kuhlbusch et al., 2011). Each carries its own set of assumptions that must be factored into the selection of any one technique:
• Long-term monitoring: Sampling over long time scales provides more data to generate robust statistical inferences about background nanomaterial parameters. Sampling during time periods of no work activity is assumed to be representative of background concentrations. • Area monitoring: Sampling of a location with the assumption that it is representative of the area as a whole. Deviations from the background sampling location may be attributed to ENMs. • Pre/Post sampling: Sampling an area with and without ENM activities can be used to indicate which activities are associated with ENM releases. This strategy assumes that any processing without nanomaterials present corresponds to the background concentration. • Size-resolved characterization: Chemical and/or morphology characterization via filter sampling coupled with transmission electron microscopy (TEM) can be combined with other techniques to provide temporal information about airborne nanomaterial characteristics. This strategy assumes the physicochemical characteristics of the ENMs are sufficiently different from background nanomaterials to allow their differentiation.
Kuhlbusch et al. did not include personal exposure monitoring (e.g., activity based sampling) in their list of exposure assessment techniques. This standard industrial hygiene practice uses a combination of aerosol instrumentation and surveys to effectively correlate the exposure concentration, with the time of exposure and workplace activity.
Instrumentation for airborne nanomaterial detection and characterization
Although there are a number of research instruments capable of detecting and characterizing airborne nanomaterials, many are not yet suitable for occupational and field studies. From the Nanoparticle Occupational Safety and Health (NOSH) Consortium, key attributes for such instruments suitable for field studies include the following: low cost; limited size resolution with 2 to 5 distinct size bins <100 nm; simple to operate, including minimal training to collect and interpret data in addition to minimal maintenance and calibration; robust and reliable operation in a wide variety of conditions, including high and low airborne particle concentrations and broad particle chemistry sensitivity (Ostraat, 2009).
Typically, multi-metric approaches are used to measure and characterize airborne nanomaterials. Real-time instruments are used to identify areas of potential concern as various instruments are available that can be used to determine mass, SA, and number concentration for time-averaged and real-time measurements. For additional characterization of airborne nanomaterials, off-line laboratory analysis may be required. In general, this requires that samples be collected with an open-faced filter sampling or from size-selective sampling devices, such as an impactor, for off-line measurements like TEM or optical microscopy, or chemical analysis.
Categories and examples of real-time instruments that detect and measure airborne nanomaterials include the following:
• Portable aerosol photometers estimate mass concentration based upon an assumed density and particle size distribution (e.g., DustTrak, Model 8520, TSI, Inc., Shoreview, MN; PDM-3 Miniram, Mie, Inc., Bedford, MA). Aerosol photometers are capable of operation in environments ranging from cleanrooms to harsh manufacturing floors and allow for rapid estimation of airborne NM concentrations. However, a limitation of these types of technologies is their difficulty in measuring airborne materials at the nanoscale (most aerosol photometers are limited detection of airborne materials with aerodynamic diameters 40 nm or larger). • Condensation particle counter (CPC) are real-time, single-particle counting instruments that grow particles to optically detectable sizes by condensing liquid onto the aerosol particles (e.g., CPC Model 3007 or P-Trak Model 8525; TSI, Inc.). Application of CPCs for NM counting has seen widespread application in a variety of settings, including stationary, indoor, ambient, workplace, and mobile platforms. Despite this widespread application, CPCs suffer from lack of specificity toward NMs unless peripheral technologies (such as a differential mobility analyzer) are used in conjunction with the CPCs. • Diffusion chargers measure the SA of airborne nanoparticles by combining ions and particles into a single stream and detecting the electric current from charged particles (nanoparticle SA monitor, NSAM model 3550 or AeroTrak 9000; TSI, Inc. or DC2000CE; EcoChem Analytics, League City, TX). These diffusion charging technologies are the only commercially available technologies for on-line NM SA determination currently available and have seen application in areas such as workplaces, residential, and other high population density areas. A major limitation of these technologies is related to charging inefficiencies when exposed to high levels of NMs or NMs sampled are smaller than 10 nm. • Differential mobility analyzers classify particles based upon the ratio of their electrostatic and drag forces that are then detected with an optical particle counter (NanoScan SMPS Nanoparticle Sizer 3910, TSI, Inc.). The maturity of this technology has permitted its application to variety of scenarios. However, similar to CPCs, differential mobility analyzers require preriphel technologies to generate usable data such as airborne NM size, number, estimated SA, or mass concentrations. • Impactors separate aerosol particles based upon the ratio of their inertial and drag forces and can also be used to collect samples on substrates for off-line analysis (Nano-Micro-Orifice Uniform Deposit Impactor [Nano-MOUDI] Model 125A, MSP, Inc., Minneapolis, MN). Due to the relatively simple design and operation of impactors, they have seen usage in multiple measurement scenarios, such as mobile source emission measurement, indoor air quality monitoring, and workplace background and activity based measurements. This simple design underscores their most significant drawback, in that impactor technologies lack real-time data output thereby limiting the usage of the data obtained.
Depending upon the strategy employed and the environmental conditions being monitored, selection of instrumentation is critical. Additional details on instruments, their applications, time resolution, measurement metrics, sampling types, and special considerations are available (see for example, Kuhlbusch et al., 2011 and Ramachandran et al., 2012).
Future Research Needs
Although progress has been made in the ability to measure and characterize airborne nanomaterials, much work remains before this analysis is routine, robust, cost-effective, and efficient. Through efforts with the National Nanotechnology Initiative, several key documents detail the strategy needs and gaps (NNI, 2011). Several key priorities of relevance to airborne nanomaterial measurements are listed below.
• Identifying the hazard: Improving aerosol nanoparticle instrumentation that is practical, robust, and cost-effective and has the ability to readily distinguish between background, incidental, and ENMs.
• Assessing magnitude of exposure: Developing exposure strategies that can determine acute and chronic exposure in addition to personal breathing zone exposure to nanomaterials.
• Assessing dose response relationship: Developing an understanding of which measurement metric is most appropriate when linking nanomaterial exposures to worker health outcomes.
Conclusions
Measuring airborne nanomaterials requires a comprehensive strategy and robust instrumentation. Several strategic methodologies have been proposed, each with their advantages and drawbacks. Additionally, although aerosol instruments have been available for many years to detect and characterize airborne nanomaterials, it has not been until recently that attempts to ruggedize these research instruments have been made. Through improvements in both methodologies and instruments, the ability to conduct exposure assessments for occupational and environmental studies will continue to improve. Differentiating between background, incidental, and ENMs remains a challenge and assessing environments for spatial and temporal variations in airborne nanomaterial concentration and characteristics.
Footnotes
Author Disclosure Statement
No competing financial interests exist.