How can exposure to nanoparticles be measured

A nanoparticle is really just a submicroscopic particle that measures less than nanometers on at least one of its dimensions. It would be possible to place hundreds of thousands of them onto the head of a pin. They are exciting to researchers because many materials act differently at the nanometer scale than they do at larger scales, and nanoparticles can be made to do lots of useful things.

Nanoparticles have been in use since the days of ancient Mesopotamia, when ceramic artists used extremely small bits of metal to decorate vases and other vessels. In fourth-century Rome, glass artisans ground metal into tiny particles to change the color of their wares under different lighting.

These techniques were forgotten for a while but rediscovered in the s by resourceful manufacturers for glassmaking again. Then, in the s, scientist Michael Faraday extensively researched ways to use various kinds of wash mixes to change the performance of gold particles. Modern nanoparticle research advanced quickly in the midth century due to technological innovations in optics. Being able to see the individual particles and study their behavior expanded the possibilities for experimentation.

The largest advances came, however, after experimental nanotechnology took off in the s. Suddenly, the behavior of single particles of gold and many other substances could be closely examined and manipulated. Discoveries about the ways that small amounts of a substance would reflect light, absorb light, or change in behavior were numerous, leading to the incorporation of nanoparticles into many more products.

Debates have since followed about their measurement. When assessing the response of cells or organisms to nanoparticles, some researchers prefer measuring particle number concentrations sometimes called PNCs by scientists. Many find PNCs challenging since extra formulas must be employed when determining the final measurement. Others prefer measuring mass or surface area concentrations. PNCs are often used for characterizing metals in chemistry.

The situation for nanoparticles is inherently more complex, however, than it is for dissolved organic or inorganic substances because unlike dissolved chemicals, nanoparticles can come in a wide variety of sizes and sometimes stick together when added to testing materials. Some will be 9 nanometers, some will be 11, some might be 18, and some might be 3. The problem is that each of those particles may be fulfilling an important role. While a simple estimate of particle number is perfectly fine for some industrial applications, therapeutic applications require much more robust measurement.

Nanoparticles are not a modern invention. Nanoparticles are produced in natural geological and especially biological systems [ 2 ]. Natural nanoparticles include volcanic sands, viruses, and proteins. Wood fires produce huge amounts of undefined carbon nanoparticles which in their manufactured and purified forms count as some of the most advanced and useful man-made nanomaterials.

Many formulations and ingredients in food, cosmetics, and pharmaceuticals, entering or in direct contact with our bodies, should be defined as nanomaterials following the standard definition employed in this article. While viruses and proteins serve as models for the design of biomedical nanoparticles such as drugs and drug delivery vehicles, they of course also highlight one of the fears concerning nanoparticles; advanced nanoparticles can travel through biological systems and have major impact on biological functions and health.

However, the natural production and exposure to nanoparticles mean that evolution to a large extent has prepared us to deal with exposure to nanomaterials [ 2 ]. Thus, we might currently be increasing our exposure to man-made nanomaterials, but our contact with this class of materials is not new. The biggest concern is probably that a fraction, although in most likelihood a minor fraction, of nanomaterials will be produced from materials that have intrinsic high chemical toxicity.

Examples are semiconductor quantum dots currently being produced for TV screens and optical applications. However, even if we assume that nanoparticles are generally more dangerous to our health, should we automatically assume that their use leads to increased adverse exposure? Nanoparticles are examples of colloidal systems. This interfacial or surface energy increases proportionally to the area between the materials.

If you therefore imagine that you have only a cubic centimeter of material, creating nanoparticles of this material will cost one million times more energy than the creation of the surface of the first cube, and this energy is stored at the interface of the particles. Nature strives continuously to lower its energy. These nanoparticles will therefore, after colliding with each other and other surfaces, stick together and recombine to form larger objects.

This ubiquitous process leads to the destruction over time of all nanoparticles. This might feel counterintuitive for us living in a world where we see mountains and other large structures invariably crumble to sand over time, but the balance of physical interactions is not the same for very small objects as for objects that we can see; surface interactions tend to strongly dominate other forces that could keep nanoscale objects apart.

Another inherent feature of nanoparticles is that they spontaneously move faster than their larger cousins. The energy from random thermal movement of molecules in gases and liquids transferred to an object by collisions is much larger in relation to the size inertia of the object for small particles.

This random or Brownian motion lets nanoparticles move large distances and collide with many objects within a very short time span. A typical suspension of nanoparticles is therefore expected to aggregate into larger objects by collision within a short time; but, how short?

If the number concentration of particles stays the same, Brownian motion results in that the half-life time, a typical measure of the time required to lose particles from a colloidal suspension by aggregation, is the same regardless of size.

One should now ponder that, in a biological system, the synthetic nanoparticles are not the only nanoparticles present which can collide and aggregate. A natural, biological environment has a very high concentration of nanoparticles in the form of e. The concentration of protein is so high that the half-life time of nanoparticles in such suspensions is less than milliseconds; only nanoparticles engineered to specifically avoid attractive interactions with biomolecules will not aggregate.

In essence, engineering such nanoparticles is the extremely demanding problem facing every designer of biomedical nanoparticles such as drug delivery vehicles. The risk that nanoparticles made for other materials applications without special design would incidentally avoid the fate of aggregation or dissolution and thereby loss of nanoscale size in a natural environment is extremely low [ 3 ].

Why does the rapid aggregation of nanoparticles matter? Almost all specific nanorisks of materials only apply to particles that have nanoscale size.

These risks relate to their fast motion and potential ability to penetrate biological tissue, their high surface area, and sometimes to the special quantum-related physical properties in terms of interacting with electromagnetic fields that nanoscale materials can have [ 2 ].

When nanoparticles aggregate, their effective size increases while their total area is reduced [ 3 , 4 ]. In close proximity, the special quantum properties couple and the aggregated particles become indistinguishable from their macroscopic counterpart [ 5 ]. Carbon nanomaterials aggregate into bundles that are indistinguishable from common soot or the graphite in your crayon.

Most importantly, as nanoparticles aggregate, deep penetration into biological organisms becomes much less probable. The increased size decreases mobility by Brownian motion; it also facilitates blocking by passive mechanisms such as cilia and narrow vasculature.

Aggregation of particles with proteins opsonins enhances clearance by the reticuloendothelial system. Finally, also the chemical toxicity of nanoparticles will be proportional to how fast a particle is dissolved, which in turn is proportional to its free surface area and therefore is decreased by aggregation. Aggregated nanoparticles will still have a larger total surface area than their solid counterparts due to porosity.

In some cases, this leads to higher catalytic activity or faster dissolution of toxic constituents than those of a solid. Biological processes during degradation of internalized materials can also theoretically deaggregate clusters of nanoparticles by active energy input.

However, on balance, spontaneous and ever-present physical processes rapidly work to reduce the nanospecific risks of nanomaterials in biological systems. It is therefore important to realize that freely dispersed colloidal nanoparticles in air or water are the ones that can pose nanospecific risks.

Nanoparticles fixed in solid nanomaterials such as it is the case in computers and composite materials lead to negligible, if any, exposure, except during production and recycling of the material. At these points, special precautions can be and are taken. To set nanoparticles free from a fixed solid or even from a liquid to a gas environment takes enormous amounts of energy compared to what is available as heat in the natural environment.

The natural forces driving aggregation, sedimentation, and clearance of nanoparticles, however, reduce the energy. Therefore, these processes that are destructive to nanoparticles occur spontaneously at a high rate. The net result is that an exploding use of nanomaterials is not likely to lead to a similar explosion of actual exposure of the public to potentially dangerous nanoparticles.

If we decide that nanoparticles pose additional specific risks and merit specific regulation, we must use methods to detect and quantify their presence in situations considered to lead to potentially harmful exposure. To prove the presence of nanoparticles in a product material or in the environment, we must identify them and measure their size; to estimate nanospecific risks, we also might have to measure other properties such as surface area and shape.

Any meaningful regulation of nanomaterials implicitly assumes that we can perform such measurements to enforce compliance; if not, the law cannot be enforced and possibly not even followed by companies, since they would be severely challenged to verify that they meet the regulations in their own production.

However, possibly, the idea that nanomaterials and their potential risks can easily be identified is deceptive. Nanoparticles in nanomaterials do not exist in vacuum.

In most cases, they will be distributed in a solid matrix [ 5 ]; in other cases, they are dispersed in a solvent, e. Only rarely, as argued above, are we likely to encounter them in a gas phase such as air, and then most likely at the point of manufacture or at the point of destruction of the material for recycling. Thus, what methods do we have to detect and measure nanoparticles as a colloidal system within another material? Detecting the presence of nanoparticles in gases, liquids, and gels is required in e.

So, how can we detect and measure the presence of nanoparticles in such environments? Natural biological environments are full of other small particulate matter, protein, micelles, bubbles, emulsifiers, mycobacteria, viruses, and liposomes.

In nature, we further find soot, debris, and volcanic sand particles that contain nano- and submicron particles. Unfortunately, generally speaking, we lack methods to determine size and composition in a matrix simultaneously [ 4 ].

To address this, we could perceivably first separate nanoparticles from a complex environment and analyze them. Or, can we? Intriguingly, separation methods tend to depend on that we know what we are looking for to devise methods to discard other particles to be able to analyze the ones of interest. Nanoparticles often will not have a clearly distinguishing feature except for their chemical composition in a natural environment that will contain natural nanomaterials.

Sometimes, as for carbon nanoparticles, even this is not true and their only distinguishing features are size and shape. If a nanomaterial is manufactured on purpose, one suggestion that has been circulated is that they are all tagged with a reporter, like supermarket barcodes. The tag can be read out by a detector to identify and even quantify by the number of detected labels how much nanomaterial is present. Such tags could be what scientists have been using in the lab for the same purpose for ages, such as radioisotope, fluorescent, color scattering, or magnetic tags.

For a moment, disregarding that also such reporters are not unique to man-made systems and any natural sample is likely to have strong optical and magnetic interactions that create a disturbing background for read-out, we should consider what introducing such labels would mean and what they can tell us.

Stable tags would in themselves be nanomaterials and often be chemically toxic materials, i. Seipenbusch et al. A good solution, enabling the identification of the emission source during the working time, is real-time monitoring of NOAA concentration in the air focused on particular tasks and events.

In this approach, the background level average concentration recorded before or after the process is the reference point. The first, lowest level of exposure relates to a ratio below 1. The fourth, highest level of exposure corresponds to a ratio higher than 2, which means that the concentration recorded during the specific event is twice as high as the background level. Results of international measurements of nanomaterials at workplaces, based on this approach, were provided by Brouwer et al.

Brouwer et al. The method is also adopted in this work for task-based exposure assessment. A standardized sampling strategy with a task-based approach guarantees that all collected data, documentation and context for the exposure measurement are harmonized and allows for comparisons among different exposure scenarios Brouwer ; Brouwer et al.

Task-based exposure assessments are most significant for activities with a high degree of daily variability, typical for the nanotechnology industry, which utilizes batch processing more often than continuous mass production Seixas et al. Exposure evaluation and risk management for NOAA requires knowledge about the specific material, such as biological and physico-chemical parameters, real-time monitoring and proper sampling for chemical and morphological microscopic characterization of nano-objects, as well as data on contextual information about the premises, workers and background.

This article presents the results of the measurements with contextual information on emission of nanoparticles at four workplaces, where different processes were carried out: synthesis of silver nanoparticles, generation of thin nanocarbon layers, 3D-printing with nanocomposites and the production of special seals from thin glass foils.

Aerosols at the workplaces were studied using online methods real-time particle concentration counters and offline methods air sampling for gravimetric evaluation and electron microscopy analysis. Measuring devices for real-time monitoring of airborne nanoparticles differ in used methods, measuring range max number of particles, diameter of particles , time interval, accuracy etc. For these measurements, three identical miniature diffusion size classifiers DiSCmini, Testo—handheld nanoparticle counter were chosen Fierz et al.

Their main advantages are as follows: low weight g , small size, portability, and battery operation without the need for an additional power supply. The aerosol particles are electrically charged in a nonradioactive unipolar diffusion charger. Time interval is 1 s for a scan, but for better readability the results in this study are presented in a minute scale average values from every 60 s.

Aerosol flow rate of the sampling setup was 0. Morphological analysis of dust samples collected on TEM grids was conducted using a field emission scanning electron microscope Hitachi SU An accelerating voltage of 5—20 kV was applied.

Observations were conducted in SE U mode. Length expressed by maximum linear diameter, nm of the nanoparticles was calculated from at least 50 objects from images magnified at least 50k times. An X-ray microanalyzer EDS, energy dispersion spectroscopy was used to carry out basic chemical analysis and confirm the absence or presence of NOAA from the suspected source. To determine mass concentration of the respirable dust fraction, the sampling filters have been weighed with a micro balance UMX2, Mettler Toledo before and after the sampling, with additional conditioning for at least 20 h in both cases.

Detailed chemical analysis of the collected dust, although it could provide relevant data, was not planned in the research. The analysis was limited to identification of elements by the EDS method to confirm a presence of the nanomaterial in work environment, in accordance with the measurement strategy recommended in the ISO standard ISO b. In same spots, measurements of background NOAA concentration as a reference for further results were executed.

Background level was recorded with the same DiSCmini classifiers at least 1 h before the work process was started. The same time was set on every measuring device. The sampling time was about 20 min for each sample. Air samples for gravimetric analysis were collected during the whole shift.

The respirable fraction the mass fraction of inhaled particles penetrating to the respiratory region was checked as a supplementary measure. During sampling, the researcher recorded information about the premises, environment conditions, ventilation, local safety control and the process itself. The worker activities were described in detail with exact time of their execution. Contextual information was later matched with the concentration profiles received from real-time monitoring devices.

Four workplaces WP situated in Polish companies with small-scale manufacturing participated in this study. Description of each workplace and studied processes are below. The worker performed several activities related to the production of seals: weighing reagents, pouring into the crucible mixing ingredients, operating laser cutting tool, manually cleaning the seals with brush removing scorched pieces , spraying with silicone. It was suspected that mixture of ultrafine particles, especially SiO 2 , could be incidentally emitted during the laser cutting of boron-aluminium silicate glass.

DM-A was placed close to the glass foil synthesis sit place closest to the worker ; DM-B was placed close to the protective chamber of the laser cutting machine. DM-C was used as a control and a mobile meter for checking possible additional sources of emission. Activities were recorded for 3. The worker wore a lab coat and disposable gloves. No other personal protective equipment PPE was worn.

The laboratory was located in an old building, in a room with poor general ventilation. Building was located in industrial area about m to the nearest industrial installation. The cubature of the studied room was 51 m 3.

One worker was involved in a process. Studies were conducted in the winter, at the end of An outline drawing of the workplace, without maintaining the exact proportions of the room, has been presented in Fig. The worker performed only the activities related to the process: turning on, cleaning, changing the electrode, operating the software, monitoring and shutting down the process. The whole process was carried out in a closed chamber.

About 5 mg of electrode was burned in the process. Average particle size declared by a worker was about 50— nm. The background level was recorded 1 h before the start of the work. The activities were recorded for about 5 h. The laboratory was located in a new facility with efficient hybrid ventilation. Facility was located close to the main road with high traffic about m distance.

The cubature of the studied room was m 3. Two workers were involved in a process. Studies were conducted in July The worker performed several activities related to the manufacturing: turning on the 3D-printer, backfilling nanocomposite granulate, operating a software, monitoring the process, checking other devices, shutting down, cleaning. It has been suspected that thermal processing of the nanocomposite during the 3D-printing process might cause incidental emission of NOAA.

The whole process was carried out in a half-closed protective chamber. Nine grams of nanopowder was used for the preparation of printer filament average particle size declared by the manufacturer was 32 nm, density 2.

DM-A was placed close to the worker, outside the protective chamber of the 3D-printer, and DM-B was placed inside the chamber. The background level was recorded 1 h before the start of work. Activities were recorded for about 4.

The worker wore protective goggles, a lab coat and disposable gloves. The laboratory was in a new, clean facility with efficient mechanical ventilation. Facility was located in secluded area. Laboratory room did not have access to the windows and was surrounded by other rooms and a corridor. The cubature of the room was 65 m 3. One worker was involved in a main process; two other workers were conducting other tasks in same room but only occasionally. Studies were conducted in August The worker performed several activities related to the synthesis: preparation of reagents, weighing, preparing the setup inside the fume hood, monitoring the process, ending the synthesis, pouring the suspension into a vessel, cleaning.

It has been suspected that the mixing of reagents could cause the incidental emission of silver nanoparticles. The whole mixing process was carried out under the working fume hood. Two hundred milligrams of nanosilver colloid was prepared in a solution average particle size declared by a worker was about 50 nm. DM-A was placed at the laboratory table where reagents were prepared, close to the worker, and DM-B was placed inside the fume hood where synthesis was conducted. Activities were recorded for about 2 h.

The worker wore protective goggles, disposable gloves and a lab coat. The laboratory belongs to a private company and was located in a new, clean room and was a part of a larger facility. Facility was located close to the inner alley with a little traffic about 60 m and close to the main, high-traffic railway route about m. In the close vicinity there were buildings of small industrial companies about 20 and 50 m.

There was a large construction work nearby about m. General ventilation in laboratory was functioning during the measurements. The cubature of the room was 48 m 3 , and the studies were conducted in October For the sake of simplicity, the graphs from DM-C are not shown. Results of the real-time measurements at WP1 of NOAA by time and number concentration during the process—laser cutting of boron-aluminium silicate glass; DM-A blue line was placed close to the glass foils synthesis site, where the worker spent most of the time; DM-B orange line was placed near the protective chamber of the laser cutting machine.

Results of the real-time measurements at WP2 of NOAA by time and number concentration during the process—generation of thin nanocarbon layers; DM-A blue line was recording outside the chamber, close to the worker; DM-B orange line was placed inside the chamber.

Results of the real-time measurements at WP2 of NOAA by time and number concentration during the process—3D-printing with a composite containing nanohydroxyapatite; DM-A blue line was placed close to the worker, outside the protective chamber of the 3D-printer; DM-B orange line was placed inside the chamber.

Results of the real-time measurements at WP2 of NOAA by time and number concentration during the process—chemical synthesis of silver nanoparticles; DM-A blue line was placed at the laboratory table where reagents were prepared, close to the worker; DM-B orange line was placed inside the fume hood where synthesis was conducted. Peaks are described under the tables.

The magnitude of the standard deviation from the average value of the background nanoparticle concentration indicates small background fluctuation. The magnitude of the standard deviation from the average value of the background nanoparticle concentration indicates a medium size of the background fluctuation. The magnitude of the standard deviation from the average value of the background nanoparticle concentration indicates a small size of the background fluctuation.

Numerical results of image analysis are presented in Table 5. If such an object fits into the size range of this fraction, there is a greater chance of it penetrating deep into the lower respiratory tract. Averaged air parameters, respirable fraction and background levels recorded at four locations are presented in Table 6. The values for pressure, temperature, humidity and speed of air were similar at each site and had no significant effect on concentrations, but they are important in showing the conditions prevailing during measurements and rejecting their effect on measurements.

Measurements were conducted in 4 different workplaces in Polish companies where various processes were conducted. The concentration profiles of NOAA varied depending on the locations and activities carried out. There were no major fluctuations in pressure, temperature and relative humidity in the workplaces Table 6.

DM-As were always placed closer to the worker, outside protective chambers and coveralls, and DM-Bs were placed as close to the process as possible. Very large differences are visible in the background levels between locations. At WP1 and WP2, the background levels were average for indoor areas, while at WP3 the background was extremely low, which was probably the result of high cleanliness and very efficient ventilation of a modern laboratory area.

On the other hand, the background level at location WP4 was high, which could have been caused by large, urban outdoor air pollution. A nanostructured object getting into the body poses a greater health risk than an analogous microstructured object, mostly due to the more developed surface, higher reactivity and the chance to release individual nanoparticles. There is no official OEL for nano silicon dioxide. There is also no official OEL for carbon black and nanohydroxyapatite.

There was no evidence for acute toxicity, skin corrosion, eye damage, germ cell mutagenicity and reproductive toxicity, and there was no data for carcinogenicity and specific target organ toxicity after single exposure incident. According to the WHO report, there are six mass concentration proposals in literature for nanosilver varying from 0.

Despite the confirmed presence of nanostructured objects that fit into the size range of the respirable fraction, it is worth to note the small mass concentration of this fraction collected at all studied workplaces Table 6. Due to different environmental conditions, types of processes and even geographic locations, the results from the task-based assessment at each workstation should be interpreted separately. Slow drop of the number concentration of particles was a result of general ventilation with low efficiency.

The low peaks a, b, c occurred during the initial processes: weighing, pouring the dusty substance into the crucible, and inserting the material into the mixer, as well as during two separate processes of automatic cutting with a laser cutter. When the first peak a appeared, the employee opened a long drawer with a brush and parts of old foils. The second peak b also occurred during minor operations at the drawer.

High peaks e, f, h occurred during manual work drawer was opened once again on the foils removed from the cutter.