Robert Thomas has more than 30 years of experience in trace element analysis. He is the principal of his own freelance writing and scientific consulting company, Scientific Solutions, based in Gaithersburg, MD.

Robert Thomas

This month's column describes the work of Professor Luis Fernandez and his team in the Department of Biology at Wake Forest University in Winston Salem, North Carolina, who are leading a project to study the effects of illegal artisanal gold mining using mercury amalgamation extraction on the human and environmental ecosystem of Peru's Madre de Dios region of the Amazon. By setting up a remote, field-based laboratory, they are monitoring mercury contamination in a wide variety of samples, including soil, fish, air, and human hair using the technique of direct mercury analysis (DMA).

	This time last year, CNN showed a fascinating documentary about illegal artisanal gold mining in the Peruvian Amazon, where as many as 40,000 illegal miners (mostly poor, indigenous Indians from Peru's Andean highlands) had invaded some of the most pristine and biologically rich sections of ancient rain forest in the Amazon basin. In just a few years, the extraction and refining of the gold using mercury amalgamation has created more than 250,000 acres of desert in the middle of the Amazonian forest in Peru's southeastern Madre de Dios region (Figure 1). There was a truly memorable scene in the documentary when Bill Weir, the CNN reporter, came out of the lush rain forest on the back of a motorcycle to be confronted by a barren wasteland of sand as far as the eye could see, where all the trees had completely vanished. It seemed surreal that this kind of deforestation could be happening in the largest rain forest in the world, home to the highest biodiversity on our planet (1).

	Peru is the world's fifth largest gold producer, and the largest in Latin America, extracting about $10 billion worth a year, with approximately 20% mined from the Amazon region. Most of the gold comes from the Andean highland, by multinational companies from the United States, Canada, Brazil and China. However, artisanal and small-scale gold mining (ASGM) in the rain forest is different. Gold has been eroded from the mountains over millions of years, coming down alluvial river channels with other sediments and soils. Pulling the gold out of the ground is like mechanized soil-filtering, using dredgers and suction pumps to suck up the sediments and send them through crude wooden sluice boxes to separate the gold from the rocks. The heaviest particles, including the gold, settle on the bottom and are collected on strips of carpet; miners have to filter about one ton of dirt and mud to get an ounce of gold, so this is all about volume. The more earth you can suck up and sift out, the more money you can make. Since 2008, when the financial crisis led nervous investors to invest in gold, the price has stayed relatively high, peaking at about $1900 an ounce in 2011. Today, gold sells for about $1300 an ounce, so miners only have to extract a few grams of gold to make a few hundred dollars, which can be up to 100x more money than they can make doing anything else.


	Figure 2: Deforestation caused by illegal artisanal gold mining in the Peruvian Amazon (Photo credit: New York Times).

	Dragging their machinery up waterways and along muddy trails, miners cut down trees to create space for their dredgers, sluices, and vacuum pumps that can open a pit as deep and wide as a five-story building in a matter of weeks. While the damage from illegal mining may not be deforesting the Amazon as fast as cattle ranching and agriculture, the destruction is profound, since destroying the soil takes away the forest's ability to regenerate itself, which is magnified significantly by the miners' use of mercury to extract the gold. Figure 2 shows an aerial view of one of the deforested areas as a result of the illegal mining. Figure 3 shows the machinery and equipment the miners use.


	Figure 3: Artisanal miners separating gold from river sediments in Madre de Dios, Peru (Photo Credit: Jason Houston).

	The miners use water hoses attached to giant diesel-powered pumps to blast the topsoil and riverbanks. They then sift the soil to search for gold. After separating the finer sediments from the heavier gravel, they mix mercury into the slurry, which is purchased on the black market. The mercury forms an amalgam with the gold, which acts like a magnet, grabbing any remaining flecks of the precious metal. The result of the amalgamation process is a ball of 50% gold and 50% mercury, like the one shown in Figure 4, which is then heated with crude blow torches to separate the gold. This vaporizes the elemental mercury, releasing toxic mercury fumes into the atmosphere, which is absorbed into the rain forest ecosystem, and inhaled by the working miners (2).


	Figure 4: The mercury forms an amalgam ball with the gold (3) (Photo credit: Rodrigo Abd, Associated Press).

	The impact of gold mining on the environment of the Peruvian Amazon is devastating. Besides the deforestation and the blasting away and erosion of the soils, the mercury enters the ecosystem, including water systems, soil, and vegetation, as well as the air. This process has gone on uncontrolled more than 35 years and, as a result, the mercury is having significant repercussions on the health of the local people, contaminating their food supply, including fish, wildlife, fruits, nuts, and vegetables, as well as polluting the air they breathe.

	It is well recognized, based on studies done on freshwater and ocean fish in the United States, that mercury released into the atmosphere and water systems by power plants and industrial bodies accumulates in the bottom mud and silt, where subsequently naturally occurring sulfur-reducing bacteria convert the inorganic form of mercury to the more toxic organic compound methylmercury [CH

. Methylmercury then gets bioaccumulated and biomagnified up the food chain to the large predator fish at the top, such as tuna, swordfish, and shark in the ocean, and perch, pike, bass, and catfish in fresh water ecosystems, which eventually gets consumed by the human population.

	In the Peruvian Amazon, it is estimated that gold extraction releases an estimated 185 tons of mercury directly into waterways each year. Methylmercury affects virtually every system in the human body, and often occurs with no distinctive symptoms. It impacts the central nervous system, kidneys, and reproductive organs, as well as causing chromosomal damage and severe skin reactions; at extremely high levels, methylmercury can cause coma, convulsions, and even death. The long-term effects of even low levels of methylmercury on the developing brain of young children are significant. It will cross over the blood–brain barrier as well as the placental barrier, impairing the growth of brain neurons in the fetus, resulting in cognitive damage, lower intelligence, and reduced brain development. The Minamata disaster in Japan in the late 1950s, where the Chisso Chemical Corporation dumped hundreds of tons of mercury into the Bay of Minamata for over 30 years, is a devastating testament to what happens when mercury pollution is allowed to occur (4).

	It is widely known that the presence of mercury in human hair generally indicates that a person has been exposed to methylmercury through a dietary source. Not surprisingly, high levels of mercury in hair samples were found in large numbers of Madre de Dios residents, many of which were above the reference exposure level set by the World Health Organization (WHO) (5). As a result, there is clearly a strong correlation between human mercury exposure and fish consumption (6). In fact, since 2009, studies have found high mercury levels in many species of fish, particularly in large catfish, which are a staple diet of the local people. It has been estimated that roughly two thirds of the approximately 120,000 residents of the region have been affected, many of them young children, who are the most vulnerable to mercury toxicity (7).

	To get a better understanding of how mercury is having such severe impact on the health of the local people, let's take a more detailed look at the work of Professor Luis E. Fernandez in the Department of Biology at Wake Forest University in Winston Salem, North Carolina, who is leading a project to study the metal's effects on human and environmental ecosystems in the Amazon. He is also the Director of the Center for Amazonian Scientific Innovation (CINCIA) at Wake Forest, a leading research institute for environmental research, including biological conservation and environmental restoration, in the Peruvian Amazon region, which was established in 2016 through a partnership with the US Agency for International Development and the World Wildlife Fund. In this role, he leads a team of researchers who are collaborating with colleagues at the Peruvian Amazon Research Institute (Instituto de Investigacion de la Amazonia Peruana, or IIAP) and the National Amazonian University of Madre de Dios (8).

	To carry out the assessment of the impact of mercury contamination on the region, Fernandez and his team, including Dr. Claudia Vega, who is coordinating the analytical work, established the first analytical chemistry laboratory dedicated to the study of environmental mercury in Peru. CINCIA's Mercury and Environmental Chemistry Laboratory (Laboratorio de Mercurio y Quimica Ambiental, or LAMQA) is based in the Amazonian town of Puerto Maldonado, in the gold mining region of Madre de Dios. The laboratory's main focus is to carry out mercury measurements directly on a variety of samples including fish, aquatic sediments, soil, air, and human hair, using a dual cell, direct mercury analyzer (DMA-80, Milestone Inc, Shelton, CT) to understand how mercury enters and moves through the region's food webs, and how it impacts wildlife and people. They have chosen this technique mainly because of the ruggedness of the instrument for a remote, field-based application, and the fact that very little sample preparation is required (9). Figure 5 shows CINCIA team members working in the LAMQA lab.


	Figure 5: Dr. Vega (top right) and her team of researchers working in the Mercury and Environmental Chemistry Laboratory (LAMQA), CINCIA's field-based laboratory in Puerto Maldonado, Peru.

	It's worth discussing the principles of direct mercury analysis. The technique is used for the determination of total mercury in solid, liquid, and gas samples, using the principle of thermal decomposition, amalgamation, and atomic absorption. A decomposition furnace is used to release mercury vapor, instead of the chemical reduction step used in traditional liquid-based analyzers. Both solid and liquid matrices can be loaded onto the instrument's autosampler, and analyzed without acid digestion or sample preparation prior to analysis. Because this approach does not require the conversion of mercury to mercuric ions, lengthy sample pretreatment steps are unnecessary. As a result, there is no need for reagents such as highly corrosive acids, strong oxidizing agents, or reducing chemicals, which means no hazardous waste to be disposed of. Direct mercury analysis is a well-established analytical technique used by the environmental, biological, clinical, food, industrial, and academic communities, which has been approved by testing/standards organizations such as the U.S. Environmental Protection Agency (EPA) (10) and the American Society for Testing and Materials (ASTM) (11).

	Direct mercury analysis can be broken down into four distinct sequences:

	Controlled heating stages are implemented to first dry and then thermally decompose a sample introduced into a quartz tube. A continuous flow of air or oxygen carries the decomposition products through a hot catalyst bed, where halogens, nitrogen, and sulfur oxides are trapped. All mercury species are reduced to elemental mercury (Hg

), and are then carried along with reaction gases to a gold amalgamator, where the mercury is selectively trapped. All non-mercury vapors and decomposition products are flushed from the system by the continuous flow gas. The amalgamator is subsequently heated, and releases all trapped mercury to the single or double beam (depending on model), fixed wavelength atomic absorption spectrophotometer. Absorbance is measured at 253.7 nm as a function of mercury content. A schematic of the DMA-80 is shown in Figure 5.

	Let's now take a more detailed look at the methodology being carried out in the field by Fernandez and his team.


	Figure 6: A schematic of the DMA-80 direct mercury analyzer.

	A small amount of sample is weighed accurately into a sample boat, and placed on the autosampler carousel. Between 0.02 and 0.05 g of sample is typically taken, depending on the mercury content. The sample is then taken through the sampling and measurement procedure described earlier. Table I shows typical operating conditions for their fish and hair sample matrices, whereas soil and air samples use slightly modified conditions.

	The measurement process involves the thermal generation of mercury vapor from the sample, which means the instrument can either be calibrated with aqueous standards, or directly with solid certified reference materials (CRMs). However, the aqueous calibration methodology has been primarily adopted in their field laboratory, where standards are typically prepared using a National Institute of Standards and Technology (NIST, Gaithersburg, Maryland) traceable stock solution of 1000 ppm mercury (Hg) preserved in 5% nitric acid (HNO

). Appropriate calibration standards are then made up in 5% HNO

, and stored in a suitable vessel. By injecting increasing sample volumes of standard into the quartz sample boats, appropriate calibration graphs are created covering the range of expected mercury levels in the samples. Low and high levels of mercury in their samples are typically addressed by covering two ranges: 0–20 ng and 50-1000 ng. A portion of the 0–20 ng Hg calibration graph is shown in Figure 7.


	Figure 7: Direct mercury analyzer (DMA) calibration graph of 0 to 20 ng of mercury (Hg).

	It is important to point out that, when quantifying lower levels of mercury, a few ppm of gold (as Cl

) is often used to stabilize the Hg, to stop it from being reduced to elemental mercury, which can be absorbed into the walls of the containers or lost when the cap is removed. The likelihood of reduction increases if the solutions are left for extended periods of time before they are analyzed (12). When gold becomes cost-prohibitive or is impractical, as it is in the Peruvian studies, sulfur ligands such as L-cysteine made up in hydrochloric acid are often used instead (13).

	To ensure the integrity of the data generated, the team analyzes quality control (QC) check standards (10 and 50 ng Hg) and CRMs at regular intervals during every sample run. Table II shows some typical data for two fish CRMs, DORM-4 (National Research Council of Canada, Ottawa, ON) and IAEA-436 (International Atomic Energy Authority, Vienna, Austria) generated on the DMA-80. It should be emphasized that these reference materials were analyzed together with the QC check standards every ten samples, so they represent analysis of the two CRMs approximately every hour. It can be seen that the measured results are in very good agreement with the certificate values for the two CRMs that were analyzed by a combination of isotope dilution (ID), inductively coupled plasma mass spectrometry (ICP-MS), and cold vapor atomic absorption (CVAA).

	Let's now take a closer look at some of the real-world data being generated by Fernandez's team in their remote, field-based laboratory in Peru. It's extremely challenging to carry out field studies in a remote part of the Amazon rain forest. Equipment, materials, and utilities you take for granted in a research environment in the United States, such as electricity, air conditioning, high purity chemicals, gases, deionized water, calibration standards, CRMs, and volumetric glassware are not easy to come by in a remote, field-based environment. For that reason, instrumentation that is rugged, robust, and easy to use is of critical importance. Even making up calibration standards might not be straightforward. Therefore, the ability to carry out direct mercury analysis on solid and liquid samples is a very attractive option.

	Another component we take for granted in the United States is being able to work in a contamination-free analytical environment, particularly when you are trying to quantitate at low ppb levels; that's not so easy to achieve in a remote laboratory set up in the Amazon rain forest. However, cleanliness is of prime consideration for the team's work, to ensure the data are of the highest integrity. For that reason, they have installed the DMA-80 in a cleanroom, which is separate from the rest of the lab, where sample preparation and other sampling procedures take place.

	The various samples are collected and first freeze dried, which is a low temperature dehydration process involving freezing the product, lowering its pressure, then removing the ice by sublimation. This is in contrast to conventional dehydration that evaporates the water using heat. Freeze drying is a well-established technique that reduces contamination, and maintains the integrity of the sample if it has to be stored for long periods of time. After being freeze-dried, the samples are kept in a freezer until they are required for analysis on the DMA. No other preparation is required, other than weighing the sample into the sampling boat and inserting them into the automated carousel for analysis, as shown in Figure 8. For the majority of the sample matrices, they calibrate with aqueous standards using double distilled water, adding L-cysteine to stabilize the mercury.


	Figure 8: Samples lined up to be analyzed using DMA.

	One of the main objectives of Fernandez and Vega's research focuses on evaluating how mercury released by artisanal gold mining affects natural and human ecosystems of the Peruvian Amazon. Through measurements of mercury concentrations in air, water, and land, and their interaction with humans, animals, and plants, they aim to evaluate the ecological impact of the gold mining. Of particular focus is assessing the potential health impact on indigenous Amazonian communities, through studies of mercury in food sources, including fish from the lakes, soils used to grow fruits, nuts, and tubers, and the air they breathe. Mercury in hair is the biomarker CINCIA is using to assess exposure levels in these vulnerable communities (14), an approach that is well documented for carrying out human ecology studies (15). The following data represent a brief snapshot of their field studies.

	A recent CINCIA study showed that uncontrolled mining has converted about 250,000 acres of rain forest to mined wastelands (16). However, very little is known about how discarded mercury from all this mining (an estimated 185 tons/year) is distributed over this landscape. To better understand this dynamic, Fernandez and Vega send teams of CINCIA researchers into the mining zone to sample soils in different areas in the mining pits. Areas left over from artisanal gold mining typically comprised three distinct categories. There are barren areas with fine tailings (such as sand and silt); barren areas of coarse tailings (gravel and cobbles); and areas of some vegetation regrowth (such as tough grasses and shrubs), which all surround deep mining pits that become filled with rain or flood water during the region's rainy season. Figure 9 shows mercury levels in soil from these three different categories, and compares them to soils from the surrounding forest as a control (17). Surprisingly, they found that, although there is a large amount of mercury released to the environment, mercury levels in the soils in abandoned mining areas are similar, or in many cases lower, than in the surrounding forest, indicating significant mobility in remnant mercury. Based on these findings, they have begun to examine mercury levels in the mining pits, which are the areas of lowest elevation in the mining landscape, and a possible sink for the mercury.


	Figure 9: Mercury levels (mg/kg) of three types of soils in mined areas and in control unmined forest sites in Madre de Dios (17).

	When Fernandez and Vega began to sample sediments at the bottom of rain-filled mining pits, they found very low levels of mercury with very little difference compared with sediments from ponds outside the mining zone. However, when they started to look at mercury levels in fish, they found a difference. Figure 10 is a bar graph that compares mercury levels in mg/kg (ppm) in fish collected from two types of water bodies in Madre de Dios, by trophic level: herbivore, omnivore, and carnivore (18). The blue bars represent mercury levels of fish in rainwater-filled mining pits contaminated with mercury, and the tan bars show mercury levels in uncontaminated lakes from a pristine area in Manu National Park, about 60 km upstream from the mining zone. They made two major observations from these data. First, the mercury levels of fish from mining-impacted water bodies are two times higher than those of fish from pristine areas. Second, these data indicate that mercury is being biomagnified, because mercury levels are significantly higher in the carnivore fish that are higher up the food chain. The World Health Organization (WHO) reference level for mercury in fish (0.5 mg/kg) is represented by the red dashed line. These results provide important information, not only about what species of fish are higher in mercury, but also what types of fish in certain ponds and lakes should be avoided and which are relatively safe to eat. This last point is of critical importance in an area where wild-caught fish is by far the major source of protein for native communities and rural populations, who don't have many other alternatives.


	Figure 10: Mercury levels in fish across three trophic (food chain) levels in mining and control sites in the Peruvian Amazon (18).

	To monitor mercury in air, Fernandez and Vega use a newly developed passive sampling method for mercury vapor that was developed by researchers at the University of Toronto (19), which relies on the natural diffusion of the airborne mercury onto an adsorbent of activated charcoal impregnated with sulfur compounds. Unlike active sampling with a pump, passive samplers are simple to use, have no moving parts, and require no electricity. It's worth pointing out that prior to analyzing the passive air samples for mercury, sodium carbonate, and aluminum hydroxide are added to the samples to minimize degradation of the instrument's catalyst tube from oxidation. In addition, the calibration curve for the passive air samples is carried out by making activated charcoal standards, the same material that is used to build the passive air samplers. Lightweight and small, these samplers are deployable in most areas, needing only a vertical support and zip ties to fix them in place. Three passive mercury samples wrapped around a tree are shown in Figure 11. This work is in its very early stages. However, preliminary results are very encouraging, and clearly show that higher airborne mercury levels are found closest to the mining areas.


	Figure 11: CINCIA's passive mercury samplers can be attached to any vertical support including street lamps, power poles, or trees (Photo credit: CINCIA).

	To take hair samples, CINCIA researchers use well established methods to ensure the analytical data are meaningful (20). Hair grows at an average rate of one cm per month, so analysis of a 4-cm segment is intended to estimate the total mercury exposure for the 4-month period preceding the analysis. Approximately 200 strands of hair, closest to the scalp, are cut using stainless steel scissors from the occipital region (back of the head) of each participant. The hair is then finely dissected, and placed in paper envelopes for storage. Approximately 20–50 mg of hair sample is then weighed accurately, and placed in the DMA-80 for analysis.

	Studies by other research groups have indicated that between 40 to 77% of more than 4000 people tested in Madre de Dios have exceeded the maximum hair mercury level of 2.2 µg/g (21,22), as defined by the Provisional Tolerable Weekly Intake (PTWI) of the World Health Organization (WHO) Expert Committee on Food Additives and Contaminants (23). However, a recent study indicates that native populations may be disproportionately affected by the mercury contamination. This study showed that mean mercury levels of native populations are three times higher than those of non-native ones, with some villages among the highest mean levels of mercury measured in the western Amazon region (24). Focusing on native populations, Fernandez and Vega are in the early stages of mapping mercury levels in Amazonian native communities, and then correlating hair mercury concentrations with observations of neuro-cognitive damage, which are the hallmarks of chronic exposure to elevated levels of methyl mercury. They are also examining the villagers' diet and environment for anything that could provide any protective factor to the high levels of mercury they get through their consumption of fish. Their research represents the first of its kind in native communities, in the Peruvian Amazon, who are being studied only a few decades after their first contact with mercury.

	To the poor migrants traveling to the southeastern Peruvian Amazon rain forest looking for a better life, artisanal gold mining represents a way out of poverty. The government is trying to in vain to stop these illegal mines by destroying the mining equipment. Unfortunately, when one is discovered and destroyed, the miners just move to another location and start again.

	The waste ores from all these abandoned mining sites have contaminated vast areas in Madre de Dios and similar regions across the Amazon, leading to soil deterioration, water quality losses, and a decrease in vegetation cover. As a result, Fernandez and his colleagues have started to test several environmental remediation treatments aimed at reducing the toxicity of mercury and other heavy metals. Recent CINCIA studies have shown that biochar, a unique type of charcoal production made from waste Brazil nut shells and cacao husks, which is based on native Amazonian practices nearly a thousand years old, may be a potential remediation tool for contaminated soils by increasing nutrients and water retention capacity, therefore improving acidity and stimulating the soil's microbial functions.

	Additionally, the use of modern technology is also playing a significant role in the success of this project, which is being used to analyze deforestation and natural forest regeneration through satellite imagery and unmanned aerial vehicle (UAV) sensors. Fernandez and his associates have developed a fleet of these drones to characterize areas degraded by gold mining using newly developed machine learning algorithms to map the growing mining areas and the spatial distribution of mercury across the region's terrestrial and aquatic ecosystems.

	Given that restoration and reforestation are likely to be part of the solution for these physically and chemically degraded landscapes, Fernandez's research team has established the largest restoration field study for areas impacted by artisanal gold mining in South America, where over 100 acres of experimental plots are being used to test the suitability of over 60 different native tree species. Computer-controlled nurseries are being set up with various native species for the ecological restoration and commercial reforestation efforts. In addition, several silvicultural treatments (the practice of controlling growth, composition, health, and quality of forests) are being evaluated for their ability to improve soil fertility and develop forest plantations.

	There is no question that on-site mercury analysis is playing a significant role in ensuring that this reforestation and restoration project is being carried out in a systematic and logical manner. In particular, the technique of direct mercury analysis is proving to be of critical importance by making it possible to take the laboratory into the field to carry out the analysis in a timely manner, particularly in an extremely high workload environment. In its third year of operation, it has proved invaluable as it keeps producing high quality data, day in and day out, with the minimum of routine maintenance-a true testament to its real world applicability and ruggedness.

	The author would like to acknowledge the invaluable contribution of Professor Luis Fernandez and Dr. Claudia Vega from the Center for Amazonian Scientific Innovation (CINCIA) at Wake Forest University, for their help in researching and writing this month's "Atomic Perspectives" column.

	(1) The Modern Gold Rush That's Destroying the Amazon, The Wonder List with Bill Weir, CNN Documentary; November 17, 2017: 

https://www.cnn.com/2017/11/10/world/wonder-list-bill-weir-peru-amazon-illegal-gold-mining/index.html

162 (2016).DOI: 10.1038/nature.2016.19999

	(3) Going for the Gold Sends Mercury Down the River, Jason Beaubien, NPR News, January 21, 2015.

 1446–1447 (2013). DOI: 10.1126/science.341.6153.1446

	(5) M.C. Sheehan, T.A. Burke, A.Navas-Acien, P.N. Breysse, J. McGready, and M.A. Fox, 

254–269F (2014). DOI: 10.2471/BLT.12.116152

	(6) A. L. Langeland, R. D. Hardin, and R. L. Neitzel, 

(3), 302 (2017). DOI: 10.3390/ijerph14030302

	(7) Mercury in Madre de Dios: Mercury Concentrations in Fish and Humans in Puerto Maldonado, L. Fernandez, Carnegie Amazon Mercury Project Research Brief No. 1, And Stanford, CA: 2013.

	(8) The Center for Amazonian Science and Innovation (CINCIA) website, Wake Forest University, 

Articles

Illegal artisanal gold mining using mercury amalgamation is poisoning people and the ecosystem in the Amazon rain forest. By taking the technique of direct mercury analysis to a remote, field-based laboratory, the team of Professor Luis Fernandez is measuring the extent of the contamination in a wide variety of samples, including soil, fish, air and human hair.

The Impact of Illegal Artisanal Gold Mining on the Peruvian Amazon: Benefits of Taking a Direct Mercury Analyzer into the Rain Forest to Monitor Mercury Contamination

The development of analytical instrumentation over the past 50 years has allowed us not only to detect trace metals at the parts per quadrillion (ppq) levels, but also to know the oxidation state, biomolecular form, elemental species, and isotopic constituents. Here, we look at how the development of atomic spectroscopy techniques has enabled a much better understanding of the links between trace metal toxicity and human disease, and, in particular, the role of lead in the health of young children.

	Understanding the effects of trace metals on human health is as complex as it is fascinating. Too low or too high a concentration of essential trace elements in our diet can affect our quality of life. On the other hand, metallic contamination of the air, soil, and water can have a dramatic impact on our well-being. There are many examples that highlight both the negative and positive effects of trace metals on our lives. For instance, the effect of lead toxicity, particularly on young children, is well documented, but is it possible to pinpoint the source of the lead poisoning? The movie "Erin Brockovich" alarmed moviegoers about the dangers of hexavalent chromium (Cr VI) in drinking water, but how many in the audience realized that trivalent chromium (CRIII) metal is necessary for the metabolism of carbohydrates and fats? Dr. Oz recently alarmed his viewers about high levels of arsenic in apple juice, but what he failed to say was that it was not the highly toxic inorganic form of arsenic that had been found, but organic arsenic that had been metabolized by the apple tree to a less toxic form. Selenium, which is found in many vegetables including garlic and onions, has important antioxidant properties, but do we know why some selenium compounds are essential, while others are toxic? Clearly these are all complex questions that have to be answered to fully understand the role of trace elements in the mechanisms of human diseases. Atomic spectroscopy has an important role to play in answering these questions.

	The development of analytical instrumentation over the past 50 years has allowed us not only to detect trace metals at the parts per quadrillion (ppq) levels, but also to know their oxidation state, biomolecular form, elemental species, and isotopic constituents. We take for granted all the powerful and automated analytical tools we have at our disposal to carry out trace elemental studies on clinical, toxicological, and environmental samples. However, it wasn't always that way. As recently as the 1960s, the majority of trace elemental determinations were predominantly carried out by traditional wet chemical methods like volumetric-, gravimetric-, or colorimetric-based assays. In fact, the pharmaceutical industry has been using a sulfide precipitation colorimetric test for the measurement of lead and other heavy metals for more than 100 years; that method was only replaced in the 

) in January 2018 by a plasma spectrochemical test (1).

	It wasn't until the development of atomic spectroscopic techniques in the early to mid-1960s that the clinical analytical community realized they had a highly sensitive and diverse trace element technique that could be automated. Every time a major development was made in atomic spectroscopy, beginning with flame atomic emission (FAE) and flame atomic absorption (FAA) in the early 1960s, electrothermal atomization (ETA) or graphite furnace atomic absorption (GFAA) in the early 1970s, inductively coupled plasma–optical emission spectrometry (ICP-OES) in the late 1970s, and inductively coupled plasma–mass spectrometry (ICP-MS) in the early 1980s, trace element detection capability, sample throughput, and automation dramatically improved. There is no question that developments and breakthroughs in atomic spectroscopy have directly impacted our understanding of the way trace metals interact with the human body. Let us now take a look at a specific examples where atomic spectroscopy techniques have allowed us to delve deeper into understanding the impact of trace metal toxicity on our lives, focusing specifically on lead (Pb).

	Lead has no known biological or physiological purpose in the human body, but is readily absorbed into the system by ingestion, inhalation, and, to a lesser extent, by skin absorption (2). Inorganic lead in submicrometer-sized particles in particular can be almost completely absorbed through the respiratory tract, and larger particles may be swallowed. The extent and rate of absorption of lead through the gastrointestinal tract depend on characteristics of the individual and on the nature of the medium ingested. It has been shown that children can absorb 40–50% of an oral dose of water-soluble lead compared to only 3–10% for adults (3). Young children and toddlers are particularly susceptible because of their playing and eating habits, and because they typically have more hand-to-mouth activity than adults (4). Lead is absorbed more easily if there is a calcium or iron deficiency, or if the child has a high fat, inadequate mineral, or low protein diet. When absorbed, lead is distributed in the body in three main areas: bones, blood, and soft tissue. About 90% is distributed in the bones, while the majority of the rest gets absorbed into the bloodstream, where it gets taken up by porphyrin molecules (complex nitrogen-containing organic compounds providing the foundation structure for hemoglobin) in the red blood cells (5). It is, therefore, clear that the repercussions and health risks are potentially enormous if children are exposed to abnormally high levels of lead.

	The toxic effects of lead have recently been exemplified by the drinking water crisis in Flint, Michigan, where public health officials and water authority personnel failed to take remedial action when they replaced Lake Michigan with the Flint River as the source of the city's drinking water, a change that resulted in corrosion of lead pipes and high levels of lead in the drinking water supply. This particular problem is still being investigated, but the Centers for Disease Control and Prevention (CDC), recently reported that at least four million households have children living in them who are being exposed to high levels of lead from a combination of old lead paint and lead water pipes. As a result, there are approximately half a million U.S. children 1–5 years of age with blood lead levels (BLL) in excess of 5 micrograms per deciliter (µg/dL), the level at which CDC recommends remedial actions be taken (6).

	Lead poisoning affects virtually every system in the body, and often occurs with no distinctive symptoms. It can damage the central nervous system, kidneys, and reproductive system and, at higher levels, can cause coma, convulsions, and even death. Even low levels of lead are harmful and are associated with lower intelligence, reduced brain development, decreased growth and impaired hearing (7). The level of lead in a person's system is confirmed by a blood-lead test, and by today's standards a blood lead level is considered elevated if it is in excess of 5 µg/dL (50 ppb) for children (8). However, the long-term effects of lead poisoning have not always been well understood. In the early and mid-1960s, remedial action would be taken if a blood lead level (or 

, as it was known then) was in excess of 60 µg/dL. As investigators discovered more sensitive detection systems and designed better studies, the generally recognized level for lead toxicity has progressively shifted downward. In 1970, it was lowered to 40 µg/dL and, by 1978, the level had been reduced to 30 µg/dL. In 1985, the CDC published a threshold level of 25 µg/dL, which they eventually lowered to 10 µg/dL in 1991. It stayed at this level until it was reduced to 5 µg/dL in 2012. However, as our understanding of disease improves and measurement technology gets more refined, this level could be pushed even lower in the future (9). Figure 1 shows the trend in blood lead levels considered elevated by the Centers for Disease Control (CDC), since the mid-1960s.


	Figure 1: The trend in blood lead levels (µg/dL) in children considered elevated by the Centers for Disease Control and Prevention (CDC), since the mid-1960s.

 (BLRV) has been used more recently (since 2012), and refers specifically to the 97.5th percentile of blood lead levels for children 1–5 years old in the United States, calculated from blood lead tests performed in the National Health and Nutrition Examination Survey (NHANES). The BLRV is not a health-based toxicity threshold, nor does it define what level is considered normal. It is intended to help identify the highest risk childhood populations and geographic areas.

	It is also important to point out that these thresholds were not all determined the same way. Only in 2012 (when the recognized level for lead toxicity was lowered to 5 µg/dL) was the population-based threshold called the BLRV and calculated from population statistics. Although all these levels could be said to describe thresholds of elevated blood lead levels generally, even the term 

wasn't specifically defined in CDC policy until 1978.

	Currently, the major source of lead poisoning among children comes from lead-based household paints, which were used until they were banned in the United States in 1978 by the Consumer Product Safety Commission. Prior to that date, leaded gasoline was the largest pollutant, before it was completely removed from the pumps in 1995. Other potential sources include lead pipes used in drinking water systems, airborne lead from smelters, and clay pots, pottery glazes, lead batteries, and household dust. However, awareness of the problem, combined with preventative care and regular monitoring, have reduced the percentage of children aged 1–5 years with elevated blood levels (≥5 µg/dL) in the US from 26% in the early-mid 1990s to less than 2% in 2014. These data were taken from a recent National Health and Nutrition Examination Survey (NHANES) report (10).

Routine Monitoring of Lead Using Atomic Spectroscopic Techniques

	There is no question that the routine monitoring of children has had a huge impact in reducing the number of children with elevated blood levels. Lead assays were initially carried out using the dithizone colorimetric method, which was sensitive enough, but very slow and labor intensive. The method became a little more automated when anodic stripping voltammetry was developed (11), but blood-lead analysis was not considered a truly routine method until atomic spectroscopy techniques became available. Let's take a more detailed look at how improvements in atomic spectroscopy instrumentation detection capability have helped to lower the number of children with elevated blood lead levels, since atomic absorption was first commercialized in the early 1960s.

	When flame atomic absorption (FAA) was first developed, the elevated blood lead level was set at 60 µg/dL. Even though this level is equivalent to 600 parts per billion (ppb) of lead, which was well above the FAA detection limit of ~20 ppb at the time, FAA struggled to accurately detect lead at these levels when sample preparation was taken into consideration. The preparation of blood samples typically involved either dilution with a weak acid followed by centrifuging or filtering, or acid digestion followed by dilution and either centrifuging or filtering. More recently, dilution with a strong base like tetramethylammonium hydroxide (TMAH) and the addition of a surfactant to allow for easier aspiration has been used. When sample preparation was factored into the equation, a blood lead level of 600 ppb was reduced to 10–20 ppb, virtually the same as the FAA instrumental detection limit.

	To get around this limitation, an accessory called the Delves Cup was developed in the late 1960s to improve the detection limit of FAA (12). The Delves Cup approach uses a metal crucible or boat, usually made from nickel or tantalum, which was positioned over the flame. The sample, typically 0.1–1.0 mL, is pipetted into the cup, where the heated sample vapor is passed into a quartz tube, which is also heated by the flame. The ground state atoms generated from the heated vapor are concentrated in the tube, and therefore resident in the optical path for a longer period of time, resulting in much higher sensitivity and about 100x lower detection limits. The Delves Cup became the standard method for carrying out blood lead determinations for many years, because of its relative simplicity and low cost of operation.

	Unfortunately, the Delves Cup approach was found to be very operator dependent, not very reproducible (because of manual pipetting), and required calibration with blood matrix standards (13). The technique became less attractive when electrothermal atomization (ETA) was commercialized in the early 1970s. This new approach offered a detection capability for lead of ~ 0.1 ppb, approximately 200x better than FAA. However, its major benefit for the analysis of blood samples was the ability to dilute and inject the sample automatically into the graphite tube with very little off-line sample preparation. In addition, because the majority of the matrix components were "driven-off" prior to atomization at ~3000 °C, interferences were generally less than the Delves Cup, which only reached the temperature of the air or acetylene flame at ~2000 °C. This breakthrough meant that blood lead determinations, even at extremely low levels, could now be carried out in an automated fashion with relative ease.

	The next major milestone in AA was the development of Zeeman background correction (ZBGC) in 1981, which compensated for non-specific absorption and structured background produced by complex biological matrices, like blood and urine. ZBGC, in conjunction with the stabilized temperature platform furnace (STPF) concept, allowed for virtually interference-free graphite furnace analysis of blood samples using aqueous calibrations (14). Such was the success of the ZBGC–STPF approach, due primarily to the fact that it could be used to analyze many different kinds of samples using simple aqueous standards, that it became the recognized way of analyzing most types of complex matrices by ETA.

	Even though ETA had been the accepted way of doing blood lead determinations for more than 15 years, the commercialization of quadrupole-based ICP–MS in 1983 gave analysts a tool that was not only 100x more sensitive, but suffered from less severe matrix-induced interferences than ETA. In addition, ICP–MS offered multielement capability and much higher sample throughput. These features made ICP–MS very attractive to the clinical community, such that many labs converted to ICP–MS as their main technique for trace element analysis. Then, as the technique matured, using advanced mass separation devices, performance enhancing tools, powerful interference reduction techniques, and more-flexible sampling accessories, detection limits in real-word samples improved dramatically for some elements. Figure 2 shows the improvement in detection capability (in ppb) of ICP-MS compared to ETA and the other atomic spectroscopy techniques.


	Figure 2: Comparison of detection capability (ppb) of atomic spectroscopy techniques used to monitor blood lead and the approximate year they were developed or improved.

	It should also be emphasized that the detection limits shown in Figure 2 are instrument detection limits (IDLs), which are based on simplistic calculations of aqueous blanks carried out by manufacturers, and not realistic method detection limit (MDL) or procedural limits of detection (PLOD) that take into consideration the sample preparation procedure, dilution steps, and multiple analytical measurements. IDLs are also only intended to be used as a guideline for comparison purposes because there are so many different ways of assessing detection capability, based on variations in manufacturer, instrument design, and methodology.

	Figure 3 is a combination of Figures 1 and 2, and shows improvement in the blood lead method detection limit (now in µg/dL and not ppb) offered by atomic spectroscopy techniques compared to the trend in blood lead levels set by the CDC. To make the comparison more valid, a factor of 100x has been applied to the instrumental detection limits to give an approximation of the achievable "real world" method detection limit in a blood sample matrix. Both plots are shown in log scale, so they can be viewed on the same graph. The main purpose of these data is to show how the blood lead levels considered by the CDC as "elevated" over the past 50 years have dropped as method detection limits of the various atomic spectroscopy techniques have been lowered, thus giving researchers more confidence in the integrity of their data.


	Figure 3: The improvement in real-world method detection capability (in µg/dL) offered by atomic spectroscopy techniques for blood-lead determinations compared to the trend in blood-lead levels regulated by the Centers for Disease Control and Prevention (CDC).

	It should also be emphasized that a degradation factor of 50–100x is quite normal when converting an IDL to an MDL, when characterizing samples by atomic spectroscopy techniques. However, when analyzing a very complex biological matrix like blood by ICP-MS, there are many different ways of calculating LODs to encompass the entire analytical procedure. One common approach to determine the PLOD is to carry out 20 runs and plot standard deviation of the standards and spiked matrix versus concentration, extrapolating the regression line to the ordinate axis, to determine the standard deviation at zero concentration (15). In a high throughput laboratory, this approach might not be realistic, because of the additional time taken. The time involved can be somewhat shortened by taking fewer readings, but doing so will clearly negatively impact the statistical data and detection limit. Whichever approach is used, one should take into account variability in sample preparation, environmental contamination, solvents, and reagents, as well as minor sampling errors from dilution or pipetting over many runs, all of which can cause variability from day to day. Given such variability, a real-world procedural LOD for Pb in blood is often three orders of magnitude worse than the instrument detection limit, and is typically around 0.01–0.07 µg/dL, depending on the type of ICP–MS technology and interference reduction technique used (9,16).

Identifying Sources of Lead Using Isotopic Fingerprinting

	An added benefit of the ICP-MS technique is that it also offers isotopic measurement capability. This feature is very attractive to many clinical laboratories, because it gives them the ability to carry out isotope tracer (17), isotope dilution (18) and isotope ratio (19) measurements, which are beyond the realms of other atomic spectroscopy techniques. In fact, the isotopic measurement capability allows researchers to get a better understanding of the source of lead poisoning by measuring the isotope ratio of blood-lead samples and comparing them with possible sources of lead contamination. The principal behind this approach, known as 

, is based on the fact that lead is composed of four naturally occurring isotopes: 

Pb, all with the same atomic number, but with different atomic masses. Thus, when naturally occurring lead is ionized in the plasma, it generates four ions, all with different atomic masses. Figure 4 shows a mass spectrum of the four lead isotopes 

Pb, together with their relative natural abundances of 1.4%, 24.1%, 22.1% and 52.4%, respectively.


	Figure 4: Mass spectrum of the four lead isotopes at 204, 206, 207, and 208 atomic mass units (amu), with their respective natural abundances.

	All the lead isotopes, with the exception of 

Pb, are products of radioactive decay of either uranium or thorium, the abundance of which will vary slightly depending on the rock type and geological area. This means that in all lead-based materials and systems, 

Pb has essentially remained unchanged at 1.4%, since the earth was first formed (20). The ratios of the isotopic concentrations of 

Pb will therefore vary, depending on the source of lead. This fundamental principle can be then be used to match lead isotope ratios in someone's blood to a particular environmental source of lead contamination.

	However, there are known, well-understood limitations of this approach. For lead fingerprinting to be useful, potential sources of lead exposure must be limited in number and scope and the lead sources must be isotopically distinct. If more than two sources of environmental lead are likely, such as from water pipes, gasoline, smelter, paint, pottery, and glazes, then mixed or combined isotope ratios will occur and, as a result, no useful data will be obtained. In addition, if someone has chronic exposure to extremely high lead levels, the person might have brittle or broken bones, and accumulated lead in the bones would be released into the bloodstream, which could shift the lead equilibrium. This release of lead from the bones could elevate blood lead levels, independent of the source of the lead exposure or contamination.

	A good example of using isotope ratios to pinpoint the source of lead poisoning that worked extremely well involved a study carried out on a group of people living in a small village near Mexico City (21). A number of the residents had abnormally high levels of lead in their blood, which came from one of two likely sources: the use of leaded gasoline, which had contaminated the soil, or glazed ceramic pots, which were used for cooking and eating purposes, or both. For this experiment, the lead isotope ratios were measured using an electrothermal vaporization (ETV) sampling accessory coupled to an ICP-MS instrument. In this sample device, a heated graphite tube, similar to the type used in ETA, is used to thermally pretreat the sample. But instead of using the tube to produce ground state atoms, its main function is to drive off the bulk of the matrix before the analytes are vaporized into the plasma for ionization and measurement by the mass spectrometer. The major benefit of ETV-ICP-MS for this application is that complex matrices like blood, gasoline, and pottery or clay material can be analyzed with very little interference from matrix components (22). An additional benefit with regard to taking blood samples is that typically only a 20–50 µL aliquot is required for analysis. Figure 5 represents a schematic of how the ETV–ICP–MS system works, showing the two distinct steps: prevaporization to drive off the matrix components, and vaporization to sweep the analyte vapor into the ICP–MS for analysis.


	Figure 5: Schematic of ICP-MS coupled with an the electrothermal vaporization sampling accessory (ETV-ICP-MS), showing the two distinct stages: (a) prevaporization to drive off the matrix components and (b) vaporization to sweep the analyte vapor into the ICP-MS instrument for analysis. Adapted with permission from reference 22.

	In the Mexican study, ETV-ICP-MS was then used to determine the lead isotope ratios of 

Pb in blood samples from a group of residents. These ratios were then compared with the two likely sources of lead contamination from the cooking pots and the gasoline samples. Figure 6 shows a subset of data taken from the study. It shows a plot of the 

Pb ratio for the blood, cookware, and gasoline samples. It can be seen from this plot that the data for the blood and cookware are grouped very tightly together around the theoretical value of the ratios (known as the 

), while the gasoline data are grouped together on their own.

Pb for blood (â»), cookware (O), and gasoline (•) samples, showing the theoretical (primeval) lead line. Adapted with permission from reference 21.

	Based on principal component analysis of the data, this result confirms that the lead isotope ratios of the blood and cooking pots are almost identical, and are very close in composition to primeval lead, with very little addition of radiogenic lead (produced from radioactive decay). On the other hand, the alkyl lead compounds used in the production of leaded gasoline are from a different source of lead and as a result generate a very different isotopic signature. These data showed very convincing evidence that the residents of this small Mexican village were getting poisoned by the glazed clay pots they were using for cooking and eating, and not from contamination of the environment by leaded gasoline, as was first suspected.

	There is no question that developments in atomic spectroscopy have helped us better understand the toxicity effects of lead over the past 50 years. Atomic spectroscopy advances have allowed us to lower the clinical practice threshold level of 60 µL/dL in the mid-1960s to the current blood lead reference value (BLRV) of 5 µL/dL. More importantly, these techniques have helped to reduce elevated blood levels of children in the United States from 26% in the early to mid-1990s to less than 2% in 2014, as well as allowing us to get a much better understanding of the environmental sources of lead contamination. However, such is the power and versatility of modern atomic spectroscopy instrumentation and its accessories, that it has also dramatically improved our understanding of other trace metal-related human diseases. The toxic effects of trivalent/pentavalent arsenic and hexavalent chromium or the nutritional benefits of different selenium species would still be relatively unknown, if it weren't for the continual improvements in ICP-MS and, in particular, its use as a very sensitive detector for trace element speciation studies using chromatographic separation technology. Even though ICP-MS has been successfully applied to many application areas since it was first commercialized in 1983, its use as a biomedical, clinical, and toxicological research tool has had a direct impact on the quality of many people's lives.

	I would like to thank Dr. Steve Pappas of the CDC for his thoughtful comments and edits to this month's 

	(1) Elemental Impurities in Pharmaceuticals: Updates: United States Pharmacopeai (USP) Website: 

http://www.usp.org/chemical-medicines/elemental-impurities-updates

	(3) Agency for Toxic Substances and Disease Registry (ATSDR), Toxicological Profile for Lead, Section 3.3: Toxicokinetics, August, 2007, (

https://www.atsdr.cdc.gov/toxprofiles/TP.asp?id=96&tid=22

	(4) Preventing Lead Poisoning in Young Children, Chapter 2: Absorption of Lead, Centers for Disease Control and Prevention (CDC), 1991, 

https://www.cdc.gov/nceh/lead/publications/books/plpyc/contents.htm

	(5) H. L. Needham, Case Studies in Environmental Medicine-Lead Toxicity, U. S. Dept. of Health and Human Services (1990).

	(6) Preventing Lead Poisoning in Young Children, Lead Information Page, Centers for Disease Control and Prevention (CDC), 

https://www.cdc.gov/nceh/lead/default.htm

	(7) Childhood Blood Lead Levels in Children Aged <5 Years: United States, 2009–2014, Morbidity and Mortality Weekly Report (MMWR), Surveillance Summaries /January 20, 2017/66 (3); 1–10, 

https://www.cdc.gov/mmwr/volumes/66/ss/ss6603a1.htm

	(8) CDC Response to Advisory Committee on Childhood Lead Poisoning Prevention Recommendations in "Low Level Lead Exposure Harms Children: A Renewed Call of Primary Prevention" (2012), 

https://www.cdc.gov/nceh/lead/ACCLPP/blood_lead_levels.htm

	(9) Record of Proceedings from the Meeting of the Lead Poisoning Prevention Subcommittee of the NCEH/ATSDR Board of Scientific Counselors, Centers for Disease Control and Prevention (CDC), Atlanta, GA, September 19, 2016.

	(10) Centers for Disease Control and Prevention (CDC), Morbidity and Mortality Weekly Report (MMWR), October 7, 2016/65(39); 1089, Source: The National Health and Nutrition Examination Survey (NHANES); 

	(11) S. Constantini, R. Giordano, M. Rubbing. 

	(13) S. Cabet, J.M. Ottoway, and G.S. Fell, 

Quality Assurance of Chemical Measurements

 (CRC Press, Boca Raton, Florida, 1st ed., 1987).

	(16) D.R. Jones, J.M. Jarrett, D.S. Tevis, M. Franklin, N.J. Mullinix, K.L. Wallon, C.D. Quarles Jr., K.L. Caldwell, and R.L. Jones, 

https://www.sciencedirect.com/science/article/pii/S0039914016307305

	(18) J.W. McLaren, D. Beauchemin, and S.S. Berman, 

Inter-Science Publishers Inc, New York, New York, 1960).

	(21) M. Chaudhary-Webb, D.C. Paschal, W.C. Elliott, H.P. Hopkins, A.M. Ghazi, B.C. Ting, and I. Romieu, 

	(22) S. Beres, R. Thomas, E. Denoyer, and P. Bruckner, 

 is the principal of Scientific Solutions, a consulting company that serves the application and writing needs of the trace element user community. He has worked in the field of atomic and mass spectroscopy for more than 40 years, including 25 years for a manufacturer of atomic spectroscopic instrumentation. He has written almost 90 technical publications, including a 15-part tutorial series on ICP-MS. He recently completed his fourth textbook, entitled 

Measuring Elemental Impurities in Pharmaceuticals: A Practical Guide

. He has an advanced degree in analytical chemistry from the University of Wales, UK, and is also a Fellow of the Royal Society of Chemistry (FRSC) and a Chartered Chemist (CChem). He has served on the ACS Committee on Analytical Reagents for the past 18 years as leader of the heavy metals' task force.

With analytical advances, the clinical practice threshold for lead has dropped from 60 to 5 μL/dL.

The Critical Role of Atomic Spectroscopy in Understanding the Links Between Lead Toxicity and Human Disease

The National Nanotechnology Initiative defines engineered nanomaterials (ENM) as those with dimensions of 1–100 nm, where their unique characteristics enable novel applications to be carried out. ENMs often possess different properties than their bulk counterparts of the same composition, making them of great interest for a broad spectrum of industrial, commercial, and healthcare uses. However, the widespread application of ENMs will inevitably lead to their release into the environment, which raises concerns about their potential adverse effects on the ecosystems and their impact on human health.

	This installment of “Atomic Perspectives” discusses the theory of single-particle inductively coupled plasma–mass spectrometry (SP-ICP-MS) and its use in characterizing and sizing metal-based nanoparticles. The single-particle analytical technique can quantitate the difference between ionic and particulate signals, measure the particle concentration (particles per milliliter), and determine the particle size and size distribution. In addition, it enables users to investigate particle agglomeration and dissolution. As a result, SP-ICP-MS is a key analytical technique in assessing the fate, behavior, and distribution of ENMs in various sample matrices. Besides discussing its fundamental principles, the real-world applicability of SP-ICP-MS will be exemplified by evaluating its capability in various sample matrices (1).

	The unique properties of engineered nanoparticles (ENPs) have made them an essential component of many consumer, industrial, and healthcare products and as a result created intense interest in their environmental behavior (2). For this reason, it is not only important to know the type, size, and distribution of nanoparticles in soils, potable waters, and wastewaters, but it is also crucial to understand their environmental cycle. Therefore, to ensure the future development of nanotechnology products, there is clearly a need to evaluate the risks posed by these ENPs that will require proper tools to fully understand their impact on the ecosystem. Current approaches to assess exposure levels include predictions based on computer modeling, together with direct measurement techniques. Predictions through modeling are based on knowledge of how they are emitted into the environment and by their behavior in the samples being studied. Although the life cycles of ENPs are now starting to be understood, very little is known about their environmental behavior. Prediction through life-cycle assessment modeling requires validation through measurement at environmentally significant concentrations. For ENPs that are being released into the environment, extremely sensitive methods are required to ensure that direct observations are representative in time and space. ENPs differ from most conventional ‘‘dissolved’’ chemicals in terms of their heterogeneous distributions in size, shape, surface charge, composition, degree of dispersion, and so on. For this reason, it is not only important to determine their concentrations, but also these other important metrics.

	The measurement and characterization of nanoparticles is therefore critical to all aspects of nanotechnology. In the field of environmental health, it has become clear that complete characterization of nanomaterials is important for interpreting the results of toxicological and human health studies. Metal-containing ENPs are a particularly significant class because their use in consumer products and industrial applications makes them the fastest growing category of nanoparticles (3).

	Many analytical techniques are available for nanometrology, only some of which can be successfully applied to environmental health studies. Methods for assessing particle size distributions include electron microscopy, chromatography, laser-light scattering, ultrafiltration, and field-flow fractionation. However, the lack of specificity of these techniques is problematic for complex environmental matrices that may contain natural nanoparticles having polydisperse size distributions and heterogeneous compositions. For this reason, sensitive detection techniques are needed if specific information about the elemental composition and concentration of the nanoparticles is required. Unfortunately, difficulties can also arise with some detection techniques due to a lack of sensitivity for characterizing and quantifying particles at environmentally relevant concentrations.

	One technique that is proving invaluable for detecting and sizing metallic nanoparticles is SP-ICP-MS (4). Its combination of elemental specificity, sizing resolution, and unmatched sensitivity makes it extremely applicable for the characterization of ENPs containing elements such as Ag, Au, Ti (TiO

), to name a few, which have been integrated into larger products such as consumer goods, foods, pharmaceuticals, and personal care products.

	Much of the early work has focused on the use of ICP-MS with particle separation techniques, such as field-flow fractionation and chromatography (5). However, more recently, SP-ICP-MS is showing a great deal of promise in several application areas, including the determination of silver nanoparticle concentrations in complex samples (5). This technique is suited to differentiate between the analyte in solution and existing as a nanoparticle without any prior separation techniques, simplifying nanoparticle analysis while eliminating complex sample preparation steps (6). This ability allows SP-ICP-MS to provide information on the size and size distribution of nanoparticles, as well as the dissolved concentration of the analyte.

	SP-ICP-MS involves introducing nanoparticle-containing samples at environmentally significant concentrations into the ICP-MS system and collecting time-resolved data. Because of the very low elemental concentrations and the transient nature of ionized nanoparticles, high sensitivity and very short measurement times are necessary to ensure the detection of individual particles as ion pulses (7,8). The number of observed pulses at the detector is related to the nanoparticle concentration by the nebulization efficiency and the total number of nanoparticles in the sample, while the size of the nanoparticle is related to the pulse intensity. Figure 1 represents the full cycle process of characterizing the size of nanoparticles that have been released into the environment from a manufactured product using SP-ICP-MS.

	In this example, nano-Ag bactericide imbedded in athletic socks is released during simulated wash cycles (step 1, Figure 1). By analyzing a simple aqueous solution with the ICP-MS system (step 2) and collecting data using the SP-ICP-MS technique (step 3), the size, size distribution, concentration, and associated dissolved material can be quantified. The dissolved Ag content is at low signal intensity, with nanoparticles creating pulses above this background where the height of the pulse relates to the mass of analyte and the number of pulses correlates to the concentration of nanoparticle in the samples. The size distribution of particles in the sample can be calculated using well-understood SP-ICP-MS theory (step 4) (9). A histogram of nanoparticle diameter versus number of events (nanoparticle number) can then be created to visualize the nanoparticle distribution in the sample, in addition to calculating the concentration of both nanoparticle and dissolved fractions released from the products (step 5). Let’s take a closer look at the individual steps in this process.

	Effectively detecting and measuring single, individual nanoparticles with ICP-MS requires operating the instrumentation in a different manner than when analyzing dissolved samples. Figure 2 shows traces from both dissolved- and single-nanoparticle analyses. In Figure 2a, a steady-state signal results from measuring dissolved elements; the output when detecting single particles is quite different, as illustrated for 60-nm silver particles in Figure 2b. Each spike in Figure 2b represents a particle. The difference in the way these data are generated plays a key role in understanding single particle analysis. The easiest way to understand this is to compare the processes involved when both dissolved elements and particles are measured.

	When dissolved elements are measured, aerosols enter the plasma where the droplets are desolvated and ionized. The resulting ions enter the quadrupole to be sorted by their mass-to-charge ratios (

). The quadrupole spends a certain amount of time at each mass before moving to the next mass; the time spent analyzing each mass is called the “dwell time.” After each dwell time measurement, a certain amount of time is spent for the electronics to stabilize before the next measurement is performed. This stabilization time is called “settling time”-that is, overhead and processing time. When analyzing dissolved elements, the resulting signal is essentially a steady-state signal. However, considering the dwell and settling times, a significant amount of the signal is not measured because of the settling time of the electronics, a critical aspect when analyzing nanoparticles, as shown in Figure 3. It is important to point out that with dissolved ions, the part of the signal that is missed is not critical because the elements are dissolved and produce a continuous signal.

	Particles present in an aqueous solution are introduced to the plasma the same way as dissolved solutions. As the droplets are desolvated in the plasma, the resulting particles are ionized producing a burst of ions (one ion cloud per particle). The ions then pass into the quadrupole. However, using conventional ICP-MS data collection, alternating between dwell time and settling time, ion clouds are not always detected. If, for example, the ion cloud happens to fall within the dwell time window, it will be detected. Otherwise, if it passes into the quadrupole or reaches the detector during the settling time, it will not be detected, leading to an inaccurate counting efficiency. Figure 4 shows that an ion cloud from a single particle can be missed if it falls outside of the dwell time window, as demonstrated by the first and third dwell time windows. However, when the ion cloud from a single particle falls within the dwell time window, it is detected, as represented by the peak falling within the second dwell time window. When multiple particles are detected in rapid succession, the resulting signal is a series of peaks, each one originating from a particle, as shown in Figure 5.

	Figure 6 is a representation of the timing parameters involved in ICP-MS analysis. The three axes represent signal intensity, mass (

), and time. With conventional analyses of dissolved ions, the mass and intensity axes are the most important: The resulting spectra are plots of m/z versus intensity. The time axis is important when analyzing a transient signal. The quadrupole scan speed is important when measuring multiple elements in a transient signal, such as for laser ablation or multielement speciation analyses.

	However, when measuring transient signals for a single mass, the time axis (transient data acquisition speed in Figure 6) becomes important, since enough data points must be acquired to define the peak. For example, with high performance liquid chromatography (HPLC)–ICP-MS, usually 4–10 points per second are enough to define a peak. Comparing HPLC peaks to single-particle signals, the ion packets from each particle are typically 1000 times narrower than peaks produced by HPLC. Therefore, data must be acquired significantly faster for single-particle analysis. Since only a single mass is typically being measured for single particle analysis, the quadrupole scan speed is not important, and the time axis becomes the “transient data acquisition speed,” which encompasses both the dwell and settling times. For that reason, the faster the transient data acquisition speed, the better suited the system is for single-particle analysis.

	In SP-ICP-MS, transient data acquisition speed consists of two parameters: dwell time (reading time) and settling time (overhead and processing time). It is very important that the ICP-MS is able to acquire signals at a dwell time that is shorter than the particle transient time, therefore avoiding false signals generated from partial particle integration, coincidence and agglomerates or aggregates. The shorter the settling time, the less chance there is of missing a particle. Figure 7 demonstrates the importance of settling time using a constant 100-μs dwell time and a constant time window. In Figure 7a, there are only two 100-μs windows to detect particles; the rest of the time is overhead, where data cannot be acquired. In this case, there are only about 100 measurements made in one second. Therefore, most of the time is wasted by scanning and settling. Figure 7b is the same time scale, but with a settling time of 100 μs. Therefore, more time is spent measuring and looking for nanoparticles-about 5000 measurements in one second. However, still half of the time is wasted. Figure 7c represents the ideal situation with no settling time. This allows for 10,000 measurements per second, with no wasted time being spent scanning and settling-the ideal situation for SP-ICP-MS.

	Another benefit of fast continuous data acquisition is that multiple points can be measured from a single particle, thus eliminating the chances that particles are missed or that only partial ion clouds from particles are detected. Figure 8 shows how this can be accomplished. In Figure 8a, the signal from a single particle is measured multiple times. The signal from each time slice is plotted, which defines the peak. When multiple particles are detected, the resulting peaks are a series of time slices, as shown in Figure 8b.

	Figure 9 shows how typical single-particle responses can be converted into peaks that define a single particle. In Figure 9a, data was collected in fast continuous mode (no settling time) with a dwell time of 100 μs. When the intensities from the first 1.6 s are plotted, it is seen that six points define a peak. In Figure 9b, the dwell time was reduced to 50 μs, which leads to twice as many data points being acquired. As a result, the peak shape is defined by 12 points, leading to a different peak shape. These examples demonstrate the benefit of sampling multiple data points per particle.

	Converting Nanoparticle Pulse Counts to Nanoparticle Diameter

	It is important to emphasize that ICP-MS is a mass-based technique where particle size is determined by relating the pulse intensity to an elemental mass. With traditional ICP-MS analysis, the first step in this process is to create a calibration curve using dissolved standards. This curve connects the signal intensity from the instrument to the concentration of the analyte entering the plasma. The next step is to relate the concentration of the dissolved analyte to a total analyte mass that enters the plasma during each reading. This relationship between analyte concentration and the mass observed per event is called the “mass flux,” which is highly dependent on the transport efficiency of the sampling process. This transport efficiency must be calculated for each instrument and under the given run conditions for the mass flux to be accurate. In this way, the resulting calibration curve relates signal intensity (counts/event) to a total mass transported into the plasma per event.

	By using well-understood SP-ICP-MS principles, the intensity of each individual pulse (counts/event) can then be transformed using the mass flux calibration curve to determine the particle mass, which can then easily be converted to particle diameter, by knowing the density and assuming the geometry (shape) of the particle is spherical (10). This process is exemplified in Figure 10, which shows a signal of multiple silver nanoparticles over time (Figure 10a), with an individual pulse at the bottom left (Figure 10b) and the dissolved ionic calibration curve on the top (Figure 10c). On the top right is shown the mass of the particle (in micrograms) per dwell time after nebulizer efficiency and flow rate have been applied (Figure 10d). The mass of the nanoparticle is then converted to a diameter, which is based on the mass fraction and the density, which is based on the shape of the particle (Figure 10e).

	Let’s now take a look at the real-world applicability of SP-ICP-MS by evaluating its capability and suitability for characterizing nanoparticles in some common sample matrices, including surface waters and human blood.

	Assessing the Fate of Silver Nanoparticles in Surface Water Using SP-ICP-MS

	Most analytical techniques are not suitable for environmental matrices, because nanoparticle concentrations are typically very low (11). Historically, particle size has been measured by dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), and transmission electron microscopy (TEM), while dissolved content has been measured by ultrafiltration. These common techniques have known limitations for measuring low concentrations in the presence of colloidal species in complex waters.

	On the other hand, SP-ICP-MS has been found to be a promising technique for detecting and characterizing metal nanoparticles at very low concentrations. Silver nanoparticles are one of the most frequently studied types of nanoparticles, because they are among the most common nanomaterials found in consumer products such as laundry detergents and personal hygiene products and tend to release free Ag ions, especially at low concentrations. The aim of this study was to investigate the use of SP-ICP-MS for the detection and characterization of metal nanoparticles in environmental waters where they can be involved in various physicochemical processes.

	It is important to point out these types of dissolved species can also be determined by ultrafiltration followed by total metal quantification using ICP-MS or atomic absorption spectrometry. However, this procedure is time consuming since it requires the preequilibration of the filtration membrane for at least three cycles of centrifugation, which is typically 20 min each (12). Additionally, aggregates and remaining stable silver nanoparticles can be counted and measured by other commonly used techniques (DLS, TEM) but SP-ICP-MS is the only practical method that can distinguish between silver nanoparticles and other colloids in surface waters in a timely manner.

	The ICP-MS system (NexION 350X, PerkinElmer Inc.,) instrumental parameters used for this analysis are given in Table I. SP-ICP-MS data acquisition was carried out using the instrument’s Syngistix Nano Application software module (13). The sample introduction system consisted of a quartz cyclonic spray chamber, a type C0.5 concentric glass nebulizer, and a 2-mm-bore quartz injector.

	Commercially available suspensions of gold and silver nanoparticles were used in this work. A reference material (NIST 8013) consisting of a suspension of gold nanoparticles (60 nm nominal diameter, 50 mg/L total mass concentration and stabilized in a citrate buffer) was used to determine the nebulization efficiency. Suspensions of silver nanoparticles were used, including citrate-coated (40 and 80 nm nominal diameter) and bare (80 nm nominal diameter) nanosilver suspensions (Ted Pella Inc.).

	The surface water was sampled in Rivière des Prairies (Montreal, Canada) and filtered with 0.2-μm filter paper before spiking with silver nanoparticles. Silver nanoparticle suspensions were added to water samples with concentrations ranging from 2.5 to 33.1 μg Ag/L and left to equilibrate under continuous and gentle shaking. Before SP-ICP-MS analysis, small aliquots of the samples were diluted to below 0.2 μg Ag/L.

	Data acquisition was performed in triplicate for each sample, and deionized (DI) water was analyzed between replicates to check memory effects. As shown in Figure 11, the Syngistix Nano Application Module generates plots of frequency versus size (nanometers) plots with an interactive focusing window, eliminating the need for any subsequent data processing using theoretical equations described earlier.

	As previously described, SP-ICP-MS data processing is based on distinguishing between the signal of dissolved metal and that of nanoparticles, counting the pulses (or events) corresponding to individual nanoparticles and converting their intensities to particle size. The frequency of the events (pulses) provides particle number concentration, and the intensity of each pulse is proportional to the mass of analyte. The latter was converted to volume and then into size knowing the density and the geometry of the particle using the Syngistix Nano Application module for fully automated data acquisition; subsequent manual data processing is not required.

	Even after filtration of surface waters at 0.2 μm, an NTA system (LM14, NanoSight Ltd.) with a green laser at 532 nm showed the presence of colloidal particles with an average diameter of approximately 110 nm. Therefore, the addition of metal nanoparticles to this complex matrix will make their detection and characterization very difficult, if not impossible, with commonly used techniques such as DLS and TEM because they lack specificity to elemental composition.

	Furthermore, even the determination of the dissolved fraction that is usually performed by ultrafiltration may be inadequate because silver ions could adsorb onto the surface of the colloids and, therefore, be retained by the filtration membrane. As a result, the proportion of dissolved metal will be underestimated. SP-ICP-MS measurements were found to be more effective and to have fewer limitations than other techniques. Additionally, the presence of other insoluble particles does not interfere with the analysis of silver nanoparticles, as the Ag signal is recorded independently of the other constituent elements of the colloids.

	The study carried out further investigations to better understand the evolution of the average particle diameter and the percentage of dissolved metal over time in both pure and river water (14). The individual data will not be presented here, but in all cases, the average particle size of the persistent nanoparticles remains substantially constant. For suspensions of particles with a nominal diameter greater than 40 nm, between 50 and 80% of the particles persist for at least five days of equilibration in pure and surface water. Under the experimental conditions of this work, the coating appears to have no significant effect on the dissolution of nanoparticles over time-both citrate-coated and bare silver nanoparticle (80 nm) suspensions showed a slight decrease of particulate silver by approximately 20% during five days. Additionally, for the same size and equilibration time, the proportion of dissolved silver was found higher in the case of citrate-coated silver nanoparticles. This does not necessarily mean that bare nanosilver is more stable than citrate-coated silver nanoparticles. It could be that the release of silver ions may be due to oxidation to residual Ag ions adsorbed on the surface of silver nanoparticles or bonded to the coating. We believe that the stability and behavior of nanoparticles in any medium will depend on the synthesis procedure. This is supported by the fact that smaller particles with a nominal diameter below 40 nm tend to dissolve at a faster rate.

	Determination of Gold and Silver Nanoparticles in Blood Using SP-ICP-MS

	The small size of nanoparticles and their potential for enhanced reactivity resulting from larger surface area per volume has raised concerns about their adverse effects on human health. Although these properties may enhance their desired application benefits, they may also introduce new, unwanted toxic effects (15). Two metal nanoparticles, gold nanoparticles and silver nanoparticles, have been widely studied. Gold nanoparticles are particularly interesting due to their desired intrinsic properties such as high chemical stability, well-controlled size and surface functionalization, while silver nanoparticles, due to their antibacterial properties, are often applied in wound disinfection and in coatings of medical devices and prostheses, and also in commercial textiles, cosmetics and household goods (16). As a result, concerns have been raised about the migration of silver nanoparticles from bandages or medical devices into open wounds and thus, the blood stream. These concerns emerge from recent publications showing that nanoparticles can directly be taken up by the exposed organs and are able to translocate using the blood stream to secondary organs, such as the central nervous system, potentially affecting the growth characteristics of embryonic neural precursor cells (17). Therefore, the need exists for researchers to detect and measure nanoparticles in blood. The work described here explores the ability of SP-ICP-MS to detect and measure gold and silver nanoparticles in whole blood (18).

Experimental Samples, and Sample Preparation

	A blood Standard Reference Material (Seronorm Trace Elements in Whole Blood, Level I) was diluted 20 times with tetramethylammonium hydroxide (TMAH) plus 0.1% Triton-X. Gold and silver nanoparticles (gold-30 and 60 nm, NIST 8012, 8013; silver-40 and 60 nm, Ted Pella Inc.) were added to each blood sample at various concentrations. To break up any agglomerated particles, the stock solutions were sonicated for 5 min before spiking in the blood. The blood samples were manually shaken before analysis.

	The ICP-MS system (NexION 350X, PerkinElmer, Inc.) instrumental parameters used for this analysis are given in Table II. SP-ICP-MS data acquisition was carried out using the instrument’s Syngistix Nano Application software module. Calibrations were carried out with both dissolved and particulate gold or silver standards, which are shown in Table III.

	Two rinses were used between samples: 1% HCl plus 0.1% Triton-X was aspirated to dissolve and remove any residual gold particles, followed by deionized water to remove traces of the hydrochloric acid. A solution of 1% HNO

 plus 0.1% Triton-X was used as a rinse solution for silver particles. This two-solution rinse approach was found to be essential because residual acid could dissolve particles in the sample. Each rinse solution was aspirated for 1 min.

	Initial tests were performed with gold nanoparticles. Figure 12 shows a blood sample spiked with a mixture of 30- and 60-nm Au nanoparticles (each approximately 100,000 particles/mL). There are clearly two size distributions, indicating that both particle sizes are seen. This sample was analyzed three times consecutively, with the measured particle sizes shown in Table IV. These results demonstrate both accuracy and repeatability of the methodology.

	Next, 40- and 60-nm Ag nanoparticles were added to the blood samples so that the final, total particle concentration was about 200,000 particles/mL. Figure 13 displays the detected particle distribution, and Table V shows results for three replicates of the spiked blood sample. It’s worth pointing out that the software module first converts the peak area intensity into mass and the resulting mass into diameter. This is then displayed as frequency of events versus nanoparticle diameter, as described earlier.

	To see if lower particle concentrations could be detected in blood, only 40-nm Ag nanoparticles were spiked into the blood samples at a nominal concentration of 50,000 particles per milliliter, half the concentration of the previous analysis. The data shown in Table VI demonstrate that even at low concentrations, Ag nanoparticles can be accurately and reproducibly measured in blood.

	As has been shown, measuring single particles with ICP-MS is quite different than measuring dissolved species. The most important factor when measuring single particles is the speed at which data can be acquired: since particle ionization events are on the order of microseconds, rapid data acquisition and elimination of the settling time between measurements are crucial. Continuous measurement allows multiple readings per particle ionization event, which results in more-accurate size determinations. For SP-ICP-MS analysis, continuous data acquisition at a dwell time shorter than or equal to 100 μs is the most important instrumental requirement for precise nanoparticle counting and sizing.

	The investigation has also shown that when using automated data acquisition software optimized for SP-ICP-MS measurements, it is possible to study the behavior of silver nanoparticles in surface water without using any subsequent manual data processing. The technique has allowed the effective and selective measurement of changing particle size, aggregation and dissolution over time at low concentrations. Based on these data, SP-ICP-MS is uniquely suited to provide such information on the fate of metal nanoparticles at very low concentrations in environmental surface waters. This work has also demonstrated the ability of SP-ICP-MS to rapidly and accurately detect and measure gold and silver nanoparticles in whole blood, both at low concentrations and in mixtures. Although this study has just focused on gold and silver nanoparticles in surface waters and blood samples, there is no doubt that it is applicable to other types of metal and metal oxide nanoparticles in a variety of complex matrices including wastewater, effluents, culture media, as well as biological tissue and fluids (19,20).

		White Paper: Weighing the Benefits and Risks of Nanotechnology, Single Particle ICP-MS Compendium of Applications, PerkinElmer Nanomaterial Reference Library, 

https://www.perkinelmer.com/lab-solutions/resources/docs/Nanomaterials_SP-ICP-MS_Compendium(012982_01).pdf

		Nanotech-Enabled Consumer Products Continue to Rise: The Project on Emerging Nanotechnologies, 2017, 

http://www.nanotechproject.org/news/archive/9231/

		D.M. Mitrano, A. Barber, A. Bednar, P. Westerhoff, C.P. Higgins, and J.F. Ranville,

		D.M. Mitrano, E.K. Leshner, A. Bednar, J. Monserud, C.P. Higgins, and J.F. Ranville, 

The National Nanotechnology Initiative defines engineered nanomaterials (ENM) as those with dimensions of 1–100 nm, where their unique characteristics enable novel applications to be carried out. ENMs often possess different properties than their bulk counterparts of the same composition, making them of great interest for a broad spectrum of industrial, commercial, and health care uses. However, the widespread application of ENMs will inevitably lead to their release into the environment, which raises concerns about their potential adverse effects on the ecosystems and their impact on human health.

Robert Thomas

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