Next Article in Journal
Comparisons Where It Matters: Using Layer-Wise Regularization to Improve Federated Learning on Heterogeneous Data
Previous Article in Journal
Mitigating Sensor and Acquisition Method-Dependence of Fingerprint Presentation Attack Detection Systems by Exploiting Data from Multiple Devices
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evidence of Volatility Metals and Metalloids at Environment Conditions

by
Svetlana B. Bortnikova
1,
Nataliya V. Yurkevich
1,*,
Sergey S. Volynkin
1,
Aleksander S. Kozlov
2 and
Alexey L. Makas
1
1
Trofimuk Institute of Petroleum Geology and Geophysics SB RAS, 630090 Novosibirsk, Russia
2
Institute of Chemical Kinetics and Combustion SB RAS, Institutskaya, 3, 630090 Novosibirsk, Russia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(19), 9942; https://doi.org/10.3390/app12199942
Submission received: 14 September 2022 / Revised: 28 September 2022 / Accepted: 29 September 2022 / Published: 3 October 2022
(This article belongs to the Section Earth Sciences)

Abstract

:
Tailings represent a significant risk to the environment globally, but very little is known about the composition of the near-surface air. We conducted laboratory experiments to determine the sizes of the particles and the chemical composition of the flow above the mine waste. A condensate of vapor–gas flow was collected in parallel with particle control by an aerosol diffusion spectrometer (ADS). We reveal that there were no aerosol particles bigger than 3 nm in the flow. The collected condensate contained chemical elements, ions of sulfates, chlorides, phosphates, and formates and a wide range of sulfur-, selenium-, and carbon-containing gases. The main findings of the study are the presence of the metals Zn, Cu, Fe, Al, Cd, Ni, and Ba and the metalloids As, Sb, Se, Ag, Co, Ti, and V in the true-gas phase or in the form of particles smaller than 3 nm in the air above the mine tailings. The surprising fact is that the migration of metals and metalloids in a true-gas form or in ultrafine particles (<3 nm) is possible, which opens up a new research direction on the volatile forms of chemical elements in various climatic conditions and their bioavailability and toxicity.

1. Introduction

The problem of air pollution caused by mine tailings poses a great danger due to its impact on the composition of the environment and on the various communities that live nearby. The atmospheric transport of metal and metalloid contaminants plays a huge role in the global, regional, and local processes of migration and in the redistribution of elements, and has important health and environmental implications [1]. The atmosphere is much more mobile than the hydrosphere and lithosphere [1,2,3,4]. The elements involved in the atmospheric-transport processes can be present in the form of gases, dispersed particles of various sizes (particulate matter [PM]), and ions sorbed by them.
The main method of assessment air pollution is collecting airborne samples using different devices: a high-volume air sampler [5,6], a proton-induced X-ray emission spectroscopy cascade impactor (PCI) sampler [7,8], the 10-stage micro-orifice uniform deposit impactor MOUDI [9,10], and high-volume samplers [11]. These methods are used to collect PM with different dimensions (>16 µm ÷ 0.5–0.25 µm). The determination of the mass, chemical, and mineral compositions of PM provides information on the concentrations of the elements in the air and the forms of their occurrence [12,13,14,15,16,17], which allows the assessment of the toxicity and bioavailability of aerosols [11,18,19]. The migration of metals in the air as part of both fine and ultrafine aerosol particles is considered the main mechanism of air pollution in regions affected by abandoned mine tailings [20,21]. The study by J. Yabe [22] provided data on the metal contents (Pb, Zn, Cd) in the blood, feces, and urine of children from three townships near the abandoned lead–zinc mine in Kabwe. It was determined that the children living in townships that were close to and in the direction of the prevailing winds from the abandoned mine dumps recorded the highest concentrations of metals in their bodies. The authors concluded that polluted dust was the main exposure route for the affected townships.
It should be noted that in addition to these two main forms of transport in the atmosphere, there is a very interesting low-temperature vapor–gas transport of a wide range of chemical elements, which is little discussed in the literature. The possibility of migration of chemical elements with a true vapor–gas phase at low temperatures and the formation of volatile metal complexes is considered in the literature only for a number of chemical elements. The possibility of entering the atmosphere and further transport due to the formation of volatile hydrides or biomethylation for As, Se, Cd, Sn, Sb, Te, Hg, and Pb has been fairly well studied [23,24]. A few works are devoted to volatile metal compounds and their transport in the atmosphere in the form of volatile carbonyl complexes of Ni, Co, Mo, and W. The most important work in this area was carried out by J. Feldmann, and results were obtained on the study of gases emanating from landfills and municipal sewage treatment plant [24,25,26]. The authors confirmed the possibility of gaseous emissions of a wide range of elements in the alkylated forms, hydrides, and carbonyl complexes using gas chromatography methods with mass spectrometric detection.
Our earlier works also showed the possibility of low-temperature vapor–gas transfer of chemical elements, both from solid matter and from solutions [27,28]. It has shown that the steam-gas flow both above the surface of sulfide tailings and in the background sites carries a wide range of elements, including alkali, alkaline earth, ore-forming metals, and metalloids. These results were obtained during the collection and analysis of condensates of steam-gas flows from sulfide tailings in field and laboratory experiments.
The question of the forms of transfer of elements remains very relevant with ultrafine particles with sorbed metals, as is widely described in the literature [10], or in true-gas forms. To elucidate the forms of migration of elements in low-temperature conditions, an experiment was carried out on an original installation, including an aerosol diffusion spectrometer (ADS; developed and manufactured by the Institute of Chemical Kinetics and Combustion SB RAS (ICKC), Novosibirsk), a circuit for collecting condensates, and a gas chromatograph/mass spectrometer (GC/MS).

2. Materials and Methods

2.1. Experiment Setup

The experiment was carried out in a sample of the material of the dump in which the cyanidation waste of the oxidation zone of the Beloklyuchevskoe deposit was stored.
The experiment setup included heating a sample of the waste material on an adjustable heating element; purging it with an airflow using a pump, a flow rate meter, and a BQ-class aerosol filter with a 1.5 L/min airflow and controlling the amount of aerosol particles in the air above the sample; collecting the condensate formed during the heating of the solid sample using a bubbler; and collecting the air into a sorbent for gas composition analysis (Figure 1). The sample temperature was determined using a digital thermocouple thermometer. The concentration of the aerosol particles in the tank was monitored using an ADS that consumes 1 L/min and was controlled from a personal computer (developed and manufactured at ICKC SB RAS). An ADS was designed for the automatic determination of the concentration and size spectrum of the aerosol particles. The principle of operation of the device was based on the known dependence of the diffusion coefficient of microparticles on their size.
The main element of the ADS was a mesh-type diffusion battery. The filling of the battery was in the form of packs of meshes arranged perpendicular to the flow. The range of particle diameters measured by the ADS was approximately 3–200 nm. The diffusion battery consisted of eight sections connected in series. The technical side of the spectrometer operation was reduced to sequential counting of the number of aerosol particles as the flow passes through the sections.
The operation of the device was based on the dependence of the diffusion coefficient (D) of microparticles on their size:
D ( r ) = k T 6 π η r ( 1 + A l r + B l r e b r l )
where k is the Boltzmann constant, T is the temperature, η is the air viscosity, r is the particle radius, l is the free path length, A = 1.246, B = 0.42, b = 0.87–constants (cgs).
This dependence leads to the fact that particles of different sizes have different deposition rates when the aerosol flow passes through porous media; that is, smaller particles move faster out of the flow, and thus, the coefficient of passage of particles through such medium contains information on the particle size. This circumstance is used in ADSs.
The positive difference between the air entering and leaving the container ensured reliable isolation of the sample from external aerosol. In the course of the experiment, after the cleanliness of the air path was checked, the heater was turned on, and every 5 s, a countable amount of aerosol particles with a diameter of more than 3 nm was recorded.
Thus, during the experiment, the condensate of the vapor–gas mixture separated from the sulfide waste substance was collected with constant control of the particle size in the flow.

2.2. Methods for Analyzing the Composition of the Waste Material

The history of formation, chemical and mineral composition of the dump was described by us earlier [28]. The sample for the experiment was a substance of quartz-pyrite bulk. To characterize the chemical composition of the sample, the content of oxides of the silicate group, the concentration of metals and metalloids were determined. The contents of major oxides in the bulk solid samples were determined via X-ray fluorescence analysis from a 3 g sample aliquot. The elemental composition of solid material was determined using inductively coupled plasma mass spectrometry ELAN-9000 DRC-e, Perkin Elmer, USA (“PLASMA” Company, Tomsk, Russia). The amount of mobile (water-soluble) forms of elements was determined from the composition of the aqueous extract. We used the standard procedure for obtaining aqueous extract from the waste material, according to the scheme: 10 g of the sample was left in 100 mL of bi-distilled water for 24 h on a magnetic stirrer. Aliquots of the obtained solutions were separated from solids by filtering through 0.45 μm membrane filter.

2.3. Methods for the Analysis of Condensates and Aqueous Extracts from Waste Materials

The contents of the inorganic and organic anions (SO42−, Cl, PO43−, HCOO) in the aqueous extracts and condensates were measured with a Kapel 105-M capillary electrophoresis system (Lumex, Saint Petersburg, Russia). Quantitative analysis was carried out using an external calibration against the areas of ions peaks using the Elforun software. For replicating of multiple samples, the relative standard deviation was less than ±15% in the concentration range from 0.1 mg/L to 200 mg/L. An Agilent 8800 ICP-MS instrument (Japan) equipped with MicroMist nebulizer was applied for the determination of the elements in water samples. High-purity argon (99.95%) was used as plasma-forming, transporting, and cooling gas. A solution of Li, Mg, Co, Y and Tl in 2% nitric acid with a concentration of 1 μg/L for each determined element (“ICP-MS Tuning Solution”, Agilent Technologies, Mulgrave, Australia) was used for the adjustment. All analytes were measured in He mode and Hydrogen mode, MS/MS O2 mode. A Sc, Y, Tl internal standard solution (15 µg/L) was mixed online with the sample via the standard ISTD mixing T-connector. Three sigma method detection limits (MDLs) and 10 sigma Limit of Quantitation (MLOQs) were calculated from 10 measurements of the preparation blank (Table 1). All measurements were conducted in three replicates (n = 3) for each element. The relative standard deviation did not exceed 13% for all measurements. All validations and sample analyses were performed in conjunction with appropriate QA/QC, including blank samples prepared using distilled de-ionized water (>15 MΩ) and high purity nitric acid for ICP-MS spectrometry. ICP-MS control were prepared using a 1.00 ± 0.05 mg/L standard multielement solution for ICP-MS (SKAT, Novosibirsk, Russia).

2.4. Method of Analyzing the Gas Composition of the Air above the Sample Surface

Analyses of the gases from the sample were carried out using a field GC/MS previously developed and manufactured at the Laboratory of Field Analytical and Measurement Technologies of IPGG SB RAS [29]. A parallel weighed portion of the sample (1 kg) with which the experiment was carried out was placed into a 1 L hermetically sealed glass pot. The sample was analyzed at a temperature of 50 °C. After the sample was kept at this temperature for 1 h, 500 mL of the sample’s gas phase was pumped from the glass through concentrators comprising thin-walled stainless steel tubes with an outer diameter of 2 mm containing a layer of Tenax-TA sorbent (0.015 cm3). The gas sample was introduced into the GC column through direct flash thermal desorption in a stream of helium at a temperature of 300 °C. The parameters of the GC column were 0.32 mm × 1 μm × 15 m (HP-5MS, Agilent Technologies, Santa Clara, CA, USA). The GC separation mode involved holding the temperature at 90 °C for 3 min then increasing it to 250 °C at a rate of 10 °C/min. The resulting GC/MS data were processed using the AMDIS (Automatic Mass Spectral Deconvolution and Identification System) program, and identification of the individual components was performed using the mass spectra of electron ionization using NIST/EPA/NIH Mass Spectral Library 2014.
In our previous studies, a number of sulfur- and selenium-containing compounds was identified in the steam–gas emissions of dumps with a similar composition [30], among which a significant proportion consisted of very volatile organic compounds with boiling points up to 50 °C. The World Health Organization has identified these as an independent subgroup [31] because their quantitative determination in the air requires special analytical procedures due to the difficulty of capturing them using standard sorbents such as Tenax.
The main method of assessing the concentration is normalizing the area of the chromatographic peak of the analyte to the area of the peak of the reference substance, determined under the same analysis conditions. In this work, we used a source of the standard concentration of 2,4,6-trinitrotoluene vapors, prepared by applying a reference substance to the surface of a carrier with a developed surface [32] (Institute of Inorganic Chemistry SB RAS, Novosibirsk, Russia). The support is based on fine stainless steel grids coated with a solution of the required concentration of the reference substance in polyphenyl ether. At room temperature, the concentration of 2,4,6-trinitrotoluene was 0.8 ppb (7.4 μg/m3). With this method of assessing concentrations, the largest contribution to the measurement error of very volatile organic substances (e.g., carbon disulfide, dimethyl selenide, dimethyl disulfide) is made by the analyte capture coefficient Ki, which is defined as the fraction of the captured substance during sampling for the concentrator compared to the total capture. The reference substance is completely captured.
To consider incomplete capture, we experimentally measured the capture coefficients for acetone, dimethyl carbonate (DMC), dimethylethyl carbonate (DMEC), and dimethyl methyl phosphonate (DMMP), and based on these data, the aforementioned parameter was approximated for the analytes under study based on chromatographic retention indices. The experiment data for determining the collection coefficients are shown in Figure 2.
As a result of this semi-quantitative approach, the concentration of analyte Ci was calculated using the following formula:
C i = C 0 × S i × V i K i × S 0 × V 0 ,
where Ci, C0—concentrations of analyte and reference substances, respectively; Si, S0—the area of the peak of the analyte and reference substance, respectively; Vi, V0—the volume of the analyte sample and the reference substance, respectively; Ki—analyte recovery factor.

3. Results

3.1. Mine Tailings Sample Composition

As shown in Table 2, the main components of the mine tailings sample were quartz (SiO2 ~ 25%), pyrite (FeS2 ~ 20%), and barite (BaSO4 ~ 24%). Other sulfides (galena PbS, sphalerite ZnS, and chalcopyrite CuFeS2), sulfosalts (tennantite Cu12As4S13 and tetrahedrite (Cu,Fe)12Sb4S13), and remnants of rock-forming minerals (potassium feldspar, mica, and chlorite) were present in significantly smaller amounts.
The composition of the aqueous extract, which characterizes the concentration of water-soluble forms of elements (present in the sample in the form of secondary sulfates), is presented in Table 3. The aqueous extract is a sulfate solution in which the main cations are iron and calcium, which form a numerous of secondary sulfates. Note the high contents of arsenic and selenium, which are apparently included in the composition of soluble sulfates as impurities.

3.2. Air Composition

When the sample was blown with clean air, it was determined that there were no aerosol particles bigger than 3 nm in the airflow. While the air was being blown in the laboratory room, the presence of particles bigger than 3 nm with an average concentration of ~10,000 cm3 was recorded (Figure 3). The figure shows only a fragment of the measurements that were obtained for 15 min. The experiment lasted 4 h, and during this time, no aerosol particles bigger than 3 nm were detected in the airflow. This means that the airflow was a true vapor–gas mixture.

3.3. Condensate Composition

The main anion in the condensate was sulfate with a 12 mg/L concentration, which is equal to 73 mg-eq%. Chloride was in a smaller amount (2.4 mg/L, 20 mg-eq %), and the two other anions (phosphate and formate) made up a small fraction of the condensate. Many chemical elements in the condensate were identified, and the main ones were Ca, Na, K, and Mg (Table 4). Of the trace elements, Zn had the highest concentration, followed by Cu and Pb. The total concentration of Fe, Al, Cd, Ni, Ba, and Sr was more than 10 µg/L. The metalloids As, Sb, and Se were found in µg/L concentrations. Other elements (Ag, Co, Ti, and V) were found in small amounts (<1 µg/L).

3.4. Composition of the Gas Phase

During the experiment, the composition of the vapor phase above the sample of the waste material in a glass container was analyzed both under stationary conditions and under continuous purging with purified air at a 3 L/min flow. The composition of volatile compounds in the vapor–gas emanations of the waste material was represented by a wide range of volatile selenides and sulfides, and there were also molecular sulfur vapors (Table 5). The highest concentrations were observed for carbon disulfide and dimethyl selenide. We previously found high concentrations of these substances at the Ursky dump, which has a similar composition [30].
However, in the experiment, the concentrations of the gases above the waste sample were insignificant because there was a constant blowing of clean air. Consequently, the main transport agent was water vapor, which was separated from the sample. The presence of chemical elements in a vapor–gas stream that does not contain aerosol particles indicates their transfer by true vapor–gas stream.
Simulation of this process is impossible because there are no thermodynamic constants of volatile compounds of elements for these PT conditions. Therefore, we can only assume that the elements found in condensates can form complex compounds with anions found in condensates, or can be carried by water vapor in the form of aqua ions or complex compounds.
The sources of the elements in vapor–gas streams are the secondary soluble sulfates formed in the waste material during the oxidation of sulfides. This is evidenced by the high correlation between the concentrations of the elements in the condensate and the water extract (r = 0.85), which reflects the amount of water-soluble forms of elements in secondary sulfates. Such a high correlation coefficient was obtained when iron was excluded from the calculations. The anomalously inert behavior of iron in vapor–gas transport has been determined in field and laboratory experiments [28], and the results obtained in this study once again confirm this pattern, whose explanation has not yet been found. It was previously determined that when sulfates are heated, sorbed water is first separated, followed by structural water, which dissolves the surface of the grains and rises in the form of steam with trapped elements [28].

4. Conclusions

The composition of the gas phase in the air above sulfide-containing mining wastes was studied. A clean, aerosol-free air stream was obtained in the laboratory experiment under the control of an ADS.
It was shown that inorganic and organic components were present in the true-gas phase. The collected condensate contained ions of sulfates, chlorides, phosphates, and formates, and its main cations were Ca, Mg, K, and Na. An amazing fact is the presence in the true-gas phase (or in the form of particles smaller than 3 nm) of elements whose compounds are traditionally considered low volatile. The metals Zn, Cu, Fe, Al, Cd, Ni, and Ba and the metalloids As, Sb, Se, Ag, Co, Ti, and V were found in slightly smaller amounts.
The gas phase contained a wide range of sulfur-, selenium-, and carbon-containing gases, including carbon disulfide, a second-hazard-class gas.
The main sources of metals in the air above sulfide dumps are pore solutions and secondary minerals.
The question of the mechanisms of atmospheric transport and forms of migration of a number of chemical elements in the true gas phase at low temperatures and specific forms of transport will be studied in the future.

Author Contributions

Conceptualization, S.B.B. and A.S.K.; methodology, N.V.Y., S.S.V. and A.L.M.; validation, S.B.B., S.S.V. and N.V.Y.; formal analysis, N.V.Y.; investigation, S.B.B., A.S.K., N.V.Y. and A.L.M.; resources, S.B.B. and N.V.Y.; data curation, N.V.Y. and S.S.V.; writing—original draft preparation, S.B.B., N.V.Y. and S.S.V.; writing—review and editing, S.B.B., N.V.Y. and S.S.V.; visualization, S.B.B.; supervision, S.B.B. and N.V.Y.; project administration, S.B.B.; funding acquisition, S.B.B. and N.V.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ministry of Education and Science of Russian Federation, grant number 0266-2022-0028. The APC was funded by Russian Foundation for Basic Research, grants number 20-05-00126.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available upon request to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Csavina, J.; Field, J.; Taylor, M.P.; Gao, S.; Landázuri, A.; Betterton, E.A.; Sáez, A.E. A review on the importance of metals and metalloids in atmospheric dust and aerosol from mining operations. Sci. Total Environ. 2012, 433, 58–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Church, K.; Hanks, P. Word association norms, mutual information, and lexicography. Comput. Linguist. 1990, 16, 22–29. [Google Scholar]
  3. Rasmussen, E.N.; Blanchard, D.O. A baseline climatology of sounding-derived supercell andtornado forecast parameters. Weather. Forecast. 1998, 13, 1148–1164. [Google Scholar] [CrossRef]
  4. Seinfeld, J.H.; Pandis, S.N. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 2nd ed.; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2006. [Google Scholar]
  5. US Environmental Protection Agency. Compendium Method TO-16: Long-Path Open-Path Fourier Transform Infrared Monitoring of Atmospheric Gases; US Environmental Protection Agency: Research Triangle Park, NC, USA, 1999.
  6. Beamer, P.I.; Sugeng, A.J.; Kelly, M.D.; Lothrop, N.; Klimecki, W.; Wilkinson, S.T.; Loh, M. Use of dust fall filters as passive samplers for metal concentrations in air for communities near contaminated mine tailings. Environ. Sci. Process. Impacts 2014, 16, 1275–1281. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Ene, A.; Popescu, I.V.; Stihi, C.; Gheboianu, A.; Pantelica, A.; Petre, C. PIXE analysis of multielemental samples. Rom. J. Phys. 2010, 55, 806–814. [Google Scholar]
  8. Corriveau, M.C.; Jamieson, H.E.; Parsons, M.B.; Campbell, J.L.; Lanzirotti, A. Direct characterization of airborne particles associated with arsenic-rich mine tailings: Particle size, mineralogy and texture. Appl. Geochem. 2011, 26, 1639–1648. [Google Scholar] [CrossRef]
  9. Marple, V.A.; Rubow, K.L.; Behm, S.M. A microorifice uniform deposit impactor (MOUDI): Description, calibration, and use. Aerosol. Sci. Technol. 1991, 14, 434–446. [Google Scholar] [CrossRef]
  10. Csavina, J.; Landázuri, A.; Wonaschütz, A.; Rine, K.; Rheinheimer, P.; Barbaris, B.; Conant, W.; Sáez, A.E.; Betterton, E.A. Metal and metalloid contaminants in atmospheric aerosols from mining operations. Water Air Soil Pollut. 2011, 221, 145–157. [Google Scholar] [CrossRef] [Green Version]
  11. Corona Sánchez, J.E.; González Chávez, M.D.C.A.; Carrillo González, R.; Scheckel, K.; Tapia Maruri, D.; García Cue, J.L. Metal (loid) bioaccessibility of atmospheric particulate matter from mine tailings at Zimapan, Mexico. Environ. Sci. Pollut. Res. 2021, 28, 19458–19472. [Google Scholar] [CrossRef]
  12. Tao, J.; Zhang, L.; Engling, G.; Zhang, R.; Yang, Y.; Cao, J.; Zhu, C.; Wang, Q.; Luo, L. Chemical composition of PM2. 5 in an urban environment in Chengdu, China: Importance of springtime dust storms and biomass burning. Atmos. Res. 2013, 122, 270–283. [Google Scholar] [CrossRef]
  13. Kumari, M.; Saroha, A.K. Performance of various catalysts on treatment of refractory pollutants in industrial wastewater by catalytic wet air oxidation: A review. J. Environ. Manag. 2018, 228, 169–188. [Google Scholar]
  14. Csavina, J.; Field, J.; Félix, O.; Corral-Avitia, A.Y.; Sáez, A.E.; Betterton, E.A. Effect of wind speed and relative humidity on atmospheric dust concentrations in semi-arid climates. Sci. Total Environ. 2014, 487, 82–90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Sánchez-Rodas, D.; de la Campa, A.M.S.; Alsioufi, L. Analytical approaches for arsenic determination in air: A critical review. Anal. Chim. Acta 2015, 898, 1–18. [Google Scholar] [CrossRef]
  16. González-Castanedo, Y.; Moreno, T.; Fernández-Camacho, R.; de la Campa, A.M.S.; Alastuey, A.; Querol, X.; de la Rosa, J. Size distribution and chemical composition of particulate matter stack emissions in and around a copper smelter. Atmos. Environ. 2014, 98, 271–282. [Google Scholar] [CrossRef]
  17. Mpanza, M.; Adam, E.; Moolla, R. Dust deposition impacts at a liquidated gold mine village: Gauteng province in South Africa. Int. J. Environ. Res. Public Health 2020, 17, 4929. [Google Scholar] [CrossRef]
  18. Guney, M.S.; Tepe, Y. Classification and assessment of energy storage systems. Renew. Sustain. Energy Rev. 2017, 75, 1187–1197. [Google Scholar] [CrossRef]
  19. Ettler, V.; Štěpánek, D.; Mihaljevič, M.; Drahota, P.; Jedlicka, R.; Kříbek, B.; Vaněk, A.; Penížek, V.; Sracek, O.; Nyambe, I. Slag dusts from Kabwe (Zambia): Contaminant mineralogy and oral bioaccessibility. Chemosphere 2020, 260, 127642. [Google Scholar] [CrossRef] [PubMed]
  20. Dudu, H.; Çakmak, E.H. Climate change and agriculture: An integrated approach to evaluate economy-wide effects for Turkey. Clim. Dev. 2018, 10, 275–288. [Google Scholar] [CrossRef] [Green Version]
  21. Mwaanga, P.; Silondwa, M.; Kasali, G.; Banda, P.M. Preliminary review of mine air pollution in Zambia. Heliyon 2019, 5, e02485. [Google Scholar] [CrossRef]
  22. Yabe, J.; Nakayama, S.M.; Ikenaka, Y.; Yohannes, Y.B.; Bortey-Sam, N.; Kabalo, A.N.; Ntapisha, J.; Mizukawa, H.; Umemura, T.; Ishizuka, M. Lead and cadmium excretion in feces and urine of children from polluted townships near a lead-zinc mine in Kabwe, Zambia. Chemosphere 2018, 202, 48–55. [Google Scholar] [CrossRef]
  23. Hirner, A.V.; Feldmann, J.; Krupp, E.; Gruemping, R.; Goguel, R.; Cullen, W.R. Metal (loid) organic compounds in geothermal gases and waters. Org. Geochem. 1998, 29, 1765–1778. [Google Scholar] [CrossRef]
  24. Feldmann, J. Volatile Metal Compounds of Biogenic Origin. In Handbook of Elemental Speciation II–Species in the Environment, Food, Medicine and Occupational Health; John Wiley & Sons Ltd.: London, UK, 2005; p. 598. [Google Scholar]
  25. Feldmann, J. Determination of Ni (CO) 4, Fe (CO) 5, Mo (CO) 6, and W (CO) 6 in sewage gas by using cryotrapping gas chromatography inductively coupled plasma mass spectrometry. J. Environ. Monit. 1999, 1, 33–37. [Google Scholar] [CrossRef] [PubMed]
  26. Feldmann, J.; Cullen, W.R. Occurrence of volatile transition metal compounds in landfill gas: Synthesis of molybdenum and tungsten carbonyls in the environment. Environ. Sci. Technol. 1997, 31, 2125–2129. [Google Scholar] [CrossRef]
  27. Bortnikova, S.B.; Silantyeva, N.V.; Zapolsky, A.N.; Yurkevich, N.V.; Saeva, O.P.; Shevko, A.Y.; Shuvaeva, O.V.; Edelev, A.V. Assessment of acid base accounting of mine waste rocks and mobility of potentially toxic elements of the Razdolinsky ore field (Krasnoyarsk Territory). In Bulletin of the Tomsk Polytechnic University, Geo Assets Engineering; Tomsk Polytechnic University: Tomsk, Russia, 2018; Volume 329, no. 12; pp. 55–72. (In Russian) [Google Scholar]
  28. Bortnikova, S.; Yurkevich, N.; Devyatova, A.; Saeva, O.; Shuvaeva, O.; Makas, A.; Troshkov, M.; Abrosimova, N.; Kirillov, M.; Korneeva, T.; et al. Mechanisms of low-temperature vapor-gas streams formation from sulfide mine waste. Sci. Total Environ. 2019, 647, 411–419. [Google Scholar] [CrossRef] [PubMed]
  29. Makas, A.L.; Troshkov, M.L. Field gas chromatography–mass spectrometry for fast analysis. J. Chromatogr. B 2004, 800, 55–61. [Google Scholar] [CrossRef]
  30. Yurkevich, N.; Bortnikova, S.; Abrosimova, N.; Makas, A.; Olenchenko, V.; Yurkevich, N.; Edelev, A.; Saeva, O.; Shevko, A. Sulfur and nitrogen gases in the vapor streams from ore cyanidation wastes at a sharply continental climate, Western Siberia, Russia. Water Air Soil Pollut. 2019, 230, 1–17. [Google Scholar] [CrossRef]
  31. Salthammer, T. Very volatile organic compounds: An understudied class of indoor air pollutants. Indoor Air 2016, 26, 25–38. [Google Scholar] [CrossRef]
  32. Platonov, I.A.; Rodinkov, O.V.; Gorbacheva, A.R.; Moskvin, L.N.; Kolesnichenko, I.N. Method for preparing standard gas mixtures and a device for its implementation. J. Anal. Chem. 2011, 72, 2410678. [Google Scholar]
Figure 1. Photograph and scheme of the experiment setup.
Figure 1. Photograph and scheme of the experiment setup.
Applsci 12 09942 g001
Figure 2. Experiment data on the capture coefficient with a sample volume of 0.5 L, given as a function of the chromatographic retention index.
Figure 2. Experiment data on the capture coefficient with a sample volume of 0.5 L, given as a function of the chromatographic retention index.
Applsci 12 09942 g002
Figure 3. Fragment of the recorder chart of aerosol particles bigger than 3 nm in the air above the sample and in the lab.
Figure 3. Fragment of the recorder chart of aerosol particles bigger than 3 nm in the air above the sample and in the lab.
Applsci 12 09942 g003
Table 1. Metrological parameters of capillary electrophoresis and ICP-MS methods (SO42–K in mg/L, Fe–Li in µg/L).
Table 1. Metrological parameters of capillary electrophoresis and ICP-MS methods (SO42–K in mg/L, Fe–Li in µg/L).
ComponentsMDLMLOQElementsMDLMLOQ
SO42−0.100.30Pb0.050.17
Cl0.100.30Cd0.040.13
PO43−0.100.30Ag0.050.17
HCOO (formate)0.100.30Co0.050.17
Ca0.050.17Ni0.140.47
Mg0.010.03As0.050.17
Na0.010.03Sb0.050.17
K0.010.03Se0.200.67
Fe0.501.7Ba0.030.10
Mn0.080.27Sr0.010.03
Al0.110.37Ti0.040.13
Zn0.150.50V0.040.13
Cu0.220.73Li0.110.37
Table 2. Composition of the tailings sample for the experiment (SiO2–Ssulfide in weight %, Cu–Li in mg∙kg−1).
Table 2. Composition of the tailings sample for the experiment (SiO2–Ssulfide in weight %, Cu–Li in mg∙kg−1).
ComponentsContentElementsContent
SiO225Cu290
TiO20.52Zn540
Al2O30.72Pb1800
Fe2O322Cd0.36
MnO0.004Co4.2
MgO0.012As650
CaO0.24Sb220
Na2O0.18Se140
K2O0.44Ag22
P2O50.031Rb4.5
BaO16Sr210
LOI6.6Ti730
Ssulfate3.2V6.5
Ssulfide24Li4.5
Note: LOI means loss of ignition.
Table 3. Physical-chemical parameters (redox potential Eh in mV) and composition of the aqueous extract from the sample (SO42–Pb in mg/L, Cd–Li in µg/L).
Table 3. Physical-chemical parameters (redox potential Eh in mV) and composition of the aqueous extract from the sample (SO42–Pb in mg/L, Cd–Li in µg/L).
ElementContentElementContent
pH2.7Pb0.43
Eh670Cd2.3
SO42−2600Ag0.81
Cl100Co6.2
PO43−0.92Ni18
Ca84As1700
Mg4.2Sb12
Na1.5Se280
K0.57Ba71
Fe530Sr110
Mn0.13Ti85
Al12V22
Zn0.20Li15
Cu0.62
Table 4. Composition of the condensate collected in a laboratory experiment (SO42–K in mg/L, Fe–Li in µg/L).
Table 4. Composition of the condensate collected in a laboratory experiment (SO42–K in mg/L, Fe–Li in µg/L).
ComponentsContentElementsContent
SO42−12Pb45
Cl2.4Cd11
PO43−0.35Ag0.10
HCOO (formate)0.55Co0.4
Ca4.3Ni17
Mg1.2As4.5
Na1.8Sb3.6
K1.6Se9.9
Fe25Ba15
Mn6.0Sr31
Al15Ti0.30
Zn235V0.06
Cu44Li3.1
Table 5. Concentrations of the gases over the substance of the test sample under stationary conditions and in the experiment.
Table 5. Concentrations of the gases over the substance of the test sample under stationary conditions and in the experiment.
CompoundFormulaConcentration, mkg/m3
Without PurgingPurge
Carbon disulfideCS210012
Dimethyl sulfideC2H6S1.5traces
Carbo selenideCSSe240.35
Dimethyl selenideC2H6Se1400.62
Disulfide, dimethylC2H6S21.6traces
Dimethyl thioselenideC2H6SSetraces-
Thiocyanic acid, methyl esterC2H3NS3.8-
Dimethyl diselenideC2H6Se2traces-
Dimethyl trisulfideC2H6S30.7-
S6, S7, S8 0.50.4
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Bortnikova, S.B.; Yurkevich, N.V.; Volynkin, S.S.; Kozlov, A.S.; Makas, A.L. Evidence of Volatility Metals and Metalloids at Environment Conditions. Appl. Sci. 2022, 12, 9942. https://doi.org/10.3390/app12199942

AMA Style

Bortnikova SB, Yurkevich NV, Volynkin SS, Kozlov AS, Makas AL. Evidence of Volatility Metals and Metalloids at Environment Conditions. Applied Sciences. 2022; 12(19):9942. https://doi.org/10.3390/app12199942

Chicago/Turabian Style

Bortnikova, Svetlana B., Nataliya V. Yurkevich, Sergey S. Volynkin, Aleksander S. Kozlov, and Alexey L. Makas. 2022. "Evidence of Volatility Metals and Metalloids at Environment Conditions" Applied Sciences 12, no. 19: 9942. https://doi.org/10.3390/app12199942

APA Style

Bortnikova, S. B., Yurkevich, N. V., Volynkin, S. S., Kozlov, A. S., & Makas, A. L. (2022). Evidence of Volatility Metals and Metalloids at Environment Conditions. Applied Sciences, 12(19), 9942. https://doi.org/10.3390/app12199942

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop