Next Article in Journal
Statistical Dynamics and Subgrid Modelling of Turbulence: From Isotropic to Inhomogeneous
Previous Article in Journal
Urban Climate Dynamics: Analyzing the Impact of Green Cover and Air Pollution on Land Surface Temperature—A Comparative Study Across Chicago, San Francisco, and Phoenix, USA
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Chemical Composition of PM10 in a Classroom near the Copper Smelter in Bor, Serbia

by
Bojan Radović
1,
Viša Tasić
1,*,
Renata Kovačević
1,
Tatjana Apostolovski-Trujić
1,
Dragan Manojlović
2,3,
Mira Cocić
4 and
Tamara Urošević
1
1
Mining and Metallurgy Institute Bor, Alberta Ajnštajna 1, 19210 Bor, Serbia
2
Faculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia
3
Department for Ecology and Chemical Technology, South Ural State University, Lenin Prospect 76, 454080 Chelyabinsk, Russia
4
Technical Faculty in Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, Serbia
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(8), 920; https://doi.org/10.3390/atmos15080920 (registering DOI)
Submission received: 4 June 2024 / Revised: 14 July 2024 / Accepted: 25 July 2024 / Published: 31 July 2024
(This article belongs to the Section Aerosols)

Abstract

:
An analysis was conducted on the influence of advancements in smelting technology at the copper smelter in Bor, Serbia, and seasonal changes on the level and chemical composition of PM10 inside and outside a classroom at the Technical Faculty in Bor in 2015 and 2019. The results of chemical analyses revealed that the average level of arsenic in PM10 within the classroom reached 11.9 ng/m3, nearly double the annual target value. In comparison, the average level of arsenic (As) in PM10 in ambient air stood at 15 ng/m3. A notable enrichment factor was observed for elements present in copper concentrates (Se > Ag > Bi > Pb > Cd > As > Sb > S > Cu > Sn > Zn) in both the classroom and outdoor air, underscoring their predominantly anthropogenic origin. Higher concentrations of As in PM10 were recorded during the non-heating season and the operation of the copper smelter with outdated smelting technology (2015). These findings hold significant implications for health protection for all citizens in the investigated area surrounding the Technical Faculty in Bor. The study highlights the need for additional measures to reduce As content in PM10 in ambient air and prevent the infiltration of suspended particles from outdoor air into classrooms.

1. Introduction

The city of Bor is situated in the southeastern region of the Republic of Serbia, close to the borders with Bulgaria and Romania. It occupies an area of 856 km2 where 41,280 inhabitants live (according to the census of 2022), a density of 48 inhabitants per km2. At the beginning of the last century, in 1903, a copper ore deposit was discovered in Bor, meaning that the city of Bor has been known for the excavation and processing of copper ore and noble metals for over a century. Initially, it was underground exploitation, although later excavations were carried out at surface mines near Bor. After World War II, the mine was nationalized, and a new enterprise was named the Mining and Smelting Basin Bor—RTB Bor. During the 1960s and 1970s, RTB Bor production exceeded 150,000 tons of cathode copper annually. During that period, metallurgical and industrial capacities were being built, new mines were being opened, and apartments, railways, roads, and other infrastructure objects were being constructed. The industrial endeavors within the confines of Bor have not been without consequences for the local environment, leaving discernible negative imprints on the air, water, and soil quality in the vicinity. Moreover, a heightened awareness about the potential health repercussions stemming from the widespread pollution has taken root. The airborne particulate matter (PM) and sulfur dioxide (SO2) contamination in Bor are predominantly sourced from the release of fugitive dust from open pits, ore waste heaps, flotation waste heaps, and point sources within the copper smelter. These cumulative emissions exacerbate environmental contamination, with a heavy emphasis on PM and SO2 [1,2,3,4,5,6,7].
The copper ore subjected to smelting in the copper smelter in Bor originated from nearby open pits and is primarily composed of chalcopyrite-pyrite minerals, enriched with As compounds such as FeAsS, Cu3AsS4, CuFeS2, Cu5FeS4, and Cu2S. The subsequent oxidation, roasting, and smelting processes precipitate a surge in heavy metal oxide concentrations and the release of SO2 gas, thereby contributing to the environmental burden [1].
The outdated technology of copper production persisted in the smelter until 2015, inevitably intensifying the pollution rates with elevated concentrations of SO2 and PM [7]. In response, the Serbian Government provided financial support for building a modern copper smelting facility, which commenced full-scale operations in 2016. This transformation aimed to reduce SO2, PM, and other pollutant emissions associated with copper smelting waste gases.
The novel smelting approach harnessed flash smelting technology [8], reshaping the intensity and composition of waste gas emissions from the smelting process. Despite these proactive efforts, air quality assessments between 2016 and 2020 showed an increased concentration of As within PM10 [5]. The air quality in Bor was significantly exacerbated during 2019–2020, attributed to shifts in ownership of the metallurgical complex.
Notably in 2018, ZiJin, a globally prominent mining conglomerate specializing in the production of copper and precious metals [9], emerged as a strategic partner for RTB Bor, acquiring a controlling stake. This alliance gave rise to the establishment of the Serbia ZiJin Bor Copper doo company, in which ZiJin held a commanding 63% share, while the Republic of Serbia retained a 37% stake.
The aerosols embedded within metals and metalloids, discharged from copper smelting plumes, manifest as a formidable threat to human well-being [10,11,12]. Extensive research spanning decades has culminated in heightened awareness regarding the toxicity of trace elements, prompting regulatory initiatives in both the Republic of Serbia and European Union nations. The scrutiny is centered on elements such as As, cadmium (Cd), lead (Pb), and nickel (Ni), whose PM10 concentration levels in ambient air are subject to regulatory oversight.
Numerous studies have underscored a connection between particulate air pollution and mortality across all age groups [13,14,15,16]. In response, items of national legislation have been enacted to safeguard human health, mandating an annual limit of 40 µg/m3 for PM10, a ceiling of 500 ng/m3 for Pb in PM10, and annual target values of 5 ng/m3 for Cd, 20 ng/m3 for Ni, and 6 ng/m3 for As content in PM10 [17].
The copper smelter waste gases are enriched with Cu and Fe oxides and other elements, such as As, Sb, Pb, and Zn [18,19]. Typical concentrations of As range from 1–10 ng/m3 in rural areas, and up to 30 ng/m3 in uncontaminated urban areas [20]. Substances such as inorganic As, Cd and Cd compounds, and Ni compounds are classified as carcinogens to humans (group 1) [21].
Average Pb concentrations in the ambient air are usually below 0.15 µg/m3 at rural sites. In most European cities, Pb levels in ambient air typically range between 0.15 and 0.5 µg/m3. In rural areas, typical Cd levels in the airborne aerosol are 0.1–0.4 ng/m3 and up to 20 ng/m3 at industrial sites [22]. In rural areas, typical Ni levels in the airborne aerosol are 0.4–2 ng/m3 and up to 50 ng/m3 near industrial sites. Ni compounds are considered human carcinogens if exposed through inhalation [22].
Good air quality in educational buildings is necessary since children and students spend a large part of their time in classrooms [23]. The increase in indoor PM10 levels can be attributed to internal and external sources. Internal sources include the generation of particles (related to combustion processes, use of sprays, and other household items) and their resuspension during intense movement and other activities in the observed enclosed space [23].
The aim of this work is an analysis of the influence of changes in smelting technology in the copper smelter in Bor, and seasonal changes on the level and chemical composition of PM10 particles in a classroom at the Technical Faculty in Bor, Serbia.
Due to the lack of sampling equipment and financial resources for sample analysis, we sampled and analyzed the PM10 fraction for only two years: 2015 (old smelting technology in the copper smelter) and 2019 (new smelting technology in the copper smelter). The period from 2020 until 2024 was not analyzed because of online classes during the COVID-19 pandemic, and the copper smelter reconstruction/testing period from April 2022 to April 2024.
The results of chemical analyses revealed that the average content of As in PM10 within the classroom reached 11.9 ng/m3, nearly double the annual target value. In comparison, the average content of As in PM10 in ambient air stood at 15 ng/m3.
This study highlights the urgent need for additional measures to reduce As content in PM10 in ambient air and prevent the infiltration of suspended particles from outdoor air into the classroom.

2. Materials and Methods

2.1. Sampling Location

The Technical Faculty in Bor (TF) is part of the University of Belgrade, the oldest, biggest, and the most prestigious state university in the Republic of Serbia. The number of students who have graduated since the establishment of the faculty is 2850, 20 students have completed specialist studies, 180 have completed master’s studies, and 119 students have defended doctoral theses [24]. Positioned approximately 1 km northwest of the copper smelter (as shown in Figure 1), the TF comprises several edifices.
The PM10 mass concentration measurements encompassed the measurement campaigns in 2015, when the copper smelter used old smelting technology, and in 2019, when the copper smelter operated with new smelting technology. The measurements span both the heating (15 October to 15 April) and non-heating seasons (15 April to 15 October). The selected classroom typically accommodates up to 20 students during lectures between 8 AM and 6 PM. The classroom’s 50 m3 space boasts a vinyl-covered floor, lacks an air conditioning system, and features windows totaling approximately 4 m2. During the non-heating season, windows in the classroom remained mostly open or partially ajar during working hours.

2.2. Sampling Equipment and Methods for Chemical Analysis

The sampling campaigns were carried out in 2015 and 2019. The PM samples were collected by using SVEN/LECKEL LVS3/6RV reference gravimetric samplers [25] with an airflow rate of 55 m3/24 h and PM10 sampling heads. A reference flow meter verified the flow rates of all sampling instruments before and after each measurement campaign. Each measurement campaign lasts a minimum of 14 days and a maximum of 30 days. A total of 82 indoor and 83 outdoor PM10 samples were collected during sampling campaigns.
One PM10 sampler was placed in the middle of the classroom, while another occupied the first-floor balcony of the same edifice. Quartz filters of the Whatman QM-A 47 mm variant facilitated PM10 sample collection. Samples were collected daily (from 9 AM to 9 AM on the next day). The weight of the filters was measured according to the procedure prescribed by standard SRPS EN12341:2015 [26]. The EN 14902:2005 [27] methodology was adhered to in preparing filters for chemical analysis. Inductively Coupled Plasma Mass Spectrometry—ICP MS (Agilent model 7700)—was applied for chemical element level determination in PM10 samples. In order to control the quality and verify the dissolution and analysis procedure, the standard reference material, NIST 1648a [28], was analyzed in the same way as the PM samples, with recovery rates spanning 75 to 125% for all presented elements.

3. Results and Discussion

3.1. PM10 Levels, Chemical Composition, and I/O Ratios

Table 1 shows the average concentrations of PM10, the chemical composition, and indoor/outdoor (I/O) ratios for the entire observation period. Data outlined in Table 1 highlight that average PM10 concentrations within the classroom and ambient air remained compliant with prescribed annual limits (40 µg/m3). Good matching is observed with prior periods’ PM10 levels in ambient air [1].
Serbian Environmental Protection Agency (SEPA) annual reports presented similar values for Bor’s PM10 levels in ambient air [29]. For example, in 2019, the TP site (less than 1 km away from the TF site) averaged annual PM10 levels of 36 µg/m3.
Chemical element levels within PM10 are closely aligned with those near Spain’s Huelva copper smelter [30,31,32] (I/O ratios of PM10 element concentrations in Table 1 exhibit minor deviations from 1.0, indicating negligible indoor sources and attributing their presence primarily to external infiltration).
Within the scope of elements with regulated content thresholds in PM10, As concentrations exceeded the annual target (6 ng/m3) both indoors (11.9 ng/m3) and outdoors (15.0 ng/m3), as depicted in Figure 2. This trend persists, reflecting heightened levels indoors and outdoors [5].
As expected, As, Cd, Cu, Zn, S, Sb, and Pb levels in PM10 were elevated because of their presence in the copper concentrates processed in the copper smelter in Bor. High concentrations of Se, Ag, and Bi in PM10 were also determined in both indoor and outdoor environments.

3.2. Enrichment Factor

To determine the anthropogenic and crustal origin of elements in aerosols, the enrichment factor is widely used [4]. As a common reference element for crustal particles in enrichment factor (EF) calculations, we used Mn because its anthropogenic sources in the studied area are negligible. The EF is defined as:
EF = X Mn air X Mn crust
where (X/Mn)air and (X/Mn)crust refer to the ratio of the concentration of element X to that of Mn in the air and in the average crustal material, respectively.
Based on the EF values, the elements can be grouped as follows: very enriched (EF > 100), medium-enriched (10 < EF < 100), and low-enriched (EF < 10) [33]. The EF calculated from the filter samples collected around four of the biggest smelters in Chile showed strong enrichment of Pb, As, Cu, and Ni [34]. The EF calculated for selected elements in Bor is shown in Table 2.
The data in Table 2 clearly show that most of the elements that are part of the copper concentrate processed in the copper smelter (Se > Ag > Bi > Pb > Cd > As > Sb > S > Cu > Sn > Zn) show very high EF values, which indicates the predominantly anthropogenic origin of those elements.
In contrast, the elements originating from the earth’s crust (Ca, K, Na, Mg, Mn, and Fe) have EF values less than 10. This indicates the background level for those elements around the TF site.
In addition, based on the data from Table 2, seasonal changes in EF can be observed, and this can be best demonstrated when comparing the I/O ratios of EF in the non-heating and heating seasons. It is noticeable that for most of the elements, the EFs and the EF I/O ratios are higher in the non-heating season compared to the values obtained in the heating season.
The changes in EF are influenced by two different phenomena. First, the changes are influenced by meteorological conditions, such as changes in wind speed and direction in the non-heating season and heating season. Namely, in the heating season, the winds that blow mostly from the north/northwest direction contribute to reducing PM pollution at the TF site. In contrast, in the non-heating period, the frequency and speed of winds from these directions are lower [1].
Additionally, the natural ventilation of the classroom is better during the non-heating season than during the heating season. During teaching hours in the non-heating season, the windows are mostly open or half-open, resulting in a higher infiltration of external PM10 pollution into the classroom. In contrast, during the heating season, the windows predominantly remain closed, limiting the infiltration of external PM10 pollution into the classroom.

3.3. The Impact of Changes in the Copper Smelting Technology on the Level of PM10 and Content of Chemical Elements in PM10 at the TF Site

During the period of using old smelting technology in the copper smelter in Bor (2015), the average PM10 levels in the classroom and ambient air at the TF site were below the prescribed annual limit, as indicated in Table 3.
The I/O ratios of concentrations of chemical elements in PM10, displayed in Table 3, demonstrate variations from element to element. However, except for Co, Sn, and Bi, there are no significant deviations in I/O ratios from 1.0.
This implies that there are no notable indoor sources, except for particle resuspension, and the presence of chemical elements in the classroom primarily originates from infiltration from the external environment.
Figure 2 illustrates that out of the elements Pb, Cd, Ni, and As, which have prescribed annual limits or target values for their concentrations in PM10, only As concentrations exceeded the annual target value both indoors (15.5 ng/m3) and in outdoor air (15.7 ng/m3).
The elevated concentrations of elements such as As, Cd, Cu, Zn, S, Sb, and Pb in PM10 result from their presence in the copper concentrates processed in the copper smelter in Bor. Furthermore, the inadequate treatment of waste gases generated in the precious metals extraction plant (Zlatara), a part of the copper smelter facilities, contributes to the heightened concentrations of Se and Ag in PM10 [35].
During the period of applying new smelting technology (2019) in the copper smelter in Bor, the average PM10 levels in the classroom and ambient air at the TF site were below the prescribed annual limit, as presented in Table 4.
The I/O ratios of concentrations of chemical elements in PM10, displayed in Table 4, demonstrate variations from element to element. However, except for Co, Mn, and Pb, there are no significant deviations in I/O ratios from 1.0. This implies that there are no notable indoor sources, except particle resuspension, and the presence of chemical elements in the classroom primarily originates from infiltration from the external environment.
Figure 2 illustrates that out of the elements Pb, Cd, Ni, and As, which have prescribed annual limits or target values for their concentrations in PM10, only the average concentration of As exceeded the annual target value both indoors (9.3 ng/m3) and in outdoor air (14.8 ng/m3).
The concentrations of elements such as As, Cd, Cu, Zn, S, Sb, and Pb in PM10 were elevated due to their presence in the copper concentrates processed in the copper smelter in Bor.
As previously explained, during the operation of the old copper smelter, high levels of Se and Ag in PM10 mainly occurred due to inadequate treatment of waste gases generated in the precious metals extraction plant. The reconstruction of this plant was not included in the old copper smelter reconstruction, resulting in the emissions of waste gases remaining the same as in the previous period.
Based on the data presented in Table 3 and Table 4, it can be concluded that the concentrations of most chemical elements found in the copper concentrates (such as As, Cd, Zn, Cu, S, Se, Ag, and Ba) decreased during the operation of the copper smelter with new smelting technology, compared to their concentrations in PM10 at the TF when the copper smelter operated with old smelting technology.
Additionally, it can be asserted that during the operation of the copper smelter with new smelting technology, there was a significant reduction in SO2 emissions compared to the period before 2016 [5,6].

3.4. Seasonal Variations of PM10 Levels and Content of Chemical Elements in PM10 at the TF Site

Table 5 and Table 6 present the average concentrations of PM10, their chemical composition, and I/O ratios during both non-heating and heating periods over the entire measurement period.
Table 5 shows the average ratio of concentrations of chemical elements during the non-heating period in the classroom and outdoor air (I/O), revealing that most of the chemical elements in PM10 indoors predominantly originate from outdoor air. Elevated levels of certain elements (Pb, Ni, Fe, K, Se, and Ba) in the classroom, compared to outdoor air, result from the resuspension of particles caused by student activities.
Among the chemical elements with prescribed limit and target values for annual PM10 content, only As exceeds the target value, by an average of 3.1 times indoors and 3.2 times outdoors, as illustrated in Figure 2.
Similarly, Table 6 displays the I/O ratios during the heating period, indicating that the majority of chemical elements in PM10 indoors predominantly originate from outdoor air.
Elevated levels of specific elements (Mn, Co, Rb, and Sn) in the classroom, compared to outdoor air, are attributed to particle resuspension caused by student activities. Among the chemical elements with prescribed limit and target values for annual PM10 content, only As surpasses the target value, by an average of 1.2 times indoors and 1.9 times outdoors, as shown in Figure 2.
Comparing the concentrations of elements found in the copper concentrate (As, Cd, Pb, Cu, Zn, S, Cr, Se, and Ag) in PM10 within the classroom during the non-heating season to those in the heating season, higher levels were identified, as indicated by the data in Table 5 and Table 6. A parallel observation can be drawn by examining the average concentrations of these elements in PM10 in outdoor air; during the observed period, their presence in PM10 in outdoor air was greater in the non-heating season than in the heating season.
As discussed earlier (in Section 3.2 concerning EF), two significant factors influence the seasonal variations in chemical element concentrations in PM10 at the TF site. The alterations in PM10 levels stem from shifts in meteorological conditions. Specifically, during the heating season, there is a higher frequency of winds from the west and northwest compared to the non-heating season [1]. This fosters aeration and diminishes the likelihood of particle resuspension from the soil during the heating season. Additionally, the natural ventilation pattern in the classroom undergoes a seasonal shift, transitioning from open windows during classes in the non-heating season to closed or nearly closed windows during the heating season.

3.5. Correlations between the Chemical Elements Determined in PM10 inside and outside the Classroom at the TF Site

The investigation into the relationships between average concentrations of chemical elements determined in PM10 at the TF involved correlation analysis over the entire observation period. This analysis was conducted separately for the non-heating and heating periods, and the resulting Pearson’s correlation coefficients (r) are presented in Table 7 for the non-heating period and Table 8 for the heating period.
Analyzing the data in Table 7 reveals a general observation that the correlations between observed chemical elements in PM10 during the non-heating period in the ambient air at TF were generally more robust compared to those between the same elements in the classroom, with a few exceptions. Furthermore, the correlations between concentrations of chemical elements present in the copper concentrate (As, Cd, Pb, Cu, Zn, S, and Fe) in the outdoor air at the TF were mostly strong (0.8 > r > 0.6) to moderate (0.6 > r > 0.4) and positive. In contrast, in the classroom, these correlations were mostly moderate and positive.
The notable disparity in correlation coefficient values between indoor and outdoor air can be attributed to the varying degrees of infiltration of certain elements from the external environment and the different sedimentation rates of these elements [36,37].
Analyzing the data presented in Table 8 leads to a general conclusion that the correlations between observed elements in PM10 during heating periods in the ambient air at the TF were, in most cases, more robust compared to the correlations within the classroom, with a few exceptions. Additionally, the correlations between concentrations of elements present in the copper concentrate (As, Cd, Pb, Cu, Zn, S, and Fe) in the outdoor air at the TF were predominantly strong to moderate and positive, whereas in the classroom, these correlations were mostly moderate and positive.
The primary explanation for this pattern is the reduced ventilation of the classroom during the heating season, which significantly diminishes the infiltration of external particulate pollution into the interior space. Several findings regarding the correlations of chemical elements in PM10 in outdoor air (shown in Table 7 and Table 8) align with the results obtained for the TP site (located less than 1 km from the TF site) in previously published papers [3,4].

4. Conclusions

This study is motivated by the imperative to spotlight air pollution’s significance through suspended particles in educational institutions across the Republic of Serbia and the latent health ramifications. Our work delves into the impact of smelting technology alterations and seasonal changes in Bor’s copper smelter on PM10 levels and composition within a chosen classroom at the TF.
Average PM10 levels indoors and outdoors at the TF remained beneath the national annual PM10 limit (40 µg/m3). However, As levels exceeded the national annual target both indoors and outdoors, nearing double the target inside and 2.5 times outside. Chemical elements originating from the copper concentrate exhibited substantial enrichment factors, affirming their anthropogenic origins.
Heightened As concentrations were noted in the non-heating period, particularly when the old smelting technology was used in the copper smelter (2015). Over the entirety of the observed period, average concentrations of Pb, Cd, and Ni in PM10 in the classroom and ambient air were below the prescribed limit and target values.
Correlation analysis unveiled robust positive correlations between chemical elements in PM10 in outdoor air during heating and non-heating periods, surpassing those observed indoors. The presented results accentuate the need to reduce As content in PM10 by constant waste gas emission control in the copper smelter and additional measures for particle infiltration prevention.
The presented results should contribute to safeguarding the health of students and citizens residing near the Technical Faculty in Bor.

Author Contributions

Conceptualization, B.R., V.T. and D.M.; methodology, R.K.; validation, T.A.-T. and T.U.; formal analysis, B.R.; investigation, B.R., V.T., T.A.-T., M.C. and T.U.; resources, R.K.; data curation, V.T.; writing—original draft preparation, B.R., V.T. and D.M.; writing—review and editing, B.R., V.T., T.A.-T., M.C. and T.U.; visualization, M.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Science, Technological Development, and Innovation of the Republic of Serbia, Grant No. 451-03-66/2024-03/ 200052, and 451-03-47/2023-01/ 200131. and by the European Union’s Horizon Europe Research and Innovation program under grant agreement No. 101060170-WeBaSOOP, “Research Reinforcing in the Western Balkans’ in Offline and Online Monitoring and Source Identification of Atmospheric Particles”.

Informed Consent Statement

Not applicable.

Data Availability Statement

Dataset available on request from the authors due to privacy.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Tasić, V.; Milošević, N.; Kovačević, R.; Petrović, N. The analysis of air pollution caused by particle matter emission from the copper smelter complex Bor (Serbia). Chem. Ind. Chem. Eng. Q. 2010, 16, 219–228. [Google Scholar] [CrossRef]
  2. Serbula, S.; Kalinovic, T.; Kalinovic, J.; Ilic, A. Exceedance of air quality standards resulting from pyro-metallurgical reduction of copper: A case study, Bor (Eastern Serbia). Environ. Earth Sci. 2013, 68, 1989–1998. [Google Scholar] [CrossRef]
  3. Serbula, S.; Ilic, A.; Kalinovic, J.; Kalinovic, T.; Petrović, N. Assessment of air pollution originating from copper smelter in Bor (Serbia). Environ. Earth Sci. 2014, 71, 1651–1661. [Google Scholar] [CrossRef]
  4. Tasić, V.; Kovačević, R.; Maluckov, B.; Apostolovski-Trujić, T.; Cocić, M.; Matić, B.; Šteharnik, M. The content of As and heavy metals in TSP and PM10 near copper smelter in Bor, Serbia. Water Air Soil Pollut. 2017, 228, 230. [Google Scholar] [CrossRef]
  5. Serbula, S.; Milosavljevic, J.; Kalinovic, J.; Kalinovic, T.; Radojevic, A.; Apostolovski- Trujic, T.; Tasic, V. Arsenic and SO2 hotspot in South-Eastern Europe: An overview of the air quality after the implementation of the flash smelting technology for copper production. Sci. Total Environ. 2021, 777, 145981. [Google Scholar] [CrossRef] [PubMed]
  6. Živković, Ž.; Panić, M.; Fedajev, A.; Veličković, M. The Challenges of Increasing the Copper Smelter Capacity on Ambient Air Quality in Bor (Serbia). Water Air Soil Pollut. 2023, 234, 82. [Google Scholar] [CrossRef]
  7. Dimitrijević, M.; Kostov, A.; Tasić, V.; Milošević, N. Influence of pyrometallurgical copper production on the environment. J. Hazard. Mater. 2009, 164, 892–899. [Google Scholar] [CrossRef] [PubMed]
  8. Kojo, I.V.; Jokilaakso, A.; Hanniala, P. Flash smelting and converting furnaces: A 50 year retrospect. JOM 2000, 52, 57–61. [Google Scholar] [CrossRef]
  9. Home-ZiJin Minning Group Co. Ltd. Available online: https://www.zijinmining.com (accessed on 15 May 2024).
  10. Kovačević, R.; Jovašević-Stojanović, M.; Tasić, V.; Milošević, N.; Petrović, N.; Stanković, S.; Matić-Besarabić, S. Preliminary analysis of levels of arsenic and other metallic elements in PM10 sampled near copper smelter Bor (Serbia). Chem. Ind. Chem. Eng. Q. 2010, 16, 269–279. [Google Scholar] [CrossRef]
  11. Pekey, B.; Bozkurt, Z.B.; Pekey, H.; Doğan, G.; Zararsız, A.; Efe, N.; Tuncel, G. Indoor/outdoor concentrations and elemental composition of PM10/PM2.5 in urban/industrial areas of Kocaeli City, Turkey. Indoor Air 2010, 20, 112–125. [Google Scholar] [CrossRef]
  12. Gonzales-Castanedo, J.; Moreno, T.; Fernandez-Camacho, R.; Sanchez de la Campa, A.; 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]
  13. Anderson, H.R.; Bremner, S.A.; Atkinson, R.W.; Harrison, R.M.; Walters, S. Particulate matter and daily mortality and hospital admissions in the West Midlands conurbation of the United Kingdom: Associations with fine and coarse particles, black smoke and sulphate. Occup. Environ. Med. 2001, 58, 504–510. [Google Scholar] [CrossRef] [PubMed]
  14. Pope, C.A.; Burnett, R.T.; Thun, M.J.; Calle, E.E.; Krewski, D.; Kazuhiko, I. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. J. Am. Med. Assoc. 2002, 287, 1132–1141. [Google Scholar] [CrossRef] [PubMed]
  15. Pope, C.A.; Rodermund, D.L.; Gee, M.M. Mortality Effects of a Copper Smelter Strike and Reduced Ambient Sulfate Particulate Matter. Environ. Health Perspect. 2007, 115, 679–683. [Google Scholar] [CrossRef] [PubMed]
  16. Atkinson, R.W.; Fuller, G.W.; Anderson, H.R.; Harrison, R.M.; Armstrong, B. Urban ambient particle metrics and health: A time series analysis. Epidemiology 2010, 21, 501–511. [Google Scholar] [CrossRef] [PubMed]
  17. Regulation for the Conditions and Requirements for Monitoring air Quality, Official Gazette of RS. Available online: https://www.paragraf.rs/propisi/uredba-uslovima-monitoring-zahtevima-kvaliteta-vazduha.html (accessed on 15 May 2024).
  18. Gonzales-Castanedo, J.; Sanchez-Rodas, D.; Fernandez-Camacho, R.; Sanchez de la Campa, A.M.; Pandolfi, M.; Alastuey, A.; Querol, X.; de la Rosa, J.D. Arsenic species in atmospheric particulate matter as tracer of the air quality of Donana Natural Park (SW Spain). Chemosphere 2015, 119, 1296–1303. [Google Scholar] [CrossRef] [PubMed]
  19. Fernandez-Camacho, R.; Rodríguez, S.; de la Rosa, J.D.; Sanchez de la Campa, A.M.; Alastuey, A.; Querol, X.; Gonzalez-Castanedo, Y.; Garcia-Orellana, I.; Nava, S. Ultrafine particle and fine trace metal (As, Cd, Cu, Pb and Zn) pollution episodes induced by industrial emissions in Huelva, SW Spain. Atmos. Environ. 2012, 61, 507–517. [Google Scholar] [CrossRef]
  20. Air Quality Guidelines for Europe, Second ed., WHO Regional Publications, Regional Office for Europe, Copenhagen, Denmark. Available online: https://www.who.int/publications/i/item/9789289013581 (accessed on 15 May 2024).
  21. International Agency for Research on Cancer, List of Classifications. Available online: https://monographs.iarc.who.int/agents-classified-by-the-iarc/ (accessed on 15 May 2024).
  22. Air Pollution by As, Cd and Ni Compounds, Position Paper. Final Version, October 2000. Available online: https://www.aces.su.se/reflab/wp-content/uploads/2016/11/as_cd_ni_position_paper.pdf (accessed on 15 May 2024).
  23. Pallarés, S.; Gómez, E.T.; Martínez, A.; Jordán, M.M. The relationship between indoor and outdoor levels of PM10 and its chemical composition at schools in a coastal region in Spain. Heliyon 2019, 5, E02270. [Google Scholar] [CrossRef] [PubMed]
  24. TF Bor. Available online: https://www.tfbor.bg.ac.rs/osnovni-podaci (accessed on 15 May 2024). (In Serbian).
  25. LVS3/6RV. Available online: https://www.leckel.de/devices/lvs3b/ (accessed on 15 May 2024).
  26. SRPS EN12341:2015; Ambient Air—Standard Gravimetric Measurement Method for the Determination of the PM10 or PM2.5 Mass Concentration of Suspended Particulate Matter. Institute for Standardization of Serbia: Belgrade. Available online: https://iss.rs/en/project/show/iss:proj:49389 (accessed on 15 May 2024).
  27. Ambient Air Quality—Standard Method for the Measurement of Pb, Cd, As and Ni in PM10 Fraction of Suspended Particulate Matter. Available online: https://standards.iteh.ai/catalog/standards/cen/374ad39c-7a3c-4eb4-9421-5ff2bec3f12e/en-14902-2005 (accessed on 15 May 2024).
  28. Standard Reference Material 1648a—Urban Particulate Matter. Available online: https://www-s.nist.gov/srmors/view_detail.cfm?srm=1648A (accessed on 15 May 2024).
  29. State of Environment in the Republic of Serbia during 2019. Available online: http://www.sepa.gov.rs/download/izv/Vazduh_2019.pdf (accessed on 15 May 2024).
  30. Sanchez de la Campa, A.M.; De la Rosa, J.D.; Sanchez Rodas, D.; Oliveira, V.; Querol, X.; Alastuey, A.; Gomez Ariza, J.L. Arsenic speciation study of PM2.5 in an urban area near a copper smelter. Atmos. Environ. 2008, 42, 6487–6495. [Google Scholar] [CrossRef]
  31. Sanchez de la Campa, A.M.; De la Rosa, J.D.; Fernandez-Caliani, J.C.; Gonzales-Castanedo, J. Impact of abandoned mine waste on atmospheric respirable particulate matter in the historic mining district of Rio Tinto (Iberian Pyrite Belt). Environ. Res. 2011, 111, 1018–1023. [Google Scholar] [CrossRef]
  32. Sanchez de la Campa, A.M.; De la Rosa, J.D.; Gonzalez-Castanedo, Y.; Fernandez-Camacho, R.; Alastuey, A.; Querol, X.; Stein, A.F.; Ramos, J.L.; Rodríguez, S.; García Orellana, I.; et al. Levels and chemical composition on PM in a city near a large Cu-smelter in Spain. J. Environ. Monit. 2011, 13, 1276–1287. [Google Scholar] [CrossRef] [PubMed]
  33. Wang, X.; Bi, X.; Sheng, G.; Fu, J. Hospital indoor PM10/PM2.5 and associated trace elements in Guangzhou. China Sci. Total Environ. 2006, 366, 124–135. [Google Scholar] [CrossRef] [PubMed]
  34. Gidhagen, L.; Kahelin, H.; Schmidt-Thomé, P.; Johansson, C. Anthropogenic and natural levels of arsenic in PM10 in central and Northern Chile. Atmos. Environ. 2002, 36, 3803–3817. [Google Scholar] [CrossRef]
  35. Kovačević, R. The Content and Composition of Respirable Particles in the Urban Area of Bor. Doctoral Thesis, University of Belgrade, Belgrade, Serbia, 2016. Available online: https://cherry.chem.bg.ac.rs/handle/123456789/2721?locale-attribute=sr_RS (accessed on 15 May 2024). (In Serbian).
  36. Tofful, L.; Catrambone, M.; Giusto, M.; Pareti, S.; Rantica, E.; Sargolini, T.; Canepari, S.; Frezzini, M.A.; Massimi, L.; Ristorini, M.; et al. Seasonal Variations in the Chemical Composition of Indoor and Outdoor PM10 in University Classrooms. Sustainability 2021, 13, 2263. [Google Scholar] [CrossRef]
  37. Chen, C.; Zhao, B. Review of relationship between indoor and outdoor particles: I/O ratio, infiltration factor and penetration factor. Atmos. Environ. 2011, 45, 275–288. [Google Scholar] [CrossRef]
Figure 1. Location of the sampling site.
Figure 1. Location of the sampling site.
Atmosphere 15 00920 g001
Figure 2. Levels of As determined in PM10 at the TF in indoor and outdoor air over the different time intervals (NHS—non-heating season, HS—heating season).
Figure 2. Levels of As determined in PM10 at the TF in indoor and outdoor air over the different time intervals (NHS—non-heating season, HS—heating season).
Atmosphere 15 00920 g002
Table 1. Daily average PM10 levels, the chemical composition of PM10, and I/O ratios for the entire observation period inside and outside the selected classroom at the TF (NS—number of samples analyzed, stdev—standard deviation).
Table 1. Daily average PM10 levels, the chemical composition of PM10, and I/O ratios for the entire observation period inside and outside the selected classroom at the TF (NS—number of samples analyzed, stdev—standard deviation).
NSAverageStdevMinMaxNSAverageStdevMinMaxI/O
82µg/m382µg/m3
PM10 in32.69.910.049.2PM10 out37.016.410.284.10.9
ng/m3 ng/m3
As11.911.70.655.0As15.017.80.470.90.8
Cd1.51.80.09.5Cd1.62.50.111.80.9
Mn12.813.50.356.2Mn11.310.10.846.81.1
Pb138.1216.44.1937.2Pb97.8163.33.51062.81.4
Cu115.5101.57.2459.7Cu196.3171.28.5653.70.6
Zn69.452.61.0270.6Zn70.075.51.2531.61.0
Ni8.15.10.124.2Ni7.35.10.524.31.1
Cr11.811.80.272.5Cr10.112.60.295.51.2
Ti24.918.34.291.0Ti20.214.73.768.61.2
Sr7.16.30.833.8Sr7.67.60.333.80.9
S1524.4780.2375.92933.5S1588.4948.9148.63645.51.0
Fe566.3442.918.91516.5Fe791.7790.022.72951.80.7
Ca1358.41015.3122.04396.9Ca1312.31202.496.76292.81.0
Mg287.4200.347.4976.3Mg415.2299.45.41439.00.7
Na518.9733.545.54126.8Na430.1611.110.82815.71.2
K600.4413.023.61828.3K533.0424.621.71504.41.1
P247.0125.41.2547.3P274.892.9148.0513.50.9
Co0.80.90.13.3Co0.60.70.13.51.4
Zr3.02.80.411.1Zr2.82.20.710.21.1
V1.72.10.110.1V2.02.10.112.00.9
Se6.78.80.253.4Se10.412.20.448.30.6
Rb1.10.70.23.7Rb1.00.60.22.81.2
Ag3.12.90.212.3Ag3.83.30.212.80.8
Sn3.12.40.28.6Sn2.52.40.211.61.3
Sb1.21.00.25.7Sb1.64.10.130.30.8
Bi1.72.90.213.6Bi1.92.70.213.00.9
Ba27.014.51.259.1Ba25.215.40.165.91.1
Table 2. Average values of EF and EF I/O ratios in non-heating (NHS) and heating seasons (HS) at the TF site during the entire observation period.
Table 2. Average values of EF and EF I/O ratios in non-heating (NHS) and heating seasons (HS) at the TF site during the entire observation period.
Chemical ElementNHS EF InNHS EF OutNHS EF I/OChemical ElementHS EF InHS EF OutHS EF I/O
Se36,38018,6631.9Se18,03821,7120.8
Ag33,42413,0422.6Ag493110,3440.5
Bi12,08569711.7Bi346713,4720.3
Pb512816493.1Pb150014141.1
Cd272728701.0Cd112211121.0
As145316480.9As7289530.8
Sb133810011.3Sb96512590.8
S7863892.0S3193470.9
Cu3213271.0Cu4415950.7
Sn4361802.4Sn2332750.8
Zn4251962.2Zn1361660.8
P25300.8P41480.8
Ni2874.0Ni13220.6
Ba2463.9Ba11200.6
Cr1381.7Cr15131.1
Ca631.8Ca240.6
Zr550.9Zr330.9
K321.5K660.9
Co431.3Co431.2
Sr321.5Sr340.9
Na321.4Na331.0
Rb230.9Rb331.0
Mg221.0Mg120.6
V120.7V110.7
Mn111.0Mn111.0
Fe110.8Fe110.9
Table 3. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site during the period of application of old smelting technology in the copper smelter in Bor (2015), (NS—number of samples analyzed, stdev—standard deviation).
Table 3. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site during the period of application of old smelting technology in the copper smelter in Bor (2015), (NS—number of samples analyzed, stdev—standard deviation).
NSAverageStdevMinMaxNSAverageStdevMinMaxI/O
45µg/m345µg/m3
PM10 in36.38.420.849.2PM10 out39.517.410.284.10.9
ng/m3 ng/m3
As15.513.30.755.0As15.717.70.470.91.0
Cd1.92.00.29.5Cd1.72.60.110.31.1
Mn5.74.90.318.8Mn7.86.20.825.20.7
Pb102.3111.54.3456.3Pb112.1182.93.51062.80.9
Cu116.098.57.2459.7Cu203.0130.011.0425.90.5
Zn77.959.75.2270.6Zn77.589.31.2531.61.0
Ni6.44.20.916.8Ni7.44.80.523.30.9
Cr9.014.30.272.5Cr13.516.50.395.50.7
Ti25.524.44.291.0Ti21.817.14.868.61.2
Sr6.77.60.833.8Sr8.79.50.333.80.8
S1560.2783.4420.52745.4S1720.0890.3148.63279.60.9
Fe463.4400.522.71296.3Fe716.6766.322.72618.50.6
Ca1618.21171.7122.04396.9Ca1394.91512.396.76292.81.2
Mg280.2182.851.5660.3Mg513.9351.078.71439.00.5
Na752.51015.045.94126.8Na810.7786.786.82815.70.9
K572.6437.523.61828.3K621.5509.521.71504.40.9
P227.671.7146.4397.8P247.173.6148.0440.90.9
Co0.81.00.13.3Co0.50.40.12.01.6
Zr3.03.40.411.1Zr2.72.20.79.51.1
V2.13.00.110.1V1.92.50.112.01.1
Se8.712.20.553.4Se12.915.30.448.30.7
Rb0.90.70.22.9Rb0.90.60.22.81.0
Ag4.83.40.712.3Ag4.73.30.712.81.0
Sn3.22.20.26.8Sn2.22.70.211.61.5
Sb0.90.60.32.4Sb1.95.20.230.30.5
Bi1.83.60.213.6Bi1.21.30.24.31.4
Ba33.814.81.359.1Ba33.913.02.165.91.0
Table 4. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site during the period of application of new smelting technology (2019), (NS—number of samples analyzed, stdev—standard deviation).
Table 4. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site during the period of application of new smelting technology (2019), (NS—number of samples analyzed, stdev—standard deviation).
NSAverageStdevMinMaxNSAverageStdevMinMaxI/O
37µg/m337µg/m3
PM10 in29.610.110.049.0PM10 out37.016.410.284.10.8
ng/m3 ng/m3
As9.39.80.636.6As14.817.70.470.90.6
Cd1.21.70.16.3Cd1.62.50.111.80.7
Mn17.715.32.156.2Mn11.310.10.846.81.6
Pb166.8270.94.1937.2Pb97.8163.33.51062.81.7
Cu115.2104.911.2381.7Cu189.6205.88.5653.70.7
Zn62.946.21.0204.2Zn70.075.51.2531.60.9
Ni9.25.40.124.2Ni7.35.10.524.31.3
Cr13.69.70.230.1Cr10.112.60.295.51.3
Ti24.514.27.858.9Ti20.214.73.768.61.2
Sr7.45.21.322.9Sr7.67.60.333.81.0
S1499.3790.3375.92933.5S1588.4948.9148.63645.50.9
Fe635.6460.918.91516.5Fe791.7790.022.72951.80.8
Ca952.5513.9351.51961.1Ca1312.31202.496.76292.80.7
Mg293.5217.247.4976.3Mg415.2299.45.41439.00.7
Na327.0268.445.5895.6Na430.1611.110.82815.70.8
K618.2403.669.71719.2K533.0424.621.71504.41.2
P256.7145.11.2547.3P274.892.9148.0513.50.9
Co0.90.90.13.3Co0.60.70.13.51.5
Zr2.92.20.49.3Zr2.82.20.710.21.0
V1.51.50.16.1V2.02.10.112.00.8
Se5.86.80.226.1Se8.48.30.530.90.3
Rb1.20.80.33.7Rb1.00.60.22.81.3
Ag1.71.10.24.2Ag3.83.30.212.80.4
Sn3.12.60.58.6Sn2.52.40.211.61.3
Sb1.31.10.25.7Sb1.64.10.130.30.8
Bi1.72.40.210.9Bi1.92.70.213.00.9
Ba24.413.81.258.4Ba25.215.40.165.91.0
Table 5. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site in non-heating seasons during the entire observation period (NS—number of samples analyzed, stdev—standard deviation).
Table 5. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site in non-heating seasons during the entire observation period (NS—number of samples analyzed, stdev—standard deviation).
NSAverageStdevMinMaxNSAverageStdevMinMaxI/O
40µg/m340µg/m3
PM10 in36.812.714.849.2PM10 out38.520.98.366.01.0
ng/m3 ng/m3
As18.325.90.796.2As19.418.10.766.50.9
Cd1.22.00.09.5Cd3.06.10.137.10.4
Mn8.18.90.338.0Mn9.57.50.827.30.9
Pb299.9506.74.32513.6Pb138.8225.13.51062.82.2
Cu302.5308.320.01204.6Cu246.7202.311.01052.41.2
Zn87.354.85.2270.6Zn86.570.01.2296.81.0
Ni12.910.00.939.9Ni10.310.80.562.71.3
Cr15.214.10.272.5Cr13.615.30.395.51.1
Ti23.518.62.273.5Ti20.013.92.066.71.2
Sr5.86.40.726.3Sr5.95.80.323.21.0
S2104.81187.1420.53745.4S1973.31313.0148.64933.81.0
Fe988.81807.922.78794.2Fe681.5741.522.72951.81.5
Ca1706.8612.81089.82694.5Ca2267.21379.696.76292.80.8
Mg302.9191.8125.6660.3Mg634.5417.878.71693.90.5
Na141.874.148.2243.9Na636.9909.286.82815.70.2
K626.3348.4232.11039.7K391.5350.921.71147.71.6
P72.0121.90.0397.8P146.5122.30.0440.90.5
Co0.30.20.10.7Co0.40.40.12.00.8
Zr1.31.30.27.4Zr2.42.20.29.50.6
V0.80.50.01.9V2.12.40.112.00.4
Se14.526.70.397.0Se10.219.80.383.11.4
Rb1.51.80.27.0Rb1.95.00.228.00.8
Ag5.53.01.314.0Ag5.43.40.714.81.0
Sn2.02.30.28.2Sn2.12.80.212.01.0
Sb0.80.50.22.4Sb2.56.60.230.30.3
Bi1.41.20.23.3Bi1.31.40.24.31.1
Ba32.69.61.359.1Ba25.815.72.165.91.3
Table 6. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site in heating seasons in the entire observation period (NS—number of samples analyzed, stdev—standard deviation).
Table 6. Average PM10 concentrations, chemical composition, and I/O ratios determined at the TF site in heating seasons in the entire observation period (NS—number of samples analyzed, stdev—standard deviation).
NSAverageStdevMinMaxNSAverageStdevMinMaxI/O
42µg/m342µg/m3
PM10 in32.99.910.049.2PM10 out37.717.312.784.10.9
ng/m3 ng/m3
As6.98.10.636.6As11.216.10.770.90.6
Cd0.91.10.24.8Cd1.01.60.19.41.0
Mn16.116.11.356.2Mn11.811.91.546.81.4
Pb49.860.24.1238.3Pb65.784.04.9362.10.8
Cu128.1117.911.2459.7Cu216.0182.78.5640.80.6
Zn49.226.01.0109.3Zn64.976.66.3531.60.8
Ni7.13.60.115.3Ni9.15.30.624.30.8
Cr12.36.90.228.9Cr10.36.10.220.01.2
Ti21.212.95.258.9Ti22.715.66.268.60.9
Sr8.27.00.933.8Sr7.37.90.733.81.1
S1420.6743.7375.92933.5S1238.6797.6365.03419.21.1
Fe578.7449.918.91516.5Fe702.0749.122.72641.00.8
Ca598.9418.1122.01794.1Ca1045.1797.2165.63220.90.6
Mg307.5231.947.4976.3Mg315.0320.55.41439.01.0
Na436.9345.445.51164.6Na377.5357.846.51126.31.2
K658.5460.223.61828.3K553.4375.884.41302.51.2
P258.1144.81.2547.3P292.493.2161.2513.50.9
Co1.00.90.13.3Co0.70.80.13.51.5
Zr3.52.20.79.3Zr3.42.21.110.21.0
V1.61.50.16.1V1.91.70.26.70.9
Se7.010.00.253.4Se12.013.40.548.30.6
Rb1.30.80.43.7Rb1.10.70.22.81.3
Ag2.22.50.212.3Ag3.73.60.212.80.6
Sn3.62.50.58.6Sn2.72.40.58.11.3
Sb1.51.10.35.7Sb1.31.70.28.61.2
Bi2.03.30.213.6Bi2.33.00.213.00.9
Ba23.314.41.258.4Ba26.514.60.147.10.9
Table 7. Pearson’s correlation coefficients between levels of chemical elements determined in PM10 at the TF site in non-heating seasons (NHS) over the entire observation period.
Table 7. Pearson’s correlation coefficients between levels of chemical elements determined in PM10 at the TF site in non-heating seasons (NHS) over the entire observation period.
NHS OutdoorAsCdMnPbCuZnNiCrTiSrSFe
As1
Cd0.709 **1
Mn 1
Pb0.491 **0.825 ** 1
Cu0.454 *0.614 ** 0.666 **1
Zn0.413 *0.592 **0.609 **0.741 **0.647 **1
Ni 0.401 * 0.496 * 1
Cr 0.430 *0.465 *1
Ti 0.670 ** 0.555 *0.570 *0.821 **1
Sr 0.844 ** 0.536 ** 0.539 *1
S 0.547 *0.729 **0.723 **0.671 ** 1
Fe 0.589 **0.750 **0.760 **0.655 **0.777 ** 0.761 **0.553 **0.851 **1
NHS indoorAsCdMnPbCuZnNiCrTiSrSFe
As1
Cd0.453 **1
Mn0.522 ** 1
Pb 1
Cu0.447 ** 0.408 *1
Zn 0.414 * 0.589 **0.437 **1
Ni 0.601 ** 1
Cr 0.408 * 0.738 **1
Ti0.677 ** 1
Sr0.479 ** 0.721 ** 0.541 ** 1
S 0.563 ** 0.586 ** 0.712 ** 1
Fe0.648 ** 0.872 ** 0.492 * 0.838 ** 1
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Table 8. Pearson’s correlation coefficients between levels of chemical elements determined in PM10 at the TF site in heating seasons (HS) over the entire observation period.
Table 8. Pearson’s correlation coefficients between levels of chemical elements determined in PM10 at the TF site in heating seasons (HS) over the entire observation period.
HS OutdoorAsCdMnPbCuZnNiCrTiSrSFe
As1
Cd0.879 **1
Mn 1
Pb0.695 **0.644 ** 1
Cu0.407 ** 1
Zn0.702 **0.876 ** 0.595 ** 1
Ni 1
Cr 1
Ti0.480 **0.495 ** 0.515 ** 1
Sr0.631 **0.647 ** 0.430 ** 0.601 ** 0.652 **1
S 0.812 ** 1
Fe 0.415 **0.783 ** 0.547 **0.462 ** 1
HS indoorAsCdMnPbCuZnNiCrTiSrSFe
As1
Cd 1
Mn 1
Pb0.537 ** 1
Cu 1
Zn0.490 ** 1
Ni 1
Cr 0.422 **1
Ti 1
Sr 1
S 1
Fe 0.700 ** 0.602 **0.566 ** 1
** Correlation is significant at the 0.01 level (2-tailed).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Radović, B.; Tasić, V.; Kovačević, R.; Apostolovski-Trujić, T.; Manojlović, D.; Cocić, M.; Urošević, T. Chemical Composition of PM10 in a Classroom near the Copper Smelter in Bor, Serbia. Atmosphere 2024, 15, 920. https://doi.org/10.3390/atmos15080920

AMA Style

Radović B, Tasić V, Kovačević R, Apostolovski-Trujić T, Manojlović D, Cocić M, Urošević T. Chemical Composition of PM10 in a Classroom near the Copper Smelter in Bor, Serbia. Atmosphere. 2024; 15(8):920. https://doi.org/10.3390/atmos15080920

Chicago/Turabian Style

Radović, Bojan, Viša Tasić, Renata Kovačević, Tatjana Apostolovski-Trujić, Dragan Manojlović, Mira Cocić, and Tamara Urošević. 2024. "Chemical Composition of PM10 in a Classroom near the Copper Smelter in Bor, Serbia" Atmosphere 15, no. 8: 920. https://doi.org/10.3390/atmos15080920

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

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop