Concentration variability of water-soluble ions during the acceptable and exceeded pollution in an industrial region

International Journal of Environmental Research and Public Health Article Concentration Variability of Water-Soluble Ions during the Acceptable and Exceeded Pollution in an Industrial Region Barbora Švédová1, Helena Raclavská1, Marek Kucbel 1,* , Jana R˚užiˇcková1, Konstantin Raclavský1, Miroslav Koliba 2and Dagmar Juchelková3 1 Centre ENET—Energy Units for Utilization of Non-Traditional Energy Sources, VŠB—Technical University of Ostrava, 17. listopadu 15/2172, 708 00 Ostrava-Poruba, Czech Republic; [email protected] (B.Š.); [email protected] (H.R.); [email protected] (J.R.); [email protected] (K.R.) 2 Diabetic and podiatric clinic, Fr ý deck á 936/59, 739 32 Vratimov, Czech Republic; [email protected] 3Department of Electronics, VŠB—Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science, 17. listopadu 15/2172, 708 00 Ostrava-Poruba, Czech Republic; dagmar[email protected] *Correspondence: mar[email protected]; Tel.: +420-597-325-448 Received: 28 January 2020; Accepted: 13 May 2020; Published: 15 May 2020   Abstract: This study investigates the chemical composition of water-soluble inorganic ions at eight localities situated in the Moravian–Silesian Region (the Czech Republic) at the border with Poland. Water-soluble inorganic ions were monitored in the winter period of 2018 (January, 11 days and February, 5 days). The set was divided into two periods: the acceptable period (the 24-h concentration of PM 10 <50 µ g/m 3 ) and the period with exceeded pollution (PM 10 >50 µ g/m 3 ). Air quality in the Moravian–Silesian Region and Upper Silesia is among the most polluted in Europe, especially in the winter season when the concentration of PM 10 is repeatedly exceeded. The information on the occurrence and behaviour of water-soluble inorganic ions in the air during the smog episodes in Europe is insufficient. The concentrations of water-soluble ions (chlorides, sulphates, nitrates, ammonium ions, potassium) during the exceeded period are higher by two to three times compared with the acceptable period. The major anions for both acceptable period and exceeded pollution are nitrates. During the period of exceeded pollution, percentages of water-soluble ions in PM 10 decrease while percentages of carbonaceous matter and insoluble particles (fly ash) increase. Keywords: water-soluble inorganic ions; particulate matter; meteorological parameters; enrichment factor; air pollution 1. Introduction The particle pollution (particulate matter—PM) represents one of the critical parameters for monitoring of ambient air quality. The effect of particulate matter on health is summarized in review [ 1 ]. Depending on the parameters of atmospheric pollution, the characteristics of the persons exposed and exposure, various forms of the disease may develop, e.g., a local or systemic disease, a curable or incurable disease, a state of simple disease, or pathological conditions complicated by persistent long-term effects. The association between exposure to polluted air and diseases of the cardiovascular system (atherosclerosis, coronary heart disease) and diseases of the respiratory system (bronchitis, pneumoconiosis, inhalation pneumonia, some types of respiratory cancer, bronchial asthma) is already explored in great detail [ 2 ]. Particulate matter contains insoluble particles: (fly ash) +resuspended particles (salts, pavement dust) +organic/elemental carbon, the water-soluble inorganic ions (WSSI), and metals present in both soluble and insoluble form. Int. J. Environ. Res. Public Health 2020,17, 3447; doi:10.3390/ijerph17103447 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2020,17, 3447 2 of 26 Particulate matter was classified by the International Agency for Research on Cancer (IARC) as carcinogenic to humans (Group 1). Ambient air pollution and particularly airborne particulate matter cause adverse human health effects including respiratory illnesses, cardiovascular diseases: myocardial infarction, cardiac arrhythmias, ischemic stroke, vascular dysfunction, hypertension and atherosclerosis [ 3 ], carcinogenic effects, and is adverse to asthma, premature death, diabetes [ 4 ], and shortens life expectancy [ 5 , 6 ]. Children in the industrial Ostrava conurbation have the high incidence of acute illnesses and allergies compared with children from other regions of the Czech Republic [7]. Air pollution can also generate psychological impacts on individuals or groups, e.g., reduce subjective well-being, cause anxiety and depression, and even increase suicide risk [ 8 ]. The health effects of exposure to aerosol particle matter are well documented and therefore is necessary for the improvement of air quality to used reference guidelines for ambient particulate concentration: the World Health Organisation Air Quality Guidelines (PM 10 24-h mean: 50 µ g/m 3 ) [ 9 ]. At present, Directive 2008/50/EC of the European Parliament and of the Council on ambient air quality and cleaner air for Europe does not specify the value for determining the smog conditions based on concentrations of PM 10 [ 10 ]. In the Czech Republic, the smog situation is declared under the Air Protection Act 201/2012 if at least one parameter exceeds the pollution levels: sulphur dioxide (250 µ g.m 3 /hour), nitrogen dioxide (200 µ g/m 3 /hour), PM 10 (100 µ g/m 3 /12 h), or tropospheric ozone (180 µ g/m 3 /hour) [ 11 ]. Stable weather conditions, together with the extensive use of coal combustion, often lead to severe smog episodes in some urban environments, especially in Eastern Europe [12]. The smog measures in the Moravian-Silesian Region (MSR) were declared during 2010 for the total time of 1031 h. The smog measures during 2018 were declared for 336 h. The shortest time of the smog conditions was 124 h in 2015. The year 2015 was characterized by the above-average temperature in winter and better dispersion conditions compared with other years [13]. The air quality not only in the Czech Republic (specifically in Moravian–Silesian Region), but also in Europe has been improved significantly over the previous decades. Nevertheless, air pollution is still a large environmental health risk problem. The Ostrava-Karvin á conurbation representing part of the Ostrava Basin is considered one of the most polluted areas in the European Union due to high concentrations of the most significant air pollutants, predominately airborne dust [ 14 ] and higher concentration of benzo(a)pyrene [15]. The study area is formed by communities and the City of Ostrava located in Moravian-Silesian Region (MSR) in the Czech Republic. The study area is located at the geomorphological unit of Ostrava Basin, which is part of the geomorphological region Western Outer Carpathian Depression. It is situated at the boundary of Northern Moravia, Silesia and Southern Poland. The region can be characterised as industrial with important energy production, metallurgy, coal mines, power engineering, chemical industry and others. The most important sources of pollution are energy production and metallurgy (production of coke, pig iron and steel). Air mass flowing represents an essential factor which influences the origin of smog episodes. The prevailing directions of air flowing are southwest and northeast. A significant decrease in pollutant dispersion in the atmosphere is caused by a decrease in the air flowing speed below 1.5 m/s. The calm periods represent up to 25% of the year. The territory of the City Ostrava has above-average occurrences of calm weather. The weather conditions combined with high industrialization of regions in the Czech Republic and Poland influence the origin of long smog episodes with concentrations of PM 10 in the atmosphere at the level of hundreds of micrograms [ 16 ] Air pollution is concentrated mainly during poor dispersion conditions, especially in the winter season [ 17 ]. The same situation was observed in the border with Poland, especially in the Upper Silesian region and in Małopolska regions. These regions located in the southern part of Poland (at the border with the Czech Republic) are one of the most polluted regions in Europe [ 18 ]. Poor air quality is caused by an excessive concentration of PM 10 [ 19 , 20 ]. The winter episodes with the high concentrations of PM 10 in the southern cities of Poland (Zabrze, Krakow) are more influenced by local pollution than long-range transport and regional transport particles [ 20 ]. The primary pollution sources of PM 10 in the area of Polish and Czech border between Ostrava and Katowice (Silesia Region) is residential Int. J. Environ. Res. Public Health 2020,17, 3447 3 of 26 heating [ 21 ]. During the years 2006–2012, the PM 10 trans-boundary transport was more significant from the direction of Poland to the Czech Republic [ 17 ]. Wielgosi´nski and Czerwi´nska [ 20 ] defined characteristics of “Polish smog”. The most important emission source of particulate matter in Poland are the so-called “low emissions” (height up to 40 m), i.e., residential boilers and traffic pollution. “Polish smog” is characterised by varied meteorological conditions and high concentrations of sulphate and ammonium ions. The main source of ammonia emissions is the combustion of biomass and coal [ 20 ]. The ammonia emission factor for domestic stove for anthracite is 0.20 g/kg, for bituminous coal from 0.7 to 1.52 g/kg, and for biomass 0.72–1.08 g/kg [ 22 ]. The main sources of NH 3 in air aerosol are not yet unequivocally identified. A study of the isotopic composition shows that, in China, 38–52% of NH 3 emissions come from burning fossil fuels [ 23 ]. Car transport is another reason for the increase NH 3 in air aerosol. Trying to reduce NO X emissions from diesel engines by using urea (NH 2 ) 2 CO reduces NOx output but also increases NH 3 emissions, causing problems for the future [ 24 ]. Emissions of NH 3 in the atmosphere react with SO 2 which significantly decreases its concentrations. Therefore, ammonium sulphate is the main constituent of PM in “Polish dusty smog” [20]. This study is focused on obtaining the information on changes in the chemical composition of water-soluble ions, trace elements and forms of carbon occurrence in relationships to the direction of air flowing and concentration of PM 10 (acceptable and exceeded pollution) to identify a source of pollution. 2. Materials and Methods 2.1. Sampling Eight localities were selected where the influences of various emission sources were assumed (Supplementary Table S1 and Figure 1). In the text, we have used an abbreviation for these localities: Ostrava-Radvanice, Nad Obc í (OR-NO); Ostrava-Radvanice, OZO (OR-OZO); Ostrava-Mari á nsk é Hory (O-MH); Ostrava-Poruba (O-P), Stud é nka (S), Doln í Lhota (DL), Vˇeˇrˇnovice (V) and Mosty u ˇ Cesk é ho Tˇeš í na (MCT). For comparison, the locality Olomouc-Svat ý Kopeˇcek (Olomouc), was selected as the background locality, without industry emissions and high traffic influence. It is a rural locality near the Zoo of Olomouc (Supplementary Table S1 and Figure 1). Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 4 of 27 the smog episode. Even during the season from 22 to 23 January 2018, concentrations of PM10 reached values higher than 100 µg/m 3 at two localities, and thus influenced the results of the chemical composition of PM10 in the winter season. Measured data in both sets for the winter season and smog episode were divided using the 24-h air concentration limit valid for PM10 (50 µg/m3) according to the Act No. 201/2012 Coll., on Air Pollution [11] and Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe [26]. Concentrations of PM10 over 50 µg/m3 are designated as the period of exceeded pollution, and period with the concentration of PM < 50 µg/m3 is designated as the period of acceptable pollution. Figure 1. (A) Border between Czech Republic and Poland; (B) Localization of the Moravian-Silesian Region and Olomouc in the Czech Republic; (C) Detail of the Moravian-Silesian Region and localization of the sampling sites; The main pollution sources in Ostrava City (D) and in the area of Těšínské Slezsko (E). 2.2. Analysis Method One-quarter of each filter substrate was extracted with 25 mL deionized water in a PET vial for 24 h. After passing through microporous membranes with a 0.22 µm pore size, the extracts were analysed by ion chromatography. Determinations of water-soluble ions SO42−-, NO3−, NH4+, Cl−, Na+, K+, Ca2+, Mg2+, PO43−, pH value, and conductivity in the particulate matter were performed by analysis of water extract by ion chromatography with the instrument 850 Professional IC (Metrohm AG, Herisau, Switzerland) according to the “Standard ISO 14911 Water quality: Determination of dissolved Li+, Na+, NH4+, K+, Mn2+, Ca2+, Mg2+, Sr2+, and Ba2+ using ion chromatography” and “Standard EN ISO 10304 Water quality: Determination of dissolved anions by liquid chromatography of ions”. Water-soluble organic carbon (WSOC) was determined according to the methodology of Karthikeyan and Balasubramanian [27] using ion chromatography (IC). Mineralisation of atmospheric aerosol particles, as well as further analyses of trace elements, were performed by inductively coupled plasma-optical emission spectrometry [28]. Determinations were performed for 18 elements: Al, As, Be, Ca, Cd, Co, Cu, Fe, K, Mn, Mo, Ni, Pb, Sb, Ti, Tl, V, and Zn (italics denote elements with concentrations below the detection limit). The concentrations of Ca and K after total decomposition (total content) were reduced by subtraction of the concentration of water-soluble ions and consequently used to calculate MD according to the Equation (1). The mineralogical phase analysis of particles was performed by X-ray diffraction (Diffractometer Bruker Advance D8, Bruker Corporation, Billerica, MA, USA) and used for verification of the presence of water-insoluble mineral phases (gypsum, zincite). The determinations of organic carbon (OC) and elemental carbon (EC) were performed using filters by thermo-optical analysis at the OC/EC Analyser (Sunset Laboratory Inc., Portland-Tigard, OR, USA). Organic matter (OM) was determined as OC multiplied by a factor of 1.4, which is commonly used for both urban areas as used e.g., in ref. [29] and rural areas [30]. The concentrations of OC/EC were measured using the method of the temperature programme EUSAAR 2 with the modification of thermo-optical Figure 1. ( A ) Border between Czech Republic and Poland; ( B ) Localization of the Moravian-Silesian Region and Olomouc in the Czech Republic; ( C ) Detail of the Moravian-Silesian Region and localization of the sampling sites; The main pollution sources in Ostrava City ( D ) and in the area of Tˇeš í nsk é Slezsko (E). Identification and quantification of selected metals in Ostrava and Olomouc were performed by X-ray fluorescence spectrometry. The sampling of particles PM 10 was performed on filters of 150 mm diameter with quartz fibres by high-volume samplers DHA 80 or MD05 produced by DIGITEL Co. with Int. J. Environ. Res. Public Health 2020,17, 3447 4 of 26 an airflow of 0.5 to 1.13 m 3 /min (Supplementary Table S1). Wind speed and direction were measured by the ultrasonic anemometer during 24 h in the winter season (18 January–28 January 2018) and during 12 h in the period of smog episode (9–13 February). The sampling of PM 10 in Olomouc was performed as 24 h measurements from 21 November to 28 November 2018. Measurements in both areas were taken during heating seasons allowing comparison of measured data from different regions. The heating season in the Czech Republic begins on 1 September and ends on 31 May of the following year (Decree No 194/2007 Coll. of the Ministry of Industry and Trade, as amended) [ 25 ]. The measurements in Olomouc were made under conditions typical of the heating season. The division of days between ordinary winter days and days of smog episode was performed based on the announcement of smog situation for PM 10 (100 µ g/m 3 per 12 h) according to the Ministry of the Environment (Act 201/2012 Coll.) [ 11 ]. The period from 18 January to 28 January 2018 is an example of typical winter conditions while the period from 9 February to 13 February represents a smog situation lasting for 78 h. Concentrations of PM 10 decreased in the period from 11 to 13 February below 80 µ g/m 3 . In total, 54 samples were obtained (in the periods of 12 h) during the smog episode. Average values of the results of chemical analyses were calculated in order to correspond to the sampling, which lasted 24 h. In total, 40 samples were obtained in the winter season. An original aim of the statistical evaluation of the results was the division of the whole set into the winter season and the smog episode. Even during the season from 22 to 23 January 2018, concentrations of PM 10 reached values higher than 100 µ g/m 3 at two localities, and thus influenced the results of the chemical composition of PM 10 in the winter season. Measured data in both sets for the winter season and smog episode were divided using the 24-h air concentration limit valid for PM10 (50 µg/m3) according to the Act No. 201/2012 Coll., on Air Pollution [ 11 ] and Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe [ 26 ]. Concentrations of PM 10 over 50 µ g/m 3 are designated as the period of exceeded pollution, and period with the concentration of PM <50 µ g/m 3 is designated as the period of acceptable pollution. 2.2. Analysis Method One-quarter of each filter substrate was extracted with 25 mL deionized water in a PET vial for 24 h. After passing through microporous membranes with a 0.22 µ m pore size, the extracts were analysed by ion chromatography. Determinations of water-soluble ions SO 42− , NO 3− , NH 4+ , Cl − , Na + , K + , Ca 2+ , Mg 2+ , PO 43− , pH value, and conductivity in the particulate matter were performed by analysis of water extract by ion chromatography with the instrument 850 Professional IC (Metrohm AG, Herisau, Switzerland) according to the “Standard ISO 14911 Water quality: Determination of dissolved Li + , Na + , NH 4+ , K + , Mn 2+ , Ca 2+ , Mg 2+ , Sr 2+ , and Ba 2+ using ion chromatography” and “Standard EN ISO 10304 Water quality: Determination of dissolved anions by liquid chromatography of ions”. Water-soluble organic carbon (WSOC) was determined according to the methodology of Karthikeyan and Balasubramanian [ 27 ] using ion chromatography (IC). Mineralisation of atmospheric aerosol particles, as well as further analyses of trace elements, were performed by inductively coupled plasma-optical emission spectrometry [ 28 ]. Determinations were performed for 18 elements: Al, As, Be, Ca, Cd, Co, Cu, Fe, K, Mn, Mo, Ni, Pb, Sb, Ti, Tl, V, and Zn (italics denote elements with concentrations below the detection limit). The concentrations of Ca and K after total decomposition (total content) were reduced by subtraction of the concentration of water-soluble ions and consequently used to calculate MD according to the Equation (1). The mineralogical phase analysis of particles was performed by X-ray diffraction (Diffractometer Bruker Advance D8, Bruker Corporation, Billerica, MA, USA) and used for verification of the presence of water-insoluble mineral phases (gypsum, zincite). The determinations of organic carbon (OC) and elemental carbon (EC) were performed using filters by thermo-optical analysis at the OC/EC Analyser (Sunset Laboratory Inc., Portland-Tigard, OR, USA). Organic matter (OM) was determined as OC multiplied by a factor of 1.4, which is commonly used for both urban areas as used e.g., in ref. [ 29 ] and rural areas [ 30 ]. The concentrations of OC/EC were measured using the method of the temperature Int. J. Environ. Res. Public Health 2020,17, 3447 5 of 26 programme EUSAAR 2 with the modification of thermo-optical transmittance. The statistical analysis and the correlation analysis (Spearman correlation coefficient) at the 0.05 level of significance were performed using the statistical software OriginPro 8.5 (OriginLab Corporation, Northampton, MA, USA). 3. Results and Discussion In 2018, the acceptable daily limit for air concentration of PM 10 (50 µ g/m 3 ) was most often exceeded at the locality V (94 times). Exceeding the air concentration limit was also very important at other localities: OR-NO (89 × ), OR-OZO (70 × ), ˇ Cesk ý Tˇeš í n (69 × ), S (47 × ), O-MH (43 × ), O-P (37 × ) [ 13 ]. The most frequent exceeding of the air concentration limit occurs at the localities V and MCT near the boundary with Poland. The average concentration of PM 10 in the period of acceptable pollution was 32.7 ± 13.0 µ g/m 3 (Figure 2). It increased 2.8 times during the period of exceeded pollution 92.8 ± 37.8 µ g/m 3 . The highest average concentration of PM 10 during the period of exceeded pollution was determined in MCT (127 ±64.4 µg/m3) and the lowest in DL (69.9 ± 8.6 µ g/m 3 ). Average concentrations of NO 2 and SO 2 for MSR were during the period of exceeded pollution 1.3 times and 1.5 times higher than in the period of acceptable pollution. Average concentrations of monitored pollutants (NO 2 , SO 2 , and PM 10 ) in 2018 for individual localities are illustrated in Figure 3. The locality OR-NO has the values for the period of acceptable pollution higher than other localities. This sampling site is situated in the immediate vicinity of the largest pollution source at the territory of Ostrava, namely the metallurgical enterprise Arcelor Mittal (now Liberty Ostrava). Moreover, it is situated at the morphologically elevated position. The locality OR-NO is situated in the NE direction from the sintering plant that represents the main pollution sources. This direction corresponds to the prevailing air mass flow during sampling period. Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 5 of 27 transmittance. The statistical analysis and the correlation analysis (Spearman correlation coefficient) at the 0.05 level of significance were performed using the statistical software OriginPro 8.5 (OriginLab Corporation, Northampton, MA, USA). 3. Results and Discussion In 2018, the acceptable daily limit for air concentration of PM10 (50 µg/m3) was most often exceeded at the locality V (94 times). Exceeding the air concentration limit was also very important at other localities: OR-NO (89×), OR-OZO (70×), Český Těšín (69×), S (47×), O-MH (43×), O-P (37×) [13]. The most frequent exceeding of the air concentration limit occurs at the localities V and MCT near the boundary with Poland. The average concentration of PM10 in the period of acceptable pollution was 32.7 ± 13.0 µg/m3 (Figure 2). It increased 2.8 times during the period of exceeded pollution 92.8 ± 37.8 µg/m3. The highest average concentration of PM10 during the period of exceeded pollution was determined in MCT (127 ± 64.4 µg/m3) and the lowest in DL (69.9 ± 8.6 µg/m3). Average concentrations of NO2 and SO2 for MSR were during the period of exceeded pollution 1.3 times and 1.5 times higher than in the period of acceptable pollution. Average concentrations of monitored pollutants (NO2, SO2, and PM10) in 2018 for individual localities are illustrated in Figure 3. The locality OR-NO has the values for the period of acceptable pollution higher than other localities. This sampling site is situated in the immediate vicinity of the largest pollution source at the territory of Ostrava, namely the metallurgical enterprise Arcelor Mittal (now Liberty Ostrava). Moreover, it is situated at the morphologically elevated position. The locality OR-NO is situated in the NE direction from the sintering plant that represents the main pollution sources. This direction corresponds to the prevailing air mass flow during sampling period. In the period of exceeded pollution, the content of ammonium ions, organic matter and PM10 increase significantly (Table 1). The concentration of individual major components in PM10 increased differently: up to 3-fold concentration increases occurred in Cl−, OM, SO42− and EC, lower than 2-fold increase occurred in NO3−, NH4+, K+ (Table 1). Figure 2 shows the boxplots for the main ions represented in inorganic aerosol (IA) and watersoluble organic carbon (WSOC), organic carbon (OC) and elemental carbon (EC) for the period of accetable pollution and exceeded pollution for all measurement. Figure 2. Boxplot in the period of acceptable and exceeded pollution for concentrations of watersoluble ions in PM10 (A); concentrations of carbon forms in PM10 (B) and for concentrations of PM10 (C). Explanations: Water soluble organic carbon (WSOC), secondary organic carbon (SOC), particulate organic carbon (POC). Figure 2. Boxplot in the period of acceptable and exceeded pollution for concentrations of water-soluble ions in PM 10 ( A ); concentrations of carbon forms in PM 10 ( B ) and for concentrations of PM 10 ( C ). Explanations: Water soluble organic carbon (WSOC), secondary organic carbon (SOC), particulate organic carbon (POC). In the period of exceeded pollution, the content of ammonium ions, organic matter and PM 10 increase significantly (Table 1). The concentration of individual major components in PM 10 increased differently: up to 3-fold concentration increases occurred in Cl − , OM, SO 42− and EC, lower than 2-fold increase occurred in NO3−, NH4+, K+(Table 1). Int. J. Environ. Res. Public Health 2020,17, 3447 6 of 26 Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 6 of 27 Table 1. The minimal and maximal concentration ranges of all measured values, arithmetical means (AVG), standard deviations (STD) and ratio of average values AP/EP for the period of acceptable (AP) and exceeded pollution (EP). Mass Concentration Acceptable Pollution (AP) Exceeded Pollution (EP) EP/AP AVG ± STD Min–max AVG ± STD Min—Max (µg/m3) (µg/m3) (µg/m3) (µg/m3) Cl− 0.66 ± 0.69 0.11–3.57 2.13 ± 1.67 0.37–7.96 3.21 SO42− 2.79 ± 1.31 0.49–5.39 8.46 ± 3.44 3.74–20.6 3.03 PO43− 0.014 ± 0.017 0.003–0.05 0.02 ± 0.04 0.001–0.25 1.64 NO3− 6.36 ± 3.26 0.63–11.30 14.0 ± 5.43 6.26–28.0 2.21 NH4+ 3.07 ± 1.65 0.17–7.52 7.72 ± 3.47 3.59–18.2 2.51 Na+ 0.29 ± 0.20 0.09–1.11 0.40 ± 0.20 0.12–1.23 1.40 K+ 0.34 ± 0.17 0.050.69 0.77 ± 0.27 0.41–1.44 2.24 Ca2+ 0.49 ± 0.35 0.18–1.95 0.84 ± 0.55 0.22–2.59 1.72 Mg2+ 0.06 ± 0.03 0.01–0.17 0.10 ± 0.07 0.03–0.51 1.75 WSOC 3.67 ± 1.79 1.05–8.24 9.30 ± 4.61 2.25 – 32.0 0.84 EC 1.26 ± 0.63 0.30–2.69 4.30 ± 2.25 1.00–11.4 3.42 OM 10.9 ± 5.86 1.96–21.4 39.1 ± 18.5 14.3–107 3.59 PM10 32.7 ± 13.0 7.15–49.0 92.8 ± 37.8 52.4–212 2.84 Figure 3. The average concentrations of NO2, SO2 and PM10 with the standard deviations for 2018. The minimal and maximal average percentage of organic matter in dust particles and watersoluble ions during the period of acceptable pollution (OM: 29.4–48.6% and IA: 53.3–66.8%) and exceeded pollution (OM: 37.3–44.7% and IA: 45.3–55.6%) is almost comparable. The average percentage of PM10 is shown in Figure 4. The percentage of inorganic particles (minerals and amorphous particles = mineral dust, MD) was derived by calculation according to Equation (1) by Amato et al. [31]: 𝑀𝐷= 𝐴 𝑙×3.89+𝐶𝑎×2.5+𝐹𝑒×1.43+𝐾×1.21+𝑇𝑖×1.67 (1) The parameter MD expresses a total (mass) concentration (with certain assumptions regarding the chemical composition of the dust) of insoluble inorganic particles (mineral phases and amorphous inorganic phase). It was used for the construction of Figure 4 in order to obtain a total composition of particles (100%). The origin of elements included in the MD parameter in the Ostrava region is from both blast furnaces and the combustion of fossil fuels. Figure 3. The average concentrations of NO2, SO2and PM10 with the standard deviations for 2018. Table 1. The minimal and maximal concentration ranges of all measured values, arithmetical means (AVG), standard deviations (STD) and ratio of average values AP/EP for the period of acceptable (AP) and exceeded pollution (EP). Mass Concentration Acceptable Pollution (AP) Exceeded Pollution (EP) EP/AP AVG ±STD Min–Max AVG ±STD Min—Max (µg/m3) (µg/m3) (µg/m3) (µg/m3) Cl−0.66 ±0.69 0.11–3.57 2.13 ±1.67 0.37–7.96 3.21 SO42−2.79 ±1.31 0.49–5.39 8.46 ±3.44 3.74–20.6 3.03 PO43−0.014 ±0.017 0.003–0.05 0.02 ±0.04 0.001–0.25 1.64 NO3−6.36 ±3.26 0.63–11.30 14.0 ±5.43 6.26–28.0 2.21 NH4+3.07 ±1.65 0.17–7.52 7.72 ±3.47 3.59–18.2 2.51 Na+0.29 ±0.20 0.09–1.11 0.40 ±0.20 0.12–1.23 1.40 K+0.34 ±0.17 0.050.69 0.77 ±0.27 0.41–1.44 2.24 Ca2+0.49 ±0.35 0.18–1.95 0.84 ±0.55 0.22–2.59 1.72 Mg2+0.06 ±0.03 0.01–0.17 0.10 ±0.07 0.03–0.51 1.75 WSOC 3.67 ±1.79 1.05–8.24 9.30 ±4.61 2.25 – 32.0 0.84 EC 1.26 ±0.63 0.30–2.69 4.30 ±2.25 1.00–11.4 3.42 OM 10.9 ±5.86 1.96–21.4 39.1 ±18.5 14.3–107 3.59 PM10 32.7 ±13.0 7.15–49.0 92.8 ±37.8 52.4–212 2.84 Figure 2shows the boxplots for the main ions represented in inorganic aerosol (IA) and water-soluble organic carbon (WSOC), organic carbon (OC) and elemental carbon (EC) for the period of accetable pollution and exceeded pollution for all measurement. The minimal and maximal average percentage of organic matter in dust particles and water-soluble ions during the period of acceptable pollution (OM: 29.4–48.6% and IA: 53.3–66.8%) and exceeded pollution (OM: 37.3–44.7% and IA: 45.3–55.6%) is almost comparable. The average percentage of PM 10 is shown in Figure 4. The percentage of inorganic particles (minerals and amorphous particles = mineral dust, MD) was derived by calculation according to Equation (1) by Amato et al. [31]: MD =Al ×3.89 +Ca ×2.5 +Fe ×1.43 +K×1.21 +Ti ×1.67 (1) Int. J. Environ. Res. Public Health 2020,17, 3447 7 of 26 Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 7 of 27 Figure 4. Average composition percentages of PM10 during the period of acceptable and exceeded pollution. Explanations: Water soluble inorganic ions (WSIIs), organic matter (OM), elemental carbon (EC), trace elements (TE), mineral dust (MD). The average pollutant content in PM10 implies that during the period of exceeded pollution, the content of organic substances 43.1 ± 12% is higher by about 7%, which is compensated by the loss of water-soluble ions (Figure 4). Increased OM shares of PM10 during smog situations have also been observed in Switzerland [32]. In the region of Ostrava, analyses of organic compounds have shown that the beginning of the smog episode is accompanied by an increase of the percentage of an unresolved complex mixture of hydrocarbons (UCM) and organic matter which cannot be reliably identified. The combustion processes are the most important source of particles PM10 and OM during both acceptable pollution and exceeded pollution. The combustion processes include the combustion of coal (lignite, bituminous coal and mixtures of both), biomass and waste (polymers—plastics). Organic compounds of sulphur occurred in all samples of PM10 during both acceptable pollution and exceeded pollution in areas with the combustion of coal. The number of organic compounds of sulphur in a deposition during exceeded pollution is two or three times higher than during acceptable pollution. The locality O-MH is characterised by high emissions from transport for both acceptable pollution and exceeded pollution. The locality O-P has similar characteristics. The combustion of biomass prevails among combustion processes. The difference in OM between acceptable pollution and exceeded pollution is not conspicuous. However, individual organic compounds connected with the combustion processes have increased concentrations. During exceeded pollution, EC is not increased despite the fact that it can be expected. This is connected to the fact that the combustion processes play an important role in the winter season even during acceptable pollution (the results of the authors’ team will be published during the year 2020). 3.1. Enrichment Factors for the Main Components in PM10 in Respect to the Background Values The aim of determination of enrichment factors (EFBC) for the main components was the comparison of their normalized concentrations in PM10 with background values. The background values were utilised because Clarke values cannot be used for secondary ions, organic matter, and elemental carbon. Enrichment factors (EFBC) for the main components of PM10 were calculated according to Equation (2). The concentration of water-soluble ions was normalized to PM10 concentrations. The background values were measured at the locality Olomouc. The results are shown in Table 2. The equation for calculation of the enrichment factor in PM10: Figure 4. Average composition percentages of PM 10 during the period of acceptable and exceeded pollution. Explanations: Water soluble inorganic ions (WSIIs), organic matter (OM), elemental carbon (EC), trace elements (TE), mineral dust (MD). The parameter MD expresses a total (mass) concentration (with certain assumptions regarding the chemical composition of the dust) of insoluble inorganic particles (mineral phases and amorphous inorganic phase). It was used for the construction of Figure 4in order to obtain a total composition of particles (100%). The origin of elements included in the MD parameter in the Ostrava region is from both blast furnaces and the combustion of fossil fuels. The average pollutant content in PM 10 implies that during the period of exceeded pollution, the content of organic substances 43.1 ± 12% is higher by about 7%, which is compensated by the loss of water-soluble ions (Figure 4). Increased OM shares of PM 10 during smog situations have also been observed in Switzerland [32]. In the region of Ostrava, analyses of organic compounds have shown that the beginning of the smog episode is accompanied by an increase of the percentage of an unresolved complex mixture of hydrocarbons (UCM) and organic matter which cannot be reliably identified. The combustion processes are the most important source of particles PM 10 and OM during both acceptable pollution and exceeded pollution. The combustion processes include the combustion of coal (lignite, bituminous coal and mixtures of both), biomass and waste (polymers—plastics). Organic compounds of sulphur occurred in all samples of PM 10 during both acceptable pollution and exceeded pollution in areas with the combustion of coal. The number of organic compounds of sulphur in a deposition during exceeded pollution is two or three times higher than during acceptable pollution. The locality O-MH is characterised by high emissions from transport for both acceptable pollution and exceeded pollution. The locality O-P has similar characteristics. The combustion of biomass prevails among combustion processes. The difference in OM between acceptable pollution and exceeded pollution is not conspicuous. However, individual organic compounds connected with the combustion processes have increased concentrations. During exceeded pollution, EC is not increased despite the fact that it can be expected. This is connected to the fact that the combustion processes play an important role in the winter season even during acceptable pollution (the results of the authors’ team will be published during the year 2020). 3.1. Enrichment Factors for the Main Components in PM10 in Respect to the Background Values The aim of determination of enrichment factors (EF BC ) for the main components was the comparison of their normalized concentrations in PM 10 with background values. The background values were utilised because Clarke values cannot be used for secondary ions, organic matter, and elemental carbon. Enrichment factors (EF BC ) for the main components of PM 10 were calculated Int. J. Environ. Res. Public Health 2020,17, 3447 8 of 26 according to Equation (2). The concentration of water-soluble ions was normalized to PM 10 concentrations. The background values were measured at the locality Olomouc. The results are shown in Table 2. The equation for calculation of the enrichment factor in PM10: EFBC =Cx PM10 measured Cx PM10 background (2) where Cxare the concentrations of the element xin PM10. Table 2. Enrichment factors for the period of acceptable and exceeded pollution using the background values of Olomouc. Localities Cl−SO42−NO3−NH4+Na+K+Ca2+Mg2+EC OM Acceptable pollution (AP) OR-NO 2.14 0.92 1.30 3.70 0.69 1.30 1.96 0.78 1.14 0.99 OR-OZO 1.14 0.88 1.81 3.81 0.27 1.01 1.30 0.68 0.83 1.29 O-MH 0.57 0.99 2.24 4.34 0.23 1.05 0.53 0.32 0.69 1.33 O-P 0.78 0.86 2.32 5.16 0.60 1.02 0.69 0.57 1.04 1.24 S 0.48 0.74 1.97 3.48 0.43 1.02 0.93 0.64 0.84 1.41 DL 0.45 0.93 2.13 4.06 0.34 0.94 0.58 0.53 0.70 1.31 V 0.41 0.55 1.18 2.13 0.71 0.58 0.88 0.39 0.44 0.73 MCT 0.87 1.06 1.63 3.52 0.52 1.30 0.80 0.64 1.15 1.91 AVG-AP 0.88 0.92 1.91 3.96 0.46 1.08 0.96 0.59 0.92 1.37 Exceeded pollution (EP) OR-NO 1.23 0.94 1.51 3.38 0.27 1.17 1.14 0.74 1.11 1.91 OR-OZO 1.06 0.85 1.53 3.29 0.13 0.75 0.52 0.26 1.18 1.89 O-MH 1.09 1.07 1.87 4.36 0.12 0.78 0.44 0.25 1.05 1.68 O-P 0.67 1.03 1.89 3.85 0.18 0.88 0.37 0.28 1.04 1.57 S 0.50 1.02 1.81 3.94 0.19 0.96 0.65 0.40 0.73 1.51 DL 0.54 1.08 1.64 3.67 0.20 0.96 0.47 0.41 0.96 1.61 V 0.86 0.68 1.14 2.77 0.13 0.66 0.27 0.18 0.98 1.55 MCT 0.94 1.00 1.48 3.76 0.16 0.81 0.39 0.34 0.97 1.75 AVG-EP 0.87 0.96 1.61 3.65 0.17 0.88 0.53 0.36 1.01 1.70 Explanations: AVG-AP the arithmetical means for acceptable pollution; AVG-EP the arithmetical means for exceeded pollution. The enrichment factors for sulphates and chlorides in PM 10 have in the periods of acceptable and exceeded pollution the comparable values. Organic matter has lower EF BC in the period of acceptable pollution compared with the period of exceeded pollution. On the contrary, NH 4+ , NO 3− , Ca 2+, Mg 2+ , K + , Na + have different behaviour and their EF BC have relatively lower values in the period of exceeded pollution. The increased concentrations of PM 10 during the exceeded pollution period result in lower concentrations of these ions. Enrichment factors show variability in some parameters, even when comparing individual localities (Table 2). A significantly higher enrichment factor for all monitored parameters except nitrates and ammonium ions was found for OR-NO and OR-OZO in the period of exceeded pollution. The highest enrichment factor for nitrates was found for the locality O-P, which is mainly affected by transport emissions. In the period of acceptable pollution, it also shows the highest enrichment factor for EC. The addition of normalized values shows that in the period of acceptable pollution, Veˇrˇnovice (V) belongs to the localities with the highest occurrence of anomalous concentrations. In the period of exceeded pollution, it is Radvanice (OR). Int. J. Environ. Res. Public Health 2020,17, 3447 9 of 26 3.2. Enrichment Factors of Trace Elements For trace elements, the enrichment factor was calculated using the standard procedure according to Equation (3): EFx=Cx Cref PM Cx Cref crust (3) where C x and C ref are the concentrations of the element xin PM 10 , and the reference element, (C x /C ref ) PM and (C x /C ref ) crust are the proportions of these concentrations in PM and in the Earth’s crust, respectively. The concentration of elements in the Earth’s crust (Clarke value) was used in accordance with Wedepohl [ 33 ]. Aluminium was used as a reference for comparing EF values with other localities in the Czech Republic (Olomouc). If the EF value >1, the element is assumed to be relatively enriched in the environment; if EF >5, the element comes from anthropogenic sources [ 34 ], the EF value ranging from 20 to 40 is considered very high, and EF >40 extremely high [35]. Cadmium exhibits an extremely high enrichment factor (14,500) in locations affected by the metallurgical industry OR-OZO, OR-NO, and O-MH. The EF Cd was five times higher than the value found for Olomouc (Figure 5). In other locations, Cd concentrations were below detection. Cadmium is one of the elements usually exhibited by the high enrichment factor >1000 [36]. Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 9 of 27 3.2. Enrichment Factors of Trace Elements For trace elements, the enrichment factor was calculated using the standard procedure according to Equation (3): 𝐸𝐹=𝐶𝐶  𝐶𝐶  (3) where Cx and Cref are the concentrations of the element x in PM10, and the reference element, (Cx/Cref)PM and (Cx/Cref)crust are the proportions of these concentrations in PM and in the Earth’s crust, respectively. The concentration of elements in the Earth’s crust (Clarke value) was used in accordance with Wedepohl [33]. Aluminium was used as a reference for comparing EF values with other localities in the Czech Republic (Olomouc). If the EF value ˃ 1, the element is assumed to be relatively enriched in the environment; if EF ˃ 5, the element comes from anthropogenic sources [34], the EF value ranging from 20 to 40 is considered very high, and EF ˃ 40 extremely high [35]. Cadmium exhibits an extremely high enrichment factor (14,500) in locations affected by the metallurgical industry OR-OZO, OR-NO, and O-MH. The EFCd was five times higher than the value found for Olomouc (Figure 5). In other locations, Cd concentrations were below detection. Cadmium is one of the elements usually exhibited by the high enrichment factor ˃1000 [36]. Figure 5. Enrichment factor for trace elements—comparison with Olomouc in the period with acceptable pollution. For chromium, the values of the EF in PM10 are usually in the range of 10–100 [36]. In MSK sites, EFCr values vary in the range of 100 to 300, the lowest EFCr value was found in Olomouc 13. The values of the EF for Cu and Zn are usually around 100 [36]. For sites in MSK, value of EFCu are lower than the value reported Di Vaio et al. [36] in the range of 10–30, while in Olomouc it reaches a value of up to 70. Transport is considered to be the main source of Cu in PM10 particles. EFZn values in MSK are 20 to 40 times and for Olomouc three times higher than EFZn according to Di Vaio et al. [36]. The source of Zn may be the burning of fossil fuels, biomass, transport and, in the case of MSK, the metallurgical industry. EFPb values for in MSK range from 2.0 to 3.0, which is 20–30 times higher than the EF value reported by Di Vaio et al. [36] ˃ 100. A minimum EF of less than 10 is given by Di Vaio et al. [36] for elements of crustal origin Fe (4) and Mn (8). In the case of Fe, the EF in PM10 in the MSK region reaches values in the range of 10–13 and for Olomouc 3. EFMn values show a large range from 10 to 100, except for the MCT site where EF is 800. The background locality Olomouc has an even lower EFMn in PM10 than value published by Di Vaio et al. [36]. The high EF values for Mn are related Figure 5. Enrichment factor for trace elements—comparison with Olomouc in the period with acceptable pollution. For chromium, the values of the EF in PM 10 are usually in the range of 10–100 [ 36 ]. In MSK sites, EF Cr values vary in the range of 100 to 300, the lowest EF Cr value was found in Olomouc 13. The values of the EF for Cu and Zn are usually around 100 [ 36 ]. For sites in MSK, value of EF Cu are lower than the value reported Di Vaio et al. [ 36 ] in the range of 10–30, while in Olomouc it reaches a value of up to 70. Transport is considered to be the main source of Cu in PM 10 particles. EF Zn values in MSK are 20 to 40 times and for Olomouc three times higher than EF Zn according to Di Vaio et al. [ 36 ]. The source of Zn may be the burning of fossil fuels, biomass, transport and, in the case of MSK, the metallurgical industry. EF Pb values for in MSK range from 2.0 to 3.0, which is 20–30 times higher than the EF value reported by Di Vaio et al. [ 36 ]>100. A minimum EF of less than 10 is given by Di Vaio et al. [ 36 ] for elements of crustal origin Fe (4) and Mn (8). In the case of Fe, the EF in PM 10 in the MSK region reaches values in the range of 10–13 and for Olomouc 3. EF Mn values show a large range from 10 to 100, except for the MCT site where EF is 800. The background locality Olomouc has an even lower EF Mn in PM 10 than value published by Di Vaio et al. [ 36 ]. The high EF values for Mn are related to the metallurgical Int. J. Environ. Res. Public Health 2020,17, 3447 16 of 26 Table 3. Comparison of concentrations of inorganic aerosols and other water-soluble ions in dust particles in the atmosphere of European cities (µg/m3). Location Period of Sampling PM10 EC OC SO42−NO3−NH4+Cl−Na+K+Ca2+Mg2+References Poland 2007 11.99 - - 2.41 2.06 1.1 - 0.12 0.03 0.03 1.10 [95] United Kingdom 2007 11.94 - - 1.53 1.87 0.65 - 1.81 0.60 0.70 0.16 Zabrze (Poland); urban background 8–12 2008 - - - 1.93 1.05 0.96 0.78 0.27 0.19 0.35 0.79 [96] Zagreb (Croatia); residential-industrial-traffic site 2006 - - - - - - 0.16 0.30 0.12 0.14 0.05 [97] Melpitz (Germany); rural background Winter 2004–2008 - - - - - - 0.57 0.43 0.18 0.11 0.07 [98] Venice, Italy Winter 2006 69.00 - - 3.63 10.93 3.68 - - 1.02 1.35 0.16 [99] Praha-Libuš (Czech Republic) Winter 04.2008–03.2009 26.68 1.59 5.99 2.86 3.15 1.67 0.22 0.16 0.13 0.22 0.03 [100] Augsburg (Germany) Winter (14.11.2007–31.3.2008) 42.70 4.44 4.182 2.285 6.77 2.515 1.836 1.19 [101] OR-NO Average concentration– Acceptable pollution 45.23 2.34 8.16 3.87 5.56 3.73 2.45 0.71 0.58 1.45 0.11 This study OR-OZO 36.09 1.29 9.58 2.80 6.51 3.27 1.20 0.23 0.38 0.88 0.09 O-MH 30.35 0.98 8.14 2.87 6.50 3.06 0.42 0.15 0.31 0.26 0.03 O-P 35.00 1.61 7.74 2.64 8.32 4.22 0.51 0.38 0.37 0.43 0.06 S 32.02 1.13 7.85 2.43 6.57 2.82 0.37 0.26 0.31 0.42 0.06 DL 35.46 1.16 8.36 3.18 7.13 3.25 0.40 0.26 0.32 0.33 0.06 V 24.13 0.87 5.88 1.99 4.88 2.08 0.37 0.35 0.26 0.36 0.04 MCT 26.66 1.39 9.25 2.61 4.10 2.09 0.59 0.31 0.34 0.35 0.05 OR-NO Average concentration– Exceeded pollution 92.01 4.56 29.40 8.16 13.21 7.15 2.84 0.59 0.95 1.76 0.20 OR-OZO 89.38 4.07 29.32 8.30 13.91 7.50 2.35 0.28 0.61 0.72 0.06 O-MH 73.49 3.63 21.20 7.44 13.53 7.61 1.85 0.20 0.57 0.51 0.05 O-P 83.93 4.12 25.74 8.26 15.04 7.57 1.56 0.49 0.72 0.57 0.08 S 78.40 2.72 20.91 7.54 13.18 6.94 0.96 0.34 0.71 0.85 0.09 DL 69.85 3.18 21.27 7.23 11.14 5.94 0.86 0.33 0.66 0.54 0.09 V 120.1 6.05 37.66 9.06 14.63 8.70 3.09 0.39 0.88 0.63 0.07 MCT 127.3 5.59 41.14 11.80 17.82 10.62 3.06 0.44 0.94 0.67 0.11 Olomouc November 2018 13.27 0.6 3.37 1.23 1.25 0.30 0.34 0.30 0.13 0.22 0.04 Int. J. Environ. Res. Public Health 2020,17, 3447 17 of 26 Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 15 of 27 (0.25 ± 0.07) indicate the more intense secondary formation of nitrate in the period of exceeded pollution than in the period of acceptable pollution. A significant correlation relationship was found between NOR and O3 (r = −0.70). At the same time, a significant correlation was found between relative air humidity and both SOR (r = 0.74) and NOR (r = 0.90). The SOR and NOR exhibited an inverse correlation relationship with the temperature (r = −0.67 and r = −0.65 respectively). A similar dependence is reported by Zhao et al. [87]. During the period of exceeded pollution, there is an increase of NOR in all localities (Figure 6) approximately 1.7 times. The most significant increase (2.4 times) was recorded in the locality MCT. During the period of exceeded pollution, the average increase in SOR is 1.8 times. Figure 6. (A) Average values of sulphur oxidation ratio (SOR) and (B) nitrogen oxidation ratio (NOR) for acceptable pollution and exceeded pollution. Nitrates range between 0.63 µg/m3 to 11.3 µg/m3 in the period of acceptable pollution, and in the period of exceeded pollution, their concentrations increase up to 6.26 - 28.0 µg/m3. The highest average nitrate concentrations in the period of acceptable pollution were found for the locality O-P (8.3 ± 4.4 µg/m3), where concentrations are affected by traffic. In the period of exceeded pollution, the highest average concentrations were measured in the localities of MCT (17.8 ± 8.6 µg/m3) and V (14.6 ± 6.7 µg/m3), localities affected mainly by residential heating. The nitrate concentration in the background locality in Olomouc was 1.25 ± 0.52 µg/m3 (Table 3). Primarily, chlorides are a significant component of aerosol in the marine environment [88]. They are released as a result of various anthropogenic activities (coal and biomass combustion, hydrochloric acid production, paper production, chlorine-containing plastics). Chlorides are an important part of the dust particles released in the sintering of Fe-ores, which can contain up to 30% [89]. The origin of chlorides from biomass combustion is determined by the correlation dependences between potassium and levoglucosan (thermal decomposition product of starch and cellulose) [90], chloride with levoglucosan (r = 0.58, n = 66, α = 0.05), and chloride with potassium (r = 0.70, n = 68, α = 0.05). In the period of acceptable pollution, the highest chloride concentration in IA was measured in the locality OR-NO with an average of 2.46 ± 1.58 µg/m3. The highest average concentration was found in the locality V (3.09 ± 2.05 µg/m3) and MCT (3.06 ± 2.83 µg/m3). The annual average background chloride concentration for Olomouc is 0.34 ± 0.14 µg/m3. The maximum chloride concentrations in the localities V and M are about nine times higher than the background value in Olomouc (Table 3). In the period of acceptable pollution, a statistically significant dependence between Cl− and NH4+, Na+, K+, EC, SO42−, SO2, and NOX was found, and in the period of exceeded pollution, a dependence was also found between NO3−, PO43−, and OM (r ˃ 0.62). Linear regression analysis with levoglucosan was performed to identify biomass combustion. Levoglucosan provided statistically significant correlation coefficient values not only for sulphates (r = 0.92), but also for potassium (r = 0.68) and chlorides (r = 0.80). Chlorides come from both coal combustion [91] and biomass combustion [92]. The study Yudovich and Ketris [93] said that world average Cl contents in coals (coal Clarke of Cl) for hard and brown coals are, respectively, 340 ± 40 and 120 ± 20 mg/kg. Moreover, the study by Jagustyn Figure 6. ( A ) Average values of sulphur oxidation ratio (SOR) and ( B ) nitrogen oxidation ratio (NOR) for acceptable pollution and exceeded pollution. 3.5. Carbonaceous Particles of PM10 Carbonaceous species, organic carbon (OC) and elemental carbon (EC), constitute a major, sometimes dominant, fraction of atmospheric particulate matter [ 102 ]. Elemental carbon is released into the atmosphere solely as a product of primary origin from the incomplete combustion of fossil fuels and biomass, but also from transport [ 103 ]. EC has a graphite-like microcrystalline structure, is refractory and strongly light-absorptive, which influenced enhancing the hydrophilicity of soot particles in PM 10 with major environmental effects [ 104 ]. Organic carbon is emitted into the atmosphere from anthropogenic or biogenic sources such as primary organic carbon (POC), or it may be of secondary origin (SOC). Secondary organic carbon is formed by condensation of organic compounds formed during photochemical reactions in the air, conversion of gas-particle from volatile organic compounds with low vapour pressure, physical and chemical adsorption [ 105 ]. The amount of organic matter in PM 10 is calculated from the OC concentration by multiplying by the factor 1.4. The OC/EC ratio is used for classifying different sources [ 106 ]. At the background locality Olomouc, the average OC concentration is 2.41 ± 1.08 µ g/m 3 , and the winter concentration is about 30% higher. The average annual EC concentration is 0.61 ± 0.34 µ g/m 3 . Winter concentration is also about approximately 30% higher. The OC/EC ratio for winter is 7.5, which is within the range for residential raw-coal combustion in China: OC/EC =2.5–10 [ 107 ]. The OC concentration during the period of exceeded pollution is higher when we compare with other parts in Europe (Table 3). The variability of OC content in PM 10 is significant during the period of acceptable and exceeded pollution. During the period of exceeded pollution, the OC concentration is higher (2.6 to 6.4 times) compared to the period of acceptable pollution (Figure 2). The lowest differences in organic matter concentration during the period of acceptable and exceeded pollution were found for the localities DL, S and O-MH. The average OC concentration during the period of acceptable pollution was 8.24 ± 4.54 µ g/m 3 (24.4 ± 8.41% from PM 10 ), the average organic matter concentration (OM) was 10.9 ± 5.86 µ g/m 3 (32.5 ± 10.6% from PM 10 ) and EC 1.26 ± 0.63 µ g/m 3 (3.91 ± 1.28% from PM 10 ). The average OC concentration for the period of exceeded pollution reaches the value of 28.7 ± 13.4 µ g/m 3 (30.8 ± 6.95% from PM 10 ), for OM 39.1 ± 18.5 µ g/m 3 (41.7 ± 7.94% from PM 10 ), for EC 4.30 ± 2.25 µ g/m 3 (4.58 ± 1.51% from PM 10 ). In the analysed group, the average OC/EC value ranges from 6.37 to 7.90, which corresponds to the burning of fossil fuels. When comparing the average concentration of OC and EC in the period of acceptable pollution with the background value in Olomouc, the increase is 3.4, and for EC, it is 2.1. In the period of exceeded pollution, the increase for OC is 11.9 × and for EC 7.2 × . Significant Spearman correlation dependence between EC, OC and wind speed, relative humidity, sulphates, nitrates, ammonium ions, and potassium were found during the period of acceptable pollution. For EC, a statistically significant dependence with chlorides was proven, which shows the effect of combustion processes. In the period of exceeded pollution, there were also statistically significant dependencies of the direction of wind and concentrations of chlorides. Int. J. Environ. Res. Public Health 2020,17, 3447 18 of 26 3.6. Impact Evaluation of the Meteorological Condition A predominant airflow of “relatively cleaner air from less polluted areas of the Czech Republic” from the southwest is typical of the area of northeast Moravia in the Czech Republic and is related to the orographic influence of the Moravian Gate (Figures 7and 8). Conversely, northeast and variable wind mass flow with low wind velocities are associated with anticyclonic situations (high-pressure systems), and they are often accompanied by deteriorated dispersion conditions, especially during the cold period of the year. Generally, during predominantly good dispersion conditions, the pollutants are usually transported from the Czech Republic into Poland, whilst during predominantly worsened dispersion conditions, it is the opposite [17]. Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 19 of 27 Figure 7. The wind rose for O-P: (A) years 2012–2018; (B) year 2018 and (C) December 2017–February 2018. Figure 8. The wind rose for MSR for (A) Exceeded pollution, (B) Acceptable pollution. Exploratory data analysis (EDA) was performed to evaluate the similarity of individual localities in terms of air pollution load. When using cluster analysis, the collected PM10 samples were divided according to the airflow direction. This division has proven to be essential since it affects the amount of PM10 and thus its composition. Differences in the amount and composition of PM10 for different wind directions are shown in Figure 9. Figure 7. The wind rose for O-P: ( A ) years 2012–2018; ( B ) year 2018 and ( C ) December 2017–February 2018. Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 19 of 27 Figure 7. The wind rose for O-P: (A) years 2012–2018; (B) year 2018 and (C) December 2017–February 2018. Figure 8. The wind rose for MSR for (A) Exceeded pollution, (B) Acceptable pollution. Exploratory data analysis (EDA) was performed to evaluate the similarity of individual localities in terms of air pollution load. When using cluster analysis, the collected PM10 samples were divided according to the airflow direction. This division has proven to be essential since it affects the amount of PM10 and thus its composition. Differences in the amount and composition of PM10 for different wind directions are shown in Figure 9. Figure 8. The wind rose for MSR for (A) Exceeded pollution, (B) Acceptable pollution. Exploratory data analysis (EDA) was performed to evaluate the similarity of individual localities in terms of air pollution load. When using cluster analysis, the collected PM 10 samples were divided according to the airflow direction. This division has proven to be essential since it affects the amount of PM 10 and thus its composition. Differences in the amount and composition of PM 10 for different wind directions are shown in Figure 9. In addition to the airflow from Poland, the direction of flow from Hungary through Slovakia is also significant, as is the direction from the Ruhr area (Germany) through Poland. Air mass flow was obtained from a database of the Czech Hydrometeorological Institute and calculated using the HYSPLIT modelling system for simple air particle trajectories [ 108 ]. The average composition of PM 10 in the days when all localities were affected by the same wind direction (204–232) from MG is in Figure 10. In these climatic conditions, the localities of V, MCT, S and DL may be considered background localities. Similarly, the contribution from transport in the locality O-P can be calculated by comparison with the background value S (23%) of PM 10 . The difference in concentrations shows that at most localities, in the case of airflow from Poland, the concentrations of water-soluble ions decreased by 12.86 ± 8.31% and the content of “others”, which mainly represents resuspension particles and amorphous fly ash particles formed by silicates or Fe-oxide matrix by 7.21 ± 5.50%. The exception is the locality V, where the share of “others” increased by about 28%. The EC content increased by 1.04 ± 0.56%, the organic matter content by 14.50 ± 10.03%. Increasing the content of OM and EC Int. J. Environ. Res. Public Health 2020,17, 3447 19 of 26 carbonaceous particles at the expense of WSIIs may pose significant health risks when carried into the respiratory system from inhalation of particulates because they can contain high concentrations of polycyclic aromatic hydrocarbons [ 109 ]. Heavy metals can act as a catalyst to stimulate the formation of secondary ions [ 110 ]. The comparison of the share of ion concentrations in airflow from Poland and airflow from Moravian Gate shows that in the case of airflow from Poland, in the locality OR-NO, which is affected by the production of iron and steel in Arcelor Mittal, there is no increase in the concentration of Cl − , Na + , K + , and Ca 2+ produced within the production technology at a higher rate than is carried by long-distance transport (Figure 10). The highest enrichment was found in chlorides (2.13–12.88) in O-MH. Sulphates are enriched 1.7–3.6 times (V), ammonium ions and nitrates exhibit lower enrichment (1.27–2.02). Enrichment of these ions is related to the combustion of fossil fuels. Significant is the increase in organic compounds, which ranges from 1.58–6.71 for organic matter with an average of 3.53. In order to identify the influence of Arcelor Mittal in the locality OR-NO, the concentration values measured during airflow from Moravian Gate in the locality OR-OZO were selected. The difference between the concentrations of PM 10 , ions and EC, OC at both sites shows that Arcelor Mittal contributes to increasing the concentrations of K + , Ca 2+ (1.2–3%), Cl − (5–6%), EC and NH4+(6–7%), SO42−and NO3−(10–11%), and OM (48–53%). Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 19 of 27 Figure 7. The wind rose for O-P: (A) years 2012–2018; (B) year 2018 and (C) December 2017–February 2018. Figure 8. The wind rose for MSR for (A) Exceeded pollution, (B) Acceptable pollution. Exploratory data analysis (EDA) was performed to evaluate the similarity of individual localities in terms of air pollution load. When using cluster analysis, the collected PM10 samples were divided according to the airflow direction. This division has proven to be essential since it affects the amount of PM10 and thus its composition. Differences in the amount and composition of PM10 for different wind directions are shown in Figure 9. Figure 9. The composition of PM 10 during different air flowing (MG—Moravian Gate) for all measurements, AVG—average. Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 20 of 27 Figure 9. The composition of PM10 during different air flowing (MG—Moravian Gate) for all measurements, AVG—average. In addition to the airflow from Poland, the direction of flow from Hungary through Slovakia is also significant, as is the direction from the Ruhr area (Germany) through Poland. Air mass flow was obtained from a database of the Czech Hydrometeorological Institute and calculated using the HYSPLIT modelling system for simple air particle trajectories [108]. The average composition of PM10 in the days when all localities were affected by the same wind direction (204–232) from MG is in Figure 10. In these climatic conditions, the localities of V, MCT, S and DL may be considered background localities. Similarly, the contribution from transport in the locality O-P can be calculated by comparison with the background value S (23%) of PM10. The difference in concentrations shows that at most localities, in the case of airflow from Poland, the concentrations of water-soluble ions decreased by 12.86 ± 8.31% and the content of “others”, which mainly represents resuspension particles and amorphous fly ash particles formed by silicates or Fe-oxide matrix by 7.21 ± 5.50%. The exception is the locality V, where the share of “others” increased by about 28%. The EC content increased by 1.04 ± 0.56%, the organic matter content by 14.50 ± 10.03%. Increasing the content of OM and EC carbonaceous particles at the expense of WSIIs may pose significant health risks when carried into the respiratory system from inhalation of particulates because they can contain high concentrations of polycyclic aromatic hydrocarbons [109]. Heavy metals can act as a catalyst to stimulate the formation of secondary ions [110]. The comparison of the share of ion concentrations in airflow from Poland and airflow from Moravian Gate shows that in the case of airflow from Poland, in the locality OR-NO, which is affected by the production of iron and steel in Arcelor Mittal, there is no increase in the concentration of Cl−, Na+, K+, and Ca2+ produced within the production technology at a higher rate than is carried by long-distance transport (Figure 10). The highest enrichment was found in chlorides (2.13–12.88) in O-MH. Sulphates are enriched 1.7–3.6 times (V), ammonium ions and nitrates exhibit lower enrichment (1.27–2.02). Enrichment of these ions is related to the combustion of fossil fuels. Significant is the increase in organic compounds, which ranges from 1.58– 6.71 for organic matter with an average of 3.53. In order to identify the influence of Arcelor Mittal in the locality OR-NO, the concentration values measured during airflow from Moravian Gate in the locality OR-OZO were selected. The difference between the concentrations of PM10, ions and EC, OC at both sites shows that Arcelor Mittal contributes to increasing the concentrations of K+, Ca2+ (1.2– 3%), Cl− (5–6%), EC and NH4+ (6–7%), SO42− and NO3− (10–11%), and OM (48–53%). Figure 10. The chemical composition of PM 10 particles (%) for airflow from Moravian Gate (MG) and Poland. Int. J. Environ. Res. Public Health 2020,17, 3447 20 of 26 4. Conclusions The influence of iron and steel production in the Silesia region (both Czech and Polish part) is reflected in a significant increase in enrichment factor (Clarke value). Enrichment factor for Cd (15,000) is enormously high, about three times higher than the value calculated in North-Western European cities and five times higher than in Olomouc. Significantly higher values of EF were found for Cu (1420), Pb (2990), and Zn (4282), which is 20 times more Cu than for the background locality Olomouc, seven times more Pb and 12 times more Zn. The influence of Fe and steel production was demonstrated by the presence of Pb-Cl-OC particles in air concentrations. The use of EDA (cluster analysis) for the analysed sample showed that the analysed samples are grouped according to the direction of the wind flow, which in the case of the airflow from Moravian Gate shows very low PM 10 air pollution. On the contrary, wind from the NE direction is primarily due to the high air pollution load, which is characterized by an increased proportion of OC (up to 14.5 ± 10.3%) at the expense of decreasing WSIIs. An increase in OC share represents a higher health risk due to PAHs and trace elements binding. By comparing the background concentration in the area (comparison of OR-NO and OR-OZO), the share of Arcelor Mittal Ostrava (now Liberty Ostrava), which is 45 ± 8 µ g/m 3 under optimal dispersion conditions, was identified. Some elements of WSIIs, Na + , Ca 2+ , and partly also K + and Cl − , which are also bound to other processes (biomass combustion), can be considered as indicator elements, showing the significance of pollution from iron and steel production. Supplementary Materials: The following are available online at http://www.mdpi.com/1660-4601/17/10/3447/s1, Figure S1: The figures of the sampling site (without locality DL) and their location on the map, Table S1: Characteristics of the localities. Author Contributions: Conceptualization, H.R.; methodology, K.R. and M.K. (Miroslav Koliba); software, B.Š. and M.K. (Marek Kucbel); validation, K.R.; investigation, B.Š., J.R., M.K. (Marek Kucbel) and M.K. (Miroslav Koliba) writing—original draft preparation, H.R., B.Š., M.K. (Marek Kucbel), D.J. and J.R.; writing—review and editing, K.R.; visualization, B.Š. and M.K. (Marek Kucbel); supervision, H.R. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the LTI19002 “Participation of Czech research organizations in European Alliance for research in energy EERA-CZ 2”; Project of Moravian-Silesian Regional Authority “Identification of the contribution of pollutants to air quality under poor dispersal and good dispersal conditions (DNA of smog)”. Acknowledgments: This study was supported by the research projects of the Ministry of Education, Youth and Sport of the Czech Republic: CZ.1.05/2.1.00/19.0389: Research Infrastructure Development of the CENET; RRC/10/2018 “Support for Science and Research in the Moravian-Silesian Region 2018” and SP2020/22 “Innovative methods for monitoring particulate matter from combustion processes”. Conflicts of Interest: The authors declare no conflict of interest. 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