Possible Health Effects of Road Dust in Winter: Studies in Poland

Abstract

Urban road dust is an increasingly important source of air pollution and poses a serious threat to human health. In Poland, the urban road dust (URD) problem is enhanced by the use of old generation transport vehicles and transport systems. Seasonal variation in URD-bound elements is not well-known in Poland and controlling their pollution level can be a tough task. Therefore, studies on winter dust pollution will help to understand the sources of URD and take appropriate measures to reduce road dust emissions in the future. We analysed the relative content of heavy metals in two representative regions of Poland, Lower and Upper Silesia, and evaluated the sources of the contamination with the following pollution indices: Enrichment Factor (EF), Geoaccumulation Index (Igeo), pollution index (PI), and Pollution Load Index (PLI). We assessed the health risk for inhabitants due to the exposure to toxic metals through URD. We found that both studied regions are quite heavily polluted in winter. Our studies clearly show that the URD-bound elements level is much higher in Upper Silesia than in Lower Silesia in winter. The results of this study are useful for researchers to bridge the gap on the pollution of elements in URD from Poland, where there is a lack of such data.

1. Introduction

Urban road dust (URD) is one of the most important sources of particles in the atmosphere, and it is emitted mainly from moving vehicles (mainly those that are stuck in traffic jams, which are arising and constantly increasing in cities) and other sources that are part of the continuously existing road flow, which depends on many coexisting factors, including atmospheric factors [1,2]. In cities, it is also apparent that the problem of URD itself has been exacerbated by various other types of pollution, mainly from industries located nearby, caused by actions such as: the combustion process of fuel, often connected to the energy and heating sectors and industries, such as cement plants, mines, steel mills, refineries, and chemical and metallurgical plants, which further worsens the state and quality of the air [3,4]. Resuspended URD consists of toxic elements and is one of the most important sources of course, fine, and ultrafine particles in the air, especially in cities with a high density of roads [1]. URD may also be subject to the re-suspension of certain particles during standard vehicle functioning and mobility or during variable wind conditions [5]. Air pollution resulting from the activity of vehicles is one of the most significant problems of modern and huge cities, affecting the health of living organisms and the environment to a tremendous extent, reaching in some sources as much as two-thirds of all pollution in cities, largely due to rush hours. Air pollution caused by car traffic accounts for about 60% of air pollution [6,7,8]. The elevated level of air pollution is observed in underground car parks, tunnels, near petrol stations, and in the vicinity of busy road sections, which affects the soil nearby. URD from transport may also be caused by friction of, e.g., tires or brake pads, which rub during use of the vehicle, and their residues can be identified in URD [9]. URD easily enters the human body through ingestion, inhalation, and dermal contact due to its small particle size (the most dangerous are PM_2.5 fine inhalable particles, with diameters 2.5 μm and smaller), especially during windy weather [10,11].

Therefore, it is crucial to study URD’s characteristics and assess its potential health risk to humans [12]. The need to constantly develop road transport networks results in an increased amount of URD which is deposited in close proximity to roads [13,14,15]. In studies of different Polish cities, including those with the use of biomonitors [16,17], compared with studies of cities from all over the world, a certain unevenness was observed in the distribution of specific heavy metals in the city (with exceedances for the geochemical background of Poland), but with values comparable or higher for similar cities in the world [18,19]. It can be concluded that the differences in the cites may be due to the cumulative effect of a number of factors observed at the sampling sites, such as the presence of road transport (including public transport such as trams and railways) and its intensity, the use of different types of heating, the type and quality of infrastructure, and the distance from industrial sites [15,18,20,21]. Apart from heating influence, it is well-known that winter temperature, humidity, and precipitation also increase the level of URD. The studies of Gustafsson et al. [22] suggest that winter sanding is also an important source of URD. Therefore, many cities try to limit URD emissions by reducing car speeds, banning the use of studded tires and sand, using stronger bitumen asphalt, and introducing special dust-binding and chemical agents for these purposes. In Poland, such solutions have not been applied thus far. Moreover, the seasonal variation in URD-bound elements, spatial distributions, and sources of metals in URD has not been thoroughly studied in Poland. Therefore, it is essential to assess the impact of URD on adverse health effects in Poland and the level of toxic agents such as metal elements or polycyclic aromatic hydrocarbons (PAHs) coming with URD in winter. Such studies on winter dust pollution will help to understand the sources of URD and control road dust emissions to reduce them in the future.

The aim of this study was to present a comprehensive health risk assessment in two selected areas that can be characterised by a high level of URD: Upper and Lower Silesia in Poland. Air pollution and the URD level in the Upper Silesia agglomeration is a key problem that has been studied many times [23,24]. The second region, Lower Silesia with its capital Wrocław, can be characterised by a predomination of households’ air pollution [20]. Emission from heat and power plants also significantly influences PM₁₀ norms, especially during the heating season, which directly influences the URD level (concentration standards recommended by the World Health Organization are as follows: for an average 24 h standard PM₁₀ dust concentration: 50 µg/m³ and standard of average annual PM₁₀ dust concentration: 20 µg/m³). Therefore, we focused on URD and selected URD-bound elements such as: Al, Zn, Cr, Cd, Co, V, Mn, Mg, Pb, As, Ni, and Cu. We carried out our studies in the winter when the URD level was higher. Similar studies have already been carried out for both regions during summer [25], and we assumed that the weather will have a key impact on the level of pollution in both regions. Such a comprehensive analysis could greatly contribute to the successful future management of air pollution and climate protection in both regions.

2. Materials and Methods

2.1. Sample Collection

We collected URD samples by sweeping dust off the road into a sterile container with a brush. At each site, URD sampling consisted of subsamples to assure representativeness for every studied site. We collected six subsamples from one site. According to our previous studies [25], we took half of the samples at one side of the road and the other half on the opposite side. The maximum distance between subsampling points was about 20 m. At intersections, we took four samples in the corners of the intersection, and two samples near the middle point. Altogether, 36 samples of 20 g were taken from all sites. We conducted sampling in February 2020, at selected six sites: three in the Lower Silesia and Upper Silesia regions (sampling was restricted to three sites at each region because of the severe weather conditions and difficulties with sample collection due to COVID-19). Table S1 (Supplementary Materials) and Figure 1 show the complex characteristics of chosen sampling sites.

2.2. General Characteristics of the Sampling Regions

Sampling of URD was performed in the largest Polish urban agglomerations, Upper and Lower Silesia. In both regions, we selected three sites each (in Lower Silesia 1–3 and in Upper Silesia 4–6), Table S1. Site selection was based on the type of environment and the nearest type of neighbourhood with separate PM sources.

Lower Silesia, with the main city of Wrocław, the capital of the Voivodeship, is inhabited by over 640,000 people (data from the Central Statistical Office for June 2020) within an area of 292.8 km². The population density is 2195 people/km². The city has 852.4 km of municipal and district roads and 715.4 passenger cars registered per 1000 inhabitants of Wrocław according to data from the Statistical Office in Wrocław for 2019.

The second examined area, Upper Silesia, with the capital of Katowice for the Silesian Voivodeship, has an area of 165 km². According to the data from the Statistical Office in Katowice, more than 290,000 people lived there in 2019, giving a population density of 1778 people/km². There are 487.5 km of communal and district hard surface roads within the city. The number of cars registered per 1000 inhabitants is higher than in Wrocław and is 761.7. The research areas in the vicinity of Katowice were the cities of Bytom, Chorzów, and Piekary Śląskie. Piekary Śląskie is a city with district rights, numbering almost 55,000 residents. The A1 motorway, the provincial road number 911, and the national road number 94 pass through this city. Piekary Coal Mine, which ended its activity in January 2020, is located in Piekary Śląskie. Bytom is also a city with district rights, neighbouring Chorzów and Piekary Śląskie. Since 2017, Bytom has been part of the Metropolis of Upper Silesia and Zagłębie. It is inhabited by approximately 164,000 people. The city area is almost 70 km². Both Bytom and Piekary Śląskie have public transport (buses and trams) as well as railways, and both of them are part of the Upper Silesian Industrial District [24].

2.3. Sample Preparation

The URD samples were delivered to the laboratory and they were prepared for further analyses The URD was weighed, homogenised, dried, and sieved in the laboratory. Samples were dried at 105 °C and sieved through a 2 mm mesh in order to remove larger particles and debris. The whole mass of each of the 6 samples was weighed and 20 g of the sample was mineralised, and obtained solutions were used to determine the selected elements.

Chemical Analysis

URD samples were analysed for extractable metals according to EPA Method 3051 and Method 200.8 (Revision 5.4) [26]. The determination of the total amount of metals with spectral purity was performed using strong acids: HCl, HNO₃, and HF. The samples were heated in a 1200 W microwave oven for 35 min. Along with the preparation of the samples, a comparative test was performed. Metal analysis was performed on all samples, including the blank sample. Metal concentrations in the analysed blank sample were subtracted from the actual samples. The determination of the metals Mn, Ni, Cu, Zn, As, Cr, Mg, Al, Co, Pb, Cd, and V in was performed by the ICP-MS, i.e., ionization using inductively coupled plasma in combination with mass spectrometry. Process conditions: the generator used a power of 1125 W, a nebulizer gas flow rate of 0.78–0.83 L/min, an auxiliary gas flow rate of 1.15 L/min, a plasma gas flow rate of 15 L/min, and a sample flow rate of 1 mL/min. All samples were measured in triplicate. Certified multi-element standard solutions, Periodic table mix 1 and Transition metal mix 2 [22], were used as calibration solutions. Detection limits were: 0.151 g/l for Al, Mg, and Zn; 0.019 g/L for As; 0.013 g/L for Cr; 0.022 g/L for Mn; 0.017 g/L for Ni; 0.0021 g/L for Cu; 0.003 g/L for Pb; 0.001 g/L for Cd; 0.002 g/L for Co; and 0.001 g/L for V.

2.4. Health Risk Assessment

2.4.1. Exposure Dose

The health risk assessment was based on the analysis of elements such as Mn, Ni, Cu, Zn, As, Cr, Mg, Al, Co, Pb, Cd, and V according to the method developed by the US EPA [27]. Two age groups were taken into account in the calculations: children and adults; they were then divided into ways of exposure to a potentially harmful substance: oral, inhalation, and dermal. Health exposure was expressed as the amount of substance that the organism absorbed within 24 h, calculated per 1 kg of body weight. Calculations were made using the formulas ADDing, ADDinh, and ADDderm:

$$\begin{gathered} ADDing=\mathrm{C}\times \frac{\mathrm{I}\mathrm{n}\mathrm{g}\mathrm{R}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{BW\times AT} \\ \mathrm{A}\mathrm{D}\mathrm{D}inh=\mathrm{C}\times \frac{\mathrm{I}\mathrm{n}\mathrm{h}\mathrm{R}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{PEF\times BW\times AT}\times 10^6 \\ ADDderm=\mathrm{C}\times \frac{\mathrm{S}\mathrm{L}\times \mathrm{S}\mathrm{A}\times \mathrm{A}\mathrm{B}\mathrm{S}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{\mathrm{B}\mathrm{W}\times \mathrm{A}\mathrm{T}} \end{gathered}$$

where:

C—average metal concentration in road dust [mg/kg];

IngR—value of daily accidental dust intake [mg/day];

InhR—daily lung ventilation [m³/day];

EF—contact frequency [day/year];

ED—duration of contact [year];

BW—average body weight [kg];

AT—averaging period [day];

PEF—particle emission factor [m³/kg];

SL—coefficient of dust adherence to the skin [mg/cm²·day];

SA—skin surface exposed to dust [cm²];

ABS—percutaneous absorption coefficient, unnamed quantity.

These parameters are shown in Supplementary Materials in Table S2.

2.4.2. Non-Cancerogenic Health Risk

Two important parameters were used to assess health risk: Hazard quotient (HQ) and hazard index (HI). They were calculated according to the following formulas:

$$\begin{gathered} HQ=\frac{\mathrm{A}\mathrm{D}\mathrm{D}}{\mathrm{R}\mathrm{f}\mathrm{D}} \\ HI=\sum \mathrm{H}\mathrm{Q} \end{gathered}$$

where ADD is the ingestion, inhalation, or dermal dose, respectively. On the contrary, RfD is the reference dose that is given in the Integrated Information Risk System (IRIS) [27] (Table S3). If HQ is larger than 1, adverse effects on human health and safety can occur. If the value of HQ is <1, the same as that of if HI < 1, there is no risk of health hazards [27].

2.4.3. Risk Calculation

The excessive risk of developing cancer (ECR) was calculated using the following formula:

$$ECR=\frac{\mathrm{C}\times \mathrm{E}\mathrm{T}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}\times \mathrm{I}\mathrm{U}\mathrm{R}}{BW\times AT}$$

However, it should be remembered that it was not possible to use all of the metals tested for this assessment, because not all of them are carcinogenic. Thus, the elements Ni, As, Pb, Cr, Co, and Cd were used to calculate the ECR. The IUR values of Ni, As, Pb, Cr, Co, and Cd were 2.6 × 10⁻⁴, 4.3 × 10⁻³, 1.2 × 10⁻⁵, 0.012, 9 × 10⁻³, and 1.8 × 10⁻³ (g/m³), respectively (IRIS). If the ECR ranged between 10⁻⁶ and 10⁻⁴, there was a low risk of cancer [27].

2.5. Calculation of Other Indices

The evaluation of the URD pollution was performed using three recommended indices: Pollution Load Index (PLI) to define the pollution level of elements in URD, Enrichment Factor (EF) to assess the level of enrichment of heavy metals in soils and to determine their sources, and Geoaccumulation Index (I_geo) to evaluate the contamination levels of the studied elements [27].

2.5.1. Single Pollution Index

Single pollution index (PI) was used to determine which element posed the highest threat. PI is the ratio of the average concentration of a studied element (from at least 5 samples) at the site and the geochemical background. The formula is given below. The geochemical background values are given in Table S4. Table S5 presents classification of contamination level according to PI [28].

$$\mathrm{PI}\mathrm{formula}:PI=\frac{Cn}{GB}$$

where:

Cn—element concentration in the sample [mg/kg];

GB—geochemical background value [mg/kg].

2.5.2. Pollution Load Index

Using the PI index, we can also determine another index, Pollution Load Index (PLI) (Table S6) [29].

PLI formula: PLI = √PI1∙PI2…∙PIn

where:

n—number of elements;

PI—index value.

2.5.3. Enrichment Factor

To determine the impact of anthropogenic activity, the Enrichment Factor (EF) was determined [30]. As a reference element, the concentration and geochemical background values for aluminium [31] were used (Table S7), which is one of the widely and successfully used reference elements [32,33,34].

EF was defined as a ratio of CF (concentration) for the studied metal n and CF for the reference metal.

$$\mathrm{EF}=\frac{\mathrm{C}\mathrm{F}\mathrm{n}}{\mathrm{C}\mathrm{F}\mathrm{b}}$$

The value of EF can be ranked in five classes [34], Table S7.

2.5.4. The Geoaccumulation Index

The Geoaccumulation Index (I_geo) was the indicator that determined the level of accumulation of heavy metals in the sample. It was calculated using the concentration of a studied metal in the sample and the value of the geochemical background of the metal in the studied area (Table S4) [35].

$$\mathrm{I}\mathrm{g}\mathrm{e}\mathrm{o}=\mathrm{l}\mathrm{o}\mathrm{g}2\frac{\mathrm{C}\mathrm{n}}{1.5\mathrm{B}\mathrm{n}}$$

I_geo is a logarithm base 2 of CF; thus, the rates of change of I_geo, n with Cn are lower than those for CFn. The value of Igeo corresponds to seven I_geo classes [36]. The classes are presented in Table S8.

2.6. Statistical Analysis

For every analysed heavy metal, statistics, i.e., the coefficient of variation (CV) expressed as a division of standard deviation and mean value, were calculated. Significant differences in element concentrations at sampling sites were analysed using the Kruskal–Wallis test (one-way ANOVA on ranks) using Statistica 13.3^®.

Research was limited to the two largest Polish agglomerations which are considered one of the largest. Unfortunately, due to meteorological conditions, sampling in Upper Silsesia was limited to the three most representative sampling sites.

3. Results

3.1. Metal Concentrations in URD

Samples of URD from both agglomerations were quite variable in terms of metal concentrations (Figure 2 and Table S9). The CV formula used the standard deviation and mean of the sample data to calculate a ratio that represented the dispersion of the values around the mean. The coefficient of variation (CV) was useful for comparison between data sets with different means and it was used in this research to show the distribution pattern of URD-bound elements at both agglomerations. Results in Figure 2 and Table S9 show that almost all the studied elements—Mn, Ni, Cu, As, Cr, Al, Pb, and Cd—were manifested with wide variations, suggesting that the presence of these elements in URD was greatly different in both studied regions. On the other hand, Zn, Mg, and Co were similarly distributed between both agglomerations. Generally, the CV values showed that for most of the metals, the anthropogenic inputs followed a different pattern, suggesting the greater impact of URD on the Upper Silesia region. Based on the calculated CV, variation was very high in the case of Ni, Cu, and Cd content in Lower Silesia. In the second studied region, the highest variation was recorded for Pb, Cd, Cr, and As, although almost all the studied metals were very variable in URD samples taken from this region, which resulted in a high content of metals at the sites in Piekary Śląskie (sites 5 and 6). The Kruskal–Wallis test showed significant differences between the concentrations of studied elements at sites 5 and 6. According to the content, the most accumulated element in URD in Upper Silesia was Al, then, in descending order: Mg > Zn > Mn > Pb > As > Cr > Cu > Ni > V > Cd > Co. For Upper Silesia, the content of metals was as follows: Al > Mg > Zn > Mn > Cr > Ni > Cu > Pb > V > Co > As > Cd. The Wrocław agglomeration showed lower element concentrations in general in comparison to the Katowice agglomeration, which is probably connected to the dominance of industries in Upper Silesia that still contribute to the high dust suspension and the great presence of post-industrial waste and metals.

3.2. Health Risk Assessment

ADD Values

The average values of average daily dose (ADD) for both regions are presented in

Table 1. The average values of ADD for Upper Silesia agglomeration (ng/kg·d).

	Mn	Ni	Cu	Zn	As	Cr	Mg	Co	Pb	Cd	V
	Adults
ADDing	8.76 × 102	3.35 × 101	9.85 × 101	1.1 × 104	3.84 × 102	2.18 × 102	7.57 × 104	6.02 × 100	8.25 × 102	6.15 × 100	2.71 × 101
ADDinh	6.31 × 10−2	2.41 × 10−3	7.09 × 10−3	7.89 × 10−1	2.76 × 10−2	1.57 × 10−2	5.45 × 100	4.33 × 10−4	5.94 × 10−2	4.42 × 10−4	1.95 × 10−3
ADDderm	1.75 × 101	6.68 × 10−1	1.96 × 100	2.19 × 102	7.66 × 100	4.34 × 100	1.51 × 103	1.2 × 10−1	1.65 × 101	1.23 × 10−1	5.4 × 10−1
	Children
ADDing	2.05 × 103	7.81 × 101	2.30 × 102	2.56 × 104	8.96 × 102	5.08 × 102	1.77 × 105	1.4 × 101	1.93 × 103	1.43 × 101	6.32 × 101
ADDinh	1.12 × 10−1	4.27 × 10−3	1.26 × 10−2	1.4 × 100	4.90 × 10−2	2.78 × 10−2	9.66 × 100	7.68 × 10−4	1.05 × 10−1	7.84 × 10−4	3.45 × 10−3
ADDderm	1.15 × 101	4.37 × 10−1	1.29 × 100	1.43 × 102	5.02 × 100	2.84 × 100	9.9 × 102	7.86 × 10−2	1.08 × 101	8.03 × 10−2	3.54 × 10−1

and

Table 2. The average values of ADD for Lower Silesia agglomeration (ng/kg·d).

	Mn	Ni	Cu	Zn	As	Cr	Mg	Co	Pb	Cd	V
	Adults
ADDing	3.66 × 102	8.04 × 101	7.13 × 101	4.10 × 102	7.28 × 100	1.52 × 102	8.70 × 103	1.02 × 101	4.12 × 101	4.23 × 10−1	2.67 × 101
ADDinh	2.63 × 10−2	5.78 × 10−3	5.13 × 10−3	2.95 × 10−2	5.24 × 10−4	1.09 × 10−2	6.26 × 10−1	7.33 × 10−4	2.97 × 10−3	3.04 × 10−5	1.92 × 10−3
ADDderm	7.30 × 100	1.60 × 100	1.42 × 100	8.19 × 100	1.45 × 10−1	3.03 × 100	1.74 × 102	2.03 × 10−1	8.23 × 10−1	8.43 × 10−3	5.33 × 10−1
	Children
ADDing	8.54 × 102	1.88 × 102	1.66 × 102	9.58 × 102	1.70 × 101	3.55 × 102	2.03 × 104	2.38 × 101	9.62 × 101	9.86 × 10−1	6.24 × 101
ADDinh	4.67 × 10−2	1.03 × 10−2	9.10 × 10−3	5.24 × 10−2	9.29 × 10−4	1.94 × 10−2	1.11 × 100	1.30 × 10−3	5.26 × 10−3	5.39 × 10−5	3.41 × 10−3
ADDderm	4.78 × 100	1.05 × 100	9.32 × 10−1	5.36 × 100	9.51 × 10−2	1.99 × 100	1.14 × 102	1.33 × 10−1	5.39 × 10−1	5.52 × 10−3	3.49 × 10−1

. Table S10 shows a detailed calculation of ADD for every element at each sampling point for adults and children (Supplementary Materials). URD from sites in Lower Silesia, in relation to Upper Silesia, is characterised by lower values for elemental intake by inhalation, which is in line with the metal content. The average value of ADD for children in Wrocław for Pb was 5.26 × 10⁻³ ng/kg·d, while it was 1.05 × 10⁻¹ ng/kg·d for Katowice. This is more than twenty-seven times higher. The most affected was site 5 in Piekary Śląskie. There, values of ADD for Cr, Zn, Mn, and Mg were the highest in the Upper Silesia region. At site 6, also located in Piekary Śląskie, the highest values of ADD for Cu, As, Pb, and Cd were noted. ADDing for As (2.67 × 10³ ng/kg·d) for children was several hundred times higher than results calculated at other analysed locations (ADDing for As at site 4 = 1.57 × 10⁰ ng/kg/d and that at site 3 = 2.47 × 10¹ ng/kg·d). The main reason for the exceedances of these values at sites in Piekary Śląskie in winter was the proximity of industries (industrial areas are located about 1 km away) and the presence of waste, as well as the emission from individual heat sources, and the pollution from the national road with intense traffic, which is near both sites. Other sources of particulate emissions from outdoor surfaces, e.g., roads, sidewalks, and sports fields, can contribute as well.

Importantly, a high concentration of metals was observed in the second studied agglomeration as well. ADDing at site 1 (Obornicka Wrocław) for Ni was high (3.53 × 10² ng/kg·d). The presence of Ni may be due to the combustion of coal, diesel oil, and fuel oil and the incineration of waste and sewage [37]. Site 1 was located on the route leading to the exit from the city of Wrocław in the direction of Poznan. It is an area with tall buildings using municipal heating. High values of ADDderm for Ni may have been caused by the accumulation of pollutants associated with heavy traffic as well. At the majority of sampling sites, ADDderm for Ni in adults was between 9.53 × 10⁻² and 1.28 × 10⁰ ng/kg·d. The exceptions were samples of URD derived from site 1 (ADDderm = 3.01 × 10⁰ ng/kg·d).

The HQing values were higher than HQderm and HQinh (Supplementary Materials Table S11). When HI was greater than or equal to one, it signified that there may be negative health effects for people exposed to the pollutants. Again, at site 6 (Piekary Śląskie), HI for adults was 3.9 × 10⁰ for As and 1.7 × 10⁰ for Pb for children. As it was mentioned above, both sites at Piekary Śląskie (sites 5 and 6) were close to a high traffic road with over 500 vehicles per hour. As a component of coal, which is often used in individual heating [38], its use in individual heating may also contribute to the high concentration of this element in URD, as this area contains compact multi-family housing where individual heating predominates. On the other hand, this element is quite common and, therefore, can often be found as an impurity in metal ores [39,40,41]. The main atmospheric emissions of As came from the mining and metal industries, since waste left from former plant activities are common in this region. The main sources of Pb in URD were vehicular traffic, the combustion processes of waste, and metal smelting or other sources from industries [42]. All of the above-mentioned reasons influence the pollution with this element in winter in this region and possible adverse effects for humans.

Human exposure to carcinogenic elements was determined using ECR (

Table 3. Excessive risk of cancer (ECR ≤ 0.0001 in grey) for Upper and Lower Silesia regions.

ECR	1	2	3	4	5	6
As adults	1.07 × 10−3	1.26 × 10−3	3.2 × 10−3	2.04 × 10−4	8.57 × 10−4	3.46 × 10−1
As children	1.21 × 10−1	1.97 × 10−2	5.14 × 10−2	3.83 × 10−3	4.42 × 10−2	3.25 × 10−2
Ni adults	2.75 × 10−3	4.48 × 10−4	1.17 × 10−3	8.69 × 10−5	1 × 10−3	7.38 × 10−4
Ni children	7.33 × 10−3	1.19 × 10−3	3.11 × 10−3	2.32 × 10−4	2.67 × 10−3	1.97 × 10−3
Co adults	1.05 × 10−2	3.72 × 10−3	5.05 × 10−3	1.29 × 10−3	4.04 × 10−3	6.05 × 10−3
Co children	2.81 × 10−2	9.92 × 10−3	1.35 × 10−2	3.43 × 10−3	1.08 × 10−2	1.61 × 10−2
Cr adults	1.92 × 10−1	3.99 × 10−2	1.49 × 10−1	8.95 × 10−3	4.62 × 10−1	7.8 × 10−2
Cr children	5.13 × 10−1	1.06 × 10−1	3.99 × 10−1	2.39 × 10−2	1.23 × 100	2.08 × 10−1
Pb adults	1.93 × 10−5	4.38 × 10−5	4 × 10−5	5.62 × 10−6	3.78 × 10−5	2.04 × 10−3
Pb children	5.14 × 10−5	1.17 × 10−4	1.09 × 10−4	1.5 × 10−5	1.01 × 10−4	5.43 × 10−3
Cd adults	1.95 × 10−5	4.26 × 10−5	1.14 × 10−4	8.88 × 10−6	3.2 × 10−5	2.28 × 10−3
Cd children	5.21 × 10−5	1.14 × 10−4	3.03 × 10−4	2.37 × 10−5	8.52 × 10−5	6.09 × 10−3

); if the ECR ranged between 10⁻⁶ and 10⁻⁴, there was a low risk of cancer. ECR in URD-bound elements As, Co, Ni, and Cr taken from all sites was not under the range limit of 10⁻⁶ for both children and adults, which may result in future cancer incidences. This shows that both regions pose a threat to human health. ECR values were under the range limit of 10⁻⁶ for Pb apart from sites 5 (children) and 6 (adults and children) in Piekary Ślaskie, and sites 2 and 3 in Lower Silesia (children), and for Cd apart from site 6 (children and adults) in Upper Silesia and sites 3 (adults) and 2 (children) in Lower Silesia. To summarise, we can note that ECR constantly exceeded ranges between 10⁻⁶ and 10⁻⁴ for all studied URD-bound elements at site 6. As this site is exceptional in terms of metal content in URD and its location in an industrial and heavy traffic area, this is not surprising. Exceeded values for all elements were also constantly noted at sites 3 in Wrocław. In the vicinity of site 3 in Bielany Wrocławskie, there is heavy traffic too, caused by the attractiveness of commercial factors, services, and industries. Therefore, we can notice that the impact of transport predominates in this region, influencing human health.

3.3. Other Indices

The calculation of PI and PLI indices for URD are presented in

Table 4. Values of PI and PLI indices for the elements in URD in both studied agglomerations (light grey—low pollution, dark grey—moderate pollution, very dark grey—high pollution).

PI	1	2	3	4	5	6	Average Upper Silesia	Average Lower Silesia
PI Al	0.01	0.08	0.14	0.18	3.17	0.21	1.19	0.08
PI Mg	0.47	0.43	0.47	2.41	6.19	3.34	3.98	0.46
PI Mn	0.57	0.44	0.47	0.13	1.94	1.46	1.18	0.49
PI Cr	4.64	0.96	3.61	0.22	11.14	1.88	4.41	3.07
PI Zn	2.17	5.43	2.92	76.39	135.42	69.64	93.82	3.51
PI Ni	5.77	0.94	2.45	0.18	2.1	1.55	1.28	3.05
PI Cu	2.69	2.85	4.98	0.45	3.3	10.91	4.9	3.50
PI Co	1.02	0.36	0.49	0.13	0.39	0.59	0.37	0.63
PI Pb	0.96	2.18	2.03	0.28	1.88	101.22	34.46	1.72
PI V	0.41	0.36	0.3	0.12	0.43	0.54	0.36	0.36
PI As	1.26	1.48	3.77	0.24	1.01	407.58	136.28	2.17
PI Cd	1.08	2.35	6.27	0.49	1.76	126.08	42.75	3.24
PLI	0.91	0.88	1.32	0.43	2.79	6.29	5.2	1.15

. The highest score for URD samples was obtained by As. PI for this element was 407.58 at site 6. In several cases, PI was greater than 10 (for Zn at all sites, i.e., 4, 5, 6 in Upper Silesia; for Ni at site 1 in the same region; for Pb, As, Cd at site 6 in Piekary Sląskie). These findings suggest extremely high levels of environmental pollution with these elements. According to the classification, a PI value above three means a high level of pollution. Zn in URD reached this value in six studied sites. Cu in URD exceeded the value of PI = 3 at three sites. Cr was also higher than three at sites 1 and 3 in Lower Silesia and site 5 in Upper Silesia. Values of Ni exceeded five at site 1, then URD from sites 3 and 5 reached values more than two. Interestingly, the higher values of Mn were restricted to the Upper Silesia agglomeration only, which might be connected with the greater impact of traffic in this region, as Mn is usually added to increase the octane number of petrol, although Mn may also be associated with other particle sources such as crustal material [41,43]. Calculations for Cd indicated high pollution with this element at site 3 in Lower Silesia and at site 6 in Upper Silesia. Among all sites, there was no URD sample that was not contaminated with any of the studied elements. In each location, there was at least one element that highly polluted the URD samples. Only V did not cause contamination in the studied sites. URD taken from site 6 was the most heavily polluted. As for PI, URD from site 6 had the highest value of the pollution load PLI (6.29) as well. According to PLI, the second most polluted location was site 5, which was also situated in Piekary Śląskie (PLI = 2.79), indicating a high level of contamination. Both sites neighbour each other; therefore, the impact of industry waste, traffic, and heating type can be overwhelming there. Only at site 3 (PLI = 1.32) was a PLI value above one was recorded, which indicated a moderate level of pollution in this area.

Table 5. EF values in URD for both studied agglomerations (light grey—poor enrichment, dark grey—moderate enrichment, very dark grey—moderately strong enrichment, creamy—strong enrichment, brown—very strong enrichment, blue—extremely strong enrichment).

Site	Mn	Ni	Cu	Zn	As	Cr	Mg	Co	Pb	Cd	V
1	42.18	431.42	201.18	162.26	94.27	347.45	35.5	76.63	71.7	80.7	30.72
2	5.29	11.37	34.48	65.81	17.92	11.65	5.23	4.37	26.35	28.50	4.36
3	3.47	18.02	36.69	33.65	27.78	26.59	3.43	3.61	14.99	46.24	2.25
4	0.74	1.01	2.51	422.52	1.33	1.19	13.31	0.69	1.55	2.71	0.66
5	0.61	0.66	1.04	42.76	0.32	3.52	1.95	0.12	0.59	0.56	0.14
6	6.86	7.24	51.10	326.05	1908.28	8.82	15.64	2.75	473.92	590.30	2.53

shows the results for EF, which is an indicator used to assess the presence and intensity of anthropogenic contaminant deposition on surface soil; in our case, it was used for URD. The highest value on the EF index was obtained for URD from site 6 for As (1908.28). The lowest level of enrichment in URD was noted at site 5 for Co (EF value = 0.12). The enrichment in the Lower Silesia agglomeration for all elements was extremely strong, although it was mostly restricted to site 1, which was probably related to the significant impact of the road and municipal heating. Strong enrichment at site 6 in the area of Upper Silesia was noted for Cu, Zn, As, Pb, and Cd, suggesting the impact of transport, industry, and individual heating. Considering Zn, the level of enrichment was extremely strong at three sites (2, 3, and 5) and very strong at three other sites (1, 4, and 6), suggesting that this element is ubiquitous as an anthropogenic contaminant. The most important sources of Zn came from discharges of smelter wastes, mine tailings, coal, transport emissions, and the use of fertilisers and wood preservatives [40].

Table 6. Igeo values in URD for both studied agglomerations (light grey—not polluted to moderately polluted, dark grey—moderately polluted, very dark grey—moderately to strongly polluted, blue—extremely polluted).

Igeo	1	2	3	4	5	6	Average Upper Silesia	Average Lower Silesia
Al	−6.81	−4.2	−3.46	−3.05	1.07	−2.81	−0.33	−2.08
Mg	−1.66	−1.8	−1.68	0.68	2.04	1.15	1.4	−1.41
Mn	−1.39	−1.78	−1.67	−3.48	0.37	−0.03	−0.34	−1.62
Cr	1.63	−0.64	1.22	−2.78	2.89	0.32	1.55	−4.82
Zn	0.53	1.85	0.95	5.67	6.49	5.54	5.96	0.66
Ni	1.94	−0.67	0.7	−3.04	0.48	0.04	−0.23	0.75
Cu	0.84	0.92	1.73	1.72	1.14	2.86	1.7	0.35
Co	−0.55	−2.05	−1.61	−3.58	−1.93	−1.35	−2.02	0.11
Pb	−0.64	0.53	0.43	−2.42	0.32	6.07	4.52	1.17
V	−1.86	−2.05	−2.3	−3.65	−1.81	−1.47	−2.04	0.75
As	−0.25	−0.02	1.33	−2.64	−0.57	8.08	6.5	−1.72
Cd	−0.47	0.65	2.06	−1.61	0.23	6.4	4.83	1.12

presents the results obtained for Igeo. According to the calculated values, elements like V, Co, and Mn did not contaminate samples of URD. Extremely high pollution was recorded again only at site 6 for Cd, Zn, and As. Additionally, the index for Zn was also very high at sites 4 and 5 in Upper Silesia. In the case of Lower Silesia, extremely high pollution did not occur. At site 1, the value of Igeo was close to a value of two, which means that URD taken from this area was strongly polluted with Ni. This element’s presence can be derived from coal, oil, and gas combustion, and heavy vehicle traffic can also be responsible for the emission of Ni [41].

Finally, the recorded concentrations of elements from our studies were compared with data obtained by other authors in various regions of the world to assess the contamination level in both studied regions (Table 7). In general, the Upper Silesia agglomeration was characterised by higher concentrations of metals (Zn, As, Mg, and Al) in URD in winter. The concentration of these elements in URD samples was several dozen times higher than at other sites all over the world. The recorded concentrations in the Lower Silesia region were not as high as those in Upper Silesia, although the content of Mn, Ni, and Al was quite high. For other elements, the values were similar to those recorded for other sites in the world.

The most important comparison was the assessment of how seasonal variation, especially coal combustion, considered as one of the main sources of pollution, could contribute to the significantly higher concentrations of metal elements in the heating period compared with the non-heating period. Severe weather conditions in winter and using winter tires and different road wear particles could contribute to significant differences in the seasonal sources of air pollution [44,45]. In the work of Rybak et al. (2020) [25], studies were conducted at similar sites in both regions in August, although the number of sampling sites in the Upper Silesia region was greater than that in our studies. Not all of the elements were studied, but the maximum content of Mn, Ni, and Cu was higher in Upper Silesia in summer, although the content of Zn, As, Cr, Mg, and Al was lower there (Table 7). This was especially notable for Al, where the winter level was almost four thousand times that of the summer level. The content of As was nearly four times higher, and the level of Zn was three times that of the summer content. In the Lower Silesia region, the content of Mn, Ni, As, Cr, and Mg was comparable in both seasons. The Cu level was two times lower in winter, the Zn content was nearly two times higher, and the Al content was one and a half times that of the summer level. Therefore, in both regions, the concentration of Al in URD in winter was higher than in summer, although the highest level of Al was recorded in Upper Silesia. Al emissions in the air can derive from the aluminium production process, coal combustion, mining, waste incineration, and motor vehicle exhaust [42]. During the winter, both regions do not receive high amounts of precipitation. It is likely that pollutants are not running off with rainwater in winter; therefore, higher concentrations of selected metals can be measured in winter, which suggests that their emission is more intense and there is no washing effect, which is advantageous for the dilution and diffusion of metals in URD [46]. The main reason for recorded high values of Al, As, and Zn in both regions was domestic heating in winter. Polish cities still battle with poor air quality, which derives directly from the use of coal-fired domestic stoves [47]. Comparing both regions, we can notice that in addition to the classic above-mentioned factors that affect air quality in winter in Poland, the presence of industries and waste in Upper Silesia has a key impact on the highest content of metals recorded in URD, which may result in adverse health effects in humans. These results are usually higher than those obtained in studies conducted all over the world (Table 7).

Beijing, in China, is considered one of the most polluted cities in the world. The non-carcinogenic risk values for As for adults were: HQing = 2.7 × 10⁻², HQinh = 2.6 × 10⁻⁶, and HQderm = 2.05 × 10⁻³ for Beijing [48]. In the case of HQing, the majority of URD from our sites was characterised by lower values. An exception was HQing for children and adults at site 6 (3.82 × 10⁰ for As); the calculated value was several times higher than the results obtained in Beijing. For Kumasi in Ghana, this value was 3.5 × 10⁻² [49]. Therefore, among these three cities, the inhabitants of Beijing are the least exposed to non-carcinogenic risk, where for inhabitants of Piekary Śląskie in Upper Silesia, the risk was the highest. HQing for children in summer in Upper Silesia was 1.3 × 10⁻¹, which is lower than that in winter [25]. Apart from site 12, the other sites in both regions were characterised by lower values than those in China. In the Lower Silesia agglomeration, the majority of sites were characterised by lower values than those obtained in Ghana for As. In the capital of China, the highest HI (5.35 × 10⁻¹, children) was recorded for Pb, while in Poland the value was lower. The only exception was site 6, where HI was above 1.7 × 10⁰, suggesting that URD from this site is more than three times as polluted with Pb than in Beijing. In summer, the content of Pb in Upper Silesia was not assessed. In the capital of Oman, Muscat, HI was 1.2 × 10⁻² [50]. Therefore, inhabitants of the Upper Silesia agglomeration are more exposed to a negative impact from Pb in URD on health than people living in the capital cities of China and Oman. HI for Lower Silesia was higher than the value obtained for Muscat, Oman (HI = 4.3 × 10⁻²), which shows that both regions in Poland can be characterised by high potential health hazards.

Table 7. Summary of the literature data on the average concentrations of selected metals in URD for Poland and other countries [mg/kg].

	Mn	Ni	Cu	Zn	As	Cr	Mg	Co	Pb	Cd	V	Al	References
Upper Silesia, Poland	622	29	70	7787	409	155	53,747	4	586	4	19	91,923	This work
Lower Silesia, Poland	260	57	50	291	5	108	6177	7	29	0.3	19	5980	This work
Upper Silesia, Poland	1619	34	175	2683	109	106	21	-	-	-	-	22	[25]
Lower Silesia, Poland	258	50	126	153	3	77	6700	-	-	-	-	5133	[25]
Lublin, Poland	-	27	66	202	-	53	-	-	23	-	-	-	[19]
Kumasi, Ghana	164	44	50	280	6	70	-	-	47	-	-	-	[49]
Changchun, China	367	35	50	162	36	63	3430	37	73	29	60	6080	[51]
Beijing, China	531	36	63	239	5	85	-	-	66	0	-	-	[48]
Manchester, UK	282	-	113	653	-	-	-	265	-	-	-	-	[52]
Delhi, India	-	36	192	284	-	149	-	121	3	-	-	-	[53]
Jazd, Iran	2256	4	9	43	-	-	-	3	19	2	-	-	[54]
Muscat, Oman	-	9	68	181	5	3	-	20	19	-	-	-	[50]
Oslo, Norway	833	41	123	412	-	-	-	19	180	1	-	-	[55]
Madrid, Spain	362	44	188	-	-	61	-	3	1927	-	17	-	[55]
Luanda, Angola	258	10	42	317	5	26	4485	3	351	1	20	4839	[56]

Table 7. Summary of the literature data on the average concentrations of selected metals in URD for Poland and other countries [mg/kg].

	Mn	Ni	Cu	Zn	As	Cr	Mg	Co	Pb	Cd	V	Al	References
Upper Silesia, Poland	622	29	70	7787	409	155	53,747	4	586	4	19	91,923	This work
Lower Silesia, Poland	260	57	50	291	5	108	6177	7	29	0.3	19	5980	This work
Upper Silesia, Poland	1619	34	175	2683	109	106	21	-	-	-	-	22	[25]
Lower Silesia, Poland	258	50	126	153	3	77	6700	-	-	-	-	5133	[25]
Lublin, Poland	-	27	66	202	-	53	-	-	23	-	-	-	[19]
Kumasi, Ghana	164	44	50	280	6	70	-	-	47	-	-	-	[49]
Changchun, China	367	35	50	162	36	63	3430	37	73	29	60	6080	[51]
Beijing, China	531	36	63	239	5	85	-	-	66	0	-	-	[48]
Manchester, UK	282	-	113	653	-	-	-	265	-	-	-	-	[52]
Delhi, India	-	36	192	284	-	149	-	121	3	-	-	-	[53]
Jazd, Iran	2256	4	9	43	-	-	-	3	19	2	-	-	[54]
Muscat, Oman	-	9	68	181	5	3	-	20	19	-	-	-	[50]
Oslo, Norway	833	41	123	412	-	-	-	19	180	1	-	-	[55]
Madrid, Spain	362	44	188	-	-	61	-	3	1927	-	17	-	[55]
Luanda, Angola	258	10	42	317	5	26	4485	3	351	1	20	4839	[56]

In Delhi (India), the highest EF score for URD was obtained for Pb (21.9) [53]. Again, in Poland, it was at site 6 (EF = 1908 for As) in Upper Silesia and site 1 (EF = 431 for Ni) in Lower Silesia in our winter studies. In summer, the very high enrichment was registered mainly for As, Cu, and Zn [25]. When we compare the EF score calculated in India for Pb (the highest value) with that in our studies, we notice that in both regions the EF score was much higher (site 6 = 473, site 1 = 71, and site 2 = 26).

The EF score in Delhi (India) for Cu was 22.4. Among the analysed sites in Poland, six had higher scores than in India, and four were characterised by extremely strong enrichment. In the city of Changchun in China, extremely strong enrichment was calculated for Cd (225), As (68), and Cu (150) [51]. In Poland, these values were the highest at sites 6 (Cd = 590, As = 1908) and 1 (Cu = 201).

The single pollution index PI for Muscat (Oman) for Zn was 1.9, and the highest values were 5.43 (site 2) and 135.42 (site 5) for Lower and Upper Silesia, respectively, which suggests extremely high contamination with Zn in Piekary Śląskie (Upper Silesia) in winter. The highest average PI for Muscat (Oman) for Cd was 5.3, while it was 6.27 (site 3) and 126.08 (site 6) in Lower and Upper Silesia, respectively. These results qualify both locations as highly polluted with cadmium. The value of this parameter for Upper Silesia was more than twenty-five times higher than that obtained in Muscat [50]. The PLI index was the highest in Upper Silesia (again at site 6, value = 6.29); in studies of Rybak (2020) [25], the highest value (4.71) was also obtained for Upper Silesia, although it was lower than in winter.

The Igeo index was 3.1 for Cu and Cr for studies conducted in Lublin, signifying heavy pollution in this region. Comparing these results with those obtained in this work, the values for Cu and Cr were lower for all of the studied locations (Igeo max: Cr = 2.89 at site 5 and Cu = 2.86 at site 6). Both maximum values for these elements were obtained in the Upper Silesia agglomeration. However, for Zn, the results of Igeo calculated for Lublin were 1.9, while for the Upper Silesia region, the above indices for all locations were above 5.5, which classifies URD from these sites as extremely polluted with this element. In contrast, URD samples from the Lower Silesia region had lower Igeo values for Zn than those obtained for Lublin for all sampling points [19]. In Changchun, China, Igeo was the highest for Cu (0.96) and Cd (6.56). In our studies, the recorded values for Cd were lower, except at site 6, where Igeo was nearly comparable (6.4). Therefore, geoaccumulation of Cd in URD derived from Piekary Śląskie was similar to that of the city of Changchun. For Cu in URD, the highest value was obtained at site 6, indicating moderately to strongly polluted samples.

4. Conclusions

Based on URD studies, we can conclude that both studied regions, Upper and Lower Silesia, are quite heavily polluted in winter in terms of dust pollution. Although sites in Piekary Śląskie, Upper Silesia (sites 5 and 6) can be characterised by an enormously high content of Zn, As, and Al, probably resulting from the heating type used by inhabitants (mainly coal-fired domestic stoves), the presence of active industries, abandoned waste dumps, and heavy traffic in this region makes Piekary Śląskie one of the most polluted of our studied regions, and living there definitely poses a high health risk for inhabitants. The conducted health risk studies indicate that the intake of contaminated URD is the major pathway of exposure to the metals. The overall hazard index (HI) was more than one in the case of URD-bound As (adults) and Pb (children) in the Upper Silesia region. In the Wrocław agglomeration, the score was low, which suggests a higher harmfulness of the URD for human health in the Upper Silesia region. Excess cancer risk (ECR) values for all studied URD-bound elements were not within safe limits, i.e., under the range limit of 10⁻⁶ in Piekary Śląskie, Upper Silesia (site 6). Exceeded values of ECR for all elements were also recorded at two traffic-related sites in Wrocław (site 3). These findings suggest that URD poses a serious carcinogenic risk in both regions, although the values from the Katowice agglomeration were much higher. When we compare our results with summer studies, we can conclude that URD in winter produces much higher carcinogenic risk to inhabitants of both regions, but this risk is more severe for the Upper Silesia agglomeration. A comprehensive assessment of both regions using the PI, PLI, EF, and Igeo pollution indices was also made. According to the pollution index (PI), Zn, Pb, As, and Cd were the primary pollutants in Upper Silesia, where their scores were a few times higher than those in Lower Silesia. The pollution index (PLI) shows that all sites in the Upper Silesia region are more severely polluted than the second studied region. Based on the PLI, we can note that the level of pollution in Upper Silesia is higher in winter, which is probably a result of domestic heating. The results of the Enrichment Factor (EF) of URD samples show that URD-bound Zn, As, Pb, and Cd in Piekary Śląskie (site 6, Upper Silesia) have extremely strong enrichment. On the other hand, URD from Lower Silesia was extremely highly enriched with Ni, Cu, Zn, As, Cr, Co, Pb, and Cd (site 1). The highest value of the EF index was obtained for URD from site 6 for As in Upper Silesia and for Ni, URD from site 1 in Lower Silesia. The average values of Igeo for the Upper Silesia region show that Zn, Pb, Cd, and As are the dominant pollutants, while in the Lower Silesia region, these are Zn, Cu, and Ni, although their values are a few times lower for the Wrocław agglomeration. The levels of metal accumulation according to Igeo were similar for summer studies, suggesting their origin from vehicle traffic, domestic emissions, and industry or waste. To sum up, our studies show that the level of URD-bound elements is higher in Upper Silesia than in Lower Silesia in winter, which is a result of domestic heating and industrial activity in this region.

Although our studies were restricted to two biggest agglomerations in Poland, the results will be useful for researchers to bridge the gap on the pollution of elements in URD from Poland, where there is a lack of such data.

Finally, our studies on winter dust pollution will not only help to understand the sources of URD and control road dust emissions to reduce them in the future, but they will contribute to knowledge of possible health risks and allow for the prevention of related diseases. Furthermore, large-scale studies including various representative areas with different characteristics are recommended, as a future study, to better understand the pollution levels and emission sources of elements in URD and possible health risks to humans.