Nature-Based Solutions in Sustainable Cities: Trace Metal Accumulation in Urban Forests of Vienna (Austria) and Krakow (Poland)

Abstract

Forests are considered one of the most valuable natural areas in metropolitan region landscapes. Considering the sensitivity and ecosystem services provided by trees, the definition of urban forest ecosystems is nowadays based on a comprehensive understanding of the entire urban ecosystem. The effective capturing of particulate matter is one of the ecosystem services provided by urban forests. These ecosystems function as efficient biological filters. Plants accumulate pollutants passively via their leaves. Therefore, another ecosystem service provided by city forests could be the use of tree organs as bioindicators of pollution. This paper aims to estimate differences in trace metal pollution between the wooded urban areas of Vienna and Krakow using leaves of evergreen and deciduous trees as biomonitors. An additional objective of the research was to assess the ability of the applied tree species to act as biomonitors. Plant samples of five species—Norway spruce, Scots pine, European larch, common white birch, and common beech—were collected within both areas, in seven locations: four in the “Wienerwald” Vienna forest (Austria) and three in the “Las Wolski” forest in Krakow (Poland). Concentrations of Cr, Cu, Cd, Pb, and Zn in plant material were determined. Biomonitoring studies with deciduous and coniferous tree leaves showed statistically higher heavy metal contamination in the “Las Wolski” forest compared to the “Wienerwald” forest. Based on the conducted analyses and the literature study, it can be concluded that among the analyzed tree species, only two: European beech and common white birch can be considered potential indicators in environmental studies. These species appear to be suitable bioindicators, as both are widespread in urban woodlands of Central Europe and have shown the highest accumulation levels of trace metals.

1. Introduction

Forests have always been inextricably linked to human existence. Along with social changes, the functions of forests—depending on the location—have also begun to change. Global trends indicate that urban areas are constantly expanding, resulting in the continuous transformation of the environment [1,2]. In 1950, urban residents made up 25% of the world’s population. In 2020, already 56.2% of the world’s population (4378 million inhabitants) lived in cities [3]. Urban areas undergo gradual biological depletion along with an increase in the human population [4]. Forests are considered to be one of the most valuable natural areas of metropolitan region landscapes. Considering the sensitivity and ecosystem services provided by trees, the definition of urban forest ecosystems is nowadays based on a comprehensive understanding of the entire urban ecosystem. The term ‘urban forest’ is often understood very broadly and comprises the entire urban forest stand, which is formed by individual trees, clusters of trees, as well as associated biotic and abiotic elements, including people and infrastructure [5]. However, the larger clusters of trees and associated vegetation that make up forests in the traditional sense are a special component of the urban forest ecosystem. Depending on the area, condition, age, or direct vicinity, a wide variety of social and biophysical processes are observed in urban forests. As a crucial component of blue-green urban infrastructure, these forests provide a broad spectrum of ecosystem services. Improved air and water quality, water retention, microclimate regulation, noise mitigation, and increased biodiversity of wildlife habitat are some of the most self-evident ecosystem services. The community also appreciates the intangible benefits provided by forests, e.g., nature-based recreation, leisure, and education. City woodlands, through aestheticizing the city’s environment as well as through their positive impact on the health and well-being of residents, make towns a more pleasant place to live. These provided ecosystem services are directly reflected in the higher values of properties adjacent to city forests [6,7,8,9]. Urban residents especially appreciated the ecosystem services of wooded urban areas during the COVID-19 pandemic [10,11], when movement restrictions were imposed. Access to cultural and sports facilities was restricted or completely forbidden [12]. At that time, forests became one of the few possible places for leisure and recreation. The development of smart cities must align with the idea of sustainable development. Society cannot focus only on technology while ignoring the critical interactions between the social and ecological components of urban systems [13]. Considering the range of ecosystem services provided by blue and green urban infrastructure, sustainable spatial management requires well-balanced management of available land that includes as many natural and semi-natural habitats as possible, such as urban forests [14].

The effective capturing of particulate matter is one of the ecosystem services provided by city forests. These ecosystems function as efficient biological filters due to the ‘rough surface’ of forest areas and also due to the geometric features of some tree leaves [15,16,17]. Moreover, many studies refer to tree species’ organs (needles, leaves, bark, roots, green shoots, and forest and tree rings) as pollutant monitors [18,19,20], which may be another ecosystem service provided by urban woodlands. Plants may accumulate pollutants passively via their leaves [16,21]. Atmospheric contaminants infiltrate tree leaves via foliar stomata [17]. Various deciduous and coniferous trees are very efficient at accumulating atmospheric particles, especially fine particles [22]. Among the most frequently used species are Norway spruce (Picea abies (L.) H. Karst), Scots pine (Pinus sylvestris L.), black pine (Pinus nigra J.F. Arnold), European white birch (Betula pendula Roth.), mountain birch (Betula pubescens Ehrh.), European larch (Larix decidua Mill.), common beech (Fagus sylvatica L.), common juniper (Juniperus communis L.), and black locust (Robinia pseudoacacia L.) [16,18,19,22,23,24,25]. Accumulation of heavy metals in plant leaves and needles is a complex process influenced by a variety of biological, physicochemical, and environmental factors. The main determinants of this phenomenon include metal availability, environmental pH, exposure to air pollutants, chemical properties of the soil, and characteristic taxonomic features of plants [17,20,26]. Taxonomic characteristics of plants play a significant role. Species with higher metabolic activity or special accumulation mechanisms are able to accumulate larger amounts of heavy metals in their tissues [27]. Some of the above-listed studies also refer to the monitoring of urban air pollution, using tree foliage as a biomonitoring tool. The temporal and spatial distribution of pollutants in cities is determined by various environmental factors, such as climate, terrain configuration, type and share of municipal greenery, as well as urban architectural structure. The level of pollution in urban areas depends on the local emission sources (vehicle traffic, household fuel combustion) and on remote sources.

Cadmium, chromium, copper, lead, and zinc are regarded as the most common pollutants of the urban environment [18,25,28]. The abovementioned elements were selected for the purpose of the study. The aim of the research was to estimate differences in trace metal pollution between the ecosystems of the urban forests of Vienna and Krakow using leaves of evergreen and deciduous trees as biomonitors. The additional objective of the research was the assessment of the ability of various tree species to be used as biomonitors.

2. Experimental Part

2.1. Study Area

The study area comprised fragments of two wooded urban areas: the “Wienerwald” Vienna forest, Austria, and the “Las Wolski” forest in Krakow, Poland (Figure 1). Both study areas are located in the closest vicinity of the cities and, as a result, are exposed to numerous anthropogenic impacts, such as airborne trace metal pollution. Vienna is situated at an elevation ranging from 151 to 543 m a.s.l., with an average of 164 m a.s.l., while Krakow is situated 188–383 m a.s.l., with an average of 220 m a.s.l. Both forest areas are located on hills, reaching 200–300 m above average city levels. The “Wienerwald”, as well as the “Las Wolski”, are the largest compact forests and recreation complexes in both cities. Furthermore, the study areas belong to the continental biogeographic region and climatically, to the temperate zone. Both the Vienna and Krakow forests are recreational areas for residents as well as fulfilling landscape and biodiversity functions.

2.2. The “Wienerwald” Forest, Vienna

The “Wienerwald” forest is located in the states of Lower Austria and Vienna and spreads in the western part of the town agglomeration at a distance of about 10 km from the center of the city. The “Wienerwald” Forest is one of the largest contiguous broad-leaved forests in Europe [29]. The forest area within the UNESCO’s World Network of Biosphere Reserves (MaB), “Biosphärenpark Wienerwald”, comprises an area of 1.050 km². In the areas of Vienna forests, there are a number of rare and endangered species and habitats. That region is part of several protection programs, including landscape conservation areas, nature conservation areas, natural monuments, and nature parks, as well as the Natura 2000 Network (“Lainzer Tiergaren”) [30,31]. The mountain ranges of the “Wienerwald” are the transition between the Eastern Alps and the Carpathians. Sampling locations in the northern part of the Vienna study area belong to the Alps’ sandstone zone, while the sampling sites in the southwestern area of the city are located in the Northern Limestone Alps. The most frequent forest types in the “Wienerwald” are beech forests (Cyclamini-Fagetum, Mercuriali-Fagetum, Galio odorati-Fagetum, and Melampyro-Fagetum) and oak–hornbeam forests (Galio sylvatici-Carpinetum). In the southern part of the “Wienerwald”, Euphorbio saxatillis–Pinetum nigrae forest types are predominant. Pedunculate oak (Quercus robur L.), common beech (F. sylvatica), and European hornbeam (Carpinus betulus L.) are the prevalent tree species in the northern part of the forest, while pines (P. sylvestris and P. nigra) are the most common in the southern part [29,32]. The area is managed by the Forestry Office and Urban Agriculture of Vienna (MA 49) (Die Abteilung Forstamt und Landwirtschaftsbetrieb der Stadt Wien—MA 49).

2.3. The “Las Wolski” Forest, Krakow

The “Las Wolski” forest spreads in the western part of Krakow, about 5 km from the center of the city, and is located on the hills forming the southeastern fragment of the Jura Krakowsko–Wieluńska range. The highest points in the Sowiniec Range are Sowiniec (358 m a.s.l.) and Pustelnik Hills (352 m a.s.l.), which rise up to 150 m above the Krakow’s elevation level. The range is built of Upper Jurassic limestones covered with a layer of Quaternary loess. The forest covers the Sowiniec Range and consists of two areas: “Las Wolski” and Sikornik forests. The total forest area is 397 hectares. The forest stands are predominantly natural, multi-species, and consist mostly of pedunculate oak (Q. robur), common beech (F. sylvatica), and European white birch (B. pendula). The most frequent forest types in the “Las Wolski” are Pino–Qercetum and Tilio–Carpinetum. Panieńskie Skały and Bielańskie Skały rock formation areas are under legal protection as nature reserves. The area of “Las Wolski” belongs to Krakow City, and its official name is the City Park and the Zoological Garden [33,34].

3. Materials

Plant material was sampled from seven locations (

Table 1. Sampling site locations.

Sampling Site		Altitude a.s.l. [m]	Geographical Coordinates
The “Wienerwald” Forest, Vienna:
1	The 19th district Döbling–Latisberg between Cobenzl and Kahlenberg	320–380	48°15′47″ N, 16°18′12″ E
2	The 18th district Währing, including Pötzleinsdorfer Park	320–400	48°15′47″ N, 16°18′12″ E
3	The 3rd district Hietzing, a neighborhood of the Lainzer Tiergarten protected area (in the vicinity of Hermesstrasse Street)	340–400	48°10′41″ N, 16°14′08″ E
4	The 23rd district Liesing, the valley of the Reiche Liesing and Gütenbach streams, north of Breitenfurterstrasse Street	320–360	48°08′57″ N, 16°14′24″ E
The “Las Wolski” Forest, Krakow:
5	Pustelnik Hill	340–380	50°03′10″ N, 19°50′52″ E
6	Sowiniec Hill	340–370	50°03′34″ N, 19°50′54″ E
7	Sikornik Hill	280–310	50°03′26″ N, 19°52′48″ E

). Four of them were situated in the eastern part of the “Wienerwald”. The following sampling sites were located in Krakow in the Sowiniec Range: Pustelnik and Sowiniec Hills in the “Las Wolski” forest and Sikornik Hill. The approximate height of all sampling locations was between 280–400 m a.s.l. Samples were collected at a minimum distance of 500 m from main roads and individual buildings in order to avoid the influence of local pollution sources. The exceptions were sampling locations in the areas of Liesing (Breitenfurterstrasse Street) and Hietzing (Hermesstrasse Street), where the distance from the road did not exceed 500 m.

Common beech (F. sylvatica), common white birch (B. pendula), Eurpean larch (L. decidua), Norway spruce (P. abies) and Scots pine (P. sylvestris) were selected for the study as bioindicators of trace metals contamination. The selection criteria for species included, among others, occurrence in all locations. The abovementioned trees belong to commonly occurring species in Central Europe.

Samples of each species were collected in seven locations. The exception was the samples of common beech (F. sylvatica L.) and European larch (L. decidua), both of which were collected only at six and five locations, respectively. It was not possible to obtain sufficient amounts of plant material at Breitenfurterstrasse and Pötzleinsdorf in the case of European larch and European beech did not occur at Hermesstrasse. Field sampling was conducted in September (2019) because the level of pollutant concentration in leaves reached maximum values at the end of the vegetation period.

For each location and species, three to five trees of approximately the same age were randomly selected. The selection of trees was based on similar trunk circumferences measured at a height of 1.3 m. To ensure that the primary samples represent the entire sampling site, samples were collected from trees not growing close to each other. The samples were collected from lower foliage at a height of 1.5–2.0 m above the ground, from all sides of the trees. The primary samples were taken from each tree. Each primary sample consisted of 10–30 fully developed leaves, without imperfections such as chlorosis and necrosis. In the case of conifers, primary samples consisted of 2-year-old spruce and pine needles and needles of larch from 5–10 shoots. Field sampling was conducted after a few days without rain at the end of the vegetation season. The material was placed in polyethylene bags.

4. Methods

4.1. Chemical Analysis

The collected plant material was not washed, according to the suggestions of the authors of comparable studies [18,23,28]. Therefore, the total deposition of trace elements was studied, including both absorbed and deposited ones. The mean sample of each species consisted of primary samples collected at one site. The samples were dried in an electric drier at a temperature of 40 °C for a period of 72 h. Needles were separated from branches. Equal amounts of biomass from primary samples per plot were mixed. Dry and homogenized samples were pulverized in an electric grinder. Portions of 0.4 g of dry-weight material were placed in Teflon vessels. A total of 5 mL of 65% HNO₃ and 3 mL of 36% H₂O₂ were added to each vessel. The mixture was mineralized in the microwave Berghof Speed Wave at a temperature of 200 °C and a pressure of 40 bar. After digestion, the samples were diluted with deionized water to a total volume of 50 mL and filtered through a hardened paper filter. The final solutions were analyzed for trace metals using flame atomic absorption spectrometry (FAAS) with the spectrophotometer model Hitachi Z-2000. Total concentrations of Cd, Cr, Cu, Pb, and Zn were determined. Chemical determinations for each sample were repeated twice.

4.2. Statistical Analysis

The analyses of basic statistics (mean, median, minimum, and maximum values) and calculations of variability (variance, standard deviation) were performed. The statistical verification of differences in concentration of individual heavy metals between samples taken in Vienna and Krakow was performed by the Kruskal–Wallis rank test. Statistical analyses were conducted at a significance level of 0.05. A correlation analysis was also performed. The results were statistically analyzed using procedures in the Statistica 12 software package (StatSoft Inc., Tulsa, OK, USA).

5. Results

The results obtained from the chemical analysis (mean concentrations, standard deviations, and medians) are summarized in

Table 2. Descriptive statistics of trace metals in the leaves of selected plant species in Vienna and Krakow (µg/g of dry weight).

Species	Location	Metal Concentration (μg/g d.w. Mean ± SD)
		Cd	Cr	Cu	Pb	Zn
European beech (Fagus sylvatica L.)	Vienna	0.08 ±0.07	1.70 ±0.32	7.51 ±0.15	1.04 ±0.64	31.11 ±2.83
	Krakow	0.80 ±0.31	2.17 ±0.19	8.53 ±0.99	4.21 ±0.13	43.52 ±8.74
	Median for Vienna and Krakow	0.31	2.00	7.60	2.92	36.11
Common white birch (Betula pendula Roth.)	Vienna	0.15 ±0.07	0.44 ±0.41	5.29 ±1.34	1.25 ±0.98	66.70 ±20.23
	Krakow	1.46 ±0.40	1.39 ±0.91	6.01 ±0.72	2.74 ±1.45	286.76 ±12.26
	Median for Vienna and Krakow	0.25	0.37	5.61	1.50	94.86
European larch (Larix decidua Mill.)	Vienna	0.00 ±0.01	1.35 ±0.03	5.86 ±0.33	1.93 ±0.25	22.67 ±1.51
	Krakow	0.38 ±0.13	1.72 ±0.56	5.83 ±1.58	2.70 ±1.02	53.88 ±11.81
	Median for Vienna and Krakow	0.25	1.37	5.62	2.11	42.30
Scots pine (Pinus sylvestris L.)	Vienna	0.11 ±0.11	1.01 ±0.88	4.01 ±1.14	0.67 ±0.69	44.49 ±21.76
	Krakow	0.68 ±0.44	1.78 ±0.47	3.35 ±1.74	3.36 ±0.86	64.35 ±30.79
	Median for Vienna and Krakow	0.19	1.41	3.82	1.21	46.45
Norway spruce (Picea abies (L.) H.Karst	Vienna	0.09 ±0.03	0.69 ±0.15	2.69 ±0.14	0.30 ±0.20	25.33 ±2.03
	Krakow	0.28 ±0.25	0.45 ±0.14	2.70 ±0.64	2.59 ±1.40	23.04 ±3.00
	Median for Vienna and Krakow	0.10	0.62	2.62	0.56	26.09

and

Table 3. Descriptive statistics of trace metals in the leaves of all species, demonstrating variation between cities (µg/g of dry weight).

	N	Average	Median	Min	Max	Variance	Std. Deviation
Descriptive statistics for all 7 sampling sites (Viena + Krakow)
Cd	31	0.38065	0.12000	0.00000	1.9000	0.219	0.46827
Cr	31	1.19645	1.37000	0.00000	2.3700	0.538	0.73357
Cu	31	5.09968	5.10000	2.10000	9.5600	4.368	2.08998
Pb	31	1.91161	1.74000	0.00000	4.3500	2.075	1.44059
Zn	31	65.64677	39.73000	17.84000	298.5000	5798.283	76.14645
Descriptive statistics for all 1–4 sampling sites (Viena)
Cd	17	0.09706	0.12000	0.00000	0.25000	0.0057	0.07540
Cr	17	0.96118	0.87000	0.00000	2.03000	0.4053	0.63666
Cu	17	4.83353	5.09000	2.53000	7.61000	3.4423	1.85535
Pb	17	0.93000	0.87000	0.00000	2.36000	0.5992	0.77406
Zn	17	40.27882	30.43000	17.84000	94.86000	456.8067	21.37304
Descriptive statistics for all 5–7 sampling sites (Krakow)
Cd	14	0.72500	0.50000	0.00000	1.9000	0.27	0.5159
Cr	14	1.48214	1.56000	0.37000	2.3700	0.58	0.7633
Cu	14	5.42286	5.22500	2.10000	9.5600	5.64	2.3745
Pb	14	3.10357	3.43500	1.00000	4.3500	1.26	1.1232
Zn	14	96.45071	48.01500	20.10000	298.5000	10,955.01	104.6662

. The concentrations of cadmium, chromium, copper, lead, and zinc varied depending on the element, plant species, and the locations of sampling sites. The concentrations in the plant material were in the range of 0.0–1.9 μg Cd/g d.w., 0.0–2.4 μg Cr/g d.w., 2.1–9.6 μg Cu/g d.w., 0.0–4.4 μg Pb/g d.w., and 17.8–298.5 μg Zn/g d.w.

Statistical analysis of the content of individual elements in plant material showed a significant positive correlation between the various metals. Correlation coefficients for cadmium, copper, chromium, lead, and zinc, calculated for the entire set of samples, ranged from 0.38 to 0.79. The strongest correlation between the analyzed elements was recorded for the following pairs: cadmium–zinc (0.79), cadmium–lead (0.58), chromium–copper (0.58), and chromium–lead (0.51).

Descending sequences of element concentrations (median values) calculated for all species in Vienna and Krakow were identical: Zn > Cu > Pb > Cr > Cd (Table 3). Regardless of plant species, the sequences for all sampling sites were almost identical. The median values of elements, presented in descending order, were Zn > Cu > Pb > Cr > Cd for larch, beech, birch, and spruce, and Zn > Cu > Cr > Pb > Cd for pine.

5.1. Biomonitor Species Variations

The study showed differences in the accumulation of individual elements in samples taken from different tree species. The highest amounts were accumulated by European beech (F. sylvatica), European larch (L. decidua), and common white birch (B. pendula). Common white birch (B. pendula) samples had the highest zinc accumulation. European larch (L. decidua) and Scots pine (P. sylvestris) samples also had higher levels of chromium accumulation. In contrast, Scots pine (P. sylvestris) samples, particularly in the vicinity of Krakow, had higher lead accumulations.

Statistical analysis also showed that, regardless of location, only for elements such as chromium, copper, and zinc were there statistically significant differences in the magnitude of accumulated elements. For chromium, European beech (F. sylvatica) trees showed the highest accumulation on average, while Norway spruce (P. abies) trees showed the lowest accumulation. For copper, these were exactly the same species. In the case of zinc, trees of the common white birch species had the highest accumulation, and, again, Norway spruce (P. abies) had the lowest. For the other elements, the tests conducted showed no significant variation in the concentration of absorbed heavy metals by individual tree species. Therefore, on the basis of the above studies, it is not possible to identify a definite leading species that could be a better environmental indicator than the other examined tree species.

Trace metal concentrations differ widely among species due to tree uptake efficiency. Taking into consideration all studied species, the highest values (median) calculated for Vienna and Krakow were measured for Cd, Cr, Cu, and Pb in the leaves of beech trees (F. sylvatica) and, in the case of Zn, in birch trees (B. pendula). Median values indicate that Cd, Cu, Pb, and Zn at the highest extent were accumulated in certain species of deciduous trees. The lowest median values for Cd, Cu, Pb, and Zn were measured in conifers: spruce (P. abies) and pine (P. sylvestris). In the case of the Norway spruce (P. abies) concentrations of all elements (with an exception for Cr) were the lowest compared with other plants, suggesting that the species is a poor biomonitor (Table 2, Figure 2). According to Sawidis et al. [18], one of the major factors is the rough structure of certain plant leaves.

5.2. “Wienerwald” and “Las Wolski” Variations

When tree species are included as a differentiating parameter, statistical analysis reveals additional information. A strong symmetry in the distribution of average concentrations of individual elements across the different tree species and sampling sites is noticeable. The observed relationship between tree species and average leaf copper concentration is highly consistent, considering both the average accumulation levels and the sampling sites (Figure 3). A higher average accumulation of chromium and zinc was found in plant material from Norway spruce (P. abies) in Vienna compared to all other species and elements. The samples from Krakow showed a higher content of cadmium and lead across individual tree species.

For each of the analyzed elements, a slightly higher accumulation was observed in the samples from Krakow (Table 3). Both average and maximum values for each heavy metal were higher in Krakow. For cadmium, chromium, and lead the differences were statistically significant (verified with the Kruskal–Wallis H test, with a significance level of 0.05). The differences for the other elements were statistically insignificant (at the assumed α level) (Figure 3). Based on the analysis of variance, it was found that the samples taken in Krakow were also characterized by greater variability in the concentration of analyzed elements.

Statistical analyses of the results between the two study areas indicate statistically significant higher concentrations of three of the five analyzed elements (Cd, Cr, Pb). This allows us to conclude that the study area in Krakow is more polluted than that in Vienna.

Regardless of the element and the species, mean values of metal concentrations were higher in the “Las Wolski” than in the “Wienerwald”, with the exception of Cr, Cu, and Zn concentrations in spruce (P. abies) (Figure 3). Statistically significant differences were stated for all species concerning several metals.

5.3. European Beech (Fagus sylvatica L.)

Higher concentrations of Cd in the leaves of F. sylvatica were found in Krakow (0.80 ± 0.31 μg/g d.w.) compared to Vienna (0.08 ± 0.07 μg/g d.w.). The differences were statistically significant (p < 0.05). Also, statistically significant differences (p < 0.01) were found with respect to the concentration of Pb: 4.21 ± 0.13 μg/g d.w. (Krakow) and 1.04 ± 0.64 μg/g d.w. (Vienna). Chromium, copper, and zinc did not show differences in concentration.

5.4. Common White Birch (Betula pendula Roth.)

Common white birch showed higher values of Cd in Krakow (1.25 ± 0.18 μg/g d.w.), while the mean concentration in Vienna was 0.16 ± 0.06 μg/g d.w. Also, higher values of Zn were observed in Krakow (286.76 ± 12.26 μg/g d.w.). For both trace elements, the differences were statistically significant (p < 0.05). There were no differences in the case of Cr, Cu, and Pb concentrations in leaves collected in Krakow and Vienna.

5.5. European Larch (Larix decidua Mill.)

European larch showed a similar pattern of metal accumulation to common white birch (B. pendula). Median values of concentrations of Cd, Cr, Cu, Pb, and Zn were higher in the “Las Wolski” forest of Kraków than in the “Wienerwald”, but statistically significant differences (p < 0.05) were only found in the case of Zn and Cd content in larch from Kraków and Vienna. The concentrations of both trace elements were higher in Krakow: Zn 53.88 ± 11.81 μg/g d.w. and Cd 0.38 ± 0.18 μg/g d.w.

5.6. Scots Pine (Pinus sylvestris L.)

In the case of Scots pine, the same tendency as for European beech was observed. Higher accumulation levels of Cd and Pb in P. sylvestris needles were detected in Krakow than in Vienna (p < 0.05), with the following values: 0.68 ± 0.44 μg Cd/g d.w., 3.36 ± 0.86 μg Pb/g d.w., and 0.11 ± 0.11 μg Cd/g d.w., 0.67 ± 0.69 μg Pb/g d.w., respectively. Chromium, copper, and zinc did not show differences in concentration.

5.7. Norway Spruce (Picea abies (L.) H. Karst)

The same tendency was observed in the case of Cd, Cu, and Pb concentrations in Norway spruce needles. Concentrations of the abovementioned elements were lower in Vienna than in Krakow. The concentrations observed in Vienna were as follows: Cd 0.09 ± 0.03 μg/g d.w., Cu 2.69 ± 0.14 μg/g d.w., Zn 0.30 ± 0.20 μg/g d.w. The concentrations of Cr and Zn in spruce needles collected from the forests of Krakow were lower; however, the differences were not statistically significant.

6. Discussion

The areas of Vienna as well as Krakow receive emissions from traffic, local industry, and combustion of fossil fuels. These are the main sources of most trace elements in the air. However, analysis of air contamination output shows that cities differ in pollution levels.

The area of the “Wienerwald” forests, because of its proximity to the capital city of Vienna, is exposed to a variety of anthropogenic influences. The major local emitters of particulate matter are the industrial sectors, road traffic, agriculture, and solid fuel combustion for domestic purposes [35]. The impact of agriculture on urban areas is secondary. It is more significant in suburban areas, where urbanization is developing and agricultural activity still exists. The annual average concentration of suspended dust (PM10) in 2009 in Vienna reached about 30 μg/m³ [36]. However, air pollution in Vienna has decreased, and its levels, measured as annual average PM10 and PM2.5 values, vary among districts. Hutter et al. [37], in an analysis based on The European Environment Agency’s air pollution data for 2019, demonstrate that the sampling site area (districts: 13—Hietzing, 18—Währing, 19—Döbling, and 23—Liesing) had the lowest annual PM10 values (15–17 μg/m³) among Vienna’s districts. Similarly, Khomenko et al. [38] pointed to the eastern parts of Vienna as the areas with the lowest PM2.5 pollution.

The “Las Wolski” forest is located within the boundaries of Kraków. Due to this proximity, the city is also influenced by various anthropogenic emissions. Air pollution has been one of Krakow’s major environmental problems for a long time [39]. Industrial plants, domestic stoves, and road transportation are pointed out as the main sources of air pollution [40]. The specific morphology of the terrain (the city is located in a basin) significantly affects the concentration of air pollution. Such a location has a limiting effect on the possibilities of vertical and horizontal natural air ventilation in Krakow [39]. Temperature inversions, the direction and speed of prevailing winds, as well as the intensity of the urban heat island additionally affect the high concentration of air pollutants in Krakow [41]. The annual average concentration of suspended dust in 2009 in Krakow reached about 70 μg/m³ for PM10 and 43 μg/m³ for PM2.5 [42]. Due to growing public awareness, and under strong residents’ pressure, the city authorities are treating the reduction and mitigation of the effects of air pollution as a priority issue. A number of efforts have been conducted to reduce air emissions in Krakow [39,40]. Despite a marked reduction in pollution levels, Krakow is one of the cities in Europe with the worst air quality. Poor-quality coal stoves are still the dominant house heating systems in the communes surrounding Krakow. Pollution from neighboring areas continually flows into the city [42]. Although air pollution has been systematically reduced, the values in 2019 were about 34.8 μg/m³ for PM10 and 25 μg/m³ for PM2.5 [42]. The values for Krakow are still more than double the annual average concentration recorded in Vienna in 2019 in the districts from which the samples were taken. The differences in Vienna and Krakow in levels of PM10 and PM2.5 are consistent with the higher values of the results obtained in this study for Krakow. Research conducted by Traczyk and Gruszecka–Kosowska on air pollution in Krakow has shown that PM samples were significantly enriched with Zn and Cd. The anthropogenic factors are indicated as sources of pollution by these metals [42]. Which is also consistent with the results of the presented study.

Vienna, with twice the population of Krakow (1.8 mln and 0.8 mln, respectively) and a larger area (415 km² and 327 km², respectively), is a bigger urban agglomeration. However, this factor does not appear to influence the rate of pollution with heavy metals. The differences between the results obtained from these two cities are clearly visible in the example of lead. The Pb concentrations in leaves collected in Krakow (3.10 μg/g d.w.) were more than three times higher than in Wienerwald, Vienna (0.93 μg/g d.w.). The higher concentration of Pb in tree leaves in Krakow than in Vienna (with the exception of P. abies) can be explained, to some extent, by the use of leaded gasoline in Poland for a longer period of time than in Austria. Similar studies carried out by [18] in Belgrade, Thessaloniki, and Salzburg showed differences in Pb concentrations in plane (13.75 μg/g d.w., 10.44 μg/g d.w., and 3.70 μg/g d.w., respectively) and pine (14.45 μg/g d.w., 12.74 μg/g d.w., and 2.46 μg/g d.w., respectively). The highest values were stated in Belgrade and the lowest in Salzburg. Although traffic emission pollutions decrease with distance from the road and usually reaches background levels at about 250–300 m [43], sometimes even at 500 m [44], we may expect that, in fact, the effect of traffic pollution has a wider range of impact. Lead is one of the elements most prone to long-distance atmospheric transport [45], and a notable proportion of the lead enrichment on pine needles in traffic- and industry-leaning areas may have to be attributed to atmospheric import [46]. A reduction in pollution from urban transport can be expected in the future due to the phase-out of lead-containing fuel, the use of more advanced emission-reducing technologies, and changes in the vehicle fleet in European countries (e.g., the growing share of electric cars).

Using trees as biomonitors in urban areas has played a key role. Although they are regarded as less effective biomonitors than mosses and lichens, trees are still widely used. Their common presence and efficiency in trapping atmospheric fine particles—a phenomenon that helps reduce particulate levels in the environment [18]—as well as the lack of mosses and lichens in industrial and urban areas, make tree leaves relevant indicators of urban pollution [22].

The descending sequence of element concentrations among the species was almost the same in Vienna and Krakow, with the exception of Pb and Cr in pine. In the “Las Wolski” forest, the Pb content in these species was higher than the Cr content. Reimann et al. (2007) [24] reported similar tendencies for spruce (P. abies), birch (B. pubescens), and European mountain ash (Sorbus aucuparia L.). Toxic elements like lead and cadmium are, to some extent, accumulated passively through deposition and foliar uptake. In the case of mobile micronutrients (copper and zinc), both passive foliar uptake and active root uptake may occur [16].

Kabata-Pendias and Pendias [47] have established the range of the concentration levels of heavy metals that are considered normal in the tissues of vascular plants. They are as follows: 0.05–0.2 μgCd/g, 0.1–0.5 μgCr/g, 5–30 μgCu/g, 5–10 μgPb/g, 27–150 μgZn/g d.w. The abovementioned authors also established 5–30 μCd/g, 5–30 μgCr/g, 20–100 μgCu/g, 30–300 μgPb/g, and 100–400 μgZn/g d.w. as toxic concentrations. In our studies, only zinc content in the leaves of the common white birch across all sampling sites in Krakow were within the toxic range. However, concentrations of Cd and Cr exceeded normal ranges: for Cd, only in a few plant samples in Vienna and in almost all samples in Krakow; in the case of Cr, in Vienna as well as in Krakow, the concentrations exceeded normal ranges in nearly all sampling sites.

Many studies suggest that some plant species concentrate trace metals in significant amounts and are regarded to be suitable indicators of atmospheric metal deposition. The studies presented in this paper confirm interspecies differences in element uptake. The lowest concentrations of Cd, Cu, Pb, and Zn were observed in conifers—spruce (P. abies) and pine (P. sylvestris). These results are consistent with studies conducted by other authors [46]. According to Reimann et al. [24], median values of Cu content were lowest in spruce needles compared to other plants.

The very wide area of the Wienerwald forest might vary in terms of pollution levels. According to Krommer et al. [35] element concentrations in bryophytes indicate that the north-east part of the area appears to be the most polluted. Our monitoring studies did not confirm the spatial pattern of pollution. Metal concentrations in leaves were low and the differences among the sites were statistically insignificant. The average concentrations of Cd, Cu, and Pb in bryophytes in the study by Krommer et al. [35] were several times higher than the concentrations in leaves found in our study. The average concentrations of Cr and Zn were at comparable levels. It suggests that tree leaves of selected species are less suitable pollution indicators than bryophytes. It is in accordance with the conclusions of Reimann et al. [24] and Tarish et al. [27].

The choice of biomonitor depends on the study area and the target elements. It depends also on the prevalence of the species within the monitoring area. The studied species are very common across Austria as well as in Poland. The best biomonitors (in particular in the less polluted areas) are the species which accumulate elements in the largest amounts. Among the tested species, the common white birch (B. pendula) and European beech (F. sylvatica) accumulated the highest concentrations of elements and proved useful in assessing the environmental pollution by trace elements in areas with high human pressure, including traffic, and in location where moss samples may be difficult to obtain [19]. Concentrations of Cu, Cd, and Pb in the leaves of common white birch in central Krakow, as reported by Piotrowska and Panek [19], were high: 15.33 μg Cu/g d.w., 0.28 μg Cd/g d.w., and 4.00 μg Pb/g d.w., respectively. These values were almost equal to the concentrations reported for the Las Wolski forest in the present study. Løbersli and Steinnes [48] emphasized the enrichment of some heavy metals or elements in birch leaves for up to a distance of 27 km from the industrial source (the smelter). This suggests that Betula pendula can be used for phytoindication studies in polluted areas, including cities. Needles of European larch (L. decidua) accumulated trace elements to a similar extent as the leaves of B. pendula and F. sylvatica, and in greater amounts than the needles of other conifers (Picea and Pinus).

Element concentrations calculated as median values for both Vienna and Krakow (with an exception for Cr) were the lowest among the studied species. This is in accordance with results by Čeburnis and Steinnes [49], supporting the view that Norway spruce (P. abies) needles are poor biomonitors. The abovementioned authors concluded that conifer needles do not appear to be suitable biomonitors of atmospheric metal deposition, especially within low-polluted areas. The opposite opinion, but referring to heavily polluted areas, was expressed by Samecka-Cymerman, Kosior, and Kempers [50] in the context of conifer species (needles of Pinus silvestris). The concentrations of Pb in Norway spruce (P. abies) needles in Wienerwald (0.3 μg/g d.w.), were very low despite the fact that Liesing and Hietzing sampling sites were located at a distance less than 500 m from the roads.

According to Samecka-Cymerman, Kosior, and Kempers [50], current- and previous-year needles of Scots pine (P. sylvestris) can be considered to be suitable biomonitors for environmental pollution (especially air pollution) by Cu and Zn. According to Lehndorff and Schwark [50] needles of P. nigra are regarded to be a good indicator, due to observed seasonal and temporal variations in the accumulation of metals. The abovementioned authors studied needles of P. nigra as a passive sampler indicator in Cologne, Germany recommend that the species is suitable for atmospheric quality analysis in areas with multiple emission sources, also in urban conurbations.

It can be stated that the least suitable bioaccumulator among all the species studied in this paper is the second-year Norway spruce (P. abies). Further studies are necessary to confirm and more broadly document the ability of the studied vascular plants to accumulate sufficient amounts of trace metals, as the literature referring to these species as phytoindicators is very limited.

7. Conclusions

Biomonitoring studies with deciduous and coniferous tree leaves showed statistically higher levels of heavy metal contamination in the “Wolski Forest” (Krakow) compared to the “Wienerwald” forest (Vienna).

Based on the conducted analyses and the literature study, it can be concluded that among the analyzed tree species, only two—European beech (F. sylvatica) and common white birch (B. pendula)—can be considered potential indicators in environmental studies. These species appear to be suitable bioindicators, as both are widespread in wooded urban areas of Central Europe and showed the highest accumulation levels of trace metals. However, it must be considered that the biomonitoring applicability of these species may be strongly dependent on the element analysed, as well as on the specific location. Particularly considering the latter, it could be presumed that an additional environmental attribute, which was not considered in the present study, could be responsible for the bioaccumulation capacity. Therefore, a study involving a larger number and variety of sampling sites would need to be conducted to draw broader conclusions. Future studies could focus on two species: European beech (F. sylvatica) and common white birch (B. pendula).