Environmental pollution is a global issue that is strongly linked with the content of toxic chemicals in the environment. Metals are notable for their wide environmental dispersion, the tendency to accumulate in the selected tissues of the human body, and the overall toxicity even at relatively low concentration of exposure (Hu 2002). Among 92 naturally occurring elements, approximately 30 metals/metalloids (Be, B, Li, Al, Ti, V, Cr, Mn, Co, Ni, Cu, As, Se, Sr, Mo, Pd, Ag, Cd, Sn, Sb, Te, Cs, Ba, W, Pt, Au, Hg, Pb, and Bi) are potentially toxic to humans (Morais et al. 2012). Trace metals of primary concern for human health and natural environment include As, Cd, Cr, Cu, Pb, Hg, Ni, Se, V, and Zn (Dore et al. 2014). As, Cd, Cr, Hg, and Pb pose main threats to human health during the exposure (Järup 2003). Some others, such as Cu and Fe, are essential to life and play irreplaceable roles but may become harmful at high content of exposure (Hu 2002). Cd, Al, Hg, Fe, Pb, and As are classified as prominent metals, which may cause adverse health effects (da Silva et al. 2005). Cr, Ni, V, Co, and As metal ions are classified as carcinogenic, because they may perform red/ox reactions to the biological systems (Rehman et al. 2017). Trace metals (TM) occur naturally in soil and minerals and may enter the air through the wind-blow dust particles. Besides the natural sources, ore and metal processing, manufacturing, combustion processes of fuels, and transport sectors are considered as the main anthropogenic emission sources of metals (HM) in the air (Harmens et al. 2011; Duffus 2002; Nriagu 1989; Nriagu and Pacyna 1988). On the other hand, anthropogenic activities, such as energy production, transportation, industrial processes, agriculture, and waste management emitting different gaseous and particulate pollutants, are responsible for the degradation of air quality and climate changes (Maione et al. 2016). The transportation and the toxicity degree of the chemicals are important parameters used to assess the spatial distribution of the contaminants and air pollution. Several toxic metals and organic compounds are associated and transported in the environment with the fine particulate matter (FPM). The presence of FPM in the air may cause several health problems that make us more vulnerable to different health diseases, such as respiratory, cardiovascular and neurological disorders, and lung cancer (Kelly and Fussell 2015). FPMs may travel at long distances and may show a large time and space variability of TM in the air (Lammel et al. 2003). The evaluation of the role and the behavior of toxic species/or compounds associated with airborne FPM is important for formulating effective control strategies and to reduce the human health risk (Schroeder et al. 1987). Due to the natural and anthropogenic pollution, our planet is faced with several environmental problems that may affect human and ecosystem health and may disturb the quality of life and ecological balances. Recently, several studies worldwide relate to the assessment of air quality and the pollution sources of the air contaminants. In the past two decades, different atmospheric models have been developed to find different versions of systems and options, from simpler to more complex atmospheric modeling systems that may cover the global, regional, urban, and street level scales (Thunis et al. 2016). The traditional sampling devices are not effective to undertake high-density and large-scale monitoring. Thus, alternative methods are developed to investigate the spatial distribution, the variability, and the content of trace elements in atmospheric deposition. Moss biomonitoring is an alternative method that can assess the content of TM in atmospheric deposition. Mosses have been applied as biomonitors of trace metals deposition across Europe for more than three decades (Harmens et al. 2010, 2013b, 2015; Zechmeister et al. 2003). It is an easily implemented and cost-effective method for air quality monitoring. The variability of moss metal concentrations may reflect the distribution patterns of metal concentrations on the moss that is site-specific and may show their local variation in atmospheric deposition and the location of the areas with high contamination of each element. Moss biomonitoring data serve to identify and evaluate the air quality objectives, not to determine the biological and ecological risk that is limited by the gaps of the safe exposure content or the thresholds below which no adverse health effects may occur. The content of particular elements in moss do not indicate the degree of the contamination, so the next logical step is to determine the occurrence of a relatively large concentration of a specific chemical compared with the normal ambient condition (Fernandez and Carballeira 2001). Despite the importance of HM contamination, there have been no sufficient data to provide a reliable view on the real extent of the problem in Europe and worldwide (Tóth et al. 2016). Albania is a small country (28,748 sq. km) positioned in South-West part of the Balkan Peninsula. The coastal area is wetted by Adriatic and Ion Seas in the west and is followed by mountain areas in the east. The mining industry and mineral processing, old technology of ex-chemical industry of the ’80th years, had caused several environmental problems of the country. There are very few data on metal atmospheric deposition in Albania. The first moss biomonitoring dated from 2010 with its first contribution to the data on European moss biomonitoring. A 2010 moss survey in Albania had addressed high metal concentrations and relatively high contamination level evaluated by moss biomonitoring (Lazo et al. 2018; Allajbeu et al. 2016, 2017; Bekteshi et al. 2015; Qarri et al. 2013). The survey was repeated in 2015, the same period with the European moss survey conducted under the framework of the UNECE ICP Vegetation Programme with the participation of about 50 countries (Harmens et al. 2015). The concentration data onto Al, As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V, and Zn in carpet-forming moss samples are reported in the European moss survey. In this paper, we consider the same TM, known as toxic elements that pose certain threats to human health and natural ecosystems.

The purpose of this study was to investigate the air quality by using moss biomonitoring trace metal deposition and to assess the occurrence of relatively large concentration of specific elements that may pose high contamination and/or ecological risk. Different models, such as contamination factor (CF) (Fernandez et al. 2000), pollution load index (PLI) (Hakanson 1980), potential ecological risk (RI) (Tomlinson et al. 1980; Boamponsem et al. 2010), and GIS technology, were used to assess the degree of contamination and the ecological risk of heavy metal atmospheric deposition in Albania.

Materials and Methods

Sampling Procedure

A field survey was performed during August and September 2015 to sample moss samples over the entire territory of the country. Carpet forming moss species Hypnum cupressiforme (Hedw) that was used in the previous study is selected as a proper bioindicator of TM deposition in this study. Due to the high variability of As, Cd, Cr, Hg, Ni, and Pb in moss collected in 2010 (Lazo et al. 2018; Qarri et al. 2013), some modification was done at 2015 network compared with the 2010 network by increasing the number of sampling sites from 44 (1.5 samples per 1000 sq km) (Qarri et al. 2014a) to 55 (approximately 2 samples per 1000 sq km). It resulted in a denser systematic sampling scheme that often is used in environmental study. The design and density of sampling scheme can significantly influence the interpretation of the survey (Mathews 1996). Systematic sampling scheme often provides better precision (i.e., smaller confidence intervals and smaller standard errors of population estimates) and more complete coverage of the target population than random sampling scheme (EPA QA/G-5S 2002). Sampling procedure and sample preparation for elemental analysis were done according to the guidelines described in the protocol of 2015 European moss survey (Frontasyeva and Harmens 2015). Sampling sites was positioned at least 300 m far from main roads, 100 m from local roads, and 200 m from villages or single houses. Sampling points was located at small forest clearings to reduce the through fall effects. Composite samples of ten subsamples collected within an area of 50 m × 50 m were used for analysis. Sampling sites in mountain areas were positioned in deep valleys, keeping the altitude lower than 1000 m. Samples were stored and transported in tightly closed paper bags. Coarse contaminants (litter, soil, animals) were carefully removed from moss samples. Moss samples were dried at room temperature for several days until a constant weight and were homogenized manually at a clean table surface. Unwashed green and green–brown parts of the moss stems that represent 3 years of the moss growth were selected for analysis. Disposable polyethylene gloves was used to avoid the potential contamination of samples during sampling and sample preparation. The geographical distributions of sampling sites are shown in Fig. 1 and Table 1.

Fig. 1
figure 1

The geographical distribution of sampling points (latitude, 41°00′N of the equator; longitude, 20°00′E of Greenwich)

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Table 1 Coordinates of sampling points (SP)
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Chemical Analysis

Total digestion of moss samples was performed by Microwave digestion (MARS, CEM, USA) according to the method presented by Stafilov et al. (2018). A 0.5-g moss sample was digested in Teflon digestion vessels in the presence of 7 ml of HNO3 (69%, m/V) and 2 ml of H2O2 (30%, m/V). All reagents used in this study were of analytical grade. The elements present in moss samples were determined by inductively coupled plasma atomic emission spectrometry, ICP-AES (Varian 715-ES, ICP optical emission). Arsenic (As) and cadmium (Cd) were determined by electrothermal atomic absorption spectrometry (ETAAS). The instrumental parameters of both methods are published at Stafilov et al. (2018) and Balabanova et al. (2010).

Hg was determined by cold vapor atomic absorption spectrometry (CVAAS) (Varian 10+ equipped with a homemade cold vapor system) as described at Lazo and Cullaj (2002). Wet digestion of homogeneous subsample (0.5-g sample and 10 ml of nitric acid 9:1 v/v in half pressure Teflon tubes) was applied for Hg digestion as was given at Lazo et al. (2018).

Three replicate per moss samples were digested, and three replicate measurements per digests were made during the analysis. The detection limits, calculated as the 3*SD of the average instrumental blanks measurements are reported in previous publications (Lazo et al. 2018). The ICP-AES and ETAAS analyses were done at the Institute of Chemistry, Faculty of Science, Sts. Cyril and Methodius University, Skopje, Macedonia. CVAAS analysis was done at the Department of Chemistry, Faculty of Natural Science, University of Tirana.

Quality Control

M2 and M3 international moss reference materials (Steinnes et al. 1997) were used to check the quality control of the ICP-AES and ETAAS analyses (Stafilov et al. 2018). Moss reference materials were analyzed together with moss samples at each 10-samples interval. The determined ICP-AES reference values reported by Stafilov et al. (2018) were in agreement with the recommended values. In addition, blank samples were measured parallel to the analysis of the moss samples. International plant reference material IAEA-140/TM (Fucus homogenate) was used to check the quality control of the CVAAS analysis (Lazo et al. 2018). The recovery of the investigated elements was checked by standard addition method. It ranged between 98.5% and 101.2% for ICP-AES, 96.9% to 103.2% for AAS. The differences between the mean contents of Hg from the respective certified values of reference material were within 15%. The recommended (Steinnes et al. 1997; Harmens et al. 2010) and the obtained values of element concentration of M2 and M3 reference moss samples are shown in Table 2. The mean content of Hg (0.036 ± 0.011 mg kg−1, DW) is in agreement with the mean certified value (0.038 mg kg − 1, DW).

Table 2 Recommended (Steinnes et al., 1997; Harmens et al. 2010) and obtained values for element concentration in reference moss samples M2 and M3 (ICP-AES and ETAAS analyses)
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Data Processing and Statistical Analyses

Statistical analysis was used to investigate the variability and spatial distribution of TM atmospheric deposition to assess the most probable pollution sources of the elements under investigation. The concentration data on the elements were interpreted on the basis of the results of descriptive statistic analysis. The distribution type of the data onto each element and their possible outlier concentrations were examined through the frequency distribution, and the frequency plots were confirmed by the statistical significance level at p > 0.05. Statistical method was applied to evaluate the background content of metals in moss samples. Matschullat et al. (2000) and Reimann et al. (2002) have used the upper concentration limits (UCL = median + 2*SDEV) to identify the outliers of each element. The UCL values are referred as the upper limit of geochemical variation, which were suggested as “threshold level” for clean up goal of environmental legislation (Reimann et al. 2002). The values of the lower concentration limits (LCL = median − 2*SDEV) are referred as the background content. For elements with high variation (CV% > 75%), the UCL and LCL level of each element are calculated as (median ± SDEV). The background content was calculated on the basis of the LCL level of each element that was replotted after excluding the outlier points higher than the respective UCL levels of the sorted original data (Qarri et al. 2014b). The average value of the outlier points lower than LCL level was used as country background content (BCi). Exponentially weighting moving average (EWMA) time series (Bekteshi et al. 2015; Qarri et al. 2014b; Salcedo et al. 1999; Morawska et al. 1998) were used to determine the respective LCL and UCL values of the elements.

The contamination of the most toxic elements were evaluated by calculating the contamination factors given by Fernandez et al. (2000):

$${\text{CF}} = {\raise0.7ex\hbox{${C_{i} }$} \!\mathord{\left/ {\vphantom {{C_{i} } {\text{BC}}}}\right.\kern-0pt} \!\lower0.7ex\hbox{${\text{BC}}$}}_{i}$$

where Ci is the median concentration of the ith element and BCi is its respective value of the country background concentration. The pollution was discussed on the basis of the contamination scale of each element given by Fernandez et al. (2000). The degree of contamination (Cdeg) was calculated as the sum of the contamination factors of all elements (Cdeg = ΣCFi) for each sampling site (Hakanson 1980). Mosses represent living organisms that are naturally exposed to metal atmospheric deposition for a long time on site specific base. Moss element concentrations may show the integrative measurements of the spatial distribution and temporal changes of trace metals that make those effective species for evaluating the atmospheric deposition risk of toxic metals. The pollution caused by most toxic metals, such as, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V, Zn, and Al, was evaluated by the models given by Tomlinson et al. (1980) and Boamponsem et al. (2010) by using the pollution load index (PLI), the PLIsite, and PLIzone calculated as follows:

$${\text{PLI}}_{\text{site}} = ({\text{CF}}{}_{1}*{\text{CF}}_{2} * \ldots *{\text{CF}}_{n} )^{1/n}$$
$${\text{PLI}}_{\text{zone}} = ({\text{PLI}}{}_{1}*{\text{PLI}}_{2} * \ldots *{\text{PLI}}_{n} )^{1/n}$$

There was no evidence for the safe contents of exposure or the threshold below which no adverse health effects occurs based on moss biomonitoring. For this reason, we applied the classification used by Hakanson (1980) and Zhang et al. (2011) to soils. Different authors have reported the use of PLI index in atmospheric deposition for assessing air quality (Antisari et al. 2011; Fernandez and Carballeira 2001). The potential ecological risk (RI) (Hakanson 1980) that represents the toxicity of metals and the environmental response was calculated as the sum of the risk factors of the elements As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V, Zn, and Al in moss samples:

$${\text{RI}} = \sum {T_{i} {\text{CF}}_{i} }$$

where, Ti represents the metal toxicity index (Hakanson 1980) of each element. The environmental classification and the values of TM toxicity factor (Ti) are shown in Table 3.

Table 3 Classification of pollution and the values of the metal toxicity index (Ti)
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The relationships between the elements in moss were tested by Pearson correlation analysis, confirmed by the statistical significance level, P < 0.01. Factor analysis (FA) was applied as an extension of the correlation analysis to assess the relationships between elements present in moss samples and to identify the most important factors that probably affect to the association of the elements in the same factor. FA may explore the hidden multivariate structures of the data (Astel et al. 2008; Reimann et al. 2002) and may clarify the links between the elements that tend to have similar origins or subsequently to develop similar associations on the data matrix. Each factor is explained on the basis of the associations of elements extracted from the correlation matrix. The statistical analyses were performed using the MINITAB 17 software package. Arc-GIS 10.2 in combination with local deterministic methods and the inverse distance weighting were used for mapping the spatial distribution of the elements and spatial interpolation of the FLsite. The FLsite is calculated as a percentile of the sum of the product of individual loads of each element (Li) and its respective site concentration (Ci) (Lazo et al. 2018; Allajbeu et al. 2017; Barandovski et al. 2008, 2015):

$${\text{FL}}_{\text{site}} = {\text{average}}\left( {100\frac{{\sum\limits_{i = 1 - n} {(C_{i} )_{\text{site}} } }}{{\sum\limits_{i = 1 - n} {(C_{i} )_{\hbox{max} } } }}L_{i} } \right)$$

Results

Trace Metal Concentrations in the Moss Samples

Descriptive statistic analysis was applied to 2015 AMS data. The most important parameters, such as mean, median, minimum, maximum, coefficient of variation (CV%), the first and third quartiles, as well as the interquartile range (IQR), are shown in Table 4.

Table 4 Summary of 2015 AMS heavy metal descriptive statistic data
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The sequence of the distribution of elements in moss samples was Hg < Cd < As < Pb < V<Ni < Cr < Cu < Zn < Al < Fe. The elements Hg, Cu, Zn, Fe, and Al show moderate variations (CV% < 75%); IQR < Q1; Q1 and Q3 values were likely focused to the median than to the minimum and/or maximum concentration values by indicating that the data show a central tendency. As, Cd, Pb, V, Ni, and Cr show high values of variability (CV% > 75%), IQR > Q1, and significant differences of Q1 and Q3 values from the respective median concentrations by indicating a high spreading of the data. The concentration data onto Hg, Cu, Zn, Fe, and Al are characterized by high differences between Q1 and minimum concentration values; small differences between Q3 and maximum concentration values, and high positive values of skweness and kurtosis. It indicates that the data are skewed right and are affected by several factors.

Spatial Distribution of the Elements

Arsenic, Cadmium, Copper, Lead, and Zinc

GIS maps were plotted to investigate the distribution patterns of As, Cd, Cu, Pb, and Zn in moss samples (Fig. 2).

Fig. 2
figure 2

GIS maps of airborne deposition of a As, b Cd, c Cu, d Pb, and e Zn in Albania evaluated by 2015 moss biomonitoring

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High concentrations of As, Cd, and Cu were found in moss samples positioned in a wide belt stretched from the north to the south in the eastern part of the country (Fig. 2a–c). Another area with high content of As, Cd, and Zn was found in the south, around oil and gas production area, and Ballshi oil refinery (Fig. 2b, e). The next anomalies with high As content in moss samples were found around the main ports of Albania in Dures, Vlora, and Saranda areas. The distribution pattern of Pb and Zn were more or less uniform throughout the whole territory. High Pb and Zn concentrations were found in the St. 36, 40, and 26, and subcontent of Pb and Zn concentrations were found in S-E part (St. 13, 18, 22, and 27). The highest Pb content was found in moss samples positioned in the north.

Chromium and Nickel

The distribution pattern of Cr and Ni were quite similar (Fig. 3). High content of Cr and Ni were found in the areas close to the metallurgical, cement production (St. 31), and petrochemical plants (St. 22). High Cr and Ni concentrations were found in the chromium and nickel mineralized area extended as a belt from the north to the southeast of Albania. The highest Ni concentrations were found in the middle of the belt close to the areas enriched with Ni, Fe–Ni, and Ni silicate mineralization. As for Cr, the highest moss concentration was found in sampling sites of Bulqiza and Librazhd areas that are characterized by high Cr minerals and Cr mining activity. High concentrations of Cr and Ni are associated with the geological factors of Cr and Ni mineral resources, mineral dumps of the former mining industry, and Cr, Ni mineral processing industry. The same distribution patterns of Cr and Ni also were found for 2010 AMS samples (Lazo et al. 2018).

Fig. 3
figure 3

GIS maps of airborne deposition of a Cr and b Ni in Albania evaluated by 2015 moss biomonitoring

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Mercury

The Hg distribution was likely uniform in the most of the territory (Fig. 4). Two anomalies with high Hg content were found in south. The highest Hg concentration was founded in the cross border between Albania, Greece, and Macedonia (St. 13, 18, 22, and 27) (Fig. 4), and the next Hg high content was found in the southern part (St. 2, 3, 4, and 5) of Albania.

Fig. 4
figure 4

GIS maps of airborne Hg deposition in Albania evaluated by 2015 moss biomonitoring

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Fig. 5
figure 5

GIS maps of moss elements concentration: a Al, b Fe, and c V in Albania evaluated by 2015 moss biomonitoring

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Aluminum, Iron, and Vanadium

Al, Fe, and V showed similar distribution patterns onto 2015 moss samples. The highest concentrations of Al, Fe, and V were found in the north and in the central part of the country (Fig. 5). Some local anomalies were found at sampling sites in the vicinity of coal deposits (St. 6), as well as of Cr and Fe–Ni mineral belt (St. 18, 22, 27, 28, 32, 40, and 41).

Temporal Trend of the Elements

The 2015 and 2010 AMS concentration data were statistically tested for significant differences by applying the Mann–Whitney test (α = 0.05).

No significant differences (α < 0.05) were found between 2010 and 2015 moss elements median concentration of Al, Cd, Fe, Pb, and V. The content of these elements was likely stable for both moss monitoring periods. Significant differences (α > 0.05) were found between median concentration of As, Cr, Cu, Hg, Ni, and Zn in moss samples collected on 2010 and 2015. Significant increment were found for As, Cr, Cu, Hg, Ni, and Zn 2015 moss concentrations compared with those of 2010, respectively: Cr (+ 95%), Cu (+ 79%), As (+ 37%), Zn (+ 34%), and Ni (+ 29%). The concentration of Hg had gone in a diverse sense. It shows a high decline in moss samples of 2015 compared with those of 2010.

The content of the elements in moss samples of Albania were compared with those of European moss survey (Harmens et al. 2013a, b). Al, Fe, Cr, Ni, and V were high and concentrations of Cd, and Pb were lower in moss samples of Albania compared to the most European countries (Harmens et al. 2013a, b).

Evaluation of Contamination Indexes CF, PLI, and RI

Contamination Factors

The contamination factors (CF) data for the elements As, Cd, Pb, Cr, Co, Cu, Hg, Ni, Pb, Zn, Fe, and Al are listed in Table 5.

Table 5 The percentile and number of stations (shown in brackets) under different contamination scale (Fernandez et al. 2000)
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The sequence of the distribution of the CF values was Cu < Zn < Fe < Al < Hg < As < V<Cr < Pb < Ni. Cu and Zn show the lowest contamination scale (median values = 1.5 and 1.6, respectively). It ranged from the suspected contamination scale to the slightly contamination scale (CF = 3.5–8.5) for Cu, and from the suspected contamination scale (CF = 1–2), to the moderate contamination scale (CF = 2–3.5) for Zn. The median CF values of Fe, Al, Hg, and As ranged from 2 to 3.5, which indicated a slight contamination scale. The CF values ranged from slight to the suspected contamination scales at approximately 89% of the entire territory, and from the moderate to high contamination scale at 11% of the entire territory. Al shows higher values of CF that ranged from slight to the suspected contamination scales at 74% of the entire territory, and from the moderate to high contamination scales at 25% of the entire territory.

The elements Cd, Cr, Ni, and Pb had shown the highest CF values, which were classified as high to extremely high contamination scale at about 30–50% of the entire territory. Based on the CF median values, the elements Cd, Cr, Ni, and Pb were associated with the moderate (C4) contamination scale. Similar results were obtained on 2010 AMS (Allajbeu et al. 2017).

The Degree of Contamination (C deg)

Further evaluation of the contamination was performed by analyzing the degree of contamination, Cdeg data (Fig. 6).

Fig. 6
figure 6

The dot plot diagram of Cdeg data. (1) Considerable degree of contamination; (2) Very high degree of contamination

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Cdeg values ranged from 18.5 to 143.5. Cdeg data show that 27% of the territory (15 sites) show considerable degree of the contamination (16 ≤ Cdeg < 32) and 73% (40 sites) show high degree of contamination (median of Cdeg = 54.7). It indicates serious anthropogenic pollution (Hakanson 1980) at the most territory of the country.

Pollution Load Index

The pollution load index (PLI) was assessed as the environmental risk caused by the contaminated soil (PLIsoil) and/or atmospheric deposition (PLImoss) (Boamponsem et al. 2010). The PLImoss shows the level of environmental contamination and highlights the sites with higher pollution than the others.

The data of PLIsite indicate that 49.1% of the total number of the sampling sites shows moderate pollution. It is confirmed by the value of the PLIzone = 3.68, calculated from the data onto 55 sampling sites, that show moderate pollution at the entire territory. As it was expected, high ecological risk values were found at the areas with high concentrations of metal moss concentrations. The most polluted zone was extended over the N-E direction that is affected by relatively high metal concentrations (Fig. 7a).

Fig. 7
figure 7

GIS maps of spatial distribution of PLIsitea and RI b data

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The Potential Ecological Risk (RI)

The methodology of the screening ecological risk assessments (SERAs) of toxic metals, given by Landis et al. (2013) and Suter (1995) to evaluate the air quality, was applied to Albania during 2010 moss survey (Allajbeu et al. 2017). This work continued the previous study on toxic metal atmospheric deposition and risk assessment of air pollution in Albania. The RI values of the elements show moderate to high contamination scale. It ranged from 188 to 1287, RI median = 368, which was similar to the RI median value of 2010 (RI = 330) (Allajbeu et al. 2017). The RI values of 2015 and 2010 indicate a considerable potential ecological risk caused by the elements present in moss samples. The elements Hg, Cd, and As show the highest RI values in moss samples by pointing those as the most important contaminants of atmospheric deposition responsible to ecological risk in Albania. Twenty-one sampling sites, or 38% of the total samples, showed moderate ecological risk (RI = 150–300). The next 38% showed a considerable potential ecological risk, and the remaining 14% showed high potential ecological risk. The Hg, Cd, As, Pb, Ni, and Cr showed a total contribution to the 2015 RI values that ranged from 90% to 95% of the total RI value (Hg = 36%, Cd = 27%, As = 10%, Pb = 7%, Ni = 11%, and Cr = 5%).

Discussion

Overview of Metal Concentration

Moss metal distribution of Albania show diverse patterns that presents diverse geographic variability in metal concentration (Figs. 3, 4, 5, 8). In principle, the elements observed in moss samples may originate from local geological factors (Aubert et al. 2006; Agnan et al. 2013: Allajbeu et al. 2017), biological, and anthropogenic sources. Regional differences were observed in moss metal concentrations that may cause different exposure level for different metals and for different areas. The metals’ exposure can occur through a variety of routes, such as dust inhalation, fume, or metals’ vaporization like mercury, ingested involuntarily through food and drink that tends to persist in liver, bones, and kidneys for years or decades (Hu 2002). The distribution pattern of TM in current moss is discussed as follows.

Fig. 8
figure 8

The comparison of HM median concentrations (mg/kg) between 2015 and 2010 AMS

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As, Cd, Cu, Pb, and Zn

In general, the presence of As, Cd, Cu, Pb, and Zn in moss samples is associated with long range atmospheric transport from other parts of Europe (Harmens et al. 2015), and with local atmospheric emission sources that may play an important role in the metal contamination during dry and wet depositions.

Arsenic in soil is generally considered of geological origin, with higher background concentration in clayey soils (Tóth et al. 2016) and in sulfide mineralizations. The northern part of Albania (Lazo et al. 2007) is known for its sulfide or metal arsenates. The main As anomalies in moss samples lies in the northern region (Fig. 2a), known as Cu and Ni sulfide minerals (Lazo et al. 2007), and thus may confirm the dominance of geological origin of As in this area. The next emitting source should be the windblown dust from industrial waste deposits and sulfide mineral dumps (Lazo et al. 2018), as well as the anthropogenic emitting sources. The most probable local anthropogenic sources of As should be from high temperature iron processing, fuels combustion, oil refinery, oil and gas industry, waste incineration, traffic emission, and wind blowing dust from industrial waste deposits. The anomaly found in the area lies at SE-SW part of Albania, known as agriculture area, is probably linked with the application of pesticides used in the past. High As concentration also was found in the Fieri area (St. 26) mentioned as a “hot spot” (UNDP CO-ALBANIA 2018) of a former nitrite fertilizers chemical plant that had used the arsenic as catalyzer during technological processing.

Cadmium is a trace element in the earth crust and mainly occurs in association with the sulfide ores. Cd in the atmosphere is emitted from a wide variety of natural and anthropogenic sources, such as airborne soil particles, forest fires, coal and oil combustion, waste incineration, iron and steel production, and cement production (ATSDR 2008). The highest Cd content was found in NE-SE metal mineralization belt mostly of Cr, Cu, Ni, and Fe deposits, and the lower in western coastal area (Fig. 2b), which is characterized by carbonate rocks and sediments of Adriatic and Ionian Seas (NAMR 2010). High Cd content in the south (Fig. 2b) is probably derived from fuels combustion, oil refinery, oil, and gas industry of this area. Weathering and erosion of cadmium-bearing rocks are probably the most important natural source of Cd in Albania.

Lead and Zinc

The distribution pattern of Pb and Zn were more or less uniform throughout the whole territory. The main sources of Pb in Albania are traffic and industrial emission sources. While traffic shows a similar extent throughout the country, some specific industrial activities are focused in the central part. The concentrations of Pb and Zn were lower in moss samples of Albania compared with the mosses of the most European countries (Harmens et al. 2013a, b). High Pb moss concentration was found in the north. It is an area with low anthropogenic emission and high content this area is not clear. High Pb and Zn concentrations were founded in the areas that are characterized by intensive mining and ferro-chromium industry and dense traffic (St. 36 and 40), respectively, on Bulqiza and Burrel. The next high Pb content in Gramsh area 9 St. 260 is probably affected by the former battery plant and its waste disposals positioned in this area. Thus, industrial emissions, road transport, and long-range transport could be the main factors affecting higher contents of Pb and Zn in these areas. A subcontent of Pb and Zn concentrations founded in SE (St. 13, 18, 22, and 27) is probably linked with transboundary pollution. From the EMEP Report (2015) for Pb, Cd, and Hg data, a high impact from Greece is evident in this area, which is in the same line with current Pb moss data.

Copper

Cu occurs naturally in the soil, and minerals and may enter the air as windblown dust particles (ATSDR 2004), mostly in the form of fine particulate matters. On the other hand, Pb often is founded near mines, smelters, industrial areas, landfills, and waste disposal sites and can be emitted in the air through different ways. Ore processing, windblown metallurgical dust, waste dumps, combustion of fossil fuels and wastes, wood production, and natural sources, such as windblown dust from native soils, decaying vegetation, forest fires, and sea spray, are the main Cu emitting sources in the air and is then carried back to earth through the atmospheric deposition (ATSDR 2004). Cu anomalies in mosses positioned in NE-SE part of the country are probably affected by the geological factors of the area that are known as Cu and Ni sulfide minerals. Another probable emitting source should be the wind blowing dust from industrial waste deposits and sulfide mineral dumps (Lazo et al. 2018). Higher Cu in different sites (St. 28, 40, 41, 49, 50, and 51) is mostly affected by geological factors, mining activity, metal smelting, combustion of fossil fuels, and the use of pesticides in the S-E part of the country (St. 2, 6, 12, 18, and 23).

Mercury

Hg is a naturally occurring metal that is widely used in different processes and manmade products (ATSDR 1999). It occurs in the environment in different forms, such as metallic, inorganic, and organic mercury. On the other hand, mercury is a global pollutant. Long-range transport has been shown as an important source of mercury in Europe (Harmens et al. 2015). Hg distribution was shown to be more or less uniform in 2015 moss samples. High Hg content was observed in the cross border between Albania, Greece, and Macedonia (St. 13, 18, 22, and 27) and the next one in the SE part of Albania (Fig. 4). A relatively uniform distribution should be the goal, because the total Hg predominately depend on the relatively stable global/hemispheric background concentration, and only the influence from major sources may result in higher values (Wangberg et al. 2001). Similar distribution view of Hg in Albania was reported by the EMEP maps obtained by the EMEP gridded emission data (EMEP Report 2015). On the same EMEP Report (2015) for Hg data in Albania, a high impact from Greece was evident on Hg atmospheric deposition in the cross border between Albania, Greece, and Macedonia that may indicate the possibility of transboundary Hg emission. The next area with high Hg content was found in the south (St. 2, 3, 4, and 5), which is likely derived by shipping emission and coal combustion facilities as the main local source of Hg emissions in this area (EMEP Report 2015).

Chromium and Nickel

Cr and Ni are naturally present in the earth crust and are emitted to the atmosphere via natural sources, such as windblown dust and forest fires, and anthropogenic sources, such as mining, smelting, refining, fossil fuel combustion, and waste incineration (ATSDR 2005, 2012). High concentration of Cr and Ni was found in N-E directions that follow the direction of Cr, Ni mineralization belt of Albania. The highest Cr and Ni concentrations were found in the middle of the belt close to the area enriched with Cr, Ni, Fe–Ni, and Ni silicate mineralization that indicate the effect of geological factors in the form of wind blowing fine mineral dust particles. In general, the mineral dust particles may be emitted during the mobilization and fragmentation process of original undispersed soil, subject to wind erosion (Perlwitz et al. 2015). The next area with high content of Cr and Ni were found close to the metallurgical plant, cement production, and petrochemical plan that may indicate the anthropogenic sources of Cr and Ni in moss samples of these areas. Beside the long-range transport, the presence of Cr and Ni in mosses of Albania is mostly associated with geological factors, mineral wastes of the former mining industry, and mineral processing industry.

Aluminum, Iron, and Vanadium

Al, Fe, and V are typical crustal elements that show similar behaviors in environmental and atmospheric deposition as the result of the emission of fine soil dust particles and iron metallurgy. A 2010 moss survey data showed higher median values of Al, V, and Fe moss concentrations of Albania compared with the respective medians of Europe. A 2015 moss concentration data of these elements are higher than those of 2010s, and the same situation should be expected for 2015 data. High contents of Al, V, and Fe are probably derived by fine soil dust particles in the air that is mostly originates from soils under erosion in sparse vegetation areas and low land use areas of Albania (Qarri et al. 2013). On the other hand, the local anomalies that were found at sampling sites in the vicinity of coal deposits (St. 6), as well as those of Cr and Fe–Ni mineral belts (St. 18, 22, 27, 28, 32, 40, and 41), are probably linked with the emission of the finest mineral dust particles in the air. The highest concentration of Al, Fe, and V were found at the areas of high Fe minerals and not at industrial areas (Elbasan aera). It may indicate a stronger effect of the wind-blown soil dust, which represents the geochemistry of soil and/or the historical deposition of these elements in soil in Al, Fe, and V distribution pattern, compared with the effect of anthropogenic sources of metal processing industry. High concentrations of vanadium also were found in the coastal area, particularly close to the main harbors of Dures and Shengjin, and at the Ardenica area. Vanadium is an anthropogenic element in the air that is derived from shipping activity, crude oil refinery, gas and oil industry, and burning of fossil fuels (Viana et al. 2014), which are present in the western part of the country.

Temporal Trend of the Elements in Moss Samples

Significant differences (p > 0.05) found for the elements Cr, Cu, As, Hg, Zn, and Ni in 2015 moss compared with 2010 moss were probably revealed to different emission level and to the different deposition rates of pollutants from the atmosphere to the terrestrial ecosystem. The average concentrations of Cr, Cu, As, Zn, and Ni in 2015 moss was increased compared with 2010 moss element concentration, whereas Hg was declined. A similar decline in Hg atmospheric deposition was found in northwest Europe compared with the Mediterranean area. The years 1991–2010 was reported as the longest drought period in Mediterranean area (Spinoni et al. 2015, 2017). The average concentrations of airborne mercury was generally lower in northwest Europe than in the Mediterranean region where the mercury-enriched minerals are abundant (Wangberg et al. 2001). Lower Hg values of the northern Europe compared with that in the south may be due to the washout process being more efficient in the removal process of Hg during long period of wet weather (Wangberg et al. 2001). It may indicate that different climatic factors that may change year after year have an important contribution to the total atmospheric flux of trace metals. As described by Sweet et al. (1998), wet and dry deposition may stimulate different processes of metals deposition flux. Wet deposition of metals is more likely controlled by the amount of precipitation, whereas dry deposition flux is mostly controlled by the concentration of trace metals present on large particles (Sweet et al. 1998). On the other hand, the Hg0 emission during the high temperatures and dry deposition of 2010 (Wu et al. 2018; Steinnes et al. 2003; Morales-Boquero et al. 2013) was reduced after 2009 when mercury polluted of “Vlora hot-spot” area in the southwest of Albania was cleaned up. The area was highly polluted by a huge content of metallic Hg in soil, caused by the former chlor-alkali plant that was destroyed in 1997. It posed a serious Hg0 supply in the local atmospheric air (Lazo and Reif 2013). Dore et al. (2014) showed that wet deposition was the most important process transferring the metals from the atmosphere to the land surface that may show an increase in the concentration and the deposition flux of As, Cd, Cr, Cu, Pb, Ni, Se, V, and Zn. The rainfall scavenging particles has been documented in other moss biomonitoring studies (Amodio et al. 2014; Morales-Boquuero et al. 2013; Connan et al. 2013; Steinnes et al. 2003). In addition, the wind-driven resuspension of surface dust is another factor that contributes to atmospheric trace metal concentrations, which represent in the environment the historic emissions. The Albanian average precipitation data show different periods of moderate to high rainfall during 2015, a relatively dry weather during 2010 (https://…/albania/precipitation). The years 1991–2010 registered as the longest and most severe drought events in the Mediterranean area (Spinoni et al. 2015, 2017).

Assessment of the Air Quality

Based on the concentrations of metals, the background level of each element in the moss samples, and in the toxicity index values (Ti) of each element, the CF, Cdeg, PLI, and RI indexes that was used for the assessment of air quality show that the territory of Albania is mostly affected by a relatively high contamination level. The eastern part of Albania is highly affected by high concentrations of metals, and the moss samples of the western part of Albania show lower metal concentrations. Albania is characterized by complex geochemical settings, mine and metal processing industry, low percentage of land use, and high erosion rate. The slag dumps of different minerals, such as Fe, Fe–Ni, Cu, and Cr minerals, are deposited in different parts of the territory that may pose high probability of emitting sources mostly as wind blowing soil dust and mineral dust fine particles. RI values are mostly affected by the concentrations of the most toxic elements with high toxicity index, Ti. In general, Hg, Cd, and As are minor elements in moss samples, and the high RI values show the effect of their high Ti values that make these elements as dangerous ones that may pose a high level of ecological risk.

The area under considerable contamination level is clearly extended over the N-E direction (Figs. 2, 4, 7, 8), which is characterized by high concentrations of trace metal loading (Lazo et al. 2018). This area is strongly affected by geological factors and intensive mining and metal processing industry. The next area was positioned in S-W direction that is mostly affected by the most toxic elements (As, Hg, and Cu) (Fig. 2). In addition, the cultivated areas are extended mostly over the western lowland and in S-E direction, which are classified as moderate to highly polluted areas (Fig. 7a, b). The contaminated sites may affect the crop cultivation for human or animal consumption that may potentially accumulate trace metals, and thus may pose risk to the human and animal health through the food chain pathway. Compared with the soil, the biomagnifications of metal concentration in moss tissues is known (Antisari et al. 2011), and it may be an indice of the accumulation of toxic elements in the food chain.

Multivariate Analysis

Very strong and significant positive correlations (r2 > 0.9, p < 0.001) were found by Pearson correlation analysis at the pairs of elements Al–Fe, Al-V, and Fe-V by indicating their similar behaviors or similar sources of origin in current moss samples. Cr-Ni, Cr–Pb, and Zn-Pb show strong and significant positive correlations (0.8 > r2 > 0.6, p < 0.001); As-Cd, Cu, Zn; Cd-Cu. Zn-Cd, Fe, Al, and V show moderate and significant correlations (0.6 > r2 > 0.4, p < 0.01) between the respective pairs of elements (Table 6). Hg stands alone and do not correlate with the elements under investigation by indicating its different behavior or sources of origin.

Table 6 Pearson correlation coefficients between element concentrations in moss samples of Albania
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To identify the origin of the elements in moss samples, Factor analysis is applied to the concentration data. Four main factors were extracted (Eigen values > 1) that represent 82.5% of the total variance. The extracted factors were interpreted as the main source categories that contribute to the element moss concentrations. The results of the factor analysis are shown in Table 7.

Table 7 Results of the FA (Sorted Varimax Rotated Factor Loadings and Communalities)
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The extracted factors can be interpreted as follows:

  • Factor 1 was the strongest factor that represents 31.0% of the total variance. It is associated by high loads of Al, Fe, V (> 0.97) and partly of Zn (0.476). This association is typical of crustal elements (Vinogradov 1962) that are probably derived from the natural pollution of wind blowing soil dust emission that indicates the role of wind blowing soil dust emission as an important source of TM in atmospheric deposition of Albania.

  • Factor 2 was the next strongest factor that represents 21.1% of the total variance. It is associated with high loads of Cu, Cd, As, and Zn (0.66–0.8). This association was probably derived from anthropogenic sources of fossil fuel combustion, iron, steel and cement production, and traffic emission (Harmens et al. 2010; Lazo et al. 2013), as well as from geological origin from local emission of wind-blowing mineral particles (Lazo et al. 2018). Long-range transport from other parts of Europe is another possible source of these elements in moss samples (Harmens et al. 2010).

  • Factor 3 that represents 20.4% of the total variance is another strong factor. It is associated with high loads of Cr and Ni (0.87–0.91) and moderate loads of Pb (0.66). This association is likely related to geological sources of Cr and Ni (Lazo et al. 2018) and probably is associated with industrial emission from Cr and Ni mining and processing industry (Cr, Ni, and Pb) (Lazo et al. 2013, 2018).

  • Factor 4 is the weakest factor that represents only 10.0% of the total variance. It was linked with high loads of Hg. Mercury is a global pollutant that shows different behavior with other elements in current moss samples. Mercury occurs naturally in the environment and is diffused from the Earth’s mantle, evaporated from the sea surface, and geothermal activity by entering the atmosphere. Long-range transport is another important source of Hg in moss samples (Harmens et al. 2010).

Conclusions

Trace metal contamination is among the main threats to atmospheric deposition, because it is a component of the air that we breath. Moss biomonitoring survey provides a unique opportunity for the assessment of metal contamination in atmospheric deposition in local and continental range. Based on the moss elements concentration, the spatial distribution maps, which predict the concentrations of As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, Zn, and Al, are produced for the whole territory of Albania. Moss metal distribution of Albania shows diverse patterns for different elements by presenting a diverse geographic variability in moss metal concentrations. The content of the elements Al, Fe, Cr, Ni, and V were high, and concentrations of Cd and Pb were lower in moss samples of Albania compared with most European countries. The eastern part can be classified as highly polluted areas from anthropogenic elements derived by geological and anthropogenic emission sources. It may affect the crop cultivation for human or animal consumption that may accumulate trace metals and thus may pose a risk to human and animal health. It is shown that the western agricultural land area can be considered a safer area for food production. The anthropogenic sources of these elements are likely clearer than their natural background. Hg mostly originated from long-range pollution and transboundary pollution. Compared with the metal contents of moss collected in 2010, significant differences were found in the concentrations of As, Cr, Cu, Hg, Ni, Pb, and Zn. The differences between two moss surveys may reflect changes in the bioavailability of the elements, resulting from wet and dry deposition respectively during 2015 and 2010 moss biomonitoring survey. The pollution loading index applied to assess the air quality and the content of metal contamination indicated moderate pollution throughout Albania. Examination of the potential ecological risk consequences found that As, Cd, Cr, Hg, Ni, and Pb pose the highest potential ecological risks, particularly in areas with high metal contents. The elements under investigation were mostly originated from long-range transport, local natural, and anthropogenic emission sources and showed high contamination and ecological risk in the most part of the territory. Due to high moss metal content, in particular in the eastern regions of Albania, where some tendencies and hotspots were identified, a continuous and detailed monitoring and assessment is suggested.