The effect of sampling scheme in the survey of atmospheric deposition of heavy metals in Albania by using moss biomonitoring

The atmospheric deposition of heavy metals in Albania was investigated by using a carpet-forming moss species (Hypnum cupressiforme) as bioindicator. Sampling was done in the dry seasons of autumn 2010 and summer 2011. Two different sampling schemes are discussed in this paper: a random sampling scheme with 62 sampling sites distributed over the whole territory of Albania and systematic sampling scheme with 44 sampling sites distributed over the same territory. Unwashed, dried samples were totally digested by using microwave digestion, and the concentrations of metal elements were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES) and AAS (Cd and As). Twelve elements, such as conservative and trace elements (Al and Fe and As, Cd, Cr, Cu, Ni, Mn, Pb, V, Zn, and Li), were measured in moss samples. Li as typical lithogenic element is also included. The results reflect local emission points. The median concentrations and statistical parameters of elements were discussed by comparing two sampling schemes. The results of both sampling schemes are compared with the results of other European countries. Different levels of the contamination valuated by the respective contamination factor (CF) of each element are obtained for both sampling schemes, while the local emitters identified like ironchromium metallurgy and cement industry, oil refinery, mining industry, and transport have been the same for both sampling schemes. In addition, the natural sources, from the accumulation of these metals in mosses caused by metalenriched soil, associated withwind blowing soils were pointed as another possibility of local emitting factors

First survey of atmospheric heavy metal deposition in Kosovo using moss biomonitoring

Bryophytes act as bioindicators and bioaccumulators of metal deposition in the environment. The atmospheric deposition of Cd, Cr, Cu, Fe, Hg, Ni, Mn, Pb, and Zn in Kosovo was investigated by using carpet-forming moss species (Pseudocleropodium purum and Hypnum cupressiforme) as bioindicators. This research is part of the European moss survey coordinated by the ICP Vegetation, an International Cooperative Programme reporting on the effects of air pollution on vegetation to the UNECE Convention on Long-range Transboundary Air Pollution. Sampling was performed during the summer of 2011 at 25 sampling sites homogenously distributed over Kosovo. Unwashed, dried samples were digested by using wet digestion in Teflon tubes. The concentrations of metal elements were determined by atomic absorption spectrometry (AAS) equipped with flame and/or furnace systems. The heavy metal concentration in mosses reflected local emission sources. The data obtained in this study were compared with those of similar studies inneighboring countries and Europe (2010–2014 survey). The geographical distribution maps of the elements over the sampled territory were constructed using geographic information system (GIS) technology. The concentrations of Cr, Ni, Pb, and Zn were higher than the respective median values of Europe, suggesting that the zones with heavy vehicular traffic and industry emission input are important emitters of these elements. Selected zones are highly polluted particularly by Cd, Pb, Hg, and Ni. The statistical analyses revealed that a strong correlation exists between the Pb and Cd content in mosses, and the degree of pollution in the studied sites was assessed

Spatial distribution and temporal trend of airborne trace metal deposition in Albania studied by moss biomonitoring

This study describes the assessment of air quality in Albania using moss biomonitoring. The moss species, Hypnum cupressiforme (Hedw) sps., was used in this study. Mosses were collected during August and September 2015 at 55 sampling sites more or less homogeneously distributed over the entire territory of the country. The spatial distribution and temporal trends of trace metal atmospheric deposition were studied through the determinationof twenty inorganic elements, Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Li, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn. ICP-AES, AAS (As and Cd) and CV AAS (Hg) analysis were used to determine the concentration of the elements. The obtained data show significant differences in the spatial distribution of the elements derived from different emission sources. High emission loads of anthropogenic elements (Cr, Ni, Cu, As and Zn) were detected in the East, and of sea salt elements, particularly Na and K, in the Western coastal line. The distribution trend of the trace metals was studied by comparing the current data with the data of a similar study performed in 2010. Due to the differences in airborne metal concentrations, their scavenging ratios from the atmosphere to the terrestrial ecosystems, and their different uptake-leaching rates during wet and dry deposition respectively of 2015 and 2010 moss grown period, different concentration levels were found in 2010 and 2015 moss metal concentrations. The 2015 moss concentration levels of anthropogenic elements Cr, Ni, Cu, As, Zn and Na had increased, while K, Mg and Hg moss concentration data had declined. Other elements show non significant differences in mosses of both monitoring periods. The contamination levels that were evaluated by calculating the contamination factor (CF) for each element provided similar results for the 2015 and 2010 moss survey. Factor analysis (FA) was applied to identify the possible sources of elements in the 2015 moss samples. Five dominant factors were identified representing longrange and local atmospheric transport of wind-blown soil dust particles (F1); local emission from chromium industry and wind-blown mineral dust particles (F2); anthropogenic sources of traffic emission and wind-blown fine mineral dust particles derived from geogenic origin natural transport from the marine environment (F4); and long-range atmospheric deposition (F5). This study emphasis that moss biomonitoring combined with data analysis and inventory of emission sources are important tools to assess air quality in Albania

Origin and spatial distribution of metals in moss samples in Albania: a hotspot of heavy metal contamination in Europe

This study presents the spatial distribution of 37 elements in 48 moss samples collected over the whole territory of Albania and provides information on sources and factors controlling the concentrations of elements in the moss. High variations of trace metals indicate that the concentrations of elements are affected by different factors. Relations between the elements in moss, geochemical interpretation of the data, and secondary effects such as redox conditions generated from local soil and/or long distance atmospheric transport of the pollutants are discussed. Zr normalized data, and the ratios of different elements are calculated to assess the origin of elements present in the current moss samples with respect to different geogenic and anthropogenic inputs. Factor analysis (FA) is used to identify the most probable sources of the elements. Four dominant factors are identified, i.e. natural contamination;dust emission from local mining operations; atmospheric transport of contaminants from local and long distance sources; and contributions from air borne marine salts. Mineral particle dust from local emission sources is classified as the most important factor affecting the atmospheric deposition of elements accumulated in the current moss samples. The open slag dumps of mining operation in Albania is probably the main factor contributing to high contents of Cr, Ni, Fe, Ti and Al in the moss. Enrichment factors (EF) were calculated to clarify whether the elements in the present moss samples mainly originate from atmospheric deposition and/or local substrate materials

Spatially valid data of atmospheric deposition of heavy metals and nitrogen derived by moss surveys for pollution risk assessments of ecosystems

For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (1990–2010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (1990–2010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (1990–2013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey. Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients. Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Modelling and mapping heavy metal and nitrogen concentrations in moss in 2010 throughout Europe by applying Random Forests models

Objective: This study explores the statistical relations between the concentration of nine heavy metals(HM) (arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb),vanadium (V), zinc (Zn)), and nitrogen (N) in moss and potential explanatory variables (predictors)which were then used for mapping spatial patterns across Europe. Based on moss specimens collected in 2010 throughout Europe, the statistical relation between a set of potential predictors (such as the atmospheric deposition calculated by use of two chemical transport models (CTM), distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils) and concentrations of HMs and nitrogen (N) in moss (response variables) were evaluated by the use of Random Forests (RF) and Classification and Regression Trees (CART). Four spatial scales were regarded: Europe as a whole, ecological land classes covering Europe, single countries participating in the European Moss Survey (EMS), and moss species at sampling sites. Spatial patterns were estimated by applying a series of RF models on data on potential predictors covering Europe. Statistical values and resulting maps were used to investigate to what extent the models are specific for countries, units of the Ecological Land Classification of Europe (ELCE), and moss species. Results: Land use, atmospheric deposition and distance to technical emission sources mainly influence the element concentration in moss. The explanatory power of calculated RF models varies according to elements measured in moss specimens, country, ecological land class, and moss species. Measured and predicted medians of element concentrations agree fairly well while minima and maxima show considerable differences. The European maps derived from the RF models provide smoothed surfaces of element concentrations (As, Cd, Cr, Cu, N, Ni, Pb, Hg, V, Zn), each explained by a multivariate RF model and verified by CART, and thereby more information than the dot maps depicting the spatial patterns of measured values. Conclusions: RF is an eligible method identifying and ranking boundary conditions of element concentrations in moss and related mapping including the influence of the environmental factors

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

&#956;-Hexathiometadiphosphato-bis[(1,4,7,10,13,16-hexaoxacyclooctadecane-&#954;6O)rubidium] acetonitrile disolvate

The asymmetric unit of the title compound, [Rb2(P2S6)(C12H24O6)2]&#183;2CH3CN, contains one half of an [Rb(18-crown-6)2]2[P2S6] unit and one acetonitrile solvent molecule. The [Rb(18-crown-6)]2[P2S6] unit is completed by inversion symmetry. Its Rb+ ion is situated near the centre of the macrocyclic cavity, but is displaced by 0.8972&#8197;(1)&#8197;&#197; from the O atoms of the crown in the direction of the [P2S6]2&#8722; moiety. The overall coordination number of the cation is eight, defined by the six crown ether O atoms and by two terminal S atoms of the [P2S6]2&#8722; anion. The hexathiometadiphosphate anion is built up from two tetrahedral PS4 units joined together by a common edge. The crystal structure is characterized by alternating layers of [Rb(18-crown-6)]2[P2S6] and acetonitrile solvent molecules stacked along [010]