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

Trace elements and nitrogen in naturally growing moss Hypnum cupressiforme in urban and peri-urban forests

We monitored trace metals and nitrogen using naturally growing moss Hypnum cupressiforme Hedw. in urban and peri-urban forests of the City Municipality of Ljubljana. The aim of this study was to explore the differences in atmospheric deposition of trace metals and nitrogen between urban and peri-urban forests. Samples were collected at a total of 44 sites in urban forests (forests within the motorway ring road) and peri-urban forests (forests outside the motorway ring road). Mosses collected in urban forests showed increased trace metal concentrations compared to samples collected from peri-urban forests. Higher values were significant for As, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Tl and V. Within the motorway ring road, the notable differences in element concentrations between the two urban forests were significant for Cr, Ni and Mo. Factor analysis showed three groups of elements, highlighting the contribution of traffic emissions, individual heating appliances and the resuspension of contaminated soils and dust as the main sources of trace elements in urban forests

Analiza sedimenta iz Lovrenškega jezera na Pohorju

The paper presents the results of sediment analyses done at a small moor lake on Pohorje. The changes in the plankton association of water fleas and diatoms whose remains accumulate in the sediment are a reflection of changing environmental factors. It was determined that the greatest dymanics of change occured in the 150 years, which coincides with the beginnings of industrialization. The age of the sediment has been determined by the analyses of the activity of the radionuclides 137Cs, 210Pb, and 241Am, which showedthat the sediment at the depth of 14cm is about 100 years old. The presence of spheroidal carbon particles (SCP), a consequence of the use of fossil fuels, confirmed dating by radiunucleids.V prispevku so predstavljeni izsledki raziskave sedimenta v barskem jezercu naPohorju. Spreminjanje planktonske združbe vodnih bolh in kremenastih alg, katerih ostanki se nabirajo v sedimentu, so odraz spreminjanja okoljskih dejavikov. Največja dinamika sprememb je ugotovljena za zadnjih 150 let, kar sovpada z začetki industrializacije. To potrjujeta tudi analizi aktivnosti radionuklidov 137Cs, 210Pb in 241Am, ki so pokazale, da je sediment na globini 14 cm star okoli 100 let in prisotnost kroglastih ogljikovih delcev (SCP), ki so posledica uporabe fosilnih goriv

Metal accumulation in mosses across national boundaries: uncovering and ranking causes of spatial variation.

This study aimed at cross-border mapping metal loads in mosses in eight European countries in 1990, 1995, and 2000 and at investigating confounding factors. Geostatistics was used for mapping, indicating high local variances but clear spatial autocorrelations. Inference statistics identified differences of metal concentrations in mosses on both sides of the national borders. However, geostatistical analyses did not ascertain discontinuities of metal concentrations in mosses at national borders due to sample analysis in different laboratories applying a range of analytical techniques. Applying Classification and Regression Trees (CART) to the German moss data as an example, the local variation in metal concentrations in mosses were proved to depend mostly on different moss species, potential local emission sources, canopy drip and precipitation

Metallakkumulation in Moosen: Standörtliche und regionale Randbedingungen des Biomonitoring von Luftverunreinigungen [Metal accumulation in mosses: local and regional boundary conditions of biomonitoring air pollution]

Metal accumulation in mosses: Local and regional boundary conditions of biomonitoring air pollution Goal and Scope. Several studies show that the concentration of metals in mosses depends not only on metal deposition but also on factors such as moss species, canopy drip, precipitation, altitude, distance to the sea and the analytical technique used. However, contrasting results have been reported and the interpretation of the spatial variability of the metal accumulation in mosses remains difficult. In the presented study existing monitoring data from the European Heavy Metals in Mosses Surveys together with surface data on precipitation, elevation and land use are statistically analysed to assess factors other than emissions that have an influence on the metal accumulation in the mosses. Main Features. Inference statistics and Spearman correlation analysis were applied to examine the association of the metal accumulation and the distance of the monitoring sites to the sea as well as the altitude. Whether or not significant differences of the metal loads in the mosses exist at national borders was examined with help of the U-test after Mann and Whitney. In order to identify and rank the factors that are assumed to have an influence on the metal uptake of the mosses Classification and Regression Trees (CART) were applied. Results. No clear tendency could be derived from the results of the inference statistical calculations and the correlation analyses with regard to the distance of the monitoring site to the sea and the altitude. According to the results of the CART-analyses mainly the moss species, potential emission sources around the monitoring sites, canopy drip and precipitation have an effect on the metal bioaccumulation. Assuming that each participating country followed strictly the manual for sampling and sample preparation the results of the inference statistical calculations furthermore suggest that in most cases different techniques for digestion and analysis bias the measurements significantly. Discussion. For the first time a national monitoring data base consisting of measurement data and metadata as well as surface information on precipitation, land use and elevation was applied to examine influence factors on the metal bioaccumulation in mosses. The respective results mirror existing knowledge from other national studies to a large extend, although further analyses are necessary to affirm the findings. These analyses should include data from other national monitoring programmes and should additionally be carried out with other decision tree algorithms than CART. Conclusions. The local variability in the metal concentration in mosses can be uncovered in terms of predictors or underlying hidden causes by using CART. Ideally, such an approach should be applied across the whole of Europe. This will only be feasible if all participating countries provide additional information about site characteristics as currently is done in for example the German moss surveys. Recommendations. The UNECE Metals in Mosses Survey experimental protocol should be improved in order to reduce the observed influences, to enhance standardisation, and to strengthen the quality control. This implies the integration of sampling site describing metadata into the assessment. Furthermore, basis research is needed to test the hypothesis concerning moss speciesspecific accumulation of depositions. Perspectives. Provided that the presented results hold true in further analyses correction factors should be applied on the moss data in order to get the depicted spatial patterns and temporal trends of metal bioaccumulation unbiased. Such factors should be calculated for natural landscape units or ecoregions that are homogeneous with regard to climate, vegetation and altitud