Phytoextraction of toxic elements by Amaranthus Tricolor grown on technogenically polluted soils in open ground conditions

Using the INAA method, the ability of Amaranthus tricolor L. variety “Valentina” growing on soils with different degree of pollution to extract heavy metals was evaluated in the field experiments. It was found that amaranth of the studied variety characterized by the content of betacianin pigment, amaranthine, in the shoots and generative organ, is able to accumulate elements such as Mn, Fe and Ni from soils. The content of most of the studied elements decreases in the following order: leaves inflorescences stems. Under conditions of soil pollution with emissions from metallurgical plant, the phytoextraction of such elements as Mn, Fe, Co, Sb increases. The content of Fe and Mn in the leaves of A. tricolor var. “Valentina” exceeds the average data for vegetation from 7 to 17 times; the Co content exceeds the average data for vegetable from 4 to 7 times; the Sb content in the leaves exceeds the average data for vegetable from 10 to 23 times. Due to the fact that amaranth forms a sufficient biomass for the growing season, it can be recommended for phytoextraction of heavy metals from soils in case of polymetallic pollution

Supplementary material for the article: Milićević, T.; Aničić Urošević, M.; Vuković, G.; Škrivanj, S.; Relić, D.; Frontasyeva, M. V.; Popović, A. Assessment of Species-Specific and Temporal Variations of Major, Trace and Rare Earth Elements in Vineyard Ambient Using Moss Bags. Ecotoxicology and Environmental Safety 2017, 144, 208–215. https://doi.org/10.1016/j.ecoenv.2017.06.028

Supplementary material for: [. https://doi.org/10.1016/j.ecoenv.2017.06.028 ]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2513

Supplementary material for the article: Milićević, T.; Aničić Urošević, M.; Vuković, G.; Škrivanj, S.; Relić, D.; Frontasyeva, M. V.; Popović, A. Assessment of Species-Specific and Temporal Variations of Major, Trace and Rare Earth Elements in Vineyard Ambient Using Moss Bags. Ecotoxicology and Environmental Safety 2017, 144, 208–215. https://doi.org/10.1016/j.ecoenv.2017.06.028

Supplementary material for: [. https://doi.org/10.1016/j.ecoenv.2017.06.028 ]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2513

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