Atmospheric Deposition of Cadmium in Croatia Studied by using moss Biomonitoring Technique and ICP-AES

Croatia participated for the first time in moss survey in 2005, in the framework of the InternationalCooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops with heavy metals inEurope (UNECE ICP Vegetation) when different species of moss samples (Hypnum cupressiforme, Pleuroziumschreberi, Brachythecium rutabulum and Homalothecium sericeum) were collected from 96 locations evenly distributedover the country. An additional 27 new sampling sites were added for the investigation in 2010. Moss sampleswere collected during the summer and autumn of 2010. Collected moss samples were air dried, cleaned and totallydigested by using microwave digestion system. Digests were analyszd for cadmium by atomic emission spectrometrywith inductively coupled plasma (ICP-AES). The results for cadmium were compared with the results obtained inprevious investigations in Croatia and some other neighboring countries and Norway as a pristine area. The contentof cadmium ranges from 0.10 mg kg–1 to 1.42 mg kg–1. It was found that the median value of cadmium (0.38 mg kg–1) is 1.41 times higher than the value obtained in the study performed in 2005. Compared to the other countries, Croatiashows insignificantly higher median value. Highest contents of cadmium were found in the Podravina region (1.14mg kg–1 and 1.42 mg kg–1) where cadmium inputs as a result of anthropogenic origin from Slovenia and Austria (Pband Zn mines and smelter plants). High levels of cadmium were also found in moss samples collected at some industrializedareas in northern parts of Croatia as a result of anthropogenic influence as well as in samples collected in theCoastal region where high levels are a result of geological origin

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

Study of nitrogen pollution in the Republic of North Macedonia by moss biomonitoring and Kjeldahl method

In the summer of 2005 and 2010, moss samples were collected from 72 sampling sites evenly distributed all over the territory of Republic of North Macedonia. Kjeldahl method was used to determine the nitrogen content in the samples. Descriptive statistics and distribution maps were prepared. Data obtained from these two surveys were compared, and additional comparison was done with data obtained from similar studies in the South-Eastern European countries and Finland as a clean area. The median value of N content in the samples collected in 2005 is 1.21%, varies from 0.70% to 1.54%, while the content of N in samples collected in 2010 ranges between 0.68% and 1.75% with the median value of 1.06%. High contents of N were found in the Northern and Central parts of the country mainly as a result of agricultural activities, industry and traffic

Mercury speciation in meconium and associated factors

Meconium is formed early in gestation and it is normally not excreted until after birth. Thus it may provide a longer and cumulative record of exposure to mercury (Hg). The present study aims to speciate Hg in meconium samples (N = 488) from Slovenian and Croatian new-borns prenatally exposed to low levels of methyl-Hg (MeHg) from maternal seafood intake and to Hg0 from maternal dental amalgam fillings. We had complete data of total Hg (THg) and MeHg in meconium and THg in maternal hair (MH), while THg and MeHg in maternal blood (MB) were available only for Croatian mothers. Personal data namely maternal seafood intake, age, pre-pregnancy BMI, parity, smoking, estimated gestational age at birth, sex, and birth weight were available for the majority of participants, except the number of dental amalgams which was in most cases missing for Croatian mothers. The median THg concentration in meconium was 11.1 (range: 0.41–375.2) ng/g and inorganic Hg (Hg(II)) presented 98.8% (range: 82%–100%, CV: 2%) of THg. We observed significant correlation between meconium and MH Hg levels, with the highest correlation between hair THg and meconium MeHg. Correlation analysis including MB (available only for Croatian population) showed a significant positive correlation between THg in meconium and THg in MB (Rs = 0.642). Additionally, MeHg from MB was correlated with MeHg in meconium (Rs = 0.898), while the correlation between Hg(II) in MB and meconium was positive, but not significant. Maternal seafood intake was significantly correlated with meconium MeHg (Rs = 0.498) and Hg(II) (Rs = 0.201). Multiple linear regression (performed on the Slovenian population, N = 143) confirmed a positive association between meconium MeHg and seafood intake. Furthermore, meconium Hg(II) was positively associated with the number of maternal dental amalgam fillings, but linear regression models did not confirm correlation between seafood intake and meconium Hg(II) levels. We assume that Hg0 released from maternal dental amalgam fillings and MeHg from seafood intake were both transported through the placental barrier and portioned between different foetal compartments including meconium. Weak correlation between maternal seafood intake and Hg(II) levels in meconium suggests that there is certain evidence of MeHg demethylation. However, because this correlation was not confirmed by the multiple regression, MeHg demethylation during prenatal life cannot be neither confirmed nor excluded. Further investigations at higher level of exposure are needed to confirm this observations. We can conclude that meconium is a suitable biomarker for MeHg and Hg0 exposure during pregnancy. However, comparability of the results reported in meconium in different studies is hindered by a lack of standardized sampling protocols, storage, and analysis

Mercury speciation in prenatal exposure in Slovenian and Croatian population - PHIME study

In recent years, several studies have addressed the issue of prenatal exposure to methylmercury (MeHg) ; however, few have actually analysed MeHg blood concentrations. Our study population included mothers and their new-borns from Slovenia (central region ; N = 584) and Croatia (coastal region ; N = 234). We have measurements of total Hg (THg) and MeHg in maternal hair, maternal peripheral blood, and cord blood. Cord blood Hg concentrations were low to moderate (median THg = 1.84 ng/g and MeHg = 1.69 ng/g). The proportion of THg as MeHg (%MeHg) in maternal and cord blood varied between 4% and 100% (coefficient of variation, CV = 32%) and between 8% and 100% (CV = 20%), respectively. Our data shows that variability of %MeHg was higher at lower blood THg levels. Concentrations of MeHg in maternal blood and cord blood were highly correlated (Rs = 0.943), in the case of inorganic Hg correlation was significant but weaker (Rs = 0.198). MeHg levels in maternal blood and cord blood were positively associated with seafood intake, maternal age, and negatively associated with pre-pregnancy BMI. Additionally, MeHg in maternal blood was positively associated with plasma selenium levels, and cord blood MeHg was negatively associated with parity. The results of multiple linear regression models showed that speciation analysis provides more defined estimation of prenatal exposure in association modelling. Associations between Hg exposure and cognitive performance of children (assessed using Bayley Scales of Infant and Toddler development) adjusted for maternal or child Apolipoprotein E genotypes showed higher model R2 and lower p-values when adjusted for MeHg compared to THg. This study demonstrates that Hg speciation improves the association between exposure and possible negative health effects