in mosses has declined the most for lead (77%), followed by vanadium (55%), cadmium 74 (51%), chromium (43%), zinc (34%), nickel (33%), iron (27%), arsenic (21%, since 75 1995), mercury (14%, since 1995) and copper (11%). Between 2005 and 2010, the 76 decline ranged from 6% for copper to 36% for lead; for nitrogen the decline was 5%.

The concentrations of iron (Fe), zinc (Zn), and copper (Cu) in the fruiting body depends on species and vary between 58.83-340.34, 19.70-99.62, and 5.03-9.37 mg/kg for Fe, Zn, and Cu, respectively. The bioaccumulation factor has subunit values for the three studied trace metals, which show the low capacity of these species of mushrooms to accumulate metals if the concentrations in soil increase over the normal threshold for these elements. The high values of translocation factor demonstrate the mobility of Fe, Zn, and Cu in the studied mushrooms.

The aim of this work was to determine the heavy metal content of the fruiting bodies of four species of wild edible mushrooms and their respective substrates. The samples were collected from Dambovita County, Romania, at various distances from of a metal smelter, to asses the concentration of Cr, Mn, Fe, Ni, Cu, Zn, Se and Cd in the wild edible mushrooms and their substrate using Energy Dispersive X-ray Fluorescence (EDXRF) spectrometry together with Flame Atomic Absorption (FAAS) spectrometry. A quantitative evaluation of the relationship of element uptake by mushrooms from substrate was made by calculating the coefficient accumulation (K(a)). A high accumulation of Zn (K(a) range 1.01 to 2.01) was observed in mushrooms growing in the vicinity of the metal smelter.

The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in 51 moss provide complementary and time-integrated data at high spatial resolution every five years since 1990. The paper 52 reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales 53(European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy 54 metal (HM) and nitrogen (N) concentrations in moss in Europe (1990Europe ( -2010; (3) correlations between concentrations of HM in 55 moss and soil specimens collected across Norway (1990Norway ( -2010; and (4) canopy drip-induced site-specific variation of N 56 concentration in moss sampled in seven European countries . While the minimum sample sizes on the European 57 and national level were achieved without exception, for some ecological land classes and elements the coverage with 58 sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe 59 has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were 60 observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the 61 moss and the soil survey data sets were correlated, indicating a decrease of HM concentrations in moss and soil. At the site 62 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 71other manufacturing industries and construction (As, Cd, Cr, Hg, Ni, Pb), electricity and heat production (e.g. Hg, Ni), road 72 transportation (Cu and Sb from brake wear, Pb from petrol, Zn from tires), petroleum refining (Ni, V), and phosphate 73 fertilisers in agricultural areas (Cd) (Harmens et al. 2011 a). N emissions and relateted deposition are due to technical 74 processes and agriculture. Pollutants which were emitted into and transported through the atmosphere finally come down at 75Earth´s surface as wet (rain, snow), occult (fog, mist, rime) or dry (gases, particles) deposition where they accumulate in 76 biota and sediments of terrestrial and subsequently of aquatic ecosystems. 78In Germany, less than 10 % of the HM load of aquatic environments is emitted from industries. More than 80 % of policyclic (Harmens et al. 2015). In contrast to measurements with tec...

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The study aims to investigate the chemical composition of airborne particulate matter with size below 2.5 �m (PM2.5) collected from Targoviste City area, in the summer of 2015. For this consideration eleven representative points have been chosen for sampling. This research provides interesting data which can clarify the relationship between PM2.5 exposure and the negative effects on human health at urban area level. Three analytical techniques have been developed for the qualitative, quantitative and morphological characterization of PM2.5. The inorganic and organic functional groups of the PM2.5 samples were investigated by Attenuated Total Reflectance - Fourier Transform Infrared Spectrometry (ATR-FTIR). The content of several elements (i.e. Pb, Cd, Cr, Ni, Cu, Mn, Al, Zn and Fe) in samples was determined by Inductively Coupled Plasma - Mass Spectrometry (ICP-MS). The measured concentration of these metals was compared with values reported by the International Agency on urban area in order to establish the minimal element level which cannot be considered as a potential health risk for the urban population. The morphological characterization of PM2.5 was performed by Scanning Electron Microscopy - Energy Dispersive Spectrometry (SEM-EDS). The elemental analysis of samples were performed by EDS and showed that airborne particle was mainly composed of elements, such as C, O, Si, Ca, N and S.

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In this study, the chemical composition of Juglandis semen extracts obtained by different extraction solvents and methods were determined by Fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy. The multivariate analyses, principal component analysis and hierarchical cluster analysis of the FTIR and Raman spectral datasets, were performed to determine the differences in the chemical composition according to the solvent (e.g., mixture of water with alcohol, glycerole, and propylene glycol) and the extraction method (i.e., ultrasound‐assisted extraction, rapid pressurized extraction, and subcritical fluid extraction). The obtained results reveal that the J. semen extracts with water‐alcohol solvent have equivalent chemical composition. A well‐defined differentiation based on extraction method could not be highlighted. Based on FTIR data compilation, it can be observed that a first classification can be made based on the solvent, acidic or basic, used for extraction methods (except subcritical fluid extraction ‐ SFE, clustering is clearly assigned by the solvent). Multivariate analysis on FTIR and Raman spectral data was able to differentiate SFE extract as a unique cluster, which means HFC134a solvent allowed a specific extraction (from organic constituents' point of view) due to the selected conditions of extraction method.