Arsenic accumulation and physiological attributes of spinach in the presence of amendments: an implication to reduce health risk

The current study examined the effect of calcium (Ca) and ethylenediaminetetraacetic acid (EDTA) on arsenic (As) uptake and toxicity to spinach (Spinacia oleracea) as well as assessed the potential human health risks. Spinach seedlings were exposed to three levels of As (25, 125, and 250 μM) alone or together with three levels of EDTA (25, 125, and 250 μM) and Ca (1, 5, and 10 mM). The effect of EDTA and Ca was assessed in terms of As contents in roots and shoots, hydrogen peroxide production, chlorophyll contents, and lipid peroxidation. The accumulation and toxicity of As to spinach plants increased with increasing As levels in nutrient solution. Exposure to As resulted in lipid peroxidation and reduced chlorophyll contents. The highest level of As alone (250 μM) showed highest human health risk (hazard quotient of 7.09 at As-250). Addition of EDTA enhanced As accumulation by spinach, while reduced As toxicity to spinach, as well as human health risk (hazard quotient of 4.01 at As-250). Similarly, Ca significantly reduced As toxicity to spinach and the human health risks (hazard quotient of 3.79 at As-250) by reducing its accumulation in spinach. Higher levels of Ca were more effective in reducing As uptake and toxicity as well as enhancing chlorophyll contents.     

Analysis of Air Quality Observations with the Aid of the Source-Receptor Relationship Approach

Abstract

In this study, an attempt was made to analyze time series of air quality measurements (O₃, SO₂, SO₄ ^2?NO_x) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify “areas of influence” have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of “areas of influence.” When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).     

First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses

In this study, the indicative value of mosses as biomonitors of atmospheric nitrogen (N) depositions and air concentrations on the one hand and site-specific and regional factors which explain best the total N concentration in mosses on the other hand were investigated for the first time at a European scale using correlation analyses. The analyses included data from mosses collected from 2781 sites across Europe within the framework of the European moss survey 2005/6, which was coordinated by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation). Modelled atmospheric N deposition and air concentration data were calculated using the Unified EMEP Model of the European Monitoring and Evaluation Programme (EMEP) of the Convention on Long-range Transboundary Air Pollution (CLRTAP). The modelled deposition and concentration data encompass various N compounds. In order to assess the correlations between moss tissue total N concentrations and the chosen predictors, Spearman rank correlation analysis and Classification and Regression Trees (CART) were applied. The Spearman rank correlation analysis showed that the total N concentration in mosses and modelled N depositions and air concentrations are significantly correlated (0.53 ≤ r_s ≤ 0.68, p < 0.001). Correlations with other predictors were lower than 0.55. The CART analysis indicated that the variation in the total N concentration in mosses was best explained by the variation in NH₄⁺ concentrations in air, followed by NO₂ concentrations in air, sampled moss species and total dry N deposition. The total N concentrations in mosses mirror land use-related atmospheric concentrations and depositions of N across Europe. In addition to already proven associations to measured N deposition on a local scale the study at hand gives a scientific prove on the association of N concentration in mosses and modelled deposition at the European scale.     

Characterization of endocrine disruptors from a complex matrix using estrogen receptor affinity columns and high performance liquid chromatography–high resolution mass spectrometry

Complex mixtures of contaminants with potential adverse effects on human health and wildlife are found in the environment and in the food chain. These mixtures include numerous anthropogenic compounds of various origins and structures, which may behave as endocrine disruptors. Mixture’s complexity is further enhanced by biotic and abiotic transformations. It is therefore necessary to develop new strategies allowing the identification of the structure of known, as well as unknown, nuclear receptor (NR) ligands present in complex matrices. We explored the possibility to use NR-based affinity columns to characterize the presence of bioactive molecules in environmental complex mixtures. Estrogen receptor α (ERα)-based affinity columns were used to trap and purify estrogenic substances present in surface sediment samples collected in a French river under mixed anthropogenic pressure. We combined biological, biochemical and analytical approaches to characterize the structure of ligands retained on columns and demonstrate the presence of known active molecules such as bisphenol A and octylphenol, but also of unexpected ERα ligands (n-butylparaben, hydroxyl-methyl-benzofuranone). High resolution mass spectrometry results demonstrate that ERα affinity columns can be used for the isolation, purification and identification of known as well as unknown estrogenic contaminants present in complex matrices.     

Polychlorinated biphenyls-containing electrical insulating oil contaminated soil treatment with calcium and magnesium peroxides

Calcium and magnesium peroxides were applied for the treatment of soil contaminated by polychlorinated biphenyls-containing electrical insulating oil (Aroclor 1016). The removal of PCB-containing electrical insulating oil was achieved with the addition of either calcium peroxide or magnesium peroxide alone and dependent on dosages of the chemical. A 21-d treatment of 60% watered soil with the moderate addition (chemical/oil weight ratio of 0.005/1) of either calcium peroxide or magnesium peroxide resulted in nearly complete (96 ± 2%) oil removal, unsubstantial increase in soil pH and almost no changes in oxygen consumption and dehydrogenase activity, making it suitable for the soil decontamination.     

Phototransformation products of tamoxifen by sunlight in water. Toxicity of the drug and its derivatives on aquatic organisms

Transformation of tamoxifen has been observed in water by prolonged sunlight irradiation. The main photoproducts, isolated by chromatographic techniques, have been identified by spectroscopic means. Photoisomerization, photocyclization and, to a lesser extent, photooxygenation appear to be involved in the degradation of the drug. The acute and chronic toxicity of the parent drug and its photoproducts were tested on non-target aquatic organisms (Brachionus calyciflorus, Thamnocephalus platyurus, Daphnia magna and Ceriodaphnia dubia). Exposure to all the compounds induced mainly chronic effects without significant differences among the parental and derivative compounds.     

Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986–1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.