Recent advances in the bioremediation of arsenic-contaminated groundwater

The biological treatment of groundwater is used primarily to remove electron donors from water sources, providing (biologically) stable drinking water, which preclude bacterial regrowth during subsequent water distribution. To the electron donors belong also the dissolved metal cations of ferrous iron and manganese, which are common contaminants found in most (anaerobic) groundwater. The removal of iron and manganese is usually accomplished by the application of chemical oxidation and filtration. However, biological oxidation has recently gained increased importance and application due to the existence of certain advantages, over the conventional physicochemical treatment. The oxidation of iron and manganese is accelerated by the presence of certain indigenous bacteria, the so-called "iron and manganese oxidizing bacteria." In the present paper, selected long-term experimental results will be presented, regarding the bioremediation of natural groundwater, containing elevated concentrations of iron and arsenic. Arsenic is considered as a primary pollutant in drinking water due to its high toxicity. Therefore, its efficient removal from natural waters intended for drinking water is considered of great importance. The application of biological processes for the oxidation and removal of dissolved iron was found to be an efficient treatment technique for the simultaneous removal of arsenic, from initial concentrations between 60 and 80 microg/l to residual (effluent) arsenic concentrations lower than the limit of 10 microg/l. The paper was focused on the removal of As(III) as the most common species in anaerobic groundwater and generally is removed less efficiently than the oxidized form of As(V). To obtain information for the mechanism of As(III) removal, X-ray photoelectron spectroscopy (XPS) analyses were applied and it was found that As(III) was partially oxidized to As(V), which enabled the high arsenic removal efficiency over a treatment period of 10 months.     

Improved statistical downscaling models based on canonical correlation analysis, for generating temperature scenarios over Greece

This study attempts to improve upon statistical downscaling (Sd) models based on the classical approach which uses canonical correlation analysis, in order to generate temperature scenarios over Greece. Considering the long-term trends of the predictor variables (1,000–500 hPa thickness field geopotential heights—using NCEP data) and the predictand variables (observed mean maximum summer temperatures over Greece), a new Sd model is constructed. Regression models using generalized least square estimators are developed in order to eliminate the trends within the time series. The advantages of the suggested method compared to the classical method are quantified in terms of a number of distinct performance criteria, e.g., Mean squared error which is the basic criterion of the estimated downscaled values relative to the observed. Finally, the suggested Sd models are used to evaluate the effects of a future climate scenario (IPCC-SRES: A2) on mean maximum summer temperatures over Greece. The results from the climate projection indicate a temperature increase for the period 2070–2100 which is smaller than the corresponding increase from the classical approach.     

Effect of macronutrients and of anaerobic digestate on the heterotrophic cultivation of Chlorella vulgaris grown with glycerol

Environmental Science and Pollution Research - The aim of this work was to investigate the kinetics of the heterotrophic growth of Chlorella vulgaris as a means of producing bio-oil for biodiesel...