As a result of its wide industrial applications, zinc has become an important contaminant in aquatic environment since it is a toxic heavy metal and some of its compounds such as zinc arsenate and zinc cyanide, may be extremely hazardous. Therefore, there is a growing need for developing simple methods capable of separating and recovering trace zinc from environmental waters. Nowadays, the ultra and microfiltration method for trace metals removal from waters by the addition of water-soluble polymers into the aqueous solutions has become a significant research area. The choice of watersoluble macroligands remains important for developing this technology. Sodium carboxymethyl cellulose (Na-CMC) was selected as complexing agent. The microfiltration experiments were carried out in stirred dead-end cell. To separate formed polymer-metal complex Versapor membranes were used. The concentration of heavy metal ions after microfiltration in aqueous solution was determined using atomic absorption spectroscopy (AAS). Effects of amount of complexing agent, pH value, type of anion, ionic strength and operating pressure on the flux (J) and rejection coefficient (R) were investigated. Experimental results indicate a considerable influence of the pH, ionic strength and type of anion on the rejection coefficient, while effect of amount of complexing agent is relatively insignificant. The Na-CMC used in the research proved to be very effective, which may be supported by the high rejection coefficients obtained (99%)

Complexation-microfiltration process for removal of heavy metal ions such as lead, cadmium and zinc from water had been investigated. Two soluble derivates of cellulose was selected as complexing agents. The dependence of the removal efficiency from the operating parameters (pH value, pressure, concentration of metal ion, concentration of complexing agent and type of counter ion) was established. Two approaches of preparation of input data and two different artificial neural network architectures, general regression neural network and back-propagation neural network have been used for modeling of experimental data. The extrapolation ability of selected architectures, i.e., the prediction of rejection coefficient with inputs beyond the calibration range of original model, was also determined. The predictions were successful, and after evaluation of performances, the models that were developed gave relatively good results of mean absolute percentage error from 4 to 14% and R-squared from 0.717 to 0.852 for general regression neural network and from 0.897 to 0.955 for back-propagation neural network.

This study focussed on a comprehensive investigation on the state of pollution and identification of potential sources of contamination of some river sediments in Serbia by polycyclic aromatic hydrocarbons (PAHs), and is the basis for setting up further monitoring programs. The sediment quality of the Danube River (km 1433-845) and its tributaries in Serbia, including the Sava River (km 202-1), were analysed with respect to PAHs and total organic carbon (TOC). We found that total PAH concentration in the sediments from the Danube and its tributaries (10.0-4140 µg kg-1) was lower than total PAH concentration in Sava River sediments (265.1-11272 µg kg-1). Principal component analysis showed that concentrations of benzo[a]anthracene, chrysene, pyrene, fluoranthene, indeno[1,2,3-cd]pyrene, benzo[a] pyrene, benzo[b]fluoranthene and benzo[k]fluoranthene in the sediments were correlated with TOC. The diagnostic ratios anthracene/(anthracene+phenanthrene) and fluoranthene/(fluoranthene+pyrene) were calculated to evaluate the emission sources of the PAHs. Therefore, these ratios indicated the predominantly pyrogenic source of the PAHs in the sediments. Results have also shown that river sediments in the Danube and Sava rivers and their tributaries were not recently polluted with PAHs, excluding only one location-S4, downstream of Šabac and characterized by heavily polluted sediment.

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Article Highlights• Lead concentration showed a decreasing trend during the entire studied period • The horse chestnut leaves showed good response to changes in trace element atmospheric concentrations • Different sources of trace elements in ambient air and in horse chestnut leaves were observed • During the studied period, traffic was one of the major sources of the measured elements in Belgrade • The trace element concentrations in PM10 were below the limits of Serbian and EU legislation AbstractIn this study, airborne particulates (PM10) and leaves of horse chestnut were collected at selected urban sites in Belgrade, Serbia, in years 2006, 2009 and 2012. All samples were analysed for trace element concentrations of As, Cd, Cr, Ni and Pb. It was found that, during the study period, the differences among PM10 mass trace element concentrations were not considerable, and that the measured mass and trace elements concentrations were below the Serbian and EU legislation limits. The highest values of trace element concentrations in leaves were observed in year 2012, with the exception of Pb. Lead concentration had a decreasing trend during the whole studied period, in both PM10 and tree leaves. Since leaded gasoline was banned in 2011, a possible reason could be an increasing number of vehicles using unleaded kind along the previous years. Although trace elements in horse chestnut leaves were accumulated only during the summer season, horse chestnut leaves showed good response to changes in trace element atmospheric concentrations. However, seasonal variability was evident in trace element source apportionment due to the lack of stationary heating system influence. The principal component analysis showed that during the studied period, one of the major sources of the measured elements was fossil fuel combustion.