Volume 16 [2014]

In the present study, batch adsorption studies were performed for the removal of malachite green and acid blue 161 dyes from aqueous solutions by varying parameters such as contact time, waste marble dust amount, initial dye concentration and temperature. The equilibrium adsorption data were analyzed by Langmuir, Freundlich and Temkin adsorption isotherm models. The Langmuir and Freundlich adsorption models agree well with experimental data. The pseudo-second order, intraparticle intraparticle diffusion and Elovich kinetic models were applied to the experimental data in order to describe the removal mechanism of dye ions by waste marble dust. The pseudo-second order kinetic was the best fit kinetic model for the experimental data. Thermodynamics parameters such as ΔG, ΔH and ΔS were also calculated for the adsorption processes. The experimental data were used to construct an artificial neural network (ANN) model to predict removal of malachite green and acid blue 161 dyes by waste marble dust. A three-layer ANN, an input layer with four neurons, a hidden layer with 12 neurons, and an output layer with one neuron is constructed. Different training algorithms were tested on the model to obtain the proper weights and bias values for ANN model. The results show that waste marble dust is an efficient sorbent for malachite green dye and ANN network, which is easy to implement and is able to model the batch experimental system.

A new concept of water management implies the utilisation of karstic water, primarily, to resolve the public water supply issue. In the future, a number of benefits such as: resolving of centralized water supply issues, reduction of surface water pollution, creating opportunities for the utilisation of surface water for other purposes, creating new tourist zones, reduction of environmental pollution, improvement of the general welfare of the population, etc., will be achieved by this concept. From the aforesaid, it can be concluded that a number of interconnected and integrated benefits will be gained by full implementation of the new concept of karst water utilisation. The application of the concept designed in this way, ultimately implies the establishment of an integrated management of all karst water in the area of Zlatibor. In order to achieve this goal, it is necessary, primarily, to solve the problem of adequate public water supply by karstic groundwater, which implies the establishment of integrated karstic water management in this area, and that is the focus of this paper.

The objective of this study is to present an integrated stochastic approach for quantifying the risk of oil spill in marine waters and adjacent coasts. This was achieved via the effective cooperation between the National Technical University of Athens (NTUA) and the Bogazici University (BU) within the framework of a bilateral joint research project. The proposed methodology integrates four models: (1) a physics-based hydrodynamic model (HYM) which computes the spatial distribution of surface water currents as the main driving force for oil transport, (2) an expert-based accident assessment model (AAM) to compute the frequency, location and characteristics of expected oil spills, (3) a physics-based oil spill model (OSM) which computes the propagation and fate of the oil slick, and (4) an expert-based impact assessment model (IAM) to compute the distribution of coastal impact due to oil contamination. The model is applied to two pilot areas: the Saronicos Gulf, Greece and Izmir Bay, Turkey. The flow fields in these areas were determined by the HYM for a large number of wind scenarios, based on which the transport and weathering of an oil slick were computed by the OSM. The most probable oil spill locations were identified by AAM based on the bathymetry, the maritime traffic and the currents. Finally, the IAM was applied to draw Coastal Oil Impact Maps in the regions of interest. Emphasis was placed on the presentation of the risk of oil reaching the coastline. Environmental sensitivity and economic importance were taken into account by assigning index values to all coastal cells.