Floods are natural disasters with significant socio-economic consequences. Urban areas with uncontrolled urban development, rapid population growth, an unregulated municipal system and an unplanned change of land use belong to the highly sensitive areas where floods cause devastating economic and social losses. The aim of this paper is to present a reliable GIS multi-criteria methodology for hazard zones’ mapping of flood-prone areas in urban areas. The proposed methodology is based on the combined application of geographical information systems (GIS) and multi-criteria decision analysis (MCDA). The methodology considers six factors that are relevant to the hazard of flooding in urban areas: the height, slope, distance to the sewage network, the distance from the water surface, the water table and land use. The expert evaluation takes into account the nature and severity of observed criteria, and it is tested using three scenarios: the modalities of the analytic hierarchy process (AHP). The first of them uses a new approach to the exploitation of uncertainty in the application of the AHP technique, the interval rough numbers (IR’AHP). The second one uses the fuzzy technique for the exploitation of uncertainty with the AHP method (F’AHP), and the third scenario contemplates the use of the traditional (crisp) AHP method. The proposed methodology is demonstrated in Palilula Municipality, Belgrade, Serbia. In the last few decades, Palilula Municipality has been repeatedly devastated by extreme flood events. These floods severely affected the transportation networks and other infrastructure. Historical flood inundation data have been used in the validation process. The final urban flood hazard map proves a satisfactory agreement between the flood hazard zones and the spatial distribution of historical floods that happened in the last 58 years. The results indicate that the scenario in which the IR’AHP methodology is used provides the highest level of compatibility with historical data on floods. The produced map showed that the areas of very high flood hazard are located on the left Danube River bank. These areas are characterized by lowland morphology, gentle slope, sewage network, expansion of impermeable locations and intense urbanization. The proposed GIS-IR’AHP methodology and the results of this study provide a good basis for developing a system of flood hazard management in urban areas and can be successfully used for spatial city development policy.

This paper suggests spatial multi-criteria model in order to assist decision makers in the selection of sites which are suitable for ammunition depots (AD). They represent military facilities which have more criteria that need to be matched than civil structures. The proposed model is based on combined use of Geographic information systems (GIS) and multi-criteria techniques. The model application is presented in the case study of Carpathian region, the Eastern part of Serbia. The model deals with nine restrictions and six evaluation criteria. Decision Making Trial and Evaluation Laboratory—Analytic Network Process (DEMATEL-ANP) multi-criteria techniques are used to determine weight coefficients of evaluation criteria. Along with the above mentioned methods, this paper introduces a new technique for the multi-criteria decision making—MAIRCA (MultiAttributive Ideal-Real Comparative Analysis) method. The MAIRCA method is used for the ranking and selection of suitable locations. The results have shown that 45 km² of the Carpathian region is very suitable for ammunition depot construction. The MAIRCA method chose location L1 as the most appropriate. Sensitivity analysis shows that the model is capable of identifying a suitable ammunition depot location. This approach can be helpful in determining suitable ammunition depot locations in other regions with similar geographic conditions and can also be successfully used for the suitability assessment of existing ammunition depots.

This paper presents spatial mathematical model in order to identify sites for the wind farms installment which can have significant support for the planners in the area of strategy and management of wind power use. The suggested model is based on combined use of Geographical Information Systems (GIS) with multi-criteria techniques of Best-Worst method (BWM) and MultiAttributive Ideal-Real Comparative Analysis (MAIRCA). Rough numbers and fuzzy logic are used to exploit uncertainty during data analysis in spatial mathematical model. The model is applied on the case study. Rough BWM model is used to determine weight coefficients of the criteria and rough MAIRCA method is used to rank separated sustainable locations. The implementation of MAIRCA method has shown that the location L3 is the most suitable for the wind farm in the area covered in the case study. Therefore, the suggested spatial mathematical model can be successfully used to identify the potential suitable sites for the wind farms in other areas with similar geographic conditions.

In this work multiwalled carbon nanotubes (MWCNTs) modified by oxidation (o-MWCNTs) and by aminofunctionalization (e-MWCNTs) were examined as potential adsorbents for arsenate removal from water. Adsorption characteristics of raw and modified MWCNTs were investigated in batch adsorption experiments. The influence of solution pH (pH range 3–10), contact time, and temperature (25, 35, and 45°C) were studied. Ethylenediamine-functionalized MWCNTs have the greatest affinity for arsenate ions, followed by o-MWCNTs and raw-MWCNTs. The obtained experimental data for raw- and o-MWCNTs fitted Sips isotherm model, while for the e-MWCNTs, the Freundlich model provided the best fit to the experimental points. The maximum adsorption capacity for arsenate ions was achieved using e-MWCNTs, 12.18 mg g⁻¹. The presence of the arsenate on the adsorbent is confirmed by FTIR spectroscopy. Thermodynamic studies indicated the spontaneity and endothermic nature of the adsorption. Sodium hydroxide solution (0.1 M) was found to desorb about 70% of arsenate from e-MWCNTs. The results with spiked drinking water samples demonstrated that e-MWCNTs, due to the present basic and acidic groups, were very efficient for the removal of arsenate ions, as well as of some cations, at pH 4.

The multistage synthesis of the multi-wall carbon nanotubes (MWCNT) modified with polyamidoamine dendrimers, A1/ and A2/MWCNT, capable of cation removal, is presented in this work, as well as novel adsorbents based on these precursor materials and modified with goethite nano-deposit, ?-FeOOH, A1/ and A2/MWCNT??-FeO(OH) adsorbents used for As(V) removal. In a batch test, the influence of pH, contact time, initial ion concentration and temperature on adsorption efficiency were studied. Adsorption data modelling by the Langmuir isotherm, revealed good adsorption capacities (in mg g-1) of 18.8 for As(V) and 60.1 and 44.2 for Pb2+ and Cd2+ on A2/MWCNT, respectively. Also, 27.6 and 29.8 mg g-1 of As(V) on A1/ and A2/MWCNT??-FeO(OH), respectively, were removed. Thermodynamic parameters showed that the adsorption is spontaneous and endothermic processes. Results of the study of influences of competitive ions: bicarbonate, sulfate, phosphate, silicate, chromate, fluoride and natural organic matter (NOM), i.e., humic acid (HA), showed the highest effect of phosphate on the decrease of arsenate adsorption. Time-dependent adsorption was best described by pseudo-second-order kinetic model and Weber?Morris model which predicted intra-particle diffusion as a rate-controlling step. Also, activation energy (Ea / kJ mol-1): 8.85 for Cd2+, 9.25 for Pb2+ and 7.98 for As(V), were obtained from kinetic data.