Summary:
The study area, located in the NE part of Chalkidiki peninsula, geologically includes two different lithological units; the underlying unit of Kerdilia and the overlying unit of Vertiskos, separated from each other by the Stratoni fault. The area of NE Chalkidiki is of great interest due to the deposits of precious and base metals, manganese deposits and the occurrences of metallic minerals. The study area consists of the most significant deposit in Greece, in fact one of the most important ones on a global scale, the Cu-Au deposit of Skouries which is emplaced in post-collisional back arc setting. Hydrologically, the area belongs to the Asprolakkas basin and covers almost the entire area of Skouries and a part of Stratoni, stretching in a total area of 91.7 km2 and due to the particular geological conditions, it is obvious that the hydrochemistry of the surface waters is affected by mineralogy, geochemistry and existing environmental pressures. The mining project of Skouries stipulated that the deposition of the ore processing waste is carried out in two different sites within the basin (in Karatzas Lakkos and Lotsanikos).
The aim of this master thesis is the characterization and modeling of the hydrochemical status of the Asprolakkas watershed (AW) and the adjacent streams that flow into it. Τhe processes , that defined and described the hydrochemical conditions of the study area, were examined according to possible scenarios based on field data collected upstream of the area prior to the start of the Skouries mining project and in combination with the prevailing environmental / geological conditions and the expected changes due to the development of the project.
More specifically, in October 2012, fourteen (14) surface water samples were collected from various locations along the AW. The physicochemical parameters of pH, temperature (T), electrical conductivity (CND) and total dissolved solids (TDS) were determined in situ, while the concentrations of major ions and trace elements were determined in the laboratory by atomic absorption spectroscopy (AAS) and inductively coupled plasma atomic emission spectroscopy (ICP-AES). The concentrations of the sulfate ions (SO4) were determined gravimetrically, while alkalinity (HCO3) was determined by titration. Geochemical modeling was performed using the PHREEQC software via the MINTEQ thermodynamic database. Three different scenarios, simulating the existing conditions (scenario A), the mixing of rainwater in various proportions (scenario B) and the water evaporation (scenario C) were examined. In addition, we examined whether the hydrochemistry of the AW can be simulated satisfactorily by the geochemical modeling and if there can be satisfactory models to explain the hydrochemistry of AW according to the mineral phases involved in the hydrological system, using the tool of inverse geochemical modeling. From the major ions and trace elements determined in this study, Pb concentrations are the most interesting ones as they are increased (up to 172.1 μg/l) compared to the limit of KYA 1811/2011 (10 μg/l) and the intervention value of the New Dutch List (75 μg /l). According to the speciation in the physicochemical conditions (pH-Eh) prevailing in the study area ,calculated using the PHREEQC software, the dominant species of major ions and trace elements are ions (Ca2+, Mg2+, K+, Na+, HCO3-, SO4-2, Ba+2, Li, Mn+2, Cd+2, Co+2). Only Pb appears to be dominated by the carbonate phases.
In scenario A, it was reported that the mineral phases that are in chemical equillibrium up to oversaturated, in the measured aqueous samples, consist mostly of carbonates (aragonite, calcite, dolomite, cerussite, hydrocerussite, magnesite, rhodochrosite), some sulfate mineral phases (barite, gypsum) and Pb hydroxides. In scenario B, the tendency of saturation indices to decrease was observed compared to scenario A, resulting in the intensive processes of mineral dissolution. Scenario C favors the precipitation of mineral phases such as anglesite, anhydrite, aragonite, barite, calcite, cerussite, dolomite, gypsum, huntite, hydrocerussite, hydromagnesite, magnesite and rhodochrosite.
According to the data processing, it was revealed that the model simulates the hydrochemistry of the watershed adequately, while the inverse geochemical modeling produced 3 different satisfactory simulations that could explain the hydrochemistry of the watershed.
