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Various types of plutonic and volcanic rocks and their alteration products from Greece (serpentinite, magnesite and andesite), have been used for sustainable removal of Uranium (U) from the acidic drainage of Kirki mine, as well as for the pH increase of the polluted solutions. In this light, this study aims at the further understanding and improvement of the ecofriendly reuse of sterile, natural raw materials (including those remaining through industrial processing and engineering testing of aggregate rocks), for remediation of acid mine drainage. The selected rocks constitute such residues of sterile materials were used as filters in experimental continuous flow devices in the form of batch-type columns, in order to investigate acidic remediation properties with special focus on U removal. The initial pH of the wastewater was 2.90 and increased after seven (7) days of experimental application and more specifically from the fourth day onwards. Uranium removal became quantitatively significant once pH reached the value of 5.09. The volcanic rocks appeared to be more effective for U removal than the plutonic ones because of microtextural differences. However, optimum U removal was mainly achieved by serpentinite: while the raw materials rich in Mg strongly reacted and remediated the pH of the drainage water waste. Furthermore, the increase of pH values due to the presence of mineral raw materials, provided increased oxidation potential which deactivated the toxic load of metals, particularly U. Consequently, batch-type serpentinite reaction with the tailing fluid caused a drop in U concentration from an initial value of 254 ppb to the one of 8 ppb, which corresponds to 97% of removal. Andesite presented the second best reactant for experimental remediation, especially when it was mixed with magnetically separated mineral fractions. Despite the fact that the proposed methodology is currently at a relatively low Technology Readiness Level (TRL), it carries the potential to become an extremely effective and low-cost alternative to conventional environmental restoration technologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Planned decommissioning of coal-fired plants in Europe requires innovative technical and economic strategies to support coal regions on their path towards a climate-resilient future. The repurposing of open pit mines into hybrid pumped hydro power storage (HPHS) of excess energy from the electric grid, and renewable sources will contribute to the EU Green Deal, increase the economic value, stabilize the regional job market and contribute to the EU energy supply security. This study aims to present a preliminary phase of a geospatial workflow used to evaluate land suitability by implementing a multi-criteria decision making (MCDM) technique with an advanced geographic information system (GIS) in the context of an interdisciplinary feasibility study on HPHS in the Kardia lignite open pit mine (Western Macedonia, Greece). The introduced geospatial analysis is based on the utilization of the constraints and ranking criteria within the boundaries of the abandoned mine regarding specific topographic and proximity criteria. The applied criteria were selected from the literature, while for their weights, the experts' judgement was introduced by implementing the analytic hierarchy process (AHP), in the framework of the ATLANTIS research program. According to the results, seven regions were recognized as suitable, with a potential energy storage capacity from 1.09 to 5.16 GWh. Particularly, the present study's results reveal that 9.27% (212,884 m 2 ) of the area had a very low suitability, 15.83% (363,599 m 2 ) had a low suitability, 23.99% (550,998 m 2 ) had a moderate suitability, 24.99% (573,813 m 2 ) had a high suitability, and 25.92% (595,125 m 2 ) had a very high suitability for the construction of the upper reservoir. The proposed semi-automatic geospatial workflow introduces an innovative tool that can be applied to open pit mines globally to identify the optimum design for an HPHS system depending on the existing lower reservoir.

A coupled methodology of nitrogen isotopes, hydrogeochemical characterization, multivariate statistical analysis, and SIAR Bayesian modeling has been employed to identify the sources of NO 3 - and N transformation processes in three alluvial aquifers (Schinos, Thiva, and Central Evia) located in central Greece where geogenic Cr(VI) co-occurs with agricultural activity and rural development. Hexavalent chromium concentrations exceed 50 μg/L in many sampling stations of the studied groundwater bodies, while nitrate contamination is evident in all three study areas with concentrations well over 50 mg/L. The mean δ 15 N-NO 3 - and δ 18 Ο-NO 3 - values are 6.67 ± 1.77‰ and 2.68 ± 1.77‰ in C. Evia, 8.72 ± 4.74‰ and 3.96 ± 4.57‰ in Schinos and 4.44 ± 1.71‰ and 2.91 ± 1.02‰ in Thiva, respectively. Domestic sewage and N-bearing fertilizers are contributing in various degrees to the observed nitrification which is the dominant transformation process of N in the studied aquifers. Multivariate statistics indicated that the main processes identified in the study areas are salinization, silicate dissolution, and groundwater contamination due to fertilizer use. It is suggested that ultramafic rock-related alluvial aquifers must be closely monitored in terms of nutrient inputs as an effective measure for controlling Cr(VI) release in groundwater., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Copper (Cu) ion in wastewater is considered as one of the crucial hazardous elements to be quantified. This research is established to predict copper ions adsorption (Ad) by Attapulgite clay from aqueous solutions using computer-aided models. Three artificial intelligent (AI) models are developed for this purpose including Grid optimization-based random forest (Grid-RF), artificial neural network (ANN) and support vector machine (SVM). Principal component analysis (PCA) is used to select model inputs from different variables including the initial concentration of Cu (IC), the dosage of Attapulgite clay (Dose), contact time (CT), pH, and addition of NaNO 3 (SN). The ANN model is found to predict Ad with minimum root mean square error (RMSE = 0.9283) and maximum coefficient of determination (R 2  = 0.9974) when all the variables (i.e., IC, Dose, CT, pH, SN) were considered as input. The prediction accuracy of Grid-RF model is found similar to ANN model when a few numbers of predictors are used. According to prediction accuracy, the models can be arranged as ANN-M5> Grid-RF-M5> Grid-RF-M4> ANN-M4> SVM-M4> SVM-M5. Overall, the applied statistical analysis of the results indicates that ANN and Grid-RF models can be employed as a computer-aided model for monitoring and simulating the adsorption from aqueous solutions by Attapulgite clay., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This study investigates the performance of support vector machine (SVM), multivariate adaptive regression spline (MARS), and random forest (RF) models for predicting the lead (Pb) adsorption by attapulgite clay. Models are constructed using batch stochastic data of heavy metal (HM) concentrations under different physicochemical conditions. Implementation of auto-hyper-parameter tuning using grid-search approach and comparative analysis is performed against the benchmark artificial intelligence (AI) models. Models are constructed based on Pb concentration (IC), the dosage of attapulgite clay (dose), contact time (CT), pH, and NaNO 3 (SN). Principle component analysis (PCA) and correlation analysis (CA) methods are integrated to assess the importance of the applied predictors and their relationship with the target. Research findings approved the potential of the grid-RF model as a marginal superior predictive model against the grid-SVM in terms of MAE, i.e., 3.29 and 3.34, respectively; moreover, the md scored the same, i.e., 0.93, which reveals the potential predictability for both. Nonetheless, grid-MARS and standalone MARS models remained likewise in their predictability. IC parameter demonstrated the highest influential among all the predictors with the highest value of importance in the case of all three evaluators. The solution pH and dose stands together with marginal differences in case of PCA method; however, solution pH and CT appeared with similarity impact using the PCA method.

The holistic approach of Driver-Pressure-State-Impact-Response (DPSIR) methodology was applied to selected Cr(VI) impacted groundwater bodies of Central Greece. The main driving forces in the study areas are agricultural activities, urban and industrial development as well as tourism. The main pressures induced by the anthropogenic activities are fertilizer use, uncontrolled urban sewage disposal and industrial effluents discharges. Groundwater stress is caused by the qualitative degradation due to Cr(VI), NO 3 - , Cl - and SO 4 2- contamination. Hexavalent chromium occurrence is attributed to both geogenic and anthropogenic sources. The maximum Cr(VI) concentration (11.7 mg/L) was measured in Oinofyta area. Important impacts are the deterioration of groundwater body chemical status as well as the decline of groundwater use efficiency. Based on the applied DPSIR, a management framework is proposed in order to address the complex environmental issue of Cr(VI) in the study areas.