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 m²) of the area had a very low suitability, 15.83% (363,599 m²) had a low suitability, 23.99% (550,998 m²) had a moderate suitability, 24.99% (573,813 m²) had a high suitability, and 25.92% (595,125 m²) 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.

In the coal phase-out era, achieving sustainable mine closure is significant and prioritizes targets for the mining industry. In this study, the already closed lignite mine of Kardia, North Greece, is investigated, where the mine void left is naturally filled with water. The viability of different repurposing land uses is evaluated, and the natural water level development inside the mine pit is investigated concerning its future uses. The potential for solar photovoltaic (PV) panels developed on mining land and its surrounding area is evaluated in combination with the application of pumped hydro storage (PHS) technology, utilizing pit lake water. Except for electricity system planning, other end-uses that offer multiple, mutually reinforcing and lasting benefits are investigated, such as recreation parks, terrestrial wildlife, aquaculture and agriculture. All repurposing scenarios are evaluated with regard to the spatiotemporal evolution of the lake, by generating forecasts of the dependent variables (rainfall and temperature) via linear (autoregressive integrated moving average) and non-linear (artificial neural network) models. The prediction of pit lake natural development redefines the new land use layout and the land repurposing decisions. This is essential for strategic planning, considering the Greek lignite mining industry’s priority regarding transitioning from the current coal-based electricity to renewable energy sources (RES) technology.

At the end of surface mining activities, the remnant voids are of great concern regarding rehabilitating the final open pits. The investigation of the sustainability of pit lakes in post-mining regions constitutes a challenging research problem. This paper aims to highlight the effectiveness of pit lakes as a rehabilitation factor. In this framework, several cases worldwide and in Greece were examined in detail and evaluated. The results indicate that mine pit lakes must be evaluated as dynamic systems, natural or artificial, which demand rational mine water management to ensure their sustainability. Specifically in Greece, it is of great importance during the transition to the post-lignite era.

The development of three-dimensional geological models has proven to be critical for conceptualizing complex subsurface environments. This is crucial for mining areas due to their various hazards and unstable conditions. Furthermore, three-dimensional (3D) models can be the initial step for the development of numerical models in order to support critical decisions and sustainable mining planning. This paper illustrates the results and the development phases of a 3D geological model within the boundaries of the Kardia lignite deposit in western Macedonia, Greece. It also highlights the usefulness of a Geographic Information System (GIS) methodology in the subsurface geological and hydrogeological analysis regarding the Underground Coal Gasification (UCG) methodology. In addition, the work focuses on the integrated geospatial framework that was developed to support the Coal-to-Liquids Supply Chain (CLSC) integration in unfavorable geological settings. A 3D subsurface geological model of the study area was developed to identify a suitable area for in situ coal conversion and UCG considering criteria related to specific coal thickness and depth. In this context, the suggested integrated geomodelling workflow can positively contribute to the implementation of conventional and innovative mining, saving time and reducing the cost to improve the quality of information needed to support decisions related to UCG implementation.

Spatial modeling and evaluation is a critical step for planning the exploitation of mineral deposits. In this work, a methodology for the investigation of a multi-seam coal deposit spatial variability is proposed. The study area includes the Klidi (Florina, Greece) multi-seam lignite deposit which is suitable for surface mining. The analysis is based on the original data of 76 exploratory drill-holes in an area of 10 km², in conjunction with the geological and geomorphological data of the deposit. The analytical methods include drill-hole data analysis and evaluation based on an appropriate algorithm, principal component analysis and geographic information techniques. The results proved to be very satisfactory for the explanation of the maximum variance of the initial data values as well as the identification of the deposit structure and the optimum planning of mine development. The proposed analysis can be also helpful for minimizing cost and optimizing efficiency of surface mining operations. Furthermore, the provided methods could be applied in other areas of geosciences, indicating the theoretical value as well as the important practical implications of the analysis.