An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Potash mining is an important economic activity in the north-east of Spain. However, one of the main environmental issues produced for such type of mining is subsidence, which generates horizontal and vertical ground displacements. A Geographic Information System (GIS)-based model is proposed as a management system in a case study with two mines. This system is able to deal with subsidence data and its behavior over time. More than 1300 control points are included in the GIS, with data since 2007. These data processed by the GIS allowed determining the module, sense and direction of the displacements, the sinking velocity and the possible affectation of subsidence to infrastructures and buildings. Hence, the system created can be a useful tool to manage subsidence data, determine its evolution, predict future environmental and social impacts and control corrective measures.

Fires in underground spaces are especially relevant due to their potential mortality. However, there is not much research in real-scale spaces done so far. In this study, several fire scenarios were analyzed in an underground drift, taking into account the main environmental variables: airflow, temperature, oxygen, and pollutants. The behavior before and after the fire load was determined, as well as the evolution of the fire over time throughout the drift and its cross-section, finding important trends of the fire based on the airflow–fuel load ratio. Furthermore, the five most representative scenarios were modeled using the fire dynamics simulator (FDS). Results obtained in the simulations, with the adjusted parameters, display a good correlation between simulated and experimental values, being able to extrapolate these values to know the performance of potential fires in other underground spaces or mines. The outcomes could also be a very useful tool to study the effectiveness of possible emergency measures or the potential impact of a fire in this type of environments.

The indicative ability of a gas indicator for the spontaneous combustion of coal is affected by the secondary oxidation of oxidized coal, from old goafs, entering a new goaf through air leakages. This phenomenon can affect the accuracy of early warning systems regarding the spontaneous combustion of coal in a goaf. In this research, three kinds of coal were selected to carry out a spontaneous combustion simulation experiment in which a temperature-programmed experimental device was used to analyze the behavior of the index gas towards raw coal and oxidized coal, for which the latter was oxidized at 70 °C, 90 °C, 130 °C, and 150 °C. The results show that the chain alkane ratio in the secondary oxidation process and the trends of oxygen, CO, and C₂H₄ concentrations are the same as those in the primary oxidation process. On the other hand, the temperature at which C₂H₄ initially appears, during secondary oxidation, is lower than in primary oxidation. The CO produced in the early stage of secondary oxidation is greater than the CO produced, at the same temperature, in primary oxidation. In this regard, the usage of C₂H₄ concentration as an indicator with which to judge the occurrence of the spontaneous combustion of coal would allow for an earlier response. In the secondary oxidation process, the temperature of the extreme value of the alkene ratio appears higher than in primary oxidation. The presence of a higher pre-oxidation temperature and a higher proportion of secondary oxidation gas will affect an indicator’s judgement when the primary oxidation enters the severe oxidation stage. The gas produced by secondary oxidation will affect the early warning of the spontaneous combustion of coal in the coal mine goaf, which should be considered in the establishment of an early warning system.

Subsidence is an important environmental and safety issue in the mining sector, yet there remain voids in knowledge in terms of management and prediction. This study aims to improve knowledge on the impact of mining operations on the surface, reducing their effect on the environment, increasing the safety of mining operations, monitoring stress behavior and predicting rock mass. Therefore, an analysis was carried out to process and analyze the measured subsidence data and, subsequently, create a numerical model to predict the surface subsidence of a case study mine. The model was developed based on a finite element method (FEM). It was achieved by considering the geological characteristics of the area, the design features of the mine, the surface subsidence measured over twelve years and the time-dependent behavior of the geological layers. The correlation obtained between the measured subsidence and the modelling results was very satisfactory, with a 90% confidence level, over the years analyzed. Hence, the efficiency of the system was confirmed, enabling the evaluation and the prediction of potential surface effects, and therefore improving the safety and environmental levels of the mining area.