Gospodarka Surowcami Mineralnymi - Mineral Resources Management

The environmental problems caused by the development and utilization of mineral resources have become important factors affecting ecological security. Guizhou is a Chinese province with relatively developed paleoweathered sedimentary bauxite deposits, abundant resource reserves, and a long history of mining. And, the demand for bauxite in Guizhou is expected to continue to grow. However, long-term or unreasonable resource development has produced a series of prominent environmental problems, such as the occupation and destruction of land resources and heavy metal pollution in soil and water bodies. Based on the existing research results in China and abroad, this paper analyzes the current situation, distribution characteristics, and development and utilization of bauxite resources in Guizhou to explain the corresponding environmental impacts. The results show that because of the many types and high concentrations of associated elements in bauxite and the high alkalinity, heavy metal components, and radioactive elements in red mud, the development and utilization of bauxite resources are associated with higher environmental risk. And more impact of bauxite mining on regional biodiversity, soil, air, surface water, and groundwater need to be evaluated. This paper also proposes coping strategies or countermeasures of environmental governance and control to achieve the green, sustainable and high-quality development of bauxite-related industries for meeting future environmental requirements.

This paper presents the results of analyses of structure, volume and trends of demand for selected major critical raw materials (CRMs) suitable for the EU’s photovoltaic industry (PV). In order to achieve the EU’s goals in terms of the reduction of greenhouse gas emission and climate neutrality by 2050, the deployment of energy from renewable sources is of key importance. As a result, a substantial development of wind and solar technologies is expected. It is forecasted that increasing the production of PV panels will cause a significant growth in the demand for raw materials, including CRMs. Among these, silicon metal, gallium, germanium and indium were selected for detailed analyses while boron and phosphorus were excluded owing to small quantities being utilized in the PV sector. The estimated volume of the apparent consumption in the EU does not usually exceed 0.1 million tonnes for high purity silicon metal, a hundred tonnes for gallium and indium and several dozen tonnes for germanium. The major net-importers of analyzed CRMs were Germany, France, Spain, Czech Republic, the Netherlands, Slovakia and Italy. The largest quantities of these metals have been utilized by Germany, France, Belgium, Slovakia and Italy. The PV applications constitute a marginal share in the total volume of analyzed metal total end-uses in the EU (10% for silicon metal, 5% for gallium, 13% for germanium and 9% for indium). As a result, there is a number of applications that compete for the same raw materials, particularly including the production of electronic equipment. The volume of the future demand for individual CRMs in PV sector will be strictly related to trends in the development of PV-panel production with crystalline silicon technology currently strongly dominating the global market.

The mean-reversion model is introduced into the study of mineral product price prediction. The gold price data from January 2018 to December 2021 are selected, and a mean-reverting stochastic process simulation of the gold price was carried out using Monte Carlo simulation (MCS) method. By comparing the statistical results and trend curves of the mean-reversion (MR) model, geometric Brownian motion (GBM) model, time series model and actual price, it is proved that the mean-reversion process is valid in describing the price fluctuation of mineral product. At the same time, by comparing with the traditional prediction methods, the mean-reversion model can quantitatively assess the uncertainty of the predicted price through a set of equal probability stochastic simulation results, so as to provide data support and decision-making basis for the risk analysis of future economy.

The demand for energy on a global scale increases day by day. Unlike renewable energy sources, fossil fuels have limited reserves and meet most of the world’s energy needs despite their adverse environmental effects. This study presents a new forecast strategy, including an optimization-based S-curve approach for coal consumption in Turkey. For this approach, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA) are among the meta-heuristic optimization techniques used to determine the optimum parameters of the S-curve. In addition, these algorithms and Artificial Neural Network (ANN) have also been used to estimate coal consumption. In evaluating coal consumption with ANN, energy and economic parameters such as installed capacity, gross generation, net electric consumption, import, export, and population energy are used for input parameters. In ANN modeling, the Feed Forward Multilayer Perceptron Network structure was used, and Levenberg-Marquardt Back Propagation has used to perform network training. S-curves have been calculated using optimization, and their performance in predicting coal consumption has been evaluated statistically. The findings reveal that the optimization-based S-curve approach gives higher accuracy than ANN in solving the presented problem. The statistical results calculated by the GWO have higher accuracy than the PSO, WOA, and GA with R ² = 0.9881, RE = 0.011, RMSE = 1.079, MAE = 1.3584, and STD = 1.5187. The novelty of this study, the presented methodology does not need more input parameters for analysis. Therefore, it can be easily used with high accuracy to estimate coal consumption within other countries with an increasing trend in coal consumption, such as Turkey.

In order to improve the utilization rate of coal resources, it is necessary to classify coal and gangue, but the classification of coal is particularly important. Nevertheless, the current coal and gangue sorting technology mainly focus on the identification of coal and gangue, and no in-depth research has been carried out on the identification of coal species. Accordingly, in order to preliminary screen coal types, this paper proposed a method to predict the coal metamorphic degree while identifying coal and gangue based on Energy Dispersive X-Ray Diffraction (EDXRD) principle with 1/3 coking coal, gas coal, and gangue from Huainan mine, China as the research object. Differences in the phase composition of 1/3 coking coal, gas coal, and gangue were analyzed by combining the EDXRD patterns with the Angle Dispersive X-Ray Diffraction (ADXRD) patterns. The calculation method for characterizing the metamorphism degree of coal by EDXRD patterns was investigated, and then a PSO-SVM model for the classification of coal and gangue and the prediction of coal metamorphism degree was developed. Based on the results, it is shown that by embedding the calculation method of coal metamorphism degree into the coal and gangue identification model, the PSO-SVM model can identify coal and gangue and also output the metamorphism degree of coal, which in turn achieves the purpose of preliminary screening of coal types. As such, the method provides a new way of thinking and theoretical reference for coal and gangue identification.

The ecological environment is significantly vulnerable to coal-mining activities in western China due to the cold and arid climate. The evaluation of land reclamation is therefore a key process that has to be known for the sustainable use of coal resources. A Bayes discriminant analysis method to evaluate the suitability level of land reclamation for coal mine lands in cold and arid regions of western China is presented. Ten factors influencing the suitability of land reclamation were selected as discriminant indexes in the suitability analysis. The data of eighty-four land reclamation units from sixteen coal-mining areas was used as training samples to develop a discriminant analysis model to evaluate the suitability level of land reclamation. The results show that the discriminant analysis model has high precision and the misdiscriminant ratio is 0.02 in the resubstitution process.The suitability levels of land reclamation for eleven sites in two coal mine lands were evaluated by using the model and the evaluation results are identical with that of the practical situation. Our method and findings are significant for decision makers in similar regions who want to prepare for possible strategies for land reclamation in the future.

This paper presents an experimental study on the leaching of heavy metals, toxic chemicals and persistent organic pollutants (POPs) – PAH, PCB and HCB – from soil dredged from the coastal area of Västernorrland in northern Sweden. The soil was stabilized with cement/slag. Samples were subjected to modified surface leaching and shake tests using technical standards of the Swedish Geotechnical Institute (SGI). The experiments were performed using different blends of binding agents (30/70, 50/50, 70/30) and binder quantities (120 and 150 kg/m3) to analyze their effects on leaching. Soil properties, tools, and workflow are described. Binders included Portland cement and ground granulated blast furnace slag (GGBFS). Samples were tested to evaluate the min/max contents of pollutants (μg/l) for heavy metals (As, Ba, Pb, Cd, Co, Cu, Cr, Hg, Mn, Mo, Ni, S, V, Zn) and the hydrocarbon fraction index in the excess water. The leaching of heavy metals and POPs was assessed in sediments after the addition of the binder. The comparison was made against the two mixes (cement/slag in 30/70% and high/low binder with low/high water ratio). The results showed that 70% slag decreases the leaching of heavy metals and POPs. The equilibrium concentrations of DOC and heavy metals at L/S 10 (μg/l) were measured during the shake experiments to compare their levels in the groundwater that was used as a leachate. The leached content was assessed at L/S 10 in the upscaling experiments using four samples for PAH, PCB and various fractions of hydrocarbons: C10–C40, C10–C12, C12–C16 and C35–C40. The shake test showed a decrease in the leaching of heavy metals and POP substances from the soil subjected to stabilization by a higher amount of slag added as a binder. A binder blend with 30% cement and 70% of GGBFS showed the best performance.

The aim of this study was to evaluate foundry waste used for various applications in terms of heavy metals quantity of fractions of their binding. The novelty of these studies is the use of speciation procedures to assess the fraction of heavy metals in foundry waste. The two most popular speciation procedures, the Tessier method and the SM&T, and also the TCLP single extraction procedure were used to evaluate the use of foundry waste in agritechnique, road engineering and construction in this research. Additionally, local soils were analyzed and compared to landfill foundry waste (LFW). It was found that LFW may have a negative impact on the natural environment when used for agrotechnological applications due to the increased concentration of mobile and bioavailable fractions (mean 9–18%) of metals. Foundry dusts were characterized by a low percentage of mobile and bioavailable (mean 2–6%) forms, although this does not include electric arc fournance dust (EAFD) (mean 17%). The metal content in TCLP extracts was low in all foundry waste samples and allowed the use of the analyzed wastes in construction and road construction. The usefulness of both speciation procedures for the assessment of the leaching of heavy metal forms from foundry waste was confirmed. However, the SM&T procedure was more effective in leaching mobile and bioavailable forms of heavy metals in foundry waste and soil samples.

The subject of this article is the problem of payment gridlocks and their significance for the enterprise sector and the risks they cause. The authors’ attention is focused here on presenting the essence of payment gridlocks, their consequences, as well as the causes on the sides of both the debtor and the creditor. In the empirical part of the article, the authors focused on assessing the problem of payment backlogs in selected mining and energy-production companies in Poland. A study on selected companies from this industry was conducted, the purpose of which was to show the scale of delayed payments with the particular identification of those that are payment backlogs (i.e. a delay of at least 60 days). Five major companies from the energy industry in Poland were selected for the study, representing both the mining and energy production sectors. These companies are Polska Grupa Górnicza SA, Jastrzębska Spółka Węglowa SA, ENEA SA, Energa SA and TAURON Polska Energia SA According to the available data, payment terms in this sector are the longest in the European Union compared to other sectors of the economy. In Poland, the situation is no different in this respect. This is especially visible in the mining industry, which is perceived as very risky when it comes to timely payments. Undoubtedly, reducing payment gridlocks in this industry is a difficult task, which results from its specificity and the number of problems it is struggling with, which have been additionally reinforced by the Covid-19 pandemic.

This paper presents the results of an analysis of selected seismic profiles (reflection and refraction data) from the Radom-Lublin area aimed at obtaining a better understanding of geological structure and the identification of hydrocarbon deposits. To accurately reproduce the seismic reflection covering the sub-Permian formations, seismic cross sections were interpreted based on effective reflection coefficients (ERC). In interpreting the results, reference was made to the results of studies of the area using other geophysical methods.
The results of these studies made it possible to obtain new information on the geology and structure of the Paleozoic complex of the Radom-Lublin area and its relationships with the basement tectonics. The structural arrangement of Carboniferous and Devonian formations as well as older Silurian, Ordovician, and Cambrian series were recognized. Selected significant tectonic and lithological discontinuities and the nature and directions of their course were characterized. Special attention was given to regional tectonic zones: the Skrzynno Fault, the Ursynów-Kazimierz fault zone and the Kock zone. The use of ERC methodology made it possible to define the boundaries of lithostratigraphic units in Carboniferous, Devonian, and older formations. The obtained results can be used to assess hydrocarbon accumulation in the area under consideration.