Review Paper
Environment
Saahil Hembrom; Neeta Kumari
Abstract
Mining activities adversely affect the groundwater quality. Human health also subsequently gets affected because of many environmental and ecological risks due to mobilization of contaminants and alteration of hydrogeochemical processes. This review assesses the hydrogeochemical characteristics and groundwater ...
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Mining activities adversely affect the groundwater quality. Human health also subsequently gets affected because of many environmental and ecological risks due to mobilization of contaminants and alteration of hydrogeochemical processes. This review assesses the hydrogeochemical characteristics and groundwater quality in mining areas emphasizing the crucial processes like rock-water interaction, acid mine drainage formation, and heavy metal contamination. These processes impact the end uses of groundwater quality like drinking, irrigation and industrial uses. To understand the causes of contamination and the availability and suitability of the water, groundwater investigation is required such as assessment of physicochemical parameters and hydrogeochemical faces. By using isotopic techniques and integration of spatial and temporal changes with remote sensing and GIS application, pollution load can be evaluated on water resources. A bibliographic analysis highlights the current research progress in mining sector, focusing on global and regional studies and their impact on water resources. Contamination from heavy metals like arsenic, chromium, cadmium, and other toxic elements has posed serious illnesses to human health and the surrounding ecosystem. The review also highlights the research gaps and prospects for improving groundwater resources through appropriate mitigation strategies like sustainable mining practices and water treatment technologies.
Original Research Paper
Exploration
Balbir Nagal; Ajay Krishna Prabhakar; Mahesh Pal
Abstract
This study delineates groundwater potential (GWP) zones across Haryana, India, for the year 2023 using geospatial techniques integrated with the analytical hierarchy process (AHP). Multiple thematic layers, including slope, land use/land cover (LULC), soil, geology, drainage density (DD), lineament density ...
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This study delineates groundwater potential (GWP) zones across Haryana, India, for the year 2023 using geospatial techniques integrated with the analytical hierarchy process (AHP). Multiple thematic layers, including slope, land use/land cover (LULC), soil, geology, drainage density (DD), lineament density (LD), elevation, rainfall, and topographic wetness index (TWI), were generated using datasets from SRTM, Sentinel-2, food and agriculture organization (FAO), and the India meteorological department (IMD) and weighted through the AHP. These layers were integrated using weighted overlay analysis (WOA) to generate the final GWP map. The GWP map was validated against field groundwater level (GWL) data from 646 wells recorded in 2018 by the central ground water board (CGWB), resulting in an accuracy of 77.55 percent. This confirmed the reliability of the geographic information system (GIS) and AHP technique. The study reveals that moderate GWP zones dominate (43.71%) the region, followed by high (33.24%) and very high (11.96%) zones, whereas low and very low GWP zones cover 7.59% and 3.51% of the area, respectively. The findings indicate that Haryana’s groundwater distribution is largely stable, with minor variation observed between 2018 and 2023. This shows stable aquifer behaviour and relatively unchanged recharge and extraction patterns over the five-year period. The outcomes of this study are valuable for strategic groundwater management, especially in arid and semiarid regions of Haryana state.
Original Research Paper
Exploration
Satyajeet Parida; Abhishek Kumar Tripathi; Tarek Salem Abdennaji; Yewuhalashet Fissha
Abstract
Coal quality is predominantly determined by its Gross Calorific Value (GCV), which directly influences its economic valuation. Traditional empirical formulas for GCV estimation, though effective, become inefficient and laborious when handling large datasets. To address this, machine learning (ML) techniques ...
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Coal quality is predominantly determined by its Gross Calorific Value (GCV), which directly influences its economic valuation. Traditional empirical formulas for GCV estimation, though effective, become inefficient and laborious when handling large datasets. To address this, machine learning (ML) techniques offer a robust alternative for accurate and rapid predictions. This study employs seven coal quality parameters. Total Moisture (TM), Ash (ASH), Volatile Matter (VM), Hydrogen (H), Carbon (C), Nitrogen (N), and Sulphur (S), as independent variables to develop predictive models for GCV. Four conventional regression techniques, namely Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Random Forest (RF), and Decision Tree (DT), along with two robust regression models Random Sample Consensus (RANSAC) and Huber Regressor (HR) are explored. The dataset comprises coal samples from five Asia-Pacific countries: China, Indonesia, Korea, the Philippines, and Thailand. Comparative performance analysis reveals that the robust regression models significantly outperform the conventional ML techniques. The RANSAC and Huber Regressor models achieve superior prediction accuracy with R² values of 0.9941 and 0.9952, respectively. These findings highlight the potential of robust regression approaches for reliable GCV estimation, facilitating efficient coal quality assessment in large-scale applications.
Case Study
Exploitation
Victor Patson Mutambo; Barnabas Mpaka; Pardon Sinkala; Matheus Ipinge
Abstract
This study evaluates rock mass ratings, rock strength parameters, and the geological structures of the dominant rock units alongside a quantitative assessment of the performance of various anchor systems for enhanced ground support in mine excavations located within the Synclinorium area. This region ...
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This study evaluates rock mass ratings, rock strength parameters, and the geological structures of the dominant rock units alongside a quantitative assessment of the performance of various anchor systems for enhanced ground support in mine excavations located within the Synclinorium area. This region is notable for its complex, folded, and mineralized formations. The deeper levels of the synclinorium are characterised by poor ground conditions, faults, and shear zones. Stress induced by mining activities worsens the situation. These factors have significantly impacted the stability of excavation. Fall-of-ground (FOG) incidents have exhibited a concerning increase over the past nine years. This trend necessitates a thorough investigation into the factors contributing to it. Our research employed empirical methods for rock mass classification, specifically utilising Barton’s Q system and Bieniawski and Scanline mapping of geological structures along the crosscut walls at a 1.50 m elevation. We conducted borehole logging and pull-out tests to evaluate the working and ultimate capacities of rock bolt anchors deployed in the excavations. Borehole cores were analysed for geological formations, colour, and grain size. The findings indicate that excavations in areas with mined-through rock and stone necessitate urgent and intensive roof support to stabilise the surrounding rock mass, thereby enhancing standing time. Additionally, we identified joint patterns, joint orientations, and the various stresses affecting the surrounding rock mass in the crosscuts. The above highlights the importance of geological data in the design of effective ground control and support mechanisms. Pull-out testing conducted at the 3360 level recorded a 28.6% failure rate in primary development despite very competent ground.
Original Research Paper
Mineral Processing
Salih Aydogan; Mohamed Taha Osman Abdelraheem; Babiker Alkloosi; Mustafa Boyrazli
Abstract
This article describes the kinetics of utilizing ammonium nitrate to dissolve pure metallic silver in hydrogen peroxide solution (H2O2). Using pure metallic silver allows for precise leaching kinetics research by removing interference from impurities and facilitating accurate interpretation of rate-controlling ...
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This article describes the kinetics of utilizing ammonium nitrate to dissolve pure metallic silver in hydrogen peroxide solution (H2O2). Using pure metallic silver allows for precise leaching kinetics research by removing interference from impurities and facilitating accurate interpretation of rate-controlling mechanisms. The impact of temperature, rotation speed, H2O2 concentration, and ammonium nitrate concentration were all examined. The results show a favorable relationship between the rate of silver (Ag) dissolution and the rotation speed. Additionally, a low concentration of ammonium nitrate (between 0.003 and 0.20 M) has advantageous effects on Ag dissolution. The dissolution rate was significantly impacted by H2O2 concentrations between 0.08 and 0.15 M, because this range of H₂O₂ concentration required to provide sufficient oxidative potential for significant silver solubility. However, this effect is less pronounced in the 0.20–0.50 M range. 20 - 50 °C range of temperatures are advantageous since H2O2 is stable in this range. It was calculated that the activation energy was 25.66 kJ/mol.
Original Research Paper
Environment
Nanang Suparman; Muhammad Andi Septiadi; Yuflih Rizkia Timoty; Faizal Pikri
Abstract
This study aims to analyse the regulatory hierarchy and its implications within the regional autonomy regime in the context of bauxite mining management in Indonesia, with a focus on Tanjungpinang City. Although decentralization grants local governments the authority to manage natural resources, overlapping ...
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This study aims to analyse the regulatory hierarchy and its implications within the regional autonomy regime in the context of bauxite mining management in Indonesia, with a focus on Tanjungpinang City. Although decentralization grants local governments the authority to manage natural resources, overlapping regulations between central and regional authorities have resulted in governance conflicts, weak enforcement, and substantial environmental degradation. Utilizing a mixed-method approach informed by Kagan’s regulatory model, this research integrates field-based environmental assessments including bauxite sediment sampling and post-mining water quality analysis with a normative analysis of mining regulations and governance practices. The findings reveal a dominance of procedural legal frameworks over substantive environmental accountability. Regional autonomy laws tend to prioritize investor interests, often at the expense of community welfare and environmental restoration. Additionally, inadequate local oversight has allowed the continued export of unprocessed bauxite, exacerbating environmental harm. This study contributes new insights by exposing the structural misalignment between regulatory authority and environmental responsibility under Indonesia’s current autonomy regime. It underscores the urgent need for regulatory reform that clarifies lines of authority, mandates in-country bauxite processing prior to export, and enforces post-mining reclamation obligations at the regional level. These recommendations aim to support policymakers in designing enforceable and context-sensitive reforms for sustainable bauxite mining governance.
