IR@CIMFR - Central Institute of Mining and Fuel Research (CSIR)
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Assessment on Sustainable Biomining: Integrating Environmental Responsibility and Economic Viability
No full textMining has long been a crucial for industrial and economic development, yet conventional practices have led to environmental
degradation, resource depletion, and social challenges. Biomining has emerged as a sustainable alternative, utilizing microor
ganisms for metal extraction and environmental restoration. This eco- friendly approach facilitates the recovery of metals from
low- grade ores and mining waste while reducing energy consumption, greenhouse gas emissions, and environmental impact.
This review provides a comprehensive analysis of biomining's economic, environmental, and social implications, emphasizing its
role in advancing the circular economy. Global case studies from Chile, China, Canada, and South Africa illustrate its feasibility
and benefits. Various biomining techniques, including heap leaching, stirred- tank bioleaching, and in situ biomining, are exam
ined for their effectiveness in recovering metals like copper, gold, and uranium. Furthermore, innovations in microbial genomics
and bioelectrochemical systems highlight the potential of engineered microorganisms to enhance metal recovery. Despite its promise, biomining faces challenges such as slow processing rates, microbial adaptation issues, and regulatory barriers. Future advancements, including synthetic biology, artificial intelligence, and policy- driven incentives, could optimize biomining applications worldwide. This review underscores biomining's potential to bridge scientific innovation and industrial sustainability, ensuring responsible resource management and reduced environmental impact
Identification of metal-tolerant herbaceous species for phytostabilization and ecological restoration of fly ash dumpsites
No full textThe global deposition of fly ash (FA) from industrial processes is a growing environmental concern due to its detrimental effects on ecosystems. Sustainable strategies such as phytomanagement offer viable solutions for restoring abandoned FA dump sites. The study assessed soil quality, herbaceous diversity, and heavy metal accumulation in species growing in FA dump of Bokaro Thermal Power Station and adjacent forest sites (FS). Soil analysis of the FA dump site revealed elevated heavy metal concentrations, including Mn (272.42 ± 11.27 mg/kg), Zn (86.92 ± 1.67 mg/kg), Ni (70.82 ± 1.53 mg/kg), Cr (57.31 ± 1.75 mg/kg), Pb (46.85 ± 1.34 mg/kg), Co (37.93 ± 1.19 mg/kg), Cu (20.49 ± 0.48 mg/kg), and Cd (1.54 ± 0.05 mg/kg), along with slight alkalinity and nutrient deficiencies. The herbaceous community was dominated by species from Poaceae and Asteraceae families with 37.8% classified as highly metal-tolerant based on Metal Tolerance Index. Species such as Cynodon dactylon, Saccharum spontaneum, and Alternanthera sessilis exhibited high importance value index and bioconcentration factors (BCF > 1) for Cr, Zn, and Pb. These species effectively stabilized metals, making them suitable for phytostabilization. PCA analysis indicated that pH, WHC, TOC, and BD significantly influenced plant metal uptake, while nutrients (N, P, K) contributed to metal immobilization. CCA analysis demonstrated that soil parameters and heavy metal availability governed herbaceous species distribution, making them potential indicators of contamination. This study highlights the potential of metal-tolerant herbaceous species for reclaiming FA dumps by improving soil quality and reducing metal mobility, contributing to sustainable land restoration
Experimental Investigation on the Mechanical and Microstructural Properties of Cemented Coal Ash Based Paste Backfill Reinforced with Polypropylene Fibre
No full textOrdinary-cemented paste backfill (CPB) has low stiffness and tensile strength. Several studies have reported pre-eminence of polypropylene (PP) fibre in improving such characteristics. The efficacy of PP fibre as a reinforcement for mine tailing-based CPB is widely explored but for coal ash-based CPB is not investigated. Therefore, through present study, the significance of PP fibre on the mechanical and microstructural characteristics of CPB prepared with coal ash was investigated. Through repeated experimental trials, the optimum solid concentration for CPB was fixed at 75wt.%. The fibre was subsequently added from 0.1‒0.5% of total dry solid weight. The results show that reinforcement did not have any trend with the slump but increased the rate of water loss through evaporation. In compare to CPB specimens without fibre, the specimens with 0.5% fibre showed enhancement in UCS by 185% (7 days), 128% (14 days), and 81% (28 days). The failure pattern of CPB was transformed from brittle to ductile through fibre reinforcement. Increasing fibre proportion from 0 to 0.5% augmented the elastic modulus by 37%, 25.4%, and 36.4%, tensile strength by 138.89%, 105.57%, and 93.61%, and failure strain by 90.5%, 86.7%, and 75% for the CPB specimens tested after 7 days, 14 days, and 28 days of curing, respectively. The SEM analyses revealed the fibre bridging impact in view of lessen pores, better compactness, integrity, and fibre-matrix bond. The present investigation could improve the ground conditions during underground winning of coal and provide a new theoretical reference for coal ash-based paste backfill mining
Zero-waste hydrogen production using Ga-In activated aluminium composites for pressurized sea water desalination
No full textAl:Ga:In composites with varying weight % were developed, effectively removing the oxide layer that hinders the
Al reaction with water. Among these developed composites, the 6:1:1 (0.75 gm Al) ratio demonstrated the
highest hydrogen production of 338 ml in 1000 s. Ex-situ XRD studies confirmed the existence of aluminium
hydroxide (Al (OH)3) with Ga and In. Ga and In, which do not participate in the reaction, are efficiently
recovered via Bayer’s method with 98 % yield. Importantly, 1 g of the 6:1:1 composite can desalinate one litre of
seawater within 30 min with the TDS, conductivity, and pH of 750–900 mg/L, 1.0–1.25 mS/cm, and ̴ 7,
respectively. This innovative approach minimizes wastage, as Ga and In are reclaimed post-reaction. Further-
more, surplus hydrogen can be turned into electricity using a suitable fuel cell, offering a sustainable means to
generate clean energy while simultaneously treating seawate
Mechanistic insights into the photocatalytic and electrocatalytic activities of MgNiO2 : role of reactive oxygen species and oxygen vacancies
No full textGranular MgNiO2 has emerged as a promising catalyst owing to its remarkable electrocatalytic activity
and photodegradation efficiency under visible light. In this work, granular surface-engineered MgNiO2
nanoparticles were synthesized using the precipitation method. The interaction of Mg and Ni, forming
Mg–Ni–O structures during high-temperature MgNiO2 synthesis, was investigated through X-ray
photoelectron spectroscopy (XPS) analysis. The presence of Ni3+ species in the ionic form indicated
charge transfer reactions in the catalyst. The band gaps of the as-prepared MgNiO2 and NiO were
determined to be 2.2 eV and 3.7 eV, respectively. The first-order transverse optical (TO) phonon modes
observed at 536 cm−1 indicated the presence of NiO, which was identified as the primary contributor to
the Raman peaks. Further, the photocatalytic degradation of caffeine under visible light achieved a
removal efficiency of 95.5% within 180 minutes. The intermediate reactive oxidative species (ROS) leading
to MgNiO2 degradation were identified, and their lifetime and diffusion length in the solution were
reported. Superoxide (O2−˙) and hydroxyl (˙OH) radicals were identified as the main ROS contributing to
caffeine degradation. The electrocatalytic oxygen evolution reaction (OER) indicated a high density of
oxygen vacancies in MgNiO2 compared to NiO, suggesting the promoter role of Mg species in the
photocatalyst. These insights provide a holistic understanding of MgNiO2 as a catalyst and its pivotal role
in green and efficient caffeine photodegradation and the electrocatalytic OE
Threshold-based inventory for flood susceptibility assessment of the world’s largest river island using multi-temporal SAR data and ensemble machine learning algorithms
No full textMajuli is the world’s largest inhabited river island and is highly prone to flood hazards, resulting in significant damage to houses and agriculturally based livelihoods. Considering its cultural heritage and unique landscape, it is necessary to prepare a flood susceptibility map (FSM) to reduce the annual damage. Therefore, the primary aim of this research is to prepare and improve the precision of FSM using microwave satellite images and six robust ensemble machine learning models. In the three main stages of FSM, each stage contributes to achieving optimal accuracy. In the first stage, a threshold-based flood inventory map has been prepared from six years of multi-temporal SAR images. In the second stage, preliminarily seventeen flood conditioning variables such as elevation, slope, profile curvature, terrain ruggedness index, topographic wetness index, distance from streams, rainfall, land cover land use, normalized difference vegetation index, distance from road, geomorphology and lithology have been prepared, but after utilizing the Boruta algorithm and multicollinearity analysis, twelve key flood-influencing variables have been selected for flood modelling. In the final stage, six robust ensemble machine learning models namely random forest, rotation forest, stochastic gradient boosting, boosted regression tree, deep boost and logit boost have been applied and subsequently compared to determine the best model. The performance of the models is evaluated with various statistical measurements, including the area under curve (AUC), sensitivity, specificity, kappa index and overall accuracy values. The results revealed that the random forest model outperformed the other models in terms of model fitness (AUC = 1) and predictive capability (0.99). Additionally, the very highly vulnerable pixels of the FSM are validated with the twenty flood locations from the field surveys, showing that the accuracy of the FSM is 100%. The FSM indicates that around 50% of the study region has a very high and high susceptibility to future flood occurrences
Smart driving assistance system for mining operations in foggy environments
No full textEnvironmental conditions such as fog and rain are among the most challenging scenarios for drivers of heavy vehicles in open-pit mines. This paper proposes an efficient camera-based driving assistance system to improve image quality for operators of heavy vehicles for safe driving in open-pit mines. The system incorporates image processing algorithms and technologies such as proximity radar and global navigation satellite system to provide multi-stage safety features while driving. Finally, the screen fitted in the dashboard is forward-facing to the operator's seat and displays the final output. The efficacy of the developed system was assessed through its implementation in open-pit mining environments with visibility range of 5 m during dense fog. The system improves the visibility range to around 30–40 m, whereas the unaided eye can only see about 5 m in extremely dense fog conditions at the mine site. The average values of contrast, structural similarity index measure, peak signal-to-noise ratio, visual information fidelity, and universal quality index for the tested images were 0.92, 0.52, 19.42 dB, 0.83, and 0.49, respectively. In image processing under dense fog where visibility is below 5 m, typical performance standards are around 0.9 for contrast, above 0.5 for structural similarity index measure, over 20 dB for peak signal-to-noise ratio, over 0.5 for visual information fidelity, and more than 0.5 for universal quality index. Thus, the test results indicate that the proposed image enhancement algorithm produced significantly improved images, proving its effectiveness in extremely low visibility situations. Additionally, the object detection model demonstrated an accuracy of 88%, indicating satisfactory performance of the system in foggy conditions. Consequently, the system can be safely employed in open-pit mining operations, allowing for the continuation of activities even in foggy conditions
Prediction of Blast Induced Ground Vibration in Deccan Trap Volcanic Rock at Ulwe Hill, New Mumbai Airport: Evaluation Based on Empirical, ANN and Multiple Machine Learning Models
No full textBlasting is a conventional method of rock breakage in mines and civil works. Ground vibration are integral part
of a blast and lot of the studies have been done by umpteen researchers with the aim to mitigate the impact of ground
vibrations on nearby structures, particularly not belonging to the owner of the mine or civil works. However, owing to
variations in geology, explosive and blast design, spatial attenuation of the ground vibration is site specific. This study
relates to a detailed analysis of data of 107 blasts acquired from, under construction, New Navi Mumbai airport site. The data was analyzed and evaluated over general regression and ANN based models, characterized by Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correlation of Determination (R 2 ), Correlation Coefficient (R), and Nash–Sutcliffe Model Efficiency Coefficient (NASH). Out of 9 models, it was found that Gradient Boosting Regression model yielded the minimum MSE, RMSE, MAE and best R 2 , R and NASH, i.e., 0.11, 0.34, 0.23, 0.51and 0.91, 0.95, 0.91 respectivel
Human health risk assessment of dietary metal intake through commonly consumed vegetables in Gaya District, Bihar, India
No full textThis study assessed the concentration of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn in commonly grown vegetables collected from the Gaya district of Bihar. Metals were determined using Inductively Coupled Plasma Mass Spectrometry following sample preparation and digestion. As, Cr, Ni, Pb and Zn exceeded the maximum allowable concentration of Food and Agricultural Organization in some of the vegetable samples. Non-carcinogenic human health risk assessment due to ingestion of vegetables was estimated using Hazard Quotient (HQ) and Hazard Index (HI) which revealed that non-carcinogenic risks were primarily due to Co, followed by Cr and Fe. The risk was higher in the leafy and underground vegetables as compared to the fruit vegetables. Of all the locations, the highest risk was estimated for Fatehpur, followed by Manpur and Bodhgaya, which was attributed to the anthropogenic activities of the locations. The HI exceeded unity in 64.3% of the vegetable samples, indicating potential health risks to the consumers and suggesting that vegetables from some locations in the Gaya district might have food safety issues. Periodic soil testing, irrigation water management, and avoidance of leafy vegetables from polluted sites are suggested to lower the health risks associated with vegetable consumption
Rare earth elements geochemistry, mineral hosts and recovery potential from Singrauli coalfield, India
No full texthe geochemical behavior and mineralogical associations of critical and rare earth elements plus yttrium (REY) in the Singrauli Coalfield, India, were investigated. Representative samples were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES) and X-ray fluorescence (XRF) to determine REY concentrations and their correlations with major oxides (SiO2, Al2O3, Fe2O3). Total REY concentrations ranged from 79 to 136 ppm (coal basis), with Ce, Nd, and La being the most abundant. Critical REY, such as Nd and Y, exceeded global averages for coal. Light rare earth elements (LREEs: La, Ce, Nd) showed strong positive correlations with SiO2 and Al2O3. Scandium also displayed a high affinity for alumino-silicate phases, consistent with its known geochemistry. In contrast, heavy rare earth elements (HREEs: Lu, Yb) correlated positively with Fe2O3, suggesting incorporation into iron-bearing minerals like hematite or goethite. Erbium exhibited a distinct pattern, with a strong positive correlation to Al2O3 and a pronounced negative correlation with Fe2O3, potentially due to redox-sensitive fractionation. Field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FE-SEM-EDX) of coal ash revealed REY (Ce, Nd) within glassy Si–Al–P phases. Higher-magnification observations identified ferromanganese minerals, zirconium silicates, and potential monazite or xenotime associations. The study concludes that the distribution and host phases of REY in the Singrauli Coalfield, particularly from the Krishnashilla and Kakri mines, indicate significant potential for secondary recovery