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.
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.
Environment
Clement Kweku Arthur; Yao Yevenyo Ziggah; Victor Amoako Temeng
Abstract
Blast-induced noise is one of the most persistent environmental challenges in surface mining, posing significant health risks to workers and nearby communities. Accurate prediction of noise levels prior to blasting is essential for mitigating its adverse impacts. This study proposes an explainable ensemble ...
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Blast-induced noise is one of the most persistent environmental challenges in surface mining, posing significant health risks to workers and nearby communities. Accurate prediction of noise levels prior to blasting is essential for mitigating its adverse impacts. This study proposes an explainable ensemble machine learning framework for predicting blast-induced noise using data from an open-pit gold mine in Ghana. Four ensemble models namely: Extreme Gradient Boosting (XGBoost), Gradient Boosting, Adaptive Boosting (AdaBoost), and Categorical Boosting (CatBoost), were developed and evaluated using a comprehensive dataset of 324 blasting events. Performances of the developed models were assessed using coefficient of determination (R²), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of the variation of the root mean squared error (CVRMSE), with XGBoost emerging as the best-performing model (R² = 1.0000, RMSE = 0.0005, MAE = 0.0004, MAPE = 0.0010, CVRMSE = 0.0013). To address the black-box nature of ensemble method, Shapley Additive exPlanations (SHAP) was employed, offering both global and local interpretability. SHAP analysis identified the distance from the blast site to the monitoring point as the most influential factor. This integrative approach not only enhances predictive accuracy but also improves model transparency, supporting sustainable mining practices aligned with United Nations Sustainable Development Goals (SDGs) 3 and 15.
Environment
Ritu Bala Garg; Gurpreet Singh
Abstract
This study presents a comprehensive investigation into the synergistic use of fly ash (FA), coal bottom ash (CBA), and quarry dust (QD) as partial replacements for conventional construction materials, aiming to mitigate environmental degradation while enhancing material performance. Individually and ...
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This study presents a comprehensive investigation into the synergistic use of fly ash (FA), coal bottom ash (CBA), and quarry dust (QD) as partial replacements for conventional construction materials, aiming to mitigate environmental degradation while enhancing material performance. Individually and in combination, a series of concrete mixes were prepared incorporating these wastes at varying proportions, and were tested for workability, compressive strength, and durability (water absorption and chloride ion penetration). Results indicate that blends of FA, CBA, and QD can effectively substitute up to 40% of cement and fine aggregates without compromising structural performance. The mixes containing 20% fly ash, 10% bottom ash, and 10% quarry dust exhibited superior compressive, split tensile, and flexural strength, and reduced water absorption and chloride ion penetration, demonstrating their potential in aggressive environments.
Environment
Ali Rasouli; Akbar Esmaeilzadeh; Reza Mikaeil; Solat Atalou
Abstract
Identifying joint sets is essential in engineering geology for rock mass classification and slope stability analysis in mining. Accurate clustering of joint sets based on dip and dip direction enhances the understanding of rock behavior and ensures stability in mine walls. This study presents a novel ...
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Identifying joint sets is essential in engineering geology for rock mass classification and slope stability analysis in mining. Accurate clustering of joint sets based on dip and dip direction enhances the understanding of rock behavior and ensures stability in mine walls. This study presents a novel clustering approach integrating the Harmony Search (HS) and Particle Swarm Optimization (PSO) algorithms to classify joint sets in the Sungun copper mine. Initially, joint characteristics were classified using the Fuzzy C-Means (FCM) method, with the elbow method selecting a four-class clustering solution. To optimize clustering, FCM was combined with HS and PSO, and joint data were assessed using Davies-Bouldin, Calinski–Harabasz, and Silhouette indices. The results demonstrated that the hybrid FCM-PSO method outperformed alternatives, achieving scores of 0.80, 347.48, and 0.57, respectively, indicating superior clustering performance and stability. In contrast, the FCM-HS method performed worse than FCM alone, ranking third overall. The findings confirm that FCM-PSO effectively classifies joint sets, providing reliable insights into rock mass behavior in the Sungun mine. Considering the features and advantages of the FCM-PSO method, it is concluded that the proposed approach has significant potential for effective joint classification in mining engineering. This improved clustering approach enhances geological analysis, supporting safer and more efficient mining operations.
Environment
Fatemeh Vesmoridi; Feridon Ghadimi
Abstract
A total of 400 stream sediment samples were analyzed for 13 elements, and stepwise factor analysis was employed to generate geochemical maps indicative of mineralization. This method was utilized to develop a Geochemical Mineralization Probabilistic Index (GMPI) through a novel approach that produces ...
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A total of 400 stream sediment samples were analyzed for 13 elements, and stepwise factor analysis was employed to generate geochemical maps indicative of mineralization. This method was utilized to develop a Geochemical Mineralization Probabilistic Index (GMPI) through a novel approach that produces geochemical evidence maps derived from stream sediment data. The study comprised a three-stage factor analysis of geochemical data collected from the Khomain Dehno region. The first factor included Zn, Pb, As, and Cd, accounting for 41.63% of the variance. The second factor comprised Mn, Mo, and Zr, explaining 21.86% of the variance, while the third factor consisted of Fe, Cu, and Ti, representing 7.79% of the variance. The cumulative variance explained by these three factors was 81%. Furthermore, a novel intelligent methodology, termed Relevant Vector Regression (RVR), enhanced with Cocoa Search (CS) and Harmony Search (HS) algorithms, is proposed for the prediction of the GMPI. The HS and CS algorithms were integrated with the RVR model to optimize its hyperparameters. In these models, Zn, Pb, As, and Cd served as input variables, while the GMPI was designated as the output variable. The performance of the predictive models was evaluated using Mean Squared Error (MSE) and the Coefficient of Determination (R²). The results indicated that the RVR model optimized with the HS algorithm exhibits superior performance, achieving an R² value of 0.99256 and an MSE of 0.0031455. These findings underscore the efficacy of the proposed approach for accurate GMPI estimation.
Environment
Mohammad Hadi Salehzadeh; Hadi Farhadian; Saeed Yousefi; Mohammad Dehju
Abstract
This study aims to assess the environmental impacts of coal mining in the Eastern Alborz region, focusing on coal mines from 2013 to 2021, using remote sensing techniques. Landsat 8 satellite images were digitized based on key environmental indices, including NDVI, NDWI, NDSI, and NDBI, and subsequent ...
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This study aims to assess the environmental impacts of coal mining in the Eastern Alborz region, focusing on coal mines from 2013 to 2021, using remote sensing techniques. Landsat 8 satellite images were digitized based on key environmental indices, including NDVI, NDWI, NDSI, and NDBI, and subsequent statistical analyses and evaluations were conducted for the study areas. To distinguish the effects of mining from those of climate change, the results were compared with a reference area located within a natural resource block (baseline area), and the outcomes were thoroughly analyzed. The findings indicate that the combined impacts of mining and climate change have caused significant environmental degradation in the region. In particular, vegetation cover has experienced a sharp decline in recent years, while soil erosion has increased at a slower rate. Projections of mining impacts on vegetation and soil were made by calculating the average NDVI and NDSI indices for 2030 and 2050 in the studied areas. These projections suggest that NDVI is expected to decrease by 0.25 by 2030 and by 0.72 by 2050, indicating further vegetation loss in the coming decades. In contrast, analysis of the NDWI index reveals no clear trend in soil moisture changes over the study period. Given the climatic conditions of the selected areas, it is essential to monitor, manage, and mitigate environmental risk factors to prevent the expansion of drought into northern forests, highlighting the need for appropriate intervention measures.
Environment
Asep Nurohmat Majalis; Muhammad Razzaaq Al Giffari; R Arif Suryanegara; M Rifat Noor; Rachmat Ramadhan; Noviarso Wicaksono
Abstract
Due to its large nickel reserves, Indonesia has become one of the world's largest nickel mining sites and producers. Nickel is a mining commodity with high economic value. However, its mining activity can negatively impact the environment if not managed properly. Therefore, mitigation of the impact of ...
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Due to its large nickel reserves, Indonesia has become one of the world's largest nickel mining sites and producers. Nickel is a mining commodity with high economic value. However, its mining activity can negatively impact the environment if not managed properly. Therefore, mitigation of the impact of nickel mining is necessary. This research has conducted erosion and infiltration tests at various locations in pre-nickel mining zones to mitigate the environmental impact of nickel mining activity. Erosion tests were performed using a rainfall simulator with five nozzles on a 12.5 m² demo plot. Infiltration tests were conducted using a double-ring infiltrometer. The result shows that surface runoff coefficients for disposal, limonite, saprolite, and quarry zones were higher than those for vegetated zones such as grassland, pepper plantation, and forest. The saprolite zone released the highest sediment load, i.e., 484.3 kg ha-1 hour-1, followed by the limonite and the pepper plantation zone, with 243.6 kg ha-1 hour-1 and 185 kg ha-1 hour-1. The highest Cr(VI) concentration, 0.7 mg L-1, was released from the disposal zone, followed by the saprolite, limonite, and pepper plantation zones, with concentrations of 0.56, 0.06, and 0.06 mg L-1, respectively. The infiltration equation obtained from each zone shows that revegetation can significantly reduce runoff. Therefore, revegetation should be prioritized in addition to end-of-pipe treatment to mitigate the impact of nickel mining activities.
Environment
Tulika Gupta; Mahasakti Mahamaya; Shamshad Alam
Abstract
The dumping of mining waste occupies extensive areas of land and poses environmental hazards, including heavy metal leaching, dust pollution, and slope failure. Iron mine overburden (MO), a byproduct of iron mining, exacerbates these issues when dumped. To address the challenges of storing MO, it was ...
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The dumping of mining waste occupies extensive areas of land and poses environmental hazards, including heavy metal leaching, dust pollution, and slope failure. Iron mine overburden (MO), a byproduct of iron mining, exacerbates these issues when dumped. To address the challenges of storing MO, it was combined with fly ash and cement to develop controlled low-strength material (CLSM). Initially, the raw materials were examined for their physical, chemical, and mineralogical properties. Subsequently, 24 different CLSM mixtures were prepared by varying cement, fly ash, MO, and water-to-binder ratios. The fresh mixes were tested for flowability, bleeding, and fresh density, while the hardened properties, including density, unconfined compressive strength (UCS), and durability, were also evaluated. Results showed that all CLSM mixes were highly flowable, with flow diameters exceeding 150 mm, and some exhibited self-leveling behavior. The 28-day compressive strength ranged from 0.52 MPa to 4.28 MPa, with a few mixes being soft enough for manual excavation. Durability tests indicated that approximately 60% of the mass remained intact after eight wet-dry cycles, demonstrating good resistance to erosion. This study highlights the potential for utilizing mining waste in sustainable construction materials.
Environment
Sadegh Abedi; Mohamad Reza Karimi; Alireza Alinezhad
Abstract
Achieving sustainable mining development is increasingly vital in addressing environmental challenges, meeting global decarbonization demands, and progressing toward a Net-Zero Emissions (NZE) future. This study proposes an integrated framework to advance sustainable mining in Iran, with a particular ...
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Achieving sustainable mining development is increasingly vital in addressing environmental challenges, meeting global decarbonization demands, and progressing toward a Net-Zero Emissions (NZE) future. This study proposes an integrated framework to advance sustainable mining in Iran, with a particular focus on the roles of emerging technologies and environmental regulations. The core research question investigates how combining fuzzy decision-making methods with intelligent modeling can guide the mining sector toward NZE goals. A multi-stage mixed-methods approach was employed. Initially, key variables were identified using the fuzzy Delphi method and expert judgment. The hesitant fuzzy analytic hierarchy process (HFAHP) was then applied to prioritize and weigh the main factors. Subsequently, fuzzy DEMATEL and interpretive structural modeling (ISM) were utilized to uncover causal relationships and hierarchical dependencies among variables. Finally, the adaptive neuro-fuzzy inference system (ANFIS) simulated potential pathways for achieving sustainable mining. Findings highlight four critical variables—carbon pricing policies, investment costs, global metal prices, and technological innovation—as the most influential drivers. Moreover, ANFIS results indicate that strengthening these factors significantly increases the likelihood of achieving the NZE scenario. Overall, the proposed model serves as a practical decision-support tool for policymakers and mining stakeholders, aiding in policy design, investment strategy develop.
Environment
Shima Rahimi; Mehdi Irannajad
Abstract
In this study, Red Mud (RM) as a byproduct in alumina production process from bauxite was used as an adsorbent for sulfate contaminant adsorption from acid mine drainage (AMD). AMD discharge led to the acidification of water which has detrimental effects on aquatic life and human health. Analytical methods, ...
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In this study, Red Mud (RM) as a byproduct in alumina production process from bauxite was used as an adsorbent for sulfate contaminant adsorption from acid mine drainage (AMD). AMD discharge led to the acidification of water which has detrimental effects on aquatic life and human health. Analytical methods, laboratory studies and molecular simulations were conducted to investigate sulfate adsorption on RM. Thermodynamic calculations were performed after optimizing of existing metal oxide in RM structure with the Material Studio software using the dmol3 and DFT method. The adsorption energy results by Adsorption locator module determined -819.09, -561.7, -268.8, -105.4, and -314.7 kcal/mol for Fe2O3, Al2O3, CaCO3, TiO2 and SiO2, respectively. The most active compounds in RM structure (iron and aluminum oxides) account for 22.5% and 13.3% in the red mud structure, respectively. In addition, seawater washing was employed as RM modification methods, and it could decrease high rates of pH and improve the sorption capacity of raw RM. The effect of this modification was investigated by simulation of solvent in adsorption environment of sulfate on RM and the dielectric constant selection. For water as the primary solvent with a dielectric constant of 78.54, adsorption energy for RM was calculated to be -35.68 kcal/mol and it was increased to -56.69 kcal/mol for the seawater medium with a dielectric constant of 86. Therefore, RM can be considered as a potential sulfate adsorbent because of cost-effectiveness and alkaline pH that can lead to the neutralization of AMD.
Environment
Hosein Esmaeili; Mohammad Ali Afshar Kazemi; Reza Radfar; Nazanin Pilevari
Abstract
This study introduces a Hybrid Markov–Bayesian Framework for predicting and managing accident risks in high-risk industries, with a specific focus on the mining sector. The framework integrates Markov models to analyze dynamic risk transitions and Bayesian networks to infer causal relationships ...
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This study introduces a Hybrid Markov–Bayesian Framework for predicting and managing accident risks in high-risk industries, with a specific focus on the mining sector. The framework integrates Markov models to analyze dynamic risk transitions and Bayesian networks to infer causal relationships among key human and environmental factors. Drawing from a comprehensive dataset of mining operations, the framework evaluates variables such as age, experience, task type, and injury characteristics to predict and control accident risks. The results highlight the model's high performance, achieving an accuracy of 87%, precision of 85%, and an F1-score of 0.84. This innovative approach enables real-time safety interventions and proactive risk management strategies. The findings underscore the framework's potential to improve workplace safety and serve as a scalable tool for accident prevention in other high-risk industries. Future research will focus on enhancing the framework’s adaptability and incorporating additional contextual variables for broader applicability.
Environment
Reyhaneh Khashtabeh; Morteza Akbari; Ava Heidari; Ali Asghar Najafpour; Rokhsareh Khashtabeh
Abstract
The Heavy Metal (HM) contamination in surface soils poses significant environmental and health concerns near the mining operations. This study examined the concentrations and health risks of the five HMs lead (Pb), nickel (Ni), copper (Cu), arsenic (As), and iron (Fe) in soils surrounding the Sangan ...
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The Heavy Metal (HM) contamination in surface soils poses significant environmental and health concerns near the mining operations. This study examined the concentrations and health risks of the five HMs lead (Pb), nickel (Ni), copper (Cu), arsenic (As), and iron (Fe) in soils surrounding the Sangan iron ore mines in eastern Iran. Sixty soil samples were collected at depths of 0-20 cm from sites adjacent to the mining area and one control site. The HM concentrations were compared to the global shale values. Soil contamination was quantified using the geo-accumulation index (Igeo). Health risks to the local residents were assessed using the US Environmental Protection Agency's Human Health Risk Evaluation Index. The analysis revealed that the lead concentrations near the mine exceeded the global shale standards, while the arsenic levels remained marginally below permissible limits established by global soil standards. The Igeo values indicated low to moderate the contamination levels for both Pb and As in the mining-adjacent areas. The risk assessment results showed that non-carcinogenic risk indices were within acceptable limits for both children and adults. However, arsenic posed a significant carcinogenic risk to adults through two exposure pathways: ingestion (3.36E-04) and dermal absorption (1.36E-04). These findings highlight the importance of implementing regular monitoring protocols for potentially hazardous elements in the mining region to prevent and mitigate pollution-related health risks.
Environment
Zakirah Raihani Ya’la; Triyani Dewi; Ali Husni; Tri Joko Santoso; Samliok Ndobe; Eka Rosyida; Maemunah Maemunah; Marhawati Mappatoba; Muhammad Saleh Nurdin
Abstract
This study was conducted to determine heavy metal concentrations in sediments, assess the level of contamination using a contamination index, and identify potential sources of heavy metal contamination using multivariate analysis. This study employed contamination indices to evaluate sediment pollution ...
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This study was conducted to determine heavy metal concentrations in sediments, assess the level of contamination using a contamination index, and identify potential sources of heavy metal contamination using multivariate analysis. This study employed contamination indices to evaluate sediment pollution levels. Heavy metal concentrations were analyzed statistically by determining the minimum, maximum, mean, and standard deviation (SD) values. According to the contamination factor (Cf), Cd showed very high contamination levels, whereas Sn, Ni, and Pb indicated moderate contamination. Hg, As, Cr, and Cu were classified as having low levels of contamination. The degree of contamination (Cdeg) ranged from low to high across the sampled sites, reflecting the varied levels of pollution severity. Multivariate statistical analyses, including Principal Component Analysis (PCA), Pearson correlation matrix, and Cluster Analysis (CA), were used to identify potential sources of heavy metal contamination. Cu, Sn, Ni, Hg, and Cr are attributed to natural geological processes, whereas Pb, Cd, and As are linked to anthropogenic activities, likely originating from the nickel mining industry. In conclusion, this study underscores the complex environmental impact of nickel mining in Morowali, highlighting the need for stringent environmental management practices to mitigate further degradation and safeguard the coastal ecosystems in Central Sulawesi.
Environment
Lateef Bankole Adamolekun; Taiwo Blessing Olamide; Muyideen Alade Saliu; Esma Kahraman; Victor Afolabi Jebutu; Yewuhalashet Fissha; Adams Abiodun Akinlabi
Abstract
Examining the applicability of laterite clay for landfill and other engineering applications is critical due to the daily challenges that practitioners face as a result of material property variation. The suitability of seven selected laterite deposits in southwestern Nigeria as usable liner material ...
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Examining the applicability of laterite clay for landfill and other engineering applications is critical due to the daily challenges that practitioners face as a result of material property variation. The suitability of seven selected laterite deposits in southwestern Nigeria as usable liner material in solid waste landfill construction was investigated in this study, taking geotechnical properties and chemical composition into account. Purposive samples were collected and tested in accordance with ASTM standard procedures for analyzing geotechnical properties. X-ray diffraction analysis was used to determine the soil's clay mineral composition. The clay mineral composition of the soil was determined using X-ray diffraction analysis. The geotechnical analysis revealed the following ranges for the samples: gravel particle size percentage (3.7% to 34.0%), fines particle size percentage (17.4% to 71.7%), liquid limit (28.1% to 65.8%), plasticity index (3.95 to 45.53), activity (0.44 to 0.81), coefficient of permeability (6.75 x10-10 m/s to 5.80 x 10-6 m/s), specific gravity (2.639 to 2.768), and maximum dry density (1462 kg/m3 to 2065 kg/m3). X-ray diffraction test revealed that the clay minerals content in the seven location clay deposit varies depending on location. The study revealed that the clay mineralogical composition affects the suitability of the soil as a landfill liner material. Four among the seven clay deposits considered in this study were found suitable as a liner for solid waste landfills as compared with landfill material standard specifications.
Environment
Kushai Caleb Aluwong; Mohd Hazizan bin Mohd Hashim; Suhaina Ishmail
Abstract
In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn ...
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In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn while high total dissolved solids water can cause kidney stones, especially when the hard water content is more than 500ppm. With growing concerns about water quality, there is a need for continuous monitoring of pH and TDS levels in surface and groundwater sources. To address this, a cutting-edge wireless sensor system leveraging on Internet of Things (IoT) technology has been developed. This system incorporates top-notch pH and TDS sensors known for their accuracy, durability, and environmental compatibility. Integrated with microcontrollers featuring wireless communication capabilities, these sensors enable seamless data transmission to a central server through IoT protocols like cellular networks. The collected data is processed and calibrated to ensure reliability and precision. The IoT platform connected to the central server manages device connectivity, data storage, and analysis, making real-time data accessible via user-friendly web or mobile applications with interactive graphs and dashboards. Power-saving features are implemented to optimize battery life in remote and off-grid locations, and weather-resistant enclosures protect the sensor nodes from harsh environmental conditions. By deploying this wireless-based sensor system, users can gain valuable real-time insights into water quality in surface and groundwater monitoring locations.
Environment
Jitendra Pramanik; Singam Jayanthu; Dr Abhaya Kumar Samal
Abstract
The environmental conditions present in underground (UG) mines working site significantly impacts the productivity, efficiency, effectiveness as well as threatened security levels. Consequently, maintaining safety in mineral excavation process requires continuous monitoring of the intricate and perilous ...
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The environmental conditions present in underground (UG) mines working site significantly impacts the productivity, efficiency, effectiveness as well as threatened security levels. Consequently, maintaining safety in mineral excavation process requires continuous monitoring of the intricate and perilous operating conditions within the mining work site. At this juncture of time, in this information age, when all walks of life is undergoing continuous modernization, with today's workplace being no exception, Internet of Things (IoT) technology is playing a key role in acquiring relevant information to support monitoring vital operational man and machine safety parameters such as temperature, pressure, humidity, luminance and noise levels, and miner's location in subterranean mining operations. This study has attempted to exhaustively explore state of current research on the use of IoT in underground mining applications. This paper examines the utilization of IoT applications for monitoring several environmental parameters, including obnoxious mine gases and dust concentrations, temperature, humidity, groundwater levels, and strata behaviour to facilitate ground support activities. This paper attempts exploitation of possible scopes of IoT integration from the implementation perspective to monitor and control the various aspects that contribute towards various types and incidents of mine accidents. This research elucidates the primary obstacles that impede the widespread implementation of IoT-enabled systems in underground mining applications.
Environment
Podicheti Ravi Kiran; Ramchandar Karra
Abstract
Opencast coal mines play a crucial role in meeting the energy demands of a country. However, the operations will result in deterioration of ambient air quality, particularly due to particulate emissions. The dispersion of particulate matter will vary based on the mining parameters and local meteorological ...
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Opencast coal mines play a crucial role in meeting the energy demands of a country. However, the operations will result in deterioration of ambient air quality, particularly due to particulate emissions. The dispersion of particulate matter will vary based on the mining parameters and local meteorological conditions. There is a need to establish a suitable model for predicting the concentration of particulate matter on a regional basis. Though a number of dispersion models exist for prediction of dust concentration due to opencast mining, machine learning offers several advantages over traditional modeling techniques in terms of data driven insights, non-linearity, flexibility, handling complex interactions, anomaly detection, etc. An attempt has been made to assess the dispersion of particulate matter using machine learning techniques by considering the mining and meteorological parameters. Historical data comprising of mine working parameters, meteorological conditions, and particulate matter pertaining to one of the operating opencast coal mines in southern India has been utilized for the study. The data has been analyzed using different machine learning techniques like bagging, random forest, and decision tree. The performance metrics of test data are compared for different models in order to find the best fit model among the three techniques. It is found that for PM10, many of the times bagging technique gave a better accuracy, and for PM2.5, decision tree technique gave a better accuracy. Integration of mine working parameters with meteorological conditions and historical data of particulate matter in developing the model using machine learning techniques has helped in making more accurate predictions.
Environment
Gregory Udie Sikakwe; Samuel Adebayo Ojo; Andrew Aondover Tyopine
Abstract
Potentially harmful elements enter into the environment through mining and agricultural activities, causing water and stream sediment pollution. Ecological risk analysis helps to determine sediment pollution, to recommend remediation measures for human health safety and the survival of aquatic ...
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Potentially harmful elements enter into the environment through mining and agricultural activities, causing water and stream sediment pollution. Ecological risk analysis helps to determine sediment pollution, to recommend remediation measures for human health safety and the survival of aquatic species. The sediments were analysed for acidity and redox potential using a pH-meter and spectrophotometer, respectively. Nickel, cadmium, arsenic, chromium, lead, zinc, and iron were measured using atomic absorption spectrophotometer. The mean value of Cd exceeded the threshold effect limit guideline indicating its adverse effect to water dwelling organisms. Anthropogenic metal input identified cadmium, lead, arsenic, zinc and chromium contamination in locations 3, 6, and 7. Modified risk assessment code, toxic response index and comprehensive ecological risk values exhibited considerable to high ecological risks in locations 3, 6, and 7. The highest comprehensive ecological risk value recorded 653.2 in location 3, showing high ecological risk to water dwelling organisms. Durbin Watson ecological risk value (2.34) is between a critical value of 1.5 < d < 2.5 showing auto correlation of the data. Potentially harmful elements obtained Durbin Watson value of 2.77, which exceeded the range showing lack of auto correlation. Strong correlation of arsenic, lead and zinc showed their affinity and common source of enrichment. Principal component analysis indicated that the sources of the elements were mostly geological weathering, sewage disposal, industrial wastes and agricultural fertilizers. The study integrated recent ecological risk indices with multivariate and regression statistics. This is helpful in interpreting related environmental problems by scientists in other parts of the world.
Environment
Abdollah Yazdi; rahim dabiri; Habib Mollai
Abstract
Geosites and their contents including minerals, fossils, etc. can strongly represent the history of a region. They greatly help our understanding of the evolution of Earth, volcanic activities, plate tectonics, and the characteristics of different environments. These are some of the vital information ...
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Geosites and their contents including minerals, fossils, etc. can strongly represent the history of a region. They greatly help our understanding of the evolution of Earth, volcanic activities, plate tectonics, and the characteristics of different environments. These are some of the vital information about 4500 million years of the Earth's life, and are our common international heritage. Geoconservation’s main purpose is the protection of geosites as major units of geoheritage, and this principle is achieved through the application of specific methods such as indexing geological phenomena, assessment, preservation, valuation, and estimating the importance of each geosite, as well as monitoring (or watching these phenomena). In this paper, geoconservation is introduced as a specialized and essential branch of geological science, which is currently under development. Therefore, geoconservation principles are presented here, and their relation to other geosciences is discussed. In addition, through scientific and cultural education related to sustainable development (in regard to the geoscience), citizens can be informed that lack of conserving natural resources would reduce geo-resources, and on the other hand, is a serious threat to geoheritage of the planet Earth. This crucial subject can be achieved by making information available and by teaching skills by which making prospective and correct decisions is possible.
Environment
Şener Ceryan; Pijush Samui; Osman Samed Özkan; Samet Berber; Şule Tüdeş; Hakan Elci; Nurcihan Ceryan
Abstract
Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) ...
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Balikesir province Akcay district (Biga Peninsula, South Marmara Region, Turkey); the studied area is located on the southern branch of the North Anatolian Fault Zone, where some earthquake, 1867 Edremit (Mw =7.0), 1919 Ayvalik-Sarmisakli (Mw = 7.0), 1944 Edremit (Mw =6.4) and 1953 Yenice (Mw = 7.2) earthquakes occurred in the historical and the instrumental period. In the said area, generally, the groundwater level is high and sandy soils are widespread. In this study, therefore topography, depth of groundwater table and soil characteristics of the said area were investigated in terms of susceptibility to liquefaction. In addition, the safety factor against liquefaction (FL) for the soil layers were determined by using simple procedure based on SPT-N values. Then the spatial distributions of the safety factor at 3 m, 6 m, 9 m, 12 m, 15 m and 18 m depths were obtained. Taking into considering FL values obtained, the liquefaction potential index and the liquefaction severity index of soil profile in the location of boring were calculated, then the spatial distributions of these index were obtained. According to the maps obtained, 5.8% of the studied area has low liquefaction potential, 10.7% medium liquefaction potential, 18.3% high liquefaction potential, and 53.8% very high liquefaction potential, and 22.7% of the study area has very low liquefaction severity, 17.1% low liquefaction severity, 47.7% moderate liquefaction severity, and 1.1% high liquefaction severity and 11.4% of the studied area has none-liquefiable soil.
Environment
Sehla Altaf; Kanwarpreet Singh; Abhishek Sharma
Abstract
The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties ...
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The expansion and contraction properties of black cotton soil make it a challenging task to construct structures on it. Hence, modifying its expansion and contraction behavior is imperative to make black cotton soil appropriate for construction purposes. This study aims to assess the geo-technical properties of black cotton soil through laboratory testing, incorporating waste foundry sand (WFS) and sodium chloride (NaCl) to utilize the combination as sub-grade material. Differential free swell, consistency limits, the standard Proctor test, and California bearing ratio (CBR) tests are conducted with varying amounts of both materials. The laboratory testing reveals that the addition of the appropriate amount of waste foundry sand, sodium chloride, or both, improve the geo-technical properties of black cotton soil (BCS). Furthermore, using the CBR values obtained, the thickness of flexible pavement is designed with the IITPAVE software and evaluated against the IRC: 37-2018 recommendations. The software analysis demonstrates a reduction in pavement thickness for varying levels of commercial vehicles per day such as 1000, 2000, and 5000 CVPD across all combinations. This mixture not only addresses the issues related to black cotton soil but also provides an economical solution for soil stabilization and proves to be sustainable as it involves the utilization of waste materials such as waste foundry sand.
