Surface Mining Research Articles

Modeling pH changes and electrical conductivity in surface water as a result of mining activities

Purpose. To develop comprehensive models for predicting the pH and electrical conductivity of surface water in Maiganga coal mine and environs affected by mining activities. Methodology. The research utilizes a combination of in-situ measurement, laboratory analysis, modeling technique using Ansys Workbench and Linear Regression for predicting the content of pollutants. In-situ measurement/data collection in the upstream and downstream were carried out to evaluate the potential impact of mining activities on surface and ground water quality. Electrical conductivity and pH were measured on the samples that were collected using Oakton 5/6 pH meter and TDS/EC meter. Findings. According to the results, the regression statistics model of pH and electrical conductivity (EC) shows that the predicted values have a pH range of 4.7–7.05 and a mean pH value of 5.5. In contrast, while the EC ranges from 454.52 to 2,720.68 s/cm (EC) with a mean value of 905 µs/cm of the downstream flow which is completely dependent on the mine inlet (pH-in and EC-in). The findings show a direct correlation between surface water pH, electrical conductivity, and mining activities in the Maiganga coal mine area and their detrimental effects on the ecosystem and water quality. Originality. The results were obtained directly from the mine site during field visit and can be compared to data from active coal mine sites. Practical value. The detrimental effect of the results of mining activities can be controlled if monitoring sensors are introduced at mines’ effluent outlet to alert the mine management of possible danger in real time.

Bedrock Geologic Database of the Indiana Portions of the Princeton, Evansville, Mount Vernon, and West Frankfort 30- x 60-minute Quadrangles

Located in the eastern Illinois Basin, the Princeton 1:100,000-scale quadrangle comprises portions of Knox, Gibson, Pike, Dubois, Posey, Vanderburgh, Warrick, and Spencer Counties in Indiana as well as small portions of Edwards, Gallatin, Wabash, and White Counties in Illinois. The mapped area is situated in the rolling topography of the Wabash Lowland and dominated by Pennsylvanian-age coal-bearing strata. Pennsylvanian siliciclastics in the Princeton quadrangle host economically important coal seams. The most widespread coal beds occur in the Carbondale Group, but the Raccoon Creek Group hosts coal of superior quality (low sulfur, low ash) in Indiana. Surface and underground mining of these coals have been extensive, with expansive impacts on the landscape and subsequent reclamation. Bedrock outcrops are obscured mainly by glacial sediments and extensive fluvial deposits from the Wabash River that formed deep channels (paleo and active) filled with outwash and alluvium. The geologic map of Gray and others (1970), the Compendium of Paleozoic Rock-Unit Stratigraphy in Indiana (1986), and Indiana Geologic Names Information System (IGNIS, https://legacy.igws.indiana.edu/ignis/) are the fundamental compilation of previous geological knowledge from this area. Additional data come from previous 1:24,000-scale mapping through the National Cooperative Mapping Program STATEMAP component. However, most information for the Bedrock Geologic Database of the Indiana Portions of the Princeton, Evansville, Mount Vernon, and West Frankfort 30- x 60-minute Quadrangles and, more broadly, the western corridor, is derived from Indiana-scale coal seam mapping conducted between 2011 and 2017 based on the National Coal Resources Data System (NCRDS), Indiana Coal Quality Database (ICQD), and geophysical logs from oil and gas wells archived in the Petroleum Database Management System (PDMS). The majority of these data were previously presented in Esri-based Indiana Coal Atlas StoryMaps for the entire western corridor. This geologic mapping project was funded in part through the STATEMAP Program supported by the U.S. Geological Survey under Cooperative Agreement No. G22AC00424. The Bedrock Geologic Database of the Indiana Portions of the Princeton, Evansville, Mount Vernon, and West Frankfort 30- x 60-minute Quadrangles is a composite geodata set that conforms to "GeMS (Geologic Map Schema)--a standard format for the digital publication of geologic maps," available at http://ngmdb.usgs.gov/Info/standards/GeMS/. Metadata records associated with each element within the geodata set contain more detailed descriptions of their purposes, constituent entities, and attributes. An OPEN shapefile version of the data set is also available. It consists of shapefiles, DBF files, and delimited text files and retains all information in the native geodatabase, but some programming will likely be necessary to assemble these components into usable formats.

Using mining waste for CO2 sequestration: exploring opportunities through mineral carbonation, nature-based solutions, and CCUS

ABSTRACT Using mining waste for CO2 sequestration presents a promising solution for managing waste and reducing greenhouse gas emissions. This article provides a comprehensive overview of established CO2 sequestration methods that can be applied to mining waste eligible for such application. Three techniques were considered: 1) passive mineral carbonation; 2) a nature-based solution (NBS); and 3) carbon capture, utilisation, and storage (CCUS). Passive mineral carbonation involves exposing mining waste rich in Ca and Mg silicates to atmospheric CO2. NBS explores the reclamation of disposal areas, estimating the carbon sequestration by topsoil, organic amendments, and revegetation. CCUS presents some storage possibilities with CO2 injection into waste piles and utilisation by incorporating waste and CO2 into cement products. Furthermore, an innovative proposal for injecting CO2 into surface and underground coal mining waste disposal areas was described as a potential action. The strategies presented in this article can be considered to offset CO2 emissions from mining projects while also contributing to waste management and more sustainable production.

Radical hope: re-contextualising oral histories from deindustrialised mining communities

ABSTRACT The anthracite coal mining landscape of northeastern Pennsylvania is in ruin, a by-product of two centuries of unchecked capitalism. Much of the land is stripped of its timber and surface mines lay abandoned. The industry began its decline after WWI and virtually collapsed during the post-WWII era. Waste piles of coal litter the landscape, and the streams and rivers are considered dead because of the minerals and high acid content of water draining from abandoned mines. Many scholars have written about the extreme work conditions the coal workers faced, the demise of the coal industry, and the impact of deindustrialization on the region’s people. Often overlooked is how members of the mining communities had a radical hope. Radical hope helps oppressed people to see that another condition and another world is possible, although not guaranteed. Re-examining oral histories from the anthracite region recorded in the 1970s, when the industry was in its great decline, demonstrates how these mining communities anticipated a future good, understanding the struggle to attain it.

An Integrated Decision Support System for Low-Disturbance Surface Mining

Low-disturbance mining in surface mining (LDM) can transform traditional surface mine production systems into a more sustainable model by reducing the disturbance of surface mining, minimizing pollutant emissions, and reducing ecological impacts. The purpose of this paper is to explore the LDM evaluation method by applying multi-criteria decision-making to provide technical support for LDM implementation. Therefore, an evaluation method based on the combination of the fuzzy analytical hierarchy process (F-AHP) and grey clustering was proposed. Analyzed in terms of the current status of the evaluation indicators (reality) and the significance of the development of the LDM (desirability). Determined the weights and low-disturbance (LD) levels of the evaluation indicators. Combined with the fuzzy technique for order preference by similarity to an ideal solution (F-TOPSIS), the low-disturbance open pit mining paths are ranked, and finally, the decision support system for low-disturbance mining in surface mining is constructed. This study not only enriches the existing literature on related technologies but also lays the foundation for further research on LDM and provides exploratory insights for deeper improvement of LD level in surface mining.

Analysis of the root causes of fatal injuries in the United States surface mines between 2008 and 2021

ABSTRACT Despite significant reductions in fatal injuries in the mining industry, the number of accidents remains unacceptable. Ongoing concern persists regarding mine equipment. This study analyzes the Mine Safety and Health Administration (MSHA) data from 241 final reports of fatal injuries in U.S. surface mines between 2008 and 2021. Predominantly, powered-haulage was the leading source of fatalities; novice miners were particularly vulnerable, and the most significant root cause group was ‘Failure to follow safe work procedures and conditions while performing the task’. Results should heighten hazard awareness for industry professionals, helping them identify and prioritise safety issues in surface mining systems.

Influence of surface mining on seasonal hydrology response to storms across eastern Kentucky, USA

ABSTRACT Mountain Top Removal and Valley Fill (MTR/VF) practices have drastically altered the surface cover, topography and hydrology of many watersheds across the Appalachian region of the US. These practices strip the bedrock from the ridges and peaks of watersheds, before removing the coal seams and depositing the waste fill into adjacent valleys. Existing research has generated conflicting outcomes as to the resulting hydrological impacts in response to storms. This creates potential issues for subsequent mitigation projects seeking to recreate prior hydrological conditions and riparian ecosystems. Our study focused on the potential influence of MTR/VF practices for a series of mined and unmined watersheds across the Eastern Coalfield of Kentucky. We analyzed rainfall-runoff response, focusing on how quickly rainfall was converted to quickflow and how much water left the catchment during storms for the 2022 water year. Lag times were shortened for the mined watersheds while quickflow coefficients reduced when vegetation cover increased. Valley fill-in mined watersheds also appears to create a delayed secondary release of quickflow from headwater locations during more extreme storms. These findings may assist future reclamation/mitigation practices for mined watersheds across Eastern Kentucky aiming to correctly recreate the hydrologic conditions that resemble those of unmined landscapes.

Bayesian network approach for reliability analysis of mining trucks

Having a safe and efficient system for mineral transportation is a top priority for all mining operations. Trucks are the most widely used material transportation systems that are applied in both surface and underground mines. Any truck failure disrupts the mineral transportation process and consequently decreases the overall output. Therefore, the reliability analysis of such equipment plays a critical role in increasing the efficiency and productivity of a mining operation. This paper proposes a novel method for analyzing the reliability of a fleet of mining trucks based on the Bayesian Network modeling. Considering the reliability block diagram, the fault tree of trucks was developed according to the logical relationship between the units. Then, a dynamic Bayesian network was constructed according to the conditional probability analysis. Moreover, the relative contributions of each truck’s component to the occurrence of the fleet failure were studied by using critical analysis. The results of this paper show that the successful operation of the fleet of trucks is most sensitive to truck no. 5, which has the highest reliability level in all time intervals. The reliability of the fleet of trucks reaches 0.881 at 20 h, and the fuel injection system of the truck’s engine is the main leading cause of the trucks failure. A proper preventive maintenance strategy should be paid more attention to improve the reliability and availability of the engine system.

Hypoxaemia and risk of asphyxia during underground work in artisanal cobalt mines.

More than half the cobalt needed for vehicle electrification originates from the southern part of the Democratic Republic of the Congo (DRC), with a substantial part being extracted by artisanal miners. To investigate oxygen saturation during underground work among cobalt artisanal miners. In a field survey, we measured oxygen saturation (SpO2) and heart rate by pulse oximetry in 86 miners from two underground mines and 24 miners from a surface mine at four different time points: before descent into the mine (T1), at 50 minutes in the mine (T2), upon leaving the shaft (T3), and 10 minutes after having left the mine (T4). Miners working underground (-36 to -112 meters) were somewhat older (34.8 ± 6.7 years) than those working in the surface mine (32.0 ± 6.5 years), and they worked more hours daily (12.6 ± 1.2 hours) than controls (9.0 ± 0.0 hours). All participants had SpO2 >95% at T1 and T4. At T2, SpO2 dropped below 93% and 80% in 35% and 10% underground miners, respectively; SpO2 was still <93% at T3 in 13%. SpO2 remained stable among surface miners. Later, we showed that underground ambient oxygen levels decreased well below 21% in several pits. Pulse oximetry revealed relevant hypoxaemia during underground work in a substantial proportion of artisanal miners. Such hypoxaemia without evidence of underlying cardiovascular disease is indicative of low ambient oxygen, due to insufficient mine ventilation. This may cause deaths from asphyxia. The hazards of low ambient oxygen in artisanal mines must be prevented by appropriate technical measures ensuring the supply of sufficient fresh air.

Reliability of LoRaWAN Communications in Mining Environments: A Survey on Challenges and Design Requirements

While a robust and reliable communication network for monitoring the mining environment in a timely manner to take care of people, the planet Earth and profits is key, the mining environment is very challenging in terms of achieving reliable wireless transmission. This survey therefore investigates the reliability of LoRaWAN communication in the mining environment, identifying the challenges and design requirements. Bearing in mind that LoRaWAN is an IoT communication technology that has not yet been fully deployed in mining, the survey incorporates an investigation of LoRaWAN and other mining IoT communication technologies to determine their records of reliability, strengths and weaknesses and applications in mining. This aspect of the survey gives insight into the requirements of future mining IoT communication technologies and where LoRaWAN can be deployed in both underground and surface mining. Specific questions that the survey addresses are: (1) What is the record of reliability of LoRaWAN in mining environments? (2) What contributions have been made with regard to LoRa/LoRaWAN communication in general towards improving reliability? (3) What are the challenges and design requirements of LoRaWAN reliability in mining environments? (4) What research opportunities exist for achieving LoRaWAN communication in mining environments? In addition to recommending open research opportunities, the lessons learnt from the survey are also outlined.

Flyrock in surface mining Part II - Causes, sources, and mechanisms of rock projection

The fracturing and movement of rock that occurs in the vicinity of a stemmed borehole charge in open pit mining operations are described by examining the effects of the emitted stress waves - shock and elastic - and the expansion of high-pressure detonation product gases. Three principal modes of momentum transfer to fractured rock are identified, all linked to gas expansion work. This work can be delivered radially (burden), axially (stemming), and in the collar zone (cratering). Flyrock is generated under unusual combinations of blast parameters and rock properties. Although infrequent and seldom predictable, the generation of flyrock can nonetheless be interpreted and modelled in terms of the principal mechanisms of rock projection described in this study. The physical processes underlying these principal mechanisms are identified and will permit the development of predictive models for flyrock velocities.

Long-term land cover changes assessment in the Jiului Valley mining basin in Romania

Introduction: Highlighting and assessing land cover changes in a heterogeneous landscape, such as those with surface mining activities, allows for understanding the dynamics and status of the analyzed area. This paper focuses on the long-term land cover changes in the Jiului Valley, the largest mining basin in Romania, using Landsat temporal image series from 1988 to 2017.Methods: The images were classified using the supervised Support Vector Machine (SVM) algorithm incorporating four kernel functions and two common algorithms (Maximum Likelihood Classification - MLC) and (Minimum Distance - MD). Seven major land cover classes have been identified: forest, pasture, agricultural land, built-up areas, mined areas, dump sites, and water bodies. The accuracy of every classification algorithm was evaluated through independent validation, and the differences in accuracy were subsequently analyzed. Using the best-performing SVM-RBF algorithm, classified maps of the study area were developed and used for assessing land cover changes by post-classification comparison (PCC).Results and discussions: All three algorithms displayed an overall accuracy, ranging from 76.56% to 90.68%. The SVM algorithms outperformed MLC by 4.87%–8.80% and MD by 6.82%–10.67%. During the studied period, changes occurred within analyzed classes, both directly and indirectly: forest, built-up areas, mined areas, and water bodies experienced increases, whereas pasture, agricultural land, and dump areas saw declines. The most notable changes between 1988 and 2017 were observed in built-up and dump areas: the built-up areas increased by 110.7%, while the dump sites decreased by 53.0%. The mined class showed an average growth of 6.5%. By highlighting and mapping long-term land cover changes in this area, along with their underlying causes, it became possible to analyze the impact of land management and usage on sustainable development and conservation effort over time.

Distribution of Soil Chemical Properties of Smallholder Farms on Derelict Mined-Sites of Jos South LGA, Jos Plateau, Nigeria

Tin mining environments have constituted a degrading challenge to smallholder farmers whose lands have been overtaken. Attempts by smallholder farmers to restore the lands to farming are faced with soil productivity constraints. Yet, these farmers struggle to cultivate farms in-between the mined lands to meet up with subsistence food requirements. To date, the farmers have identified areas with low and high potentials due to years of continuous cultivation. This study was conducted in an environment that had undergone mining on a larger scale and is now undergoing surface mining on a small scale. Thirty-one (31) soil samples were taken at a depth of 0-20cm to investigate the spread of soil chemical properties on smallholder farms. Coordinates of the samples were acquired using GPS to create georeferenced continuous surfaces. The results indicated that the majority of the soil's chemical properties varied moderately. Organic matter (0.89-1.74%) and nitrogen (0.045 - 0.096%) needed mostly by crops were very low due to uninformed distribution of soil chemical properties. Geostatistics was used to generate continuous surfaces through Kriging. The small nugget effect showed spatial continuity between the neighboring points. Strong spatial dependence occurred for all soil nutrients tested, due to intrinsic soil properties such as soil parent material, topography, texture, and mineralogy. Generally, the spread of soil nutrients on the smallholder farm coincides with the smallholder farmers' identified potential areas. The study suggests that for proper nutrient interventions on the farms, distribution of soil nutrients on the farms should be done to avoid excesses and shortages of inorganic and organic interventions.

Identifikasi Unsur Penyusun Sedimen Sungai Klagison Kota Sorong Papua Barat Daya Menggunakan Metode X-Ray Fluorescence (XRF)

The Klagison River is one of the rivers in Sorong City, West Papua. Surface mining activities occur in the Klagison River drainage area which is one of the causes of changes in the geomorphological conditions of the Klagison River. to identify the constituent elements of the Klagison River sediment using X-Ray Fluorescence (XRF). Determination of sampling points using the purposive sampling method and sediment collection tools using the Ekman grab. The method for analyzing sediment constituent elements uses the XRF (X-Ray Fluorescence) method. Based on the research results, there are various types of elements contained in the Klagison River sediment, namely the elements Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Zr and Re. The dominant metal element concentrations from the 5 observation stations are the elements Fe&gt;Si&gt;Cl&gt;Al&gt;Ca&gt;Ti. At observation station 5, the elements Fe&gt;Si&gt;Cl&gt;Al&gt;Ca&gt;Ti are highest compared to the other 4 observation stations, this is because station 5 is the estuary of the Klagison River so it is the last place where liquid waste settles

A review of icing prediction techniques for four typical surfaces in low-temperature natural environments

As a common phenomenon in nature and industrial fields, icing always adversely affects life, and plays negative effects. Although series of anti-/de-icing techniques are widely investigated, icing prediction techniques on surfaces under low-temperature natural environment are more important due to effectively reduce or even prevent icing caused harms. To understand the current research progress of icing prediction techniques, four typical static and moving surfaces that are prone to ice formation were selected as the research objects in this study, including road, transmission line, wind turbine blade and aircraft surfaces. As summarized, prediction methods mainly include physical models, statistical models, and machine learning. For road surface, statistical analysis, theoretical analysis and data mining methods are widely used, with the average prediction accuracy reaching 80%. For wind turbine blade and transmission line surfaces, both model-driven and data-driven methods were used, resulting in average prediction accuracies of 80% and 90%, respectively. For aircraft surface, the method of numerical analysis combined with machine learning is the mainstay, with a deviation of less than 20%. Summary and outlook are finally given, which are beneficial for the optimization of ice prediction technology in different industrial fields.

Legacy coal mining impacts downstream ecosystems for decades in the Canadian Rockies

Mountaintop removal coal mining leaves a legacy of disturbed landscapes and abandoned infrastructure with clear impacts on water resources; however, the intensity and persistence of this water pollution remains poorly characterized. Here we examined the downstream impacts of over a century of coal mining in the Crowsnest Pass (Alberta, Canada). Water samples were collected downstream of two historical coal mines: Tent Mountain and Grassy Mountain. Tent Mountain hosts a partially reclaimed surface mine that closed in 1983. Selenium concentrations downstream of Tent Mountain reached 185 μg/L in a lake below the mine spoil pile, and up to 23 μg/L in Crowsnest Creek, which drains the lake and the mine property. Further downstream, a well-dated sediment core from Crowsnest Lake records increases in sediment, selenium, lead, carbon, nitrogen, and polycyclic aromatic compounds that closely tracked the history of mining at Tent Mountain. In contrast, episodic discharge of mine water from abandoned underground adits at Grassy Mountain drive periodic (but short-term) increases in iron, various metals, and suspended sediment. These results underscore the lasting downstream impacts of abandoned and even reclaimed coal mines.

A new indicator for estimating the degree of mining-induced land subsidence: the overburden’s average GSI value

Underground coal mining leads to land subsidence, which, in turn, results in damage to buildings and infrastructure, disturbs the original ecological environment, and hinders the sustainable development of coal mining cities. A reasonable estimation of land subsidence, on the other hand, is the foundation for building protection, land reclamation, and ecological environment reconstruction. However, when we applied the existing land subsidence estimation theory to the deep mining areas of the Ordos coalfield in western China, there was a significant deviation between the estimations and the measurements. To explain such unusual case, we propose using the overburden’s average GSI (Geological Strength Index) value instead of the compressive strength (UCS) of rock specimens for a better representation of the overburden’s overall properties. By using on-site subsidence monitoring results and historical data, we provided evidence which supports that the overburden’s average GSI value has a much greater impact on subsidence rates than the UCS. Subsequently, we investigated the relationship between three typical overburden’s GSI values and the subsidence rates via a calibrated numerical model, revealing the variation patterns of maximum surface subsidence when the overburden’s average GSI value is set at 30, 50, and 75, respectively. Finally, on the basis of the measured and simulated results, we discussed a non-conventional strip mining method for mining subsidence control in the deep mining areas of the Ordos coalfield in western China, and explained why it is possible and what are the significant advantages behind. The proposed methods, findings, and suggestions in this paper are therefore quite helpful for researchers and engineers who wish to estimate and control the mining-induced land subsidence, as well as for those who are particularly interested in the study of environment science related to land subsidence.

Assessment of the concentration of toxic metals (aluminum, cadmium and manganese) in the soil and evergreen plant species at the Sastavci surface mine and its vicinity

The study aims to determine the concentration of Al+3, Cd+2 and Mn+2 in the soil and parts of evergreen plant species - juniper and white pine - at the surface mine Sastavci (Badanj) and its vicinity in order to determine the possibility of using evergreen plants as an ecological indicator or for phytoremediation. Globally, as a result of various anthropogenic activities such as traffic, agricultural activities, waste incineration, industrial production, mining, etc., it represents a serious problem leading to pollution with toxic and potentially toxic metal cations. One of the more innovative techniques used for the remediation of mining areas is phytoremediation. By applying phytoremediation, certain plant species in polluted areas have the ability to act as accumulators or hyperaccumulators, absorbing toxic metals from the soil through the plant roots and transporting them to the upper parts. This research has been conducted to determine the concentration of Al+3, Cd+2 and Mn+2 at the surface mine itself and its surroundings, as well as to monitor the distribution of metal cations in the system of roots, branches, needles, and fruits of the evergreen plant species - white pine and juniper. The results showed that the sampled soil was contaminated with Cd in zones I and II for both plant species, since the concentrations exceeded the limit values, while the concentration of Cd in zone III as well as in the control zone was below the determination limits for both plant species. The concentration of Mn in the soil from the white pine and juniper zone was above the world average in all three zones, as well as in the control zone itself. The soil was most enriched with the analyzed elements in the surface mine of zone I and zone II. According to the analysis of elements in the parts of white pine, roots, branches, needles and fruits, the highest concentration of Al was detected in the root in zone I, while the lowest concentration was recorded in the fruit (cones) in the control zone, an increased concentration of Cd was recorded in the branches in zones I and II, and the highest concentration of Mn was recorded in needles in zone II. The highest Al concentration was recorded in the juniper root in zone I and the lowest in the juniper fruit in the control zone, the Cd concentration was the highest in the juniper root zone I, and the lowest in the juniper fruit and the highest Mn concentration was recorded in the juniper needles in zone I. Based on the obtained values of the coefficient of biological absorption, it can be concluded that white pine is not suitable for phytoextraction or phytostabilization of the tested elements. The analysis of biological factors (bioconcentration, translocation and bioaccumulation factor) indicated possible usage of juniper in phytoextraction only for Cd.

Pametno rudarstvo

Industry 4.0 has become a global strategic initiative of scientific and technological development, which was launched by the most developed industrial countries in the world, and today has gone the furthest in its implementation. In essence, it is a new model of application of information and communication technology, based primarily on their integration with the object of application (for example in mining - production (BTO), transport, maintenance, etc.). The development and application of the elements of Industry 4.0 in this area leads to the establishment of the smart mining (SM) model, the elements of which will be presented in this paper. As an illustration of the application of this model in our conditions, and for the "Drmno" surface mine, this paper will present a model of planning and maintenance management of ERP (production-technological resource planning) and MES (work order management) model for Industry 4.0 , which uses a private cloud computing model.

PMScenes: A Parallel Mine Dataset for Autonomous Driving in Surface Mines

PMScenes: A Parallel Mine Dataset for Autonomous Driving in Surface Mines