Mining Activities Research Articles

A quantitative framework for measuring sustainable development goals in mining operations

The growing concern over the environmental and social impacts of mining activities has increased interest in evaluating the alignment of mining practices with global sustainability goals. This study provides an in-depth examination of five major Iranian mining complexes including: GolGohar, Sarcheshmeh, Sungun, Zarshuran, and Sangan, and their adherence to the Sustainable Development Goals (SDGs), which encompass a broad spectrum of environmental, social, and economic challenges. The study employs a novel methodology to quantify and assess the degree of alignment between these mining complexes and the SDGs. The SDGs were systematically categorized into three key areas: environmental sustainability, social and economic well-being, and responsible operations and partnerships. The performance of each mining complex within these categories was evaluated using targeted questions and a set of indicators, providing a holistic view of both strengths and areas needing improvement. The findings revealed significant challenges in environmental sustainability, particularly in climate action and clean energy, with Sungun achieving the highest scores and Zarshuran the lowest. In social and economic well-being, progress was evident in poverty reduction and education, though concerns persisted in gender equality and healthcare access, where GolGohar led and Zarshuran lagged behind. Responsible operations and partnerships showed successes in industry innovation, yet there was a need for greater focus on sustainable urban development and partnerships. Zarshuran excelled in this area, while Sungun exhibited the weakest performance. Overall, the study highlights the need for substantial improvements in environmental practices and social inclusion across all complexes, including the top-performing GolGohar, to better align the mining sector with the SDGs and foster a more responsible and inclusive industry.

Empowering Communities to Reduce Dependence on Unlicensed Mining and Minimize Corporate Losses: A Case Study of PTBA in December 2023

This study aims to analyze the impact of community empowerment programs on reducing dependence on unlicensed mining and to measure the potential losses incurred by PTBA due to these activities. The time sample used in this research is December 2023. A quantitative approach is used to calculate the income earned by the community from six empowerment programs, including bamboo downstream processing, snakehead fish farming, reclamation plant cultivation, maggot farming, quail farming, and eel farming. The total income generated by these programs for 93 beneficiaries reached USD 13,238.22 per month, with an average income per program ranging from USD 153.70 to USD 244.39, which remains below the regional minimum wage (UMR) of Muara Enim Regency, set at USD 233 per month. This income is compared to assess how competitive the alternative livelihoods provided by the empowerment programs are. In addition, this study calculates PTBA’s losses from unlicensed mining in the same month, based on the extraction of 0.175 million tons of coal, the market price of USD 58.28 per ton, and the lost royalties of 8%. The total financial loss reached USD 10.2 million, with USD 815,920 in lost royalties. The analysis underscores the importance of expanding and strengthening community empowerment programs to further reduce unlicensed mining activities, while also mitigating the financial and environmental impacts on the company.

Evaluation of Germination and Early Seedling Growth of Different Grasses Irrigated with Treated Mine Water

Coal mining is known to have negative impacts on the environment, necessitating land rehabilitation after mining activities. Amongst the problems associated with coal mining is the accumulation of acid mine drainage characterized by large amounts of heavy metals and high acidity. The impact of these environmental problems on the ecosystem around mining areas underscores a need to devise strategies that will ensure sustainable restoration of the ecosystem integrity to ensure environmental protection. Of these, treatment of acid mine drainage using calcium sulfate dihydrate, which is subsequently used for irrigation during phytoremediation, holds great promise for restoration of open-cast mines. However, although grasses are used for rehabilitation of coal mined areas, the impacts of treated mine water on the germination, seedling emergence, and plant growth of grasses are not well known. The aim of the study was to evaluate the germination and early seedling growth responses of different forage grasses to treated mine water. Seven forage grass species were selected, with four species represented by two varieties while others were represented by one variety, totaling 11 forage grasses. For each plant entry, 100 seeds were placed in J.R. Petri’s dishes lined with Whatman No. 2 filter paper and watered with distilled and mine water to assess germination. For the seedling establishment experiment, only five species were studied, in which twenty seeds per species were sown in pots containing mine soil and irrigated using distilled and treated mine water. The final germination percentage (FGP), germination rate index (GRI), corrected germination rate index (CGRI), and T50 were determined for the germination trail and total biomass was assessed for the seedling growth trail. The highest FGP for all grasses was attained under controlled conditions, using distilled water, ranging from 38–94%. All grasses germinated when watered using treated mine water and had a FGP ranging from 20–91%. Relative to distilled water, GRI and CGRI were highest only for L. multiflorum cv AgriBoost when seeds were watered using the treated mine water. All grasses watered with treated mine water produced high biomass for the first two weeks, after which biomass production started to decline. Two grasses, Eragrostis curvula cv Ermelo and Lolium multiflorum cv Archie, showed tolerance to treated mine water irrespective of its high electrical conductivity (557 mS∙m−1). Therefore, these grasses could be used in the rehabilitation of coal-mined areas irrigated with treated mine water.

Ecological risk assessment of heavy metals contaminated mining sites of eastern india using soil and moss.

The blooming industrialization and urbanization is leading to increased mining operations. These intensified mining activities emit heavy metals into the environment, posing serious threats to ecosystems. Hence, this study focused on assessing heavy metal pollution in mining soil, utilizing mosses as bioindicators. The ecological risk, geo-accumulation factor, and contamination factor have been calculated to know the harmful effect of heavy metals on ecosystem. The study covered three distinct mining sites of eastern India within Odisha: Jajpur's Sukinda Valley (SP1, Cr), Keonjhar's Joda-Barbil (SP2, Fe and Mn), and Sundargarh's Koira-Joda (SP3, Fe). The collection of 48 soil samples through random sampling revealed significant variations in heavy metal concentrations. SP1 recorded Cr concentration of 6572 ± 445mg/kg and Ni of 8042.47 ± 501.38mg/kg, surpassing eco-toxicological levels. The storage site in SP2 exhibited the highest Fe concentration at 9872 ± 502mg/kg, and Mn levels in SP3 were at 7884 ± 432mg/kg. Storage areas in all three regions held the highest concentrations of heavy metals. Mosses in studied area demonstrated as potential bioindicators for monitoring heavy metal pollution. EF and Igeo assessments showed Cd, Pb, Hg, and other heavy metal contamination compared to earlier investigations. This study indicated higher ecological risks for Pb, As, Cu, Ni, and Zn. The Hyophila involuta accumulates Mn, Cr, Cd, Pb, Fe, and Hg, while Barbula arcuata accumulates Mn, As, and Cu in SP1. Hyophila involuta and Trematodon longicollis accumulate Mn, Cr, Cd, Pb, Fe, Hg, and Zn in SP2. Trematodon ambiguous accumulates Cd, Fe, and Ni, while Fissidens diversifolius accumulates Mn, Cr, Hg, As, Cu, and Zn in SP3. These findings emphasize the necessity of monitoring heavy metal pollution in contaminated zones using moss as a potential bioindicator.

Machine learning-assisted risk evaluation of heavy metals in the Hainan gold mining region, China.

This study employed machine learning (ML) to thoroughly investigate the impact of informal mining activities on the distribution and pollution status of heavy metals in soils near private gold mines in Hainan Province, southern China, a region known for its ecological sensitivity and economic importance. By systematically collecting surface soil samples and samples at depths of 0.5-1m from 175 drilling sites, a comprehensive quantitative analysis was conducted on major heavy metal elements, including lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), and zinc (Zn). Combined with evaluation methods such as the Pollution Load Index (PLI), Normalized Pollution Index (NIPI), and Ecological Risk Index (ERI), the study revealed a high level of soil pollution at informal mining sites. The findings indicated that the average concentrations of Pb, Cd, Hg, As, and Zn in surface soils significantly exceeded the background values for soils in China, with a pronounced positive correlation observed between these heavy metal elements in both surface and deep soil profiles (r > 0.5). Furthermore, leveraging the heavy metal content in surface soils and the constructed environmental indicators, the predictive accuracy for metal content in deep soils was found to range from R2 = 0.27 to 0.68, suggesting that informal mining activities have led to substantial variations in metal content across different soil profiles. Through the application of a random forest model for predictive analysis of the PLI, NIPI, and ERI, high prediction accuracy was achieved (R2 = 0.78, 0.86, and 0.60, respectively). The study demonstrates that informal mining activities not only elevate the risk of soil pollution but also alter the distribution patterns of heavy metals. Also, this study provides a crucial foundation for the scientific assessment of soil quality and potential environmental hazards, while also affirming the efficacy of ML techniques in forecasting soil quality parameters.

Prevalence and risk of occurrence of visible birth defects in mining areas in South Kivu: A hospital-based cross-sectional study.

Possible contamination related to mining activities might contribute with other risk factors in increasing the burden of birth defects (BDs) in many developing countries including the Democratic Republic of Congo. The subsequent prevalence is frequently underestimated. Implementation of focused public health interventions is hindered by the paucity of comprehensive data. We assessed the potential impact of mining on the prevalence and occurrence of visible BDs in neonates in South Kivu (SK). A hospital-based cross-sectional study was conducted among 65,474 newborns registered in 7 hospitals in SK from 2016-2021. Hospitals were categorized based on mining activities in their respective catchment areas. Living in a mining zone was the exposure, whereas the outcome was visible BDs. Prevalence was estimated per 100,000 live births, and risk of occurrence with odds ratio (OR) and their 95% confidence interval. 261 neonates with visible BDs were recorded accounting for a prevalence of 399 cases per 100,000 live births. The prevalence ranges between 217 and 1365 cases per 100,000 live births. An increased risk was found in mining zones(OR=2.07; 95%CI=1.59-2.68), Mubumbano(OR=1.72, 95%CI=1.22-2.43), and Mwenga(OR=3.89, 95%CI=2.73-5.54), whereas a reduced risk was reported in non-mining zones(OR=0.48, 95%CI=0.37-0.62) in Katana (OR=0.49, 95%CI=0.33-0.73). Musculoskeletal(28.74%) and central nervous systems(19.92%) were the most common BDs. A significant difference in prevalence for BDs involving the face, GI system and abdominal wall, musculoskeletal, central nervous and genitourinary systems between mining and non-mining zones was found(p<0.001). There is an excessive risk for visible BDs in areas with hazardous mining activities in SK region.​​ More complex studies are needed to define the possible causal relationship. Moreover, findings generated herein should be corroborated by other research design, periodically monitored by public health authorities, and used to inform initiatives promoting enhanced environmental health, access to pediatric surgical care, and public health campaigns aimed at decreasing risk of BDs.

Hydrochemical characterization and health risk assessment of shallow groundwater in a northern coalfield of Anhui Province, China

In a global context, the hydrochemical characteristics of shallow groundwater in coalfields exhibit high degrees of diversity and complexity that are rooted in the intricate interplay of geological variations, diverse climatic conditions, and extensive human activities. The specific types and concentrations of ions, such as Ca2+, Cl−, and NO3−, show stark differences across geographical regions. Given the crucial roles of coalfields as energy suppliers, the potential environmental contamination risks posed by mining activities to groundwater cannot be overlooked as such pollution directly impacts human health and ecological safety. This study focuses on the Huainan coal mining area in northern Anhui Province (China), where shallow groundwater samples were systematically collected and analyzed to determine the hydrochemical characteristics and ascertain the water quality status. By integrating hydrogeochemical analysis techniques with inverse modeling methods, it was revealed that the groundwater in this region is predominantly HCO3-Ca type, exhibiting weak alkaline characteristics. The formation mechanisms are primarily governed by silicate rock weathering and mineral dissolution–precipitation processes, albeit with discernible influences from human activities. PHREEQC simulations were used to further confirm the precipitation tendencies of minerals like calcite, dolomite, and fluorite as well as the significant dissolution characteristics of halite. The inverse modeling pathway analysis reveals specific hydrochemical processes along different paths: paths I and IV are notably dominated by Ca2+ dissolution–precipitation and cation exchange–adsorption processes, whereas paths II and III are closely associated with the precipitation of calcium montmorillonite as well as dissolution of kaolinite, calcite, quartz, and mineral incongruents. Moreover, evaluations based on the entropy-weighted water quality index (EWQI) indicated overall positive trends of the groundwater quality indicators within the Huainan mining area, reflecting the effectiveness of regional water quality management efforts and providing a scientific basis for future water quality protection and improvement strategies. In summary, this study not only deepens our understanding of the groundwater chemistry in the Huainan coal mining area but also underscores the importance of scientifically assessing and managing groundwater resources to address the environmental challenges potentially arising from coal mining activities.

Study on failure mechanism of cracked coal rock and law of gas migration

China possesses abundant coal resources and has extensive potential for exploitation. Nevertheless, the coal rock exhibits low strength, and the coal seam fractures due to mining activities, leading to an increased rate of gas emission from the coal seam. This poses significant obstacles to the exploration and development of the coal seam. This paper focuses on studying the failure mechanism of fractured coal rock by conducting uniaxial and triaxial compression experiments on the coal rock found at the Wangpo coal mine site. Simultaneously, in conjunction with the findings from the field experiment, a gas migration model of the mining fracture field is constructed to elucidate the pattern of coal seam gas distribution during mining-induced disturbances. The study structure reveals that coal rock exhibits three distinct failure modes: tensile failure, shear failure, and tension-shear failure. The intricate fissure in the rock layer will intensify the unpredictability of rock collapse patterns. The compressive strength of coal rock diminishes as the confining pressure drops. The coal rock in the working face area will collapse as a result of the lack of confining pressure. In the rock strata above the mining fracture zone, the gas pressure is first higher and then significantly falls with time. After 100 days of ventilation, the low gas pressure area changes little, so to ensure the safety of the project, the ventilation time of the fully mechanized mining surface is at least 100 days. The research results will help to establish the core technology system of coal seam development and improve the competitiveness of coal seam resources in China.

Ground subsidence prediction with high precision: a novel spatiotemporal prediction model with Interferometric Synthetic Aperture Radar technology

ABSTRACT As the extraction of mineral resources intensifies, ground subsidence in mining areas has escalated, posing substantial challenges to sustainable development and operational safety. This subsidence, resulting directly from mining activities, significantly compromises the safety of nearby residents by damaging residential structures and infrastructure. Thus, developing precise and dependable methods for predicting ground subsidence is crucial. This study introduces an innovative Cabs-Unet model, which enhances the U-Net architecture by integrating a Convolutional Block Attention Module (CBAM) and Depthwise Separable Convolutions (DSC). This model aims to predict the spatiotemporal dynamics of the Interferometric Synthetic Aperture Radar (InSAR) time series. Employing Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) technology, we gathered and validated data on ground subsidence at the Pengzhuang coal mine from May 2017 to November 2021, covering 130 scenes, with its accuracy corroborated by levelling survey results. An empirical evaluation of the Cabs-Unet model in two distinct subsidence zones demonstrated superior performance over conventional methods like Convolutional Long Short-Term Memory (ConvLSTM) and Predictive Recurrent Neural Network (PredRNN), with Root Mean Square Error (RMSE) values of 1.44 and 1.70, respectively. These findings highlight the model’s efficacy in accurately predicting spatiotemporal InSAR ground subsidence. Further predictive analysis using InSAR data indicated an expected increase in subsidence, projecting cumulative declines of −457 mm in Area A and −1278 mm in Area B by 17 July 2022. Our model proves effective in assessing subsidence, promptly detecting potential risks and facilitating the rapid implementation of risk mitigation strategies.

Geochemical fractionation of trace elements in ostreid and gastropod shells: A potential proxy for heavy metal pollution in Ghana’s coastal environment

The content of trace elements from Crassostrea tulipa (Ostreidae, Bivalvia) from four localities (Pra Estuary, Densu Estuary, Kpone Beach, and Anyanui Creek) along the coast of Ghana has been used as a bioindicator of environmental pollution. The lowest values of heavy metals correspond to the Crassostrea shells from Densu Estuary and Anyanui Creek, whereas the highest contents are recorded in the shells from Pra Estuary and Kpone Beach. Densu Estuary and Anyanui Creek are located in areas not affected by major industries, and only Densu is located in a densely urbanized setting. Crassostrea shells from Densu Estuary are only enriched in Ni. However, the Total Organic Carbon content of the sediments of the Densu Estuary indicates anthropogenic organic pollution not evidenced by the composition of Crassostrea shells. The Crassostrea shells from the Pra Estuary show enrichment in most of the analysed trace elements (Li, Be, V, Cu, Cr, Zn, Ga, Y, Sn, Pb, U, Th, ∑REE, and As) compared with other studied sites. This enrichment is related to heavy metals influx to the Pra River by the mining activities, extensive forest clearance, and loss of soil minerals. The Crassostrea shells from Kpone Beach present comparatively high content of some trace elements (Be, Ba, Cu, Zn, Nb, Pb, and REE). The metal pollutants are related to the input of the Heavy Industrial Area of Tema (located around 3.5 km west of Kpone Beach) and urban effluences from the Greater Accra Region. The high content of Ba, Cu, Zn, and Pb in Crassostrea is directly related to high phytoplankton productivity (mainly for diatoms) linked to the input of trace metals transferred into the marine food webs. In addition, some analyses of gastropod shells from Kpone Beach indicate that Cerithium and Nerita are more sensitive to accumulating Ni and As than Crassostrea. The values of trace metals from the Crassostrea shells of the Densu Estuary and Anyanui Creek are comparatively low. Considering the role of Crassostrea shells as bioindicators for heavy metals pollution, the less polluted localities are Anyanui Creek and Densu Estuary, whereas Pra Estuary and Kpone Beach are affected by anthropic activities such as mining, urban effluents, and industry.

Assessment of the relationship between mineral extraction in the southern hemisphere and sustainable development

Sustainable mineral policies are needed to achieve environmental and social equity in the global South. This study explores the need to align mineral mining in the global South with the United Nations Sustainable Development Goals (SDGs). It studies the impact of mineral mining on sustainability in 29 global South economies from 2000 to 2021. It also conducts robustness analysis and heterogeneity tests to analyze the mediation effect and the impact of the release of SDGs on sustainability. The main conclusions are as follows: (1) Mineral mining has an inhibitory effect on sustainable development and has become a constraint for the achievement of sustainable development goals in the global South; (2) The more mineral-rich a country is, the more serious the adverse impact of mining activities is. The harm of mineral mining to sustainable development is most serious in Africa; (3) Mineral mining leads to an increase in ecological footprint and undermines environmental sustainability, while mineral rents may become a source of funds for clean production, offsetting the adverse effects of mineral mining; (4) The release of SDGs has prompted leaders of various countries to legislate and reform in the field of minerals, helping countries achieve sustainable development goals. The research results provide an effective reference for promoting environmental and social sustainable development in the global South.

Evaluating Swarm Robotics for Mining Environments: Insights into Model Performance and Application

The mining industry is experiencing a transformative shift with the integration of automation, particularly through autonomous haul truck systems, and further advancements are anticipated with the application of swarm robotics. This study evaluates the performance of four swarm robot models, namely baseline, ant, firefly, and honeybee, in optimizing key mining operations such as ore detection, extraction, and transportation. Simulations replicating real-world mining environments were conducted to assess improvements in operational efficiency, scalability, reliability, selectivity, and energy consumption. The results demonstrate that these models can significantly enhance the precision and productivity of mining activities, especially in complex and dynamic settings. A case study of the Pilbara iron ore mine in Australia is presented to illustrate the practical applicability of these models in an actual mining context. The study also highlights specific enhancements in each model, including role specialization in the ant model, advanced communication in the firefly model, and improved localization combined with hybrid control in the honeybee model. While the honeybee model showed superior performance in high-precision tasks, its reliability was limited under high-error conditions, and it faced a computational resources bottleneck in large-scale operations, highlighting the need for further development. By evaluating these models against performance criteria, the study identifies the most suitable swarm models for various mining conditions, offering insights into achieving more sustainable, scalable, and efficient mining operations.

Leveraging machine learning and Landsat time series for high-resolution mapping of mining-induced vegetation changes in Ouagadougou, Burkina Faso

Quarries are open pit mines, where construction materials such as granite and clay are extracted from the earth's surface, leading to a major disturbance of vegetation and subsequent degradation of ecosystem services. Assessing mining-associated degradation over time remains a challenge. This paper uses a temporal series of Landsat satellite image extracted from Google Earth Engine (GEE) for monitoring mining effects on land cover around the West African city of Ouagadougou, Burkina Faso. We conducted a binary classification of quarry and non-quarry using Landsat 9 images. To account for varying quarry patterns, we applied the LandTrendr algorithm to analyze images from 1990 to 2022, mapping annual vegetation disturbance and recovery. This generated high-resolution land cover maps with over 90 % accuracy across 257 quarries (38 km²). LandTrendr identified disturbance years with 87 % accuracy and assessed recovery in abandoned quarries. Remote sensing accuracy was validated through fieldwork and analysis of historical aerial photos. Our findings revealed that major disturbances coincided with new quarrying activities, particularly during urban expansion from 2005 to 2019, with NDVI decreasing by 0.3 in active mining areas. Vegetation recovery was observed in 23 % of the abandoned quarries, with NDVI increases by 0.15 within five years post abandonment, particularly in clay quarries. The strongest recovery occurred in given up abandoned from 2015 to 2019, aligned with increased conservation efforts. Our approach offers valuable insights into mining impacts and vegetation resilience in semi-arid environments, informing sustainable urban planning and environmental management in rapidly transforming regions of West Africa.

Cadmium Distribution and Bioavailability in Paddy Soil Profiles from Regions Impacted by High Geochemical Background and Mining Activities, &amp;lt;?A3B2 pi6?&amp;gt;Southwestern China

Cadmium Distribution and Bioavailability in Paddy Soil Profiles from Regions Impacted by High Geochemical Background and Mining Activities, &amp;lt;?A3B2 pi6?&amp;gt;Southwestern China

Exploring acid mine drainage treatment through adsorption: a bibliometric analysis.

Discharge of acidic wastewater from mining activities (acid mine drainage (AMD)) is a major global environmental and public health issue. Although several approaches, including chemical precipitation and membrane technology, have been developed to treat AMD, adsorption has emerged as the most promising technology due to its cost-effectiveness and efficacy. Despite the wide adoption of adsorption in treating AMD, the evolution of research in this area remains poorly understood. To address this gap, a bibliometric analysis of the most recent literature involving the application of adsorption in AMD remediation was conducted by merging datasets of articles from Scopus (1127) and the Web of Science Core Collection (1422), over the past decade (2013-2022). This analysis revealed a yearly increase of 11% in research publications, primarily contributed by China, the United States, and South Africa. Keyword analysis revealed that natural schwertmannites and their transformations, activated carbon, zeolites, and clay minerals, are the most extensively employed adsorbents for the removal of common metals (arsenic, chromium, iron, manganese, among others). The findings underscore the need for future focuses on recovering rare earth elements, using nanoparticles and modified materials, pursuing low-cost, sustainable solutions, integrating hybrid technologies, pilot-scale studies, exploring circular economic applications of AMD sludges, and inter-continental collaborations. These insights hold significant future implications, serving as a valuable reference to stakeholders in the mining industry.

Lead (Pb) removal from gold mining-impacted water utilizing palm oil fuel ash (POFA)

Mining, particularly gold mining, is a lucrative industry. However, it poses significant environmental risks, such as releasing heavy metal elements into the soil and water. After gold mines are exhausted, whether they are small or large scale, the excavated sites often need to be repaired. This situation has led to a global concern regarding the presence of heavy metals from mining activities, which are known to be carcinogenic and harmful to living organisms. The concentration of heavy metals in these areas often surpasses safety limits, necessitating advanced treatment methods for their removal, especially lead (Pb) compounds from gold mining waste. One effective treatment method is the adsorption process. This study examined POFA's inherent capacity to remove lead from water contaminated by gold mining without modification. This method was preferred due to its high efficiency and cost-effective option for removing heavy metal compounds. According to the experiment's results, the largest adsorption capacity of 0.816 mg/g was followed by the greatest removal efficiency of 91.837%. The isotherm analysis found that the Langmuir model provided an outstanding fit for the experimental data. Thus, this relationship suggested that on the surface of the POFA, a monolayer and an adsorption process suitable for physical adsorption took place.

Assessement of the physico-chemical quality of Groundwater in the Zagora area, Morocco

Abstract The Zagora region heavily relies on groundwater as a crucial water resource for a range of human activities. Mining activities can have significant impacts on groundwater quality in the areas surrounding mining sites. The primary objective of this study is to analyze and evaluate the effects of pollution on the quality of groundwater in the Zagora area, with a particular focus on mapping and identifying its sources. It is based on the use of Geographic Information Systems (GIS) and the spatial variation of the physico-chemical parameters of the studied water sources. Assessing the physico-chemical quality of groundwater in Zagora, involves evaluating several parameters that can affect its quality. These parameters include temperature (T°C), pH, electrical conductivity (EC), dissolved oxygen (O2), chlorides (Cl−), sulfates (SO4 2−), nitrates (NO3 −), nitrites (NO2 −), ammonium (NH4 +), and orthophosphates (PO4 3−). The results of the physico-chemical analysis have shown that, the electrical conductivity ranged from 501.59 to 3173.92 μs/cm, while sulfate concentrations ranged from 91.87 to 363.02 mg/L. The spatial distribution of the results indicates that the water samples were collected from different locations, and there are variations in the levels of parameters analyzed. Some of the parameters, such as electrical conductivity, and sulfate, have higher levels in some locations compared to others, indicating potential sources of pollution or natural variability in the water composition. The GIS analysis also revealed that the areas with poor water quality were clustered around specific locations, indicating potential sources of contamination. Therefore, further investigation and monitoring of the water sources may be necessary to ensure safe and healthy water consumption.

Model of environmental management due to coal mining on the Separi River in Tenggarong Seberang District, Kutai Kartanegara Regency, East Kalimantan Province

Coal mining has a significant impact on reducing river water quality. The decline in river water quality causes problems for human life and the environment. Therefore, this research aimed to evaluate river water quality and develop strategies for improving river water quality due to open pit coal mining activities in Tenggarong Seberang District and develop environmental improvement strategies. Several chemical parameters, including pH, TSS, Fe, and Mn, were observed through laboratory tests to determine water quality in the Separi River used in coal mining. The next step was determining environmental improvement strategies using the ISM approach. Twenty stakeholders from related agencies and institutions using FGD were involved in developing a policy strategy. The results of the analysis showed that there has been a decrease in river water quality standards due to mining activities in the research area, and the quality is still below the standard quality. Therefore, two significant strategies must be a priority for the environmental management of the Separi River. First, Conducting an environmental audit of the factors causing the decline in river water quality is necessary. Second, there must be warnings and legal sanctions for negligence in oil spills and oil used from coal mining.

Stay with the green: New insights into ancient copper smelting in the Tonglüshan site, China

This paper presents new archaeometallurgical analyses from the Tonglüshan site, a famous ancient mining and smelting site in China. Results show that the primary phases in slag samples from two sites (Sifangtang and Lujia’nao) are all of a vitreous matrix, interspersed with fayalite crystals, wüstite, and hercynite. The trapped metallic particles in the slag are mainly raw copper with few sulfides present, which indicates a direct reduction process of oxidic ore. Iron-rich minerals were likely to be added as flux implied by the few unreacted inclusions in the slag samples. The extremely low copper content in the slag samples demonstrates a high rate of copper recovery, indicating that the copper smelting technology in the region had reached a considerably advanced level. In the meantime, the variations in metal content in slag samples from different periods reveal the diachronic changes in this copper smelting technology. The Tonglüshan site, with its millennia of ancient mining and metallurgical activities, provides an excellent material base for detailed studies on technological evolution.

Evaluation of the geochemical background of soil in a hyper-arid zone using a multivariate statistical methodology: The case of the city of Antofagasta in the Atacama Desert

This study investigates the geochemical background and factors influencing the variability of 19 environmentally relevant elements in the soils of Antofagasta, Chile, a region known for its extensive mining activities. Employing robust multivariate statistical techniques on a dataset of 94 soil samples, we identified four main factors explaining 70% of the total variance in elemental concentrations. These four factors reflect the influence of Jurassic volcanic rocks, intrusive rocks, marine sediments, and mafic to intermediate intrusive rocks. Cluster analysis revealed three distinct geochemical populations, each reflecting a unique combination of natural and anthropogenic influences. We established background concentrations for each element within these clusters using robust statistical methods. Geostatistical analysis, employing inverse distance weighted interpolation, produced factor distribution maps that, when integrated with geological data, provided insights into lithological and anthropogenic influences on soil geochemistry. Our findings highlight the complex interplay between natural geological processes, the region's unique arid climate, and anthropogenic activities in shaping the geochemical landscape of Antofagasta. This study contributes to the understanding of geochemical backgrounds in mining-intensive, arid regions and provides a methodological framework applicable to similar environments worldwide.