Mining Operations Research Articles

Validation of water quality parameters using ion balancing and electrochemical approaches: a case study

ABSTRACT The present study validates the accuracy of water quality analysis for twenty geo-referenced water samples from a watershed of Gaya district, Bihar, using ion balancing and electrochemical approaches. Analytical data were presented using box plots, Gibbs diagram and descriptive statistics. Regression equations of various chemical parameters and ionic strength with electrical conductivity (EC) are reported for routine conversion and outlined mathematical equations for data validation. The pH and EC of the water samples varying from 4.9 to 8.7 and 190 to 800 µS cm−1, respectively. Calcium (Ca2+), magnesium (Mg2+), sodium (Na+) and potassium (K+) varied from 0.88 to 2.53, 0.4 to 1.6, 0.8 to 3.75, and 0.01 to 0.22 meq L−1 whereas, bicarbonate (HCO3 –), chloride (Cl–) and sulphate (SO4 2–) ranged from 1.3 to 6.0, 0.25 to 1.5 and 0.01 to 0.6 meq L−1, respectively. Consistency between calculated and measured values judged the correctness based upon relative error (RE %) of the water analysis data. Overall RE on an average of ca. 6% and 5% is reported regarding consistency between the calculated and measured specific conductivity ( calc. and .) and ionic strength ( calc. and .), respectively and difference was statistically non-significant. The ion balancing method showed very good to good analytical data quality for 80% of water samples, while electrochemical approaches (EC and ionic strength) indicated good to moderately good analytical data quality for 85% of the investigated samples. Taking cognisance of the outcome of all validation approaches, an overall 20% rechecking of water samples including (sample ID S3, S8, S13 and S14) is proposed for better analytical data quality for further data mining operations.

Increase The Percentage of Coal Conservation Deposited in ROM Drainage Areas

The research aims to increase the conservation percentage of trapped coal in the ROM A1 drainage area from February to June 2024 by improving fine coal management and adding value to the conservation of PJP. This study also seeks to reduce penalties from fine coal blending into sellable products and minimize environmental pollution in the ROM A1 area. The study employs a descriptive method, focusing on implementing coal conservation in drainage areas by determining the scope of each conservation object. Root cause analysis using a Fishbone diagram was used to identify key improvement strategies for increasing coal conservation percentages. Initial observations in the ROM A1 drainage area revealed 6,829 tons of unpreserved fine coal, primarily due to rainwater runoff. The results showed that with proper implementation of conservation techniques, including the installation of fine coal traps and the centralization of fine coal in collection points, the conservation rate improved from 0% to 62% by April 2024. In tangible terms, 83 tons of fine coal, worth IDR 26,434,928, were saved, contributing to both environmental conservation efforts and economic benefits for the company. This study highlights the importance of continuous coal conservation efforts, especially in mining operations where environmental and financial impacts can be significant.

Creating near real-time alerts of illegal gold mining in the Peruvian Amazon using Synthetic Aperture Radar

Abstract Peru’s Southeastern Amazon deforestation trends can be attributed to alluvial gold mining. Illegal mining occurring in forestry concessions, national parks, and the territories of Indigenous People Organizations is of particular concern. We present a methodology to create near real-time alerts of deforestation caused by alluvial gold mining. A time series of Sentinel-1 Synthetic Aperture Radar (SAR) data from February to December 2022 is created in Google Earth Engine (GEE) and assessed using Morton Canty’s Omnibus Q-test change detection algorithm. Resulting detections are validated with high-resolution optical imagery from Planet NICFI’s monthly basemaps and Planet Scope daily imagery. The alerts identify the location and timing of large areas (group pixels of <1 ha) of forest loss due to gold mining activities within buffer zones of indigenous territories and protected areas. The overall accuracy of the forest loss analysis conducted with this change detection method was 99.98%, based on an independent accuracy assessment. This effort has resulted in a public web platform that displays the location of near real time alerts, so Peruvian enforcement agencies can more effectively allocate resources and staff to addressing active illegal mining operations. These results demonstrate the applicability of open-source SAR data to monitor forest loss over areas where cloud cover is more persistent and to improve tools that deliver timely, critical information to decision-makers. Future applications of our method could expand this approach to other drivers of deforestation.

Effects of Artisanal Mining on Land Degradation in Zamfara North-West, Nigeria

This paper analyzed the effects of artisanal mining on land degradation. It took critical look on both legal and illegal mining activities in the study areas and their level of devastated effects on land texture and structure over space. The method implored is both probability and non-probability approaches. The purposive targeted populations for the study were licensed and unlicensed small scale gold mining operators in the study areas, with a sample population of 100 person, and types of data used is both primary and secondary sources. Data was analyzed using descriptive statistic and frequency chart that indicated major challenges was illiteracy 31% and lack of coordination among miners 23%, major effect of land degradation was water pollution and deforestation had 30% and 23% respectively, and effects of artisanal mining on land degradation was degradation of arable land had 20% and exposing the soil to wind and chemical had 18%. It had a serious implication on ecosystem. The paper concluded that artisanal mining of mineral ores had caused serious damages on the land resources both soil and rivers. Therefore, to ensure sustainability in mining activities and to secure a quality environment, the following recommendations are hereby suggested, Educating local miners on the dangers of open cast mining and grinding of gold ore using the same grinder for grains to be consumed and Policy makers should avoid politicizing vital issues that will threaten peace and security of people in Zamfara and its environs.

Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach

The mining industry is a key contributor to Western Australia’s economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportunities of integrating renewable energy sources into isolated power systems, particularly under uncertainties associated with renewable energy generation and demand. A robust optimization approach is developed to model a multi-source hybrid energy system that considers risk-averse, risk-neutral, and risk-seeking strategies. These strategies address power demand and renewable energy supply uncertainties, ensuring system reliability under various risk scenarios. The optimization framework, formulated as a mixed integer linear programming problem and implemented in Python using the Gurobi Optimizer, integrates renewable energy sources such as wind turbines, photovoltaic arrays, and demand response programs alongside traditional diesel generators, boilers, combined heat and power units, and water desalination. The model ensures reliable access to electricity, heat, and water while minimizing operational costs and reducing reliance on fossil fuels. A comprehensive sensitivity analysis further examines the impact of uncertainty margins and the value of a lost load on the total system cost, providing insights into how different risk strategies affect system performance and cost-efficiency. The results are validated through three case studies demonstrating the effectiveness of the proposed approach in enhancing the resilience and sustainability of isolated power systems in the mining sector. Significant improvements in reliability, scalability, and economic performance are observed, with the sensitivity analysis highlighting the critical trade-offs between cost and reliability under varying uncertainty conditions.

Uncertainty in underground mining operations: a bibliometric and systematic literature review analysis

Purpose This study aims to provide a comprehensive review of the existing literature on uncertainty in underground mining operations, using a bibliometric and systematic analysis covering the period from 1975 to 2024. Design/methodology/approach To achieve this, the following questions were addressed using a mixed-method approach involving bibliometrics, text mining and content analysis: How has the field of uncertainty research in underground mining operations evolved? What are the most prominent research topics and trends in uncertainty in underground mining operations? and What are the possible directions for future research on uncertainty in underground mining operations? Findings As a result, bibliometric networks of 327 journal articles from the Scopus database were created and examined, the main research topics were underground mining management; rock mechanics; operational optimization; and stochastic systems. Finally, the inclusive investigation of uncertainty in underground mining operations and its prominent patterns can serve as a basis for real-time direction for new research and as a tool to improve underground mining activities by implementing advanced technology for innovative practices and optimizing operational efficiency. This is fundamental to identify unknown variables that impair the planning, operation, safety and economic viability of underground mines. Originality/value This research is 100% original because there is no review research on the uncertainty present in underground mining operations.

Improvement of Coal Mining-Induced Subsidence-Affected (MISA) Zone Irregular Boundary Delineation by MT-InSAR Techniques, UAV Photogrammetry, and Field Investigation

Coal mining-induced ground subsidence is a severe hazard that can damage property, infrastructure, and the environment in the vicinity when the deformation is not negligible. The boundary of a mining-induced subsidence-affected zone refers to the area beyond which the ground subsidence is less concerned. Accurately measuring mining-induced ground deformation is essential for delineating the irregular boundary of the impacted area. This study employs multitemporal interferometric synthetic aperture radar (MT-InSAR) techniques, including differential InSAR (DInSAR), InSAR stacking, and interferometric point target analysis (IPTA), to analyze coal mine subsidence and delineate the boundaries of the mining-impacted zones. DInSAR accurately reconstructs, locates, and detects the trend in mining-induced subsidence and correlates well with documented mining operations. The InSAR stacking method maps the spatial variation of the ground’s average line-of-sight (LOS) velocity over the mining area, delineating the boundary of the impacted zone. IPTA analysis combining multilook and single-pixel phases achieves millimeter-level surface measurement above tunnel alignments and measures unevenly distributed deformation fields. This study considers an average of 4 cm per year of surface deformation in the LOS direction as the subsidence threshold value for delineating the boundary of the mining-induced subsidence-affected (MISA) zone during the active coal mining stage. Interestingly, there are twin transportation tunnels near the mining area. The twin tunnels completed before the coal mining activities started were functioning well, but damage was observed after the mining began. Our study reveals the tunnels are located within the InSAR-derived MISA zone, although the tunnels approach the MISA boundary. As direct signs of subsidence, ground fissures have been identified near the tunnels via field investigations and UAV photogrammetry. Furthermore, the derived distribution of ground fissures validates and verifies InSAR measurements. The integrated approach of MT-InSAR, UVA photogrammetry, and field investigation developed in this study can be applied to delineate the irregular boundary of the MISA zone and study the accumulating effects of mining-induced subsidence on the performance of infrastructure in areas proximate to coal mining activities.

Optimization of Filling Material Ratio in Yellow Phosphorus Slag Mine

Yellow phosphorus slag has been considered as a potential cement substitute for mine filling material due to its cementing activity; however, its slow setting and low early strength have limited broader use. This study investigates the grading, compactness, and strength of yellow phosphorus slag combined with tailing sand. Using yellow phosphorus slag as an aggregate, cement as a binder, and mixing tailing sand in different ratios, this study evaluates its feasibility as a coarse aggregate in mine backfill. The key findings are as follows. (1) The grading index of tailing sand was 0.5, aligning with Fuller grading, but it required mixing with coarse aggregates to enhance strength and reduce cement consumption. Yellow phosphorus slag, with a grading index of 0.97, does not match Fuller’s curve and thus benefits from mixing with tailing sand. (2) For mixtures of waste rock and tailings, the 5:5 ratio aligned closely with Fuller’s theory, showing optimal packing density and strength. Mixtures of yellow phosphorus slag and tailings at ratios of 3:7, 4:6, and 5:5 had R2 values of 0.73, 0.80, and 0.85, respectively, confirming reliable fit. The 5:5 mixture provided the best packing density and strength. (3) A new strength prediction model, accounting for aggregate, cement, and water effects, suggests that a 5:5 ratio with a 71% mass concentration and 1/7 ash–sand ratio meets industrial strength requirements. FLAC3D simulations indicated that cemented backfill reduces stress concentrations caused by excavation and supports stability during mining while also absorbing energy through compaction, creating favorable conditions for safe mining operations.

Environmental Threat Assessment Framework for Mining Activities in Guinea: An Integrated Approach for Sustainable Development.

The present study aimed to investigate the environmental consequences of mining activities in boke bauxite mining areas and the Kerouane iron mining project in Guinea using a mixed-methods approach that combines quantitative and qualitative data. A reference matrix was used to evaluate the impact of the mining activities, classifying them as negligible, moderate, or significant. Data were collected from October 2022 to January 2023 by assessing their impact on water pollution, soil, noise, air quality, vegetation, fauna, and flora. These findings indicate concerns regarding the water pH, electrical conductivity, and turbidity in both the Boke and Kerouane regions. The soil composition analysis revealed the presence of Cr, Cu, Ni, and Zn in both the Boke and Kerouane project areas. Noise levels exceeded the guideline levels and substantial amounts of particulate matter (PM) were detected, with high levels of PM10 in mining operations. The Kerouane Iron Project resulted in the direct loss of 2929 ha of natural habitats and 466 ha of modified habitats, with the extraction of approximately 1.291 billion tons of ore anticipated over a 22-year mine lifespan. This study proposes an environmental threat assessment framework that integrates technical and human activity data to evaluate the environmental impacts of mining activities comprehensively. To promote sustainable development and minimize the negative impacts of mining, an integrated index of economic and environmental performance in the mining sector is recommended, along with collaboration between researchers and policymakers to develop effective climate-change mitigation strategies.

Analysis of Sustainability Variables in Revegetation of Ex-Oil and Gas Mining Operation

Revegetation after petroleum mining operations is a complex and multifaceted issue that requires careful consideration of sustainability factors to ensure long-term success. PT Pertamina Hulu Rokan has taken its environmental responsibilities seriously and has restored ex-mining land through replanting efforts at ex-well sites, ex-production facilities, and ex-borrow pits. This is important for environmental sustainability, especially after mining oil and gas. This study aims to identify important variables in maintaining the sustainability of revegetation activities at PT Pertamina Hulu Rokan by describing the intensity of influence and interdependence between variables and grouping them from the most influential to the least influential. Focus group discussions (FGDs) were used to collect data, and the MICMAC approach was used to analyze the relationships between variables. This research has identified 13 ecological, socioeconomic, and conflict mitigation variables that are important in land revegetation activities. Based on the results, the relationships between these variables have been derived by highlighting the key indicators that trigger sustainable revegetation efforts, namely variables such as envreg, amdal, local business development (lbd), and relationship. The lbd variable strongly influences the welfare variable, amdal, and the other variables strongly influence the company's image. Post-mining land revegetation efforts at PT Pertamina Hulu Rokan demonstrate the company's commitment to environmental sustainability. By considering sustainability variables in the revegetation process after petroleum mining operations, PT PHR ensures that its rehabilitation efforts can restore land while promoting sustainable practices and providing benefits to local communities.

Developing a Technology for Driving Mine Workings with Combined Support and Friction Anchors in Ore Mines

This study summarizes the experience of conducting and maintaining mining operations in unstable zones in mines in Kazakhstan, assessing the mining and geological technical conditions of their operation under difficult mining and geological conditions. A field study and analytical modeling with an assessment of the stability of the boundary mass using the Barton mining method enabled the development of a technology for sinking mining operations with combined fasteners and friction anchors in ore mines.

Innovative computational model for optimal deep coal mining under large-scale crustal stress conditions.

Understanding and controlling the ground stress in deep coalfield mining is crucial for ensuring mine safety and efficiency. This study aims to address two unresolved scientific issues in ground stress research: the selection of optimal excavation plans and the large-scale rapid acquisition of ground stress data. A novel computational model is proposed for key rock layer control under different crustal stress conditions. The model considers the complexity and uncertainty of ground stress distribution by simplifying the key rock strata into a fixed-fixed beam model and calculating their safety through mechanical methods. Introducing an innovative approach for acquiring large-scale stress fields using GPS data. By inverting large-scale strain fields in the coalfield area, combined with World Stress Map (WSM) and measured data, accurate stress fields are obtained. The proposed optimal excavation plan can be applied to various coalfield locations worldwide, providing a scientific basis for safe and efficient mining operations. Additionally, the innovative use of GPS data in obtaining large-scale stress fields offers a valuable tool for assessing ground stress variation.

Deformation prediction of overlying strata in multi-seam mining based on the influence function method-key stratum hybrid model

The extraction of coal seams from subterranean strata has the potential to induce displacement and deformation within the overlying strata. This leads to fractures in the strata and surface subsidence. The repetitive mining of coal seams, especially in scenarios involving multiple coal seams, can reactivate previously stabilized rock strata, causing them to subside and deform again. This exacerbates deformation and compromises the structural integrity of the strata. Consequently, there is an imperative need to thoroughly investigate the patterns of movement exhibited by overlying rock layers as a result of the recurrent extraction of coal seams. In recent years, significant progress in this field has been the effective utilization of the Influence Function Method-Key Stratum (IFM-KS) hybrid model. This model, distinguished by its amalgamation of mechanical and geometric methodologies, has proven to be efficacious in scrutinizing the movement dynamics of overlying strata in the context of single-layer mining operations. Based on that, this paper introduces a novel model for predicting rock layer movement and deformation in multi-seam mining. The calculation results derived from this model reveal the dynamics of rock layers' movement and deformation following secondary disturbances during repetitive mining. The accuracy and reliability of this newly proposed model in predicting rock movement during dual-layer coal mining are validated through both theoretical calculations and UDEC numerical simulations. The results demonstrate a high degree of consistency between the numerically simulated rock displacement and mathematical calculations and the rationality of the model. Based on the rock strata movement calculation results, the corresponding porosity distribution is also derived. Compared to single-layer coal mining, multi-seam mining could cause greater changes in porosity in the goaf area and extensive damage to rock strata. More fracture pathways between coal seams occur and a volume of air-leakage quantity is expected. This computational model provides invaluable insights for predicting rock strata deformation and porosity distribution in repetitive mining scenarios of a similar nature.

Blasting techniques applied to control vibrations, flyrock, and slope damage while ensuring compatibility with fragmentation

Blasting operations in mines near communities are of increasing social concern and scientific investigation due to the potential structural damage and human discomfort caused by blasting induced vibrations. Therefore, a technical-scientific approach is necessary to conduct these activities safely and sustainably compatible with fragmentation requirements of the scale of production. This paper presents a case study of an open-pit mine located in Brazil, where blasts are frequently carried out near a community. Additionally, controlling flyrock is extremely important in this mine due to the proximity of people to the blasting sites, as well as controlling the slope damage. Thus, it became necessary to develop a methodology for the application and combination of techniques and simulation fo blasting-induced vibration and wall control, flyrock and fragmentation such as attenuation law, signature holes, decking charge techniques, pre-split holes. The proposed methodology was effective, validated, and is recommended for open-pit mines operating near communities.

Development of New Spray Dust Suppression Materials in Metal Mines and Prediction of Algorithm Simulation Effect

PROBLEM: Dust contamination in metal mining poses substantial dangers to environmental quality and human health. Modern mining operations cannot use traditional spray dust suppression methods because they are poorly adapted to changing climate conditions, low efficient, and detrimental to the environment. INTRODUCTION: Dust pollution seriously impacts the environment and human health in metal mine operations. Traditional spray dust suppression technology has many problems, such as limited effect, environmental impact, and poor climate adaptability. OBJECTIVES: The purpose of this article is to develop a new type of spray dust suppression material and predict its dust suppression effect through algorithm simulation. Firstly, efficient and environmentally friendly dust-reducing materials were screened, and after evaluating the dust-reducing effect under laboratory conditions, the optimal material combination was determined. METHODS: Using computational fluid dynamics (CFD), a numerical model of the spray process was constructed to simulate the dust suppression effect of different materials under different climatic conditions. RESULTS: The results show that the highest dust reduction efficiency of the new spray dust reduction material is more than 4.3% higher than that of the traditional material, and it shows good stability. CONCLUSION: The new spray dust control material and its effect prediction method studied in this article provide an effective solution for dust control in metal mines, which has important theoretical value and practical application prospects.

Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines

To address the scheduling challenges associated with the increasing deployment of battery-swapping trucks in open-pit mines, this study proposes a multi-objective scheduling optimization model. This model accounts for the unique characteristics of battery-swapping trucks by incorporating constraints related to battery swapping alerts, the selection of battery-swapping stations, and the impact of ambient temperature on battery capacity. The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. The aim is to identify an optimal scheduling solution without violating any model constraints. Results demonstrate that both the basic genetic algorithm and the adaptive genetic algorithm effectively achieve truck transportation scheduling. However, the adaptive genetic algorithm surpasses the basic genetic algorithm, reducing the total transportation costs by 5.6% and total waiting time by 17.4%. It also reduces the number of battery swaps and transportation distance by 15.8% and 1.2%, respectively. The proposed multi-objective scheduling optimization model successfully minimizes the waiting time and transportation costs of battery-swapping trucks while ensuring the completion of production tasks. This approach provides valuable technical support for improving the production and transportation efficiency of open-pit mining operations.

Behind the Renewed Interest in Nuclear Power

Electricity demand is outstripping the ability of markets and electric grids to respond quickly to meeting the generation and transmission and distribution system needs for supporting a 21st‐century economy. Electricity demand is increasing faster than it has in decades as manufacturing rebounds, and data centers and cryptocurrency mining operations proliferate across the United States. At the same time, there is mounting pressure on governments globally to reduce greenhouse gas (GHG) emissions in the electricity sector by transitioning buildings and transportation systems away from fossil fuels to electricity.

Subsidence and Uplift in Active and Closed Lignite Mines: Impacts of Energy Transition and Climate Change

This study examines the combined effects of decommissioning lignite mining operations and long-term climate trends on groundwater systems and land surface movements in the Konin region of Poland, which is characterised by extensive open-pit lignite extraction. The findings reveal subsidence rates ranging from −26 to 14 mm per year within mining zones, while land uplift of a few millimetres per year occurred in closed mining areas between 2015 and 2022. Groundwater levels in shallow Quaternary and deeper Paleogene–Neogene aquifers have declined significantly, with drops of up to 26 m observed near active mining, particularly between 2009 and 2019. A smaller groundwater decline of around a few metres was observed outside areas influenced by mining. Meteorological data show an average annual temperature of 8.9 °C from 1991 to 2023, with a clear warming trend of 0.0050 °C per year since 2009. Although precipitation patterns show a slight increase from 512 mm to 520 mm, a shift towards drier conditions has emerged since 2009, characterised by more frequent dry spells. These climatic trends, combined with mining activities, highlight the need for adaptive groundwater management strategies. Future research should focus on enhanced monitoring of groundwater recovery and sustainable practices in post-mining landscapes.

CMMI & Lean-Based Metrics Governance Model to Ensure Data Accuracy & Consistency for Ai/Ml Applications for Sustainable Operations in Mining Industry

In today’s competitive business environment, even small improvements in productivity and efficiency can have a huge impact on company’s profitability. Whether it is through reduced lead time/waste, minimized downtime or improved quality, operation managers are looking for any advantage at every stage. Lean management is a long-term operational discipline that methodically seeks to enhance efficiency and quality by eliminating wastage. The concept is being used in varied industries and helped by improved productivity, safety & better management. Lean in being used by few mining companies also at a small scale, which has helped them in limited way. AI/ML is another important technology used by many organizations. Many global mining companies have also used it for improving operational efficiency, which have helped miners in a limited ways in improving the productivity and safety. Mining companies have to deal with tons of data set generated from heavy machinery and plants, which have to be stored, processed, and stored. There are many challenges in the data set generated/used by AI/ML-application for mining operations. One of the key challenges in AI/ML is accessibility and availability of accurate & consistent data. To ensure consistency of data there is a need for a governance structure which will guarantee the availability of required accurate data set for AI/ML system. One possible solution could be, CMMI’s metrics processes used by IT companies and have helped in improving quality. CMMI’s Metrics related processes are being used extensively by the organizations for better monitoring & control of key measures. This paper explores the possibility of usage of CMMI’s metrics practices with lean implementation in mining for ensuring availability of accurate data sets for AI/ML applications. The proposed framework will put a governance model in place to ensure accuracy & consistency of data to be used for AI/ML-applications in Mining.

Monitoring Aeolian Erosion from Surface Coal Mines in the Mongolian Gobi Using InSAR Time Series Analysis

Surface mining in the southeastern Gobi Desert has significant environmental impacts, primarily due to the creation of large coal piles that are highly susceptible to aeolian processes. Using spaceborne remote sensing and numerical simulations, we investigated erosional processes and their environmental impacts. Our primary tool was Interferometric Synthetic Aperture Radar (InSAR) data from Sentinel-1 imagery collected between 2017 and 2022. We analyzed these data using phase angle information from the Small Baseline InSAR time series framework. The time series analyses revealed intensive aeolian erosion in the coal piles, represented as thin deformation patterns along the potential pathways of aerodynamic transportation. Further analysis of multispectral data, combined with correlations between wind patterns and trajectory simulations, highlighted the detrimental impact of coal dust on the surrounding environment and the mechanism of aeolian erosion. The lack of mitigation measures, such as water spray, appeared to exacerbate erosion and dust generation. This study demonstrates the feasibility of using publicly available remote sensing data to monitor coal mining activities and their environmental hazards. Our findings contribute to a better understanding of coal dust generation processes in surface mining operations as well as the aeolian erosion mechanism in desert environments.