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By J S. Kuszmaul, T O. Aspinall

The applicability of environmental geotechnics for erosion management is increasing in importance worldwide. The environmental impact of mining and evolving environmental legislation has been receiving increased attention worldwide in the last two decades (Bradfield, Shultz and Stone, 1996). The potential impacts associated with unstable spoil dumps from mine operations is the focus of concern both by the mining industry, environmental legislative agencies and members of the public. This is because of the need to increase the reliability of erosion prediction and in the minimisation of costs for spoil dump design. Engineered slopes of mine spoils may be stable at the end of construction, but they can deteriorate over time. Engineering design of mine spoil dumps seeks to reduce the potential for such erosion damage through correct selection of an initial stable landform scheme (Goh, 1997). The design of mine spoil dumps must also conform to the specifications of evolving legislation. The Queensland Environmental Management Overview Strategy (EMOS) states that, for minimised degradation of the surface area due to erosion during the development of a project, the erosion rates should be between 12 - 40 tonnes/hectare/year and that the depths of rills and gullies be limited to less than 30 cm (QDPI, 1988). The aim of engineering design is to ensure the long-term stability of the spoil dumps. The implementation of effective planning and operating procedures through recontouring and grading assists in the reshaping of spoil dumps to a safe, stable and non-erodible environment.

Jan 1, 1998

By Matthew Clay, Colin Chambers, Susan Hookham

Opencast (quarries) and underground mines around the world use blasting methods to mine valuable ore. Traditional blasting systems use technologies such as electric delay detonator systems (developed in the 1950s) and non-electric detonator systems (developed in the 1970s) to initiate a detonation train to blast rock more effectively, and so retrieve valuable product more efficiently. However, the lack of precise control over blast timings with these approaches can result in undesirable outcomes such as significant flyrock, excessive ground vibration, uneven grade of rock and misfires (in which sections of the blast can remain unfired). The development of Electronic Initiation Systems (EIS), first used in the 1990s, introduced a higher level of control over the blast. These systems greatly reduce the negative issues associated with blasting. However, this precision introduces complexity, and with this complexity comes difficulty in demonstrating the predictability, safety and reliability of such systems.

Jan 1, 2017

A compilation of papers presented at the Fifth WVU Conference on Coal Mine Electrotechnology in Morgantown, West Virginia, on July 30, 31, and August 1, 1980. Papers cover areas of electromagnetics/power systems, power systems, monitoring and control, and communications.

Jan 1, 1980

By Jorge Luis Cáceres Córdova

Durante los procesos mineros, el comité ejecutivo gestiona decisiones -confiables y económicamente rentables- según la información requerida. En ese sentido, el presente texto señala una metodología que integra las herramientas de gestión donde se garantice la confiabilidad de los activos de forma sostenida que prevenga pérdidas de producción, se reduzca los costos operativos, se evita riesgos a la salud y medio ambiente y se establezca una política de sustento cuantitativo a pedidos, cambios, bajas, terciarizaciones, entre otros, en base al riesgo y beneficio.

Sep 1, 2015

By M. Ge, C. Mborah

"The acoustic emission/microseismic monitoring (AE/MS) technique has widely been used in the mining environment for the monitoring of rock mass stability. A successful implementation of the method is hinged on being able to accurately determine the P- or S-wave arrival which is then used in the determination of the source of an event. Determination of the arrival phase is usually performed visually by a human expert. However, the mining environment is characterized by high noise levels and different noise types of varying intensities. Therefore, performing manual phase picking on time series data acquired from the AE/MS monitoring system can sometimes be tedious and time consuming if not impossible. In this paper, a proposal for improving manual P-wave phase arrival picks is discussed. The method involves the filtering of the AE/MS data using a stationary discrete wavelet transform (SDWT) method. After filtering, appropriate scales/levels of the multi-level decomposition process are then selected for further processing. The first step in the picking process after filtering, requires the computation of the signal power and the root mean square (RMS) using the signal amplitudes at each scale. The preliminary P-phase arrival time is picked using the results of the calculated power and RMS values respectively. The calculated RMS values are then superimposed on the calculated power values to determine the final arrival picks. If the arrival time picks obtained by both methods coincide or are within 5 to 10 sample points, the pick is considered reliable. The accuracy of the method was verified using AE/MS data from two datasets obtained from two separate underground mines. The results of the study showed that the picking method is reliable and robust. Based on the data studied, it can be concluded that the method will help reduce the time usually spent in processing AE/MS data from mines. INTRODUCTION A successful identification and location of the source of acoustic emission/microseismic (AE/MS) events is mainly dependent on the onset time of the P-wave phase. In many seismic networks, initial picks are performed by picking algorithms followed by manual picks by human experts. If the waveform signal-to-noise ratio (SNR) is low, the P-wave onset time picks by the human expert is generally reliable and accurate [1]. However, for waveforms with high SNR, picking of the P-wave onset could be a major challenge. Also, due to the volume of data acquired daily, manual processing could be stressful and time consuming [2]. These challenges continue to provide motivation for alternative means of providing reliable and efficient ways of improving manual phase picking. The AE/MS technique has been an intergral part of safety monitoring in mines [3] due to its capacity to identify zones of instability in a monitoring area. To obtain an accurate source of an AE/MS event however depends on the quality of the data used for P-wave phase picking [4, 5]. AE/MS data from mines are generally contaminated with excessive background noise generated by the different mining operations. The AE/MS signals of interest are mostly buried in background noise which makes it difficult to pick the P-wave phase arrivals [4]. Processing AE/MS data acquired in noisy environment remains a major challenge due to the weak nature of AE/MS signals [6]. As noted by [4] most of the data recorded in the mine environment are mainly due to events not related to AE/MS events of interest. The complexity of data in this type of environment makes the detection and picking of P-wave arrival by human experts a very difficult task."

Jan 1, 2017

In line with DML Resources continual forward management policies, the Roscommon Quarry operation has recently installed and commissioned a Nordberg 7 ft Symons cone crusher and a HP 300 cone crusher. Both machines have enhanced the production capabilities and quality control of the Roscommon comminuition circuit and they will provide efficient and reliable crushing well into the next century.

Jan 1, 1994

Hydraulic fluid power systems are advantageous whenever power output must be accurately and safely controlled. The load movers, cylinders, jacks, rotary actuators and hydraulic actuators in these systems can be made to smoothly and accurately start, stop, reverse, hold position or move steadily under heavy and variable loads or torques. Because hydraulic systems are simple, compact, reliable, and low cost compared to other power methods and because they can deliver controlled power anywhere on the machine to which a hose can be routed, they are a pan of almost every type of machine found on a coal mining section. Some of the functions they perform are positioning drill booms, driving drill pots on roof bolters, positioning curter booms, raising, lowering, and swinging conveyors, driving conveyors on continuous miners, raising, lowering, and applying sustained loads to longwall roof supports, and advancing the face conveyor and roof supports in longwall mining operations.

Jan 1, 1982

By R. L. Miller

"Miners worldwide use a tremendous amount of energy in producing finished minerals for the end user market. In accomplishing this goal, they incur energy costs that can range from 20% to 30% of the total cost of production, so there is fertile ground for cost savings. To unlock this huge value in cost reduction, energy analysis is the key and is broken into several segments: 1. Fuel analysis for power generation 2. Energy supply & demand 3. Opportunity cost for lack of power 4. Backup power 5. Power contracts 6. Energy efficiency 7. Renewable energy 8. Continuous energy management FUEL ANALYSIS FOR POWER GENERATION What is the first thing we evaluate when looking at power supply alternatives for the mining industry’s large power requirements? Is it 1) site, 2) engineering, procurement, and construction companies, 3) independent power producers, 4) turbine vendors, 5) grid connections, or 6) fuel supply, logistics, and infrastructure? In evaluations of power supply alternatives for mining companies with special emphasis in developing countries, there is one over-riding conclusion: reliable fuel supply drives the energy generation economic engine. Evaluating several different fuels including liquefied natural gas (LNG), natural gas, diesel, heavy fuel oil, and liquefied petroleum gases (LPG) among others, the best project outcomes are those where fuel supply, pricing, logistics, and infrastructure are given an extensive amount of time during the analysis stage. In an assessment of the twenty-year costs of generating power from multiple fuels, each fuel’s costs were placed into three separate net present value (NPV) buckets of: 1) capital, 2) operating and maintenance, and 3) fuel. Within a range of 65% to 85% for all fuels, fuel cost was the largest component of the NPV of the life cycle power generation costs. So if 65% to 85% of your life cycle power generation cost is one item, shouldn’t miners spend a corresponding amount of time in the analysis stage fully understanding this key determinant for a successful power project? In developing countries where power generation infrastructure may not exist or does not exist at the same level as is found in North America and Europe, fuel analysis becomes even more important. One of the key questions for fuel importation in developing countries is the draft at existing ports to allow larger vessels to dock at the jetty. Can larger ocean-going tankers dock at the port for off-loading, or is the port’s draft too shallow, thus forcing a Single Point Mooring (SPM) system or Conventional Buoy Mooring (CBM) system to be constructed at substantial capital expense? Once fuel can be imported, sufficient onshore storage capacity should exist, or must be built to off-load the entire fuel cargo from the larger ships. Additionally, the throughput capacity of the pipeline from SPM/CBM must allow a rapid unloading of the fuel from ship to shore to eliminate steep demurrage costs for the project."

Jan 1, 2017

By D Kent

"There has been a revolution occurring in underground mining over the last several years, where big headline items such as the Internet of Things (IoT), optimisation, managing data, data mining etc – the list of current catchphrases, goes on. In the end these are nothing new; but the ‘things’ (sensors) are becoming smaller, cheaper and easier to deploy, and the analysis much more powerful as computer processing speeds increase. However, to take advantage of the myriad of devices out there and gain the processing power to analyse and use the data, a reliable ‘conduit’ is needed for that information to be delivered where it can actually be used. That is, a high quality data network.Modern mining is like any other industry in the information age: the access to reliable data is the first, critical step in improving productivity (Stevens, 2015). The convergence of communications onto an IP (Internet Protocol) backbone has been the driving force in enabling the productivity gains in general industry over the last two decades.This paper overviews how this technology has developed as an enabler in accessing productivity and safety benefits, and how it has used access to large amounts of data to manage mining processes underground. Reams of data are useless, but with the reliable receipt, analysis, processing and feedback system in place to use that data, benefits can be realised.Automated mining systems are increasingly being seen as a key requirement for a productive mining operation, and the importance of an integrated communication network infrastructure to support such systems is growing. Another emerging driver is the much talked about IoT and data analytics, both dependant on reliable, accurate, high volume data.The author will outline how communication infrastructure is fundamental to the operation of such systems, and explain why the resultant communication networks require much more than just increased bandwidth (data capacity) to properly support the automation and other data hungry systems within the overall mine operation.Mining operations embarking down this road are discovering that the required network must be based on a true enterprise level architecture to, not only enable the mine’s current plans for remote or automated mining, but also to provide a scalable and integrated platform for future developments. The emerging issues for the communication network to truly support automation systems include: increased complexities of operating and maintaining multiple networks integration issues with disparate systems problems with reporting, particularly as demands for corporate reporting and compatibility with enterprise systems become the norm ongoing management challenges, which will only increase with the proliferation of new technologies.How certain mining operations lay the necessary foundations to meet their current requirements, while supporting their visions for a more automated and proactively managed mine, will be explored.CITATION:Kent, D, 2017. Modern mining – why bandwidth matters, in Proceedings 13th AusIMM Underground Operators’ Conference 2017, pp 123–128 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Oct 16, 2017

By R. Adsero

The volume of data produced by operating mines has increased substantially over the last 10 years. However, the volume of data and analytical capability has been negatively correlated to equipment productivity for at least the last seven years. In simple terms, as the volume of data has increased equipment performance has declined. Table (2010) tells us that ?The calamity of the information age is that the toxicity of data increases much faster than its benefits?. More data does not guarantee improving productivity; but more data is also not the cause of declining productivity. Similarly, when equipment performance does start to improve, (it must ? there really is no option if mines want to remain competitive), it will not be the data nor analytics which causes it; it will be the people using the resources at their disposal; including the data. Data and analytics can help if the toxicity of the data can be managed. The simplest form of business improvement using data is benchmarking. The objective of benchmarking is to understand and evaluate the current position of a process in relation to ?best practice? and to identify areas and means of performance improvement. The application of benchmarking involves four key steps: (1) Analyze and understand in detail existing processes; (2) Analyze and understand the processes of others; (3) Compare your own performance with that of the others analyzed; and (4) Design and implement the changes necessary to close the performance gap(s). There are however, many in the mining industries who have shunned equipment benchmarking because they believe that, ?every mine is a pilot?. In other words, the differences between mine operations make comparisons between them of little value. This paper will present a valid approach to benchmarking equipment performance and reliability, accounting for the differences and similarities between operations, producing a result which can be used to add value to mines around the world.

Feb 23, 2014

The coal reserve base is defined for coalbeds having sufficient thickness for underground mining within a depth range compatible with economic recovery. The reserve data are compiled by the Federal Bureau of Mines by updating and reevaluating previous estimates of the U.S. Geological Survey, State geological surveys, and others. Through the application of computer techniques, the tonnages are compiled by State, county, coalbed, and rank. Coal reserve base is allotted to sulfur categories by a statistical apportionment of data from available Bureau of Mines reports and records. The coal reserve base in those States east of the Mississippi River, minable by underground methods, is estimated to be 169 billion tons in coalbeds greater than 28 inches in thickness to a maximum depth of 1,000 feet. Excluding those coals in reliability categories other than measured and indicated, the underground reserve base includes 162 billion tons of bituminous coal and 7 billion tons of anthracite. Of the total, 27 billion tons contains 1.0 percent or less sulfur. Most of this low-sulfur coal is in the southern Appalachian area. Approximately 16 percent of the underground reserve base is without available analyses. Included in this report is a glossary of terms applicable to a classification system for coal resources and reserves. The purpose of this system is to provide a common yardstick for determining coal resources and reserves.

Jan 1, 1974

By Henry P. Cole

A comprehensive review of published research was carried out to identify methods for teaching and assessing critical but nonroutine skills needed for coping with emergency situations. Specific methods for assessing critical skills proficiency in aviation, medicine, organization management, the military, and other industrial/technical workplaces are described. The potential application of these methods for teaching and assessing (1) critical first aid and (2) self-rescue and escape skills to underground coal miners in annual refresher training is explored. Research and development activities that may improve mine health and safety training are suggested. Most of these research and development activities were completed later in the project. This additional work is reported in the project technical report #2 and the final report. The research reported in the present document was completed in 1984 -85. Many of the initial findings reported in this document are updated in the later project final report.

Jan 1, 1988

By Y. Zhang, C. Zhou, M. Girman

Wireless technologies are increasingly being implemented in underground mines for various purposes such as communications, tracking, remote control, remote sensing, and environmental monitoring. However, the adoption comes with risks as common wireless systems, such as WiFi, Bluetooth, IWT (Innovative Wireless Technologies) wireless system, often operate in the unlicensed ISM (industrial, scientific, and medical) band. The shared nature of the ISM band can lead to interference among devices and consequently cause performance degradation and reliability issues. In this study, we developed two wireless communication evaluation boards as a tool to evaluate the performance and reliability of a wireless system with the presence of electromagnetic interferences (EMI) from other wireless systems in underground environments. We adjusted various parameters including signal power from adjacent frequency channels, noise power within the same channel, the movement of personnel, and communication packet size. Our findings indicate that, while the power of the EMI source plays a key role, the motion of personnel in the tunnel also has a strong impact on performance, and this impact increases as the power of EMI sources increases. In noisy environments, smaller packet sizes are preferable as they enhance the likelihood of successful transmission. High levels of interference or noise can lead to increased packet loss or error rates, potentially causing communication links to fail completely or become ineffective. The evaluation boards utilized in this study are based on a practical wireless transmission system deployed in a remote controller for a heavy mining machinery used in underground coal mines. The results and findings presented in this paper can aid in the design of wireless systems that are resilient to EMI in underground mining environments.

Feb 1, 2025

By Fengming Li, Baocheng Song, Yuemin Zhao, Hailin Dong, Liping Peng, Chusheng Liu, Chenlong Duan

The large-scale vibrating screens with high processing capacity and efficiency are now in great demand in the mineral processing industry of China. However, as the equipment is always suffering from the strong external harmonic exciting force, the inertial force and the impact from the minerals, the fracture of the beam and the crack of the lateral plate are easy to occur, which has a negative effect on the reliability of the equipment itself and the industrial production. Considering the essential high reliability of the equipment, a new large-scale vibrating screen with duplex statically indeterminate mesh beam structure (VSDSIMBS) was developed. The natural characteristics, namely, the natural frequency (or the modal frequencies) and the natural mode, and the dynamic characteristics of the VSDSIMBS were obtained by the modal analysis and the harmonic response analysis. In addition, the dimensions and the constructions of the statically indeterminate plate and the mesh beam were chosen as the design parameters, to which the sensitivity of the whole mass, the maximum deformation and the maximum stress of the duplex statically indeterminate mesh beam structure (DSIMBS) were summarized for the optimization of the DSIMBS. Now the large-scale VSDSIMBS is being well used in China.

Jan 1, 2014

By J. L. Bellanca, L. R. Swanson

DISCLAIMER The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. Mention of any company or product does not constitute endorsement by NIOSH. ABSTRACT Proximity detection systems (PDSs) for mobile machines have the potential to decrease injuries and fatalities. Early adopters of the technology have identified some challenges, which presents an opportunity to explore and improve the integration of mobile PDSs in underground coal mines. The current study applied the task-technology fit framework to investigate the fit between mobile PDS technology and mining relative to health and safety, from the perspective of leaders at two coal mines. Quantitative results from the study show that mine leaders evaluated mobile PDS favorably for training and ease of use, system feedback, user authorization and experience, and less favorably for safety, compatibility, task completion, and reliability. Qualitative results reveal specific task, mine, and system characteristics that may have influenced leaders' evaluations. The study includes considerations for safe technology integration. INTRODUCTION Striking, pinning, and crushing accidents related to mobile machines continue to be a major concern in underground coal mining. The National Institute for Occupational Safety and Health (NIOSH) linked 22 of the 75 underground mine fatalities reported between 2011 and 2015 to power haulage [1]. The Mine Safety and Health Administration (MSHA) asserts that proximity detection systems for mobile machines (mobile PDSs) could help to prevent these types of fatal injuries [2]. Mobile PDSs use a collision avoidance technology that allows the mine to establish hazard zones and employ electromagnetic sensors to detect workers equipped with a miner-wearable component (MWC) working near these mining machines. The authors characterize a mobile PDS as an automated technology, because—in line with Lee & See’s [3] definition of automation—a mobile PDS actively “selects data, transforms information, makes decisions, or controls processes” (p. 50). When the system detects workers in the established hazard zones, it issues alerts and slows or stops the mobile machine. Even though a mobile PDS may be a viable and promising safety solution, there are still a number of questions regarding how well this automated technology will fit with mining tasks and conditions. Using a mixed-methods approach, the current study explored factors that influence the fit of mobile PDSs in the underground mining environment.

Jan 1, 2019

By A. Bhattacherjee

Industries in general and the mining industry in particular have become more safe than ever before. However, there is a need to increase the search for the causes of mining work-related injuries and to contribute to their reduction through job design, work procedures, and worker training. Mine accident and hazard control has to be practiced in a manner which is consistent with the overall objectives of the mine management, among which are the optimum allocation and effective utilization of the resources. The purposes of this paper are to (i) review the role risk analysis in safety management with references from mining and other industries; (ii) discuss the risk measures appropriate for injury analysis; (iii) present a set of analytical tools to injury experience data in under-ground coal mines; (i v) apply these tools on case study example; (v) discuss the results of the case study; and (vi) amplify the application limitations and the future research needs.

Jan 1, 1991

By Yi Yang, Xiuzhu Su, Wei Sung Ng, Shuiping Zhong, Miao Chen

With over 260 tons of gold reserves, the Shuiyindong gold mine is one of the largest Carlin-type gold deposits in China. A particular challenge in the processing of the ore is the presence of carbonaceous compounds, which can cause substantial losses in recoveries via the preg-robbing and adsorption of gold. To investigate the structural properties of the native carbon and to compare between different characterization techniques for such compounds, pre- and post-flotation mineral samples containing 0.9–4.8% non-carbonate carbon from the Shuiyindong mine have been examined via mineralogical and thermogravimetric approaches, as well as spectroscopic techniques, including X-ray photoelectron spectroscopy (XPS), near-edge X-ray absorption fine edge structure spectroscopy (NEXAFS), solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy, Raman spectroscopy and preg-robbing measurements. NEXAFS and DRIFT yielded the most reliable results, indicating that 60–75% of the organic carbon in all samples consist of aliphatic alkenes with substantial unsaturated content, highly similar to activated carbon, with the remainder being graphitic and humic. Speciation by XPS was sub-optimal due to spectral overlaps between graphitic and aliphatic carbon, and between carboxylic and carbonate functionalities, while NMR spectroscopy could not provide reliable speciation of the carbon groups. The preg-robbing strength was strongly correlated to the aliphatic content and structural disorder in the carbon, while no such relationship was found with the graphitic and humic content.

Nov 29, 2021

By Paul Gottlieb

This paper reviews the status of automated applied mineralogy today and describes the history and fundamental theoretical and practical bases underpinning the development of automated systems. Details are given of the technical challenges that were faced in creating the new technology and in applying it to a range of applications. In recent years, automated mineralogy has become established as an essential enabling technology for the reliable acquisition of statistically sound comprehensive mineralogical and metallurgical data. This has had a revolutionary effect on the industrial use of such data in the study of geology, mining and mineral processing. Previously, using manual methods, it was not feasible to attempt this work because the large data sets required could not be assembled in a realistic timescale. There was a reliance on individual expert mineralogists and this was not scalable. The speed, reliability, detail and repeatability of the modern automated measurements has now made this type of analysis routine. Automated Applied Mineralogy has come of age! More than 100 systems have been installed around the World. Automated mineralogical analysers such as QEMSCAN® were originally developed as diagnostic metallurgical tools to improve mineral processing plants using samples drawn from plant surveys, bench and pilot-scale tests. They were used mainly for the assessment and auditing of size fractions of mill products, such as concentrates and tails. Subsequently, they began to be used for concentrator design and optimisation where ore characterisation was used to help understand the relationship between the feed ore and its subsequent behaviour in the plant. They are now widely used to measure exploration cores and drill chips from drilling programs to predict eventual metallurgical performance. Ore samples can be classified into metallurgical, as well as geological types, by combining mineralogical features in the ores with metallurgical properties related to grade control, separation, comminution, flotation and leaching behaviour. Three-dimensional block models of ore deposits are now being created based on processing response in addition to geological and mining properties. The development of automated systems began in Australia, the United Kingdom and Canada in the late 1970s and early 1980s. There were many technical challenges. Mathematical theories of randomness, sampling theory, image analysis and stereology were developed to ensure sample representivity so that meaningful information could be obtained. Sample preparation, presentation and measurement methods were developed to ensure that the random sampling was preserved during the measurements. Methods of automatic measurement and mineral identification evolved from the use of electron microscopes, fitted with backscattered electron brightness and energy dispersive X-ray detectors. Operational procedures were required to ensure that these instruments could accommodate a large number of samples and operate unattended for long periods of time. The new technology was progressively applied to a range of commodities and applications and new analysis methods, such as liberation measurement, were needed for metallurgical interpretation of mineralogical data.

Jan 1, 2014

By J. Paraszczak

Application of teleoperated and automated (or ?autonomous?) mobile equipment in underground metal mines is a promising avenue for overcoming some of the challenges facing mine operators. These include, but are not limited to, the issues related to safety and health of underground workers, better use of the shift time leading to increased productivity, skilled manpower shortages, and remoteness of some mine sites. Autonomous load-haul-dump machines and trucks offer several benefits over man-operated ones, but their use at their full capacity is a challenging and complex task. This paper makes an overview of commercially available equipment and systems and their applications. It examines factors affecting adversely availability, utilization, and production efficiency of autonomous vehicles and compares them to conventional man-operated machines. Technical and operational aspects are discussed and their criticality is analyzed. Based on that, recommendations concerning means and measures that may help raise operational effectiveness are given. It is stressed that due to a scarcity of publicly available information on the performance and cost of autonomous loading and haulage operations, more field studies and in-depth analysis are needed.

Feb 23, 2014

By Robert D. Thomson

The Bureau of Mines has compiled coal reserve data for the United States as of January I, 1974, for bituminous and anthracite coalbeds 28 inches or more in thickness to a maximum depth of 1,000 feet and for Lignite beds 40 inches thick or greater. These data were organized by State, county, coalbed, and rank. To evaluate the reserve by sulfur content, the reserve and analytical data from the Bureau of Mines energy data bank were synthesized using computer techniques. The reserve base in the Eastern States was determined to be 202.3 billion tons. Bituminous coal accounts for the greatest reserve base: 161.5 billion tons of deep-minable coal, and 32.5 billion tons of strip-minable coal. Virtually all of the anthracite reserve base, 7.3 billion tons, is minable by underground methods. All of the lignite, 1 billion tons, is strip minable. Subbituminous coal is not significant in the Eastern United States, About 14 percent of the bituminous coal reserve base, 26.5 billion tons, contains 1.0 percent or less sulfur. About 87 percent of the anthracite reserve base, 6.3 billion tons, is low-sulfur coal.

Jan 1, 1975