The SME Guide to ESG Resources

Cemented rockfill (CRF) is commonly used in conjunction with underhand cut-and-fill mining methods to provide ground support in weak rock mass conditions, particularly in the underground gold mines in Nevada (Seymour et al. 2013). The CRF supports the overlying material in the mine roof and also confines the surfaces of rock pillars and abutments, thereby enhancing their ground support capabilities. If the CRF is designed, batched, and placed properly, it typically provides a safe, stable back for the next undercut. However, as wider undercut spans are implemented, a better understanding is needed of the engineered properties of this material and also the design methods that are used to evaluate its performance (Pakalnis et al. 2005; Tesarik et al. 2007; Barnard and Sandbak 2017).

Increased use of underhand methods in the last 30 years has improved safety in many mines. However, with the continual drive for more efficient and cost-effective mining, there is a need to thoroughly understand the geotechnical properties of cemented fill so that safe, stable openings can be designed while optimizing costs and production schedules.

Fatigue presents several challenges for the mining industry. Depending on the specific occupation, daily work or operational setup on any given mine site, mining jobs can have a fair amount of labor-intensive tasks mixed with monotonous and repetitive duties. Combined with the long working hours and shift-work schedules of mining work, the prevalence of fatigue in mine workers may seem rather unsurprising.

This study characterizes physiological measures of heat exposure among US underground miners. Unlike previous heat stress research that reported only maximum and mean temperature measurements, this analysis demonstrates a dynamic pattern of physiologic heat strain, with core body temperatures changing frequently and exceeding the 38 °C limit multiple times per shift.

Each year, hundreds of mine workers are involved in machinery-related accidents. Many of these accidents involve inadequate or improper use of lockout/tagout (LOTO) procedures. To mitigate the occurrence of these accidents, new safety methods are needed to monitor access to hazardous areas around operating machinery, improve documentation/monitoring of maintenance that requires shutdown of the machinery, and prevent unexpected startup or movement during machine maintenance activities. The National Institute for Occupational Safety and Health (NIOSH) is currently researching the application of Internet of Things (IoT) technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program.

Miners and OGE workers had higher prevalence estimates than both nonmanual and manual labor workers for all health risk factors except current smoking. Both miners and OGE workers were significantly more likely than other manual labor workers to report smokeless tobacco use and not always wearing seatbelts. Compared with other manual labor workers, OGE workers were significantly more likely to report obesity, and miners were significantly more likely to report inadequate sleep.

EXAMiner allows mineworkers to search for hazards by performing a virtual workplace examination with the goal of finding as many hazards as possible. The interactive PC-based application can be used with the 30-plus preloaded images of scenes from four locations at a stone surface mine-in the pit, at the plant, in the shop, and along mine roadways-or trainers can upload their own panoramic images.

The software was designed to be used by trainers during Part 46 annual refresher training, quarterly training meetings, or pre-shift toolbox talks.

There are two options to create a training session: 1.Choose scenes created by NIOSH and have mineworkers perform a virtual examination at one of four locations at a surface stone mine. These include the pit, at the plant, in the shop, and along haul roads and other mine roadways. 2.Import your own panoramic pictures to create customized site-specific scenes to use as training materials at any type of mine, in any sector. This provides the capability to create training materials that address specific hazards your mineworkers are encountering in the workplace. This provides the ability to continually add content to the software, importing as many panoramic pictures as are available to address the changing needs of your mineworkers.

After completing a workplace examination, mineworkers receive feedback on their performance and are provided additional information to reinforce their knowledge of mine site hazards.

The extraction, transport, and processing of coal produces respirable-sized dust that can be inhaled by miners and cause disabling and potentially fatal lung diseases known as coal workers' pneumoconiosis (CWP, commonly called "black lung") or silicosis. Once contracted, there is no cure for these lung diseases, so prevention is the goal. Since 1970, NIOSH has offered health screenings to underground coal miners to identify CWP in individuals and to track CWP prevalence across the industry. After an initial 30-year downward trend, CWP prevalence has been increasing over the last 20 years.

Coal dust particles larger in size than respirable dust, known as float coal dust, are also produced during mining. Float coal dust settles out of the ventilating air onto the floor, ribs, and roof of underground mining entries. This dust can be lifted back into the air from these surfaces to fuel powerful explosions which have contributed to numerous fatal mine disasters.

To address these issues, coal mine operators search for and implement control technologies that limit worker exposure to respirable dust and minimize the deposition of float coal dust. The controls discussed in this second edition of this handbook range from long-utilized controls that have developed into industry standards to emerging controls that continue to be researched.

The handbook is divided into six chapters. Chapter 1 discusses the health effects of exposure to respirable coal and silica dust. Chapter 2 discusses respirable dust sampling instruments and sampling methods. Chapters 3, 4, and 5 focus on respirable dust control technologies for longwall mining, continuous mining, and surface mining, respectively. Chapter 6 discusses float coal dust sampling and control technologies.

Respirable crystalline silica (RCS) exposure occurs in many industries and the potential health effects of RCS have been well-documented. Monitoring is an essential part of any RCS exposure control plan but the timeliness of data from the lab and the cumulative cost of analysis may limit the extent and the effectiveness of the monitoring process. Field-based monitoring procedures offer a supplement to sample analysis completed by an off-site laboratory. By eliminating the time spent transporting samples and waiting for laboratory results, results are available the same or next day to allow operators to make decisions regarding controls. This enhances the ability to collect data more effectively, enables better control over potential exposures, and protects worker health.

The FAST (Field Analysis of Silica Tool) software processes raw Fourier transform infrared (FTIR) data from a field-based instruments and calculates an RCS mass and concentration estimate for each sample. The results can contribute to decision-making to decrease worker exposure to RCS. Field-based monitoring and FAST can be used by anyone with an interest in evaluating RCS exposure but it is primarily intended for industrial hygienists and other workers with health and safety responsibilities, specifically within the mining industry (although workers in other industries will also find it useful). No specialized training in analytical techniques is necessary.

Important Note for FAST users: FAST is designed to work in concert with an easily implemented monitoring approach developed by NIOSH which uses portable FTIR analyzers and dust sampling cassettes at the mine site. As detailed in the software guide, RCS results from this initial release of FAST are accurate if a sample is collected in a coal mine. Choosing a commodity prefixed with the type "other" means that no adjustments are made for other minerals that might be present in addition to crystalline silica.

Therefore, for samples collected in mines other than coal, the results should be considered as approximations. The possible presence of other minerals may decrease the accuracy of the quantification model, and the true result may be greater or less than the approximation. Future releases of FAST will offer improved accuracy for commodity types besides coal.

The purpose of these Toolbox Talks is to provide information related to workplace hazards and risks to workers at Stone, Sand, Gravel, and Aggregates (SSGA) operations. This information can be used to increase workers' health and safety. This series of Toolbox Talks was created using data from two sources: interviews with SSGA mine workers about hazards and risks at their worksite, and nonfatal and fatal injury data reported to the Mine Safety and Health Administration (MSHA) during the years 2009-2014. Each Toolbox Talk includes a quote from a mine worker to demonstrate a first person experience with a hazard or risk. This first person experience is then linked to MSHA injury data to show that these experiences are consistent with the realities of accidents, injuries, and fatalities. Finally, several questions are included that can be used to start a discussion about a specific Toolbox Talk topic - for instance, questions for the slips and falls topic are focused on having mine workers identify where slips and falls are likely to occur at their mine site and ways mine workers can protect themselves from slip and fall injuries. Altogether there are 13 talks included in this series.

To advance a more tangible understanding of health and safety climate in the U.S. mining industry, the National Institute for Occupational Safety and Health (NIOSH) surveyed members of mining workforces about experiences at their respective mine operations. The survey measured four personal (i.e., risk tolerance, thoroughness, sense of control, and adaptability) and six organizational (i.e., organizational support, supervisor support, supervisor communication, coworker communication, worker engagement, and training) constructs to determine significant influences on health and safety (H&S) performance, which was measured in the form of worker proactivity, compliance, and reported near misses or other incidents. This report, unlike other safety climate reports, focuses on individual perceived safety climate [Neal and Griffin 2006] versus crew-based approaches to such assessments.

Participants consisted of 2,683 workers-both salaried and hourly-at 39 mine sites throughout 17 states. The mines represented nine major companies and three mining subsectors (coal, stone, sand, and gravel, and industrial minerals). This report analyzes, assesses, and presents data about these safety climate constructs to help those who manage companies, mine organizations, or groups of workers, to develop, target and improve, or implement parts of a health and safety management system (HSMS) to support workers' H&S performance while reducing the likelihood of workplace incidents.

A video tutorial describing the use of NIOSH developed software called EVADE. EVADE matches up recorded video and logged data to identify potential health exposure risks. The video comes from a worker-mounted camera and the logged data comes from a personal assessment monitor used to measure either dust, noise, diesel, or chemical exposure. This tutorial shows where to access and download this free software, and then how to create, save, and perform a basic exposure assessment using the software.

A numerical-model-based approach was recently developed for estimating the changes in both the horizontal and vertical loading conditions induced by an approaching longwall face. In this approach, a systematic procedure is used to estimate the model's inputs. Shearing along the bedding planes is modeled with ubiquitous joint elements and interface elements. Coal is modeled with a newly developed coal mass model. The response of the gob is calibrated with back analysis of subsidence data and the results of previously published laboratory tests on rock fragments. The model results were verified with the subsidence and stress data recently collected from a longwall mine in the eastern United States.

The 2007 United States Mine Safety and Health Administration (MSHA) database reported 217 knee injuries in underground coal. From workers' compensation data, the National Institute for Occupational Safety and Health (NIOSH) determined that the average cost per knee injury in this industry was $13,121.29 yielding nearly three million dollars as an estimated financial burden of these injuries on the industry in 2007. (1) Recently, NIOSH has investigated various types of interventions that underground coal mining companies may implement as means of decreasing mine workers' risk for developing knee injuries. To encourage mining companies to implement this training program and interventions currently in development, NIOSH performed an analysis of workers' compensation data for one underground coal mine in Illinois and six in Pennsylvania. The data were for the 2004, 2005, and 2006 claim years of each mine and included medical and indemnity costs for injuries to each body part, the number of injuries per body part, and the annual audited payroll. The rating formulas for the respective states were utilized to determine workers' compensation premiums for 2008 which require injury data from 2004 to 2006. For each mine, the costs of workers' compensation premiums were determined with all the injuries reported. A second analysis was then performed whereby all knee injuries were excluded. By eliminating knee injuries, the annual workers' compensation premiums decreased by 1.1% to 16.2% depending on the mine's size and injury statistics. The savings that were observed ranged from $4,206, a 1.3% savings, to $1,454,767, a 6.4% savings. The cost of implementing the NIOSH recommended interventions is minimal; therefore, an overall savings for the mine would be expected.

In 2013, the National Research Council (NRC) issued the consensus study report, Improving Self-Escape from Underground Coal Mines (National Research Council, 2013; available at https://www.nap.edu/login.php?record_id=18300External). The NRC report (p. 2) defined self-escape in the event of a mine emergency as "the ability of an individual or group of miners to remove themselves from the mine using available resources," and called for detailed task analysis of self-escape to describe self-escape behaviors and required capabilities, knowledge, and skills.

In response to this report's recommendation, the Centers for Disease Control (CDC) and The National Institute for Occupational Safety and Health (NIOSH) funded work to accomplish a detailed task analysis. The scope of this project was bounded between (a) miners making the decision on their own or based on notification by coworkers or mine management of the need to evacuate due to a hazardous situation, and (b) completed self-escape at exit from the underground mine. The goals of this effort were two-fold: (1) to produce a set of specific recommendations to facilitate self-escape that would reduce task demands to operate within individual cognitive capabilities; (2) to facilitate and optimize human performance in meeting task demands, and increase the likelihood of success through eliminating tasks, redesigning tasks to reduce differences between task demands and individual capability, or improving human performance through better training and/or assistive tools and technology.

The project consisted of four phases, and the current paper focuses on the cognitive task analysis (CTA) work done in Phase 4. During Phase 1, we developed data collection protocol and materials and secured NIOSH Institutional Review Board approval and clearance from the U.S. Office of Management and Budget (OMB), which is required to collect data from persons outside the government. In Phase 2, we identified self-escape tasks, organized them into categories, and identified which tasks are critical to successful escape. In Phase 3, we performed hierarchical task analysis recommendations development. Finally, in Phase 4, we performed a CTA to describe thought-based components of escape, particularly information sharing, goal setting, planning, and decision-making, and developed results-based recommendations.

This infographic on fall protection helps workers identify three essential steps to take when using a personal fall arrest system: select and inspect, put on, and tie off. The body text details these steps and components, and the top and bottom banners provide data from the Mine Safety and Health Administration (MSHA) to support how important the proper use of fall arrest systems is to safety. Depending on their duties, mine personnel commonly have the need to use fall protection at work, and this infographic is designed to give them critical tips that will be easy to remember and easy to implement. For Spanish speakers, download the same infographic with text in Spanish PDF.

This study was developed as part of an effort by the National Institute for Occupational Safety and Health (NIOSH) to better understand rock-mass behavior in longwall coal mines in highly stressed, bump-prone ground. The floor-heave and no-floor heave phenomena at a western U.S. coal mine cannot be properly simulated in numerical models using conventional shear-dominant failure criteria (i.e., Mohr-Coulomb or Hoek-Brown failure criterion). Kim and Larson (2019) demonstrated these phenomena using a user-defined model of the s-shaped brittle failure criterion in conjunction with a spalling process in FLAC3D.

Researchers from the National Institute for Occupational Safety and Health (NIOSH) have been conducting research with the goal of gaining a better understanding of ground stress redistribution resulting from mining. Part 1 of this research involves representing stress redistribution using empirical equations or numerical models that are calibrated to observations and measurements.

Numerical models are used to evaluate mine layout design to establish better procedures for predicting ground stress in mining to identify safe and unsafe working areas and escapeways. Current published guidance by the Mine Safety and Health Administration (MSHA) recommends an approach to calibrating models to observations, but it does not include recommendations for using in situ measurements to calibrate such models. A specific goal of this research is to explore and demonstrate procedures for calibrating numerical models to both observations and measurements.

Underhand cut-and-fill mining has allowed for the safe extraction of ore in many mines operating in weak rock or highly stressed, rockburst-prone ground conditions. However, the design of safe backfill undercuts is typically based on historical experience at mine operations and on the strength requirements derived from analytical beam equations. In situ measurements in backfill are not commonplace, largely due to challenges associated with instrumenting harsh mining environments. In deep, narrow-vein mines, large deformations and induced stresses fracture the cemented fill, often damaging the instruments and preventing long-term measurements.

The National Institute for Occupational Safety and Health (NIOSH) conducted a research study to document and develop safe practices for the use of shotcrete as ground support in underground mines, particularly in underground metal mines operating in weak host rock. Shotcrete is the generic name for a mixture of cement, sand, fine aggregate, and water that is applied pneumatically and compacted dynamically under high velocity. The objective of this research is to reduce mine worker fatalities and injuries resulting from rockfall accidents. Although the information, techniques, and technology covered in this publication will impact both the mining and construction sectors, the primary audience is the mining industry with a focus on underground metal mines operating in weak ground conditions.

Gaining an SLO and achieving ESG both require immediate direct and local intervention, ideally before sending in an exploration team or deciding to develop a project. Understanding what social risks and challenges the company faces and what issues matter to the community are vital to the success of a mining project. The best way to accomplish this immediate direct and local interaction is by conducting grassroots mining legal diagnoses and SLO diagnoses. Mining legal diagnoses seek to identify legal risks faced by a company's endeavors. An SLO diagnosis is a tool that will provide a basis for "doing the right thing" for all stakeholders impacted by a project.

Ausbil Funds Management dropped Rio Tinto from Ausbil's $30 million sustainable equity fund because of severe backlash against Rio Tinto following the destruction of the 46,000-year old cultural site at Juukan Gorge in Western Australia.

While a social license to operate is already one of the biggest challenges facing the mining industry, maintaining an SLO is getting harder. Part of the reason is growing community empowerment. Local residents are increasingly willing – and able – to demand a say on mining projects and a bigger share of the spoils, drawing support from legal and social media-savvy NGOs and local politicians.