Mine In Queensland Research Articles

The Value of Drilling—A Chance-Constrained Optimization Approach

Managing uncertainty is a core challenge in mine planning. Mine planners often represent various planning variables, such as equipment performance and geological parameters, as random variables due to inherent uncertainties. This paper looks at geological uncertainty and its impact on mine planning. Some traditional approaches to manage this uncertainty include using conditional simulations or mathematical programming in the planning process. Drilling additional holes, despite its cost, is a common method to reduce uncertainty using additional samples to reduce deposit variance. In this paper, we first outline an ore blending optimization model which uses chance-constrained programming to manage property limit risk when selecting the order of ore feed into a processing facility. In coal mining, in tactical planning horizons, the order of coal seam removal is usually predetermined, allowing a blending model to ensure optimal feed properties. Using chance-constrained programming allows us to blend the uncertainties from geological models to maximize plant output while adhering to property constraints. We use the chance-constrained blending model to determine the value of additional information from infill drilling. The model prioritizes drilling locations that reduce uncertainty and improve blending outcomes. A case study on a coking coal mine in Queensland, Australia, demonstrates the model’s application, highlighting significant improvements in blending by reducing the variance of high-quality blocks. The study concludes that targeting high-quality blocks for variance reduction can better accommodate lower-quality material, offering a more valuable approach than the traditional focus of reducing uncertainty in low-quality blocks. This approach provides insights for improving mine planning strategies and showcases the potential of chance constraints in optimizing ore blending under uncertainty.

Rural and regional homelessness in Queensland mining communities: Implications for rethinking the housing and homelessness policy landscape

Rural homelessness has largely been silenced in homelessness narratives and social policy in Australia and throughout the world. This paper reports on data from a larger qualitative study about homelessness in rural and regional Central Queensland mining communities located within the Bowen Basin region, inland from Australia's eastern seaboard. Semi-structured, qualitative interviews and focus groups were conducted with people who had lived experience of homelessness in the rural mining communities of Mackay (regional), Moranbah and Dysart (rural), and service provider representatives and community advocates. The qualitative analysis revealed that people experience homelessness in rural and regional communities in unique ways that are different to metropolitan constructions of homelessness. This research identified rural and regional poverty, the nature of boom or bust economies, over-stressed human service providers, social isolation and lack of affordable housing as factors contributing to homelessness in rural and regional mining communities. This paper highlights the urgent need for more scholarly research to inform and promote more critical social policy approaches that frame homelessness as a public policy priority in rural and regional mining communities.

The 'Mine Medical': an opportunity for preventative and primary care.

For many rural and remote regions of the world, the resources sector forms a necessary part of the local economy. Many workers and their families live in the local community and contribute to the social, educational and business fabric of that community. More still fly into rural areas where medical services exist and are required to support them. Australian coal mines require that all workers undertake a periodic medical examination to assess their fitness for their duties and to monitor for specific diseases inclusive of respiratory, hearing and musculoskeletal conditions. This presentation contends that the 'mine medical' is an untapped opportunity for the primary care clinician to gather data about the health of the mine employees and to understand, not only their health status, but also the incidence of preventable diseases. This understanding may assist a primary care clinician to design interventions for coal mine workers at a population and individual level that will improve the health of communities, while reducing the burden of avoidable disease. In this cohort study, 100 coal mine workers, working in an open cut coal mine in Central Queensland, were examined to the Queensland coal mine workers medical standards, and their data recorded. The data were then deidentified, apart from the principal job role, and collated against measured parameters including biometrics, smoking, alcohol consumption (audit), K10, Epworth Sleepiness Score, spirometry and chest X-ray imaging. At the time of submission of the abstract, data acquisition and analysis is continuing. Preliminary data analysis reveals higher levels of obesity, poorly controlled blood pressure, elevated blood sugar levels and chronic obstructive pulmonary disease. The author will present their findings of the data analysis and discuss formative opportunities for intervention.

Stress-strain behaviour of unsaturated compacted coal rejects and tailings

The paper presents the results of an experimental study aimed at evaluating the stress-strain response of unsaturated tailings (Mixed Plant Reject and Dewatered Tailings) from a mine in Queensland, Australia, which can be applied to further optimise current tailings disposal strategies of the mine. Triaxialtests at constant gravimetric water content were performed on specimens prepared at different compaction states using dynamic and static methods, to determine their shear strength. The dynamically compactedspecimens display a higher strength than that statically compacted ones, which highlights the significance of stress history for tailings strength. As-compacted and post-testing suction measurements, performed using a high-capacity tensiometer, showed a reduction in matric suction irrespective of the material type, which is caused by mechanical wetting. The strength envelope was found to be non-linear, partly because of suction changes during testing. Post-testing suction measurement showed spatial variability within each specimen, with the central part of the samples experiencing the maximum suction reduction. The paper concludes with a discussion on the interpretation of such results.

The finch in the coal mine: Interrogating the environmental politics of extinction narratives

AbstractThe black‐throated finch is an endangered species whose highest quality remaining habitat directly overlaps with the site of the controversial Adani Carmichael coal mine in Central Queensland, Australia. The image of this finch has been widely used by anti‐Adani protest groups as a powerful symbol for the destructive nature of greenfield coal mining. Drawing on extinction studies literature, we problematise the use of the black‐throated finch as a symbol of imminent extinction, highlighting how activists have constructed a fixed finch on‐the‐brink ontology that narrows possible futures for the species. We identify how the finch has been strategically deployed as an affective tool for engaging publics while the anti‐Adani campaign has been primarily driven by concerns around climate change futures. We use primary sources of anti‐Adani ephemera as well as interviews with key scientists, activists, and image‐makers involved in the debate about the Carmichael coal mine. We argue that critical evaluation of the effects and potential consequences of simplified environmental activist narratives and the instrumentalisation of nonhumans is needed to support and enable activism that centres care and responsibility within multispecies entanglements. Engagement with the complexities of environmental intervention in relation to the finch, and not exclusively the mine, is also necessary to locate openings through which more‐than‐human futures can be creatively imagined and enacted.

Characterization Analysis of Airborne Particulates from Australian Underground Coal Mines Using the Mineral Liberation Analyser

Exposure monitoring and health surveillance of coal mine workers has been improved in Australia since coal workers’ pneumoconiosis was reidentified in 2015 in Queensland. Regional variations in the prevalence of mine dust lung disease have been observed, prompting a more detailed look into the size, shape, and mineralogical classes of the dust that workers are being exposed to. This study collected respirable samples of ambient air from three operating coal mines in Queensland and New South Wales for characterization analysis using the Mineral Liberation Analyser (MLA), a type of scanning electron microscope (SEM) that uses a combination of the backscattered electron (BSE) image and characteristic X-rays for mineral identification. This research identified 25 different minerals present in the coal samples with varying particle size distributions for the overall samples and the individual mineralogies. While Mine 8 was very consistent in mineralogy with a high carbon content, Mine 6 and 7 were found to differ more significantly by location within the mine.

Rapid assessment of mine rehabilitation areas with airborne LiDAR and deep learning: bauxite strip mining in Queensland, Australia

Rehabilitation of disturbed sites is a complex process requiring constant monitoring and assessment, with current methods being somewhat obsolete, manual, and rather fraught with risk in terms of beneficial outcomes of the evaluation. This study challenges the status quo of manual assessments and build a new methodology to recognise a clear need for a quasi-automated and reliable remote sensing method to achieve rapid mine rehabilitation monitoring. The aim of this study was to innovate and develop an ensemble analytic methodology for the use of airborne LiDAR, in conjunction with deep learning, to rapidly evaluate the rehabilitation status of post-mined areas. Airborne LiDAR datasets, obtained via an Optech ORION m/c 200 sensor, were collected over bauxite mining operations on the western coast of Cape York Peninsula, Queensland, Australia. These datasets were processed into a 3 D point cloud using the Esri ArcGIS Pro platform. An ensemble analytical approach was developed, leading with a Convolutional Neural Network (CNN) algorithm, which was trained to recognise, then classify images of the reference site (natural ecosystems) and active rehabilitation areas. The result of this classification was then leveraged, training in turn a support vector machine (SVM) algorithm which assessed the entire LiDAR collection, resulting in a predictive surface of rehabilitation status. This surface, as the final analytical product, was assessed for validity using ground-truth plot data and an ordinary least squares regression model, as well as comparison to subject matter expert evaluation through a Delphi expert panel assessment. The results indicate that the predictive surface, as the final analytical product, had statistically significant correlation coefficient with multiple attributes (or predictor) that correlated with the rehabilitation status interpretation. These predictor variables were primarily structural in nature and included the canopy height, sub-canopy height, key species as a proportion of canopy, herbaceous ground cover percentage, litter ground cover percentage, and distance from haul road (p < 0.05). A Delphi expert collaboration comprised of ten environmental science subject matter experts and 600 observations, indicated a high precision (r = 0.89 at p < 0.05) of the prediction surface when compared with a subject expert panels assessment, as well as a high Total Deviation Index (TDI) of 16% (p < 0.05). This indicated positive agreement between the panel’s assessment and the predictive surface. This study suggests that airborne LiDAR and deep learning ensemble analytics can be used as a rapid means to estimate the rehabilitation status of disturbed sites.

Mapping the Morbidity Risk Associated with Coal Mining in Queensland, Australia.

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.

Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations.

Two years of satellite observations were used to quantify methane emissions from coal mines in Queensland, the largest coal-producing state in Australia. The six analyzed surface and underground coal mines are estimated to emit 570 ± 98 Gg a-1 in 2018-2019. Together, they account for 7% of the national coal production while emitting 55 ± 10% of the reported methane emission from coal mining in Australia. Our results indicate that for two of the three locations, our satellite-based estimates are significantly higher than reported to the Australian government. Most remarkably, 40% of the quantified emission came from a single surface mine (Hail Creek) located in a methane-rich coal basin. Our findings call for increased monitoring and investment in methane recovery technologies for both surface and underground mines.

In situ flexural failure of unbonded fibre reinforced shotcrete linings in response to point loading

In shotcrete lining design there are a number of analysis methods available to estimate the ultimate point load resistance. However, little experimental evidence is available to confirm the validity of these estimates. To address this deficit, a series of full-scale load tests were undertaken on macro-synthetic fibre reinforced shotcrete (MSFRS) linings constructed in an underground coal mine in Queensland, and steel fibre reinforced shotcrete (SFRS) linings constructed as part of a tunnel project under construction in Sydney, Australia. Areas of lining were tested to destruction to identify the point load resistance. All the tests reported in this paper involved predominantly flexural failure of the shotcrete lining.The tests comprised regions of ∼70–100 mm thick FRS lining with bolts placed orthogonally at ∼1000–2500 mm centres. Load was applied using an inflatable lifting bag with a load capacity of about 500kN and maximum displacement capacity of 150 mm. Although the FRS used in the trials displayed post-crack strain-softening behaviour in accompanying ASTM C1550 tests, all the in situ tests resulted in strain-hardening behaviour with no evidence of a dip in load resistance upon cracking of the concrete matrix. The peak load resistance was many times greater than the load resistance measured at first crack, which was confirmed with numerical and analytical modelling. Substantial post-peak ductility was noted in all the tests.

Homelessness and domestic and family violence in Queensland mining communities: The experiences of women and families accessing safe and affordable housing

Increasingly scholars across the world are developing sophisticated approaches to understanding the impacts of homelessness and domestic and family violence (DFV) for women and women headed families. This paper reports on qualitative research undertaken in Queensland mining communities about the experiences of women and their families who have experienced homelessness due to family breakdown or DFV. This paper presents a subset of data from a larger study with a specific focus on an analysis of five women's experiences, including some data from interviews with homelessness service providers and community representatives. This research provides a regional and rural frame of reference for understanding structural factors affecting women and families experience of homelessness and domestic and family violence. The paper concludes with a discussion of two key recommendations. These are (1) Improving access to safe and affordable housing for women and families in mining communities and (2) strengthening social planning to address women's safety and housing needs in these communities.

Biologically facilitated precipitation of metals in low-Fe waters at the sulphidic Mount Chalmers mine, Queensland, Australia

Biofilms enriched in copper and zinc have formed at the aqueous-air interface and in subaqueous environments at the abandoned Mount Chalmers volcanic-hosted massive sulphide mine in Queensland, Australia. Remedial activity on site has limited acid mine drainage and associated iron-rich discharges, and surface waters leave the site at pH ~ 7. Unlike in many other oxygenated metal-sulphide environments, (bio)precipitates at this site conspicuously lack iron and manganese. Hence, this site provides an opportunity to observe the interactions of microorganisms with other metals, unobscured by the usually dominant Fe and Mn processes. Small subunit rRNA gene sequencing analyses suggest that biofilms are dominated by neutrophilic species of moss, diatoms, fungi and rotifera, as well as minor cyanobacteria and photosynthesising microorganisms adapted to high metal loads (e.g., up to ~ 8 mg/L Zn and ~ 2 mg/L Cu) in surface waters. Microbial communities formed metal-bearing biofilms on a time-scale of months. Investigations of these biofilms using scanning electron microscopy with electron dispersive x-ray spectroscopy and synchrotron-based X-ray fluorescence microscopy indicate that biofilms are intimately associated with metals, especially Cu and Zn, with Cu concentrations of up to ~ 20 wt%. Microorganisms on site help to catalyse dissolution and precipitation processes, although abiotic precipitation and anthropogenic intervention (raised pH) are the main geochemical drivers of remediation. Our observations suggest that microorganisms catalysed metal accumulation processes by (1) providing a substrate to which metals can attenuate during wetting and drying cycles and (2) micro-fossilisation induced by microorganism-metal interactions. This site provides a unique view of the impacts of rehabilitation processes on the microbial community, and vice versa. However, small numbers of bacteria that can contribute to acid mine drainage remain in the biome, ready to proliferate should remediation activities wane. Processes identified at this site are also relevant for potentially economic, enhanced metal extraction from legacy mine sites.

Sustainability of beef production from brigalow lands after cultivation and mining. 2. Acland Grazing Trial pasture and cattle performance

Context Agricultural land used for open-cut coal mining in Queensland is required by law to be returned to a safe, stable and self-sustaining state for agriculture. Aims The aim of this research was to identify whether rehabilitated pastures on post-mine soil at a site near Acland could viably support cattle production. Methods Five years of field data from Botanal pasture assessments, pasture quality, cattle liveweights and faecal observations, plus supplementary cattle liver data, were used to compare pasture and cattle performance from mined and unmined previously cultivated brigalow land. Subtropical pasture species were sown in 2007 (Rehab1, 22 ha), 2010 (Rehab 2, 32 ha) and 2012 (Rehab3, 22 ha) in three rehabilitated paddocks and in 2012 in an unmined (Control, 21 ha) paddock. The paddocks were grazed for 117–190 days of each year by Angus cattle. Key results Mean total standing dry matter in grazed pasture over the five trial years was consistently higher in Rehab 2 (5656 kg/ha) than in the other paddocks. Rehab 1 (3965 kg/ha) and Rehab 3 (3609 kg/ha) performed at an intermediate level and the Control paddock produced less pasture (2871 kg/ha). Grass leaf crude protein was higher in Rehab 2 than in the other paddocks and declined significantly (P &lt; 0.001) across all paddocks as pasture aged. Pasture species remained perennial, palatable and productive in all paddocks; however, pasture yield, quality and composition trends over time suggested that pasture rundown occurred across all paddocks. The mean liveweight gain (LWG) per head when grazing the trial paddocks (trial LWG) was higher (P &lt; 0.05) in the Rehab 2 cohort than the other paddock cohorts in Years 3 and 5, and trial LWG in the Control cohort was not significantly (P &gt; 0.05) different from one or more of the rehabilitated paddock cohorts each year. Cattle production per hectare during the trial grazing periods was also consistently highest in Rehab 2 (5-year mean trial LWG 131 kg/ha) compared with the other paddocks (67–80 kg/ha). Conclusion The rehabilitated pastures in use by the mine were considered at least as productive as the surrounding unmined brigalow landscape. Implications The Acland rehabilitation process was considered successful in establishing pastures that were able to viably support cattle production.

Sustainability of beef production from brigalow lands after cultivation and mining. 1. Sown pasture growth and carrying capacity

Context New Acland coal mine in south-eastern Queensland is seeking to rehabilitate mined land to pastures that are safe, stable and sustainable for beef production. Little is known of the productivity and sustainability of grazing previously mined land in the Darling Downs study region. Additionally, information is required to specify management guidelines for sustainable grazing of regional land types retired from cultivation. Aims Identify pasture growth characteristics, rainfall use efficiencies and long-term carrying capacities of subtropical sown pastures established on lands rehabilitated after open-cut coal mining in comparison to sown pastures established on un-mined but previously cultivated lands. Methods Pasture growth and quality (% nitrogen) were observed using the Swiftsynd methodology in ungrazed exclosures with three sites on rehabilitated lands of the Acland Grazing Trial over a 5-year period (2014–2018), and 13 sites on unmined lands over periods of 2–5 years providing data for modelling pasture growth. Key results Peak pasture yield (TSDM for autumn harvests) averaged for 2017 and 2018 was greater (P &lt; 0.1) on rehabilitated sites than unmined Poplar Box land type sites (5957 and 2233 kg/ha respectively) but similar to Brigalow Uplands and Mountain Coolibah land type sites (3946 and 3413 kg/ha respectively). Pasture rundown was evident, with pasture N uptake decreasing over 5 years at some sites. Soil mineral N supply (potentially mineralisable N and mineral N) in spring was a useful indicator of N uptake over the following growing season. Simulations using the GRASP pasture growth model for the grazing trial period predicted rainfall use efficiencies of 12.0, 7.0, 9.1 and 4.8 kg/ha.mm rainfall for rehabilitated sites and unmined sites on Brigalow Uplands, Mountain Coolibah and Poplar Box land types respectively. Long-term carrying capacities based on estimates of long-term median pasture growth and 30% utilisation were 4.39, 3.58 and 5.92 ha/adult equivalent respectively for the unmined land types, and 2.45 ha/adult equivalent for the rehabilitated lands. Conclusions Rehabilitated land can be as productive as unmined but previously cultivated land. Implications Grazing management plans for sustainable management of mined and unmined lands can be developed using data from the present study. The plans will assist with the transition of rehabilitated lands to commercial agriculture.

What localizes beneath: A metric multisensor localization and mapping system for autonomous underground mining vehicles

AbstractRobustly and accurately localizing vehicles in underground mines is particularly challenging due to the unavailability of GPS, variable and often poor lighting conditions, visual aliasing in long tunnels, and airborne dust and water. In this paper, we present a novel, infrastructure‐less, multisensor localization method for robust autonomous operation within underground mines. The proposed method integrates with existing mine site commissioning and operation procedures and includes both an offline map‐building process and an online localization algorithm. The approach combines the strengths of visual‐based place recognition, LIDAR‐based localization, and odometry in a particle filter fusion process. We provide an extensive experimental validation using new large data sets acquired in two operational Australian underground hard‐rock mines (including a 600m‐deep multilevel mine with approximately 33 km of mapping data and 7 km of vehicle localization) by actual mining vehicles during production operations. We demonstrate a significant increase in localization accuracy over prior state‐of‐the‐art SLAM research systems and real‐time operation, with processing times in the order of 10 Hz. We present results showing a mean error of 0.68 m from the Queensland Mine data set and 1.32 m from the New South Wales Mine data set and at least 86% reduction in error compared with prior state of the art. We also analyze the impact of the particle filter parameters with respect to localization accuracy. Together this study represents a new approach to positioning systems for currently deployed autonomous vehicles within underground mine environments.

An examination of house price movements in Queensland resource communities

ABSTRACT Successive mining “booms” have created wide-ranging, long-term socioeconomic impacts in many parts of Australia. Property markets were both directly and indirectly affected by the mining booms. Towns associated with mining activities experienced significant, rapid shifts in supply and demand levels for housing as well as changes to the amount and type of development occurring. The most recent “mining boom” in Queensland impacted on housing market dynamics, with impacts evident at all stages of the resource cycle. Housing markets were also indirectly affected by new actors and new drivers for buying property in these markets – as an investment. This paper aims to show that the “mining boom” was only one stage of a more complete cycle, and the impacts of this resource cycle on housing were particularly nuanced. Even in the short term, the importance of housing market stability-particularly measured through availability and affordability is important to the wellbeing of a town, and the underlying community. During the most recent cycle, housing markets in Queensland mining towns were uniquely affected.

Development of Digital Subterranean Models for Real-Time Open Cut Horizon Control

A reliable coal seam sensing system is required to improve the productivity of selective mining in open-cut mining operations. A prototype system based upon commercial ground penetrating radar equipment, which measures coal thickness from the top of an exposed surface down to an underlying coal-interburden interface and generates digital subterranean models of the subsurface seam boundaries, was developed for this purpose. The models can be deployed to commercially available in-cab assistive guidance systems for bulldozers and other mining machinery in existing production processes, and can further contribute to the databases required for remote operation and control in a complete digital mine scenario. The system was evaluated at a production open cut coal mine in Queensland, Australia, with promising results. The benefits reported by operational personnel who evaluated the digital surface model in the mining environment provide strong motivation for ongoing technology development.

Economic and social indicators between coal mining LGAs and non-coal mining LGAs in regional Queensland, Australia

Coal mining is deemed beneficial for the national economy, although it might not be the case at regional level. Main benefits from coal mining at national level include exports, government royalty, employment, and income. At regional level, coal mining can increase stress not only on the environment but also on public services, housing, and job markets. Little is known on whether coal mining brought positive changes to the regions over time.This paper examines selected socio-economic indicators between coal mining and non-mining local government areas (LGAs) in Queensland, Australia. This study differs from other research in three important ways. First, this study is focusing on coal mining activities, instead of the overall mining sector, and focusing on regional Queensland. Coal mining is the largest contributor to the total direct expenditure of the minerals and energy sector in Queensland. By limiting the observations to LGA level in one state, which is Queensland, this study has advantage of fewer confounding factors that are correlated with each other such as institution and political environment. Second, this study examines the effect of coal mining through the business cycle of expansion, downturn, and recovery by employing census time-series data for about one decade, starting 2006 up to 2016. Therefore, this study provides a better understanding of the effect of coal mining over time. Third, this study looks at socio-economic indicators that are less discussed in the regional development literature in relation to mining impacts such as housing, low income, and public service indicators.

Improving Coal Quality Estimations with Geostatistics and Geophysical Logs

In most modern coal mines, there are many coal quality parameters that are measured on samples taken from boreholes. These data are used to generate spatial models of the coal quality parameters, typically using inverse distance as an interpolation method. At the same time, downhole geophysical logging of numerous additional boreholes is used to measure various physical properties but no coal quality samples are taken. The work presented in this paper uses two of the most important coal quality variables-ash and volatile matter-and assesses the efficacy of using a number of geostatistical interpolation methods to improve the accuracy of the interpolated models, including the use of auxiliary variables from geophysical logs. A multivariate spatial statistical analysis of ash, volatile matter and several auxiliary variables is used to establish a co-regionalization model that relates all of the variables as manifestations of an underlying geological characteristic. A case study of a coal mine in Queensland, Australia, is used to compare the interpolation methods of inverse distance to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with an external drift. The relative merits of these six methods are compared using the mean error and the root mean square error as measures of bias and accuracy. The study demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with an external drift. The results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter, and when using wireline density logs as the drift variable there is improvement in the estimation of the in situ ash. The economic benefit of these findings is that cheaper proxies for coal quality parameters can significantly increase data density and the quality of estimations.

The Effect of Weathering on Salt Release from Coal Mine Spoils

Coal mine spoils have the potential to create environmental impacts, such as salt load to surrounding environments, particularly when exposed to weathering processes. This study was conducted to understand the effect of physical and chemical weathering on the magnitude, rate, and dynamics of salt release from different coal mine spoils. Five spoil samples from three mines in Queensland were sieved to three different particle size fractions (&lt;2 mm, 2–6 mm, and &gt;6 mm). Two samples were dispersive spoils, and three samples were nondispersive spoils. The spoils were subjected to seven wet–dry cycles, where the samples were periodically leached with deionised water. The rate, magnitude, and dynamics of solutes released from spoils were spoil specific. One set of spoils did not show any evidence of weathering, but initially had higher accumulation of salts. In contrast, broad oxidative weathering occurred in another set of spoils; this led to acid generation and resulted in physical weathering, promoting adsorption–desorption and dissolution and, thus, a greater release of salts. This study indicated that the rate and magnitude of salt release decreased with increasing particle size. Nevertheless, when the spoil is dispersive, the degree of weathering manages salt release irrespective of initial particle size. This study revealed that the long-term salt release from spoils is not only governed by geochemistry, weathering degree, and particle size but also controlled by the water/rock ratio and hydrological conditions of spoils.