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Lindsay Simpson has doggedly pursued an incredible story: how could a company with a globally disastrous reputation for environmental destruction along with a dubious financial status woo an Australian Prime Minister, a State Premier and a handful of regional mayors to back a project to build Australia's largest coalmine and the world's largest coal terminal only kilometres from the Great Barrier Reef? Investigative journalist, former academic and author, Simpson's personal story reveals the truth behind the Adani controversy. Doorknocking at Adani's Indian HQ to hand over a petition from the Australian Conservation Foundation signed by Australia's most prominent citizens; she also lobbied politicians in Parliament House in Canberra, questioning their motives that ensured the mine was approved. Simpson investigates the power of the social movement Stop Adani which has captured the national imagination, proving that while Adani might have gained the political will to build the mine, it has never gained the social will of the people. Adani, Following Its Dirty Footsteps: A Personal Story documents the inconceivable story of how Australian governments abrogated their responsibilities to protect this world heritage icon; bypassing environmental safeguards, thereby irrevocably damaging Australia's reputation as environmental steward of some of the world's most valuable natural assets. This book lays bare the pecuniary interests of Australia's leaders serving a country which is the largest exporter of coal and how money rules over protecting the environment.-- Source other than Library of Congress.

As the world's largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.

\"Coal is the commodity that powered the technologies that made the modern world. It also brought about unique communities marked by a high degree of social solidarity and self-help. Mining was central to working class life, drawing rural populations into industrial labour, but it often took place in picturesque landscapes, so that its black spoil heaps became a central symbol of the degradation of pastoral life by the demands of an extractive industry. Throughout Europe and the USA photographers have pictured the characteristic landscapes of the industry, and continue to do so as strip mining devastates huge areas of land. Not only landscape photography but also documentary, portraiture, photojournalism and art photography have been used in order to portray mines and miners. This book presents three interlinked strands of investigation. The first is the way in which the production of coal created paradigmatic communities grounded in particular landscapes. The second concerns the role of photography in exploring, delineating and critiquing mining communities. This in turn involves an examination of the aesthetic and social characteristics of a number of genres of photography. Lastly, it considers the growth and decline of these sites, the geographic shift of the industry to other places, and the re-presentation of traditional localities through the lens of the heritage industry and industrial tourism.\"-- Provided by publisher.

Spontaneous combustion of coal is one of the major hazards threatening production safety during longwall mining. Mining-induced voids, which provide passages for air leakage, are the key factor triggering spontaneous combustion of coal in longwall goafs. In this study, a comprehensive method, which combined pressure balance, grouting injection, and filling fissures, was proposed to prevent spontaneous combustion of coal in longwall goafs with complex air leakage. Field engineering practice was carried out in Sitai Coal Mine in China. The results demonstrated that with the application of the proposed method, in the working face, the concentration of CO was decreased from 31ppm to 0 and the air leakage quantity was decreased from 261 to below 80 m3min-1. The gas samples analysis from the gob areas also indicated that concentrations of O2 and CO were successively decreased, indicating that the risk of spontaneous combustion of coal in goafs was eliminated. The above mentioned analysis indicates that, the method proposed in this study is useful and efficient. Successful application of this technology could provide reference for the treatment of other coal mines.

In recent years, the ecology, security, and sustainable development of modern mines have become the theme of coal mine development worldwide. However, spontaneous combustion of coal under conditions of oxygen supply and automatic exothermic heating during coal mining lead to coalfield fires. Coal spontaneous combustion (CSC) causes huge economic losses and casualties, with the toxic and harmful gases produced during coal combustion not only polluting the working environment, but also causing great damage to the ecological environment. China is the world’s largest coal producer and consumer; however, coal production in Chinese mines is seriously threatened by the CSC risk. Because deep underground mining methods are commonly adopted in Chinese coal mines, coupling disasters are frequent in these mines with the coalfield fires becoming increasingly serious. Therefore, in this study, we analyzed the development mechanism of CSC. The CSC risk assessment was performed from the aspects of prediction, detection, and determination of the “dangerous area” in a coal mine (i.e., the area most susceptible to fire hazards). A new geophysical method for CSC determination is proposed and analyzed. Furthermore, the main methods for CSC fire prevention and control and their advantages and disadvantages are analyzed. To eventually construct CSC prevention and control integration system, future developmental direction of CSC was given from five aspects. Our results can present a reference for the development of CSC fire prevention and control technology and promote the protection of ecological environment in China.

As a core component of the fully mechanized mining face, intelligent control of the shearer is fundamental to achieving unmanned mining and improving equipment reliability. To address the limitations of traditional optimization and deep reinforcement learning algorithms in achieving rapid and accurate self-adaptive control, this study proposes a novel shearer drum height control strategy based on the Deep Deterministic Policy Gradient (DDPG) algorithm. The 4602 workface at Yangcun Coal Mine and the MG2 × 55/250-BWD shearer model were used as engineering cases. A hybrid SVD-CWT and AlexNet transfer learning method was employed to identify coal and rock cutting states, achieving an accuracy of 95.06%. A DDPG-based self-adaptive hydraulic height adjustment model was then developed and validated through Matlab/Simulink and AMESim co-simulation, as well as a similarity-based physical test platform. Results show that the proposed method significantly outperforms conventional and fuzzy PID controls, reducing response time to 0.091 s and steady-state error to 0.00052 mm. Compared with TD3 and SAC algorithms, the system exhibited faster response, higher stability, and stronger anti-interference capability. The mean maximum error between simulation and experimental results was only 3.14%, confirming the feasibility and robustness of the proposed control strategy. This study provides a reliable approach for intelligent, adaptive height control of shearers under complex coal seam conditions.

\"A fire broke out in the coal seams of their town years ago, and the flames are still smoldering underground. Margaret and Fritzi, the two sisters who are the heroines of Invitation to the Bold of Heart, the debut novel by Swiss writers Dorothee Elmiger, are the last remaining youth of this vanishing town. Their inheritance is nothing but an abandoned swathe of land ruled by devastation. But the sisters won't accept this state of affairs--they set out on an expedition, determined to piece together the fragments of their family history. Only by learning their own story can they look to the future with hope. When they rediscover a long-forgotten river, the Margaret and Fritzi can sense a new life ahead. Invitation to the Bold of Heart is a startling dystopian tale of hope and exploration and a testament to the timeless need of youth to rebel against authority\"--Jacket.

Due to the complex geological conditions of coal-rock, the cutting head of coal mine excavation machines experiences severe fluctuations in loads, making it difficult for existing macroscopic controls to accurately capture the microscopic loads on the cutting pick. Therefore, a dynamic simulation and intelligent control model for the cutting head load of an adaptive roadheader based on multi-scale coupled simulation is developed. The study first modifies the classical load model through finite element method to accurately simulate the microscopic interaction between the cutting pick and the rock mass. The non-dominated sorting genetic algorithm II in elite strategy is used to construct a multi-objective optimization model to determine the optimal parameters for cutting head speed and swing speed. Finally, load dynamic control is achieved by combining radial basis function proportional-integral-derivative controller, and multi-body dynamics-discrete element method and proximal policy optimization are introduced to improve the adaptability to complex working conditions. Test results from different operation scenarios showed that the path planning error of the model met high-precision excavation requirements in regular roadways. During the long-term stable operation phase, the energy consumption ratio and energy utilization efficiency were significantly improved compared to traditional solutions. Faced with slight changes in coal-rock hardness, this model provided early warnings effectively. Under single-point fracture failure, load stability was quickly restored. In the constant operating condition performance test, the model demonstrated significant steady-state control accuracy with minimal mean square error and zero overshoot. Furthermore, a pilot engineering application in a high-gas coal mine roadway demonstrated that the relative error between the simulated and measured loads was controlled within 6.5%, validating the practical feasibility of the proposed system. This study can effectively reduce pick failure, improve excavation efficiency, provide core technical support for the \"less manpower, unmanned\" operation of coal mines, and assist in the safe and efficient upgrading of the coal industry.