Greenhouse gas emissions from shallow uncovered coal seams

This study discusses a method of quantifying emissions from surface coal mining that has been trialled in Australia. The method is based on direct measurement of surface emissions from uncovered coal seams in mine pits, concurrent measurement of residual gas content of blasted coal in mine pits, and measurement of pre-mining gas content of the same seam from cores retrieved from exploration boreholes drilled away from active mining. The results from one of the mines studied are presented in this paper. In this mine, the pre-mining gas content of the target seam was measured using cores from an exploration borehole away from active mining. Gas content varied from 0.7 to 0.8 m³/t and gas composition varied from 16% to 21% CH₄ (84–79% CO₂). In-pit measurements included seam surface emissions and residual gas content of blasted and ripped coal. Residual gas content varied from 0.09 to 0.15 m³/t, less than twofold across the mine pit. Composition of the residual gas was in general 90% CO₂ and 10% CH₄, with slight variation between samples. Coal seam surface emissions varied from 1.03 to 7.50 mL of CO₂-e per minute and per square meter of the coal seam surface, a sevenfold variation across the mine pit.     

土壤源热泵技术对温室气体(GHG)减排的贡献

提出了热泵耗煤当量的概念.以邯郸地区为例,分析了电力驱动热泵供热技术(以土壤源热泵为例)替代锅炉房供热后,供暖季单位住宅建筑面积锅炉房的耗煤量与土壤源热泵耗煤当量的差别.计算出供暖季单位住宅建筑面积温室气体CO2排放的减少量.分析了影响温室气体减排量的几个因素.     

Effective goaf gas capture design at Ravensworth Underground Mine

This paper highlights a reliable goaf gas capture system developed and used at Ravensworth Underground Mine since its trial in 2009. The method utilises horizontal holes drilled from underground sites and connected to an underground gas pipeline. This system incorporates a gas suction and flaring plant designed specifically for this method. The current method has captured effectively a total longwall, and adjacent goaf gas accounts for over 85%. The design of the holes drilled has been the success of the gas flow reliability. The flow is extraordinarily consistent and predictable. The management of the underground pipeline determines the overall reliability of flow. The design has resulted in Ravensworth Management being confident to remove a gas bearing bleeder roadway and still manage the existing tailgate roadway for allowing access as required. The reduction of CO₂ equivalent emissions recorded is approximately 0.35 × 10⁶ tons annually. This design has further improvements to be added to allow use at any other site with gas in the overlying strata.     

Fracturing,caving propagation and influence of mining on groundwater above longwall panels——a review of predictive models

Historically there have been a number of different hypotheses and empirical models developed in an attempt to describe the nature of fracturing above longwall panels in underground coal mining. The motivation for such models varies, ranging from understanding the impact of mining on surface subsidence,to back-analysis of caving behaviour in the immediate roof behind the longwall face. One of the most critical motivating factors that is taking on increased importance in many coalfields, is the need for better understanding, and hence prediction of the impact of mining on overlying strata, particularly strata units acting as aquifers for different groundwater horizons. This paper reviews some of the major prediction models in the context of observed behaviour of strata displacement and fracturing above longwall panels in the southern coalfields of New South Wales, south of Sydney. The paper discusses the parameter often referred to as ‘‘height of fracturing\" in terms of the critical parameters that influence it, and the relevance and appropriateness of this terminology in the context of overlying sub-surface subsidence and groundwater impact. The paper proposes an alternative terminology for this parameter that better reflects what it is and how it is used. The paper also addresses the potential role of major bedding shear planes mobilised by mining and their potential influence on overlying subsidence and groundwater interference.     

△P index with different gas compositions for instantaneous outburst prediction in coal mines

In this study we measured the △P(initial speed of gas emission)index with different gas concentrations of carbon dioxide(pure CO2,90% CO2+10% CH4,67% CO2+33% CH4,50% CO2+50% CH4,30% CO2+10% CH4 and pure CH4)of coal samples from the No.2 coal seam in the Yaojie Coal Mine,Gansu province,China.The effect of carbon dioxide concentration,gas composition,coal strength and particle size of coal samples on the △P index was investigated.The experimental results show that with gas of various compositions,the △P value of three samples were clearly different.The △P index of coal samples A,B and C(0.2～0.25 mm)were 4,6 and 7 with pure CH4 and 22,30 and 21 when pure CH4 was used.Carbon dioxide concentration affects the△P index markedly.The △P index increases with an increase in carbon dioxide concentration,especially for coal B.Hence,the△P index and K(another outburst index)values tested only with pure CH4 for prediction of the danger of outburst is not accurate.It is important to determine the initial speed of gas emission given the gas composition of the coal seam to be tested for exact outburst prediction.     

九里山矿14区放顶煤开采瓦斯涌出规律分析

分析了焦作矿务局九里山矿放顶煤工作面沿底掘进及开采期间各生产工序瓦斯涌出规律． 与顶分层开采对比, 放顶煤开采相对瓦斯涌出量降低, 绝对瓦斯涌出量增加倍数小于产量提高倍数, 各生产工序以放煤时瓦斯涌出量最大; 沿顶掘巷的平均瓦斯涌出量是沿底掘巷的１ ．２５ 倍, 沿底掘进不增加突出危险性     

基于BP神经网络分源预测综采面瓦斯涌出量研究

为了提高综采工作面瓦斯涌出量的预测精度,根据综采工作面瓦斯来源的分析,在瓦斯分源预测方法的基础上,融合神经网络预测技术,建立BP神经网络分源预测模型。结合某矿1242（1）工作面地质条件和开采技术条件,利用BP神经网络分源预测模型对工作面瓦斯涌出量进行了预测,结果表明,BP神经网络分源预测模型预测精度能满足现场需求,与分源法相比较,在综采工作面瓦斯涌出量预测中方便简洁而且具有很高可信度,其应用前景更广泛。     

煤与瓦斯突出区域预测方法探讨

采用多参数综合分析方法进行区域性预测，划分突出危险区和突出威胁区的范围，分区、分级管理，指导煤矿安全生产。     

Underground pressure characteristics analysis in back-gully mining of shallow coal seam under a bedrock gully slope

We studied underground pressure and its mechanism during back-gully mining in a shallow coal seam under a bedrock gully slope, by means of physical simulation, numerical modeling and field monitoring.The results show that the intensity of underground pressure is related to its relative position at the coalface. The underground pressure is intensive and the support resistance reaches a maximum when the coalface is at the bottom of the gully, whereas the underground pressure is moderate and decreases gradually when the coalface passes the gully. The mechanism of these changes is analyzed when the slope rotated in a reversed direction to the slope dip during back-gully mining and form an unstable, multilateral block hinged structure, due to slipping. The subsidence of multilateral blocks is considerable when the block fragmentation is small, resulting in enormous changes in the underground pressure. With an increase in the mass of the block body, the block displacement will be reduced in conjunction with an increased clamp effect by both the unbroken rocks and broken rocks in the goaf, resulting in a decrease of the underground pressure.     

Gas diffusion in a cylindrical coal sample – A general solution,approximation and error analyses

The analytical mathematical solutions of gas concentration and fractional gas loss for the diffusion of gas in a cylindrical coal sample were given with detailed mathematical derivations by assuming that the diffusion of gas through the coal matrix is concentration gradient-driven and obeys the Fick’s Second Law of Diffusion. The analytical solutions were approximated in case of small values of time and the error analyses associated with the approximation were also undertaken. The results indicate that the square root relationship of gas release in the early stage of desorption, which is widely used to provide a simple and fast estimation of the lost gas, is the first term of the approximation, and care must be taken in using the square root relationship as a significant error might be introduced with increase in the lost time and decrease in effective diameter of a cylindrical coal sample.     

煤层瓦斯含量预测方法研究

利用矿井采掘区煤层瓦斯含量实测值，在瓦斯地质定性分析基础上，通过丰富翔实的钻孔资料建立井田未采掘区合用的煤层瓦斯含量预测公式，从而达到对井田煤层瓦斯含量预测的目的。为大型矿井煤层瓦斯含量预测提供了思路和方法。     

高瓦斯矿井一次采全高综采工作面瓦斯治理

介绍了晋城矿区寺河矿高瓦斯矿井一次采全高工作面瓦斯治理方法和瓦斯利用情况,提出了高瓦斯矿井一次采全高工作面瓦斯治理途径和技术,指出高瓦斯矿井高产高效、安全生产的根本出路在于提高瓦斯抽放率,加强瓦斯利用,进而提高矿井的综合效益.     

家用燃气灶具的CO排放预测与界限气设定

同一管网引入不同来源的天然气已成为规划建设阶段的常见做法.不同天然气气源的组成可能存在差异,为了解不同燃气组成对民用燃烧灶具的CO排放的影响,避免大量终端用户的室内环境品质受到损害,对民用灶具的CO排放进行了实验研究.首先考察了中国12T天然气组成的分布并利用华白数相等与碳氢原子数守恒原则,确立了6组原组成天然气以及对应的三组分天然气,并测试灶具在每组燃气运行下的CO排放情况;对原组成天然气以及对应的三组分天然气的CO排放差异进行了讨论;在灶具上测试了以华白数和PN数为变化依据的不同三组分天然气.实验表明:三组分天然气的CO排放与原组成天然气等价;气质参数华白数和PN数可以描述灶具在不同燃气组成下运行时的CO变化规律;在PN-W图上存在等CO排放线簇,可用于家用灶具使用不同组成燃气的CO排放预测,并以此为依据提出了一种确立CO排放界限气的思路.对保障室内环境空气品质以及输配管网气源质量管理,都具有现实意义和实用价值.     

瓦斯事故类型影响严重程度的灰关联分析

煤矿瓦斯事故是煤矿事故防治的重点.在瓦斯事故中,瓦斯爆炸、瓦斯窒息及中毒、煤与瓦斯突出事故往往会造成严重的人员伤亡和财产损失.在所有的瓦斯事故中,由瓦斯爆炸事故引起的死亡人数最多,这和历年的瓦斯事故死亡人数情况相符合.作者基于灰色系统理论,对瓦斯事故类型的影响严重程度进行了灰色关联分析,从灰关联角度验证了煤矿瓦斯事故防治的重点应是:防治瓦斯爆炸、瓦斯窒息及中毒、煤与瓦斯突出事故.     

瓦斯事故类型影响严重程度的灰关联分析

煤矿瓦斯事故是煤矿事故防治的重点.在瓦斯事故中,瓦斯爆炸、瓦斯窒息及中毒、煤与瓦斯突出事故往往会造成严重的人员伤亡和财产损失.在所有的瓦斯事故中,由瓦斯爆炸事故引起的死亡人数最多,这和历年的瓦斯事故死亡人数情况相符合.作者基于灰色系统理论,对瓦斯事故类型的影响严重程度进行了灰色关联分析,从灰关联角度验证了煤矿瓦斯事故防治的重点应是：防治瓦斯爆炸、瓦斯窒息及中毒、煤与瓦斯突出事故.     

Bayesian discriminant analysis for prediction of coal and gas outbursts and application

Based on the principle of Bayesian discriminant analysis, we established a model of Bayesian discriminant analysis for predicting coal and gas outbursts. We selected five major indices which affect outbursts, i.e., initial speed of methane diffusion, a consistent coal coefficient, gas pressure, destructive style of coal and mining depth, as discriminating factors of the model. In our model, we divided the type of coal and gas outbursts into four grades regarded as four normal populations. We then obtained the corresponding discriminant functions through training a set of data from engineering examples as learning samples and evaluated their criteria by a back substitution method to verify the optimal properties of the model. Finally, we applied the model to the pre-diction of coal and gas outbursts in the Yunnan Enhong Mine. Our results coincided completely with the actual situation. These results show that a model of Bayesian discriminant analysis has excellent recognition performance, high prediction accuracy and a low error rate and is an effective method to predict coal and gas outbursts.