Forecasting Methane Emissions from Hard Coal Mines Including the Methane Drainage Process
Forecasting Methane Emissions from Hard Coal Mines Including the Methane Drainage Process
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DOI：
10.3390/en12203840
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发表时间：
2019-10-01
期刊：
影响因子：
3.2
通讯作者：
Brodny, Jaroslaw
中科院分区：
文献类型：
--
作者：
Tutak, Magdalena;Brodny, Jaroslaw
关于地下采矿，甲烷是一种气体，一方面对开采过程构成威胁，另一方面为经济发展创造机会。由于煤炭开采，大量煤炭主要通过通风系统进入自然环境。由于甲烷是一种温室气体，其排放对全球变暖有重大影响。然而，甲烷也是一种高能量气体，可以作为一种非常宝贵的能源利用。甲烷的这些不同性质促使人们分析煤层甲烷排放的当前和未来状况，同时考虑到其使用的可能性。因此，以下文章介绍了1993-2018年波兰硬煤矿甲烷排放量的研究结果及其到2025年的预测。为了预测甲烷排放量，研究方法的基础上开发的人工神经网络和选定的统计方法。采用多层感知器（MLP）网络建立预测模型。这项研究的目的是制定一种方法来预测甲烷排放量，并确定未来几年可能进入自然环境的甲烷量的趋势以及甲烷排放过程中可使用的甲烷量。利用神经网络开发的方法，进行的研究和研究结果构成了一种新的方法，在分析和预测的范围内从硬煤矿甲烷排放量。所获得的结果证实，这种方法在采矿实践中效果良好，也可以成功地用于其他行业，以预测温室气体和其他物质的排放。
With regard to underground mining, methane is a gas that, on the one hand, poses a threat to the exploitation process and, on the other hand, creates an opportunity for economic development. As a result of coal exploitation, large amounts of coal enter the natural environment mainly through ventilation systems. Since methane is a greenhouse gas, its emission has a significant impact on global warming. Nevertheless, methane is also a high-energy gas that can be utilized as a very valuable energy resource. These different properties of methane prompted an analysis of both the current and the future states of methane emissions from coal seams, taking into account the possibilities of its use. For this reason, the following article presents the results of the study of methane emissions from Polish hard coal mines between 1993-2018 and their forecast until 2025. In order to predict methane emissions, research methodology was developed based on artificial neural networks and selected statistical methods. The multi-layer perceptron (MLP) network was used to make a prognostic model. The aim of the study was to develop a method to predict methane emissions and determine trends in terms of the amount of methane that may enter the natural environment in the coming years and the amount that can be used as a result of the methane drainage process. The methodology developed with the use of neural networks, the conducted research, and the findings constitute a new approach in the scope of both analysis and prediction of methane emissions from hard coal mines. The results obtained confirm that this methodology works well in mining practice and can also be successfully used in other industries to forecast greenhouse gas and other substance emissions.