N. M. Shahani; M. J. Sajid; I. M. Jiskani; B. Ullah; A. R. Qureshi
Abstract
In this work, we employ the fuzzy logic technique to achieve and present, for the first time, a proper analysis of the actual intensity of the increase in the coal miners’ fatality rates in Pakistan from 2010 to 2018, compared with China and India, with an objective to minimize the impact of incidents ...
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In this work, we employ the fuzzy logic technique to achieve and present, for the first time, a proper analysis of the actual intensity of the increase in the coal miners’ fatality rates in Pakistan from 2010 to 2018, compared with China and India, with an objective to minimize the impact of incidents on the miners’ fatalities. The average and yearwise fatality rates in Pakistan, compared with China and India, are used for the fuzzy logic technique in order to calculate the actual degree of flexibility for the surging fatalities. The findings show that both the average (2010-2018) and yearwise fatality rates in 2011, 2015, and 2018 are 2.44, 1.74, and 1.6, respectively. In the fuzzy logic technique, the variables whose membership function (µ) values are ≥ 1 represent the absolute truth. The membership function values for the years 2011, 2015, and 2018 are alarmingly high for the fatalities of coal miners. Similarly, except for 2014 and 2010, where 0 represents the absolute falseness, the results for the remaining years indicate high fatality rates with a flexibility (or small extent) of its corresponding membership function (µ) values such as 0.623, 0.739, 0.219, 0.173 and 0.115, and 0.714, 0.24, 0.01, 0.324 and 0.317 using the average and yearwise analysis, respectively, compared with China. Likewise, the fuzzy logic membership function (µ) values compared with India in the remaining years are 0.704, 0.795, 0.386, 0.159, 0.352 and 0.306, and 0.675, 0.795, 0.386, 0.186, 0.321 and 0.322, respectively. The proposed fuzzy logic analysis has been founded based on the theory of fuzzy sets to properly identify the miners’ fatalities, and also to suggest the implementation of appropriate recommendations to reduce the fatalities in the coal mines in Pakistan.
M. J. Sajid; N. Shahani; M. Ali
Abstract
Mining is among the oldest industries. It is the primary source of raw materials for most of the sectors. Little is known about the complex inter-sectoral carbon linkages of the mining industry. In this work, we estimate the inter- and intra-sectoral carbon linkage impacts of the mining sector across ...
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Mining is among the oldest industries. It is the primary source of raw materials for most of the sectors. Little is known about the complex inter-sectoral carbon linkages of the mining industry. In this work, we estimate the inter- and intra-sectoral carbon linkage impacts of the mining sector across ten major economies by applying an input-output model, and the hypothetical extraction method and its modified version. The hypothetical extraction method removes an industrial block from an economic system, and afterwards, it makes a comparison between the before and after removal values. China with 195.47 Mt has the highest mining emissions, followed by USA, India, and Canada with 110.99 Mt, 108.79 Mt, and 76.92 Mt, respectively. The India’s mining sector with 26.33 t/104 $ is the most carbon-intensive, followed by Japan and Canada with 6.84 t/104 $ and 5.22 t/104 $, respectively. China’s carbon emissions with -11.56% and -11.28%, respectively, have been affected the most by the total extraction of mining sector and forward carbon linkages, while for the backward carbon linkage, Canada with -1.33% has been affected the most. Canada has the highest mixed and internal emissions of 0.42 Mt and 47.88 Mt, respectively. However, China has the highest net-backward and net-forward emissions of 16.91 Mt and 189.22 Mt, respectively. For all nations, the mining sector is a net exporter of emissions to other industries. Based on the numerical findings, in this work, we discuss the mitigation measures for both the direct and indirect mining emissions.
