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The betterment of environmental conditions is widely recognized as a significant priority for India, which is a critical aspect of the Sustainable Development Goals (SDGs). As an emerging economy, pursuing economic expansion is paramount, requiring significant amount of energy and a degree of openness to other nations. Meanwhile, the nation's energy demands are heavily met by the usage of biomass and coal energy sources. Furthermore, the nation is part of the top consumer of biomass and coal energy globally. However, over the last 50 years, the level of ecological footprint in India has surged by about 82%, despite the country's commitment to achieving environmental sustainability, which tends to raise concerns such as: What is the role of India's major energy sources, biomass, and coal energy, towards ecological sustainability? Does economic globalization promote and hinder India's environmental sustainability goals? As a result, this current study offers answers to these concerns by investigating the effect of economic globalization, coal energy, and biomass energy on the ecological footprint in India while controlling economic growth. Using the dynamic ARDL to analyze the dataset from 1970 to 2018, the result suggests that biomass energy and economic globalization improve ecological quality. However, economic growth and coal energy impede ecological quality in India. Furthermore, we adopted the time-varying causality test solely to understand the causality analysis, which established that economic globalization, biomass energy, economic growth, and coal energy could forecast the future direction of the ecological footprint.

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Environmental perception is an important research direction of coal mine sustainable development. There is much dust in the underground working environment of coal mine. This study is to identify the marker (ball) in the coal mine, which provides a basic to convert the coordinate of large-scale fully mechanized mining face point cloud to the geodetic coordinate. Firstly, in the face of the phenomenon that the uneven distribution of underground point cloud is more serious, this study further has studied on the basis of complete and incomplete geometry point cloud and generated multi-density geometry point cloud for the first time. Secondly, aiming at the problem that the geometric features of underground point cloud are not obvious enough, this study has increased the weight of point cloud normal vector in the training process of network model, so that the network model is more sensitive to different geometric features. Finally, this study has used a variety of advanced deep neural networks to directly analyze point clouds to verify the proposed method. The results show that the method proposed in this study has been combined with the dynamic graph convolution neural network (DGCNN) established earlier, which can more accurately identify the ball in tens of millions of the point clouds of coal mining process. Most importantly, this work is not only of great significance to improve the production efficiency and safety in fully mechanized mining face but also lays a foundation for realizing intelligence in the mining field and avoiding the harm of dust explosion and other accidents to workers.

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This study examines the long-term effects of coal and geothermal consumption on carbon emission while controlling for globalization and economic growth toward carbon neutrality in newly industrialized countries, including Brazil, China, India, Mexico, Malaysia, the Philippines, South Africa, Turkey, Indonesia, and Thailand for the period of 1990-2008. We compare the resulting relationships from various estimation techniques, such as fixed-effect ordinary least squares, dynamic ordinary least squares, fully modified ordinary least squares, and method of moment quantile regression. Overall, this study determines that the consumption of coal and geothermal energy is a significant determinant with a causal effect on carbon emission. The rise in coal energy consumption significantly increases carbon emission across all quantiles (0.1-0.90), whereas the rise in geothermal energy consumption reduces it across all quantiles (0.1-0.90). This relationship is also consistent across all quantiles (0.1-0.9). Policy suggestions are proposed on the basis of these findings.

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The regularities of obtaining foamed alkali-activated geopolymer materials based on different wastes of coal power engineering (fly ash, fuel (boiler) slag, ash, and slag mixture) were considered. The phase composition of the studied waste showed the presence of a significant amount of the amorphous phase, as well as a crystalline phase. mostly in the form of high quartz. The microstructure of studied the waste showed that the fly ash consisted of monodisperse hollow aluminosilicate microspheres, the fuel slag was represented by polydisperse irregular particles, and the ash and slag mixture included both of these materials in different ratios. Blowing agents such as aluminum powder, hydrogen peroxide, and sodium hypochlorite were chosen to achieve the porous structure of the geopolymer materials. The calculations of the geopolymer precursor compositions were carried out. Samples were synthesized, and their physical and mechanical properties, such as density, strength, porosity, and thermal conductivity, were analyzed. The micro- and macrostructure of the samples, as well as the pore distribution of the obtained geopolymers were studied. Conclusions were made on the choice of the most-optimal foaming agent and the optimal coal combustion waste suitable for the synthesis of the geopolymer materials.

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This current study seeks to investigate the policy implication of Turkey's recent energy policies on its sustainable development. This study uses Turkey's country-specific data and series of 1974 to 2018 for effective investigation and justification of the findings of this study with emphasis on both short-run and long-run implications. Three models were fitted to achieve study objectives to accommodate both environmental sustainability and economic impacts. Ecological footprint was considered better measure and used as proxy for the environment related model. In summary, with environment models, the selected series (per capita GDP, industrialization, agriculture, coal as a single energy use, and mixed energy use) except per capita GDP2 were found positively and significantly related to ecological footprint in both short run and long run which translates to poor performance of Turkey's environment. Also, using economic growth model, the selected series (industrialization, energy use, and agriculture) were all confirmed positively and significantly related to the economic growth (per capita GDP). Additionally, environmental Kuznets curve (EKC) was established for Turkey's environment and economic performance. Furthermore, using Granger causality as robust check to these findings, a nexus was found among the series confirming the validity of the cointegration (short- and long-run policies) estimations and results. In congruence with literature and hypotheses, the results from cointegration estimation shows that the twin polices may be good to the economic performance but will spark off adverse effect on environment.

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Coal-based energy production is the most utilized method of electricity production worldwide and releases the highest concentration of gaseous, particulate, and metallic pollutants. Toxicological research has shown that coal combustion by-products are carcinogens, endocrine disruptors, and cardiorespiratory toxins. This article aims to systematically review the epidemiological literature on the impact emissions from coal-based power production has on morbidity and mortality worldwide. Two thousand one hundred and fifty-two articles were retrieved based on search criteria. Word search of abstract and article text filtered the results to 95 articles. Forty articles were included after screening. The literature indicates a significant adverse effect from particulate matter and polyaromatic hydrocarbon emissions on morbidity and mortality. There is a lack of consistency of exposure assessment and inadequate control of significant potential confounders such as social economic status. Future research should focus on improving exposure assessment models, specifically source-apportionment and geographic information system methods to model power plant-specific emissions.

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Anthropogenic activities in search of livelihood come with its environmental implications. This is in line with the current crusade of the United Nations sustainable development goals (SDGs) target 7 and 13 for effective clean energy access and mitigating the adverse effect of climate change issues. Since the seminal study of Kraft and Kraft (1978) on the nexus between energy and gross national product, there has been no consensus in the extant literature in the last four decades. To this end, the current study applies recent data for the case of Nigeria from 1970 to 2017 on an annual frequency. Modified Wald causality test of Toda-Yamamoto is in conjunction with the recent gradual shift causality test with Fourier approximation for robustness and precision of analysis. Empirical results show the pollutant driven economy as one-way causality is seen running from pollutant emission to economic growth. This suggests that economic growth is driven by dirty energy sources that are from non-renewable energy sources. This is further validated in the pollution haven hypothesis (PHH) confirmed in the study by the causality seen running from foreign direct investment and carbon dioxide emissions. Additionally, the exploration of natural resources also engenders economic expansion in Nigeria. Based on the current study findings, a couple of submissions are made such as the need for a paradigm shift to cleaner energy sources. More so, the need for the adoption of cleaner, eco-system friendlier innovations, and technologies will aid in the attainment of the SDGs of mitigating climate and pollution issues.

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Coal-based energy production is the most utilized method of electricity production worldwide and releases the highest concentration of gaseous, particulate, and metallic pollutants. This article aims to systematically review the public health impact of coal-fired power plant emissions on children's health. PubMed, Web of Science, and Toxline databases were queried for the past 20 years. Inclusion criteria included original scientific articles with (a) coal-fired power plant exposure assessment, (b) at least one primary pediatric health outcome, and (c) assessment of potential sources of confounding and bias. Only morbidity and mortality studies were included; economic analysis and risk assessment studies without a primary health outcome were not included. Of 513 articles initially retrieved, 17 epidemiological articles were included in the final systematic review after screening and eligibility. The articles reviewed showed a statistically significant adverse effect on pediatric neurodevelopment; birth weight and pediatric respiratory morbidity was associated with exposure to coal-fired power plant emissions, primarily particulate matter and polyaromatic hydrocarbon exposure. There is a lack of consistency of exposure assessment and inadequate control of significant potential confounders such as social economic status. Future research should focus on improving exposure assessment models with an emphasis on source-apportionment and geographic information system methods to model power plant-specific emissions.

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