Economic sensitivity analysis of dual perspectives induced by energy scarcity for energy-dependent region

Will greenhouse gas emissions increase with mining depth in coal mines? An analysis of gas occurrence under varying in-situ stress conditions

The rapid development of the economy leads to the high demand for deep coal resources, which further poses the potential problem of deep gas (or methane) emissions. The clarification of deep gas occurrence law for coal mines provides theoretical and data support for methane emission predictions, and assists industrial and mining enterprises in planning targeted emission reduction measures. This study defined and verified the existence of a critical depth for the deep gas occurrence in coal mines based on a multiple-scale case study of how the gas occurrence is associated with depth and stress status changes in the Pingdingshan No.8 Coal Mine. In addition, 882 sets of gas content data from 7 major mining areas in China were collected and their gas content distributions among various depths were statistically analyzed to prove the universal existence of critical depth. The results show that the critical depth of Pingdingshan No.8 Coal Mine is 509 m, and the critical depth of other Chinese areas is about 400 to 1000 m. Significant differences were observed in the pore space, surface, and gas desorption characteristics for coal samples with different depths and stress states. The pore structure in the critical depth area is relatively developed, and gas is easily accumulated. The gas occurrence of both normal and abnormal gas gradually increases with the depth's increase in areas above the critical depth, whereas the gas occurrence gradually decreases for areas below the critical depth, showing that the existence of critical depth lead to significant deviations in gas emission predictions. The results provide a fundamental reference for gas emission prediction, greenhouse effect assessment, and carbon emission factor calculation and indicate that using the traditional linear method may be misleading for evaluating deep gas occurrence and emission.

Spatiotemporal dynamics of near-surface ozone concentration and potential source areas in northern China during 2015-2020

Near-surface ozone (O3) pollution has become one of the main factors hampering urban air quality in northern China. However, on a spatiotemporal scale, dynamic transport paths and potential source areas of O3 in northern China are ambiguous. In addition, we suspect that the contribution of transportation activities to urban O3 concentrations developed in northern China may be underestimated. In this study, the HYSPLIT, PSCF, CWT and GTWR model were used to study the transmission paths, potential source areas and driving factors of urban O3 concentration on a spatiotemporal scale. The average annual concentration of surface O3 (the 90th percentile of MDA8) was 172 ± 29 μg/m3 in northern China from 2015 to 2020. In terms of inter-annual variation, the urban O3 concentration increased from 2015 to 2018, and decreased after 2018. On the spatial scale, the areas with high O3 concentration were mainly clustered in industrial cities (Tangshan, Baoding, Shijiazhuang, Xingtai and Handan). During the study period, the area with high O3 concentration in northern China shifted from northwest to southeast. From 2015 to 2020, the influence of long-distance air mass trajectories from Xinjiang and Siberi on airflow transport in Beijing city dominates (78.60%) The average percentage of short-distance transport trajectories from Shandong Peninsula region is about 21.40%. The core potential source areas of O3 pollution shifted from northwest to southeast, but the contribution to O3 pollution in Beijing gradually weakened during the same period. Temperature and relative humidity were the main meteorological driving factors affecting O3 concentration in the study area, while population density, the proportion of secondary industry in GDP, industrial smoke (dust) emissions, and passenger traffic were the main non-meteorological factors. During the period study, the influence of industrial and traffic emissions had a more significant impact on O3 concentration in northern China, which will require that more attention be paid to emission mitigation in the regional industrial and passenger transportation sector, as well as the joint prevention and control of O3 pollution in northern China in the future.

Multiperspective-driven factorial metabolic network analysis framework for energy-water nexus vulnerability assessment and management-policy simulation

Energy and water are rapidly consumed as the most basic strategic resources of various nations. It is of vital importance to systematically explore the environmental and economic impacts of energy-water co-management policies. This study is to develop a multiperspective-driven factorial metabolic network analysis framework (MPDF) to (a) investigate the direct/indirect/total resource consumption response mechanisms induced by changes in production and consumption; (b) explore the factor interactions of different policies in diverse energy and water metabolic networks by initiating factorial analysis; (c) quantify the economic effects of co-management policies by proposing multiple vulnerability indicators. A typical energy-dependent region, Shanxi Province, China was selected as a case study. The results indicated that the production- and consumption-oriented policies have various guidelines for reducing direct and indirect energy-water consumption. Significant interactions in simulation results suggest synergistic effects across sectors. Considering that Shanxi's energy-water nexus economic vulnerability is as high as 2.22%, it is recommended to prioritize the allocation of resources to sectors with significant factor effects to avoid economic losses. Implementing corresponding resource conservation policies for light industry, machinery manufacturing, construction can reduce water consumption by 18.8%. The findings are expected to provide a solid scientific basis for formulating co-management strategies to alleviate resource scarcities.

Modelling the Relationships among the Key Factors Affecting the Performance of Coal-Fired Thermal Power Plants: Implications for Achieving Clean Energy

Most countries depend on coal-fired thermal power plants (CTPPs) to meet energy demands. However, the adverse environmental impacts of CTPPs also remain a major concern. As the energy generations from renewable energy resources are still in the developing stage, reliance on CTPPs is inevitable. Hence, the efficiency of CTPPs has to be improved, while decreasing carbon emissions. This study aims to identify and evaluate the key factors that need to be addressed in improving the performance and minimizing the carbon emission of CTPPs. With the literature review and industrial interaction, twenty-four key factors are identified. Next, an integrated approach of the fuzzy analytic hierarchy process (FAHP) and fuzzy decision-making and trial laboratory (FDEMATEL) is used to evaluate the key factors. FAHP prioritizes the key factors and FDEMATEL reveals the relationship among the key factors. Results indicate air preheater leakage, plugging by ash, high levels of air ingress, air preheater secondary fire, and high levels of corrosion as the top five key factors affecting CTPP performance. Based on the outcome, the study offers some implications that may assist the industrial management in taking timely actions in improving the performance of CTPPs.