By originally integrating the structural decomposition analysis (SDA) into a computable general equilibrium (CGE) model, this paper simulates and analyzes the impact and mechanism of energy taxes on carbon emissions. Changes in carbon dioxide emissions, energy consumption structure, and other macroeconomic variables are investigated under different pre-set scenarios. The conclusion shows that the imposition of an ad valorem energy tax will indeed impact the production and consumption of enterprises. A higher tax rate leads to more pronounced reductions in carbon dioxide emissions. The carbon intensity effect is the dominant factor driving national carbon emissions and carbon emission intensity decline. Although the production structure effect and final demand effect play a role, their influences are relatively weak. While levying energy taxes, subsidies for personal income tax or corporate production tax can achieve double dividends. The progress of energy utilization technology is capable of increasing unit energy output and easing the negative impact of energy tax collection, and the gross national product may rise rather than fall. Under this circumstance, the production structure effect will play a greater role because the total demand coefficients of various industries for energy industry products will further decline. Only by levying energy taxes on coal and oil, exempting energy taxes on natural gas, or using energy tax revenue to subsidize investment in the natural gas industry can the government optimize the energy consumption structure. Subsidies will boost final demand for the natural gas mining and processing industry and increase the consumption share of natural gas, a cleaner energy source than coal and oil, which is critical in the current energy transition process.
The Dexing copper mine is the largest open pit copper mines in Asia, with mining and beneficiation history stretching back more than half a century; consequently it has large amounts of ore tailings. The mineralogy, chemical composition and distribution of elements in the impounded tailings are of great significance to the future utilization and reclamation of the tailings ponds. In total, 1400 tailing samples from 35 drill cores were collected from the 1 tailings pond at the Dexing copper mine. All samples were analyzed to determine their chemical composition. The particle size, XRD, pH and sequential extraction fractions of selected samples were determined. The silt-size fraction dominates the grain-size distribution. Quartz and sericite are the most abundant gangue minerals in the tailings, with medians of 54.3 and 23.7%, respectively. 3D modeling of the tailings pond suggests that the distribution of particle size, minerals and elements is mainly controlled by the gravitational separation during tailings discharge. Silica, Cu, Mo and Ti are enriched in the dam area of the tailings pond, whereas Al 2 O 3 and K 2 O are enriched in the impoundment area. The potential Cu, Ti and sericite reserves in the tailings pond were estimated at 38 149 tons, 142 175 tons and 8.15 million tons, respectively. The tailings are not significantly oxidized and so their environmental risk is low under the present circumstances. Their weak alkalinity and presence of carbonate minerals provide the tailings buffering capacity to weak acids. Sequential extraction data suggest that the mobility of elements in the tailings pond is low; however, about 6040 tons of Cu, 428 tons of Zn, 252 tons of Mo, 145 tons of As and 66 tons of Pb, may be released if the physicochemical conditions change and the tailings become acidic.
China's Carbon trading system is developed from her experience of participation in CDM projects. Chinese government's resolution to reduce carbon emissions serves as a key drive for China's carbon trading system. Pilot carbon trading centers have been set up. Compulsory and voluntary carbon trading market will compliment with each other at different stages. Chinese government should optimize her carbon trading policies to incentive more stakeholders to participate in the carbon trading system.
With the expansion of urbanization scale, more and more infrastructures are being rebuilt in downtown areas. A majority of metropolises in China, however, have numerous cultural relics and historic sites. This situation has hindered redevelopment of infrastructures to some extent. As an important component in urban fabrics, metro development project can relief urban traffic pressure while causing less impact on the surface environment. In order to study the impact of urban subway construction projects and the influence of their operations on cultural and historical relics, this paper used cases of metro projects in cities of Beijing and Xi'an as examples, for following research tasks and objectives: 1) to classify cultural and historic relics, and to analyze their characteristics and protection requirements based on classification; 2) to study main influences of subway engineering to cultural relics during the underground construction process; 3) to analyze the negative effects of subway train vehicles on cultural relics during the operation process. Results showed that there are different influences of subway engineering on different types of culture relics. Land subsidence is the main factor affecting cultural relics during the construction process; while vibration generated by subway train vehicle during operation process, is the main negative effect for cultural relics and historical buildings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.