China has proposed the goals of a carbon peaking target in 2030 and a carbon neutrality target in 2060 to mitigate climate change. In China, Eco-industrial parks (EIPs) are one of the platforms for ...achieving energy conservation and emission reduction. This study aims to investigate the future CO2 emissions reduction potential by evaluating two different types of national EIPs in China. Firstly, we constructed carbon emission inventories for EIP-N in Zhejiang Province and EIP-L in Shandong Province. Subsequently, leveraging these inventories, we developed an integrated model aimed at predicting the carbon emission peaks for both EIPs and discerning the main contributors. Secondly, we took EIP-N and EIP-L as examples and applied the Long-range Energy Alternatives Planning (LEAP) model to establish three different scenarios for analyzing the future trends in carbon emissions. In a Business as usual (BAU) scenario (continue the current energy conservation and emission reduction policies), EIP-L can achieve carbon peaking, while the carbon emissions of EIP-N will continue to increase. In the Emissions control (EMC) scenario (considering the reduction of fossil fuels and the increased use of cleaner energy sources), EIP-N and EIP-L are projected to peak in 2029 and 2027, respectively. In the Reinforce mitigation (RFM) scenario (with fewer emissions from fuels and a higher share of clean energy generation), both EIPs are expected to achieve carbon peaking by 2025. Finally, we proposed the deep decarbonization of EIPs with different industrial characteristics. This study applied the LEAP model to the EIP scale, explored the paths of deep decarbonization development in different EIPs under the constraint of dual-carbon targets, providing a demonstration for China and other developing countries to achieve the goal of carbon capping in EIPs during rapid industrialization.
•Analyze potential of energy and CO2 reductions in China’s iron and steel industry.•A National Energy Technology—Iron and Steel (NET-IS) model is developed.•Potential CO2 emission reductions could ...achieve 818.3 MtCO2 during 2015–2030.•Promoting low-carbon technologies is the most effective way for emissions reduction.•Emission abatement cost would be 1740 CNY/CO2 in 2030 in iron and steel industry.
The iron and steel industry plays an important role in mitigating global climate change. As the largest steel producer and consumer, China bears the primary responsibility for energy savings and CO2 emission reduction in the iron and steel industry. In this study, taking China as the empirical context, we analyze the effectiveness of the following four strategies on the potential of energy savings and emission reduction: phasing out backward production capacity in accordance with the current major policies, adjusting the production structure to increase electric arc furnace steelmaking, promoting low-carbon technologies, and switching to clean fuels. Under the principle of cost minimization, the mitigation potential of different strategies until 2030 and the technological development paths for reducing energy and CO2 emissions in China’s iron and steel industry are identified via an established National Energy Technology model. The results show that promoting low-carbon technologies is the most effective strategy for energy savings and emission reduction alongside cost minimization. Compared with existing policies, these strategies could lead to a cumulative reduction of 818.3 MtCO2 (4.1%) during the period 2015–2030. Therefore, policy makers should provide financial or administrative support to promote the development of specific production and low-carbon technologies such as non-blast furnace iron-making and endless strip production.
Purpose/Significance Argument mining, a research hotspot in the field of computational linguistics, provides machine processable structured data for computational models of argument. Argument mining ...tasks are closely related to artificial intelligence (AI) technologies, such as natural language processing and knowledge representation. There are numerous systematic studies in academia and a clear technical realization route has come into being. New research results continue to emerge as a result of rich resources and rapid development and iteration of deep learning, large language models (LLMs), and other technologies. This study, which reviews the research status and progress of argument mining, can serve as a resource for future research and application development. Method/Process Through literature review, this paper systematically reviews the relevant research basis (including foundational techniques and semantic representation models), summarizes the related technical system in terms of task framework
Clean energy is urgently needed to realize mining projects’ sustainable development (SD). This study aims to discuss the clean energy development path and the related issues of SD in the ecological ...environment driven by big data for mining projects. This study adopts a comprehensive research approach, including a literature review, case analysis, and model construction. Firstly, an in-depth literature review of the development status of clean energy is carried out, and the existing research results and technology applications are explored. Secondly, some typical mining projects are selected as cases to discuss the practice and effect of their clean energy application. Finally, the corresponding clean energy development path and the SD analysis model of the ecological environment are constructed based on big data technology to evaluate the feasibility and potential benefits of promoting and applying clean energy in mining projects. (1) It is observed that under different Gross Domestic Product (GDP) growth rates, the new and cumulative installed capacities of wind energy show an increasing trend. In 2022, under the low GDP growth rate, the cumulative installed capacity of global wind energy was 370.60 Gigawatt (GW), and the new installed capacity was 45 GW. With the high GDP growth rate, the cumulative and new installed capacities were 367.83 GW and 46 GW. As the economy grows, new wind energy capacity is expected to increase significantly by 2030. In 2046, 2047, and 2050, carbon dioxide (CO2) emissions reductions are projected to be 8183.35, 8539.22, and 9842.73 Million tons (Mt) (low scenario), 8750.68, 9087.16, and 10,468.75 Mt (medium scenario), and 9083.03, 9458.86, and 10,879.58 Mt (high scenario). By 2060, it is expected that CO2 emissions reduction will continue to increase. (2) The proposed clean energy development path model has achieved a good effect. Through this study, it is hoped to provide empirical support and decision-making reference for the development of mining projects in clean energy, and promote the SD of the mining industry, thus achieving a win-win situation of economic and ecological benefits. This is of great significance for protecting the ecological environment and realizing the sustainable utilization of resources.
The content of this graphical abstract is divided into four sections. Starting from the research questions, research objectives, significance, methods, and results of this study are expounded. A wind energy development optimization model is constructed to reduce carbon dioxide emissions through wind power generation. Finally, the conclusion is that by introducing clean energy technologies, carbon emissions from mining projects can be significantly reduced, and reliance on traditional energy sources can be reduced. Display omitted
•This study has the following important highlights:•Clean energy technology: Introducing wind energy as a traditional alternative.•Big data-driven method: Data analysis and modeling techniques are optimized.•Wind energy optimization model: The related development model is constructed.•Carbon reduction discovery: Carbon emissions reduction for years is predicted.
A critical issue has been absent from the conversation on dynamic capabilities: the two seminal papers represent not only different but contradictory understandings of the construct's core elements. ...Here, we explore the reasons for this, using author cocitation analysis to inform our analysis. Our findings suggest that the field is being socially constructed on the basis of two separate domains of knowledge and that underlying structural impediments have impeded dialog across the domains. In light of this evidence, then, we take up the challenge to find a solution to this dilemma. By employing a contingency-based approach, we show that there are ways to unify the field that rely, paradoxically, on integrating the two contradictory views, while still preserving the assumptions that led to their differences.
This paper summarises the concepts of the Internet of things and its examples of application in libraries throughout the world. Given the existing university library digital infrastructure, a ...development path for our national university intelligent libraries based on the Internet of things was studied in detail from three aspects. We hope more university libraries will move towards true university intelligent libraries.
Carbon emissions caused by economic growth are the main cause of global warming, but controlling economic growth to reduce carbon emissions does not meet China's conditions. Therefore, how to ...synergize economic growth and carbon emission reduction is not only a sustainable development issue for China, but also significant for mitigating global warming. The territorial spatial functional pattern (TSFP) is the spatial carrier for coordinating economic development and carbon emissions, but how to establish the TSFP of synergizing economic growth and carbon emission reduction remains unresolved. We propose a decision framework for optimizing TSFP coupled with the multi-objective fuzzy linear programming and the patch-generating land use simulation model, to provide a new path to synergize economic growth and carbon emission reduction in China. To confirm the reliability, we took Qionglai City as the demonstration. The results found a significant spatiotemporal coupling between TSFP and the synergistic states between economic growth and carbon emission reduction (q ≥ 0.8220), which resolves the theoretical uncertainty about synergizing economic growth and carbon emission reduction through the path of TSFP optimization. The urban space of Qionglai City in 2025 and 2030 obtained by the decision framework was 6497.57 hm2 and 6628.72 hm2 respectively, distributed in the central and eastern regions; the rural space was 60,132.92 hm2 and 56,084.97 hm2, concentrated in the east, with a few located in the west; and the ecological space was 71,072.52 hm2 and 74,998.31 hm2, mainly located in the western and southeastern areas. Compared with the TSFP in 2020, the carbon emission intensity of the TSFP obtained by the decision framework was reduced by 0.7 and 4.7 tons/million yuan, respectively, and realized the synergy between economic growth and carbon emission reduction (decoupling index was 0.25 and 0.21). Further confirming that TSFP optimization is an effective way to synergize economic growth and carbon emission reduction, which can provide policy implications for coordinating economic growth and carbon emissions for China and even similar developing countries.
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•Spatiotemporal coupling exists between TSFP and synergistic states between economic growth and carbon emission reduction.•MFLP and two-stage algorithm obtain the quantitative structure of synergizing economic growth and carbon emission reduction with high robustness.•PLUS model can establish the TSFP of synergizing economic growth and carbon emission reduction.•TSFP Optimization is an effective way to synergize economic growth and carbon emission reduction.
