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In order to achieve sustainable development goals, China has further increased its goal of reducing carbon intensity and has made digitalization an important support for sustainable development. However, the impact of digitalization on carbon intensity reduction is still unclear. In this context, this paper first evaluates the digitalization level of 30 provincial regions in China and then constructs a spatial Durbin model for two stages, 2012–2015 and 2016–2019, so as to explore the spatial spillover effects of carbon intensity in different stages and the important roles of digital infrastructure and digital inputs in carbon intensity reduction. The main findings are as follows: (1) the current digitization level of each province in China is widely disparate, with the region showing a high level in the east and a low level in the west; (2) carbon intensity reduction has a significant spatial spillover effect, as shown by a 1% reduction in local carbon intensity and a 0.21% reduction in neighboring regions; and (3) digitalization has a more significant positive impact on the reduction in carbon intensity in stage 2. The research results are strong demonstration that digitalization drives sustainable development. [ABSTRACT FROM AUTHOR]

With the process of economic transformation and structural adjustment, low-carbon development has become an intrinsic and realistic demand for China's national economic and social development. This paper builds a system dynamic (SD) model of China's low-carbon development based on the internal influencing mechanisms of carbon sources, carbon flows, and carbon sinks, and then explores the impact of carbon sources, carbon flows, and carbon sinks system on carbon emissions under different scenarios. The model in our study is effective and practical, and it can not only clearly demonstrate the interaction mechanism between various systems but also provide effective policy recommendations for policymakers. The results show that (1) with the steady growth of the economy, China's total energy consumption and carbon emissions have increased significantly. By 2025, the total energy consumption will reach 628 798 ten thousand tons, and the carbon emissions will reach 689 257 ten thousand tons; (2) as for energy and industrial structure, on the one hand, energy restructuring is more effective in reducing carbon emissions than is industrial restructuring; (3) carbon sinks also play an important role in reducing greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

Green growth has become an increasingly important paradigm for sustainable economic growth, resource development, and environmental protection. As the main focus in energy led green growth is a move away from fossil energy to clean energy, sustainable green growth resource development needs to measure both energy and environmental efficiencies. As the largest global energy consumer and carbon emitter, China has had to deal with serious energy and environmental issues in recent years, with its regional green growth performances being poorly assessed. Therefore, green growth clean energy-environmental efficiency assessments were examined in this paper, for which an integrated principal component analysis-data envelopment analysis based analysis approach was developed. It was found that while China's green growth has had a significant increasing trend in recent years, overall it was still at a low level, with the imbalances in China's regional economic development being reflected in its green growth. However, the excellent development and utilization of clean energy in most regions have significantly promoted a continuous improvement in China's green growth and the move toward sustainable resource development and utilization is contributing to long-term green growth. Green growth has also placed new demands on sustainable resource development in China. Therefore, underdeveloped regions that have sustainable resource endowments need to develop industrial systems that have clean energy as the main axis, and developed regions need to develop high-end industries that have low energy consumption and encourage mutual support systems between regions to ensure optimal sustainable resource, green growth development patterns. [ABSTRACT FROM AUTHOR]

As the largest energy consumption country, China now pays more and more attention to photovoltaic power generation because solar energy is the largest renewable and sustainable energy reserve in the world. In this case, the photovoltaic power generation plant project plays a crucial role in sustainable development, especially in the underdeveloped northwest region of China. This paper focuses on applying bi-level programing to the multimode resource-constrained project scheduling problem (MRCPSP) in photovoltaic power generation plant construction, which simultaneously considers the practical hierarchical organization structure and an uncertain decision-making environment. A bi-level fuzzy random multiple objective model is developed, wherein the government agency is in the upper decision level, while the contractor is in the lower decision level. Then, motivated by the particular mathematical nature of the proposed bi-level MRCPSP model, a hybrid intelligent algorithm is designed. Finally, a practical case from the Shenneng Futa Kashi-Tashi-Kuergan photovoltaic power generation plant project in a Chinese energy company is applied, and the results validate the practicability of the proposed model and solution algorithm for solving practical photovoltaic power plant project scheduling problems. [ABSTRACT FROM AUTHOR]

The austere environmental and resource developing situation in China poses adverse conditions to power generation enterprises, especially thermal power enterprises. Moreover, the new round electric market reform is being pushed forward vigorously, which greatly affects the future developing path for power generation enterprises. A comprehensive competition performance and ability evaluation is significant for power generation enterprises' laudable and sustainable development in the current situation. In this paper, a novel hybrid multi-criteria decision making (MCDM) framework is established for the evaluation. To effectively deal with the hesitation and uncertainty frequently occurring in the evaluation process, we combine the fuzzy set theory and the hesitant fuzzy linguistic term set (HFLTS) with traditional MCDM methods, Analytic Hierarchy Process (AHP), and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The HFLTS-AHP method is used to determine the weight allocation of criteria, and fuzzy-VIKOR further gives performance rankings of the alternatives. The evaluation index system is established based on sustainable perspective and enterprise management, which contains ten sub-criteria from four aspects, "economy," "environment and society," "resource and technology," and "sustainable development." In empirical analysis, four large power generation enterprises are selected to perform the competition ability evaluation with the proposed framework. The results provide a reliable competition performance rank for the four alternatives and indicate that during the evaluation process, the sub-criteria "return on capital," "electricity trading rate," and "renewable energy installed capacity proportion" are more important. Finally, to verify the validity and robustness of the model, a set of sensitivity analyses are conducted. The proposed hybrid MCDM framework shows the advantages and practical value for competition ability evaluation of power generation enterprises. [ABSTRACT FROM AUTHOR]

This paper describes the progress of the research and practice on incorporating mobile sources, especially motor vehicles, into Shenzhen Emissions Trading System. Insights gained through Shenzhen's experience will provide useful insights to others that may have cause to consider the expansion of their Emissions Trading System (ETS) to include mobile sources. In order to incorporate public transportation into the ETS pilot, the city has formulated quantitative greenhouse gas emissions standards for bus and taxi companies, drawn the baselines for energy consumption and carbon emissions of public transportation, and revised local emissions trading regulations. For the further inclusion of non-public transportation vehicles, studies were made on emissions quantification, allowances allocation, non-compliance penalties, and emission reductions certification. In the future, the work will focus on legal safeguards and trading mechanisms. [ABSTRACT FROM AUTHOR]

China's photovoltaic (PV) enterprises have experienced difficulties under the influence of the growth slowdown of international market and trade protectionism since 2012. In this paper, from a new perspective of building a hierarchical network model, by using the minimum spanning tree (MST) technique, the market characteristics of China's PV enterprises was researched. The economic distance in the MST was calculated by using PV enterprises' daily closing price of stocks during the years 2007-2013. With the analysis of the topology of hierarchical network, the community structures of the network are derived and some influential enterprises are identified. It is necessary for PV enterprises to deeply connect and cooperate with each other to cope with market risk. What's more, the key factors that affect the hierarchical network were also studied; the result indicates that assets expansion and the core technology competitiveness are important factors for the development of PV enterprises. In the end, some suggestions are put forward to promote sustainable development of China's PV industry. [ABSTRACT FROM AUTHOR]