Search Results (306)

Under the construction background of carbon peak and carbon neutrality, high-energy-consuming enterprises, represented by the electrolytic aluminum industry, have become important carriers for energy conservation and emission reduction. These enterprises are characterized by significant energy consumption and high carbon emissions, greatly impacting the economic and environmental benefits of regional power grids. Existing research often focuses on grid revenue, leaving high-energy-consuming enterprises in a passive regulatory position. To address this, this paper constructs an economic dispatch strategy for power grids that considers waste heat utilization in high-energy-consuming enterprises. A typical representative, electrolytic aluminum load and its waste heat utilization model, for the entire production process of high-energy-consuming loads, is established. Using a tiered carbon trading calculation formula, a low-carbon production scheme for high-energy-consuming enterprises is developed. On the grid side, considering local load levels, the uncertainty of wind power output, and the energy demands of aluminum production, a robust day-ahead economic dispatch model is established. Case analysis based on the modified IEEE-30 node system demonstrates that the proposed method balances economic efficiency and low-carbon performance while reducing the conservatism of traditional optimization approaches. Full article

Chinese public building carbon emissions trading system (CETS) pilots have employed different carbon quota methods over more than ten years. However, there are few quantitative comparisons on CETS emission reduction effects in different pilots based on the carbon quota analysis. This paper first calculates the annual carbon quotas of public buildings based on carbon quota allocation methodologies from municipal policy documents. Then, the factors affecting the carbon quotas of public buildings are analyzed. Finally, the emission reduction effects are analyzed and compared between the pilots. The findings are concluded as follows: (1) Public building stock area and energy efficiency demonstrate significant effects on the carbon quota. (2) The average annual carbon quota deficits of public buildings were 929,800 tons in Beijing and 596,000 tons in Shanghai, while the carbon quota was an annual surplus of 296,400 tons in Shenzhen, indicating that carbon quota allocations in Beijing and Shanghai pilots are more conducive to promoting the active participation of high-emission enterprises. (3) The emission reduction effect in Beijing is most pronounced, followed by Shanghai and finally Shenzhen. Accordingly, the reasons for the difference in emission reduction effects are analyzed. This study contributes to the carbon quota allocation and emission reduction of public buildings. Full article

The Carbon Emissions Trading System (ETS) serves as a market-based mechanism to drive renewable energy (RE) investments, yet its heterogeneous impacts on different stakeholders remain underexplored. This paper treats the carbon market as an exogenous shock and develops a multi-agent equilibrium model incorporating carbon pricing, encompassing power generation enterprises, power transmission enterprises, power consumers, and the government, to analyze how carbon prices reshape RE investment layouts under dual-carbon goals. Using panel data from Zhejiang Province (2017–2022), a high-energy-consumption region with 25% net electricity imports, we simulate heterogeneous responses of agents to carbon price fluctuations (CNY 50–250/ton). The results show that RE on-grid electricity increases (+0.55% to +2.89%), while thermal power declines (–4.98% to −15.39%) on the generation side. Transmission-side RE sales rise (+3.25% to +9.74%), though total electricity sales decrease (−0.49% to −2.22%). On the consumption side, RE self-generation grows (+2.12% to +5.93%), yet higher carbon prices reduce overall utility (−0.44% to −2.05%). Furthermore, external electricity integration (peaking at 28.5% of sales in 2020) alleviates provincial entities’ carbon cost pressure under high carbon prices. This study offers systematic insights for renewable energy investment decisions and policy optimization. Full article

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

Capturing CO₂ emitted by coal chemical enterprises and injecting it into oil reservoirs not only effectively improves the recovery rate and development efficiency of tight oil reservoirs in the Ordos Basin but also addresses the carbon emission problem constraining the development of the region. Since initiating field experiments in 2012, the Ordos Basin has become a significant base for CCUS (Carbon capture, Utilization, and Storage) technology application and demonstration in China. However, over the years, projects have primarily focused on enhancing the recovery rate of CO₂ flooding, while issues such as potential reservoir damage and its extent have received insufficient attention. This oversight hinder the long-term development and promotion of CO₂ flooding technology in the region. Experimental results were comprehensively analyzed using techniques including nuclear magnetic resonance (NMR), X-ray diffraction (XRD), scanning electron microscopy (SEM), inductively coupled plasma (ICP), and ion chromography (IG). The findings indicate that under current reservoir temperature and pressure conditions, significant asphaltene deposition and calcium carbonate precipitation do not occur during CO₂ flooding. The reservoir’s characteristics-high feldspar content, low carbon mineral content, and low clay mineral content determine that the primary mechanism affecting physical properties under CO₂ flooding in the Chang 4 + 5 tight sandstone reservoir is not, as traditional understand, carbon mineral dissolution or primary clay mineral expansion and migration. Instead, feldspar corrosion and secondary particles migration are the fundamental reasons for the changes in reservoir properties. As permeability increases, micro pore blockage decreases, and the damaging effect of CO₂ flooding on reservoir permeability diminishes. Permeability and micro pore structure are therefore significant factors determining the damage degree of CO₂ flooding inflicts on tight reservoirs. In addition, temperature and pressure have a significant impact on the extent of reservoir damage caused by CO₂ flooding in the study region. At a given reservoir temperature, increasing CO₂ injection pressure can mitigate reservoir damage. It is recommended to avoid conducting CO₂ flooding projects in reservoirs with severe pressure attenuation, low permeability, and narrow pore throats as much as possible to prevent serious damage to the reservoir. At the same time, the production pressure difference should be reasonably controlled during the production process to reduce the risk and degree of calcium carbonate precipitation near oil production wells. Full article

As inevitable outcomes of the digital economy’s low-carbon development, green data centers play a crucial role in environmental impact and underlying mechanisms. This study focuses on green data center establishment as a representative practice, utilizing Chinese A-share listed companies and urban data from 2009 to 2023 to construct a multi-period difference-in-differences model. From a supply chain perspective, we investigate the impact of green data centers on corporate carbon emissions and their mechanisms. The results demonstrate that regional establishment of green data centers significantly promotes corporate carbon emission reduction, with conclusions remaining robust after a series of comprehensive robustness and endogeneity tests. This process primarily operates through two channels: green total factor energy efficiency and green attention. Green data center establishment significantly enhances green total factor energy efficiency and corporate green attention. The more developed the regional digital infrastructure and the higher the computing power development levels, the stronger the incentive effect on corporate carbon reduction. Heterogeneity analysis reveals that green data centers have more significant promoting effects on carbon emission reduction in state-owned enterprises and high-tech enterprises. This research contributes to a deeper understanding of the effects, mechanisms, and regional variations related to green data centers in facilitating corporate carbon emission reduction. Full article

Amidst the dual challenges of escalating ecological environmental pressures and economic transformation globally, green innovation emerges as a pivotal pathway toward achieving high-quality sustainable development. To elucidate how digitalization and novel productive forces synergistically drive the green transition, the research utilizes panel data from 30 provincial-level administrative regions in China spanning 2009 to 2022, constructing a green innovation efficiency measurement frame-work grounded in the Super Slack-Based Measure (Super-SBM)model, alongside a novel productive forces evaluation system based on the triad of laborers, labor objects, and means of production. Employing spatial difference-in-differences and double machine learning methodologies within a quasi-natural experimental design, the research investigates the causal mechanisms through which digital empowerment and novel productive forces influence regional green innovation efficiency. The findings reveal that both digital empowerment and novel productive forces significantly enhance regional green innovation efficiency, exhibiting pronounced positive spatial spillover effects on neighboring regions. Heterogeneity analyses demonstrate that the promotive impacts are more pronounced in eastern provinces compared to central and western counterparts, in provinces participating in carbon trading relative to those that do not, and in innovation-driven provinces versus non-innovative ones. Mediation analysis indicates that digital empowerment operates by fostering the aggregation of innovative talent and elevating governmental ecological attentiveness, whereas new-type productivity exerts its influence primarily through intellectual property protection and the clustering of high-technology industries. The results offer empirical foundations for policymakers to devise coordinated regional green development strategies, refine digital transformation policies, and promote industrial structural optimization. Furthermore, this research provides valuable data-driven insights and theoretical guidance for local governments and enterprises in cultivating green innovation and new-type productivity. Full article

In the context of China’s “dual carbon” goals and rising green trade barriers, green transformation is key to improving total factor productivity (TFP) and competitiveness in marine industries. This study uses panel data of Chinese listed marine enterprises (2014–2023) and a multidimensional fixed-effects model to examine how green innovation, export, and R&D investment jointly affect TFP. Results show that (1) green innovation has an inverted “S”-shaped nonlinear effect on TFP, with marginal returns rising, then accelerating, and finally declining; (2) positive synergies exist between green innovation and both exports and R&D, while the export–R&D interaction negatively affects TFP, indicating coordination challenges.; and (3) ownership heterogeneity matters, as state-owned enterprises benefit from stronger institutional support, mitigating negative effects, while private firms are more vulnerable due to weaker green technology mechanisms. This study emphasizes green innovation as a driver for sustainable productivity growth in marine enterprises and suggests policies that improve institutional frameworks, incentives, and resource allocation to support high-quality green innovation. Full article

The convergence of intelligent computational innovations—exemplified by cognitive intelligence—into the real economy is fundamentally transforming traditional industries and driving high-quality development. As a cornerstone of national economic growth, the energy sector faces mounting pressure to meet demands for green, low-carbon, and sustainable development, particularly under “dual carbon” targets and tightening regulatory frameworks. This study examines how digital transformation in this sector facilitates or impedes carbon emission reduction and green growth. Focusing on five key energy subsectors, including coal mining and processing, a coupling coordination model assesses the interaction between digitalization and greening. Utilizing panel data spanning from 2014 to 2023, the study systematically evaluates the level of digital–green coordination across the sector. The results indicate notable inter-sectoral variation, alongside a consistent upward trend in the overall coupling coordination, reaching moderate to high levels. These findings offer critical strategic insights for policymakers and energy enterprises seeking to harmonize digital innovation with green transition goals. The empirical evidence underscores the potential of next-generation technologies to expedite intelligent system upgrades, embed green development practices, and enhance enterprise-level carbon reduction and sustainability performance. Full article

Amidst escalating concerns about climate change, manufacturers are increasingly pressured to adopt a low-carbon supply chain (LCSC). Financial constraints deter numerous companies from embracing low-carbon initiatives in a competitive landscape. Inclusive internal financing (IIF) provides operational funds from capital-abundant members to capital-constrained members, resolving funding shortages internally within the system. However, when dominant members cannot support all such enterprises, selective internal financing (SIF) or hybrid financing (HF) becomes necessary. This paper studies the operation and financing strategies of a competitive LCSC. Within the framework of an LCSC where two capital-constrained retailers compete, using Stackelberg game theory and the backward induction method, three game-theoretical models are developed under IIF, SIF, and HF. The results indicate that increased competition intensity reduces product sales price, the manufacturer’s carbon emission reduction level, and profit. When competition intensity is high, SIF more effectively enhances carbon emission reduction level, product sales quantity, and profit acquisition. HF reduces profits for the allied retailer and diminishes its competitiveness, yet enhances the competitive strength of the rival retailer. Numerical analysis demonstrates that when equity financing in HF exceeds 0.546, the allied retailer becomes unprofitable and is driven out of the market. This study complements LCSC finance research and provides references for supply chain operations and financing strategy formulation. Full article

This study investigates the coupling coordination between carbon emission efficiency (CEE) and carbon balance (CB) in the Yellow River Basin (YRB), aiming to support high-quality regional development and the realization of China’s “dual carbon” goals. Based on panel data from 74 cities in the YRB between 2006 and 2022, the Super-SBM model, Ecological Support Coefficient (ESC), and coupling coordination degree (CCD) model are applied to evaluate the synergy between CEE and CB. Spatiotemporal patterns and driving mechanisms are analyzed using kernel density estimation, Moran’s I index, the Dagum Gini coefficient, Markov chains, and the XGBoost algorithm. The results reveal a generally low and declining level of CCD, with the upstream and midstream regions performing better than the downstream. Spatial clustering is evident, characterized by significant positive autocorrelation and high-high or low-low clusters. Although regional disparities in CCD have narrowed slightly over time, interregional differences remain the primary source of variation. The likelihood of leapfrog development in CCD is limited, and high-CCD regions exhibit weak spillover effects. Forest coverage is identified as the most critical driver, significantly promoting CCD. Conversely, population density, urbanization, energy structure, and energy intensity negatively affect coordination. Economic development demonstrates a U-shaped relationship with CCD. Moreover, nonlinear interactions among forest coverage, population density, energy structure, and industrial enterprise scale further intensify the complexity of CCD. These findings provide important implications for enhancing regional carbon governance and achieving balanced ecological-economic development in the YRB. Full article

This paper empirically investigates the impact of energy transition on corporate performance by utilizing panel data from A-share listed companies in Shanghai and Shenzhen between 2008 and 2022. Employing a fixed-effects model, the analysis incorporates key mediating variables including financing constraints, research and development (R&D) investment, corporate reputation, and investor attention. The results demonstrate that the energy transition exerts a significantly positive effect on firm performance, primarily through alleviating financing constraints and stimulating R&D activities. These effects are notably stronger among firms with higher market responsiveness and in regions exhibiting greater levels of economic development—particularly small- and medium-sized enterprises (SMEs), non-state-owned firms, enterprises located in eastern China, and those operating in high-carbon-emitting industries. Furthermore, enhanced corporate reputation and heightened investor attention serve as important amplifiers, reinforcing the positive relationship between energy transition and firm performance. This suggests the existence of a virtuous cycle wherein “transition investment” facilitates “resource integration,” ultimately leading to superior “performance outcomes.” The findings highlight the strategic value of aligning energy transition efforts with firm-level capabilities, indicating that sustainable investments can serve as a pathway to both environmental and economic gains through enhanced competitiveness and stakeholder engagement. Full article

Reducing carbon dioxide emissions within carbon-intensive industries is a critical strategy to effectively combat global warming. The accelerated cultivation and enhancement of new quality productivity has created new momentum directed towards industrial low-carbon transformation. Using data from a sample of Chinese provinces and enterprises between 2011 and 2022, this study quantifies, evaluates, and explores the influence and mechanisms of new quality productivity on the low-carbon transformation of carbon-intensive industries. The research findings show that: (1) Fostering new quality productivity effectively promotes the low-carbon transformation of carbon-intensive industries and plays a positive, empowering role. Industrial innovation, digital stimulation, technological innovation, and green empowerment all support the low-carbon transformation of carbon-intensive industries, with their respective impacts gradually decreasing in turn. (2) Mechanism analysis confirms a chain transmission mechanism of “new quality productivity—environmental protection investment—green innovation—the transformation of carbon-intensive industries” at the macro-provincial level. In micro-level carbon-intensive enterprises, a positive U-shaped relationship between new quality productivity and low-carbon transformation of carbon-intensive industries is evident, and the main pathways include increasing low-carbon, energy-saving investment and improving the ESG performance of high-carbon emission enterprises. (3) Advancing transformation is more pronounced in central and western areas, high-carbon areas, non-carbon trading pilot areas, and non-energy-rich ecologically fragile areas. The government and enterprises should take advantage of the development opportunities of new quality productivity and adopt low-carbon behaviors to promote transformational development. Full article

Driven by the global energy transition and the pursuit of “dual carbon” goals, sustainability risks within the coal supply chain have emerged as a central obstacle impeding the low-carbon transformation of high-carbon industries. To address the critical gap in systematic and multidimensional risk assessments for coal supply chains, this study proposes a hybrid framework that integrates the analytic hierarchy process (AHP) with the fuzzy comprehensive evaluation (FCE) method. Utilizing the Delphi method and the coefficient of variation technique, this study develops a risk assessment system encompassing eight primary criteria and forty sub-criteria. These indicators cover economic, operational safety, ecological and environmental, management policy, demand, sustainable supply, information technology, and social risks. An empirical analysis is conducted, using a prominent Chinese coal enterprise as a case study. The findings demonstrate that the overall risk level of the enterprise is “moderate”, with demand risk, information technology risk, and social risk ranking as the top three concerns. This underscores the substantial impact of accelerated energy substitution, digital system vulnerabilities, and stakeholder conflicts on supply chain resilience. Further analysis elucidates the transmission mechanisms of critical risk nodes, including financing constraints, equipment modernization delays, and deficiencies in end-of-pipe governance. Targeted strategies are proposed, such as constructing a diversified financing matrix, developing a blockchain-based data-sharing platform, and establishing a community co-governance mechanism. These measures offer scientific decision-making support for the coal industry’s efforts to balance “ensuring supply” with “reducing carbon emissions”, and provide a replicable risk assessment paradigm for the sustainable transformation of global high-carbon supply chains. Full article

Under the “Dual Carbon” strategy, collaborative governance of port atmospheric pollutants and carbon emissions is critical for low-carbon transformation. Focusing on Ningbo-Zhoushan Port (48% regional ship emissions), this study examines government, port enterprises, and public interactions. A tripartite evolutionary game model with numerical simulation reveals dynamic patterns and key factors. The results show the following: (1) A substitution effect exists between government incentive costs and penalty intensity—increased environmental governance budgets reduce the probability of government incentives, whereas higher public reporting rewards accelerate corporate emission reduction convergence. (2) Public supervision exhibits cyclical fluctuations due to conflicts between individual rationality and collective interests, with excessive reporting rewards potentially triggering free-rider behavior. (3) The system exhibits two stable equilibria: a low-efficiency equilibrium (0,0,0) and a high-efficiency equilibrium (1,1,1). The latter requires policy cost compensation, corporate emission reduction gains exceeding investments, and a supervision benefit–cost ratio greater than 1. Accordingly, the study proposes a three-dimensional “Incentive–Constraint–Collaboration” governance strategy, recommending floating penalty mechanisms, green financial instrument innovation, and community supervision network optimization to balance environmental benefits with fiscal sustainability. This research provides a dynamic decision-making framework for multi-agent collaborative emission reduction in ports, offering both methodological innovation and practical guidance value. Full article