Industry-urban integration (IUI) is an innovative strategy that has emerged as a pivotal pathway for promoting resource and environmental management. Green economic efficiency (GEE) represents a major trend in global economic transformation and significantly impacts IUI, warranting further investigation. Drawing on data from the Yangtze River Delta region from 2012 to 2023, this study employs heterogeneity analysis, mediating effect, and threshold effect mechanisms to comprehensively evaluate the GEE’s role in IUI. The findings reveal the following key insights: First, the impact of GEE on IUI varies across regions, with a stronger effect in economically developed areas and non-resource-based urban areas with green economic efficiency policies. Second, the mediating effect identifies the improvement strategies of the GEE that indirectly drive IUI by enhancing government fiscal decentralization (GFD). Third, the relationship between the GEE and IUI demonstrates a threshold effect driven by technological innovation (Tech). Upon TECH capability rising above a critical level, the beneficial influence of GEE on IUI becomes markedly more evident. This study offers policy recommendations to advance both the GEE and IUI, contributing to the integration of environmental, economic, and societal strategies.

Policy synergy plays a pivotal role in shaping strategic enterprise decisions during the ongoing transition towards renewable energy. This study thoroughly examines policy synergy, including environmental taxes (ETs) and fiscal tax policies (FTPs), which propel enterprise digital transformation (DT) within the renewable energy transition. Using panel data on Chinese A-share listed enterprises from 2008 to 2023, this study empirically examined the impact of ETs and FTPs on enterprise DT. The results revealed that ETs drive enterprise DT significantly. Although FTPs are generally recognised as effective, they exhibit diminishing marginal returns. Crucially, this study identified a non-linear threshold effect: FTPs unleash their full potential when the ETs pressure exceeds a specific intensity. This implies that ETs, as sticks, are a prerequisite for FTPs to function effectively in the context of a renewable energy transition. Heterogeneity analyses show that the effects of policy synergies vary substantially across institutional and market contexts. Additionally, the mediation analyses suggest that ETs foster enterprise DT through green innovation, reduce financing constraints, and diminish executive overconfidence. This study provides evidence that environmental and fiscal policy instruments can foster enterprise DT and support renewable energy transitions, offering valuable insights for designing effective policy toolkits in the context of renewable energy development.

The global transition to renewable energy (RE) hinges on the design of effective and economically efficient policy portfolios. This study develops a Stackelberg game-theoretic model of a power supply chain—comprising a generation company, a retailer, and consumers—to dissect the intricate relationships between subsidy policies, market mechanisms, and consumer behavioral characteristics. We rigorously evaluate three policy scenarios: No Subsidy (N), Subsidized Consumers (C), and Subsidized Generation Companies (G). The model explicitly quantifies subsidy perception efficiency gap between consumers and producers, and it embeds this analysis within an integrated framework combining Renewable Energy Certificate (REC) trading and Renewable Portfolio Standards (RPS). Our findings reveal that the effectiveness of a subsidy is determined not by its target (consumer vs. generation company) but by the recipient's perception efficiency. Subsidies enhance social welfare only when this efficiency surpasses a critical threshold. Furthermore, consumer environmental preferences emerge as a consistently positive driver of green power adoption and social welfare across all scenarios. We also identify a welfare-maximizing threshold for REC prices, whereas overly stringent RPS mandates are shown to be detrimental. These insights provide a robust theoretical foundation for designing coordinated, consumer-aware RE policies that can accelerate the energy transition while optimizing social welfare.

China’s effort to establish a provincial-municipal two-tier carbon emissions budget system faces a critical challenge: how to fairly distribute municipal carbon emission rights under provincial carbon constraints while accounting for diverse regional interests. This study aims to address this gap by proposing four municipal carbon allowance allocation schemes from equity and efficiency perspectives, using Anhui Province to analyze their differentiated outcomes. To balance diverse regional interests, the research introduces the Preference Score Compromise (PSC) method, developing a composite allocation scheme that integrates fairness and efficiency. Quantitative analysis via Gini coefficient and optimization models reveals significant municipal preferences for schemes: Suzhou and Fuyang favor the per capita principle, Huaibei and Ma’anshan prefer the grandfathering principle, while Hefei and Wuhu prioritize economic output. Under the composite scheme, Hefei, Ma’anshan, and Fuyang obtain larger carbon shares (collectively one-third of the province’s total), whereas Huangshan, Chizhou, and Tongling have smaller allocations. Notably, this scheme minimizes overall abatement costs while balancing efficiency and fairness. Additionally, a regional carbon market based on this scheme with 10–20

This paper examines the impact of digital economy development on household energy burden inequality in the context of China's low-carbon transition. Using panel data from the China Family Panel Studies (CFPS) covering the years 2012-2022, the empirical analysis suggests that while the digital economy has grown rapidly, it has also exacerbated the inequality in household energy burdens. The mechanism analysis indicates that the development of the digital economy primarily affects energy expenditure inequality, especially spending on clean energy, which contributes to disparities in household energy burdens. Moreover, significant differences in energy burdens exist between urban and rural households, with rural households facing heavier energy burdens than their urban counterparts. The inequality in energy burdens also varies across different income groups, with the disparity becoming more pronounced. The findings of this paper provide scientific evidence and policy implications for energy transition and the cautious promotion of carbon peaking and carbon neutrality.

Enterprise green technology innovation efficiency (GTIE) is a crucial driver of low-carbon energy transformation (LCET), with artificial intelligence (AI) emerging as a pivotal tool for augmenting enterprise GTIE. This study leverages data from the International Federation of Robotics and employs the Super-EBM-GML model to assess enterprise GTIE. By conducting an empirical analysis of annual data encompassing Chinese A-share listed enterprises from 2008 to 2022, this study uncovers the effects of AI on LCET through a comprehensive examination of both the heterogeneous environmental factors and internal regulatory mechanisms that affect enterprise GTIE. The heterogeneity analysis reveals that AI significantly boosts GTIE in competitive, high-tech, non-state-owned, and labor-intensive enterprises. However, AI has no positive effect on state-owned enterprises and even hampers technology-intensive enterprise GTIE. Furthermore, this study emphasizes that AI indirectly facilitates enterprise GTIE by alleviating financial constraints and bolstering research and development investments. Additionally, the threshold mechanism shows that human capital significantly amplifies the effect of AI on enterprise GTIE when a certain threshold is surpassed. However, the relationship between AI and income growth has an inverted U-shaped curve. This study provides valuable insights for devising optimal strategies for harnessing AI to support LCET from the perspective of enterprise GTIE, thereby offering valuable guidance for aligning LCET for effective energy management.

In response to the U.S. chip embargo, China has proposed export controls on crucial materials like gallium, germanium, and graphite. However, few studies have explored the economic impacts of these trade sanctions policies. This study aims to address this gap by examining theoretical mechanisms and constructing a global input-output database for the chip, gallium-germanium, and graphite sectors. Using a dynamic computable general equilibrium model, we evaluate the dynamic economic impacts of Sino-U.S. technological competition and conduct robustness tests. The results show that in the initial stage of policy implementation, under the most extreme situation of chip embargo, the GDP of China, U.S., and the world decreases by 1.051%, 0.006%, and 0.201%, respectively; that of Japan, South Korea, and Chinese Taiwan, which follow the U.S. in implementing chip sanctions, decreases by 0.109%, 0.177%, and 0.330%, respectively. China's export controls on crucial raw materials are shown to reduce national economic damage and have a large negative impact on Japan, South Korea, and Chinese Taiwan. Moreover, these negative impacts tend to worsen over time. Our findings reveal that Sino-U.S. technological competition is unfavorable to the economic interests of the two countries and poses challenges to global economic recovery in the post-pandemic era, indicating the importance of narrowing the gap and reducing the confrontation between China and the U.S. for global economic growth.

Ratcheting-up of countriesu2019 Nationally Determined Contributions (NDCs) is urgently needed to keep the Paris Agreementu2019s 2 u00B0C goal within reach. However, unbalanced climate policies may lead to inequitable impacts on trade and competitiveness, which is becoming a major obstacle for countries to advance ambitious climate actions. To address this problem, we propose an NDC enhancement scheme based on cost-fair differentiated carbon pricing mechanism (DCPM). Using a global computable general equilibrium model, we compare the proposed DCPM-based scheme with another two reference NDC enhancement schemes (i.e., the constant emissions ratio scheme, and the uniform global carbon price scheme) in terms of their impacts on competitiveness and regional welfare. The results show that, with the joint global target being identical, the DCPM-based scheme results in more equitable competitiveness impacts than the other two schemes. It also performs better in balancing regional welfare impacts and promoting progressive burden-sharing. The DCPM-based scheme can provide helpful guidance for countries to reconcile their competitiveness concerns and to coordinate climate policies while achieving enhanced climate goals.

The clean energy transition centered on photovoltaic solar and wind power is widely regarded as the fundamental way to achieve the Paris Agreement's pledges. The development of clean energies, however, relies much more on critical minerals than that of conventional ones. It is therefore vital to incorporate mineral constraints into integrated assessment modeling and designing of energy transition pathways. To this end, we reexamine the feasibility of China's energy transition evaluated by 5 typical integrated assessment models, then reconfigure the pathways and assess possible trade and warming risks by designing primary mineral supply, recovery and technological progress scenarios. The results indicate that the contribution of solar and wind power to achieve the Paris Agreement goals may far below our expectation due to critical mineral constraints, and the installed capacity of the targeted two renewables will averagely decline by over 56.7% and 68.9%, respectively, by 2060 under the 1.5 °C warming limit. This may lead to an emission gap of carbon reduction by up to 2.35 GtCO2, which will greatly challenge China's attainment of carbon neutrality.

This research delves into the interaction among green finance, the digital economy, and carbon emission mitigation. This analysis utilizes a comprehensive dataset covering the period from 2010 to 2022, meticulously gathered from all thirty-one provinces, alongside autonomous regions and municipalities, that constitute the vast geographical expanse of China. The results uncover several pivotal insights: green finance emerges as a crucial instrument in fostering regional carbon emission mitigation; correspondingly, the digital economy also lends a hand in reducing regional carbon emissions; the extent of green technology innovation occupies a central moderating position in the interplay between green finance and carbon emission mitigation; a threshold effect is observed in the impact of green finance on regional carbon emission mitigation, displaying distinct patterns contingent upon the regional population size; the influence of green finance on carbon emission mitigation reveals regional disparities, with the most prominent contribution manifesting in the western region, trailed by the central region, while its impact on the eastern region is comparatively less pronounced; Similarly, the influence of the digital economy on decreasing carbon emissions shows disparities across regions, notably boosting carbon reduction efforts in the eastern regions, while its effect is less marked in the central and western regions.

Enterprise green technology innovation (GTI) is a critical indicator for promoting renewable energy substitution, and intelligent transformation plays a pivotal role in this process. In this paper, we use a semi-parametric partial linear additive model to investigate the impact of intelligent transformation on enterprise GTI, which analyzes the panel data of Chinese A-share listed enterprises from 2008 to 2022. The findings reveal that intelligent transformation impacts enterprise GTI significantly with results withstanding robustness testing. The study shows that the improvement pathways of intelligent transformation on enterprise GTI are particularly pronounced in competitive enterprises, high-tech enterprises, and labor-intensive enterprises, while it has adverse impacts on technology-intensive enterprises. Further, the study identifies the improvement pathways of intelligent transformation indirectly impact enterprise GTI by easing financing constraints and strengthening research and development (R&D). Moreover, the improvement pathways of enterprise GTI quantity and quality are impacted by the fixed asset ratio. Specifically, an inverted U-shaped relationship emerges between the fixed asset ratio and the enterprise GTI quantity, while excessively low fixed asset ratios impede enterprise GTI quality and exceed a specific threshold markedly enhances GTI quality. This study provides valuable insights into intelligent transformation into the external and internal improvement pathways on enterprise GTI, which promotes economic growth and fosters high-quality renewable energy substitution development.

The concurrent acceleration of digitalization and urgent carbon reduction goals makes it critical to understand the spatial relationship between digital technology spillover and cross-regional carbon transfers. To this end, we investigate how interprovincial digital technology spillovers affect carbon transfers across China's economic sectors. Using a multi-regional input-output model for 31 Chinese provinces, we identify strong spatial correlations between sectoral carbon transfers and regional digital technology spillovers. We find that this relationship hinges on eco-friendly product development, market-aligned innovation, and sector-wide industrial transformations within their respective sectors. These findings provide policymakers with actionable, sector-specific insights for harnessing digitalization to mitigate carbon emissions, thereby advancing sustainable development and the pursuit of carbon equity.

The protection of natural resources was vital to promote the effective and sustainable utilization of nonrenewable energy. Resource taxation is an important policy tool for protecting natural resources and the ecological environment, and for realizing sustainable economic development. This study focuses on the coal resource tax reform and utilizes the difference-in-differences (DID) model to assess its impact on regional real GDP and resource tax revenue using panel data from 30 provinces in China spanning 2006 to 2021. We found that coal resource tax reform had significantly positive influence on the real GDP and resource tax revenue, and its effect on the latter was greater than that on the former. The reform contributes to improvements in energy structure, industrial agglomeration, and social consumption levels, which ultimately drives real regional GDP growth. The robustness test further confirms the robustness of these findings. This study puts forward several implications aimed at fostering ongoing enhancement of the coal resource tax reform policy, augmenting policy implementation flexibility, and providing guidance for enterprise technology research and advancement. By harnessing the supportive role of natural resource elements, policymakers can facilitate a green economic transformation and achieve high-quality economic development.

The International Clean Energy Market (ICEM) has emerged as one of the fastest-growing sectors in the energy industry. The increasing financialization and integration of the ICEM has meant that internal systemic risks have begun to surface, which can potentially seriously threaten the stable development of the ICEM. To explore systemic risk management strategies that can be enacted in the ICEM, this paper utilizes the Weighted Turbulence Model (WDTI) to measure the evolutionary characteristics of the systemic risk levels within the ICEM from 2012 to 2022. Subsequently, it explores spillover structure in the ICEM through volatility spillover effect (VSE). The results obtained indicate that the occurrence of systemic risk days in the ICEM is closely related to impact events, and its systemic risks are characterized by their rapid eruption, which can erupt more than twice. The volatility in any specific sub-sector within the ICEM can propagate throughout the entire system. The spillover pattern of volatility in the ICEM shows similarities across various economic cycles. The fuel cell market is specifically identified as the Systemically Important Market (SIM) within the ICEM. This paper establishes a theoretical foundation for managing systemic risk and ensuring the stability of ICEM.

China has made great efforts to establish an ecological compensation mechanism, but there lacks empirical evidence on whether this scheme effectively reduces air pollution. To test the effectiveness of air quality ecological compensation (AQEC) on air pollution control, this study considers 114 resource-based cities in China and uses a multi-period difference-in-difference (DID) model for empirical analysis. The finding shows that the AQEC policy significantly reduces the concentration of air pollutants by promoting air pollution prevention and local authority enthusiasm for pollution abatement, resulting in an average annual decrease in PM2.5 concentrations of approximately 3.9 mu g/m(3) in the pilot cities. The AQEC policy of resource-based cities in eastern and northern China, and those with less financial pressure have greater inhibitory effects on air pollution. The study recommends establishing long-term protection mechanisms and implementing differentiated policies focused on green technological innovation and financial autonomy.

OBJECTIVES:This paper investigates the role of digital finance in promoting environmental sustainability within a group of 52 developing economies from 2010 to 2019. Specifically, it examines whether digital finance effectively contributes reducing CO2 emissions in these nations. METHODS:This paper is a quantitative study which employs the IV-GMM (instrumental variable generalized methods of moment) approach that tackles any potential endogeneity. Furthermore, to ensure robustness of results, this paper also utilizes different measures of financial development. RESULTS:Estimation results from this study reveal the presence of inverted U-shaped relationship between digital finance and CO2 emissions. This suggests that the beneficial effects of digital finance may take time to materialize. Additionally, this research also records the presence of the Environmental Kuznets Curve and a significant impact of renewable energy, trade openness, financial development, urbanization, and population on CO2 emissions. CONCLUSIONS:It can be concluded that it may take time for digital finance to become beneficial to the environment. Therefore, in addition to digital finance, countries should also adopt other measures simultaneously (use of renewable energy, combination between digital finance and financial development).

Green technology innovation (GTI) is a crucial factor in the global quest for sustainability. This study examines the impact of environmental, social, and governance (ESG) ratings provided by SynTao Green Finance on the GTI of Chinese A-share listed enterprises from 2007 to 2022. By utilizing the time-varying difference-in-differences (DID) model and examining the promotion effect of GTI in application and authorization, the study demonstrates a positive relationship between higher ESG ratings and enterprises’ GTI. This conclusion is substantiated through rigorous robustness tests. The findings indicate that ESG ratings facilitate enterprises’ GTI by addressing financing constraints, mitigating agency issues, and fostering research and development investment. Moreover, ESG ratings are found to be beneficial for enterprises operating in highly competitive markets and garnering significant analytical attention, while not being conducive to GTI in heavily polluting or manufacturing enterprises. By overcoming the limitations of the traditional Ordinary Least Square model in dealing with time trends and persistence effects, this study elucidates the influencing factors of ESG ratings on enterprises’ GTI. Consequently, it provides valuable insights for enterprises to develop targeted sustainable strategies and achieve a mutually beneficial outcome for the economy and the environment.

This study examines the systemic risk caused by major events in the international energy market (IEM) and proposes a management strategy to mitigate it. Using the tail-event driven network (TENET) method, this study constructed a tail-risk spillover network (TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19 pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets (SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Enterprise green technology innovation (GTI) is vital for global sustainable development. However, the optimal strategies are needed to understand how environmental investments (EIs) impact enterprise GTI. This study analyzes the impact of EIs on the GTI of A-share listed enterprises in China from 2008 to 2022. Our results show that EIs significantly promote enterprise GTI, and these findings are robust. Heterogeneity analysis reveals that non-state-owned enterprises (non-SOEs) and enterprises in the eastern and western regions benefit more from EIs in promoting GTI. Labor-intensive combinations of EIs contribute to the growth of enterprise GTI quantity, while technology-intensive combinations of EIs are detrimental to the growth of enterprise GTI quality. Specifically, the intermediary conduction mechanism identifies that EIs substantially enhance enterprise GTI through three channels: financial constraints, research and development (R&D) investment, and environmental awareness. The threshold test mechanism demonstrates that EIs inhibit enterprise GTI when the price-to-book (P/B) ratio crosses a certain threshold; however, EIs promote enterprise GTI once the book-to-market (B/M) ratio crosses a different threshold. Our findings can provide useful references for governments and enterprises, and help to promote environmentally sustainable development and economic growth.

The worsening air pollution and frequent occurrence of haze have intensified urban ecological risk. It is crucial to investigate whether environmental regulation, as a government tool for urban ecological management, can effectively reduce the likelihood of ecological risk. Most previous studies focused on ecological risk of landscape, watersheds, and wetlands, but ignored atmospheric ecological risk. In this study, the panel data of Chinese cities were used to comprehensively measure the ecological risk induced by PM2.5 in various regions, and the role of environmental regulation in reducing ecological risk was tested, which provided empirical references for the study of air pollution-oriented ecological risk. The study found that the ecological risk level was high across China's regions, and the overall regional differences in ecological risk have slightly decreased. Environmental regulation demonstrates a noteworthy capacity to reduce local and adjacent ecological risk, particularly in higher-risk areas. The study further reveals that regulations have the highest inhibitory effect on ecological risk in central regions, and their impact has become more pronounced since 2012. Consequently, this research not only provides valuable data for measuring and evaluating urban ecological risk in China and addressing the current high-risk ecological situation through environmental regulation but also aids the government in expediting the resolution of ecological carrying capacity deficits and mitigating the risks to regional ecological balance.