This study examines how convertible bond issuance affects corporate innovation using a panel of Chinese listed firms from 2006 to 2023. The findings indicate that convertible bonds significantly enhance firms’ innovation output, as reflected in patenting activities. Mechanism analysis indicates that this effect operates through both internal capability enhancement and external governance mechanisms. Specifically, convertible bonds increase R&D investment and facilitate digital transformation, while simultaneously improving analyst attention and alleviating financing constraints. The innovation-enhancing effect is more pronounced among firms lacking directors’ and officers’ liability insurance and those with lower institutional ownership, suggesting that convertible bonds partially substitute for weak external monitoring. Further analysis indicates that for convertible bonds with a shorter weighted average conversion duration, the innovation-enhancing effect is more pronounced. Moreover, convertible bonds not only increase innovation output but also enhance its efficiency and quality, thus serving as a significant catalyst for corporate innovation.

Low-carbon infrastructure development constitutes a critical issue in global carbon governance. This study develops an extensive provincial-level green finance (GF) index and utilizes manually collected data from infrastructure-related industries spanning 2000-2022 to empirically examine the impact of GF on the embodied carbon efficiency of infrastructure. The findings reveal that GF significantly enhances the embodied carbon efficiency of infrastructure, primarily through three mechanisms: increasing investment in pollution control, stimulating green technological innovation, and promoting energy structure optimization. The positive effect of GF on infrastructure embodied carbon efficiency is more pronounced in provinces with higher marketization levels, coastal regions, areas with greater infrastructure investment, and those with stronger environmental awareness. Extended analyses suggest that GF not only reduces the input of energy factors in infrastructure construction but also boosts output value. By optimizing the factor allocation structure of infrastructure-related sectors, GF facilitates the low-carbon transition of infrastructure while sustaining economic growth. Moreover, GF contributes to both CO2 emissions reduction and high-quality development at the provincial level, demonstrating the dual dividends of coordinated carbon mitigation and economic advancement.

ObjectiveM50 steel, as a prevailing material for aero-engine bearing rings, typically undergoes cold ring rolling prior to quenching and tempering to achieve ring formation. However, due to the high deformation resistance of M50 at ambient temperature, conventional cold ring rolling processes under large deformation conditions are prone to induce micro-and nano-scale damage, adversely affecting grain refinement and thereby limiting the inheritance of microstructural characteristics during subsequent quenching and tempering, resulting in constrained enhancement of mechanical properties. Thus, a method has been proposed to further enhance the grain refinement of M50 steel under identical cold ring rolling parameters through electro-pulse assistance, thereby improving the microstructural heredity effect during its quenching and tempering process.MethodsThe electric pulse-assisted cold ring rolling-quenching and tempering (EPCRR-QT) process was employed, wherein pulsed electric current was synchronously applied during cold ring rolling to further optimize the microstructure. The evolution behavior of the microstructure during quenching and tempering was systematically analyzed.ResultsThe findings indicate that compared with specimens subjected to conventional cold ring rolling followed by quenching and tempering, those processed via EPCRR-QT exhibited a 15.2% refinement in prior austenite grain size. Additionally, reductions are observed in retained austenite content, Mo2C carbide content, and the fraction of low-angle grain boundaries. Correspondingly, Vickers hardness values increase by 4.7% in the quenched state and 4.4% in the tempered state.

Green technological innovation represents one of the critical driving forces for addressing environmental issues and advancing the sustainable development process. As a key driver of the new round of technological transformation, artificial intelligence is bound to exert significant impacts on firms’ green technological innovation. In this study, green technology innovation is divided into clean production and pollution control technology innovation according to the production link. A double fixed-effects model was used to test the impact of AI using data from Chinese listed companies from 2006 to 2020. The research findings are as follows: First, artificial intelligence has a significant contribution to green technology innovation in different segments. Second, mechanism analysis reveals that artificial intelligence enhances green technological innovation by improving human capital caliber and firm efficiency. Third, heterogeneity analysis shows that the greater the intensity of environmental regulation a firm faces, the greater the incentive for the firm to use AI for green technology innovation; its effect on pollution control technological innovation is more significant for firms in high-pollution industries; and its effect on clean production technological innovation is more prominent for enterprises in low-pollution industries.

Urban green spaces, as a crucial nature-based solution to mitigate "urban diseases", have received significant attention due to their pivotal role in providing ecosystem services. Available studies on the assessment of ecosystem services in urban green spaces predominantly rely on two-dimensional spatial characteristics, with insufficient exploration of three-dimensional structural attributes and their associated ecosystem service effects, which makes it difficult to comprehensively and accurately reveal the actual contribution of green space to enhance residents' well-being. We systematically reviewed current methods in assessing ecosystem services in urban green spaces, critically analyzed the limitations of two-dimensional spatial assessment approaches, and highlighted the application of emerging technologies (e.g., LiDAR, street view imagery, and artificial intelligence algorithms) in three-dimensional spatial evaluation. Then, we proposed an innovative framework integrating advanced technologies with three-dimensional assessment of urban green space ecosystem services, and discussed future research directions to address the challenges of current technologies, particularly in terms of data processing efficiency and multi-scale applications, aiming to provide theoretical support and practical guidance for the refined management and sustai-nable development of urban green spaces.

In the quest for carbon neutrality, optimizing the spatial layout of urban green infrastructure (UGI) is crucial for the carbon sink efficiency of green spaces. Morphological spatial pattern analysis (MSPA) can precisely classify raster images, greatly supporting the optimization of spatial structures. It is still a novel approach in the field of urban green space carbon sink performance research. This paper utilized MSPA along with hotspot analysis and various statistical methods to investigate and elucidate the mechanism of green infrastructure (GI) spatial pattern characteristics and carbon sink performance in 210 study units (each measuring 2 km x 2 km) in the central city of Nanjing. Results categorized study units into high, medium, and low carbon sink performance levels, revealing variations in the correlation between spatial patterns and carbon sink performance levels. Lower carbon sink performance levels show a stronger positive correlation with Core, while higher carbon sink performance levels exhibit a stronger negative correlation with Islet and Branch. We further introduced environmental factors such as temperature and Normalized Vegetation Index (NDVI) to reveal the indirect relationship of action of MSP affecting the performance of GI carbon sinks. Based on these findings, we proposed relevant strategies to improve the performance of GI carbon sinks from the MSP perspective.

Climate change and energy issues have important implications for the future of the planet. The energy transition plays a vital role in addressing the global energy and climate crisis, while artificial intelligence (AI) is a core driver of this transition. On the basis of data from 262 Chinese cities between 2006 and 2019, a comprehensive city-level index for AI is constructed, and the impacts of AI on the energy transition and the corresponding mechanism are explored. The results suggest that AI significantly promotes the energy transition, and the promotion effect is greater in resource-based cities and central and eastern cities at the city level, as well as in strategic emerging industries and capital-intensive industries at the industry level. Regarding the influence mechanism, AI development can improve the energy transition by promoting green technology innovation and digital transformation. However, importantly, at higher levels of AI development, risks such as the energy rebound effect could arise. In this case, excessive investment and use of electricity may counteract the increase in the energy transition. Thus, while acknowledging AI's pivotal role in the energy transition, it is equally critical to be aware of potential risks.

Under the carbon neutrality target, optimizing infrastructure investment pathways and spatial layouts requires an integrated consideration of their embodied carbon emission effects. Based on a quantitative assessment of embodied carbon efficiency in infrastructure, this study delineates the provincial-level features and heterogeneities in optimal infrastructure investment. The findings indicate that, while the embodied carbon efficiency of infrastructure has shown an upward trend across provinces, the overall level remains relatively low. Results from the zero-sum game DEA model reveal that optimal infrastructure investment exhibits a spatial pattern characterized by “higher in the east and lower in the west”, aligning with the theory of regional economic gradient development. Using a data-driven club convergence algorithm, provinces are classified into three clubs according to the optimal infrastructure investment level. The results demonstrate a persistent divergence among clubs, highlighting the risk of a “Matthew effect”. Moreover, intra-club disparities in infrastructure investment are identified as the core drivers of regional inequality. The findings offer valuable insights for policymakers in formulating infrastructure investment strategies and carbon reduction policies.

Eliminating poverty and combating climate change are the twin pillars of global sustainable development. Investigating the relationship between poverty alleviation and carbon emissions reduction can provide valuable insights for global poverty governance and climate action. This study treats China's national-level povertystricken counties (NPC) policy as a quasi-natural experiment, adopting the difference-in-differences approach to explore the effects and influencing mechanisms of poverty alleviation policies on carbon emissions intensity using county panel data from 2010 to 2018. The empirical findings reveal that the NPC policy notably lowered local carbon emissions intensity by a remarkable 9.12%, generating environmental benefits of 20.2-121.2 billion yuan. Mechanism analysis demonstrates that the NPC policy contributed to poor counties' green development by promoting industrial upgrading and improving ecological restoration. Heterogeneity analysis reveals that the carbon emissions reduction effect of the NPC policy was more pronounced in counties with large populations and rich resource endowment. Finally, the study proposes practical recommendations to advance the low-carbon effects of economic support policies.

Promoting the intelligent transformation and green development in manufacturing is a vital part of building a modern industrial system. Therefore, the role of intelligent manufacturing in promoting the green development of firms is worthy of in-depth study. This paper takes the implementation of intelligent manufacturing pilot demonstration projects (IMDP) in China as a quasi-natural experiment, and manually sorts out the list companies with IMDP. The difference-in-difference method is adopted to investigate the effect of intelligent manufacturing on the corporate environmental performance. Empirical results reveal that intelligent manufacturing has noticeable improved the corporate environmental performance through increasing investment in environmental protection, expanding human capital and innovating green technology. This confirms the “green dividends” in enterprise intelligent transformation does exist. Further analysis shows that the “green dividends” brought by intelligent manufacturing is more pronounced in non-state-owned, capital market concerned, and large-scale enterprises. This study theoretically reveals the relationship between intelligent transformation and manufacturing's green development, and provides practical guidance for the promotion of national industrial intelligent policy, which enlightens the high-quality development of manufacturing in emerging economies.

This paper begins by establishing a three-party game model involving three key players: the insurer, the firm, and the government. This model is used to analyze the utility of each party in various scenarios, one of which encourages green innovation within the firm. According to this model, when the insurer rejects insurance coverage and the government maintains a neutral stance on environmental liability insurance, the firm may opt to engage in green innovation. Green innovation fundamentally serves as a mechanism to mitigate environmental pollution risks stemming from the firm’s operational processes. In cases where the insurer declines underwriting, it becomes rational for the firm to enhance its risk management through green innovation, which can be viewed as a mitigating factor in the context of environmental liability insurance. To comprehensively examine the overall impact of environmental liability insurance on the green innovation endeavors of firms, we use a mediation effect model utilizing firm-level data from heavily polluting industries. This paper delves into the intricate relationship between environmental liability insurance and the capacity of heavily polluting firms to engage in green innovation, along with the mediating influence of financing constraints between these two factors. The findings of this analysis suggest that the acquisition of environmental liability insurance enhances the green innovation capabilities of firms operating in heavily polluting industries by alleviating financing constraints, serving as a mediating factor in this regard.

This paper investigates the impact of interest rate liberalization on corporate green investment by taking the cancellation of the lower limit of the loan interest rate of financial institutions by the People's Bank of China in July 2013 as an exogenous quasi-natural experiment. We find that the interest rate liberalization will boost corporate green investment. Specifically, for every one standard deviation increase in interest rate liberalization, the enterprise green investment intensity increases by 9.6% of the sample standard deviation on average. Moreover, underlying mechanisms show that interest rate liberalization reform can improve corporate green investment by easing financing constraints, improving market competition, and reducing business risks. In addition, the impacts are more profound on enterprises facing higher environmental supervision intensity, lower attention of capital market, higher degree of regional marketization, and lower degree of financialization. Extended analysis show that interest rate liberalization will further promote the substantive innovation of green technology and improve environmental performance after enhancing the green investment of enterprises. This study contributes to playing the role of financial services in the green transformation of the economy.

The “City in a Park” (CIP) is a new concept of urban transformation and development proposed in China in recent years, guiding the construction of healthy and sustainable living environments. This paper analyzes urban planning based on the CIP concept from a synergetic perspective, aiming to explore how the integrated planning of ecological spaces and built environments can promote systematic sustainable development in ecology, economy, and society. This research employs methods including document collection, unstructured interviews, field observations, and participatory observation, focusing on a case study of the Sichuan Tianfu New Area (STNA), a demonstration zone for the CIP. The study finds that the planning of the STNA extends the planning scope of urban ecological spaces beyond the traditional urban construction boundaries, not only preserving the natural resources but also enhancing the city’s overall sustainability through regional ecological services. By designing ecological spaces as green infrastructure that connects urban and rural areas, the primary sector is more readily integrated with the secondary and tertiary sectors, facilitating the integration of the urban and rural infrastructure and industries. The STNA integrates urban and rural administrative divisions, builds a cross-departmental collaborative management platform, and guides public participation in the planning process, ensuring the efficiency and effectiveness of planning implementation and enhancing the equitable sharing of social services. This research provides new insights into comprehensive, cross-disciplinary, and ecology-oriented urban planning. It offers evidence for an understanding of the application pathways and effects of the CIP concept in urban planning practice and provides valuable experience for other cities to promote harmonious coexistence between the city and nature.

This paper examines the industrial chain ripple effect of ESG in upstream and downstream companies from the perspective of the entire industrial chain, utilizing data from Chinese A-share listed companies. The study reveals that the ESG performance of upstream and downstream companies significantly enhances the ESG performance of midstream focal companies within the industrial chain. The ripple effects of industrial chain ESG are more pronounced when the focal firm demonstrates financial stability, maintains geographic proximity to the upstream and downstream chains, possesses a larger firm size, or operates under private ownership. Further, the paper finds that corporate ESG initiatives exert industrial chain ripple effects through two channels: optimizing the matching of supply and demand between upstream and downstream companies and focal firms; and stabilizing the supply-demand relationship through interactions between focal firms and upstream and downstream entities. This study aims to elucidate the phenomenon of focal firms adopting ESG practices, and how it is affected by upstream and downstream entities within the industrial chain. It offers a novel perspective for fortifying the resilience of industrial chains against market uncertainties and disruption risks, thereby advancing the sustainable development of these chains.

Green manufacturing and corporate ESG performance are two vital issues related to sustainable development. Utilizing manually collated data of green factory, publicly listed company data and corporate ESG scores disclosed by the Bloomberg database, this paper adopts a difference-in-difference approach to explore the impact of green manufacturing on corporate ESG performance. The empirical results demonstrate that green manufacturing significantly enhances corporate ESG performance by expanding green investment and alleviating financing constraints. Further analysis indicates that green manufacturing plays a more crucial role in improving corporate environmental performance and social responsibility. The findings offer valuable insights for refining government environmental regulatory tools and for corporations aiming to enhance their ESG performance.

The main application of the informative data in the sector which are related to the energy are defines and explains as one of the crucial elements of Energy Internet. The advancement of the grid system are very vital as well as promising and faces many issues that are connected with the implementation of the renewable energy including solar and wind energy. The capacity of collecting of the data is the main elements of make are easy in taking decisions. The advancement of the technologies and its improvement has many benefits and advantages which was shown by the data analytic of the renewable source of energy in the various power stations. This is the framework which shows the development and growth of the potential establishment of the analyzation of the data and information in the smart grid and the utilities of power by the renewable resources. The seven domains and approaches are used for the purposed of predicting the stability, flexibility and safety from the advancement of the grid system. The secondary qualitative methods are used to define and explain the importance of the grid system in relation with the renewable source of energy that is wing and solar energy.

This paper examines whether and how internal whistleblowing enhances innovation. We have discovered that the establishment of an internal whistleblowing system help to increase firms' innovation output, in terms of patent application and citation. Furthermore, our paper draws on the monitoring effect of whistleblowing on CEO, and the evidence shows that whistleblowing reduces executives' misconduct and therefore increases investment in R&D. Besides, we also find that such monitoring effect between employees also improves firms' innovation efficiency. Finally, we find that whistleblowing has a positive impact on firm's profits among more innovative firms. This paper aims to investigate how employee monitoring enhances firm innovation, making a contribution to the growing literature on innovation.

As the most fundamental unit of urban development, the performance of green space carbon sequestration in neighborhoods is, therefore, a crucial factor in the pursuit of carbon neutrality. Consequently, studying the performance of carbon sequestration from the spatial structure of green spaces in conjunction with the recreational features of the neighborhood is urgent and necessary. Herein, for the first time, we combined four types of indicators, namely carbon sequestration, green space spatial structure, natural environment, and human activities, using three types of 15-minute neighborhoods in the Nanjing metropolitan area as an example. As observed, the area indicator percentage of landscape (PLAND) contributed directly to the carbon sequestration of green areas and also influenced the carbon sequestration by affecting the average normalized vegetation index (NDVI) level; the shape indicator Simpson's evenness index (SIEI) not only helped to reduce the average temperature in the neighborhood but also improved the average NDVI level, both of which can contribute to carbon sequestration; the aggregation indicators aggregation index (AI) had no direct effect on the carbon sequestration performance but contributed to it by lowering the temperature. Thus, the current study revealed the mechanism by which the spatial characteristics of residential green spaces influenced carbon sequestration and proposed a new direction for future sustainable urban development.

To cope with increasing environmental pollution, the Chinese government has introduced a nationwide Environmental Protection Tax Law (EPTL) policy, which encourages enterprises to step up pollution control efforts and optimize their production decisions. However, the “green cost” generated by the EPTL policy has received less attention in existing research. Based on the manually collected data on China's listed companies during 2013–2020, this paper innovatively calculates the substitution elasticity of green capital to labor. By regarding the EPTL policy as a quasi-natural experiment, the difference-in-difference (DID) model and other causal identification methods are further adopted to examine the real effect and influencing mechanism of green tax reform on labor share. The results indicate that the EPTL policy significantly reduces the labor share through two influencing paths: promoting green capital and squeezing out low-skilled labor. This finding demonstrates that the EPTL policy leads to green capital gains and human capital losses, and it is mainly low-skilled labor in enterprises that “pay for” environmental policy shocks. By decomposing the labor share, we find that the EPTL policy leads to a decrease in employees' average wages and an increase in labor productivity, which indirectly proves the rationality of the two mechanisms. Further analysis reveals that in capital-intensive and growth enterprises, and in enterprises that did not receive green subsidies from the government, the decrease in labor share caused by the EPTL policy is more pronounced. Finally, this paper proposes targeted policy recommendations for governments seeking to balance national welfare and green development.

Based on the inter provincial panel data from 2014 to 2019, this paper empirically investigates the impact of technological innovation on the stability of economic growth. The conclusions are as follows: first, on the whole, technological innovation plays a positive role in promoting the stability o