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The research investigates how the resumption of the China certified emission reduction (CCER) market affects Chinese manufacturers' stock market valuations from an operations and supply chain management (OSCM) perspective. The paper draws from a resource-based view to examine the moderating effects of supply chain concentration (SCC), operational slack, and operational efficiency (OE) on the relationship between the CCER market and manufacturers' stock market valuations. This paper employs the event study method to examine market responses to CCER. The results reveal that the resumption of the CCER market significantly enhances the market valuations of high-pollution manufacturers to a greater extent than those of manufacturers with lower pollution levels. Additionally, the research findings indicate that SCC and operational slack attenuate the positive effect of CCER market resumption while OE amplifies it. This paper contributes to the OSCM literature by urging businesses to focus on the roles of SCC, operational slack, and OE in the CCER framework to harness the advantages of the CCER system better. • Resumption of China certified emission reduction positively affects manufacturers. • Operations and supply chain management factors are important moderators. • Manufacturers with varying pollution levels face different institutional impacts. • The event study method is employed to examine manufacturers' market responses. [ABSTRACT FROM AUTHOR]

Global environmental problems are worsening. Among various regulatory measures, market-oriented approaches are most favored by governments worldwide. Using provincial panel data from 2004 to 2020, a multi-period DID model was hereby constructed to empirically study the pollution reduction effects of the pilot policy for carbon emissions trading in China. Findings of this paper could be listed as follows: (1) The pilot policy has achieved notable reductions in waste gas and solid waste, although its effect on wastewater pollutants has been less pronounced; (2) Pollution reduction in the pilot regions can be achieved by optimizing the energy consumption structure; (3) Significant variations in pollution reduction effects are observed between the Northern and Southern pilot regions, with notably stronger policy effects in the north across various pollutants compared to the south. Overall, this paper offers pertinent policy recommendations to aid the Chinese government in enhancing its carbon market. [ABSTRACT FROM AUTHOR]

Green finance can effectively support industrial upgrading and technology development, such as artificial intelligence (AI). In this paper, we attempt to pursue the possibility of a win-win situation for achieving an eco- and tech-friendly society. By asking where and how we could develop green finance and AI innovation simultaneously, this paper conducts an empirical investigation on the influence of green finance on the development of AI in China from 2011 to 2020. Based on the panel data from the 30 provinces, we introduce spatial measurement, policy effect, heterogeneity, and threshold analyses to present deeper insights into the impact of green finance on AI innovations. Indeed, green finance could promote the progress of AI innovation. China's green finance pilot policy is verified to promote the progress of local AI innovations. Furthermore, the spatial spillover effect and regional heterogeneity are observed as well. The promotion effect is most significant in the western area, where the green finance index is relatively low. Besides, the threshold analysis also considers how to increase the marginal effect of green finance in different areas. Finally, several policy recommendations are proposed, which contribute to providing specific directions for the policymakers to improve AI innovation and achieve sustainable development at the same time. [ABSTRACT FROM AUTHOR]

As China's economy continues to grow rapidly, the importance of green and sustainable development is increasingly prominent. In this context, enterprises have undergone significant changes in all aspects of the value creation process. Based on the data of Chinese a-share listed companies from 2011 to 2021, this paper links the digital transformation of enterprises with the green technology innovation of enterprises. The focuses on the relationship between the enterprises' digital transformation and the enterprises' green innovation and its Local-neighborhood effect. Research shows that the digital transformation of enterprises will promote the enterprise green technology innovation, and this relationship will have a Local-neighborhood effect in different regions, and this spatial spillover effect is mainly achieved through the transfer of high-tech industries between regions. The results of heterogeneity test show that the effect of green technology innovation is the strongest in Beijing-Tianjin-Hebei economic circle, and the weakest in Pearl River Delta economic circle. Based on the spatial econometric model, this paper provides empirical evidence for the government and the state to formulate the regional development strategy of enterprises' digital transformation and green innovation. • Spatial panel Durbin model reveals digital transformation's impact on green technology innovation and regional spillover. • The effect of digital transformation of enterprises on their own green technology innovation has a "local-neighborhood" effect. • The spatial spillover effect is mainly realized through the transfer of high-tech industries between regions. • The strongest green technology innovation effect is found in the Beijing-Tianjin-Hebei economic circle. [ABSTRACT FROM AUTHOR]

The widespread use of digital technology has driven a huge change in the way payments are made. Based on the micro-data of the China Family Panel Studies (CFPS), this paper explores the relationship between mobile payment and carbon emissions from the consumption side. With the exogenous impact of Alipay's "Collecting Five Blessings" campaign, this paper finds that mobile payment significantly increases household consumption carbon emissions, but the marginal effect is gradually decreasing. Mechanism analysis shows that mobile payment mainly realizes the above impact through promoting the increase of consumption expenditure and upgrading of consumption structure. Further analysis indicates that carbon reduction policies introduced by the Chinese government in the personal consumption sector can mitigate the carbon emissions growth associated with mobile payments. Still, there is a need to strengthen policy measures further to effectively address the issue of rising carbon emissions from household consumption. [ABSTRACT FROM AUTHOR]

As the battery recycling market in China is still in an embroynic stage, the mechanisms, channels, pricing, and efficiency of battery recycling are shrouded in opacity. Battery recycling in China is currently dominated by electric vehicle manufacturer, supplemented by other market players such as battery producers and electric vehicle retailers. Due to the lack of information, battery recycling lacks cooperation and communication, and the whole market is dealing with "Information Island." Therefore, based on information sharing and channel competition, this paper designs a Stackelberg game model with an electric vehicle manufacturer, an electric vehicle retailer, and a third-party recycler as the primary participants. This study found that effective information sharing can reduce intensified market competition and promote the transformation of market players into "collaboration state". To promote partnership in the battery recycling market, this paper proposes a revenue-sharing contract incentive for the electric vehicle retailer to share demand information about battery recycling. It finds a revenue-sharing contract based on information sharing can help companies and competitors make appropriate behavioral choices in the battery recycling market. This study demonstrates that information sharing benefits the electric vehicle manufacturer and the third-party recycler while offering no advantages to the electric vehicle retailer. The decreasing accuracy of demand signals results in the diminishing value of information sharing for the electric vehicle manufacturer and the third-party recycler. The revenue-sharing contract can incentivize the electric vehicle retailer to share information. [Display omitted] • A battery recycling mode of electric vehicles is constructed. • Effective information sharing would encourage market players to be more collaborative. • A revenue-sharing contract is designed to incentivize the electric vehicle retailer to share information. • Inaccurate information and channel competition reduce the attractiveness of information sharing. • Inter-firm information sharing is beneficial for building an efficient battery recycling system. [ABSTRACT FROM AUTHOR]

This paper studies examines how a firm's position in the global value chain affects its pollutant emissions. This paper integrates China's firm-level trade data into China's multi-regional input-output tables to provide an index to measure a firm's position in global value chains. Based on a firm-level pollution dataset (2000–2014) in China, this paper conducts an empirical analysis and find that the most-downstream firms on the global value chain have lower pollutant emission intensity. Our results also suggest that the production factor structure effect, the knowledge absorption effect and the abatement investment effect together contribute to the emission intensity gap between the most-upstream firms and the most-downstream firms. These novel results are significant in guiding firms towards reducing their emissions and promoting a green global value chain, with the ultimate goal of achieving multinational environmental protection. [Display omitted] • The most-downstream firms have lower pollutant emission intensity. • A supply chain disruption shock is used as an instrumental variable. • Factor structure, knowledge absorption and abatement investment are channels. • Effects on firms with diverse ownership and trade patterns are heterogeneous. [ABSTRACT FROM AUTHOR]

With the growing global energy demand and limited production of conventional crude oil, the extraction of unconventional heavy and extra-heavy oil is receiving unprecedented attention. China is the fourth largest producer of heavy oil. High viscosity and complex formation environments increase the difficulty of exploiting heavy oil. To alleviate the economic cost and environmental pollution pressure brought by heavy oil production, China has achieved significant advancement in the innovation of heavy oil recovery, including accelerating the transformation of thermal technology to non-thermal technology and the use of new energy technology to achieve the goal of low-carbon economy and green environmental protection. Based on the background of heavy oil in China, this paper recharacterizes the high-viscosity mechanism of heavy oil. From different aspects, including basic principles, main characteristics, applicability, limitations, and challenges, this paper comprehensively reviews existing heavy oil recovery technologies, including thermal recovery, in-situ upgrading, cold recovery, and new energy technologies. Currently, in China, the main target of heavy oil recovery is achieving the "carbon peaking and carbon neutrality" goals, which can be described as low energy consumption, low emission, and low pollution. To facilitate the low-carbon transition in the extraction of heavy/extra-heavy oil and attain environmental sustainability goals, it is essential to increase the proportion of non-thermal factors in thermal recovery technologies, develop efficient in-situ catalysts, adopt clean cold extraction techniques, and advance the development of new energy technologies. [ABSTRACT FROM AUTHOR]

Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

In the domain of global socio-economic dynamics, the pivotal role of food production (FP) cannot be overstated. It constitutes the bedrock of fundamental human necessities while being inexorably linked with critical aspects such as economic expansion, societal equilibrium, and geopolitical interplays. The multifaceted nature of FP appears through its direct impact on macroeconomic indicators and its latent influence on international relations and policy-making. This critical nexus underscores the imperative for a comprehensive understanding and strategic management of food production processes to sustain and enhance global socio-economic stability and growth. Investigating the nexus between green finance (GF) and FP is pivotal for ensuring national security and promoting sustainable economic development. This research thus paper examines GF's impact on FP in China as outlined in the 2017 green finance policies. It employs the difference-in-differences (DID) method and analyzes a balanced panel dataset comprising 282 cities in China from 2009 to 2020. The results show that GF has an inhibitory effect on FP, and this remains valid after a range of reliability checks, including parallel trend assessments and placebo tests. Further findings of transmission mechanism analysis indicate that non-agricultural factors and financial exclusion are critical for GF's inhibitory effect on FP. Heterogeneity analyses show that GF's inhibitory effect on FP is more pronounced in the main food-producing areas, the main food-marketing areas, and cities with better infrastructure. The empirical results of this paper comprehensively illustrate GF's impact on FP and how it contributes to the achievement of food security objectives. [ABSTRACT FROM AUTHOR]

This paper addresses the significant challenges faced by distribution system operators (DSOs) in competitive electricity markets due to uncertainties arising from electricity markets, electric vehicles (EVs), and conventional loads. To tackle these challenges, this paper proposes a pseudo-local reserve market between the DSO and EVs, which enables the DSO to integrate EV flexibility into the overall market framework while compensating for deviations in the conventional load across the wholesale electricity market. Furthermore, a two-stage framework is developed to facilitate the participation of EVs in electricity markets. In the first stage, the reserve capacity of EVs is integrated into the decision-making process for day-ahead bidding, taking into account uncertainties of the load and electricity. In the second stage, the day-ahead results are coordinated to enable the efficient dispatch of EVs for real-time market participation. To assess the efficacy of the proposed framework, a case study is conducted within a 31-node distribution system situated on a university campus located in Guangdong, China. This paper investigates the economic impact of load deviation constraints on EV reserves, revealing a penalty reduction of 3100 CNY for a daily reservation of 1000 EVs and a net profit increase of 1300 CNY for DSOs utilizing reserves. It further introduces a method for quantifying reserve capacity, enhancing DSO decision-making accuracy. • A pseudo-local reserve market is established considering EV's reserve potential. • Optimal bidding strategy for DSO in China's electricity markets is constructed. • A framework for EV coordinated V2G operation is developed. • The proposed method can limit load deviation cost for more profits. [ABSTRACT FROM AUTHOR]

Resilience is an important aim of climate adaptation in urban development planning. Since 2015, sponge city (SC) pilot construction in China has highlighted the importance of urban water systems, but has paid insufficient attention to extreme and long-term climate change risks. This paper aims to provide a new method for evaluating the urban water system climate resilience (UWSCR), classify China cities in combination with climate hazards, conduct case studies on SC pilots, and propose ways to improve the UWSCR in SCs. Firstly, Taking heavy rain and drought as hazards, an evaluation index system of UWSCR is established, including engineering resilience (ENR), ecological resilience (ECR) and evolutionary resilience (EVR). A combination model based on the analytic hierarchy process and entropy weight method is used to measure the UWSCR of 27 SC pilot cities and 253 non-pilot cities at or above the prefecture level in China. Secondly, coordinating hazard index and UWSCR index, cities are divided into four types. The results show that the ENR and EVR of SC pilots exhibited an increasing trend from 2010 to 2020 and were greater than those of non-pilots. Among the four types, Resilient Cities and Low Risk Cities with high climate resilience (CR) were mainly distributed in the eastern and central regions of China. High Risk Cities and Vulnerable Cities with low CR were mostly distributed in the central and western regions. Among the cities of high CR, SC pilots accounted for 63.0% of the pilot samples, while non-pilots only accounted for 26.5% of the non-pilot samples. Finally, this paper analyzes the typical cases of SC pilots, and puts forward some suggestions, such as considering the UWSCR systematically and holistically, improving the ECR of UWSCR, making medium-term to long-term adaptation planning and providing differentiated policy support. The originality of this work is to identify four types of cities from the perspective of UWSCR and provide reference for improving the CR of SCs. [Display omitted] • Against climate change, security risks of urban water systems have intensified. • Sponge city pilot projects in China highlighted the importance of urban water system. • The climate resilience of urban water system in China was evaluated and classified. • The proportion of high-resilience cities in the sponge city pilot sample is high. • The evaluation of urban water system climate resilience can guide sponge city constructions. [ABSTRACT FROM AUTHOR]

The relationship between government and enterprise has attracted extensive attention. Under the increasingly severe requirement of sustainable development, there is still a lack of research on the economic effect of political acuity from the perspective of enterprise's positive party value creation. We built a dictionary of political acuity and demonstrated reliability through machine learning algorithms such as K-Nearest Neighbor (KNN). Then, based on the annual reports of China's listed companies from 2013 to 2020, the relationship between political acuity, ESG atmosphere, and corporate performance is empirically discussed. Examination through the formal institutional perspective of informal institutionalization shows that the positive acuity of the Communist Party of China(CPC) and the democratic parties(DPC) will improve corporate performance, while the negative acuity will have an early warning effect on performance. Furthermore, the stronger ESG atmosphere synergized this relationship. The CPC's negative acuity has supervision effect on non-state-owned companies, and this supervisory effect still exists in the ESG atmosphere. However, whether the moderating effect is considered or not, the positive political acuity of state-owned enterprises doesn't significantly improve performance. We found that the CPC's embedding in corporate governance will lead to both economic and political benefits, and have thresholds. We constructed a political acuity dictionary and introduced text analysis and nonparametric estimation method in this paper, which provided a basis and reference for future research on political acuity at the enterprise level. Our findings also enrich the institutional theory and the embeddedness theory. Meanwhile, our research broadened the boundary of political parties, ESG, and enterprises, the integration of ideological values and formal institutions, and had practical implications for the green transformation of firms and the precise positioning of political party functions. • We build a dictionary of political acuity for the first time. This dictionary provides a new measurement perspective for the study of corporate political sentiment and sustainable development. • From the perspective of positive value creation, we examine the impact path of a company's party acuity, ESG atmosphere, and financial performance. This paper helps to expand the governance boundaries of ideology and formal institutions, political concepts, and corporate behavior. • We explored the accounting consequences of political acuity for different types of firms, and measured the economic and political effects thresholds. • We introduced machine learning, python crawler, text analysis, and nonparametric estimation methods into this paper, which helped to expand the technical approach to corporate governance and green transformation. [ABSTRACT FROM AUTHOR]

Environmental protection and sustainable development are now profoundly ingrained in the public consciousness in the modern era of the global green revolution. First, this paper uses an evolutionary game model to theoretically analyse the impact of environmental regulation and green finance on enterprises by dissecting the game behaviour between local governments, banks and enterprises. Then, we incorporate entrepreneurial spirit into the model to determine whether entrepreneurial spirit accelerates the achievement of green sustainability objectives. Environmental regulation and green finance are found to contribute substantially to the innovation of green technologies by local enterprises, while entrepreneurial spirit accelerates this process. Finally, we empirically test the findings based on a prefecture-level panel dataset from 2007 to 2020. We find that green finance has a positive impact in Central and Western cities of China, while Eastern cities are in greater need for government environmental regulation controls. For entrepreneurial spirit, the incentive effect of entrepreneurial spirit on the level of green technology innovation is more significant in Central and Western regions of China. This paper enriches the field of research on entrepreneurial spirit and regional green sustainable development by providing empirical evidence for the evaluation of environmental regulatory and green financing policy impacts. [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

With the increasing severity of global warming, the goal of carbon sequestration and emission reduction in various industries has become an important responsibility for sustainable development. As an important part of carbon sink, the improvement of net carbon efficiency in the plantations industry will make a great contribution to the realization of the "double carbon" target in agriculture. However, there are large spatial and temporal differences in the net carbon efficiency of the plantations sector in various provinces, and there is still a large scope for increasing carbon sink and reducing carbon emission. In this paper, we have analyzed spatial and temporal trends in the net carbon sink efficiency of the plantations' production processes in 31 provinces in China (excluding Hong Kong, Macao and Taiwan) from 2000 to 2020. On this basis, we have analyzed the influencing factors of net carbon efficiency in the plantations' production process through an extended Kaya constant equation. Through the geographically and temporally weighted regression model, we explore the spatio-temporal heterogeneity of the influencing factors, and further analyze the driving and restraining factors of net carbon efficiency in plantations' production process, in order to propose appropriate countermeasures. The study shows that: (1) The net carbon efficiency of plantations sector in China increase between 2000 and 2020, and the development of net carbon efficiency is uneven across regions. (2) The geographic center of net carbon efficiency of China's plantations industry shift from the northeast to the southwest and is consistent with the migration direction of agricultural inputs. (3) The influencing factors of net carbon efficiency in the plantations sector show large regional differences, and can be specifically divided into four major types of zones. In this regard, this paper provides more appropriate countermeasure suggestions for increasing carbon sink and reducing carbon emission in each zone, with a view to achieving the goal of double carbon in agriculture with practical significance. • Net carbon efficiency is a new objective indicator to measure the carbon sink level of cropland. • Cultivated land carbon sink capacity is closely related to agricultural inputs. • Regional differences in the factors influencing net carbon efficiency. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the water-energy-food nexus (WEFN) system, focusing on its interlinked structure and dynamic characteristics. This paper proposes a dynamic series-loop data envelopment analysis (DEA) model with a directional distance function for measuring WEFN efficiency in China. A spatial Durbin model is constructed to investigate the impact of extreme temperatures on WEFN efficiency. The results are as follows. (1) Compared with the black-box DEA model and series network DEA model, a series-loop network DEA model can reflect the "networking effect" and "looping effect" in the WEFN system. (2) The WEFN system performs well with an average series-loop efficiency of 0.875, but the efficiency of the water subsystem scores low and needs improvement. (3) At the national level, extremely high and low temperatures have no significant effect on the WEFN efficiency in local or adjacent provinces, whereas average temperature promotes the WEFN efficiency in local provinces but hinders it in neighboring provinces. In the regions with a low temperature difference, average temperature has no impact on the WEFN efficiency of both the province itself and its neighboring provinces. Overall, this study provides valuable insights into the complex interlinkages within the WEFN system and highlights the importance of considering these relationships when improving the system efficiency. [ABSTRACT FROM AUTHOR]

With the fragmentation of global production, the share of intermediate trade in international trade has increased significantly. Nevertheless, more research must be done on how intermediate trade factors influence energy consumption. This paper utilized the multi-regional input-output (MRIO) model to categorize China's energy utilization into six parts based on its position within the global production chain. Additionally, it examined the impact of intermediate factors on China's energy consumption through index decomposition analysis (IDA). The results revealed that: (1) from 2000 to 2014, intermediate factors led to an increase of 1380.96Mtces in China's energy consumption, accounting for around 37% of the national total; (2) the reduction in efficiency is the primary cause of the surge in domestic intermediate energy consumption, while the increase in market proportion is the dominant driver promoting international intermediate energy consumption growth; (3) the international intermediate proportion contributed the most among all intermediate factors. Drawing upon the findings above, this paper proposed policy recommendations to regulate China's rising energy consumption, precisely the escalation of intermediate process energy usage, focusing on the global production chain. [Display omitted] • Energy consumption is divided into six parts based on the intermediate destination. • Fifteen factors is decomposed based on index decomposition analysis. • The contributions of the structure, proportion, and efficiency changes is considered. • This paper shows a way of identifying the composition of energy consumption. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality, China must grasp the intricate factors driving coal market, as it addresses coal consumption and reduces the carbon footprint. While previous studies have identified certain factors, they have largely overlooked the impact of the overall industry sector on the coal market. In this paper, a hybrid causal machine learning model was proposed that combine with least absolute shrinkage and selection operator (LASSO), multiple linear regression (MLR), peter and clark momentary conditional independence (PCMCI) and interpretable machine learning. The approach employed a complex network perspective to identify 10 key factors in China's coal market from three dimensions: industrial sector, foreign trade and energy market. The hierarchical pattern of these factors is classified into two levels: direct factors, primarily encompassing crude oil futures, exchange rates and architectural decoration, and intermediary factors, mainly including the chemical industry and building material. Interestingly, this paper reaffirms the roles of crude oil futures and exchange rates in the coal market, as identified in prior studies. Additionally, it uncovers new influential factors primarily driven by the chemical industry and architectural decoration, previously unexplored. Furthermore, this paper found a significant contemporaneous relationship between crude oil futures and coal price index (0.151) as well as coal consumption (0.102), and the strong relationship between coal consumption and the Indonesian Rupiah to Chinese Yuan exchange rate (0.063) was also confirmed. Among the emerging dominant factors, the coal price index and the chemical industry (0.145), along with coal consumption and building materials (0.250), also exhibit a strong contemporaneous relationship. These findings highlight the importance of considering the entire industry sector while analyzing the coal market and promoting a cleaner transformation of the industry in China, and the paradigm presented not only applicable to the coal market, but can be extended to other industries. [Display omitted] • Better grasping key factors in China's coal market critical to carbon neutrality. • A comprehensive study encompassing industrial sector, foreign trade and energy market. • A novel hybrid machine learning models and industry-wide features are introduced. • Identification and categorization of direct and intermediary factors. • Findings offer a new paradigm for decision-making, driving cleaner production reforms. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of China's environmental regulations, with a focus on the green credit policy, on green innovation in pursuit of the "carbon peak and carbon neutrality" goal. Given the implementation of the 2012 Green Credit Guidelines, this paper employs the Difference-in-Difference Method (DID) and conducts a quasi-natural experiment to empirically examine the interactions among the central government, local governments, and high-pollution and high-emission enterprises by exploring the impact of green credit policies on green innovation of these enterprises. Relying on 4503 samples of 237 high-pollution and high-emission enterprises listed in the main board in China from 2003 to 2021, this study reveals that the green credit policy can improve green innovation of these enterprises. Specifically, this study explores the detailed mechanism through which the green credit policy enables these enterprises to increase their market concentration and then the monopoly profits, which in turn promotes their green innovative productivity. In addition, this paper also reveals how local governments' political and financial incentives may serve as positive and negative moderating factors, respectively, within the impact mechanism. This study has valuable implications for how to effectively formulate and implement environmental regulations by balancing the interests of the central government, local governments and enterprises. [ABSTRACT FROM AUTHOR]

It is a controversial question of whether environmental regulation can achieve the double dividend of improving environmental quality and increasing employment and income. This paper takes Chinese migrant population as the main research object and uses the Chinese Household Income Projects data (CHIPS) and the emission data of major pollutants at the prefecture-level city jointly. Based on the classic Mincer wage equation, we investigate the impact and mechanisms of environmental regulation on the income of Chinese migrant population. The results show that: (1) The intensity of environmental regulation significantly improves the income level of the migrant population, and for every 1% increase in the intensity of environmental regulation, the wage income of the mobile population will rise by 4.96%. (2) The documented positive effect of environmental regulation is more significant in non-public firms, the eastern regions and high-skilled workers. Conversely, for the female and elderly group, 1% increase in environmental regulations will restrain their income growth by 4.95% and 0.37%, respectively. (3) The influencing mechanisms include both the direct effect of labor demand and the indirect effects of firm performance and technological innovation. (4) we find that 1% increase in environmental regulations respectively raise the income of the low- and moderate-income migrant population by 10.834% and 3.579%, while having no significant impact on the high-income group, thus reducing the income gap of the migrant population. The findings of this paper provide theoretical support and practical evidence for achieving a coordinated development of ecological environmental protection and income improvement for socially disadvantaged groups in China. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

Digital transformation has the potential to significantly impact household energy consumption (HEC) by promoting the adoption of energy-efficient technologies. This paper utilizes the time-varying Difference-in-Differences (DID) model to evaluate the causal effect of digital transformation on HEC within China's households. We find that HEC is positively impacted by digital transformation, as embodied by the "Broadband China" strategy; and the results remain reliable when many robustness tests are taken into account. Specifically, digital transformation has the potential to indirectly increase HEC by consumption upgrade and internet development mechanisms. The heterogeneity analysis reveals that the impact of digital transformation on HEC varies significantly across different household and regional. High-income, low skilled, rural areas, as well as households in areas with higher levels of development and marketization, are more likely to be affected by the digital revolution in production and consumption, which will inevitably lead to an increase in HEC. These insights are crucial for developing effective strategies to reduce HEC and promote sustainable development. [Display omitted] • Assesses digital transformation's impact on China's household energy use. • Identifies significant increase in energy consumption due to digitalization. • Examines mechanisms of how digital transformation affects energy use. • Provides insights for harmonizing digital and green transformations. [ABSTRACT FROM AUTHOR]

The current research investigating the effectiveness of policy-driven transformation in resource-based cities has focused mainly on city-level impacts and has overlooked firm-level evidence. This paper filled this gap by focusing on its impact on firm-level carbon emissions. Drawing on the quasi-natural experiment of China's reform of resource-based city transformation, we utilize a difference-in-differences (DID) model based on nationwide firm-level tax survey data from 2009 to 2016. The findings indicate a noteworthy reduction in firms' carbon emissions due to the reform, particularly in growing-type resource-based cities and within the manufacturing industry. The empirical results provide evidence that the implementation of the "Plan" has effectively enhanced the level of urban resilience. Moreover, the findings demonstrate stronger effects on large firms, publicly owned firms, and firms in municipal districts. • Resource-based city transformation is effective at mitigating firm carbon emissions and enhancing urban resilience. • Different development stages exhibit heterogeneity in the effectiveness of firm emissions reductions. • Sector- and firm-specific characteristics play a significant role in reduction in firms' carbon emissions. [ABSTRACT FROM AUTHOR]

Accurate prediction of the Particulate Matter 2.5 (PM 2.5) plays a crucial role in the accurate management of air pollution and prevention of respiratory diseases. However, PM 2.5 as a time series is extremely difficult to accurately predict. In this paper, a Hybrid Integration (HIG) algorithm that combines data pre-processing, time-series decomposition, signal decomposition, a prediction module, a matching strategy, and a hybrid integrated optimization algorithm is proposed. First, the optimal parameters for the four individual models were selected by integrating multiple evaluation perspectives. Additivity was then determined by Seasonal and Trend decomposition using LOWESS (STL), followed by refinement decomposition using signal decomposition. The four new sequences were reconstructed using Range Entropy (RangeEn) and mapped to the models. Additionally, Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) methods were optimized using the HIG algorithm. The results show that the HIG-RNN and HIG-LSTM are more advantageous than the ordinary method in terms of reasonable weight assignment. Finally, an innovative confusion test method was developed to test the stability of the prediction direction. To ensure generalizability, validation was performed using PM 2.5 data from two regions of China. The results show that the method significantly improves the prediction performance and provides a powerful tool for policy formulation and management. [Display omitted] • A hybrid integration (HIG) algorithm is proposed. • Prediction results were evaluated using the original COI and improved ICOI. • Creative time-frequency analysis bypasses traditional time series constraints. • RangeEn can assess entropy series for regularity to avoid excessive decomposition. • A pioneer confusion test for model direction consistency check was developed. [ABSTRACT FROM AUTHOR]

The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO 2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO 2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO 2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO 2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO 2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO 2 systems as promising alternatives to air conditioning systems in railway transportation. • This paper evaluates the potential of theCO 2 system in high-speed trains from an energy performance and environmental benefits perspective. • A high-fidelity model of the transcritical CO 2 system is developed and validated for effectiveness through experiments. • The energy and environmental evaluations are conducted based on China's four-vertical-and- four-horizontal railway lines. • The results indicate that the CO 2 system presents a competitive alternative for air conditioning systems in high-speed trains. [ABSTRACT FROM AUTHOR]

The lengthening of the global value chain (GVC) and the deepening of the transnational labor division system have led to frequent cross-border flows of metal values worldwide, and the pattern of the international metal trade is facing reconstruction. This paper combines a new trade accounting framework and a complex network model to construct global metal domestic value added (DVA) and foreign value added (FVA) flow networks based on global multi-regional input‒output (MRIO) tables for 2000 and 2007–2022 and then analyzes their structural topological features and spatio-temporal evolution trends at the macro, medium, and micro levels. Then, the main driving factors are investigated using the exponential random graph model (ERGM). The results show that the DVA and FVA networks are expanding and have obvious aggregation effects and small-world characteristics, that the community divisions show a trend toward regional integration and worldwide multipolarity, and that Germany is the most important transportation hub and trade medium in the FVA network, while China and the United States are, respectively, the largest creator and consumer of the world's metal value flow. In addition, the DVA network is more susceptible to node attribute effects such as GDP, trade openness, population size and foreign direct investment, while the FVA network is more susceptible to exogenous network effects such as geographic distance and colonial ties. [ABSTRACT FROM AUTHOR]

While exploiting natural resources, human beings have also left irreversible damage to the environment. The salt caverns left behind by the mining of salt are one of them. With the proposal of the "dual carbon" background, clean power and energy storage power stations have also become one of the focuses of sustainable development. The abandoned salt cavern is combined with the energy storage power station, and the excess electric energy is used to compress the air during the low power consumption period through the non-supplementary combustion mode, and the air kinetic energy is converted into electric energy during the peak power consumption period to realize the zero-carbon salt cavern energy storage conversion. This method can not only achieve zero carbon utilization of the abandoned environment, but also achieve energy storage and conversion, which is a very meaningful research. Based on spherical fuzzy sets, cumulative prospect theory and VIKOR, this paper constructs a novel combined research framework to analyze the risk of zero-carbon salt cavern compressed air energy storage (SAES) power station, and takes China 's first zero-carbon SAES power station project as an example. The results show that the overall risk of the zero-carbon SAES power station is 0.3467, which is a low risk. The key risks are non-supplementary combustion thermal energy storage technology risk, salt cavern creep and leakage risk, and the risk tolerance limit is +31.54 %. [ABSTRACT FROM AUTHOR]

The development prospect and sustainability of new energy vehicles (NEVs) are facing numerous challenges under the coupling influence of various factors, which has become a major strategic issue in the automotive industry research within China. Establishing a prediction method to forecast the development trends of NEVs under the complex conditions is of great significance. This paper comprehensively addresses the relevant factors influencing the sales of NEVs over temporal depth and spatial breadth, including random white noise and lag effect resulting from lag operators of influencing factors. A multivariate forecasting approach utilizing the ARIMA model and its optimized model, alongside the GBDT model were adopted to forecast NEV sales in China. The findings demonstrate that: 1) NEVs have exhibited a trend of rapid growth, but are still susceptible to random interference and lag effects caused by influencing factors. Key technology breakthroughs, accessibility of charging infrastructure, and national policy support remain as primary drivers of NEVs development; 2) The ARIM–IO– LSTM model achieved high prediction accuracy with a goodness-of-fit R 2 exceeding 90%, outperforming the ARIMA and ARIMA-IO models by 23.586% and 20.790%, respectively, while the ARIMA-IO model improved accuracy by 5.126% compared to ARIMA. The method of model combination and outlier incorporation have proved to be practical solutions for strengthening model accuracy. 3) In the next 3–5 years, the NEV industry will enter a stage characterized by steady progress with an upward trend. Adapting the intensity, scope, and direction of policy support, coupled with achieving technological breakthroughs and enhancing infrastructure construction, are essential for sustaining industrial development and attaining desired objectives. [ABSTRACT FROM AUTHOR]

The time-varying dynamics of the transition to renewable energy reflect the effectiveness and efficiency of energy policy. This paper investigates renewable energy transition behavior in China using Markov regime-switching models. Two distinct phases, expansion and contraction, are identified based on the growth rates of renewable energy consumption share. We find that since China started its new-energy national strategy in 2005, there has been an extended period in which it has been in the expansion state, although it occasionally reverts to a contraction state. Intriguingly, we uncover that the timing of transition state changes can be explained by the changes in policy-related, market-based instruments and risk-related indexes. These findings present implications for policymakers in developing more precise and effective policies, that drives investment choices to align with the goal of a sustainable energy system. [Display omitted] [ABSTRACT FROM AUTHOR]

Using fracturing fluids to modify coal seams to boost their permeability is an essential way to address the technical challenges of the resourceful and efficient extraction of coalbed methane from coal reservoirs in China. However, some current fracturing fluids are toxic or corrosive and pollute groundwater resources, which becomes one of the obstacles to the development of fracturing and penetration technology. Five new types of composite clean fracturing fluids were developed in this paper with Yunnan anthracite coal in China as the research object. The changing rules of functional groups and pore structures, which have a vital influence on gas adsorption and permeability of the treated coal samples, were systematically explored through infrared spectroscopy and low-temperature nitrogen adsorption experiments, and the highly efficient, environmentally friendly, and safe fracturing fluids that are suitable for the experimental coal seams were preferred. The new fracturing fluid effectively reduces the structure of aliphatic hydrocarbon and the structure of oxygen-containing functional groups, improves aromaticity, and lowers the adsorption capacity of coal for methane. Meanwhile, it simplifies the pore structure of coal and improves the average pore diameter. The research results are essential to the clean production and efficient exploitation of coalbed methane resources and safe coal production. • Five new clean fracturing fluids was prepared. • Analyze the effect of different clean fracturing fluids on coal microstructure. • Explored the mechanism of action of clean fracking fluids on coal. • Determined the optimal ratio of clean fracturing fluid. [ABSTRACT FROM AUTHOR]

As the global food supply chain becomes increasingly unstable, food security is gaining importance in China. Nevertheless, factors such as water scarcity, limited land resources, and global climate change pose great challenges to increasing food production. Therefore, it is crucial to explore sustainable development models for food systems. In this paper, a multi-objective crop layout model considering crop rotation is constructed and solved using the INSGA2-DS algorithm. Various precipitation scenarios were established for climate change. Data analysis and optimization were conducted under different precipitation scenarios. Applied in the plain area of southwestern Shandong Province, the model can increase soybean yield by 6.78%, net carbon sequestration intensity by 0.04%, net benefit by 2.09%, and crop water productivity by 3.91% during a median flow year. Optimization tends to increase the total area planted with food crops during wet years and decrease it during dry years. The optimization model can enhance water productivity and carbon sequestration intensity of crops, as well as prevent unreasonable fluctuations in the area planted with food crops. This enables the benefits of water conservation and yield increase to be fully utilized, and reduces yield and economic losses due to dry years. The models help to rationally allocate soil and water resources, effectively respond to climate change risks, and provide robust decision support for regional food crop planning. [ABSTRACT FROM AUTHOR]

Establishing an intuitive link between driving factors of household energy consumption activities and inequalities is important for the understanding of household heterogeneity in energy consumption behaviours. This paper proposes a novel typology framework based on machine learning approaches and data from 3637 Chinese households in 2014 from 85 cities. Activity-based energy consumption was measured, highlighting inequalities across activities, regions and household types. The results showed significant energy consumption disparities between urban/rural and north/south households, especially in cooking, space heating and vehicle activities. By identifying driving factors of energy consumption, a new household typology classified samples into 6 (all), 6 (urban) and 7 (rural) types. Within these types, households with similar demographic structures, lifestyles and energy consumption habits were clustered. Demographic structure, region, and primary energy demand were used as the basis for the typology. The findings demonstrated how household lifestyle differences explained the cause and underlying driving factors of urban-rural energy consumption inequalities and provided suggestions for city-by-city and type-by-type measurements to support effective low-carbon transformation in cities. • Activity-based household energy consumption (HEC) is measured and calibrated. • Household energy consumption inequalities exist in urban/rural and the north/south groups. • A four-step machine-learning approach well classifies households into reasonable clusters. • Activity-based variables are driving factors for HECs in a LASSO model. • Inequality is narrowed in household clusters and type-by-type policies are needed. [ABSTRACT FROM AUTHOR]

Terrace abandonment in hilly and mountainous regions, particularly in China, has become a significant concern. However, comprehensive assessments of abandonment patterns and underlying causes are still lacking. This paper elucidates the patterns, determinants, and impacts of terraces abandonment in China by using data from a survey of 580 villages across 346 counties and employing spatial analysis and the Heckman two-stage model. Terrace abandonment, which began in the 1990s, has progressively intensified, peaking in 2015. Currently, 51.55% of surveyed villages experience terrace abandonment, affecting 21.17% of households and 8.37% of the total terrace area, with a distinct prevalence in the South and scarcity in the North. Key factors contributing to terrace abandonment include low returns compared to other options, wildlife damage, high engagement in non-farm labor, and substantial non-farm income. In 2021, terrace abandonment led to the loss of 9.36 million tons of grain production capacity, enough to fulfill the yearly consumption requirements of 23.4 million people. Moreover, terrace abandonment undermines the cultural importance of terraced agriculture, reduces tourism potential, and hinders rural rejuvenation. The challenge of terrace abandonment is anticipated to worsen with the increase in non-farm economic activities and ecological restoration projects in hilly and mountainous regions. It is crucial for the government to implement measures to enhance terrace management. These measures include reducing operational costs for large contiguous plots, promoting the cultivation of cash crops to increase revenues from extensive scattered plots, and advocating for the reforestation of agricultural land to enhance the ecological value of remote terraces at higher altitudes. Addressing these issues can achieve sustainable terrace use and management, contributing to broader rural development and ecological goals. [Display omitted] • Terrace abandonment has been observed across approximately 60 countries. • 21.17% of households and 8.37% of terrace areas have experienced abandonment. • Terrace abandonment has led to a decrease in China's grain production capacity by 9.36 million tons. • Terrace abandonment may intensify because of the expanding non-farm economy and ecological restoration. [ABSTRACT FROM AUTHOR]

As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

Energy and water are interdependent. Water is essential for energy production, and energy is indispensable for water processes. This paper develops a Stackelberg game based bi-level multi-objective model for optimal water allocation under uncertainties from an energy-water nexus perspective, which considers energy-related water consumption and water-related energy production. It handles the hierarchical decision-making problem between the river basin authority and the subareas, as well as the tradeoffs between social equality and ecological damage. The upper level of the model makes schemes on water allocation for multiple subareas, and the lower level decides on water allocation for different types of power generation. To generate reasonable and practical strategies for water allocation, ɛ -constraint method and KKT conditions are used. A case study of Minjiang River, China is given to demonstrate the applicability and practicality. Scenarios analysis is also conducted to demonstrate the effectiveness of the model and the effects of the control parameter changes. The results indicate that the river basin authority would allocate larger water resources to the subareas with higher energy demand. It is concluded that the proposed allocation method is advantageous to the subareas with higher water utilization efficiency. The proposed bi-level model demonstrates its reasonableness and superiority to the single-level model. Policy implications are finally provided to support the sustainable development of energy-water nexus. • A bi-level model for water allocation in energy-water nexus system is proposed. • The hierarchical decision sequence between the river basin and subareas is solved. • The tradeoffs between social equality and ecological damage are made. • Optimal water allocation for multiple subareas and energy resources are quantified. • Uncertainties in decision-making environment are handled by fuzzy set theory. [ABSTRACT FROM AUTHOR]

The battery electric vehicle (BEV) industry, commanding over half of the global market share in China, has garnered significant attention in response to escalating concerns about climate change. NCM (LiNi x Co y Mn z O 2) batteries, prized for their high energy density, are pivotal in this industry. However, their production relies on critical metals, posing environmental challenges. Recycling processes aim to address this issue by recovering critical metals from end-of-life batteries. The industry is updating from NCM 111 to NCM 811 batteries to enhance energy density and reduce costs, but the key factors influencing the material flows and environmental impacts remain uncertain. This paper aims to identify the key factors contributing to the potential differences in material flows and environmental impacts introduced by the NCM battery upgrading in China. Following the new energy vehicle sales projections in China until 2035, a dynamic material flow analysis was employed to calculate material demands, recovered amounts, and substitution rates for various upgrading scenarios. The study reveals that the majority of retired batteries until 2035 were sold between 2022 and 2029. Material substitution rates prove to be more sensitive to the upgrading scenario than the lifetime and growth rate of BEVs. Faster NCM 811 penetration results in over 2.5 times more saved cobalt demand compared to additional nickel demand. A life cycle assessment of NCM batteries reveals a 39% lower global warming impact for NCM 811 compared to NCM 111, highlighting environmental benefits from increased energy density and reduced cobalt consumption. The energy density improvement contributed 85%, while the alteration in material composition contributed 15% to the global warming reduction in NCM 811. Recycling emerges as a crucial strategy in mitigating environmental impacts across all categories, particularly addressing eutrophication, previously deemed challenging due to the difficulty in recovering Li 2 CO 3. [ABSTRACT FROM AUTHOR]

Addressing the urgent need for accurate carbon emissions forecasting to support global emissions reduction goals, this paper introduces a novel approach for carbon emissions prediction that dynamically considers the spatial–temporal correlation of carbon emissions across forecasting targets. Traditional statistical and machine learning models have limitations, such as oversimplification and inefficiency in capturing evolving dynamics among multiple forecasting targets, alongside a focus on longer forecasting horizons like monthly or yearly. To tackle these, we propose an innovative Dynamic Spatial–Temporal Graph Convolutional Recurrent Network (DSTGCRN), a blend of graph convolutional and recurrent neural network structures customized for up-to-date multi-regional spatial–temporal predictions at a daily level. Comprehensive empirical analyses on datasets from China, the US, and the EU confirm DSTGCRN's superior performance and robustness across diverse geographical contexts. It outperforms the second-best among 10 baseline models, achieving 40.6%, 24.6%, and 38.5% improvements in MAE, RMSE, and MAPE, respectively, across various horizons. The incorporation of environmental data, including temperature and Air Quality Index, as supplementary predictors in the DSTGCRN model, has demonstrated its efficacy in the context of the China dataset. The DSTGCRN model's improved accuracy and daily multi-regional forecasting deepen emission dynamics understanding, supporting the development of informed and region-specific environmental policies that can respond promptly to changes. [ABSTRACT FROM AUTHOR]

This study delves into the nexus between the efficiency of carbon emission allocation and the efficiency of green development within the context of innovative city construction. Leveraging data from 283 prefecture-level cities and corresponding provincial-level panel data spanning the period from 2005 to 2019 in mainland China, the research employs the zero-sum gain DEA model to compute provincial carbon emission allocation efficiency and allocate allowances. Furthermore, it utilizes the all-factor non-radial directional distance function and the SBM-DEA model to gauge the green development efficiency of prefecture-level cities. The double-difference method is applied to evaluate the impact of innovative city construction on regional green development efficiency. The results indicate that an imbalance between carbon emission allocation efficiency and emission quotas detrimentally affects urban green development. However, technological progress, factor accumulation, and the institutional environment associated with innovative city building mitigate this negative impact. Heterogeneity analysis reveals a differentiated effect of innovative city building on regional green development efficiency. This paper not only explores the concept of achieving an equitable distribution of carbon emission allowances but also examines how innovative city building influences regional green development. By establishing connections between urban policies, the equitable distribution of carbon emission allowances, and regional green development, it introduces a new perspective for promoting high-quality development at the regional level. [ABSTRACT FROM AUTHOR]

Given the phase-out of subsidies, the Chinese government has issued a series of non-subsidized industrial policies to support the development of the power Lithium-ion Battery (PLiB) industry, recognized as pivotal for achieving carbon neutrality in the transportation department. However, existing literature provides limited evidence on the contribution of non-subsidized industrial policies, particularly to the PLiB industry. To bridge this gap, using data of 31 PLiB listed firms and 279 relevant non-subsidized industrial policies, this paper analyzes the effects of non-subsidized industrial policies on the global value chain (GVC) embedding position. The results reveal that non-subsidized industrial policies significantly raise the GVC embedding position of Chinese PLiB firms, and the positive effects are prone to increase over the research period. Further investigation shows that there is heterogeneity among PLiB firms, with the raising effects on the GVC embedding position being more significant in eastern and middle PLiB firms, private PLiB firms and midstream PLiB firms. The mechanism verification shows that non-subsidized industrial policies raise GVC embedding position of PLiB firms through technological innovation effect and scale economy effect, while competitiveness effect does not give full play. These findings provide important recommendations for better design of the industrial policies to improve the international competitiveness of PLiB industry and other strategic emerging industries. • This study investigates the effects of industrial policy from the perspective of non-subsidized industrial policies. • Non-subsidized industrial policies raise global value chain embedding position of China's Power Lithium-ion Battery firms. • Mechanisms of technological innovation effect, scale economy effect and competition effect are verified. [ABSTRACT FROM AUTHOR]

Different from developed markets, China capital market is dominated by retail investors. In the digital age, retail investors are increasingly making their voice heard through online channels, which is a new form of shareholder activism in China. This paper examines the association between retail investor activism (RIA) and corporate greenwashing behavior (CGB) using the data of question raised by investors on official investor interactive platforms (IIPs) in China. We discover that the RIA on IIPs is negatively associated with CGB. The mechanism analysis shows that the RIA helps to curb CGB through promoting information transparency and improving internal corporate governance level. We also find that the association between RIA and CGB is strengthened in regions with weaker green finance and environmental regulation, and in industries with weaker product market competition. This indicates that the RIA, a type of private governance, can serve as a substitute to the governance effect of the government and the product market. Further studies show that RIA on unofficial channels such as stock forums or search engines can promote CGB, contrary to the conclusion about IIPs. Our research suggests that strengthening the rights of retail investors through official channels helps to reduce CGB and demonstrates the importance of official channels in the governance role of RIA in emerging markets. [ABSTRACT FROM AUTHOR]

The factors that influence residents' willingness to accept long-term compensation are largely ignored, which leads to coal-to-electricity compensation failures. The core of Internet use is a viable solution to the inefficient coal-to-electricity transition for clean energy. This study employs the Heckman two-stage model to show that the compensation standard for coal-to-electricity transition should range from 25.61 to 174.07 yuan per person. Internet use has significantly promoted the compensation amount for the coal-to-electricity transition among residents. The conclusion is consistent with the theory of "information transmission", indicating that netizens are particularly concerned about the positive information that interferes with the clean energy subsidy standards. The propensity score match method and replacement variables ensure the stability of the research conclusion. Secondly, a subdivision of the sample has shown a significant positive impact of internet use on women in rural areas with lower education levels in northern China. The paper also found that the increase in the importance of different Internet use promotes the amount of compensation for residents' coal-to-electricity transition. The driving mechanisms behind the increase include the learning effect, transaction cost effect and marketization effect, and the family life cycle was found to exhibit an inverted "U" regulation function in the relationship. Therefore, this study provides new policies for the determinants of compensation standards for the coal-to-electricity transition with Internet use. [ABSTRACT FROM AUTHOR]

The implementation of new-type infrastructure plays a crucial role in driving low-carbon economic development in China and worldwide. This work employs fixed-effects model, mediated-effects model, spatial Durbin model, and meta-analysis to thoroughly examine the influence of new-type infrastructure on total factor carbon productivity using panel data of 274 Chinese cities spanning from 2011 to 2021. The findings indicate that: firstly, new-type infrastructure has a notable and beneficial impact on total factor carbon productivity, but there is heterogeneity in resource endowment, city scale, and policy intensity. New-type infrastructure can only promote total factor carbon productivity enhancement in non-resource cities and large cities. Under the influence of smart city policies, new-type infrastructure has a stronger effect on total factor carbon productivity enhancement. Secondly, digital finance and marketization are important ways for new-type infrastructure to improve total factor carbon productivity. Thirdly, via spatial spillover effect, new-type infrastructure may boost total factor carbon productivity not only in the local region but also in places that are spatially connected. Accordingly, this paper offers policy recommendations for the government to encourage the investment and development of new-type infrastructure to support total factor carbon productivity growth. • Increasing total factor carbon productivity can achieve a balance between "carbon reduction" and "economic growth". • In the digital age, the construction of new-type infrastructure is crucial. • Quantitative indicators at the city level can provide a more detailed study of issues. • There are direct, indirect and spatial effects of new-type infrastructure on total factor carbon productivity. [ABSTRACT FROM AUTHOR]

While existing literature acknowledges the development of digital capabilities as essential for enterprises to achieve digital transformation, it falls short in offering comprehensive theoretical insights into the dynamic evolution of these capabilities, especially in the field of environmental and sustainability issues. This paper addresses this gap by employing an exploratory single-case study methodology to investigate the intricate process through which an ecological restoration enterprise in China updates its digital strategy, facilitating the dynamic evolution of its digital capabilities from a resource orchestration theory perspective. Our findings reveal a sequential evolution from digital strategy renewal to resource orchestration and, ultimately, the advancement of digital capabilities. Specifically, the enterprise engages in a co-adjustment and co-creation process, aligning its resources with a digital strategy refresh and fostering the emergence of digital integration and innovation capabilities through effective resource management. This includes the accumulation and divesting of resources as part of the construction process, alongside the enrichment and bundling of resources. This research bridges the gap in the current literature by providing a nuanced understanding of the mechanisms that drive the evolution of digital capabilities, and it offers a theoretical framework that integrates strategic renewal with resource orchestration for environmental and socio-economic sustainable development. Furthermore, the insights gained provide vital managerial implications for the governance, corporate social responsibility and policy of industrial digitalization towards global environmental practice and sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

The central environmental protection inspection is an institutional innovation in China that aims to supervise enterprises by monitoring government environmental enforcement. This paper examines the effectiveness of central environmental protection inspection in improving enterprise environmental performance by using a quasi-natural experiment of the first round of central environmental protection inspection. The study reveals that the central environmental protection inspection improves enterprise environmental performance by strengthening local government environmental enforcement and environmental attention. This is evidenced by the increase in enterprise environmental capital expenditure and the decrease in pollution discharge fees. The impact of central environmental protection inspection on enterprise environmental performance is strengthened by local governments' environmental regulation and environmental fiscal expenditure, as well as by public participation. Under the pressure of central environmental protection inspection, heavily polluting enterprises engage in production process improvement and R&D investment, which can improve their economic performance. This can ultimately lead to a competitive advantage for enterprises, promoting a win-win situation for both environmental and economic performance. [ABSTRACT FROM AUTHOR]

This paper examines the spread of green building development in China by analyzing the implementation of the LEED certification system across 31 provinces from 2006 to 2022. To investigate spatial differences, spatial-temporal evolution, and spatial spillovers of green building development in China, we employed various statistical methods, including Standard Distance Ellipse, Dagum's Gini Coefficient, Kernel Density Estimation, Markov Chain Analysis, Moran's I Exponential Analysis, and Social Network Analysis. The findings reveal the formation of a green building cluster in a northeast-southwest orientation, at the core of the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta regions. There is compelling evidence of substantial regional disparities in green building development, primarily driven by inter-regional differences, which has resulted in a significant gap between the eastern and non-eastern regions. This study identifies the presence of "club convergence" and the "Matthew effect" in China's green building landscape, where spatial factors play a crucial role. Furthermore, a distinct and stable spatial clustering is observed, indicating a complex and multi-faceted spatial association network that goes beyond geographical proximity and neighborhood effects. This network reveals diverse positions and roles for provinces and cities. The eastern provinces and cities are found to exert strong control and dominance while also playing a significant siphoning role. On the other hand, the western provinces and cities have been marginalized, experiencing minimal dividend spillover from the development of other provinces. • Green building cluster with a northeast-southwest orientation has been formed. • Inter-regional differences are the main spatial source. • "Club convergence" and the "Matthew effect" are observed. • Regions demonstrate "Spatial spillovers" and "Relative maintenance". • Major green building cities form "Siphon plateau". [ABSTRACT FROM AUTHOR]

Solar composting chamber is an important way for disposing rural domestic waste locally, which requires the participation of farmers. However, few studies have explored farmers' cooperation preference for solar composting chamber, even without considering farmers' heterogeneity. Therefore, this paper divides the farmers into three types: economic, social, and cognitive dominant. The Choice Experiment method is used to investigate all types of farmers' cooperation preference and willingness to accept subsides for the solar composting chamber, using the survey data of China's Shaanxi province. The findings show that social-dominant farmers favor supply models that incorporate government subsidies, more participating farmers, and technical support, while economic-dominant farmers prefer models that include closer construction distances in addition to those. In contrast, cognitive-dominant farmers prefer models with more withdrawal flexibility in addition to the aforementioned factors. Furthermore, economic-dominant farmers have the lowest value of willingness to accept subsidies, i.e., 10,923 dollars, while cognitive-dominant farmers have the highest, i.e., 22,197 dollars. According to the results, policy implications are suggested, including incentivizing farmers' participation by enhancing government subsidies and technical support, and developing diverse cooperation models. • Farmers play an important role in supply of solar composting chamber. • The farmers are categorized into economic, social, and cognitive types. • Choice experimental is used to measure all types of farmers' cooperation preference. • The farmers' willingness to accept subsidies are calculated. • Supply model with subsidies, participants and technical support are most favored. [ABSTRACT FROM AUTHOR]

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance. • Green finance has significantly reduced China's provincial carbon emissions. • The upgrading of energy structure and industrial structure is a positive channel to reduce carbon emissions. • Green innovation strengthens the carbon reduction effect of green finance, but reveals the potential "greenwashing". • Green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. • Policymakers should develop flexible, dynamic and coordinated green finance development policies. [ABSTRACT FROM AUTHOR]