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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]

The power industry in China is the foremost emitter of carbon, necessitating a clean transition in its power generation segment for successful decarbonization. Identifying and quantitative analysis the critical factors that shape the transition and their operational mechanisms will help achieve a secure low-carbon transformation of the energy system. Nonetheless, the body of extensive research in this particular field remains notably limited. To bridge this gap, this paper initiates by developing a comprehensive mechanism framework (REEP) for the transition towards cleaner power generation including Resource endowment (abbreviated as R), Electricity market (abbreviated as E), Economic development (abbreviated as E) and Policy implementation (abbreviated as P) four fields. This framework is based on monthly power generation data derived from four categories of power generation sources at the provincial level in China, spanning the years 2014–2019. It dynamically and quantitative elucidates the multifaceted impacts of various influencing factors on the evolution of the power generation structure. Based on the REEP framework, we observe the power generation structure evolution trends. The study's findings underscore the significance of resource endowment as a paramount internal factor influencing the clean evolution of the power generation structure, while economic development emerges as a pivotal external driving force propelling its transformation. Despite wind and solar power generation accounting for a relatively small proportion at the end of the 14th Five Year Plan period, it is imperative for China to continue promoting the extensive development of renewable energy. While we should coordinate national power transmission and distribution on the foundation of incentivizing technological innovation in emission reduction and the development of energy storage technology. This approach is essential to comprehensively advance the low-carbon and stable development of the energy system, ultimately facilitating the realization of the dual-carbon goal. [ABSTRACT FROM AUTHOR]

Remanufacturing is a critical tool for solving resource depletion and environmental deterioration by reducing raw material and embedded energy consumption. The Chinese government, like many other countries, has been keenly interested in remanufacturing during the past ten years, because of its potential material and energy usage reductions. However, the development of the remanufacturing industry has been unsatisfactory because of little knowledge of its key industry indices. Many potential customers of remanufactured products do not trust the quality of remanufactured products. The major objectives of this paper are to classify the key industrial indices of the remanufacturing industry and to suggest future directions for improvements. To achieve these objectives, this paper used a combined method of grey incidence analysis and grey clustering, which are suitable for distinguishing critical industry indices that can measure the status of development situation of the remanufacturing industry. This approach was successfully applied to a case in Jiangsu Province, China, and consequently developed useful governmental and industrial policy recommendations for remanufacturing enterprises to promote that industry. The research results identified the “total number of employees with a master's degree or above”, the “total number of engineering and technical staff” and the “number of intermediate technicians” as the most appropriate industry indices to reflect the development situation of the remanufacturing industry in China. There are two more important findings. The first is that remanufacturing talents are the most important internal impetus of the remanufacturing industry and should be paid more attention to. The second is that investment in the remanufacturing industry does not have a strong positive correlation with industry characteristics. The “annual revenue of the remanufacturing industry” and huge investment have not played an effective role in promoting this industry so far. The main contribution of this paper is to provide an effective decision-making tool for defining key industry indices that have an important effect on the remanufacturing industry. The tool provides decision-makers a scientific basis for developing and implementing appropriate industry policies and improvement measures to expand the size and scope of the remanufacturing industry in the future. [ABSTRACT FROM AUTHOR]

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. This paper uses system dynamics (SD) to establish models of long-term development of the renewable energy power industry under FIT and RPS schemes, and provides a case study of China's wind power industry by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also reveals the process of coordination between the two policy tools in the development of the renewable energy power industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of the renewable energy power's long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that the integrate implementation of FIT and RPS can promote long-term and rapid development of China's wind power industry given the constraints and actions of the mechanisms of RPS quota proportion, the tradable green certificates (TGC) valid period, and fines. In addition, in the period of the construction of the TGC market, RPS quota growth rate and fine have a no significant effect on industrial development, however, with TGC market game becoming more and more fierce, both of them have a significant positive impact on the long-term development of the industry. TGC valid period has little effect on industrial development in our study. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

The production and sales of electric vehicles in China are continuously increasing, and a massive wave of scrap batteries is about to emerge. However, there are many challenges in the power battery recycling, such as a disorganized recycling system, a lack of standards, and low efficiency. In addition, the power battery recycling supply chain faces issues such as a lack of transparency, inadequate data management, low trustworthiness, and counterfeit products. Therefore, it's crucial to establish an efficient and sustainable power battery supply chain recycling system. Blockchain technology can provide solutions in decentralized data management, privacy protection, and anti-counterfeiting traceability. It addresses existing problems and improves the Power Batteries Reverse Supply Chain (PBRSC) ecosystem. Thus, this paper proposes a blockchain-based PBRSC management integration framework. Firstly, a four-layer blockchain power battery recycling platform is designed. Secondly, based on the proposed PBRSC framework, this paper studies three key component technologies: double-chain structure and its storage mechanism, information tracing module, and smart contract enabled battery trading management. Then, the validity and feasibility of the double-chain structure was demonstrated experimentally. Finally, the above architecture and key technologies are implemented in the system, the main functional modules are displayed on the interface, and the effectiveness of the framework is explained in cooperation with related enterprises. [ABSTRACT FROM AUTHOR]

Green credit policy (GCP) is a measure the government takes to protect the environment, which will impact firms' behavior. Using a Chinese GCP launched in 2012 as a credit shock and the data of Chinese listed firms from 2007 to 2018, this paper investigates the impact of this credit policy on corporate charitable donations. This paper employs the difference-in-differences method, defining heavy-polluting firms as the treatment group and non-heavy-polluting firms as the control group. Our results show that the GCP significantly improves the charitable donations of heavy-polluting firms. Mechanism analysis indicates that GCP impacts charitable donations through financial constraints and environmental regulatory pressure. Heterogeneity analysis suggests that this effect is stronger for non-state-owned enterprises and firms with weaker external monitoring. Our findings enrich the research on the economic consequences of green credit policy and have practical implications for regulators and policymakers. [ABSTRACT FROM AUTHOR]

China facing the challenge of coordinated development of "ecology, economy, and well-being". Scholars have conducted some research on the relationship between enviromental regulation and employment, but there is less research on the role of clean technology innovation in the employment effect of environmental regulation, which is the purpose of this paper. Using the panel data of 22 industrial sectors in China, the paper uses the number of clean technology patents to measure the level of clean technology innovation, and examines the moderating effect of clean technology innovation in the employment effect of environmental regulations. The results show that: (1) With the gradual improvement of environmental regulation, the impact of environmental regulation on employment presents the characteristics of inhibition first and then promotion. (2) Clean technology innovation has a moderating effect on the employment effect of environmental regulation. It should encourage the green upgrading of traditional technologies, support the development and optimization of private enterprises in various industries, so as to promote enterprises to effectively reduce pollution emissions and create jobs through green technology upgrading at the initial stage. [Display omitted] [ABSTRACT FROM AUTHOR]

In 2020, China formally proposed the goal of achieving carbon peaking in 2030 and achieving carbon neutrality in 2060. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This paper creatively puts forward the view of low-carbon digital economy from the perspective of resource flow, digital flow and energy flow, and studies the synergy effect of low-carbon digital development by constructing the synergy model of low-carbon digital development economic and social development. Based on theoretical research, this paper constructs a synergy model and evaluation index system between low-carbon digital development and economic and social development, and an empirical analysis was conducted based on data related to regional low-carbon digital development and economic and social development in China from 2014 to 2019. The empirical results show that the development of China's low-carbon digital economy is the main driving force for future economic and social development. The effects of low-carbon digital economy on economic and social development varied across regions due to their different regional development patterns. The spatial pattern shows a trend of "high in the east and low in the west". Further, if the low carbon economy and the digital economy included in the stimulus policies can play a synergistic role, it will be able to play the greatest role in promoting economic and social development. And such a scenario is used as a practice in different regions of China in future. The research conclusion of this paper enriches the discussion on the construction of ecological civilization and the construction of a community with a common future for mankind. The conceptualized model of low-carbon digital economy and economic-social development. [Display omitted] [ABSTRACT FROM AUTHOR]

China has implemented a robust regime of livestock environmental regulations (LERs) to control pollution caused by livestock production. However, little is known about the effectiveness of LERs on the livestock industry chain. This paper explores the vertical integration (VI) of the livestock industry chain under the constraints of LERs during 2008–2019. Based on the financial statements of Chinese-listed livestock enterprises, the degree of VI during 2008–2019 is calculated by the input-output table (2018). Then, this paper delves into the treatment effects of LERs on VI by using the difference-in-differences (DID) model based on taking the LERs as a quasi-natural experiment. The findings reveal that (1) LERs can significantly promote the VI of the livestock industry chain and the forward integration of enterprises. This conclusion is still robust in multiple cases. (2) Mechanism analysis shows that LERs cause industrial structure adjustment and production layout relocation, accelerate the expansion speed and scale of capital in the breeding sector, and increase the transaction cost of breeding enterprises. (3) LERs contribute to a 48.45% increase in capital intensity and a 3.05% increase in the selling expense ratio of the breeding enterprises. Finally, this paper provides pertinent policy implications. • The degree of vertical integration was manually compiled by using input-output table. • The treatment effect was estimated by taking regulations as a quasi-natural trial. • The transaction cost and capital deepening of livestock enterprises play key roles. • We propose a layout to balance production and consumption by regional complementary. [ABSTRACT FROM AUTHOR]

Carbon emission policy aims to restrict carbon emissions from energy-intensive companies. It encourages target companies to take green innovation but brings fulfillment pressure. Policy prospects for a low-carbon economy are widely discussed in current studies while insufficient attention has been paid to the effect of the policy on the operating activities of target companies. Using the data of Chinese A-share listed companies from 2007 to 2020, this paper explores the effect of carbon emission policy on the financial performance of target companies. The main empirical results prove the significant positive effect of the policy on the financial performance of target companies and reject the interference of earnings management and survivor bias. Further analysis indicates that target companies significantly reduce the selling, general and administrative (SG&A) expenses and non-operating expenses. The trade of carbon quotas between target companies is allowed and it is regarded as non-operating activity. Results of non-operating revenues and expenses prove that target companies tend to actively reduce carbon emissions but the action does not exceed the policy expectation. The increasing efficiency of asset utilization represents that target companies have taken relevant measures to deal with overcapacity. This paper confirms the positive policy responses of target companies. Policy implications are proposed from the perspective of coverage expansion and market incentive mechanisms to realize the full potential of target companies for carbon emission reduction. [ABSTRACT FROM AUTHOR]

Policy has been the driving force behind the rapid development of China's new energy vehicle (NEV) industry. However, the policy network that supports NEV development has been underexplored. This paper explores NEV as an innovative niche for sustainable transition and investigates the evolutionary mechanism of its policy network by combining insights from policy network, strategic niche management and technology innovation system (TIS) theories. Operationally, this paper adopted a social network analysis method to study the NEV policy network in various niche development stages consisting of 377 NEV policy documents formulated by government agencies between 2000 and 2021. Results show the NEV policy network evolves towards bigger, newer actors and is more heterogeneous in creating joint efforts in policymaking that promotes niche development and facilitates a transition to a market niche. Specifically, the policy network expands continually, and network density reaches the maximum of 0.635 at the end of the technological niche. Six agencies are identified as dominators in NEV policymaking. Collaboration on NEV policymaking exhibits obvious organisational heterogeneity, especially in the market niche with an E-I value of 0.576. This study enhances understanding of the evolutionary patterns of policy network and its function on supporting TIS development for immaturely sustainable technologies. The findings also provide important insights into the NEV policymaking process. [Display omitted] • The policy network of China's new energy vehicle continually expanded as the niche evolved. • Several government agencies are identified as dominators that lead policymaking. • Collaboration on policymaking has evolved towards greater heterogeneity. • Network evolution pattern differs significantly in different stages of the technological niche. • Network evolution pattern tends to be stable when it comes to the market niche stage. [ABSTRACT FROM AUTHOR]

As China's longest-implemented market-based environmental regulation policy, emission charges have contributed outstandingly to improving the ecological environment and reducing firms' pollution emissions. We assess the impact of emission charges on the innovation quality of Chinese firms based on the perspective of firms' breakthrough technological innovation. By observing Chinese A-share listed firms with heavy pollution from 2011 to 2020, we find that corporate breakthrough technological innovation positively moderates the emission charges to enhance the quality of corporate innovation. Our mechanism tests suggest that emission charges and breakthrough technological innovation positively affect innovation quality by improving the means of green innovation of enterprises. In addition, heterogeneity analysis shows that emission charges and firms' breakthrough technological innovation are only effective in improving the innovation quality of state-owned firms, and the effect on the innovation quality of non-state-owned firms is not significant. Our findings suggest that the imposition of emission charges and incentives for firms to embark on breakthrough technological innovation can effectively improve the quality of innovation. • The article is probably the first literature to explore the effects of breakthrough technological innovation and emission charges on the innovation quality of heavily polluting enterprises in China, enriching the research on the impact of enterprise innovation models on environmental regulation. • Based on the IPC information of enterprise patent applications, the paper distinguishes enterprise innovation patterns and explores the moderating effect of breakthrough technological innovation on emission charges to enhance the quality of enterprise innovation. • This paper provides micro evidence on the impact of environmental regulation on innovation quality based on the perspective of firms' breakthrough technological innovation, which has important implications for adopting environmental regulation to achieve a "win-win" situation between pollution control and improving innovation quality. [ABSTRACT FROM AUTHOR]

As a renewable energy source, wind power has received growing attentions, but mostly been utilized in wind power farms or high-rise buildings where the wind with high speed is available. Few studies focus on the micro-wind utilization in low-rise buildings due to the bottleneck that the wind speed cannot meet the minimal speed requirement of small wind turbines. This paper aims to identify the optimal building design which could enable the harvesting of the maximal micro-wind power around low-rise residential buildings. Based on the comparison among different building shapes and the computational fluid dynamics (CFD) analysis via software Phoenics , this paper identified that the building shape of “composite prism” could enable the harvesting of the most micro-wind power. The identified building shape was then tested in a simulated environment of a residential community in Pingtan Island, China. The local wind conditions, long-term community planning, and the requirement of comfort level were all considered in the simulation model. The result shows that the potential of utilizing wind energy in low-rise residential buildings is huge by adopting the proposed building shape of “composite prism”. The finding has significant implications for renewable energy utilization in built environment. [ABSTRACT FROM AUTHOR]

The commercial sector is one of the key sectors in China’s economic transformation and carbon emissions control. This paper applies VAR and STIRPAT models to investigate the major influencing factors of CO 2 emissions in China’s commercial sector over the period 1980–2014. According to the empirical results, per capita GDP, urbanization and energy structure have positive effects on CO 2 emissions while energy intensity has negative effect on CO 2 emissions in the long term. Besides, per capita GDP ranks as the most important driving factors of CO 2 in China’s commercial sector, followed by urbanization, energy structure and energy intensity in that order. This paper argues that reducing energy intensity and improving energy structure are the means to realize CO 2 emission reductions in the commercial sector in the short and long term, respectively. Besides, this paper forecasts that CO 2 emissions in China’s commercial sector will be 1942 Mt by 2030, which is huge and about half of the CO 2 emissions of the European Union in 2014. The findings have important implications for policy-makers to enact CO 2 emission reduction policies. [ABSTRACT FROM AUTHOR]

Whether industrial agglomeration can promote an increase in energy efficiency is of great importance to not only China’s energy conservation and emissions reduction plans, but also China’s future sustainable development. This paper uses statistical data from 285 cities, from 2004 to 2013, to analyze the effect of industrial agglomeration on energy efficiency. The spatial autocorrelation tests show that there is significant spatial autocorrelation and spatial heterogeneity in urban energy efficiency. Although dynamic spatial econometric results show that industrial agglomeration can promote an increase in energy efficiency from a country level, there are significant differences at a regional level. In the east, the effect of industrial agglomeration on energy efficiency has a threshold effect, but in central and western areas, industrial agglomeration can promote the increase of energy efficiency, with the positive effect in western areas greater than that in central areas. Finally, based on the research, this paper puts forward concrete suggestions to enhance energy efficiency. [ABSTRACT FROM AUTHOR]

A carbon reduction labelling scheme is an effective policy tool for motivating enterprises or organizations to reduce their life-cycle-based carbon emissions to benefit the environment. This paper uses system dynamics to model enterprises' compliance with a combined government policy instrument for a carbon reduction labelling scheme, that is, government subsidies and economic sanctions. A case study of paper enterprises in China is provided to demonstrate the application of the proposed model in which two optional technological plans to reduce the enterprises' carbon emissions are examined. The technological plans are categorized as a low-cost and high-cost plan. The simulation results show that both the technological plans are vulnerable to the combined policy making, and the high-cost plan shows superior environmental performance for carbon emissions reduction. However, the enterprises are more inclined to choose the low-cost plan because of superior economic performance. The study offers insights to help enterprises select optimal actions on carbon emissions reduction and to inform government of possible sustainable policy design to promote low-carbon development. The model limitations are discussed as a basis for further improvements in low-carbon development. [ABSTRACT FROM AUTHOR]

As green growth is considered an effective method to save energy and reduce emissions, the questions of how to achieve it and which factors drive green growth have become hot topic. Although there are some studies on the factors impacting the achievement of green growth, they are limited in quantity. Moreover, most of them are primarily focused on specific influencing factors, such as political factors, environmental regulation (ER), technological innovation (TI), and so on; while there is little discussion of the interaction effects in an integrated methodological framework. Accordingly, this paper develops an integrated model to investigate the relationships among ER, TI and regional green growth performance (RGGP). The model is tested using empirical data on 30 provincial administrative regions in China during 2011–2012 by employing structural equation modeling (SEM) approach that can effectively investigate the relationships between observed and latent variables and the relationships among latent variables simultaneously. The hypothesis H 1 of this paper is not confirmed, and the results show that ER has a significant negative effect on RGGP. Both the hypotheses H 2 and H 3 are confirmed, namely, ER significantly positively influences TI, and TI has a positive impact on RGGP. This finding provides empirical evidence to support the Porter Hypothesis that properly designed ER may positively affect RGGP through motivating TI. According to the results of hypotheses H 1 , H 2 and H 3 , we find that ER couldn’t directly promote RGGP, but RGGP will be positively impacted by TI driven ER. The finding supports the view of ecological modernization theory that green growth practices may be promoted by TI driven ER, but whether ER can bring green growth practices is uncertain. Furthermore, the finding indicates that TI is a bridge for linking ER and RGGP. Based on our findings, we present some important implications that can be useful for policy-makers and enterprise managers to promote green growth practices in China. [ABSTRACT FROM AUTHOR]

In 2015, China’s oil safety is seriously endangered with its oil dependence on imports exceeding 60% for the first time. One of the most direct and effective ways of improving oil safety is to reduce oil consumption by substituting automotive fuels. This paper, from the perspective of reducing the cost of oil dependence, constructs a conceptual model of substituting automotive fuels and an evaluation model, and studies the substitutive effects of three kinds of substitutive policies in transportation industry: natural gas, ethanol, and methanol, which have been either put into real practice or in the period of demonstration, and are attached great importance by Chinese government. The results show that the international oil price will drop after implementing the alternative fuel policies, and the absolute value of Chinese economy to oil price elasticity is smaller. The three substitutive policies can obviously reduce the cost of oil dependence, among which ethanol does the best, followed by natural gas and methanol, though the effects vary insignificantly. Taking environmental effect, resource and technology of three alternative policies as a whole, this paper suggests that China should promote natural gas alternative policy in short-term. [ABSTRACT FROM AUTHOR]

With the onset of industrialization over the past several decades, the rural areas are undergoing considerable changes in China. Optimal rural industrial land use distribution provides a spatial foundation for sustainable development in rural areas. Moreover, the importance of appropriate rural industrial land use adjustment is evident in rural spatial restructuring. This paper investigates rural industrial land use patterns and its impact on rural areas in Pinggu District of Beijing based on a combined method of “landscape indices” and the “geospatial analysis.” Subsequently, this paper proposes a rural industrial land use adjustment. The results show that according to the relevance of township and village enterprises (TVEs) to rural development, rural industrial land can be classified as rural industry land (RI-land) and non-rural industry land (NI-land). “Small scale, spontaneous dispersion” is the overall rural industrial land use pattern in China, and the spatial patterns between the two types of rural industrial land are quite different: the pattern “dispersion inside rural settlements” is usually observed in RI-land, while “agglomeration around regional central towns” and “linear sprawl” are common on NI-land. Considering the peculiarity of TVEs, the dispersion for RI-land is designed to absorb the surplus labor and raw materials nearby in the countryside to enhance their output-efficiency, whereas the agglomeration for NI-land is to pursue the efficiency of agglomeration economies. This paper also revealed that current disperse rural industrial land use pattern has generated polluting effects on the environment. Therefore, following the “classification principle,” rural industrial land use adjustment should not merely pursue economic efficiency and agglomeration efficiency but should also engage in labor absorptivity and environmental benefits. The formation and development of rural industrial land in China is quite different from traditional industrial land; these differences are largely attributed to their unique driving mechanisms and historical backgrounds. In particular, the traditional Theories of the Location of Industries directed by “agglomeration,” are unsuitable for rural industrial land in China. Therefore, the results in this paper can help form a basis for sustainable planning of rural industrial land and contribute to rural transformation development in China. [ABSTRACT FROM AUTHOR]

This paper investigates the decoupling of carbon dioxide (CO 2 ) emissions from agricultural economic growth in 30 Chinese provinces from 1997 to 2014. First, CO 2 emissions from agricultural production activities, farming, and livestock husbandry are computed. Then, this paper explores the spatial and temporal heterogeneity of CO 2 emissions and their intensity in China’s agricultural sector. Finally, this paper compares decoupling of China’s agricultural CO 2 emissions from agricultural output value across different regions and years. The results indicate that fertilizer, in-season rice cultivation, and cattle generated the most CO 2 emissions in the categories of agricultural production activities, farming, and livestock husbandry, respectively. The results also show that East China covered more periods of the strong decoupling of CO 2 emissions from agricultural output value between 1997 and 2014. To decrease CO 2 emissions, this paper suggests imposing a higher value-added tax on fertilizer producers, while waiving value-added tax for organic fertilizer and substituting animal manure for conventional fertilizers where possible. [ABSTRACT FROM AUTHOR]

Sustained increase in Chinese household income has exerted positive impact on the consumption of goods and services. This paper aims to analyze the unequal impacts of household consumption across different income households on the whole CO 2 emissions, by utilizing a semi-closed input-output model and hypothetical extraction method. The semi-closed input-output model moves household consumption activities into the intermediate use along with dividing urban and rural households to several groups by their income levels, and the hypothetical extraction method (HEM) is used to estimate the reductions of CO 2 emissions relative to total emissions after extracting the consumption of each household group. The results show that: (1) the impact on CO 2 emissions generated by urban households’ consumption are 1.8 times as much as that of rural ones; (2) excluding consumption of higher-income households from the economy would cause greater CO 2 emission reductions than lower ones. Specifically, urban highest-income households have the most relative reductions of CO 2 emissions, which are −12.2% in 2007 and -13.8% in 2012, while for rural highest-income households are −5.1% in 2007 and -5.1% in 2012. And urban and rural highest-income households are respectively 3.8 and 1.8 times on the relative reductions of the lowest-income ones; (3) the relative reductions of household CO 2 emissions from food sectors is the most, while from residence sectors is the least. Based on the above conclusions, this paper puts forward consumption-based policy implications. [ABSTRACT FROM AUTHOR]

Household e-wastes have been increasingly generated, which has brought environmental burdens in most countries, especially in rapidly developing countries. With the unprecedented industrialization and urbanization, China has faced more serious problems concerning household e-wastes. Moreover, informal e-waste collecting has brought environmental burden due to improper treatment of invaluable parts of e-wastes. Thus, formal e-waste collecting enterprises have emerged with support from the government. But they are still difficult to survive. This paper contributes to systematically identify barriers for formal channels of household e-waste collection in China considering different stakeholders such as the government, households, collectors, and treatment plants. Using perspectives from experts in e-wastes formal collecting enterprises in Liaoning Province, this paper develops three steps based on the method of grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) to reveal the most serious barriers in both the short and the long term by examining causal and effect relationships among these barriers. The results show that households’ habits of selling e-wastes to peddlers is one key barrier, which should be carefully considered in the short term. Support from the government such as providing subsidy and tax reduction for formal collecting enterprises is elemental. [ABSTRACT FROM AUTHOR]

Eco-innovation has become a core engine for long-term stable economic development, as well as a fundamental way to ease the tension between economic growth and environmental resources management. Through the construction of a measurement index system, this paper evaluates the level of regional eco-innovation in 30 Chinese provinces from 2000 to 2014. This paper also employs panel data analysis to study the factors that influence Chinese regional eco-innovation. The results show that, during the observation period, the levels of eco-innovation increased significantly overall. However, the regional comparison of the eco-innovation index revealed an obvious, gradually decreasing distribution pattern from east to west. Factors such as technology push, market pull, and environmental regulation pull have positive but differentiated influences on the eco-innovation throughout China and among the eastern, central and western regions. Based on these heterogeneous influences and the targets of ecological civilization construction, promoting the regional synergy of technology push, market pull, and environmental regulation pull is necessary to improve the level of eco-innovation in China. [ABSTRACT FROM AUTHOR]

The late 1990s and early 2010s witnessed China’s efforts to reform its coal industry towards sustainability. A series of rigorous initiatives were launched to consolidate its coal resources and upgrade its mining sector. The “mine closure and production reduction campaign” (MCPRC) and “coal resources consolidation campaign” (CRCC) were among the notable. This paper conducts a general review of the policies and regulations relating to these initiatives with Shanxi, one of the key coal-producing provinces and one of the pilot areas for reform, as a case study. The paper argues that the “one-size-fits-all” approach may have brought short-lived political and economic benefits. However, in the long run, a rationally-designed, stable, socio-economically and environmentally co-ordinated regulatory framework for both large and small coal mines is needed for the sustainable development of China’s coal sector. This finding would be helpful for the potential similar reform initiatives for the coal sector and for the wider energy sector across the country. [ABSTRACT FROM AUTHOR]

In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China's economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China's sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China's sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China's sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

In recent decades, China has been facing serious water pollution crises. To address this problem, discharge standards for wastewater treatment plants in China are becoming more and more stringent. Also, the sewage charge for compliant emissions and the penalty rate for non–compliant emissions have increased significantly. This paper comprehensively investigates the economic and environmental implications of such wastewater management policy in China. In this paper, a general framework for the analysis of WWTPs’ behavior and the resulted economic and environmental consequences is presented, and the impacts of discharge standard, charge rate, and penalty rate are analyzed. The trade–offs between the operational cost, environmental impact, and pollutant emissions are identified. This study also provides some insightful management implications for concerned policy makers. [ABSTRACT FROM AUTHOR]

The Chinese government committed to controlling carbon dioxide (CO 2 ) emissions and promoting development of non-fossil fuels. Thus, it becomes a top priority for the government to develop effective climate policies. Against such background, this paper develops a new multi-country computable general equilibrium (CGE) model with detailed energy disaggregation. This study evaluates the impact of single policy instrument (carbon tax) and combined policy mixes, in order to investigate driving factors affecting the policy performance. The main findings are as follows. Firstly, the driving factors can be classified into two types. The first type of factors affects cost-effectiveness significantly, while the second type generates considerable effect on emission performance. Secondly, cross-border externalities function as important barriers to the CO 2 emission reduction, since they imply extra competitiveness loss and result in considerable carbon leakage. Finally, this paper considers two integrated policy mixes, wherein carbon tax revenue is recycled to reduce capital tax or support clean energy subsidy. These policy mixes can improve both cost-effectiveness and emission performance, and thus perform better than carbon tax alone. In this way, carbon tax revenue can be used to improve the performance. Looking ahead, complicated policy mixes are preferred to improve the performance of China's carbon tax. [ABSTRACT FROM AUTHOR]

The energy consumption and carbon emissions of the urban building sector have been growing so rapidly in recent decades that developing low-carbon buildings has become a common trend in the world. However, the current developing situation of low-carbon buildings in China's urban area is still dissatisfactory though some measures have been taken. Thus, it is valuable to explore the critical factors responsible for the imperfect low-carbon development. Based on the extant researches, this paper firstly concluded 18 possible factors affecting the development of low-carbon buildings in China's urban area Then, with the data collected from a questionnaire survey, 6 critical factors are identified through factor analysis. The research also employed structural equation modeling to further indicate the influence priorities of the 6 critical factors over corporate low-carbon willingness. The results show that all of these critical factors have significant impacts on low-carbon constructionand return on investment has the first priority over low-carbon willingness. Correspondingly, six proposals are proposed at the end of the paper with the aim to provide a reference for the effective development of urban low-carbon buildings. It is worthy to mention that the results are also valuable for the construction of resource saving and environmental-friendly society in China. [ABSTRACT FROM AUTHOR]

Although a large number of reviews have studied different scales of forest ecosystem services, few have concentrated on accounting the spatiotemporal dynamic changes of forest ecosystem services in a region. To make a more accurate accounting, this paper selects intense data sets that assess the physical quantity and value of forest ecosystem services in Anhui provinces from 2009 to 2014. Regulating and supporting services such as water conservation, carbon sequestration and oxygen release, soil conservation and air purification are included in the paper as variables. Optimize analysis was further conducted in order to identify the spatial and temporal heterogeneity during the study period. We establish a dynamic ecosystem services assessment model with the coefficient of spatial heterogeneity and coefficients of scarce resources and social development to analyze the trend of the value in Anhui province. This model is designed for comparisons of forest services in different scales in Anhui province. The results demonstrate that the total value of forest ecosystem services is beyond the previous estimation while using spatiotemporal visualization. The implications are that the evaluation of forest ecosystem services should be measured more accurately with the help of big data in the future. [ABSTRACT FROM AUTHOR]

Traffic and transportation industry is a carbon-intensive industry in China. The implementation of environmental regulation is of important practical significance. Nowadays, literatures lack of quantitative analysis on transport industry's sustainability performance under the environmental regulation. By using a directional distance function, this paper aims to investigate the effect of environmental regulation on this industry. Furthermore, this paper measures its green total factor productivity under the general intensity of regulation and strict regulation from 2000 to 2010. Results show that the economic growth mode in transportation industry is still the extensive mode, while there is great potential for the improvement of energy saving and production. [ABSTRACT FROM AUTHOR]

Despite the important policy and welfare implications of China's energy issues, to date there has been little investigation from a micro-level perspective of the misallocation of resources in manufacturing enterprises. To fill this gap, this paper deals with resource misallocations in China with special reference to energy and labor inputs. Using a large, novel dataset of manufacturing enterprises from Zhejiang province, we employ a simultaneous system of equations for (gross) industrial output value, wage bill, energy expenditure and carbon emissions. The explanatory variables include labor, educational attainment of employees, capital value, materials, and a list of energy-related variables. Our results show that, for the same energy content, non-coal energy inputs are more productive than coal and coal-related fuels. Non-coal energy is more environmentally friendly but more expensive than coal-related fuels. Using the model estimates, we conduct Wald tests on whether the marginal productivity of labor and energy significantly differ from their respective factor costs. The main findings are that there is substantial resource misallocation in manufacturing enterprises, with labor being underpaid and energy overpaid, on average, in comparison to their marginal productivity. For energy misallocation, however, the pattern varies considerably among the various subsectors. Specifically, energy is over-used in sectors such as Textile , Paper , Chemical , Plastics , Non-metallic , Ferrous metals and Non-ferrous metal . By contrast, energy is under-used in sectors such as Beverages , Textile-wearing apparel , Leather , Metal , Transport equipment , Electrical machinery and Communication equipment . These findings can assist decision-makers in targeting the sectors where there is the most misallocation, identifying which input factors are inappropriately used, improving economic efficiency and lowering overall production costs by reducing allocative inefficiency. [ABSTRACT FROM AUTHOR]

The development of China's forestry resources has never been more challenging due to serious problems such as shortage, inferiority and uneven distribution of forestry resources. Therefore, the study and evaluation of China's forestry resources has a great significance to improve efficiency and ensure the sustainable development of the forestry resource. Meanwhile, the vast territory, huge population and widespread forest landscape of China have led to the numerous indexes and the huge data. To perform the research and evaluation accurately, this paper utilized the big data theory to analyze the relevant data of China's forestry resources. This study collected the data from 31 inland provinces and municipalities of China from 2005 to 2013, after which we carefully examined economic, social and ecological factors to choose assessment indexes and processed data accordingly. Firstly, we performed a cross-sectional dataset analysis using the method of data envelopment analysis to investigate the forestry resources efficiency in 31 inland provinces and municipalities of China in years 2008, 2012 and 2013. Secondly, we analyzed time series data of the 31 inland provinces and municipalities from 2005 to 2013 using the Malmquist total factor productivity index method. Our results showed the dominant factor that restraining forestry resources efficiency for the 31 inland provinces and municipalities is the implemented technology. So we suggest increasing the investment in science and technology to improve the overall efficiency of forestry resources, along with improvement of operation and management by relevant administrative departments to improve technology utilization. The innovation of this paper lies in the dynamic process of analysis. [ABSTRACT FROM AUTHOR]

Climate change and human activities have affected ecological environment in recent decades. This paper investigates the ecological environment change of the Mu Us sandy land based on a combined analysis of land cover and normalized difference vegetation index (NDVI) change trends. The results show that land cover changed moderately during 1990–2010, and areas experienced conversion accounted for 10% of the total land surface. The NDVI values show an evident increase at about 0.0076 year −1 during 2000–2014. This rate is lower than that of Shaanxi-Gansu-Ningxia region (0.0117 year −1 ), but greatly exceeds those of the Three-North Shelter Forest and the upper reaches of the Yellow River. Four categories of grids have been identified for accurate ecological restoration through analyzing the ecological performance index mainly based on land cover and NDVI indicators. The ecological restoration projects laid important foundation for ecological reconstruction in the Mu Us, while the wetting trend has been major climatic factors in vegetation improvement since 2000 (R = 0.687, P ≤ 0.01). However, both field investigation and statistical data analysis indicate that the ecological restoration in the Mu Us are experiencing increasing challenges, due to the growing human activities and still fragile eco-environment. Therefore, this paper suggests that urban–rural development and coal exploitation in this region should give full consideration to the carrying capacity of water and land resources. Overall, the evolving ‘science’ of ‘BIG DATA’ on coupled human-environment system can help to reveal the dynamics of ecological environment, and contribute valuable information for decision making concerning natural resources management and urban–rural development. [ABSTRACT FROM AUTHOR]

Theoretical studies of pollution haven hypothesis predict that differentiated environmental regulation policies will result in inter-country relocation of polluting industries. This paper investigates pollution haven hypothesis at domestic level in China. Using panel data of 30 provincial level regions for the period 2004 to 2013, this paper empirically examines to what extent multiple environmental policies affect intra-country relocation of polluting industries in China. It is found that the implementation of both economic policy instrument like pollution discharge fee and public participation like letter complaints on environmental problems encourages industrial relocation, whereas the implementation of environmental legal policy instrument like laws, regulations and rules prevents polluting industries from relocating to other regions. It is also found that the relocation effect of environmental policies varies with industrial characteristics. Compared with water pollution-intensive industry, air pollution-intensive industry dominated by stated-owned capitals are insensitive to legal policy instruments. These findings suggest that the validity of pollution haven hypothesis is jointly associated with the type of environmental policy as well as industrial characteristics. [ABSTRACT FROM AUTHOR]

Sustainable consumption (SC) is key for sustainable development, but only limited studies have examined how to motivate SC among consumers in developing countries. Younger consumers tend to more sustainable consumption while whether they really understand the SC concept is not clear. To explore the role of SC understanding for motivating SC behaviors, this paper develops a concept model with hypotheses to propose that SC understanding mediates relationships between influencing factors and SC behaviors. Based on 623 usable questionnaires collected from junior high schools and senior high schools in three eastern cities of China, five influencing factors for SC behaviors are identified, they are, education, awareness & attitude, social influence, effectiveness of energy saving and emission reduction for sustainable products, and differentiation of sustainable products from regular products. Statistic results through hierarchical regression analysis demonstrate that SC understanding is necessary to motivate SC behaviors with certain influencing factors. Chinese adolescents can understand the SC concept through education and then purchase sustainable products. Only if sustainable products can show benefits of energy saving and emission reduction, Chinese adolescent would like to use these products. Environmental awareness and attitude can bring environmental treatment and disposal of products, but SC understanding is necessary. This paper contributes to extend the TPB to develop a conceptual model including education as one influencing factor for SC behaviors. It also develops three factors for SC behaviors from the product life cycle perspective. Besides, it also contributes to extend the previous studies about motivation of SC consumption to adolescents in an emergent economy of China to examine the role of SC understanding. Statistic results reveal the low implementation level of SC behaviors, and the government should highlight sustainable education to improve sustainable awareness and SC understanding. It is also shown that adolescents would like to purchase sustainable products if environmental performance of such products can be demonstrated, which also provide insights for enterprises to achieve win-win opportunities. [ABSTRACT FROM AUTHOR]

As global warming intensifies, the reduction of carbon emissions is imminent. Carbon price is directly related to whether carbon can be effectively reduced. Therefore, accurately forecasting carbon price has important practical significance. Aiming at the nonstationary and nonlinear characteristics of carbon price, this paper proposes a novel hybrid model for forecasting carbon price, which is based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), multiscale fuzzy entropy (MFE), complete ensemble empirical mode decomposition (CEEMD), improved random forest by salp swarm algorithm (SSARF), improved back propagation by cuckoo search (CSBP), improved extreme learning machine by whale optimization algorithm (WOAELM) and error correction (EC), named ICEEMDAN-MFE-CEEMD-SSARF-CSBP-WOAELM-EC. Firstly, carbon price is decomposed by ICEEMDAN, divided into high-, medium-, and low-complexity components by MFE. Secondly, high-complexity components are merged and secondarily decomposed by CEEMD, which are still recorded as high-complexity components. Then, SSARF, CSBP and WOAELM are used to forecast high-, medium-, and low-complexity components, respectively, and forecasting results are reconstructed. Finally, EC is carried out using an extreme learning machine to obtain the final forecasting results, and the Diebold-Mariano test is introduced for a comprehensive evaluation of the model. Taking carbon price in the pilot cities of Shenzhen and Hubei as examples, after 6 aspects and 20 comparative experiments, the results show that the proposed model has higher forecast accuracy, with MAPE, MAE and RMSE up to 0.03131, 0.00089 and 4.02e-06 in Hubei, and its forecasting ability is better than other commonly used international carbon financial price forecasting models, providing a theoretical and data basis for carbon pricing and formulating carbon reduction policies in China. The main contributions of this paper are the improved primary decomposition, the use of secondary decomposition, and the innovative combination of three optimal models to forecast carbon price, but it still needs to be optimized for practice. [Display omitted] • Propose improve CEEMDAN by using Hermite interpolation and calculating residuals first. • High complexity components are secondarily decomposed to reduce its complexity. • Improved RF by SSA, named SSARF, is proposed to solve the dilemmas of RF. • Propose a high-accuracy hybrid model for carbon price forecasting. • Compare multi-faceted experiments to prove the validity of the proposed model. [ABSTRACT FROM AUTHOR]

Carbon trading is an important market instrument and policy tool to promote China's practice of low-carbon energy conservation and strive to achieve carbon peaking by 2030 and carbon neutrality by 2060. To improve market flow and respond to the national strategy to support the development of carbon trading in China, a smart carbon trading process optimization framework based on blockchain technology is developed in this article. First, the paper analyzes the current state of carbon trading in China's power sector and identifies the future development trend and barriers to carbon trading in China. Second, a framework for a smart carbon trading system based on the structure and traits of blockchain technology is created to optimize the carbon trading process. Third, the smart contract for the smart carbon trading system is built (including execution logic, transaction matching, contract fulfillment, and other elements). This mechanism measures the reputation of trading users. Finally, policy suggestions are provided to solve the current issues and challenges. According to the research conducted for this paper on "blockchain + carbon trading in China," carbon trading supported by blockchain technology can guarantee transaction security and efficiency, accurately preserve transaction records, and offer a high level of automated settlement. [ABSTRACT FROM AUTHOR]