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The Tibetan Plateau works as an important environmental and ecological barrier for the Asian continent. The researches on Tibetan environment and ecology are becoming extensive, but there is no systematic summary of research hotspots and trends in this field. Here, we analyzed 9180 publications retrieved from the WOS and CNKI during 2000 ~ 2020. The characteristics of publication, keywords with a 5-year interval and co-occurrence analysis were carried out so as to reveal the evolution and development trends of topics. The results show that articles increase dramatically since 2012. Except for common concerns like evolution, climate change, and precipitation, diversity was been studied more by Chinese scholars, while the USA, Germany, UK, and Australia researchers focused more on adaptability, basin western Tibet, lake, barley, and ore-related themes, respectively. Besides, China closely collaborated with the USA, Australia, and Germany in topics of evolution, climate change and degradation, precipitation, and diversity. The institutions located in Chinese different economic regions focused on different research keywords, such as vegetation, growth, trace elements, and geochemistry. The CAS contributed the most articles with 4254, showed advantages both in quantity and quality. Few articles were published by researchers affiliated to Free University of Berlin but with higher citations. It is the only one institute outside of China in the top 20. Main research hotspots include climate change, geology, and diversity. In future researches, ecological management and rehabilitation of mining area and tailings ponds, waste disposal, and changes of soil and water quality are worthy of attention and funding.

This study investigated the research trends, key areas, and directions of water rights (WRs) using bibliometric data based on the Science Citation Index Expanded (SCI-E) and Social Sciences Citation Index (SSCI). This paper presents a comprehensive review of annual output, research fields, cooperative networks, published journals, and hot spot evolution from 1971 to 2020. The results show that the number of published papers on WRs has an exponential upward trend. This research mainly focuses on water resources, environmental sciences, environmental studies, law, agronomy, and political science. Rutgerd Boelens and Barbara Van Koppen are authors of the most widely published and influential factors in the field. Leo Heller, Priscila Neves-Silva, and Jeroen Vos have been the most recently active authors. University of New Mexico and the United States Department of Agriculture are the organizations with the most publications and total citations, respectively. The USA, China, Australia, the UK, The Netherlands, and Spain are among the most productive countries for WR research. Keyword analysis showed that the study of WRs has gone through three stages: the exploration of laws and regulations, comprehensive management, and technology development and application. Literature citation cluster analysis shows that a highly central article provides a strong link between internal research on WRs. Western USA, trading WRs, and constitutional reform were hot spots before 2010, while economic anthropology, combined effect, public attitude, and integrated assessment modeling have become popular recently. The study results can help experts understand the research progress in WRs.

The existing literature on smart city pilots mainly focuses on the city level and rarely addresses the firm level. This paper assesses the impact of smart city pilot policy (SCP) on firms' total factor productivity (TFP) and explores the impact of SCP under different heterogeneities as well as the mechanisms of action of the SCP. The LP approach is used in this paper to measure firms' TFP, and the impact of SCP is analyzed by the DID model with firms' panel data from 2009 to 2019 as research objects. First, it was found that the SCP can significantly increase the TFP of firms (0.041). Second, through heterogeneity analysis, we found that SCP can strengthen the monopoly position of monopolistic firms and state-owned enterprises. Moreover, the SCP can also alleviate the development imbalance of TFP between firms in coastal and non-coastal areas. In addition, SCP can significantly improve TFP of heavy polluting enterprises. Finally, we find that the important ways for SCP to improve firms' TFP is increasing investment in technological innovation, talent agglomeration, attracting financing, improving resource allocation efficiency, and digital transformation. The study provides unique insights for policy makers and business managers in China and other emerging countries to enhance TFP and achieve corporate sustainable development.

With ecological civilization becoming an increasingly high profile topic, terms such as carbon neutrality and carbon markets have entered the research landscape. Carbon prices are the core of carbon markets. After analyzing the eight carbon trading markets in China, this paper finds that carbon prices are poorly balanced, i.e., they vary widely between pilots. Regional carbon prices show a discrete distribution, and regions with better carbon market development do not have a spatial demonstration effect on neighboring regions. Therefore, in the initial stage of China's unified carbon trading market, the mandatory control threshold amount should be lowered to allow more enterprises can participate in emission reduction. Reliance on nonclean energy should be weakened, investment in environmental protection and emission reduction should be strengthened, the proportion of carbon offset in forestry should be increased, and a carbon tax should be gradually introduced. The paper's overall aim is to bridge regional barriers and narrow differences to achieve a smooth transition from pilot regions to national and global carbon markets.

The use of clean energy can promote the coordinated development of the economy and the ecological environment. However, few studies have paid attention to the changes in the health status of residents in the process of economic development and energy use. To fill this gap, this paper uses health energy intensity, which refers to the amount of energy consumed per unit of health status (composed of population mortality, maternal mortality, and perinatal mortality), to explore the impact of clean energy (expressed by the share of clean energy consumption in total energy consumption) on economic development and healthy energy intensity. By using the panel data of 30 provinces and cities in China from 2005 to 2019, this paper constructs a simultaneous equation model for empirical analysis from the perspective of the whole country and areas with different income levels. The results show that from the national perspective, in the early stage of clean energy development, the level of economic development and healthy energy intensity increased; however, with the further development of clean energy, the sample period shows that the level of economic development and the healthy energy intensity decreased. Heterogeneity analysis shows that in both high-income and moderate-income areas, clean energy has a U-shaped effect on economic development; but in low-income areas, clean energy has an inverted U-shaped effect on economic development. In high-income and low-income areas, clean energy has an inverted U-shaped effect on healthy energy intensity; but in moderate-income areas, clean energy has a U-shaped effect on healthy energy intensity. China's clean energy market is still in its early stage, and the research conclusions of this paper provide a theoretical basis for the realization of China's clean energy development.

With economic growth, China's energy consumption and industrial agglomeration have increased significantly. This paper uses China's provincial-level energy-intensive industries from 2004 to 2017 as the research object and employs a multi-dimensional panel fixed effect model to investigate the impact of industrial agglomeration on energy efficiency and its mechanism. Results show the following: (1) In general, industrial agglomeration and energy efficiency have a significant "inverted U-shaped" relationship, with an inflection point of 3.309. As the degree of agglomeration increases, energy efficiency first increases and then decreases, but the degree of agglomeration does not cross the inflection point. (2) The impact of industrial agglomeration on energy efficiency has regional heterogeneity. In the eastern and central regions, there is no significant non-linear relationship between industrial agglomeration and energy efficiency but a monotonous positive correlation. In the western region, industrial agglomeration has a significant "inverted U-shaped" impact on energy efficiency, with an inflection point of 3.495, but the agglomeration degree is still on the left of the inflection point, suggesting that a moderate increase in agglomeration is conducive to the improvement of energy efficiency. (3) Industrial agglomeration improves energy efficiency by increasing human capital and promoting fixed asset investment. Therefore, this paper argues that the agglomeration of energy-intensive industries in various regions should be increased to improve energy efficiency. However, it is necessary to raise the industrial threshold in the western region to prevent industrial agglomeration from crossing the inflection point.

The digital economy is an important way to relieve current pressure on resources and the environment. Based on ecological modernization theory and global value chain theory, this paper adopts panel data of 17 manufacturing industries from 2000 to 2014, uses the non-radial directional distance function and the meta-frontier method to measure China's green total factor productivity (GTFP) and its sub-indices, and takes the embedding degree and embedding position as moderating variables and threshold variables to construct an econometric model to explore the relationship among the digital economy, global value chain, and GTFP. The results show that (1) the digital economy has a positive effect on GTFP in both time and space. And in terms of time, the digital economy mainly enhances GTFP by improving technical efficiency and narrowing the technology gap. (2) Global value chain embedding position positively moderates the relationship between the digital economy and GTFP; In terms of sub-samples, labor-intensive and capital-intensive industries show the same impact characteristics as the total sample. (3) Further, it is found that the digital economy and GTFP have nonlinear characteristics. There is a single threshold effect on the embedding position. When the embedding position is low, the digital economy is positively correlated with GTFP but not significant; when the threshold value is crossed, the digital economy can significantly promote GTFP. The conclusions of this paper are helpful to realize the digital economy to promote the green development of the manufacturing industry, and provide an effective reference for the realization mechanism of China's green economy transformation and ecological civilization construction in the post-pandemic era.

PM2.5 has a significant negative impact on human health and atmospheric quality, and accurate prediction of its concentration is necessary. When using common point prediction models for PM2.5 concentration prediction, the influence of various uncertainties on PM2.5 concentrations makes the prediction results suffer from poor accuracy. To address this issue, this paper proposes the quantile regression neural network (QRNN) model based on the least absolute shrinkage and selection operator (LASSO), combined with kernel density estimation (KDE) for probabilistic density prediction of PM2.5 concentrations. The model uses LASSO regression to select the influential factors, and then the quartiles of daily PM2.5 concentrations calculated by the QRNN model are imported into the KDE model to obtain the probability density predictions of PM2.5 concentrations. In the paper, empirical analyses are carried out with the cities of Beijing and Jinan in China as well as six other datasets, and the prediction performance of the model is assessed by using evaluation criteria in both point prediction and interval prediction. The simulation reveals that the predictive performance of the LASSO-QRNN-KDE model is well, and the model is not only effective in filtering high-dimensional data, but also has a higher accuracy compared to common research models. In addition, the model is able to describe the uncertainty of PM2.5 concentration fluctuations and carry more information on the variation of PM2.5 concentrations, which can provide a novel and excellent PM2.5 concentration prediction tool for relevant policy makers.

China's living arrangement has changed as the economy grows and society makes progress. More and more people prefer to live alone. In 2018, a total of 240 million people chose to live alone in China, with an annual growth of 0.53% per year. How will the growing number of people living alone affect the resources consumption and the ecological environment? Based on the data from 1998 to 2017 at provincial level, this paper selects domestic water and electricity consumption to represent resources consumption, and household garbage generation to represent ecological environment, taking the proportion of single-person households in the total households as the explanatory variable and age, education, and household appliances as the control variables. This paper aims to apply dynamic panel models to analyze the impact of solitary population on resources consumption (water and electricity resources as representatives) and on waste generation. The results show that (1) people living alone consume more resources and generate more garbage, while household waste is influenced most, followed by household electricity consumption and household water consumption, (2) positive relations between age and resources consumption and waste generation have been identified, and (3) the energy-saving technology of home appliances is conducive to resources conservation and emission reduction.

Improving green energy efficiency is crucial to promoting China's high-quality economic development and reducing the environmental pollution. In this paper, the Malmquist-Luenberger index measures the green energy efficiency of 30 provinces in China from 2004 to 2019. Based on the measurement results, the spatial Durbin model is used to empirically study the impact of environmental regulation on green energy efficiency and its spatial spillover effects. The results show that China's green energy efficiency is low, and its growth mainly comes from technological progress (TECH) rather than technological efficiency (EFFCH). The eastern region has the highest efficiency of green energy, followed by the West and the lowest in the Central region. The estimation results of the spatial Durbin model show that both environmental regulation and green energy efficiency have a significant spatial correlation. Environmental regulation can improve the green energy efficiency in the local province but inhibit green energy efficiency in the adjacent provinces. Finally, this paper puts forward relevant policy suggestions according to the research results.

Strategic emerging industries are key areas to transform the traditional industrial model of high pollution, high energy consumption, and high emissions. This paper focuses on the measurement of financing efficiency of strategic emerging industries. On the one hand, in order to overcome the interference of external environment and statistical error existing in the traditional single data envelope model, the SSBM-BOOT five-stage model is proposed. On the other hand, Malmquist index method and Luenberger productivity method are combined to evaluate dynamic efficiency, which select Beijing-Tianjin-Hebei listed companies' data. The results show that (1) external environmental factors play a significant role in financing efficiency. The empirical results of the SSBM-BOOT five-stage model show that environmental factors "raise" the efficiency value of the whole Beijing-Tianjin-Hebei region. (2) Based on the revised data and the overall and decomposition results of SBM-ML index, it can be seen that the regional industry is still in the stage of scale expansion, and the financing efficiency depends on technological innovation that needs to be improved. Finally, the paper puts forward the concrete strategies of creating industrial development environment, promoting technological innovation, and establishing green investment and financing mechanism.

Under the background of "the Belt and Road" and "the economic corridor of China, Mongolia and Russia" initiatives, it is of great significance to study the temporal and spatial evolution characteristics of urbanization in Russia. This paper studied the population urbanization level, economic urbanization level, social urbanization level, eco-environment urbanization level, and their coupling coordination development degree during 2005-2020 in Russia. First, combining with the Population-Economic-Sociology-Eco-environment model, the paper constructed the index systems to evaluate the urbanization development levels in Russia. Second, based on the comprehensive weighting method of entropy weight and variation coefficient, this paper calculated the population urbanization level, economic urbanization level, social urbanization level, and eco-environment urbanization level in Russia. Third, this paper used the coupling coordination model to measure the coupling coordination degree of the urbanization development levels in Russia. Finally, the spatial differentiation of the population urbanization level, economic urbanization level, social urbanization level, eco-environment urbanization level, and their coupling coupling-coordination degree was performed, respectively, by using ArcGIS. The results are as the following. First, from 2005 to 2020, the economic urbanization level and eco-urbanization level have shown the increasing trend in Russia. The population urbanization level and social urbanization level have shown the stable changing trend in Russia. The eco-environment urbanization and economic urbanization contribute larger share to the urbanization system compared with the population urbanization and social urbanization. The coupling coordination development degree of population urbanization level, economic urbanization level, social urbanization level, and eco-environment urbanization level has showed a slight increasing trend. However, the overall situation of the urbanization in Russia is still in the moderate uncoordinated recession stage. Second, the federal subjects with high urbanization development levels are mainly distributed in Moscow city, Moscow Region, Sverdlovsk Region, Tumen Region, Saint-Petersburg city, Republic of Tatarstan, Krasnoyarsk Territory, Republic of Bashkortostan, Chelyabinsk Region, Nizhny Novgorod Region, Krasnodar Territory, Rostov Region, and Khanty-Mansiysky Autonomous Area. The federal subjects with low ones are mainly located in Republic of Khakasia, Republic of Marii El, Republic of Kabardino-Balkaria, Republic of Tyva, Republic of Karachaevo-Cherkessia, Republic of Kalmykia, Republic of Altay, Jewish Autonomous Area, and Republic of Ingushetia. Third, spatially, from 2005 to 2020, the urbanization pattern of population, economy, society, eco-environment, and their coupling coordination degree in Russia all show unbalanced development characteristics. The population urbanization pattern and the social urbanization pattern have not changed significantly, showing the spatial characteristics of "high west, low east," and "high middle, low north, low south." The economic urbanization pattern has been increasing significantly, showing the spatial characteristics of "high core, low edge." The eco-environment urbanization pattern has not changed significantly, showing the spatial characteristics of "high north, low south." The coupling coordinated development degree of urbanization pattern has showed a slight increasing trend, showing the spatial characteristics of "high middle, low north, low south," "high west, low east". Finally, we suggest policies and strategies that can boost the growth and development of the urbanization in Russia.

Based on the unique micro-data of newly built polluting firms for the period of 2009–2018, this paper adopts the conditional logit model to empirically evaluate the impact of environmental regulations on the location choice of polluting firms. Moreover, we extend the theoretical model by considering that the environment regulations not only influence the pollution cost but also the level of technological innovation and labor cost. The empirical results show that polluting firms tend to flow into areas with stringent environmental regulations, which supports the Porter hypothesis, but the effect of environmental regulations have a divergent impact on heavily polluting firms. Heterogeneous analysis indicates that environmental regulations have shown a positive impact on the location choice of private and foreign-funded firms but no significant impact on that of state-owned firms; the impact of environmental regulation is consistent with pollution haven hypothesis for firms in the central region but is in line with Porter hypothesis for firms in other regions. Meanwhile, the probability of air polluting firms entering areas with stricter environmental regulations is higher than that of water-polluting ones. Finally, this paper further empirically tests the conduction mechanism, that is, environmental regulations can affect the location choice of polluting firms by affecting the regional technological innovation capabilities and labor cost.

Rapid urban expansion and energy transformation are two major challenges facing China. Many researchers have explored urban compactness and energy efficiency, but there is little literature on the coordinated development of the two. Therefore, this paper takes 35 cities in China as research object: The urban compactness evaluation index system is established, and the score is calculated using the entropy weight method; considering the bad output, SBM is used to calculate the green total factor energy efficiency (GTFEE); and the coupling coordination degree model is used to calculate their coordinated degree. The following conclusions can be inferred: (1) Although China's urban compactness has increased, it has not maintained a steady upward trend. Some more developed cities have the phenomenon of compactness rising first and then falling; (2) The overall GTFEE shows a continuous upward trend, but there is still much room for improvement, and regional disparities are significant; (3) The degree of coordination between the two maintains a steady upward trend, and the city's compactness lags behind GTFEE. Based on the findings of the study, this paper proposes policy recommendations that can serve as a reference for key decision-makers and are critical in promoting China's urbanization and energy transformation.

This paper aims to conduct a systematic overview of green growth literature and reveal the evolution, hot topics, as well as future directions of this field. Given the dispersion of the existing related studies, the development and evolution process of green growth have yet to be comprehensively reviewed. The qualitative review cannot objectively and quantitatively screen out important keywords, possibly leading to bias. This study uses a hybrid method based on bibliometric analysis and the fuzzy Delphi method to review 806 papers from the Scopus database. The findings show that there is an exponential rise in publications with the leading authors, countries, and institutions concentrated in South Korea, China, and the USA. The contents of core literature are focused on pathways and influencing factors of green growth. Hot topics, including policy support, resource management, emission reduction, and the application of new technology, are summarized. The top 5 keywords for future directions are energy, economy, emission, development, and management. The findings offer some valuable contributions to both academic and practical investigations of green growth.

National environmental protection supervision and control has become essential means to regulate the environmental behavior of enterprises. Furthermore, the optimization, promotion, and sustainability of relevant policies are key topics of inquiry. Taking the implementation of national environmental protection supervision policies as the time series, this paper studies the impact of national environmental protection supervision and control on corporate production efficiency. It uses the multi-phase difference-in-difference (DID) method and explores the sustainability of said policies. Results indicate that, first, national environmental protection supervision and control can considerably enhance corporate production efficiency, and green technology innovation plays a vital role as an intervening variable. Second, national environmental protection supervision and control can only boost the increase in corporate production efficiency in the short term, and the impact will no longer be noticeable in the third year. This paper provides a decision-making basis for constantly boosting and revising national environmental protection supervision and control policies and stimulating green technology innovation.

In the recent two decades, construction and demolition (CD) waste is becoming a major source of municipal waste which causes severe damage to the environment. To solve the problem, waste recycling measures are gradually used to turn waste into treasures. Meanwhile, several kinds of policies such as waste disposal charging fees have been issued to stimulate stakeholders' behavior to take waste recycling measures to promote the CD waste recycling industry. However, the CD waste recycling rate is still too low in China. In order to promote CD waste recycling industrial development, this paper aims at introducing subsidy and environmental tax policies to promote CD waste recycling. Based on system dynamics method, this study establishes a model to determine the proper subsidy and environmental tax range. According to the simulation results, three kinds of incentive policies are obtained, namely, single subsidy policy, single environmental tax, and combined incentive policies. Optimal single subsidy and environmental tax are in the interval, [10, 30] and [20, 60], respectively. The best combination strategy is subsidy = 10 yuan/ton and environmental tax = 20 yuan/ton. The results from this paper could be a foundation for government to establish incentive policies to promote CD waste recycling.

Green finance aims to intervene in investment and financing behaviors through financial means, so as to promote upgrading of heavily polluting industries. Whether it can reduce illegal pollution discharge behaviors is the focus of this paper. This paper is to explore the impact of green finance on illegal emissions of heavy polluting firms. Taking green finance pilot zones (GFPZ) in 2017 as a quasi-natural experiment, the paper measures illegal emission behaviors based on day-night difference of PM

In the context of green finance, whether listed companies in heavily polluting industries can convert the external pressure of environmental information disclosure into internal motivation is critical to achieving environmental governance goals. This paper selects 946 listed companies of 16 heavily polluting industries in the Shanghai and Shenzhen stock markets as samples to explore whether environmental information disclosure can help companies increase bank credit support and reduce debt financing costs to transform their external pressures into internal motivation. The empirical results show that there is a significant positive correlation between environmental information disclosure and bank credit decisions. From the perspective of financing scale, heavily polluting companies have the inherent motivation to disclose environmental information actively and proactively to obtain more credit support. There is no significant relationship between the corporate debt financing cost and environmental information disclosure. This paper puts forward some critical policy suggestions for government decision makers, heavily polluting enterprises and financial institutions.

This paper is based on analyzing the process of green innovation inspiration and green innovation compensation effect after the implementation of environmental regulations by the Chinese Government. This paper tests the hypothesis using the evolutionary game model and studies the underlying behavioral characteristics of the government, enterprises, and the relevant influencing factors. These influencing factors further aid in examining the evolution law applicable on both sides, which are aligned with the dynamic replication equation and evolutionary equilibrium states under different situations. The key variables used in this study include the concentration of government's environmental regulation, the cost of the regulations, economic penalties, enterprise's green innovation-related income, expenditures, and the enterprise's performance appraisal. Moreover, the results of this study reflect the system stability and equilibrium strategy on the proportion of retained earnings spent by enterprises on green innovation activities and the Government's strict environmental regulations. In the process of game strategy selection between the government and enterprises, the net income and weight of eco-efficiency indicators of the enterprises actively carrying out green innovation activities play a decisive role. Moreover, there should be reduced weight of economic benefits and increase the economic sanctions and innovation subsidies of enterprise pollution behaviors. Furthermore, reduced cost of regulations and innovation expenditures help guide enterprises to rationally allocate superior resources to enhance green enterprise innovation and take the level of innovation to the point that it achieves a win-win green sustainable development of economic performance and environmental performance.

Free-trade zones are highlands of regional development that have a radiating effect on surrounding cities. This paper uses Yangtze River Delta Urban Agglomeration (YRDUA) data from 2003 to 2018, to examine the impact of the China (Shanghai) pilot free-trade zone (SPFTZ) on green total factor productivity (GTFP) in the YRDUA. It uses the regression discontinuity (RD) method and analyzes the influence mechanism with the help of the mediating effect model. The paper presents the following major findings. The establishment of the SPFTZ significantly promoted GTFP in the YRDUA, with technological progress being the main driving force. An analysis using the mediating effect model found that financial efficiency and industrial structure upgrading play a complete mediating role in GTFP growth in the YRDUA. Therefore, the SPFTZ should make use of its policy advantages, take full advantage of the effect of the green growth pole, and promote green mutual development with the YRDUA.

Labor agglomeration with heterogeneous skills has different effects on urban air pollution. Based on the panel data of 263 prefecture level cities in China from 2006 to 2019, this paper constructs a Spatial Durbin Model to explore the impact of skill heterogeneous labor agglomeration and the interaction between skill heterogeneous labor agglomeration on urban air pollution. The results show that there is a positive U-shaped relationship between high-skilled labor agglomeration, low-skilled labor agglomeration, and urban air pollution. From the perspective of restraining urban air pollution, high-skilled labor agglomeration is stronger than low-skilled labor agglomeration. Under the influence of high skilled labor agglomeration, the inhibitory effect of low-skilled labor agglomeration on urban air pollution is enhanced. High-skilled labor agglomeration and low-skilled labor agglomeration reduce the degree of urban air pollution by promoting the improvement of urban innovation level. Based on this, this paper puts forward some policy suggestions, such as further promoting urban labor agglomeration, formulating reasonable urban population management policies, strengthening labor exchange and learning, and carrying out labor knowledge and skills training.

The domestic wastewater collection and treatment rate of Nairobi, Kenya are not high. The wastewater in the Kibera slum on the outskirts of the city that is directly discharged to the environment and pollution of the surrounding water body is a serious problem. This paper takes the domestic wastewater in the slum area as the research objective and researches on the wastewater characteristics, collection, and treatment, therefore providing the reference for the wastewater collection and treatment technology in the region. In this paper, domestic wastewater in the Kibera slum of Nairobi was sampled and investigated to find out the characteristics of wastewater discharged, the way of discharge of the household wastewater, and the management in this area. The study shows that there are differences in the concentration of main pollutants such as nutrients and organic matter in the wastewater from the household discharged to the residential river in the slum area. The domestic wastewater in this slum area contained a high concentration of nutrients such as nitrogen and phosphorus and other organics, total suspended solids (TSS), total coliforms and color, and with no treatment methods. Therefore, economic and feasible treatment technology needs to be developed. A pilot study was conducted on the treatment of domestic wastewater in the slum area by combining the seed extract of the natural plant Moringa oleifera as a coagulant and vertical flow constructed wetland (VFCW) at Tongji University, Shanghai, China. The VFCW system was efficient in chemical oxygen demand (COD), TSS, turbidity, total phosphorus (TP), and phosphates (PO

With the introduction of national carbon neutrality targets, carbon emission reduction actions in developed countries have become a hot topic as part of the international community's drive to take action to mitigate climate change. Carbon emission efficiency is an important indicator that can be used to measure progress toward carbon emission reduction targets. The relationship between green technology innovation and carbon emission efficiency has not been adequately studied, and the transmission mechanism is not yet clear. Based on the above research gaps, taking 32 developed countries that have proposed carbon neutral targets as research samples, this paper used spatial econometric models to explore the impact of green technology innovation on carbon emission efficiency and adopted spatial mediation model and spatial moderation model to analyze the transmission effects of economic development, urbanization, and financial development on environment-related green technology and carbon emission efficiency. This paper aimed to provide a policy basis for developed countries to mitigate carbon emissions and achieve carbon neutrality goals as soon as possible. The following results were obtained: (1) Luxembourg, Norway, and Switzerland were found to be efficient in terms of carbon emissions, while most developed countries were in an inefficient state. (2) Environment-related green technology innovation significantly improved carbon emission efficiency. (3) Economic development and urbanization had a mediating role on green technology innovation and carbon emission efficiency. In other words, green technology innovation could have an indirect impact on carbon emission efficiency by influencing economic development and urbanization. (4) Financial development could positively moderate the sensitivity of carbon emission efficiency to green technology innovation. Improving the level of green technology innovation is one way to improve carbon emission efficiency, and the mediating effect of economic development and urbanization can be used as a focus point to improve carbon emission efficiency. The pressure of carbon emission reduction can be moderated by finance development. The results of this study provide theoretical support that will assist developed countries in achieving their carbon neutrality targets.

Flexible strategy of carbon tax is an important chip for the government to promote the implementation of carbon emission reduction. However, low-carbon technological innovation of enterprises is bound to produce market competition problems with traditional production technology. Based on this, in order to explore the relationship between heterogeneous objectives, carbon tax pricing strategy of government and decision-making of heterogeneous enterprise in the market, and how the government can make better use of carbon tax to promote the implementation of carbon emission reduction, this paper constructs and analyzes a three-stage dynamic game model between the government and heterogeneous enterprises. It is found that higher carbon tax pricing is not necessarily conducive to promote the implementation of carbon emission reduction. When the government's primary goal is to promote low-carbon technology innovative enterprise to increase innovative investment, the government should adopt the unified pricing strategy of carbon tax and improve carbon tax pricing; When the primary goal of the government is to promote the promotion of low-carbon products, the government should adopt the differentiated pricing strategy of carbon tax and reduce the carbon tax pricing of low-carbon technology innovative enterprise. In addition, this paper also studies the impact mechanism of different government pricing strategies on heterogeneous enterprise decision-making under heterogeneous objectives of government.

With China's economy entering the stage of high-quality development, manufacturing energy carbon emission efficiency has become the focus of academic attention. It is of great significance to study the convergence of manufacturing energy carbon emission efficiency for realizing high-quality development of manufacturing in China. Based on the panel data of China's manufacturing sub-sectors, this paper measures and analyzes the evolution trend of manufacturing energy carbon emission and its efficiency. On this basis, this paper uses the coefficient of variation and convergence model to test the convergence of manufacturing energy carbon emission efficiency. The results show that China's manufacturing energy carbon emissions and its efficiency demonstrate an increasing trend. Coal was the main source of manufacturing energy carbon emissions. The manufacturing energy carbon emission efficiency does not have σ convergence, but has [Formula: see text] convergence, and its convergence has industry heterogeneity. The manufacturing energy carbon emission efficiency exits scale effect and technology effect, but not the effect of opening to the outside world and institutional effect, and its effect exists industry heterogeneity. By reducing carbon emissions, adopting differentiated policies, adjusting the industry scale, and enhancing the industry technology intensity, China's manufacturing can improve the energy carbon emission efficiency and promote high-quality economic development.

Emerging markets face severe ecological and environmental problems in periods of economic and political transition. The existing literature analyses the impact of technology on environmental benefits and the role of technology on the green innovation of enterprises, mostly from the perspective of technology spillover in enterprises in mature markets. Based on a sample of 229 Chinese cross-border mergers and acquisitions (MAs), this paper explores the role of technology-driven cross-border MAs (TDC MAs) in green innovation, finding that TDC MAs have a significant promoting effect on green innovation. A higher degree of ownership concentration positively promotes the relationship between TDC MAs and green innovation in the enterprise. This paper divides enterprises into state-owned enterprises (SOEs) and political connection enterprises, with the nature of SOEs negatively affecting the relationship between TDC MAs and green innovation, the nature of political connections significantly promoting the relationship. Similarly, formal institutional distance negatively interacts with TDC MAs to affect the green innovation of enterprises, while informal distance interacts positively with TDC MAs. This paper has important implications for emerging market enterprises in realising the transformation of the mode of economic growth and achieving harmonious development between enterprises and the environment.

Surface coal mining causes vegetation disturbance while providing an energy source. Thus, much attention is given to monitoring the vegetation of surface coal mining regions. Multitemporal satellite imagery, such as Landsat time-series imagery, is an operational environment monitoring service widely used to access vegetation traits and ensure vegetation surveillance across large areas. However, most of the previous studies have been conducted with change detection models or threshold-based methods that require multiple parameter settings or sample training. In this paper, we tried to analyze the change traits of vegetation in surface coal mining regions using shape-based clustering based on Normalized Difference Vegetation Index (NDVI) time series without multiple parameter settings and sample training. The shape-based clustering used in this paper applied shape-based distance (SBD) to obtain the distance between time series and used Dynamic Time Warping Barycenter Averaging (DBA) to generate cluster centroids. We applied the method to a stack of 19 NDVI images from 2000 to 2018 for a surface coal mining region located in North China. The results showed that the shape-based clustering used in this paper was appropriate for monitoring vegetation change in the region and achieved 79.0% overall accuracy in detecting disturbance-recovery trajectory types.

In 2020, China promised to achieve carbon peaking by 2030 and carbon neutrality by 2060, and these targets are famous as “Goal 3060” in China. Chinese resource-based cities are concerned about the realization of Goal 3060 to practice national action against environmental change. In this paper, this study evaluates the impact of population, economic growth, energy intensity, industrial structure, fixed asset investment, and urbanization level on carbon emissions in Chinese cities. To do so, the paper divides 36 Chinese cities into four types (growing city, mature city, recessionary city, and regenerative city) from 2003 to 2017 by factor investigation according to the diverse development stages. The extended STIRPAT model is used to assess the impact of various factors on CO2 emissions in the Yellow River basin and diverse city levels. The panel regression analysis was conducted for the basin as a whole and cities at different development stages through a fixed-effects model and a linear regression model with Driscoll-Kraay standard errors. The results show that (1) the total carbon emissions in the Yellow River basin continued to climb during the study period. However, the growth rate slowed down significantly after 2012. In addition, there are differences in the total carbon emissions and growth rate of different cities. (2) Population, real GDP, energy intensity, industrial structure, and fixed asset investment all have a significant positive impact on carbon emissions in the overall basin except the urbanization level which has a significant negative influence on carbon emissions. (3) There is heterogeneity in the influencing factors of carbon emissions in resource-based cities at various development stages. Based on these results, corresponding policies are proposed for different types of cities to help resource-based cities achieve the 3060 dual carbon goal.

The green credit is one of the effective tools to save energy and reduce pollution, which mainly applies in industry. Thus, this paper explores the impact of green credit on the upgrading of China's industrial structure from the perspective of industrial sectors, by means of a dynamic panel model with the dada from 2005 to 2016. The upgrading of industrial structure is divided into three dimensions to be analyzed-rationalization of industrial structure (RIS), advancement of industrial structure (AIS), and greenization of industrial structure (GIS). The empirical results are also explained by four influence mechanisms-resource allocation, technological innovation, credit catalysis, and policy guidance mechanism. This paper finds that on the national level, green credit has a positive impact on the upgrading of China's industrial structure and plays a significant role in promoting the greenization and advancement of industrial structure. However, on the regional level, the effect of green credit is more complex. First, green credit has a significant positive effect on the GIS in the eastern, central, and western regions of China, which suggests that green credit is conductive to the cleaner production of industry across the country. Second, green credit also has a positive impact on the AIS in these three regions, but the effect is only significant in the eastern region. Third, in terms of the RIS, the effect of green credit is positive but not significant in the eastern and central regions. However, it is negative, not significant as well, in the western region, which can be explained from the perspective of the resource allocation and technological innovation mechanism. In addition, there is a significant positive correlation between the previous period and the current value of RIS, AIS, and GIS, which indicates that there is a significant positive inertia dynamic feature in the upgrading of China's industrial structure.

China, as the world's largest carbon dioxide emitter, is bound to assume the important responsibility of energy conservation and emission reduction. To this end, each city, led by representative municipalities, must enhance efforts in carbon emission reduction to jointly realize China's low-carbon transition. Taking four representative municipalities, namely, Beijing, Tianjin, Shanghai, and Chongqing as the case cities, this paper establishes a decomposition analysis for the driving factors of carbon emissions by applying the LMDI method covering data from 2007 to 2017. Kaya identity is used to decompose the effects into eight driving factors: GDP effect, industrial structure effect, energy intensity effect, overall energy structure effect, population effect, urbanization effect, per capita energy consumption effect, urban and rural energy structure effect. The results show that at the municipality level, the driving factors that contribute to carbon emissions are the GDP growth effect and the population effect, with the former still being the most important factor in the municipalities with faster economic growth; and industrial structure effect is the most important factor that inhibits carbon emissions, followed by energy structure effect. This paper considers the driving factors of both the production side and the residential consumption side from the city level. The research reveals the main driving factors that effect the carbon emissions of megacities in developing countries, and highlights the leading role of megacities in terms of carbon emission reduction in China and even the world. The paper thereby puts forward policy implications for China's economic policies.

Continuously improving freshwater aquaculture efficiency will promote the sustainable development of freshwater aquaculture, which is crucial to ensure aquatic food supply. In particular, measuring the total factor productivity (TFP) of freshwater aquaculture to find ways to improve its efficiency is of great significance to sustainable development of freshwater aquaculture industry. Therefore, based on directional distance function, this paper constructs a meta-frontier Malmquist index (MMI) model by considering the regional heterogeneity to evaluate the TFP of freshwater aquaculture of China from 2004 to 2019. The results show that (1) from the perspective of time, TFP fluctuated significantly from 2004 to 2012, while after 2013, TFP remained around 1 with small fluctuation. In other words, freshwater aquaculture in China began to maintain a relatively negative state of development. (2) From a regional point of view, this study found that freshwater aquaculture TFP of inland region is better than the TFP of coastal region. (3) From the decomposition index, the variation of freshwater aquaculture TFP was driven by the combined effect of technology change (TC) and technical efficiency change (EC). In addition, the decomposition index efficiency shows that the technical efficiency decreases and the management efficiency changes little. (4) The gap of freshwater aquaculture technology in coastal areas is very small, and close to the optimal technical level. While in inland region, on the contrary, there is more room for improvement. According to the above empirical results, this paper finally gives some policy suggestions to improve the TFP to ensure the sustainable development of freshwater aquaculture.

Management of economic growth targets is a universal measure employed by worldwide governments for macroeconomic regulation, as well as an important mechanism for central governments to motivate local governments and officials. This paper extracted panel data on annual economic growth targets and environmental regulation indicators from government work reports (2009–2016) of 284 China’s prefecture-level cities to empirically investigate the impact of economic growth targets set by governments of prefecture-level cities on the environmental regulation intensity. The study concludes that an increase in economic growth targets significantly weakens the intensity of environmental regulation. The conclusion still holds true after robustness tests by changing measurement variables, regression samples and conducting endogenous tests. This also corroborates that empirical results in this study are robust. The underlying reason for the inhibitory effect may be that local governments to achieve economic growth targets prefer less stringent environmental regulations so as to expand outputs in the short term, mainly by increasing the proportion of secondary industry in GDP, land transfer area and fixed asset investment. Further research in this paper also finds that the negative effect of a local government’s annual economic growth target on environmental regulation intensity only exists in cities with low economic development levels and low openness to the outside world.

Green building development(GBD) plays an important role in improving carbon emission reduction efficiency of the construction industry(CEEOCI), and accelerating the construction industry to achieve carbon neutrality goals. In this paper, for the first time, the topic of "green building development promotes carbon neutrality in the construction industry" is included in the crossover research category of industrial economics and space economics. A framework for the analysis of the impact mechanism of GBD and CEEOCI under the dual perspective of "industry-space" is proposed. Based on China's provincial panel data from 2008 to 2019, using the intermediary adjustment model and the spatial Dubin model to analyze and test the industrial mechanism, spatial mechanism, and spatial effect attenuation boundary of the GBD effect on CEEOCI. The results show GBD is found to promote CEEOCI, and both the GBD and CEEOCI have a clear "center-periphery" spatial pattern. Meanwhile, the impact of GBD on CEEOCI has a "industry-space" two-dimensional mechanism. From an industrial perspective, GBD can change the supply-demand relationship of the construction market by promoting the greening of supporting industries in the construction industry and stimulating green consumption in the market, and ultimately achieve the overall improvement of CEEOCI. From a spatial perspective, GBD can form a new sectoral growth pole and provide elemental support for the improvement of CEEOCI through the polarization effect, but the polarization effect is higher in the range of 1000 km, while attenuation occurs outside the range of 1000 km. This paper provides not only a scientific and effective medium and macro analysis framework for green building development emission reduction performance evaluation but also a new theoretical basis and policy direction for the construction industry to improve carbon reduction efficiency and achieve industrial carbon neutrality.

The paper evaluates the species richness, material transfer, energy flow, and system function of the southwestern Yellow Sea Ecosystem (SYSE) indicating intensive human intervention affecting this large marine ecosystem. Twenty functional groups were chosen to represent the basic components of the SYSE for Ecopath modeling based on offshore surveys, annual bird observations, and the China Fisheries Statistical Yearbooks. Forty-nine species based on 15 functional groups of Ecopath model were assessed by stable isotopic analysis (SIA) to verify ecosystem features, energy flow, and trophic structure of the SYSE derived from Ecopath model. Results showed there was a clear correlation of the estimated trophic structure calculated from SIA and the Ecopath model with R2=0.7184. The SYSE Ecopath model was still at an immature and unstable stage according to outputs of the modeling parameters. This paper provides a verification method of detecting the ecosystem features and maturity, stability, and resilience of marine ecosystems by comparing outputs from Ecopath models with SIA.

With China already committing to peak carbon dioxide emissions before 2030 and achieving carbon neutrality before 2060, green development is urgent. It is necessary to clarify the driving mechanism of green development to design the path of green development scientifically. From the internal perspective of the green development system, this paper divides the green development power into external power and internal power. The external power is the political pressure formed by the public's green demands. The internal power is the endogenous power of green development transformed by the political promotion willingness of local government leaders. The research shows that (1) the green demands from the public and the accompanying political pressure can form the driving force of green development. (2) The political promotion intention has not been transformed into the endogenous driving force to promote green development in the research period. (3) The external driving force of public appeal is closely related to economic development, income and consumption levels, and education. This paper enriches the research literatures on the driving mechanism of green development and provides theoretical and practical exploration for the driving path of green development.

The total factor CO2 emission performance (TFCEP) of transportation industry has received increasing research interests, while existing literature pays little attention to its regional inequality and driving factors. In order to uncover the regional inequality of TFCEP in China's transportation industry, this paper used Theil index and combined with geographical detector model (GDM) to explore the driving factors and their interactions on TFCEP in Chinese transportation industry. The results revealed that the TFCEP of transportation industry showed a promising increase during 2003-2017 with an annual growth rate of 0.12%, and the improvement was contributed by the technical efficiency change. The TFCEP in the Eastern region performed better than that in the Northeast, Central, and Western region. Regional inequality of TFCEP did exist and exhibited an obvious downward trend. The within-region inequality had a greater impact on the inequalities than between region. Freight turnover was the main driving factor of TFCEP in the transportation industry, followed by the energy intensity and per-capita GDP. In the Eastern and Western regions, freight turnover had the greatest impact on TFCEP, while in the Central and Northeastern regions, urbanization rate and energy intensity were the dominant factors, respectively. The interactions between energy intensity and freight turnover were highly influential. This paper provides important insights for different regions to formulate targeted carbon emission reduction policies.

China Tarim River Basin is located in an arid area, whose rapid socioeconomic development intensifies the current water resources shortage. To allocate water resources reasonably, this paper introduces the bankruptcy theory into the cooperative game model to contract a linear function describing the degree of satisfaction of each region's declared water demand. Bankruptcy theory solves the problem of insufficient information about players in the cooperative game. From the perspective of the cooperative game's stability, the bankruptcy allocation stability index (BASI) is used to evaluate and compare water resource allocation results in the Tarim River Basin in 2025 and 2030 under different scenarios. Moreover, this paper uses the improved TOPSIS model to build the harmony index of water-economy-environment (HWEE) to evaluate the harmony of water resources, economy and environment in each region. The results show that the model is more suitable for the actual water allocation game and has a good application value than the classical bankruptcy theory. Moreover, the stability index and HWEE proposed in this paper also have better applicability, and the allocation scheme with the same game weight in each region is more stable.

Behind the rapid development of China's logistics industry, there are problems of high energy consumption and high pollution. Under the dual constraints of resources and environment, promoting the low-carbon transformation of the logistics industry is the key to achieving sustainable development of the logistics industry. This paper applies the epsilon-based measure (EBM) model which considers undesirable output and global Malmquist-Luenberger (GML) index to measure the logistics efficiency under the low-carbon constraints of 30 provinces in China from 2005 to 2017, that is, the green total factor productivity (GTFP), and characterizes its temporal and spatial evolution characteristics through visualization and spatial analysis methods. Then, this paper uses the geographically weighted regression (GWR) model to analyze the influence of industrial agglomeration level, informatization level, foreign direct investment, logistics energy intensity, traffic network density, and technological innovation capability on the GTFP of the logistics industry. The findings of this paper show that (1) during the inspection period, the overall average GTFP of the logistics industry was 0.992, which did not reach the effective level, and the spatial differentiation showed that the average GTFP of eastern was greater than that of in central, and that of in central was greater than that of in western. (2) The GTFP of the logistics industry has experienced an alternating process of rising and falling in time, with large fluctuations. Also, in terms of spatial dimension, there is a trend that high-level areas gradually gather to the southeast, and there is significant spatial autocorrelation. (3) For the logistics industry, high-efficiency areas and high-output areas show significant spatial homogeneity. (4) The estimation results of the GWR show that the direction and intensity of the multi-dimensional driving factors on the GTFP of the logistics industry are different in different regions, showing obvious spatial non-stationary characteristics.

China's Loess Plateau Region (LPR) plays a significant role in national ecological security and development. Due to the advantage that relates environment with economy, eco-efficiency has become an important indicator of sustainable analysis. Using cross-level panel data for the period 2006-2017, this paper studied LPR's static eco-efficiency and dynamic performance through a combined application of DEA super-efficient slack-based measure and Malmquist Productivity Index at multi-scales. LPR's eco-efficiency was found to experience a slight increase during the study period. The value decreased roughly from east to west, with high eco-efficiency mainly distributed in provincial cities and resource-based cities. The decomposition of the Malmquist Index indicated that technological change contributed most to the improvement of eco-efficiency in the LPR. Besides, this paper explained the variations of eco-efficiency based on the integrated input-output indicators and TOBIT regression model. Economic scale, population density, government regulation, technical innovation, and openness degree were identified as positive influencing factors, while the structure of the industry and land-use intensity were found to have negative impacts on eco-efficiency. Resource-based cities were found to have stronger potentials for eco-efficiency improvement than non-resource-based cities. This paper revealed the characteristics of LPR's eco-efficiency from three perspectives: a spatiotemporal perspective, a macro-meso-micro perspective, and a static-dynamic perspective. The findings of this study hold important implications for policy makers.

Technology prediction is an important technique to help new energy vehicle (NEV) firms keep market advantage and sustainable development. Under fierce competition in the new energy industry, there is an urgent necessity for innovative technology prediction method to effectively identify core and frontier technologies for NEV firms. Among the various methods of technology prediction, one of the most frequently used methods is to make technology prediction from patent data. This paper synthesizes the frequent pattern growth (FP-growth) algorithm and input-output analysis to construct a new technology prediction method based on the knowledge flow perspective, takes the data of NEV patent family in 1989-2018 the Derwent patent database as a sample, divides the data according to the 5-year standard, and uses the method to identify the core and frontier technologies in the NEV field during different periods. Furthermore, the multiple co-occurrence method applies to analyze the technology layout and evolution patterns in China's NEV field. The results show that the technology prediction method proposed in this paper can effectively identify core and frontier technologies to achieve NEV technology prediction.

The rapid development of the urban economy in China and the accompanying income growth experienced by urban residents have increased demand for tourism and leisure, which has brought pressure on the urban tourism environment system (UTES), making the contradiction between tourism economic development and the ecological environment increasingly acute. While seeking to rationalize the economic, social, and ecological benefits of tourism, reducing the fragility of the UTES and improving its anti-interference and recovery capabilities have become attracted significant attention from scholars in China and elsewhere. This paper establishes a definition of resilience for an UTES and constructs an evaluation index system for it in terms of the social, economic, and ecological environments. It also establishes an entropy weight-TOPSIS resilience evaluation model to measure resilience in regional systems, using ArcGIS to analyze the standard deviation ellipse and center of the gravity track of the resilience. System dynamics was used to construct diagrams of causal relationships and stock flow for the constituent elements of UTES to show the mechanisms that promote its resilience. This paper investigates 14 cities of Gansu Province in particular to simulate the resilience model of a regional system.

In China, the local government's "land for development" strategy has led to a large number of urban construction land allocated to the industrial field, which has promoted the rapid development of industry and economy in the short term but also brought serious environmental quality losses. This paper systematically sets out how land misallocation works on urban air quality and employs the spatial Durbin model (SDM) to conduct an empirical analysis on the panel data of 283 China cities at or above the prefecture level. The result shows that, stimulated by financial maximization and political promotion, in order to obtain more fiscal revenue and growth performance, local governments prefer to allocate a large number of urban construction land to industry and related fields, which leads to the underestimation of industrial land price and the misallocation of land resources. Land misallocation has exerted significant inhibiting effects on the air quality of local and their surrounding cities through inhibiting the upgrading of industrial structure. Further analysis reveals that the bigger the city, the lesser the inhibition effects of land misallocation on upgrading of industrial structure and urban air quality and vice versa. The conclusions of this paper can provide a useful reference for local governments to optimize land allocation, promote economic restructuring, and environmental quality upgrading.

Problems of ecological environment and resources have become an important factor restricting the high-quality development of China's economy. How to better integrate into the sustainable development model has become an important goal of macro-policy regulation in the transition period. Mining industry is a fundamental industry in China. Strengthening the incentive role of mining innovation is of great importance for ensuring China's energy security, reducing emissions and promoting economic growth. However, whether environmental regulation can induce technological innovation ability, that is, the existence of Porter effect, is still controversial. It is helpful to study the influence of the Porter hypothesis on mining enterprises for their sustainable development. Based on the data of listed companies in China from 2003 to 2018, and against the background of the SO2 emission trading pilot policy implemented in 2007, this paper studies the incentive effect of the market-incentive environmental regulation on the technological innovation ability of mineral resource enterprises, tests the existence of Porter effect, and discusses the heterogeneity. The results show that the market-incentive environmental regulation has a significant incentive effect on the innovation of mining enterprises, and there is significant Porter effect on mining enterprises. The robustness test confirms the correctness of this conclusion. At the same time, this paper also discusses the variation of the characteristics of heterogeneous enterprises, and finds that enterprises with utility model patents, no low-carbon behavior, and non-provincial cities and regions with high environmental regulation are more sensitive to the SO2 emission trading pilot policy. This paper verifies the incentive effect of the market-incentive environmental regulation on the innovation ability of mining enterprises, and provides a reference for the formulation of innovation incentive policies for mining enterprises in China.

As a new and cost-effective renewable energy power generation technology, offshore wind power is getting more and more attention. The development of offshore wind power industry is affected by policy-making, technology management, resources and environment, market supply and demand, and the relationship among the influencing factors is complex. This paper analyzes the factors that affect offshore wind power industry from a unique and comprehensive perspective. Fourteen factors are selected and interpretative structural model (ISM) is established to study the relationship between the influencing factors of offshore wind power industry. The results show that 14 influencing factors can be divided into five levels: the first level is the surface factors, including the economic incentive policy, operation mechanism, industrial chain, energy market mechanism, investment, and financing mechanism; the second and third levels are the intermediate factors, including generation cost, operation management, and offshore wind power technology; the fourth and fifth levels are deep-seated factors, including development planning and grid price, site selection, R&D investment, environmental protection policy, and offshore wind power supply. Deep-seated factors have a direct impact on the intermediate factors, the intermediate factors have an important impact on the surface factors, and the surface factors directly affect the development of offshore wind power industry. The influence of the 14 factors selected in this paper on offshore wind power industry is from bottom to top, from deep to shallow.

Using the extended science citation index database (SCI) and social science citation index (SSCI) databases, this paper analyzed the characteristics of publications, research foundations, research hotspots, and the evolutionary tracks of studies in the field of energy, environment, and climate change from 1990 to 2019 using a bibliometric method. This method is useful because it involves the quantitative analysis of large amounts of literature, using mathematical and statistical method. The results showed that the United States (US), the United Kingdom (UK), and China were the countries with the most published papers in the field. The US plays a key role in the cooperation between international institutions. An assessment conducted by the Intergovernmental Panel on Climate Change (IPCC) created the standard scientific reference for the research on climate change and its consequences. From 2006 to 2016, a large number of co-cited papers laid a solid foundation for research in the field. During this period, the research focused on the impact of climate change on the ecological environment, began to propose different countermeasures, and formed a set of mature research methods. From 2017 to 2019, there was an acceleration in the growth rate of the number of published articles. Strategies to address climate change, including renewable energy and energy transition, were the focus during this phase. Future studies are expected to focus on climate change mitigation strategies and energy policies. The findings provide a reference for researchers and can help policy makers balance economic development with environmental protection.

To promote the development of the green and low-carbon wood industry and explore the current status and trend of China's used-furniture recycling, this paper summarizes the research status of used-furniture recycling and interprets governmental strategies, such as the development of used-furniture recycling system, the way of handling used-furniture by manufacturers, and the attitudes of customers towards used-furniture, through extensive literature reviews and market research. From such three respects as government, furniture manufacturers, and consumers, the problems of national used-furniture recycling are analyzed, for example, imperfect system, high cost, and weak awareness. Therefore, to solve the above issues, it is necessary to construct national used-furniture recycling system and methods. The government should pay attention to the construction of recycling network, the supervision and support of entrepreneurial responsibilities, and the formulation of recycling standards. For furniture manufacturers, the improvement of the durability and recyclability of furniture and the development of new models and new technologies for furniture recycling and transportation are their primary assignment. And for consumers, the improvements of their concepts of consuming and the environmental protection are in focus. In sum, it aims to provide both suggestions for the amelioration of the measures and methods, and support for the understanding of the change, of used-furniture recycling in China.

Green total factor productivity (GTFP) improvement is an important way to achieve sustainable development, and how to improve GTFP has become the focus of attention of governments and scholars. This paper constructs a GTFP evaluation index system to characterize social, economic, ecological, cultural, and politically sustainable development, and analyzes the impact of environmental regulations on GTFP in the context of increasing innovative labor force. The results of the study are as follows: Firstly, China's GTFP continues to improve, with a decrease in low-value provinces and an increase in high-value provinces; there is an agglomeration effect of GTFP in the eastern and western regions. Secondly, under the role of innovative human capital, the threshold effect of China and the eastern and western regions is significantly positive in the first stage and insignificant in the second stage. The threshold effect of the central region is not significant in the first stage, but significantly negative in the second stage (- 11.650); the effect of environmental regulation in the eastern region is the strongest. Thirdly, the control variables in the upper period GTFP, national and eastern RD investment, level of foreign openness, local fiscal expenditure, central and western information construction, western tertiary industry development, urbanization, foreign direct investment, level of foreign openness, and local fiscal expenditure can increase GTFP. In this regard, the government should adhere to innovative talent cultivation and investment in science and technology to build a talent ecological environment for regional sustainable development, adjust environmental regulations in time to meet the demand for sustainable development to realize the GTFP regional linkage enhancement.

This paper discusses the effect of network infrastructure on environmental pollution reduction and the realization mechanism behind it. Based on the panel data of 285 cities in China from 2005 to 2019, this study regards the "Broadband China" pilot policy as a quasi-natural experiment to clarify the pollution emission reduction effect of network infrastructure construction through differences-in-differences method and other methods. The research results show the following: (1) The Broadband China pilot policy has reduced environmental pollution, that is, the construction of network infrastructure has the effect of environmental pollution reduction. The conclusion is still established after a series of robustness tests such as parallel trend test, placebo test, and instrumental variable method. Through the heterogeneity test, it is found that the pollution reduction effect of network infrastructure construction is more obvious in non-resource-based cities, first and second tier cities, and cities in the eastern region (2). The construction of network infrastructure plays a restraining role on local environmental pollution. Due to the insufficient level of regional linkage and the siphon effect of pilot cities, the spatial spillover characteristics of the pollution reduction effect are not obvious (3). The mechanism of action shows that green innovation is an important mediating effect mechanism for network infrastructure construction to reduce environmental pollution. Cities in regions with high degree of marketization and environmental regulation can strengthen the effect of network infrastructure construction on environmental pollution reduction. The research conclusions are conducive to accelerating the development of the digital economy represented by the construction of network infrastructure and provide a useful reference for promoting the level of environmental pollution reduction and achieving high-quality development.

With the advent of the Industry 4.0 era, the digital economy (DE) has become a new driver of sustainable development. This paper focuses on DE's green and environmental value. Based on the panel data of 108 cities in the Yangtze River Economic Belt from 2011 to 2019, we evaluated the temporal and spatial evolution of DE and green total factor productivity (GTFP). The spatial Durbin model analyzes the direct and spatial spillover effects of DE on GTFP, the green efficiency change (GEC), and the green technical change (GTC). The results show that the DE maintains a stable growth trend. GTFP and GTC show a similar fluctuating upward trend, while GEC shows a fluctuating downward trend. Both DE and GTFP show a clustering trend of "high in the lower reaches and low in the upper and middle reaches" and a typical center-periphery pattern over time. Second, for the direct effect, DE has a significant positive impact on GTFP, mainly on GTC rather than GEC. The promotion effect is stronger at the new normal stage, in the lower reaches, and the three major urban agglomerations. Third, for the spatial spillover effect, DE has a trickle-down effect on GTFP and GTC and a siphon effect on GEC, more potent at the new normal stage and in the lower reaches. Compared with peripheral cities, DE has significant trickle-down effects on GTFP, GTC, and GEC in the three major urban agglomerations.