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Manufacturing is both an essential pillar of China's economy and a significant source of environmental pollution, and there is an urgent need for the manufacturing industry to use green innovation to accelerate its goal of sustainable development. From the intellectual property protection (IPP) perspective, this paper uses Chinese manufacturing and its 26 sub-sectors as a sample from 2003 to 2018, examining the impact of two-way foreign direct investment (FDI) coordinated development in manufacturing green innovation capability. The empirical results suggest that two-way FDI coordinated development enhances manufacturing green innovation, and this finding still holds after endogeneity and robustness tests. Under the influence of IPP, the relationship between two-way FDI coordinated development and manufacturing green innovation capability is nonlinear. Under the influence of macroscopic, mesoscopic, and microscopic dimensions IPP, the effect of two-way FDI coordinated development on manufacturing green innovation capability is U, Steps, and N shaped respectively. This paper's findings can provide empirical evidence for the government to formulate industrial development strategies and for manufacturing enterprises to improve their green innovation capabilities to achieve sustainable development. [ABSTRACT FROM AUTHOR]

As one of the most swiftly industrializing countries in the world, China is struggling with significant challenges facing its environment, in particular in its marine ecosystems. Hence, economic activities increasingly are influencing these ecosystems, requiring their study crucial for sustainable development. Therefore, it is paramount perceiving the potential implications of economic growth and foreign direct investment (FDI) for marine health. The study aims to explore the impact of economic growth and FDI on China's marine ecosystem during 1980–2019, examining the probable intersections of economic advancement, FDI, and marine sustainability, the study used a novel nonlinear Fourier Autoregressive Distributed Lags (FARDL) approach. Notably, the paper confirms the Fishing Grounds Load Capacity Curve (FGLCC) hypothesis, demonstrating a nonlinear affiliation among income levels and maritime conditions. Moreover, the results point out that FDI initially worsens marine conditions until a certain threshold is reached, marking a pivotal change in the influence of FDI from environmental degradation to improvement. In addition, the study underscores the critical need for policies that balance economic development with Chines' marine environmental sustainability, emphasizing the importance of intended regulatory and strategic interventions. These insights are vital for enhancing marine requirements and ensuring well-being and health of future generations, providing significant implications maritime policymakers in addressing marine environmental challenges amid economic development. [Display omitted] • Analyzes China's marine sustainability from 1980 to 2019 using the Fishing Grounds Load Capacity Factor. • Proposes and tests the Fishing Grounds Load Capacity Curve hypothesis. • Evaluates marine Pollution Haven and marine Pollution Halo hypotheses. • Provides evidence for FGLCC and marine Pollution Haven based on Fourier ARDL modelling. • Offers insights into balancing economic growth and marine ecosystem preservation in China through key policy levers. [ABSTRACT FROM AUTHOR]

Abstract The huge energy intensity gaps among Chinese prefectures make the overall reduction of energy intensity extremely difficult. Energy intensity convergence (EIC), i.e., catching-up of the high energy intensity prefectures with the low ones, is imperative for narrowing these gaps. As one of the most important channels for international technology diffusion, foreign direct investment (FDI) has great impact on energy intensity and may be beneficial for the convergence. Based on pollution haven Hypothesis, however, FDI may result in energy intensity divergence. To provide an in-depth understanding of the mechanisms of FDI-induced convergence/divergence, this paper employs Markov Chain approach to examine the impact of FDI on EIC for 256 Chinese prefectures in the period from 2005 to 2014. Moreover, we particularly emphasis on the influences of local specific characteristics, such as human capital, resource endowment, and environmental regulation, on FDI-induced convergence/divergence. Our study on 256 Chinese prefectures finds that FDI helps prefectures with higher energy intensity to catch up with lower ones, which strengthens EIC. The impact of FDI on EIC varies depending on different local characteristics. Among all characteristics mentioned above, human capital and environmental regulation benefit the convergence-driving effect of FDI, while this effect is hindered by resource endowment. More comprehensive and detailed policies are recommended to address energy intensity gaps in China. Graphical abstract Image 1 Highlights • The impact of FDI on energy intensity convergence is investigated. • The Markov chain approach is employed in this paper. • The results suggest FDI strengthens energy intensity convergence in China. • Human capital and environmental regulation promote FDI-induced convergence. • FDI-induced convergence is hindered by resource endowment. [ABSTRACT FROM AUTHOR]

The international investment literature consistently indicates that enterprises, functioning as pivotal components of the economic system, engage in diversified outward foreign investment activities, thereby catalyzing the transition towards a greener and more sustainable economy and society. Based on the overseas investment data of Chinese listed companies from 2009 to 2019, this paper adopts a comprehensive approach comprising the two-way fixed effects model, propensity score matching technique, and difference-in-differences set up to evaluate the impact of the enterprise's overseas investment quantity and decision-making of host countries on green development. The findings explore that an increase in outward investment quantity facilitates the enterprise's green transition, which withstands robustness testing, including the decomposition of the green transition index, adjustments to the sample timeframe, and exclusion of corporate samples from top-tier cities. Such promoting effects are more pronounced among listed companies investing in low- and middle-income countries, as well as those located in provinces aligned with the Belt and Road Initiative in China. Further, an enterprise's overseas investment decision-making by the proposal of the BRI has exhibited a substantial and enduring enhancement of green development. This discovery underscores a pragmatic trajectory for the enterprise's green transformation, driven by proactive engagement in high-level openness. [ABSTRACT FROM AUTHOR]

High-quality economic development focuses on achieving effective qualitative improvement and reasonable quantitative growth in the economy, which is the essential way for China to achieve sustainable development. This paper aims to investigate the role of financial development in the impact of foreign direct investment on high-quality economic development. GDP and green total factor productivity are used to measure the quantity and quality of economic development, respectively. We construct benchmark panel regression models, nonlinear interaction term models, and panel threshold models to examine the threshold effect of FDI on high-quality economic development based on the scale, structure, and efficiency of financial development. A series of tests are conducted to check the robustness of the estimates. Our results show that green total factor productivity in China is primarily driven by green technology progress. Additionally, foreign direct investment has a positive impact on China's high-quality economic development, with a threshold effect and nonlinear characteristics. Specifically, the scale of financial development affects the influence of foreign direct investment on the quantity of economic development, while the efficiency of financial development affects its influence on the quality of economic development. Furthermore, the structure of financial development affects both the quantity and quality of economic development. This study presents novel findings that contribute to understanding the role of financial development in the impact of foreign direct investment on high-quality economic development. Likewise, our research has implications for achieving high-quality development. The introduction of foreign direct investment under the high-quality development of the economy should comprehensively consider financial development. • The impacts on high-quality economic development of financial development and FDI were discussed. • The scale, structure and efficiency of financial development were considered. • Both quantity and quality of economic development were focus on. • The green total factor productivity in China was measured. • Policy implications of introducing FDI in China were proposed. [ABSTRACT FROM AUTHOR]

Nowadays, countries around the world are increasingly emphasizing the green concept in their foreign investment cooperation. As an important means to guide the green development of China's economy, green credit policy may affect the overseas investment decisions of Chinese enterprises and ultimately affect the investment efficiency. Based on the overseas direct investment data of Chinese A-share listed companies from 2007 to 2019, this paper calculates the overseas investment efficiency at the enterprise level by expanded Richardson model, and further tests the influence of green credit policy on the overseas investment efficiency of Chinese enterprises. The results show that green credit policy can improve the efficiency of enterprises' overseas investment, especially for state-owned enterprises and enterprises in low environmental regulations areas. Therefore, China's financial institutions should strengthen the implementation of green credit policies and formulate differentiated credit schemes for enterprises with different characteristics under the supervision of relevant departments. The results of this paper verify the effectiveness of the green credit policy, which is very important for accelerating the green development of China's overseas investment. [ABSTRACT FROM AUTHOR]

Existing studies pay little attention to when or under which conditions foreign direct investment (FDI) can spill energy-saving technologies. From a perspective of energy-biased technical change and using a two-layer nested constant elasticity of substitution (CES) production function, this paper investigates the energy-saving spillover effect of FDI on technical change (i.e., energy-saving spillovers) in China between 2002 and 2015. In particular, we consider the conditions of marketization, industry, technology, and labor mobility to examine whether and when FDI has energy-saving spillovers. The results indicate no income inequality effect, i.e., there is no evidence supporting that FDI flowing into low- and middle-income regions increases energy consumption, while FDI flowing into high-income regions conserves energy. However, there is a condition effect: FDI can improve (support the halo effect) or deteriorate (contradict the halo effect) the environmental performance under different conditions. Moreover, there is a threshold effect: the direction of FDI spillovers varies with the different levels of the threshold variables. An increasing marketization motivates enterprises to select energy-biased technologies. It is more likely to generate energy-saving spillovers in the regions with a lower specialized agglomeration level. FDI will have energy-biased spillovers when domestic technological level is relatively high with an evident energy-biased technology. In addition, a moderate labor mobility is beneficial to the energy-saving spillovers of FDI. [ABSTRACT FROM AUTHOR]

Based on the analysis of foreign direct enterprises in China, our study developed a novel conceptual Structural Equation Model for assessing the role of environmental innovation behavior in mediating environmental regulations and performance of Chinese foreign direct investment enterprises, from the perspective of host country government and parent company. This paper performed a thorough investigation of selected foreign direct investment enterprises in China. Through the structural equation model analysis and the bootstrap mediating method, we established that innovation behavior plays a fully mediating role. Although environmental regulation and cross-border environment management have no direct effect on high-level environmental performance, environmental regulation stimulates environmental innovation behavior either directly or indirectly through the parent company. Further, our study revealed that the effect of parent company cross-border environment management is more obvious than that of local environmental regulation on environmental performance. Nevertheless, the combined effect of the two mediating variables is the highest; though, they play varied roles across the different independent variables. This study, additionally, offers crucial policy recommendations for managers, governments and key stakeholders of China towards augmenting FDI whilst embracing environmental protectionism mechanisms. [ABSTRACT FROM AUTHOR]

Abstract The imbalance and insufficiency of China's regional economic development has led to huge differences in regional energy efficiency. Reducing the differences in regional energy efficiency has become an urgent energy issue in China. The constant absorption of foreign direct investment (FDI) has brought advanced technologies to China, which has an important impact on China's energy efficiency. To explore whether FDI can reduce regional energy efficiency differences, this paper investigates the existence of energy intensity convergence while incorporating foreign direct investment (FDI). Since existing research on regional energy intensity convergence lacks of consideration of the data spatial dependence, we focus on spatial econometric model to test energy intensity convergence. We use panel data of 30 provinces in China over the period of 2005–2014 to test energy intensity convergence by β convergence model. The empirical results show that considering the spatial dependence of the data, FDI can promote the formation of conditional energy intensity convergence. Further analysis found that the spillover effect of FDI plays an important role in this formation. In addition, the convergence speed accelerates after considering the spatial dependence. Finally, the spillover effect of FDI, which is global, inhibits the declining speed of energy intensity during the research period. The scale effect of FDI and energy rebound effect plays an important role in the effect of FDI on energy intensity. These results show that guiding foreign investment more reasonably in each province in China can make contributions to the reduction of energy efficiency differences. Highlights • Use spatial econometric approach to test the convergence of energy intensity. • FDI can promote the convergence of energy intensity. • The spillover effect of FDI plays an important role in the formation of energy intensity convergence. • The effect of FDI on energy intensity has brought a rebound effect. [ABSTRACT FROM AUTHOR]

Abstract: In China many investments especially from foreign companies are located in industry parks. However, the general situation and management perspectives of developing Chinese industrial parks are not very clear to the westerners. With the rapid development, industrial parks will play a key role in China''s economy, therefore, those issues relating with China''s industrial parks need to be further discussed. This paper is one of such efforts. It will review the development of China''s industrial parks, including characterizing industry parks in China and discussing the main site selection criteria and important aspects for foreign investors. The main focus of this paper is to discuss the current environmental management practices of industrial parks because such parks have been main sources of pollution. New development strategy for industrial parks, such as eco-industrial development, should be considered and implemented. [Copyright &y& Elsevier]

This paper provides a pioneering study of the interactive relationship between shadow economy and environmental pollution by applying the data of the 31 provinces in China from 2005 to 2015. Side effects of shadow economy including environment pollution have been proved by plenty of articles, yet still have not attracted enough public attentions. If the severe pollution will in turn further increase the size of the shadow economy, then the environmental situation in the present will lead to an even worse unhealthy economy growth path. This paper firstly adopts MIMIC (Multiple Indicators Multiple Causes) method to calculate the size of shadow economy, then uses the Generalized Method of Moments (GMM) specification to analyze the interplay between shadow economy and pollution in association with environmental regulation, economic growth, foreign direct investment and educational level. The results show that shadow economy and pollution do have a positive interaction between each other, statistically significant at 1% level. Also, both pollution and shadow economy have a U-shaped non-linear relationship with environmental regulation, but an inverse U-shaped non-linear relationship with economic growth. Finally, foreign direct investment (FDI) and education level have positive linear impacts on both pollution and shadow economy, too. But the effect from FDI is weak and less significant. Image 1 • The percentage of shadow economy on GDP is calculated based on MIMIC model. • The possible interaction relationship between shadow economy and pollution is explored. • Environmental regulation and economic growth have non-linear effect on both shadow economy and pollution. • FDI and education level have linear effect on both shadow economy and pollution. [ABSTRACT FROM AUTHOR]

Analyzing the influencing factors of environmental pollution is of utmost significance for formulating pollution control strategies. However, the extant research did not take into consideration the spatial effects, which may result in an insufficient understanding of the results. To explore the spatial agglomeration of environmental pollution, the externalities of economic units are integrated into environmental pollution research. Using a panel data from 2005 to 2017 of 30 Chinese provinces, this paper quantitatively analyzed the main driving factors affecting environmental pollution by utilizing the spatial Durbin model (SDM). To better test the marginal effects from the spatial dependence, the influence of each contributing factor is further decomposed. The main results are as follows: (1) The quartile maps of China's environmental pollution show obvious characteristics of spatial disparity and clustering. (2) Owing to the correlation and similarity between economic units, China's environmental pollution shows a steady spatial agglomeration effect among regions. (3) Analysis of the SDM indicates that per capita GDP, technology, urbanization, and population exert different influences on environmental pollution. Moreover, the impacts of urbanization and foreign direct investment on environmental pollution vary essentially among regions, and one change in the abovementioned variables will not only exert influence on environmental pollution in one region but also extend its spatial effects in neighboring regions through a spatial transmission mechanism. Also, an inverted U-shaped nexus is also supported for environmental pollution accordingly. According to the empirical results of this paper, several major policy implications are proposed. [ABSTRACT FROM AUTHOR]

A growing literature on the pollution haven hypothesis has surged for decades. In this paper, we employ a city-level data set of 150 Chinese cities in 2014, and take spatial spillovers into account by using spatial econometric models, to investigate whether foreign capital inflows drive environmental degradation in China. The results suggest that foreign direct investment is negatively related to air pollution in China, indicating evidence of pollution halo hypothesis. Moreover, foreign direct investment has significant spatial technological spillovers, improving air quality in China. This study also finds that there is no evidence of an inverted U-shaped curve between income and air pollution. As income levels increase, air quality continues to worsen. The development of the tertiary industry is found to have a positive effect on air pollution. Densely populated cities tend to demand for better environmental quality. From the above analysis, it follows that policies handles are urgently needed to improve air quality in China. [ABSTRACT FROM AUTHOR]

This paper mainly investigates how 2008's Beijing Olympic Games affects environmental efficiency of China's cities. First, we evaluate environmental efficiency through metafrontier directional distance function (DDF), and compare environmental efficiency in different region from static and dynamic perspectives. We also analyze the different treatment of before Olympic Games, during Olympic Games, after Olympic Games on different groups. We find that TGR in the east is the highest, which indicates that environmental production technology in the east has relatively less difference than other three regions. During Olympic Games positively affected environmental efficiency in Beijing, which negatively affected on environmental efficiency under metafrontier in neighbor cities. After Olympic Games positively affected environmental efficiency in Beijing and co-host cities, however, which has insignificant effect on environmental efficiency in neighbor cities. We try to propose some policy implication. First, it is import to develop high-end industry and lengthen value chain of China's secondary industry. Furthermore, it is necessary to improve environmental threshold of FDI and attract clean FDI, which can decrease environmental pollution. Last, China will host 2022 Winter Olympic Games. It is important to use more environmental-soundly building material, and increase clean renewable energy public bus, which can promote green Olympic Games. [ABSTRACT FROM AUTHOR]

This paper examines the spatial impacts of foreign direct investment (FDI) on sulfur dioxide (SO 2 ) emissions in the Beijing-Tianjin-Hebei region located in northern China. To avoid making coefficient estimation errors, we use spatial panel data on 10 cities in the Beijing-Tianjin-Hebei region for 2000 to 2013. We first analyze the effects of FDI on air pollution levels in the Beijing-Tianjin-Hebei region from ordinary least squares (OLS). Then, the existence of a spatial correlation is examined via a Lagrange Multiplier (LM) test, and the Spatial Durbin Model (SDM) is adopted to investigate the influence of FDI on SO 2 emissions in this region. The results show that FDI has a significantly positive impact on SO 2 emissions, suggesting that an increase in FDI inflows would increase air pollution levels in the Beijing-Tianjin-Hebei region. Furthermore, the air quality of local cities is also influenced by FDI inflows in surrounding areas. [ABSTRACT FROM AUTHOR]

The shadow prices, or marginal abatement cost, of pollutants is a useful measure of environmental performance. Unlike much of the previous studies focusing on only one kind of pollutants, this paper applies the (multiplier) by-production approach to measure the shadow prices of carbon emission, sulfur emission, and dust. The case of regional economies in China is considered. As the foreign direct investment may have an impact on the environmental performance, a spatial Durbin model is utilized to identify the impact of foreign direct investment on the shadow prices of pollutants. The results show that the shadow prices of all three pollutants have been increasing over time which indicates the environmental performance of China has been improving. Moreover, the spatial regression results imply that both foreign direct investment and technology export volume positively impact the shadow price of pollutant emissions across the provinces of China. [Display omitted] • Shadow prices of three pollutants are calculated. • We explore the factors affecting shadow prices of bads in China. • FDI has a positive effect on environmental performance. • The environmental performance of China was improving. [ABSTRACT FROM AUTHOR]

Renewable energy is particularly important for achieving energy security and emission reduction targets. However, China's renewable energy technologies are still diffusing slowly. Based on the two-part model and the fixed-effect Tobit model, this paper investigates the factors affecting the diffusion of renewable energy technologies in 28 provinces in China between 2006 and 2017 from the perspective of an innovation system. It is found that increasing the renewable energy tariff surcharge subsidy, the share of relevant employees, and grid density will drive the diffusion of renewable energy technologies. Reducing the share of coal consumption will increase the probability of adoption of renewable energy technologies. Furthermore, a certain province's or other provinces' renewable energy technology patent stocks both provide the knowledge infrastructure for the increase in the share of renewable energy generation. In contrast, the crowding-out effect of foreign direct investment will hinder the expansion of renewable energy generation share. Therefore, the failures in the six aspects of institutional design, market structure, personnel factor, external interaction, knowledge infrastructure, and physical infrastructure, will lead to the slow diffusion of renewable energy technologies. • China's renewable energy technologies are still diffusing slowly. • The factors affecting the DRET from the perspective of innovation system. • This paper selects multiple indicators to measure DRET. • Failures in innovation system will lead to the slow DRET. [ABSTRACT FROM AUTHOR]

Using panel threshold model and data of 30 provinces in China from 2004 to 2015, this paper empirically tests the impact of outward foreign direct investment (OFDI) on provincial industrial wastewater discharge and sulfur dioxide (SO 2) emissions and its threshold effect. The results show that, with increase in the stock of OFDI, the discharge of industrial wastewater and industrial SO 2 emissions in all provinces are significantly reduced. OFDI stock increases by 1% whereas industrial wastewater discharge and industrial SO 2 emissions will be decreased by 4.3% and 7.76%, respectively. We conducts a threshold test on the impact of OFDI on environmental pollution and finds that there is a single threshold for the impact of OFDI on provincial industrial wastewater discharge and industrial SO 2 emissions. When the scale of OFDI exceeds the corresponding threshold value, with the increase of OFDI, enterprise will adopt clean technologies to decrease industrial wastewater discharge and industrial SO 2 emissions. Provincial environmental pollution will be significantly reduced. Conversely, if the scale of OFDI is below the threshold value, the impact of OFDI on provincial industrial wastewater discharge and industrial SO 2 emissions is not significant. Finally, the paper proposes policy recommendations to expand OFDI scale and reduce domestic environmental pollution. Image 10052 • The mechanism of the effect of OFDI on home country's environmental pollution is studied. • Panel threshold model is used to test the impact of OFDI on industrial wastewater discharge and SO 2 emissions. • OFDI reduces home country's environmental pollution only when the scale of OFDI exceeds the threshold value. • The increase of energy consumption has deteriorated environmental quality. • The increase of urbanization rate has reduced environmental pollution. [ABSTRACT FROM AUTHOR]

Improving the efficiency and productivity of the water supply sector is related to the mitigation of a country's water resources crisis and the governance of the water ecological environment. This paper employs a sequential data envelopment analysis (DEA) approach to examine the comparative efficiency of China's urban water industry by using the country-level data from 1998 to 2017, and then attempts to make a cross-country comparison of the technology gap in the urban water industry between China and major OECD countries. The results show that China's urban water sector performance is improving despite falling short of urban water development in the major OECD. The gap between the performance of China's urban water sector and that of major OECD countries is narrowing. Efficiency improvement has become the main driver of productivity growth of urban water sector in both China and the major OECD countries. Besides, the reduction of capital deepening in the water industry and the easing of water stress could improve the water industry's performance in efficiency. While increased foreign direct investment instead reduces the water industry's efficiency, increased R&D expenditure can improve efficiency, but both are not statistically significant. These findings indicate that compared to major OECD countries, China's urban water industry should strengthen the reform change as soon as possible from asset-heavy to asset-light operation and service, and then improve the water conservation system. [ABSTRACT FROM AUTHOR]

In this paper, a model for the slacks-based measure of super-efficiency in data envelopment analysis (SBM-DEA) was used to measure the green innovation efficiency (GIE) of 79 cities in the Yellow River Basin (YRB) from 2003 to 2018. In addition, the panel threshold model was employed to test the nonlinear relationship between environmental regulation intensity (ERI) and GIE. According to the results, the average GIE in the YRB was 0.68. However, the GIE exhibited a rising and fluctuating temporal trend and the following spatial trend: "lower reaches > upper reaches > middle reaches." Moreover, ERI had a double threshold effect on GIE in the YRB. That is, ERI had a significant positive impact on GIE only when ERI ranged between 0.595 and 0.899. Furthermore, the upper, middle, and lower reaches of the YRB exhibited different nonlinear correlations between ERI and GIE. Therefore, it is essential to implement environmental regulations that are appropriate for the actual conditions of each region. In addition, the per capita income, teacher resources, industrial structure, and actual utilization of foreign capital are significant factors affecting GIE in the YRB. These findings can help governments formulate suitable environmental policies and promote green innovation in the YRB, thereby contributing toward the goal of global sustainable development. • The efficiency of green innovation in the Yellow River Basin increases. • The efficiency of green innovation shows a spatial pattern of "lower reaches > upper reaches > middle reaches". • Regulations have a double threshold effect on the efficiency of green innovation. • The efficiency of green innovation must be improved based on the actual development of each region. [ABSTRACT FROM AUTHOR]

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment. Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. [Display omitted] • Energy efficiency has spatial positive correlation and agglomeration characteristics. • Energy consumption structure mainly affects energy efficiency. • Environment Kuznets Curve exists in China. • "Pollution paradise hypothesis" exists in foreign direct investment. • Environmental pollution is transferred to surrounding provinces through resource trades. [ABSTRACT FROM AUTHOR]

In the social context of mitigating climate change and achieving carbon neutrality, the improvement of carbon emissions efficiency and the protection of biological carbon sequestration have emerged as hot topics recently due to their prospects in carbon dioxide emissions reductions. A large volume of studies has identified the spatial distribution characteristics and influencing factors of carbon emissions efficiency. The contributions of our study lied in constructing a system to measure net carbon sink efficiency. Secondly, this study discussed the carbon neutrality performance of Chinese cities from three different aspects of carbon dioxide emissions, carbon sequestration of vegetation and net carbon sink efficiency. Thirdly, this paper identified the influencing factors of net carbon sink efficiency, and examined the direct and indirect effect of different factors. For this purpose, we evaluated the net carbon sink efficiency of 285 cities in China from 2012 to 2017 using a slacks-based measure model, and explored its spatial distribution characteristics, then employed a spatial Durbin model to explore the influencing factors of net carbon sink efficiency. Our main findings indicate that the net carbon sink efficiency steadily increased during the study period, whereas their spatial characteristics were "high at both ends and low in the middle" from the south to the north. There is a significant spatial autocorrelation in the net carbon sink efficiency of Chinese cities. Several kinds of measures can be applied to promote net carbon sink efficiency, such as increasing the proportion of tertiary industry, promoting economic growth, attracting foreign direct investment, increasing road area, promoting technological progress and strengthening environmental regulation. However, the increase of urban population may decrease efficiency. Nevertheless, an obvious spatial spillover effect exists in the net carbon sink efficiency of Chinese cities. The results can provide policy recommendations for the government to formulate differentiated carbon neutralization policies. [Display omitted] • The carbon sequestration is considered to calculate net carbon sink efficiency (NCSE). • The NCSE is used to discuss the carbon neutral performance of Chinese cities. • Chinese NCSE steadily increased and showed significant spatial autocorrelation. • Spatial Durbin model was adopted to study the influencing factors of NCSE. [ABSTRACT FROM AUTHOR]

In the early stages of China's economic development, the ecological and environmental problems left over from the extensive approach were gradually exposed. Urban environmental problems such as haze attack and water pollution not only related to residents' happiness, but also challenged urban economic structural transformation and sustainable development. Based on the panel data of 211 cities in China from 2007 to 2016, this paper uses the entropy weight method to construct the evaluation index of urban living environment, and empirically analyzes the impact of improving living environment on urban innovation. The results show that for each 1% improvement in the urban living environment, the urban innovation raises by 34.5835; there is an inverted-U relationship between the two. In the analysis of the transmission mechanism, each 1% increase in the concentration of high-quality innovative talents will raise the urban innovation by 4.6548; and each 1% increase in foreign direct investment (FDI) spillover effect will reduce the urban innovation by 0.6498. The results of the geographic weighted regression (GWR) model show that the urban living environment, high-quality innovative talents gathering, and FDI spillover effect have obvious spatial differences in urban innovation. In short, this paper provides innovative inspiration for governments and enterprises to balance ecological environmental protection and sustainable urban development. Image 1 • The improvement of urban living environment can significantly promote urban innovation. There is an inverted "U" relationship between the two. • The high-quality innovative talents gathering promotes urban innovation;FDI spillover effect cannot. • Spatial differences in the impact of the three on urban innovation. [ABSTRACT FROM AUTHOR]

China's accelerating urbanization has intensified the contradiction between city development and atmospheric environment. Fine particulate matter (PM 2.5), as the primary form of air pollution, seriously threatens human health, and negatively impacts atmospheric visibility and the climate. As its study area, this paper takes China's Yangtze River Economic Belt (YREB), which comprises three crucial urban agglomerations and has suffered frequent severe haze episodes in recent years. To achieve the coordinated development of urbanization and air quality in YREB, it is of practical significance to research the effect of urbanization on PM 2.5 concentrations. Using a prefecture-level panel dataset of YREB over the period 2003–2014, this paper adopts spatial econometric techniques to investigate the spatial dependence pattern of PM 2.5 concentrations and analyze the effects of population urbanization, land urbanization, and economic urbanization on PM 2.5 concentrations in YREB both empirically and theoretically. Results indicate that PM 2.5 concentrations in YREB exhibit obvious global positive spatial autocorrelation, and, from the local perspective, high-high clustering regions expand from the lower reaches of YREB to the middle reaches. There is no significant U-shaped, N-shaped, inverted U-shaped, or inverted N-shaped relationship between economic urbanization and PM 2.5 concentrations in YREB, but an incremental linear linkage exists. Population urbanization exerts a significant and positive effect on PM 2.5 concentrations in YREB, while land urbanization shows a negative but insignificant influence. By contrast, population urbanization is a more important influencing factor on PM 2.5 concentrations in YREB than is land urbanization. In addition, the empirical evidence denotes that the population scale and secondary industry have promoting effects on PM 2.5 concentrations, whereas foreign direct investment has an inhibitory impact, and technology level shows no significant influence. • PM 2.5 concentrations in YREB showed global positive spatial autocorrelation. • Spatial autocorrelation of PM 2.5 concentrations in some regions varied dynamically. • Economic urbanization and population urbanization aggravated PM 2.5 pollution in YREB. • Population urbanization was a more important affecting factor than land urbanization. • Mechanisms by which urbanization affected PM 2.5 concentrations in YREB were analyzed. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the effects of environmental policy on environmental conditions resulting from China''s accession to the WTO. We estimate environmental technological efficiency under both weak and strong disposability assumptions and use the difference to calculate the pollution abatement cost (PAC). We then undertake Tobit regression analysis on several explanatory variables, including dummies for different time periods and regions. Generally, our findings show that China''s accession to the WTO did not guarantee better environmental conditions even though China adopted stronger regulations to meet the higher standards. In particular, the eastern region does not seem to be strictly regulated. These interesting results may be partly attributable to China''s need to attract foreign investment and may represent a case in which institutional regulations are not always effective in practice. [Copyright &y& Elsevier]

Research on the influence of spatial correlation network structures on low-carbon innovation can inform policymaking in the construction of cross-regional collaboration mechanisms for low-carbon innovation. Based on the data of provincial manufacturing patent applications in China from 2004 to 2017, the primary objective of the proposed approach of social network analysis (SNA) is to empirically investigate the structural characteristics of the spatial correlation network and influencing factors. The process for the method is as follows. (1) The spatial metric (specifically, the European distance) is used to measure the similarity between provinces, and SNA is used to construct the spatial correlation network. The minimum spanning tree (MST) method is applied to verify the effectiveness of the construction method, and (2) the characteristics of the spatial correlation network and influencing factors are analyzed by the quadratic assignment procedure (QAP). The results show the following: (1) China's low-carbon innovation exhibits a network structure of spatial correlation, and the spatial correlation network density among thirty provinces in China is as high as 0.3483; (2) spatial spillover effects decrease gradually from China's eastern provinces to the western provinces, and the western and central undeveloped manufacturing provinces mainly receive spillovers from the eastern and central manufacturing provinces; (3) the significant value of the degree of openness is 0.001, indicating that it is the primary influencing factor of the spatial correlation network of China's low-carbon innovation (the correlation degree of the obtained spatial network significantly increases as the differences in the degree of openness decrease), and the difference of foreign capital utilization and the difference in the degree of openness show a positive correlation. The major focus/achievement described in the paper is that China's manufacturing exhibit significant characteristics of regional agglomeration and central developed manufacturing provinces, and several eastern provinces exert the primary spatial spillover effect, showing disequilibrium between the eastern and western regions overall. The degree of openness is the main factor that affects the correlation network. This study provides an opportunity for the construction of a cross-regional collaborative mechanism and green innovative development of the spatial correlation network. [ABSTRACT FROM AUTHOR]

Using panel data from 2003 to 2016, this paper estimates the green development efficiency of 34 cities in Northeast China based on the SBM-DEA model and determines whether industrial agglomeration promotes or impedes green development efficiency. The results show the following: (1) The average green development efficiency of Northeast China exhibits a fluctuant upward trend in 2003–2016, and there are significant spatial differences. (2) During the revitalization period, industrial agglomeration hinders green development efficiency. A U-shaped relationship exists between industrial agglomeration and green development. (3) Economic development level and foreign direct investment are positively related to green development efficiency, while industrial structure, energy consumption structure and environmental regulation are negatively related. Economic development level has the greatest positive influence and environmental regulation the strongest negative influence on green development. Several corresponding policy implications are proposed for promoting green development and revitalization. • The average green development efficiency of Northeast China exhibits a fluctuant upward trend. • Significant spatial differences exist in the green development efficiency in Northeast China. • A U-shaped relationship exists between industrial agglomeration and green development. • Economic development has the greatest positive effect on the green development. • Environmental regulation has the strongest negative influence on green development. [ABSTRACT FROM AUTHOR]