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CO2 emissions have become a topical issue worldwide, but few studies have considered the spatial effect of income on carbon emissions and explored the relationship between CO2 emissions and income by establishing direct, indirect, and total environmental Kuznets curves (EKCs). Using an annual panel dataset collected over the 1997–2017 period in China, this study first analyzed the spatiotemporal evolutionary process of CO2 emissions and subsequently developed direct, indirect, and total EKC-based spatial Durbin model (SDM) and partial derivative approach. These results indicate that, first, CO2 emissions have characteristic positive spatial autocorrelation, with gravity centers that have shifted westward. Second, the direct EKC forms a line, while the total EKC resembles a lying-S shape as well as the total EKC, which indicates that compared to local economic growth, neighboring growth plays a very different role in impacting local CO2 emissions. Furthermore, neighboring economic growth seems to have stronger impacts on local emissions, and the turning point of the total EKC comes much earlier than that of the conventional EKC due to the spillover effects of economic growth. Finally, the growth of the population, as well as the rise of energy intensity, can stimulate CO2 emissions in both local and neighboring regions. Industrialization seems to have a nonsignificant impact on emission changes due to the offsetting effects of the positive direct and negative indirect impacts of the share of secondary industry. Improvements in local urbanization may lead to an increase in emissions, while neighboring improvements may have stronger restricting effects; thus, urbanization improvement is beneficial to emissions reduction. This study provides more scientific information from both local and neighboring perspectives, which may differ from conventional results but still be beneficial for emissions reduction policy-makers to introduce corresponding measures. [ABSTRACT FROM AUTHOR]

We investigate the relationship between China's high growth and environmental pollution from the agricultural and industrial sectors by estimating the environmental Kuznets curve (EKC). We used panel data of Chinese cities at the prefecture level and above for the period between 2011 and 2015 and estimated the EKC models using the system generalized method of moments (GMM). We found that agricultural chemical oxygen demand (COD) and industrial wastewater depict N-shaped and reverse N-shaped curves. Further, an EKC for agricultural nitrogen balance has been established. We find that industrial sulfur dioxide (SO2) emissions and their emission intensity support the EKC hypothesis. Our research is then used to provide policymakers with guidance on mitigating environmental pollution by comparing and scrutinizing the characteristics of agricultural and industrial pollution in China. [ABSTRACT FROM AUTHOR]

Accompanied with the increasing complicated global value chain (GVC) networks is the carbon emission transfers among countries. Utilizing the complex network analysis alongside quadratic assignment procedure (QAP), this paper detects the community structure and influencing forces of the emission transfers under GVCs. The results imply that the bipolar structure of the network transformed gradually to tripolar owing largely to the surging of carbon emissions from China. Evidence on the existence of environmental Kuznets curve (EKC) in the emission transfers from high-income countries to low-income countries, and a U-shape relationship transfers in the reverse direction, suggesting that growing carbon emissions from both low- and high-income countries transferred to other high-income countries gradually. Gaps in technology, especially in patent applications, between source and destination countries played an important role therein. [ABSTRACT FROM AUTHOR]

Estuarine sediment quality is highly associated with anthropogenic activities in watersheds. This study attempts to couple socioeconomic patterns with estuarine sediment quality via legacy organochlorines in 14 Chinese coastal watersheds. Sedimentary concentrations of HCHs, DDTs, and PCBs showed a significant spatiality in estuary, up to 48.7 ± 15.1, 89.0 ± 46.4, and 54.5 ± 17.2 ng g−1, which were predominated by β-HCH, p,p′-DTs, and tri- to penta-PCBs, respectively. Ecological risk of organochlorines was negligible except few moderate risks for DDTs and PCBs against the first class quality of the marine sediment quality guidelines of China. Sedimentary DDT and PCB concentrations were significantly delineated by an environmental Kuznets curve model as a function of non-agricultural GDP per capita in watersheds, while HCHs by an increasing linear model. Findings of this study provide a tool to quantify the contribution of anthropogenic development in watershed to environmental change in estuary across the world. [ABSTRACT FROM AUTHOR]

Low-carbon transformation has become a key priority in China, as demonstrated in the implementation of the Carbon Peak, Carbon Neutralization policy, leading to increasing concern of environmental performance at the corporate level. This paper measures the carbon emission of 1,089 Chinese companies through the EIO-LCA-based approach. Then we examine the impacts of international crude oil price fluctuations and the corporate development level on carbon emissions of individual companies. Our results indicate that an increase in international crude oil price uncertainty could inhibit the company's carbon emission. In parallel, we find that there might exist an environmental Kuznets curve (EKC) inverted U-shaped correlation between the company's development level and its environmental performance. However, some exceptions to corporate carbon performance may emerge, resulting from specific corporate characteristics such as the state-owned nature and whether the firm is listed on the stock exchange. Our results could help companies optimize their internal carbon emission structure during the low-carbon transition process and contribute to effective policy regulations towards the target of carbon reduction. [ABSTRACT FROM AUTHOR]

China is a rising power of the twenty-first century with its brilliant economic performance as a result of the transition to the free market economy model. However, China's economic development process has caused high environmental costs. For the past decade, China has been the leading country responsible for global carbon dioxide emissions (CO2). Therefore, determining the dynamics that have a reducing effect on CO2 emissions in China is very important for the development of sustainable environmental policies. This paper aims to examine the impacts of the institutional structure on environmental sustainability in China. To this end, the study follows the method of cointegration with multiple breaks that produce robust econometric results and consider structural changes. According to the results, (i) the validity of an N-shaped EKC relationship is supported between economic growth and environmental pollution. (ii) Industrialization and trade have an increasing impact on environmental pollution. (iii) Political rights and civil liberties have a reducing effect on environmental pollution. Consequently, this study implies that political rights and civil liberties can make an important contribution to achieving sustainability goals in China. [ABSTRACT FROM AUTHOR]

With sustained economic growth, environmental pollution in China has become increasingly serious and displays certain regional differences. Therefore, it is of great significance to explore the spatiotemporal evolution characteristics of economic growth, energy consumption, and environmental pollution in China and understand the dynamic pollution mechanisms for the implementation of regional collaborative governance. Based on the theory of the environmental Kuznets curve, this paper uses panel data from 31 provinces in China from 2008 to 2018 and applies a spatial analysis model to study the correlation among economic growth, energy consumption, and the spatial distribution of environmental pollution. A spatial measurement method is adopted to study the spatial effects of economic growth and energy consumption on environmental pollution. The results show that economic growth, the energy structure, and industrial pollution in China are spatially correlated and that there are different agglomeration areas in the spatial distribution. In terms of the temporal dimension, the energy consumption effect and technological pollution effect in China led to increased environmental pollution, and changes in the structure effect indirectly improved the environmental situation. In the spatial dimension, the high‐value clusters of the structural, energy consumption, and technological pollution effects are mainly in the central and western regions of China, and the low‐value clusters are mostly in the eastern and northeastern regions of China. [ABSTRACT FROM AUTHOR]

Understanding changes in livestock production and their relationship with socio-economic and environmental impacts is important for exploring the pathways towards sustainable development goals (SDGs) of food systems. We used pig production in China as a case study to evaluate how socio-economic indicators influence pig production and nutrient losses using the environmental Kuznets curve (EKC) and Gini index. The recent acceleration in pig production is driven by an increase in average consumption of pig products per capita and government policies that support new pig production systems. The relationship between the rapid growth of worldwide pig production and its environmental impacts can be described using the EKC. The turning point in the EKC, i.e. the average income at which environmental degradation starts to decrease, is estimated to be USD 15–35 000 per capita when the pig production density is greater than 5.0 head per hectare of arable land. China's pig production has not yet reached the EKC turning point; however, given the uneven distribution of pig production systems and supply chains (feed and water) and the limited land availability for utilizing manure nutrients, the continued increasing demand for pork in China will inevitably result in continued environmental degradation. The EKC turning point should be reached earlier than the global average level, especially as environmental regulation has been reinforced since 2014. Future government policies and regulations that optimize geographical locations for sustainable pig production (i.e. better spatial planning) and support improved manure nutrient management at both regional and farm levels are required. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) formed during coal combustion is responsible for over half of the increase in the greenhouse effect, globally. It is crucial to conduct a comprehensive analysis and accurate prediction for coal production and consumption to optimize coal utilization and control emissions. However, several unstable factors inhibit the accurate forecasting of coal. Therefore, taking into account both effect and efficiency of prediction, the Hubbert model is applied in this study to forecast China's peak coal production, peak year, and future production. Additionally, a combined model, with weights determined by a flower pollination algorithm and no-negative-constraint theory, is proposed to forecast coal consumption, which is superior to that of all individual models. Subsequently, accounting for the vital effect of CO2 from coal combustion on economic issues, correlation analysis and an environmental Kuznets curve (EKC) are applied to quantitatively examine the relationship among coal consumption, economic development, and carbon emissions. The results of this estimation suggest that, compared to the US, China's economic development relies more on coal consumption; however, the EKC indicates that China has still not reached the 'inflection point'. Accordingly, it is essential for policymakers to balance the relationship among coal utilization, economic development, and the environment. [ABSTRACT FROM AUTHOR]

Highlights • The Environmental Quality Index is constructed based on dynamic data-driven methods. • Spatial Durbin Model is used to examine the environmental Kuznets curve in China. • Provincial spatial effects of environmental quality were strengthened since 2006. • Interdepartmental dependency accelerates the occurrence of the turning point of EQI. Abstract China is facing the challenge of maintaining sustainable economic growth in an environmental friendly manner. Therefore, it is of great necessity and importance to forecast the turning point of China’s environmental pollution. In this field, a frequently used empirical framework is the environmental Kuznets curve (EKC); however, the majority of the literature examining the EKC has focused on specific pollutants, which may have led to controversial estimation results because of the different characteristics of various pollutants. Therefore, in this study, a self-assessed environmental quality index (EQI) is constructed across 8 environmental factors that account for important pollutants and environmental emergencies by using the overall entropy method, and this EQI index is used to investigate the existence of EKC in China. Moreover, given that many environmental pollutants, especially air pollutants, may flow across regions, appropriate spatial econometric tools are employed to account for the potential spatial dependence of the environmental quality. Using the panel data of 30 provinces and autonomous regions for the period 2006–2015, the empirical results indicate evidence for an N-shaped relationship between the EQI and income per capita; this suggests that the overall environmental quality in China would first worsen and then gradually improve as the economy continues to grow. In addition, good governance is an important factor to accelerate the occurrence of the turning point of EKC. For policymakers, targeted policies and industrial upgrades would favor relatively underdeveloped regions and improve environmental quality. [ABSTRACT FROM AUTHOR]

Correlation between urbanization and environmental pollution is a major focus of study in geography, environmental science, and economics. Particulate matter is the primary pollutant of air pollution and made up of heavy metal, organic carbon and aromatic hydrocarbon and complicated chemicals. PM 2.5 are fine particulate matter with diameters that are less than 2.5 μm. The aim of this study on the relationship between urbanization and PM 2.5 concentration is to achieve a win-win situation of both economic development and environmental protection, which is of great significance to sustainable development in China. This paper uses PM 2.5 remote sensing data and statistical yearbook data from 2000 to 2011 to build four panel data models within the urbanization-PM 2.5 concentration Environmental Kuznets Curve (EKC) framework. The goal is to find out the correlations between PM 2.5 concentration and economic urbanization, population urbanization, and space urbanization. Furthermore, scenario simulations are set to predict when China will reach inflection point and achieve its target concentration. Results show that the relationship between economic urbanization and PM 2.5 concentration is an inverted N-shaped or inverted U-shaped curve. Most cities in East China have reached the second inflection point of inverted-N curve to step into the win-win stage while many cities in Middle China still need 10–15 years to arrive at the inflection point of the inverted-U curve. Therefore, China is under great pressure to prevent PM 2.5 pollution and pursue more targeted PM 2.5 -reduction policies for air quality improvement. [ABSTRACT FROM AUTHOR]

With China's rapid urbanization and industrialization, carbon emission in Chinese cities deserve special attention, and promoting low-carbon city (LCC) is considered essential for China. However, different cities present different development stages and carbon emission scenarios. This study presents the factors affecting carbon emission by introducing a city development-stage framework. The method of logarithmic mean Divisia index (LMDI) is adopted to decompose emission factors into energy structure, energy intensity, industrial structure, economic output and population scale. Beijing is chosen as the case city in this study, and four development stages for the city are identified by using the Environmental Kuznets Curve (EKC) theory, namely, S 1 (−1991), S 2 (1991–2004), S 3 (2004–2022) and S 4 (2022-). As the data collected for analysis are only available for the period of 1995–2014, this study focuses on the factor analysis for the stage S 2 and S 3 . The results show that the main driving factor for carbon emission increase in the stage S 2 is economic output, followed by population scale, while the main factor contributes to carbon emission reduction in this stage is the industrial structure. In the stage S 3 , the economic output is the top contributor to increase carbon emission, followed by population scale and energy structure, whereas energy intensity is the main influencing factor in curbing the carbon emission. Although the paper refers to the specific case of Beijing, the understanding on the driving emission factors in different development stages not only provides policy-makers and practitioners with valuable references for adopting effective measures to reduce carbon emission, but also provides other cities internationally with important lessons for accelerating the development of LCC. The innovative economic development stage framework incorporates carbon emission characteristics provides a new approach for understanding driving emission factors at city or national level. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to investigate the validity of the environmental Kuznets curve (EKC) hypothesis for the period between 1977 and 2013 by using the sub-elements of carbon (CO) emissions in China. To this end, the fully modified ordinary least squares and pairwise Granger causality methodologies have been employed. As a result, it is found that financial development leads to an improvement in environmental performance in China for many kinds of pollution, including the following: liquid fuel pollution, solid fuel pollution, residential buildings and commercial and public services pollution, and electricity and heat production pollution. The findings indicate that an increase in per capita consumption of energy will lead to an increase in eight different sub-elements of the carbon emissions. The highest impact is for per capita CO emissions and the lowest impact is for liquid fuel CO emissions. The findings also suggest that the EKC hypothesis is valid for CO emissions from gaseous fuel consumption, liquid fuel consumption, solid fuel consumption and transportation. However, the EKC hypothesis is not valid for aggregate CO emissions, CO emissions from residential buildings and commercial and public services, from electricity and heat production and from manufacturing industries and construction. [ABSTRACT FROM AUTHOR]

CO 2 emissions have become a topical issue worldwide, but few studies have considered the spatial effect of income on carbon emissions and explored the relationship between CO 2 emissions and income by establishing direct, indirect, and total environmental Kuznets curves (EKCs). Using an annual panel dataset collected over the 1997-2017 period in China, this study first analyzed the spatiotemporal evolutionary process of CO 2 emissions and subsequently developed direct, indirect, and total EKC-based spatial Durbin model (SDM) and partial derivative approach. These results indicate that, first, CO 2 emissions have characteristic positive spatial autocorrelation, with gravity centers that have shifted westward. Second, the direct EKC forms a line, while the total EKC resembles a lying-S shape as well as the total EKC, which indicates that compared to local economic growth, neighboring growth plays a very different role in impacting local CO 2 emissions. Furthermore, neighboring economic growth seems to have stronger impacts on local emissions, and the turning point of the total EKC comes much earlier than that of the conventional EKC due to the spillover effects of economic growth. Finally, the growth of the population, as well as the rise of energy intensity, can stimulate CO 2 emissions in both local and neighboring regions. Industrialization seems to have a nonsignificant impact on emission changes due to the offsetting effects of the positive direct and negative indirect impacts of the share of secondary industry. Improvements in local urbanization may lead to an increase in emissions, while neighboring improvements may have stronger restricting effects; thus, urbanization improvement is beneficial to emissions reduction. This study provides more scientific information from both local and neighboring perspectives, which may differ from conventional results but still be beneficial for emissions reduction policy-makers to introduce corresponding measures., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With rapid socio-economic development over the past three decades in China, adverse effects of human activities on the natural ecosystem are particularly serious in arid regions where landscape ecology is fragile due to limited water resources and considerable interannual climate variability. Data on land use, surface and ground water, climate, gross domestic product (GDP) per capita from the middle Heihe River Basin were used to (i) examine changes in water consumption, land use composition, and vegetation cover; (ii) evaluate the effectiveness of short-term management strategies for environmental protection and improvement, and (iii) apply and extend the environmental Kuznets curve (EKC) framework to describe the relationship between economic development and environmental quality in terms of the normalized difference vegetation index (NDVI). The results showed that with rapid development of agriculture and economy, land use change for the period 1986–2000 was characterized by the expansion of constructed oases, considerable contraction of oasis-desert transitional zone and natural oases. This has led to a decrease in ecosystem stability. Since 2001, effective basin management has brought about improved environment conditions, with a more optimal hierarchical structure of vegetation cover. The original EKC model could not explain most of the observed variation in NDVI ( R 2 = 0.37). Including additional climate variables, the extended EKC model to explain the observed NDVI was much improved ( R 2 = 0.78), suggesting that inclusion of biophysical factors is a necessary additional dimension in the relationship between economic development and environmental quality for arid regions with great climate variability. The relationship between GDP per capita and NDVI, with the effect of precipitation and temperature taken into consideration, was adequately described by an N-shaped curve, suggesting that the relationship between society and the environment followed a process of promotion, contradiction, and coordination. [ABSTRACT FROM AUTHOR]

Since China's central authority began enforcing the environmental target responsibility system and introduced environmental indicators to the official ranking tournament in 2007, an ecological transformation has emerged in the intergovernmental competition (IGC) among localities. Because the extant literature on the environmental Kuznets curve (EKC) remains unclear regarding how that ecological IGC transformation changes the EKC economy-pollution correlation, this research investigates the degree to which the transformed IGC changes the form of the EKC, and how that altered EKC varies for different pollutants (i.e., SO 2 and CO 2 ) and in different regions (i.e., the eastern, central, and western regions). The results demonstrate a consistently inverted U-shaped relationship between income and SO 2 emissions in all three regions, whereas when CO 2 emissions are taken as the pollution indicator, the EKC hypothesis holds only in the eastern and central cities, and a positive linear income-CO 2 nexus is found in the western region. Spatial analysis reveals that whereas the IGC flattens the inverted U-shaped curves between income and SO 2 emissions, it has led to a higher economic cost, corresponding to the turning point of the EKC for CO 2 emissions. The findings indicate that the ecological transformation of the IGC has facilitated a positive up-down yardstick competition in the strategic interactions of sustainable development across local Chinese governments, which can lead to a kind of balance between centralization and decentralization by inspiring local officials' adaptability and activity in reducing pollutant emissions and strengthening the officials' responsiveness to performance rankings. This study elucidates the environmental impacts of IGC in China and provides an institutional explanation for the strategic interactions among local governments when they are tackling the environment-economy nexus under multitask conditions.

Abstract: Release of CO2 has caused significant climate change, and agricultural land use consitutes an important carbon source as well as principal carbon sinks. This paper, by examining carbon functions of main agricultural land in China, shows that in 2000-2008 the annual growth rate of carbon emission for arable land amounted to 2.47 percent, the average annual growth of carbon sinks for forest reached 3.19 percent, and the diminishing rate of carbon sink for grassland turned to be small but quite distinct. For arable land, higher carbon emissions are mainly located in its central provinces and major agricultural provinces, while higher carbon intensity in its eastern coastal provinces. Agricultural land of 9 provinces in China was found with net carbon emissions, primarily in the agricultural provinces and ecologically fragile urban areas, whereas the other 22 provinces with net carbon sinks. The EKC tests between carbon intensity of agricultural land and agricultural output per capita illustrate a significant inverted Ucurve relationship; as for agricultural output per capita, the inflection point of 9,615 RMB yuan was surpassed by 11 provinces, mainly in eastern China, developed cities and the northeast region. Finally, policy recommendations are proposed to reduce carbon emissions of agricultural land use across China. [Copyright &y& Elsevier]

In contrast to the common dismal view of China's environment, this article highlights local and national sustainability efforts in China and examines the location characteristics of China's Eco-Communities (Shengtai Qu), communities that achieved significant sustainability per the evaluation of the Chinese government. It explores what the Chinese experience implies to the environmental Kuznets curve (EKC) concept in the context of nature-society relations and sustainability studies. The research was based on field research in eight Chinese provinces in 2001, 2004, and 2006, in addition to Chinese governmental and academic sources. At the national level, there appeared to be a positive environment-development relationship: The Eco-Communities tended to concentrate in more developed eastern China. The Eco-Communities displayed unique spatial patterns that are strikingly at odds with conventional wisdom, however. They were often found in the periphery of their provinces away from the wealthiest areas, poorer and smaller in economy and population compared to other communities in the provinces. Contrary to the EKC, the findings illustrate that communities can achieve environmental improvement along with economic growth, thus a win-win, nature-society relationship, at early stages of development. Natural resource endowments and environmental governance appear to be more important than development level in determining an area's sustainability. Environment-development research should move beyond the traditional EKC debate to better understand nature-society relations and sustainability. [ABSTRACT FROM AUTHOR]

Abstract: The relationship between economic development and environmental quality is a debated topic. Environmental Kuznets curve (EKC) is one prominent hypothesis, positing an inverted U-shaped development–environment relationship. Here we test this hypothesis using data from Shenzhen, People''s Republic of China. Established in 1980 as the first special economic zone in China, Shenzhen has developed from a small village into a large urban-industrial agglomeration with the highest income level in the country. The enormous expansion of infrastructure, industrial sites and urban settlements has profoundly changed the local environment. We utilize environmental monitoring data from Shenzhen on concentration of pollutants in ambient air, main rivers, and near-shore waters from 1989 to 2003. The results show that production-induced pollutants support EKC while consumption-induced pollutants do not support it. [Copyright &y& Elsevier]

Transportation and environmental degradation, with indirect and direct effects, play a significant role in determining the health of a nation's citizens. This study uses bootstrap ARDL with a Fourier function to examine transportation, environmental degradation, and health dynamics in the United States and China. In the long run, the results support the cointegration relationship between transportation, environmental degradation, and health in both countries. The results show the contingency of the causality where a negative impact of transportation on environmental degradation exists in the United States while a positive impact exists in China. The effect of environmental degradation on health is negative in the United States while a positive effect exists in China. Regarding the causal direction between the variables of interest, the implications provide policymakers in developing strategy and policy for sustainable development., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lin and Wu.)

• There are significant spillover effects of industrial and haze pollution in China. • The EKC for composite industrial, haze and industrial smog pollution is examined. • The heterogeneity of EKC exists among different pollutants, regions and cities. • 'PRT' 'Low-carbon city' and 'SO 2 emission trading' strike an environmental-economic balance effectively. Although an 'inverted U-shaped' economy-environment nexus is proposed in the Environmental Kuznets Curve (EKC) hypothesis, this initial configuration is considered to be too restrictive. Considering the diversified pollution, regional heterogeneity and strong government intervention in China, this article investigates EKC's heterogeneity in a panel of 290 cities from 2001 to 2018. Through the investigation of the lag effect and spatial spillover effect of pollution emissions, the heterogeneity of EKC is examined among different pollutants and different regions. Moreover, such heterogeneity pattern also exists between pilot cities and non-pilot cities of three environmental policies ('pollution rights trading (PRT)', 'low-carbon city' and 'SO 2 emission trading'). The results show that different curve shapes and turning points are associated with EKC heterogeneity. Three regulations are considered effective to strike a balance between urban emission reduction and long-term economic growth. Pollution rights' trading could contribute to the earlier 'decoupling' between urban pollution (both industrial pollution and haze pollution) and economic growth in the pilot cities significantly. The implementation of the 'low-carbon city' and 'SO 2 emission trading' are considered conducive to reducing the emissions of industrial SO 2 , with the former also resulting in fewer industrial smog emissions. The main contributions of this study are to identify both the temporal and spatial effects of pollution, develop the multidimensional analysis framework on the heterogeneity of EKC and investigate the dual effects of institutional power upon EKC as well as EKC heterogeneity. The implications, nevertheless, are considered as 1) the coordinated environment prevention and control between different regions and 2) the strict inspection of existing policy implementation by respecting each of their heterogeneous effects between regions. [ABSTRACT FROM AUTHOR]

With the increasing trend of global warming, the Chinese government faces tremendous pressure to reduce CO 2 emissions. The purpose of this study is to accurately measure CO 2 emissions at the city scale in China and examine the environmental Kuznets curve, thereby providing a reference for decision-making. Corrected NPP-VIIRS nighttime light data were used to accurately estimate carbon dioxide emissions at the provincial and city scales in China. Then, based on the STRIPAT model, 291 cities in China were used to verify the environmental Kuznets curve. Our results show that on the provincial scale, the R2 between the estimated value and the statistical value of carbon dioxide reaches 0.85. Western cities in China emit more CO 2 , as do economically developed cities and industry- and mining-dominated cities. There are two CO 2 emission hot spots in the north and one cold spot in the south. It was found that the environmental Kuznets curve on the city scale exists. This study has practical value in utilizing NPP-VIIRS data for the estimation of city CO 2 emissions. The results also have academic value for determining factors that contribute to carbon dioxide emissions and can provide a reference for relevant decision makers. This study could be considered the first to simulate CO 2 emissions at the provincial and city levels in China based on a NPP-VIIRS nighttime light model to explore the associated geographical distribution characteristics and potential influencing factors. • NPP-VIIRS data is useful when exploring the CO 2 emissions of cities in China. • Developed cities and cities dominated by industry and mining emitted more CO 2 in 2015. • The EKC hypothesis is valid, with a turning point at around CNY 73,071. • Secondary industries have a positive effect on CO 2 emissions. • Emissions are affected by Jan's average temperature, expenditure ratio of science and technology, and road density. [ABSTRACT FROM AUTHOR]

The Environmental Kuznets Curve (EKC) is an important tool to analyze the relationship between environment and per capital income. But two significant issues have been overlooked: why some points are above the EKC while others are below it? And what factors caused this phenomenon? Based on the data of 30 provinces in China over 2005–2016, this paper aimed to solve the above two questions. For the first question, we take the point on EKC as the theoretical pollution emission value of the different economic development stages; and use the difference between the theoretical pollution emission and the actual pollution emission under the same per capita income as the pollution emission efficiency. The difference value is used to reflect whether the pollution emission of the corresponding economic development stage of each region exceeds the standard and by how much. The result shows that most of the provinces with low pollution emissions concentrated in the north of the Yangtze River. Great progress has been made in China's pollution reduction work during 2015–2016. Then, for the second question, through the analysis of multiple mediating effects, we find that Environmental regulation, industrial transfer, proportion of output value of heavy pollution industry, energy consumption structure and energy using efficiency are important determinants to the pollution emission efficiency in Chinese province. [ABSTRACT FROM AUTHOR]

This paper examines the environmental Kuznets curve (EKC) relationship between energy consumption and economic growth in upper-middle-income regions of China with the panel data of 21 provinces from 2000 to 2017. The influence mechanism of socio-economic factors on the EKC of these regions is also detected. The results show that the energy consumption EKC fitting map in these regions conforms to the classical environmental Kuznets curve, which is an inverted "N" type, and the inflection point is ahead and more accurate after adding spatial effects. The direct effect of energy consumption has delayed the inflection point, indicating that the level of industrialization, urbanization, and population density have a significant impact on EKC. At the same time, it is found that the level of industrialization and population density have a positive relationship with energy consumption, while the level of urbanization has a negative correlation with energy consumption. The spatial spillover effect of the indirect effects of total energy consumption, coal consumption, and crude oil consumption shows that the level of industrialization has a significant and negative link with EKC. The increase in the level of industrialization will affect the total energy consumption of neighboring areas and the consumption of coal and crude oil., Competing Interests: The authors declare no conflicts of interest.

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world's largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China's carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status. [ABSTRACT FROM AUTHOR]

Worldwide socioeconomic development has resulted in huge irretrievable environmental problems in various ecosystems. This study employed seven coastal watersheds in two provinces, Zhejiang and Fujian, China forming a gradient to testify the environmental Kuznets curve (EKC) interactions between socioeconomic development and environmental impact at a watershed scale. Annual socioeconomic indicators, including gross domestic product (GDP) and its components, registered population (agricultural and non-agricultural population), and electricity consumption, and annual discharges of chemical oxygen demand (COD) and ammonium were collected at a county level, and land use pattern to generate watershed level dataset in the period of 2011-2016. Results indicated that non-agricultural GDP per capita of the non-agricultural population and discharge of COD or ammonium per unit of total GDP were top-ranked pair-indicators significantly fitting the EKC model instead of the classic GDP per capita and pollutants. The development of seven selected watersheds have passed the turning point of the EKC and entered impact-reducing development stages along the EKC, i.e., the three Zhejiang watersheds are at the low-impact development stage, the Huotong Stream watershed from Fujian province was at impact-declining development stage right, and other three Fujian watersheds were at medium-impact development stage. In term of the environmental impact indicator, pollutant discharge per unit of total GDP serves as a development impact indictor per se. These findings might provide an EKC-based approach to support and strategize the watershed management for sustainable development in the world.