China, which is the largest carbon emitter and the largest developing country in the world, faces the challenge of achieving energy conservation and emission reduction without sacrificing economic ...development. Improving carbon productivity consists a possible way to seek a coordination between economic development and carbon emission reduction. Therefore, it is of great significance to examine the effects of socioeconomic development on China's carbon productivity and accordingly provide policy suggestions for China's low-carbon economic development. However, this topic has not been adequately addressed in previous studies. In order to fill this gap, this study detailed an empirical investigation into the impacts of socioeconomic development on China's carbon productivity. First, aided by spatial analysis methods, a detailed analysis of the spatiotemporal patterns and dynamics of China's province-level carbon productivity was conducted. Moreover, using an extended STIRPAT model and panel data modeling technique, the effects of a range of socioeconomic factors on China's carbon productivity were quantitatively examined. The results indicated that China's carbon productivity increased gradually between 1997 and 2016, and carbon productivity in East China was much higher than that of their counterparts in Central China and West China. Provincial administrative units with highly developed economies witnessed spectacular increases in carbon productivity. Panel data analysis demonstrated that GDP per capita, technology level, trade openness, and foreign direct investment exerted positive effects, while energy consumption structure, industrial proportion, and urbanization level exerted negative effects, on China's carbon productivity. Based on the findings of this study, a series of policy suggestions with respect to improving China's carbon productivity were proposed.
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•We apply spatial analysis method and STIRPAT model to evaluate China's carbon productivity.•The impacts of socioeconomic factors on China's carbon productivity were investigated.•Evident regional imbalances exist in China's province-level carbon productivity.•GDP per capita, technology, trade openness, and FDI increase carbon productivity.•Energy mix, industrialization, and urbanization decrease carbon productivity.
Exploring the impacts of urbanization on carbon dioxide emissions is a task that is of great significance in efforts to build low-carbon cities in China. While existing literature has identified ...links between carbon dioxide emissions and urbanization, the impacts of various mechanisms in various urbanization subsystems (economic, demographic, spatial, and social urbanization) on carbon dioxide emissions remain largely unexplored. This study conducts a comprehensive assessment of the multiple effects of urbanization on carbon dioxide emissions in the Yangtze River Delta, based on city panel remote sensing and statistical data covering the years 1992 to 2013. A stepwise panel data model was applied in combination with environmental Kuznets curve theory, so as to address four aspects of urbanization. The results show that carbon dioxide emissions increased notably in the Yangtze River Delta from 141.01 million tons in 1992 to 1448.28 million tons in 2013, and Shanghai and Suzhou were the largest two emitters in region. The impacts of urbanization on carbon dioxide emissions varied with different subsystems of urbanization. Economic urbanization exerted a positive impact in relation to carbon dioxide emissions with the relation between carbon dioxide emissions and gross domestic product per capita showing a Kuznets curve association. Population urbanization has exerted two opposing effects on carbon dioxide emissions, and population density and the proportion of urban population play a negative and positive role respectively. Spatial urbanization was here positively associated with carbon dioxide emissions, a result of the effects of the construction of new infrastructures and the conversion of existing land uses. Social urbanization demonstrated negative correlations in relation to emissions, mainly by improving low-carbon awareness in the general public. The effects of social consumption were insignificant. In addition, a number of control variables were also estimated to have varied effects on carbon dioxide emissions. The different influences of urbanization must, our findings indicate be considered in the task of formulating emission reduction measures for the Yangtze River Delta. Our analysis casts new light on the importance of exploring the multiple effects of urbanization in relation to emissions, knowledge which is vital to building low-carbon cities.
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•The impacts of urbanization on CO2 emissions were explored in Yangtze River Delta.•A comprehensive index system of urbanization was established based on four aspects.•Economic urbanization and CO2 emissions confirmed a Kuznets curve relationship.•Population urbanization exerted two opposing effects on CO2 emissions.•Spatial and social urbanization were positively and negatively associated with CO2 emissions.
Following several decades of rapid economic growth, China has become the largest energy consumer and the greatest emitter of CO2 in the world. Given the complex development situation faced by ...contemporary China, Chinese policymakers now confront the dual challenge of reducing energy use while continuing to foster economic growth. This study posits that a better understanding of the relationship between economic growth, energy consumption, and CO2 emissions is necessary, in order for the Chinese government to develop the energy saving and emission reduction strategies for addressing the impacts of climate change. This paper investigates the cointegrating, temporally dynamic, and casual relationships that exist between economic growth, energy consumption, and CO2 emissions in China, using data for the period 1990–2012. The study develops a comprehensive conceptual framework in order to perform this analysis. The results of cointegration tests suggest the existence of long-run cointegrating relationship among the variables, albeit with short dynamic adjustment mechanisms, indicating that the proportion of disequilibrium errors that can be adjusted in the next period will account for only a fraction of the changes. Further, impulse response analysis (which describes the reaction of any variable as a function of time in response to external shocks) found that the impact of a shock in CO2 emissions on economic growth or energy consumption was only marginally significant. Finally, Granger casual relationships were found to exist between economic growth, energy consumption, and CO2 emissions; specifically, a bi-directional causal relationship between economic growth and energy consumption was identified, and a unidirectional causal relationship was found to exist from energy consumption to CO2 emissions. The findings have significant implications for both academics and practitioners, warning of the need to develop and implement long-term energy and economic policies in order to effectively address greenhouse effects in China, thereby setting the nation on a low-carbon growth path.
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•The nexus between economic growth, energy use and CO2 emissions for China examined.•Cointegration tests suggest presence of long-run relationship among the variables.•Generalized impulse response due to the external shocks to the system examined.•Bi-directional causality between economic growth and energy consumption.•Unidirectional causality from energy consumption to CO2 emissions.
Rapid economic growth, industrialization, and urbanization in China have led to extremely severe air pollution that causes increasing negative effects on human health, visibility, and climate change. ...However, the influence mechanisms of these anthropogenic factors on fine particulate matter (PM2.5) concentrations are poorly understood. In this study, we combined panel data and econometric methods to investigate the main anthropogenic factors that contribute to increasing PM2.5 concentrations in China at the prefecture level from 1999 to 2011. The results showed that PM2.5 concentrations and three anthropogenic factors were cointegrated. The panel Fully Modified Least Squares and panel Granger causality test results indicated that economic growth, industrialization, and urbanization increased PM2.5 concentrations in the long run. The results implied that if China persists in its current development pattern, economic growth, industrialization and urbanization will inevitably lead to increased PM2.5 emissions in the long term. Industrialization was the principal factor that affected PM2.5 concentrations for the total panel, the industry-oriented panel and the service-oriented panel. PM2.5 concentrations can be reduced at the cost of short-term economic growth and industrialization. However, reducing the urbanization level is not an efficient way to decrease PM2.5 pollutions in the short term. The findings also suggest that a rapid reduction of PM2.5 concentrations relying solely on adjusting these anthropogenic factors is difficult in a short-term for the heavily PM2.5-polluted panel. Moreover, the Chinese government will have to seek much broader policies that favor a decoupling of these coupling relationships.
•The direction and strength of the link between PM2.5 level and their drivers are analyzed.•Spatial regression and geographical detector techniques are used.•A spatial agglomeration effect was ...identified in city-level PM2.5 level.•Population density, industrial structure, industrial dust, and road density increase PM2.5 level.•Trade openness and electricity consumption have no significant effect on PM2.5 level.
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The frequent occurrence of extreme smog episodes in recent years has begun to present a serious threat to human health. In addition to pollutant emissions and meteorological conditions, fine particulate matter (PM2.5) is also influenced by socioeconomic development. Thus, identifying the potential effects of socioeconomic development on PM2.5 variations can provide insights into particulate pollution control. This study applied spatial regression and the geographical detector technique for assessing the directions and strength of association between socioeconomic factors and PM2.5 concentrations, using data collected from 945 monitoring stations in 190 Chinese cities in 2014. The results indicated that the annual average PM2.5 concentrations is 61±20μg/m3, and cites with more than 75μg/m3 were mainly located in North China, especially in Tianjin and Hebei province. We also identified a marked seasonal variation in concentrations levels, with the highest level in winter due to coal consumption, lower temperatures, and less rainfall than in summer. Monthly variations followed a “U-shaped” pattern, with a down trend from January and an inflection point in September and then an increasing trend from October. The results of spatial regression indicated that population density, industrial structure, industrial soot (dust) emissions, and road density have a significantly positive effect on PM2.5 concentrations, with a significantly negative influence exerted only by economic growth. In addition, trade openness and electricity consumption were found to have no significant impact on PM2.5 concentrations. Using the geographical detector technique, the strength of association between the five significant drivers and PM2.5 concentrations was further analyzed. We found notable differences among the variables, with industrial soot (dust) emissions playing a greater role in the PM2.5 concentrations than the other variables. These results will be helpful in understanding the dynamics and the underlying mechanisms at work in PM2.5 concentrations in China at the city level, and thereby assisting the Chinese government in employing effective strategies to tackle pollution.
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•This paper expands the EKC theory from the perspective of urbanization.•The UEKC means eco-environmental quality following a “U” trend with urbanization.•The UEKC of urban ...agglomerations is a logarithm-quadratic compound function.•The turning point of UEKC was found at an urbanization rate of 47%.
Urbanization is one of the most consequential human activities on earth. The contradictions between urbanization and the eco-environment are particularly prominent in urban agglomerations with high industrial concentrations. Based on the Environmental Kuznets Curve (EKC) theory, we propose the hypothesis of the Urbanization-EKC (UEKC), which states that in the process of urbanization, eco-environmental quality first deteriorates and then improves, following a “U” trend. Taking 19 Chinese urban agglomerations as empirical cases, this paper analyzed the multi-dimensional coupling curves between urbanization and the eco-environment. The results show that the coupling curves between urbanization and the eco-environment are heterogeneous, as a result of differences among urban agglomerations and various eco-environmental indicators. In five mega-urban agglomerations, we found that the coupled curve of urbanization and eco-environmental quality index (EQI) is a compound function containing logarithm and quadratic terms, following the “U” curve shape of “quick down, slow up”; the turning point of EQI improvement was found at an urbanization rate of 47%. The empirical results validate that the UEKC hypothesis is tenable for developed urban agglomerations. This study provides a methodological reference for researching the evolutionary relationship between urbanization and the eco-environment and provides decision support for a more harmonious development of humans and nature in China's urban agglomerations.
While urbanization has boosted the global economy, it is putting increasing pressure on air quality. Previous studies on the link between urbanization and air pollution have tended to focus on ...individual aspects of urbanization. In addition, research into the global scale has been scarce. This study constructed an urbanization index system integrating demographic, spatial, economic, and social components and divided 190 countries into 4 subpanels according to the national income levels, in order to identify the heterogeneity effects of urbanization on PM2.5 pollutants for the period 1998–2014 from a global perspective. The results of the panel regression models prove that the effect of urbanization on atmospheric contamination varied significantly across the income-based subpanels. The model analysis shows that demographic urbanization has a significant positive effect on PM2.5 concentrations in all subpanels. Spatial urbanization had exerted a negative effect on air pollution in high-income countries and a positive influence on air pollution in other countries. Social urbanization, in contrast, presented the opposite trend. Additionally, the model analysis shows that the economic urbanization in upper-middle-income and high-income groups can effectively alleviate PM2.5 pollutants. This study indicated that the level of development needs to be taken into account when government policy makers formulate targeted measures to control haze and improve air quality.
•The impacts of urbanization on PM2.5 concentrations were investigated globally.•Urbanization index was established from demographic, spatial, economic and social aspects.•Panel data of 190 countries were divided into four subsamples based on income levels.•The impact of urbanization on PM2.5 varies in different income countries.•Governments cannot ignore the development stage when improving air quality.
•The relationship between urban form and CO2 emissions is investigated.•A panel data model is used, taking the period 1990–2010.•The growth of urban areas correlates positively with CO2 ...emissions.•Increases in urban continuity has an inhibitory effect on CO2 emissions.•Increased urban shape complexity exhibits a positive influence in relation to CO2 emissions.
Urban form is increasingly being recognised by scientists for the potential role it might play in the coordination of sustainable urban development and the reduction of CO2 emissions. However, despite increasing interest in the morphology of cities in climate change science, few quantitative estimates have been made of the effects of urban form on CO2 emissions. The goal of this study is to quantify this relation, using panel data for China’s 30 provincial capital cities from 1990 to 2010. In order to meet this aim, we first selected a series of urban form indicators, which we quantified by applying spatial metrics to remotely sensed data. We then estimated CO2 emission levels using a unified standard method recommended by the IPCC Guidelines, and subsequently performed a panel data analysis. The results of the study demonstrated a positive correlation between the growth of urban areas and CO2 emission levels. Further, it was also found that increased “urban continuity” led to reductions in CO2 emissions and that, conversely, increased “urban shape complexity” exerted a positive influence in relation to CO2 emissions. The findings of this study indicate that measures to make existing cities in China more compact may in fact help to reduce levels of CO2 emissions, just as increasing fragmentation or increased irregularity with respect to urban form may contribute to increased CO2 emissions. If serious about achieving meaningful reductions in CO2 emissions, decision makers and planners should take urban form into consideration when developing low-carbon cities in China.
The existence of Pollution Haven Hypothesis (PHH) is still being hot debated due to its importance in environmental and industrial policymaking. However, research concerning the PHH in relation to ...local areas and regions within country borders is limited. Therefore, this research focused on the relationship between the migration of pollution-intensive industries (PIIs) and environmental efficiency (EE) at the prefecture level throughout China's Guangdong Province from 2001 to 2014. Firstly, this research found that many PIIs migrated from the core industrial region of the Pearl River Delta (PRD) to peripheral Non-Pearl River Delta (NPRD) areas after 2006. A Data Envelopment Analysis (DEA) model was used to evaluate industrial EE of a range of different cities. Then, analysis using PMG/ARDL regression model shows that industrial EE maintained a negative long run equilibrium relationship with PII migration in the NPRD region where PIIs have moved out, but had little correlation with PII migration in the PRD where PIIs have moved in. The results show pollution transfer caused by migration of PIIs from the PRD to the NPRD region in Guangdong Province that supports the PHH. The NPRD had become a pollution haven for PIIs in the PRD. This study proposes that policymakers should build a series of environmental regulatory policies and industrial developing policies to avoid the creation of pollution havens in the developing area in China, instead of simply pollution emission control policies.
•Impact of migration of pollution-intensive industries (PIIs) on efficiency is explored.•Pollution transfer is caused by migration of PIIs from the core region to periphery.•Economic growth, population density, and technology improve environmental efficiency.•Our results support the Pollution Haven Hypothesis in Guangdong Province.
•Two interactive coupling models were developed on urbanization and eco-environment.•We find the double-exponential curve is in the form of an inverted-U curve.•The dynamic of coordination evolved ...into a superior balance in rapid urbanization.•The coordinated patterns of most sample cities are sensitive to the eco-environment.
China's high-speed economic growth has been characterized by rapid urbanization and a series of environmental issues. This study investigates the urbanization and eco-environment system from the perspective of interactive coercing theory and proposes a new comprehensive index system for the assessment of urbanization and the eco-environment. This is done using interactive coercing model (ICM) followed by a dynamic coupling coordination degree model (DCCDM) to estimate the relationship between urbanization and the eco-environment. This study focuses on the interactive coercing relationship, coupling coordination degree and coordinated patterns in the BTH (Beijing–Tianjin–Hebei) region, China, with panel data collected from 1980 to 2011. The main conclusions are as follows: (1) demographic urbanization and eco-environmental endowment make the greatest contribution to the compound system, indicating that they are the critical factors to consider when analyzing the interactive coercing relationship between urbanization and the eco-environment; (2) we find the double-exponential curve of urbanization and the eco-environment is in the form of an inverted-U curve, and thus the Kuznets hypothesis is confirmed by the empirical analysis; and (3) the dynamic of coordination of the selected cities shows an S-shaped curve and the corresponding state of the degrees evolves into the rudimentary symbiosis phase from the harmonious development phase during rapid urbanization, and it is revealed that the coordinated patterns of most sample cities are sensitive to the eco-environment, which indicates that the urban environment is subject to great pressure. The comprehensive indexes and the interactive coupling models may help the governments better understand the complex coupling relationship, and develop sustainable urbanization development strategies that better balance urbanization and eco-environmental protection.
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