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The adoption and ratification of relevant policies, particularly the household enrolment system metamorphosis in China, led to rising urbanization growth. As the leading developing economy, China has experienced a drastic and rapid increase in the rate of urbanization, energy use, economic growth and greenhouse gas (GHG) pollution for the past 30 years. The knowledge of the dynamic interrelationships among these trends has a plethora of implications ranging from demographic, energy, and environmental and sustainable development policies. This study analyzes the role of urbanization in decoupling GHG emissions, energy, and income in China while considering the critical contribution of energy use. As a contribution to the extant body of literature, the present research introduces a new phenomenon called “the environmental urbanization Kuznets curve” (EUKC), which shows that at the early stage of urbanization, the environment degrades however, after a threshold point the technique effects surface and environmental degradation reduces with rise in urbanization. Applying the autoregressive distributed lag model and the vector error correction model, the paper finds the presence of inverted U-shaped curve between urbanization and GHG emission of CO2, while the same hypothesis cannot be found between income and GHG emission of CO2. Energy use in all the models contributes to GHG emission of CO2. In decoupling greenhouse gas emissions, urbanization, energy, and income, articulated and well-implemented energy and urbanization policies should be considered. [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]

In the recent past Beijing has experienced rapid development. This growth has been accompanied by many problems including traffic congestion and air pollution. Understanding what stimulates urban growth is important for sustainable development in the coming years. In this paper, we first estimate a binary auto-logistic model of land use change, using physical and socioeconomic characteristics of the location and its access to major centers within the city as predictors. We find that variables determining regional access, like time distance to the city center, the Central Business District (CBD), industrial centers, employment centers, and the transportation system, significantly impact urban land conversion. By using measures of access to predict land use change we believe that we can better understand the planning implications of urban growth not only in Beijing but other rapidly developing cities. [ABSTRACT FROM AUTHOR]