Chinese Journal of Urban and Environmental Studies

With the rapid development of digital technologies based on information and communication technology (ICT), some studies suggest that the development of the digital economy is bound to have a significant impact on energy consumption. There are also studies demonstrating from different perspectives that ICT plays an important role in improving energy efficiency. Then, will the rapid development of the digital economy lead to a sharp increase in energy demand (electricity demand), thus affecting China’s socio-economic transition to green and low-carbon development? To this end, it is of great practical significance to explore the relationship between the digital economy and energy consumption from theoretical and practical perspectives. Focusing on the issue of ICT and its impacts on energy consumption, this paper clarifies the internal influencing mechanism between ICT and energy consumption. On this basis, this paper compares and analyzes the models, methods, and data in existing studies from the aspects of measurement of ICT’s direct energy consumption, empirical research on ICT and energy consumption, and discussions on rebound effects. After a brief summary, this paper identifies their shortcomings and explores future research directions.

A city’s economic structure and energy mix would change when the city is developed to accommodate more residents, visitors, and activities. This paper reviews Macao’s economic growth, energy use, and greenhouse gases (GHG) emission from 1985 to 2020. Specifically, Macao’s gross domestic product (GDP), energy use, and GHG emission have surged after the gaming industry was liberalized in 2002. The official data show that Macao’s GDP was MOP 11 billion in 1985, increased by four-fold to MOP 54 billion in 2000, and then surged rapidly to MOP 445 billion in 2019. Additionally, Macao’s total energy use increased from 8,840TJ in 1985 to 48,330TJ in 2019 while Macao’s GHG emission increased from 0.70Mt of CO₂-equivalent in 1985 to 6.13Mt of CO₂-equivalent in 2019. Macao’s GHG emission from all local sources per capita and GDP per capita exhibit an inverted U-shaped relationship, showing an environmental Kuznets curve. Due to the negative impact of COVID-19 pandemic, Macao’s GDP dropped by 56% to MOP 194 billion while its total energy use and GHG emission dropped by 33% and 17% to 32,198TJ and 5.06Mt of CO₂-equivalent, respectively, in 2020.

The Paris Agreement signed in 2015 basically established the post-2020 international climate system. The agreement no longer emphasizes the differences between countries of the North and South. It requested each country to outline and communicate their post-2020 climate actions, which were legally termed as “nationally determined contributions” (NDCs). However, in the process of negotiating the implementation rules and regulations, there is still a big divide between developing and developed countries. Thus it is important to evaluate countries’ responsibilities, obligations and capacities for addressing climate change in the post-Paris era. By adopting the Delphi method, this paper establishes a more comprehensive index system to quantitatively evaluate countries’ capacities for addressing climate change, and to further identify and determine their capacities under the Paris Agreement. According to the evaluation results, there is still a large gap between developed and developing countries in their capacities for addressing climate change. Developing countries with weak capacities fall behind mainly in terms of the industrialization process, Human Development Index (HDI) and urbanization rate. Developed countries with strong capacities lack commitments and actions in terms of helping developing countries to mitigate and adapt to climate change. This paper, by expanding the use of the Delphi method with a multi-dimensional evaluation system that includes a historical responsibility index, attempts to provide a reference for differentiating countries’ capacities and responsibilities in global climate governance, and to promote a more equitable and reasonable global climate governance system.

Along with the aggravation of climate change, various weather and climate extreme events (abbreviated as climate extremes) are becoming more frequent. During the transition to the use of clean energy, the power system will show increasingly prominent features such as high ratio of clean energy, high ratio of electrification, and a high proportion of electric and electronic equipment, coupled with summer and winter load peaks. Against this backdrop, this paper studies the impacts of climate extremes on the power system using the Texas power outage as an example, and proposes general adaptation measures to cope with climate extremes. For a start, this paper reviews the power outage in Texas caused by an extreme cold wave across the North America in 2021, and conducts an in-depth analysis of its causes. Then, based on the theoretical framework of disaster risk management, this paper analyzes the weather and climate disaster risks, extreme events, exposure, and vulnerability faced by the power system in the context of climate change and extreme events. Finally, in order to build a new power system, this paper establishes an overall framework for the power system to mitigate and adapt to climate change, and summarizes the key techniques involved in power generation, transmission, distribution, and consumption, as well as key technologies in the fields of power supply, power grid, power load, and energy storage, and the strategies and measures for addressing climate change.

This paper analyzes the development pattern of 35 megacities from 1980 to 2020 and examines the impact of megacity’s growth on the city system. We use primacy, urban concentration, Zipf’s coefficient, and entropy to characterize the city system in a country with a megacity. Our analysis finds the following: (1) The growth rates of megacities are faster than the totals of the national population and national urban population in general; (2) the growth of megacities makes the city system diverge; (3) the development of megacities tends to be companied by the shrinking of small cities; and (4) emerging megacities has substantial impacts on urbanization strategy, urban planning, and policy.

City clusters are important carriers for China’s future urbanization and vital areas for promoting coordinated regional development and common prosperity. The authors first divide the city clusters into Types I, II, and III according to the characteristics of their development stages, and measure the degree of development of city clusters by using city-level night time light (NTL) data and inter-city commuting time, and empirically identify the types of China’s city clusters. On that basis, the authors examine the influence of city cluster development on the inter-city disparity from a perspective of urban agglomeration. The results show that the development of Type I city clusters can lead to the widest inter-city disparity, and that of Type II city clusters ranks the second place in this regard, while that of Type III city clusters can narrow the inter-city disparity. Furthermore, using the 268-year historical geographic data of the Qing Dynasty, the authors construct instrumental variables to address the endogeneity issues, and find that the above conclusions are robust. This study also finds that the factor allocation for the development of Types I and II city clusters is oriented towards labor, while that for Type III city clusters is oriented towards capital. Besides, different types of city clusters vary in the extent of correcting factor misallocation for their development. The differences in the orientation of factor allocation and the extent of factor misallocation correction constitute the main mechanism for the heterogeneous influence of city cluster development on the inter-city disparity. China’s city cluster development strategy should adopt a category-based approach to avoid homogenization, conform to the objective laws, and make greater use of central cities’ spatial spillover effects.