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Promoting urban green growth necessitates a dual focus on reducing carbon emissions and fostering high-quality development. However, the body of research on the coupling relationship between high-quality urban development and carbon emissions remains remarkably limited. Taking Guangdong province as an example, this study strived to establish a comprehensive evaluation system for high-quality urban development encompassing economic, societal, and ecological dimensions and further conducted an in-depth examination of the spatiotemporal pattern and driving forces of coupling coordination degree between high-quality urban development and carbon emission intensity during 2000–2017. The coupling coordination degree in Guangdong province has shown continuous growth, transitioning from moderate incoordination to moderate coordination. The coupling coordination degree showed the overall spatial distribution characteristics of "high in southeast and low in others", with Zhuhai, Zhongshan, Foshan, Guangzhou, Dongguan, and Shenzhen as the core. Notably, technological advancement, environmental governance, and economic development emerge as pivotal factors that positively affect carbon emission intensity reduction, environmental quality improvement, and coupling coordination enhancement. This research provides valuable insights for achieving harmonized high-quality development in Guangdong province involving policies of regional differences, industrial competitiveness, and new-type urbanization. [ABSTRACT FROM AUTHOR]

The digital economy plays an important role in the high-quality development of cities, and low-carbon urban development is an integral part of this evolution. Therefore, it is important to explore the impact of the development of the digital economy on urban carbon emissions. By considering 21 cities in Guangdong Province as the object of the research, this study measured the levels of the digital economy from 2011 to 2019 by using an entropy weight-based TOPSIS model, analyzed the spatiotemporal changes, and used geographically and temporally weighted regression to examine the spatiotemporal heterogeneity of the impact of the digital economy on urban carbon emissions. The results showed the following: (1) The development of the digital economy in Guangdong Province in general exhibited a stable trend of growth, and the average level of its development in the 21 cities considered increased by 3.4 times during the study period. (2) The level of development of the digital economy in the Pearl River Delta was significantly higher than that in northern, western, and eastern Guangdong, with Shenzhen being the most developed city in this regard (0.8473), and Shanwei being the least developed (0.0633). (3) The impact of the development of the digital economy on carbon emissions had significant spatiotemporal heterogeneity. The benefits of the development of the digital economy in terms of a reduction in carbon emissions was the most significant in the Pearl River Delta, and regional differences were prominent. (4) The reductions in carbon emissions in cities with a highly developed digital economy were more significant than has been reported in past studies in the area. However, it had a negative effect on the urban carbon emissions in cities with a poorly developed digital economy. The results of this study can be used to guide policies related to the high-quality development of the urban digital economy. [ABSTRACT FROM AUTHOR]

Development zones constitute a special type of place‐based policy that has been implemented worldwide. As an essential economic development engine, Chinese National Economic and Technological Development Zones (NETDZs) are perceived as a successful example. However, few studies have looked into the channel effects at work in development zones concerning industrialization and urbanization, despite the crucial nature of such effects with regard to sustainable development of development zones. Following a brief description of NETDZs and their theoretical mechanisms with urban economic performance, industrialization, and urbanization, this study used a simultaneous equation model to generate empirical evidence of the impact of the establishment of NETDZs on urban economic performance and its channel effects through industrialization and urbanization. The results confirm that NETDZs exerts a positive and significant impact on urban economic performance, and NETDZs also show indirect influence in urban growth through urbanization. Although significant and positive intermediation of industrialization remains invalid, foreign direct investment and investment in fixed assets are still crucial in Chinese industrialization. Both industrialization and urbanization play an important role in Chinese urban economic development. Meanwhile, compared with eastern regions more influenced by urbanization, industrialization still acts as a major impetus in inland China. [ABSTRACT FROM AUTHOR]

As a result of global climate change and urban development, the interaction between urban form and carbon emissions has become a frontier issue and a key area of carbon emission research. This paper presents a scientometric analysis of 2439 academic publications between 2002 and 2021 on urban form and carbon emissions to explore the current state of global research and future development potential. Citespace and VOSviewer were the primary analysis tools. The results showed the following: (1) The number of articles published on urban form and carbon emission research shows an increasing trend, especially after 2012. (2) Scientific research institutions and authors in developed countries paid attention sooner to the urban ecological environment. With the deepening of economic globalization, developing countries began to pay more attention to the urban environment. (3) Through an analysis of keyword clusters, timelines, and stacked area charts, the development of the urban form and carbon emissions can be divided into the following three stages. The first is the budding stage, which is characterized by preliminary research on the atmospheric environmental impact factors. The second stage is the development stage, with urban areas becoming the leading research object of carbon theory. The third stage is the mature stage, which is characterized by an emphasis on the optimization of carbon emissions. (4) Finally, the influence of urban form on carbon emissions includes four main aspects: land use, built environment, transportation networks, and development patterns. [ABSTRACT FROM AUTHOR]

The urban form (e.g., city size, shape, scale, density, etc.) can impact the air quality and public health. However, few studies have been conducted to assess the relationship between the urban form and PM2.5 concentrations on a regional scale and long-term basis in China. In this study, we explored the impact of the urban form on the PM2.5 concentrations in four different regions (i.e., northeast, central, east, western) across China for the years 2000, 2005, 2010, and 2015. Five landscape metrics were classified into three characteristics of the urban form (compactness, shape complexity, and urban expansion) using high-resolution remote-sensing data. With considerations given to regional differences, panel-data models and city-level panel data were used to calculate the impact of the urban form on the PM2.5 concentrations. The results of the study indicate that urban expansion is positively correlated with the PM2.5 concentrations across China, with the only exception being the country's western region, which suggests that urban extension is conducive to increasing the PM2.5 levels in relatively developed regions. Meanwhile, the positive relationship between the irregularity of cities and the PM2.5 concentrations indicates that reducing the urban shape complexity will help to mitigate PM2.5 pollution. Moreover, urban compactness, which mainly refers to the landscape-division-index values, proved to have a negative effect on the PM2.5 concentrations, suggesting that the optimization of urban spatial compactness could reduce PM2.5 levels. The findings of this study are beneficial for a better understanding of the intensity and direction of the effect of the urban form on PM2.5 concentrations. [ABSTRACT FROM AUTHOR]

Abstract The improvement of CO 2 emission efficiency is of great significance to realizing energy-saving and emission reduction targets and achieving low-carbon development. While it is increasingly recognized that urban form could significantly influence the CO 2 emissions of urban areas, few studies have been able to quantify the implications of urban form in relation to CO 2 emission efficiency. The purpose of this paper is thus to contribute to existing literature by empirically quantifying how urban form influences CO 2 emission efficiency. CO 2 emission efficiency in this study is presented in terms of CO 2 economic efficiency (CEE) and CO 2 social efficiency (CSE). Firstly, we calculated the CEE and CSE of nine cities in the Pearl River Delta (Guangzhou, Shenzhen, Zhuhai, Foshan, Jiangmen, Zhaoqing, Huizhou, Dongguan, and Zhongshan) using locally important socioeconomic variables over the period 1990–2013. Then, seven landscape metrics were selected in order to quantify three dimensions of urban form (extension, irregularity, and compactness) using remote sensing data. Finally, panel data models were utilized to estimate the associations between urban form and CO 2 emission efficiency. We identified a negative correlation between urban sprawl and CEE as well as CSE, a finding that indicates that urban growth decreases CO 2 economic efficiency. Further, increasing irregularity in the form of cities was found to decrease both CEE and CSE—a larger degree of irregularity, in other words, results in lower CO 2 emission efficiency. Conversely, urban compactness was identified as having a significant positive influence on both CEE and CSE, indicating that the compact development of cities can actually help to improve CO 2 emission efficiency. The findings of this study hold important implications for building low-carbon cities in China. Highlights • The impact of urban form on CO 2 emission efficiency is investigated. • Panel data models are utilized, taking the period 1990–2013. • Increases in urban area bring about inhibitory effects on CO 2 emission efficiency. • Urban shape irregularity correlates negatively with CO 2 emission efficiency. • Building more concentrated cities will help to improve CO 2 emission efficiency. [ABSTRACT FROM AUTHOR]

The development zone has been considered the engine of China's urban development in recent decades. However, the prosperity of development zones has also brought many land use problems. Given the lack of high-resolution time-series land-use data, the impact of development zone construction on urban land use has not been adequately addressed within the existing literature. Employing new annual high-resolution satellite data, this article for the first time quantifies the impact of development zones on the expansion of urban areas and on changes in land-use intensity across China, identifying spatial and temporal differences in their impact using Propensity Score Matching with a Difference-in-Difference (PSM-DID) model. Using panel data for 235 Chinese cities from 1990 to 2015, we found that establishing development zones increased the expansion of urban areas and reduced the urban land-use intensity in the short term (usually 2 years). From spatial perspectives, the impact of development zones on land use displayed spatial heterogeneity. Finally, we put forward policy suggestions to improve the land use intensity of development zones in the context of sustainable development. • Construct an analytical framework for the impact of DZs on the urban land use. • Quantify the impact of DZs on the scale and intensity of urban land use in China. • The establishment of DZs has a significant short-term impact on urban land use. • Significant differences exist in the impact of DZs on urban land use in different regions. • Proposes the policy recommendations for the improvement of DZs land-use intensity. [ABSTRACT FROM AUTHOR]

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With rapid urban development in China in the last two decades, the three-dimensional (3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area (two-dimensional (2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System (GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes. [ABSTRACT FROM AUTHOR]

While the existing literature has investigated the influence of high-speed rail (HSR) on urban economic outcomes, relatively little is known about the influence of HSR on urban land expansion mainly due to the lack of long-term and high-resolution urban land use data. Taking an example of Chinese cities which have made tremendous progress in the construction of HSR during the last decade, this study empirically documents the impact of HSR on urban land growth of Chinese cities by using a panel dataset containing annual 30-m resolution impervious surface data and socioeconomic variables from 2003 to 2015. The influence of HSR on urban land use is estimated by combining the approaches of propensity score matching and difference-in-difference analysis. Our empirical findings indicate that HSR has a significant and positive influence on urban land expansion, suggesting that cities are expected to experience faster urban land growth after the construction of HSR. In addition, HSR facilitates faster urban land expansion for cities in central and western China than those in eastern China, and faster urban land expansion for cities with lower development levels than those with higher development levels. Policymakers may need to consider the heterogeneous impacts of HSR on urban land expansion when introducing HSR to promote urban land development. • This study estimates the impact of HSR on urban land expansion of Chinese cities. • Propensity score matching and difference-in-difference methods are both used. • HSR has a significantly positive influence on urban land expansion in China. • HSR facilitates faster urban land expansion for cities in central and western China than those in eastern China. • Cities with lower development levels have faster urban land expansion than those with higher development levels. [ABSTRACT FROM AUTHOR]

The construction of high-speed rail (HSR) networks is of great significance to researchers in the fields of regional development, regional structure, and regional integration. Whilst a large number of studies have estimated the impacts of HSR networks on regional economic development, accessibility, and commuting behavior, how urban spatial structures evolution in the HSR era remain largely unexplored. Thus, the purpose of this paper is to explore how the urban structures (urban hierarchical structure and urban physical structure) of cities in the Yangtze River Delta evolution by employing a reverse gravity model and a gravity deviation model in the HSR era. Our findings indicate that in the HSR network, the traffic attractiveness of cities in Pan-Yangtze River Delta showed an obvious hierarchical distribution (taking on a spindle shape), and that the first-tier cities comprised of Shanghai and Nanjing. We further found that the impacts of introducing a HSR network on urban land growth were greater in non-HSR cities than in cities with HSR. In addition, the growth rate of urban land was found to be higher in areas surrounding HSR stations than in the city at large. This shows that the introduction of HSR significantly stimulated the development of the cities making up the study area. More importantly, after the opening of the HSR network, the center of gravity of the urban areas of 75% cities that were connected to the HSR network was found to deviate towards the HSR station. Differences in the pattern and degree of deviation were identified, thus indicating the presence of individual differences in the effects of HSR on urban growth in different cities. Image 1 • The impact of HSR networks on urban hierarchical and physical structure is explored. • A reverse gravity model and a gravity deviation model are utilized, taking 2008–2013 into consideration. • In the HSR network, the traffic attractiveness of cities showed an obvious hierarchical distribution. • The impacts of introducing a HSR network were greater in non-HSR cities than in cities with HSR. • The center of gravity of the urban areas of 75% cities was found to deviate towards the HSR station. [ABSTRACT FROM AUTHOR]

To reduce carbon dioxide (CO 2) emissions attributed widely to human activities, previous studies have paid great attention to the relationships between socioeconomic development, urban forms and CO 2 emissions in cities, and provided relevant emission mitigation policies through the effective urban spatial planning. However, whether and how different features of urban forms (such as compactness) affecting the levels of CO 2 emissions is still debatable, specifically considering the different development levels of the cities. Therefore, this study is to synthetically explore how socioeconomic factors and urban forms work together to affect CO 2 emissions with the consideration of differences in development levels of five city tiers in China. First, CO 2 emissions in each city were derived from provincial energy statistics, radiance-calibrated nighttime light imageries, and population distribution data based on a disaggregating model. Then, a set of variables representing socioeconomic factors and urban forms were acquired from the city statistics and land use data, respectively. After obtaining the balanced dataset of these five city tiers from 1995 to 2015, the panel data analysis was finally applied to evaluate the consequences of socioeconomic factors and urban forms on CO 2 emissions under different development stages. The estimation results show that the economic development, population growth, and urban land expansion are important factors that accelerating CO 2 emissions in all the city tiers. Besides, irregular or fragmented structures of urban land use could result in more CO 2 emissions due to the increase in potential transportation requirements in all the city tiers. Notably, an increasing concentrated pattern in the urban core is found to increase CO 2 emissions in the tier-one cities, but to promote the reduction of CO 2 emissions in other four city tiers. The urban spatial development with a compact and multiple-nuclei pattern is suggested to be closely linked with a lower level of CO 2 emissions. Such results highlight the importance of a city's development level for decision-making involving the mitigation of CO 2 emissions, and provide scientific support for building a low-carbon city from the perspective of both socioeconomic development and urban spatial planning. • Differentiated impacts of socioeconomic factors and urban forms on CO2 emissions are explored. • Socioeconomic growth and urban land expansion promote CO 2 emissions in all city tiers. • Urban forms in different development levels have different impacts on CO 2 emissions. • Fragmented patterns of urban land can result in more CO 2 emissions in all city tiers. • Compact and centralized developments do little to reduce emissions in tier-one cities. [ABSTRACT FROM AUTHOR]

The significant economic development witnessed in China in recent decades has been accompanied by the increasing expansion of urban areas. Although a growing literature has analyzed the characteristics and driving forces of urban land expansion, less attention has been paid to examining the different expansion determinants driving fine-scale urban land use (residential land, administration and public services land, commercial land, and industrial land) change. This paper aims to identify the differences of multi-mechanisms driving fine-scale urban land use expansion based on big data and machine learning, in the Huizhou downtown area in 2000–2015. The Random Forest (RF) algorithm is used to identify the natural, transportation, location, social, and POI factors driving land expansion by considering different urban land-use categories. Our RF estimations showed that enormous differences existed between various urban land-use types in terms of the role they played in this expansion and their relation to potential determinants, during the different urban development stages studied. Transportation, location, and the distribution of actual land use were found to exert a greater influence on urban land expansion than other factors. All the findings above provide detailed spatiotemporal knowledge and targeted information that can aid in understanding fine-scale urban land use dynamics. In this way, sound planning strategies for different fine-scale land uses can be formulated more scientifically. The strength of association between these factors and urban land expansion differed greatly depending on the different land-use types involved as well as the urban development stage that it occurred within. These results cast a new light on the importance of investigating the potential driving forces in the expansion of different urban land-use types. • The determinants of fine-scale urban land expansion are explored based on big data and machine learning. • Natural, transportation, location, social, and POI factors are considered. • Random Forest method is used considering the period 2000–2015. • The strength of association between factors and urban land expansion differed greatly across land use types. • Transportation, location, and the distribution of actual land use exert a greater influence. [ABSTRACT FROM AUTHOR]