Optimising the spatial structure of cities to promote low-carbon travel is a primary goal of urban planning and construction innovation in the low-carbon era. There is a need for basic research on the structural characteristics that help to reduce motor traffic, thereby promoting energy conservation. We first review the existing literature on the influence of urban spatial structure on transport carbon dioxide emissions and summarise the influence mechanisms. We then present two low-carbon transportation oriented patterns of urban spatial structure including the traditional walking city and the modern transit metropolis, illustrated by case studies. Furthermore, we propose an improved model Green Transportation System Oriented Development (GTOD), which is an extension of traditional transit-oriented development (TOD) and includes the additional features of a walking city and an emphasis on the integration of land use with a green transportation system, consisting of the public transportation and non-auto travel system. A compact urban form, effective mix of land use and appropriate scale of block are the basic structural features of a low-carbon transportation city. However, these features are only effective at promoting low-carbon transportation when integrated with the green traffic systems. Proper integration of the urban structural system with the green space system is also required. The optimal land use/transportation integration strategy is to divide traffic corridors with wedge-shaped green spaces and limit development along the transit corridors. This strategy forms the basis of the proposed urban structural model to promote low-carbon transportation and sustainable urban growth management.

Provincial carbon emissions research is necessary for China to realize emissions reduction targets. Two-level decomposition model based on the Kaya identity was applied to uncover the main driving forces for the energy related carbon emissions in Shandong province from 1995 to 2011, an important energy base in China. Coal consumption is still the biggest contributor to the increased carbon emissions in Shandong. Decomposition results show that the affluence effect is the most important contributors to the carbon emissions increments. The energy intensity effect is the dominant factor in curbing carbon emissions. The emission coefficient effect plays an important negative but relatively minor effect on carbon emissions. Based on the local realities, a series of environment-friendly mitigation policies are raised by fully considering all of these influencing factors. Sustainable mitigation policies will pay more attention to the low-carbon economic development along with the significant energy intensity reduction in Shangdong province.

Understanding the factors that affect residents’ environmental conservation behaviors help in managing the environment of tourist sites. This research provides an integrative understanding of how residents near tourist sites form their environmental conservation behaviors by merging the norm-activation model and cognitive-affective model into one theoretical framework. Results of the structural analysis from a sample of 642 residents showed that this study’s proposed composite model includes a satisfactory level of predictive power for environmental conservation behaviors. The findings identify the following two dimensions of awareness of environmental consequences as having a key role in predicting environmental conservation behaviors: (1) awareness of positive consequences of environmental protection; and (2) awareness of disaster consequences. Results also show that environment attachment and personal norms about environmentalism played a mediating role between awareness of environmental consequences and environmental conservation behaviors, and that personal norms about environmentalism were the most powerful factor in predicting behaviors. Several practical implications were derived from the research findings that can contribute to environment management policy both within and outside the field of tourism, mostly notably: (1) how the effective promotion of these factors can encourage environmental conservation behaviors for residents; and (2) how governments can develop and implement environmental management measures to improve locals’ awareness of positive consequences of environmental protection.

With the transition in the regional development discourse to knowledge- and innovation-based economics, the cultivation of innovation capacity has gained importance as an initiative to enhance regional sustainability and has emerged as a policy goal. An understanding of the formation of innovation clusters is critical to the cultivation of regional innovation capabilities. Except for the location and regional development conditions’ factors, researchers emphasize a built environment’s role in the formation of innovation clusters. Based on the spatial database of 12,516 high-tech firms in 2017 in the Pearl River Delta (PRD), this study developed a conceptual framework for the built environment. The framework comprises living, service, perceptual, industrial, and physical aspects. The direction and intensity of the correlation between built environment factors and high-tech firms are discussed using the spatial regression model and geographical detector (GD) technique. The results show a highly concentrated spatial distribution pattern of high-tech firms in the PRD. A significant county-level spatial autocorrelation is revealed through Moran’s I. According to the model, we determine the positive impacts of technology support, transport infrastructure, and living service levels on the agglomeration of high-tech firms as well as the negative impact of the public service level. The GD’s result demonstrates different levels of impact intensity of built environmental factors. We argue that a comprehensive understanding of the influence of built environment factors on innovation agglomeration will help policymakers develop targeted policies to foster local innovation capabilities and promote sustainable regional development.

Since the 1980s, the rapid, extensive, and dispersed urban expansion in the Pearl River Delta megalopolis (PRDM) has led to landscape fragmentation and the inefficient use of construction land. Like other developed regions in China that are subject to the dual challenges of shortages of construction land and deterioration of the ecological environment, it is becoming increasingly important in the PRDM to improve the land-use efficiency of urban construction. However, current methods for assessing land-use efficiency do not meet the emerging needs of land-use planning and policymaking. Therefore, using the American Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) nighttime light imagery and Landsat TM data, this study aims to develop a timely and efficient approach to model the high-resolution economic efficiency of construction land (EECL). With this approach, we mapped the reliable EECL of the PRDM at township level and with a one-kilometer grid. Next, the study compared the temporal changes and revealed the spatial-temporal dynamics in order to provide a scientific reference for informed land-use planning and policymaking. The results show that since 1998, the economic efficiency of construction land in the PRDM increased in general but varied significantly throughout the area. Further, these disparities widened from 1998 to 2012 between the PRDM’s inner and peripheral circles. Only one-fifth of the towns and subdistricts were categorized as fast-growth or ultrafast-growth, with the majority located in the most developed areas of the PRDM’s inner circle. In order to improve the efficiency of construction land in the PRDM and realize sustainable development, differentiated land-use policies for the inner and peripheral circles were proposed. The inner circle should focus on promoting the efficiency of existing construction land and encourage urban renewal, while the peripheral circle should enhance the control of new construction land and improve its efficiency.

Resource endowment and resource carrying capacity (RCC) are the most important cornerstones of regional sustainable development. By applying a newly established RCC method, namely, the relative resources carrying capacity (RRCC) method, we evaluated the RCC in the Tarim River basin (TRB) in arid China in Xinjiang during 2000-2011. Research results show that the relative resources carrying capacity can be effectively served as indicators of regional resources sustainable development status. Taking Xinjiang as the reference region, the TRB can be characterized as an area with an overloaded population and surplus economy during the whole research period, where land resources are relative advantage resources carrying the regional population growth and economic development and water resources are relative disadvantage resources restricting rapid regional development. Taking TRB as the reference region, 42 counties and cities in TRB performed significant temporal and spatial disparities according to the RRCC based on population and economic perspectives. Based on the spatial-temporal evolution of RRCC, 42 counties and cities in TRB were classified into four matching modes (A, B, C, and D). The spatial-temporal evolution characteristics and mechanisms about the 42 prefectures and cities were examined, and the suitable development strategies for every different mode were recommended.