In China, dynamic spatial–temporal evolution and urban–rural gap in carbon emissions of residential building sector are crucial for understanding the current state, which is faced with great challenges related to emission mitigation. To overcome the challenge, this study employed the gravity center model to explore spatial–temporal evolution of carbon emissions and analyzed the driving factories leading the differences between urban residential buildings and rural residential buildings via decomposition analysis. Meanwhile, Tapio decoupling index is used to predict the future movement of the gravity center. Our results indicated that: (i) the carbon emissions gravity center of both residential building types tends to move south; (ii) the northeast and northwest regions play the largest role in driving the gravity center movement of urban residential buildings and rural residential buildings, respectively; (iii) per capita disposable income is the primary factors affecting the gravity center movement. (iv) the gravity center of both residential building types might tend to move westward in the future. Overall, this study attempts to remedy the current lack of research pertaining to spatial–temporal evolution laws governing carbon emissions in the Chinese residential building sector and provides a reference point for the implementation of targeted urban and rural emission reduction policies.

Mega infrastructure projects (MIPs) have become increasingly important to the realization of sustainable development in China. Sustainable development is a process of dynamic balance, and coordinating the triple bottom line (the environmental, social, and economic dimensions) will enable more sustainable development of MIPs. However, previous studies have lacked consideration of coordination when applying sustainable development principles to the systematic identification of risks to MIPs. The goals of this study were to clarify the definition and dimensions of the sustainable development of MIPs and to identify the key risks of MIPs. A literature review was performed to extend the definition of sustainable development of MIPs by combining the triple bottom line with a fourth coordination dimension. A conceptual model of MIP risk identification was then proposed from an extended sustainable development perspective, 22 sustainability elements and 75 risk factors were identified, and the key risk factors were determined based on the interview responses and fuzzy set theory. The results show that economic risks have a high probability, social risks have a high loss, environmental risks have an intermediate probability and loss, and coordination risks have the greatest impact. In addition, the three most important key risk factors were found to be construction and installation cost overruns, land acquisition and resettling cost overruns, and information sharing with the public. Identifying key risk factors can provide information to help stakeholders understand the risk factors associated with MIPs and formulate reasonable risk response strategies.