The CO₂ emission mitigation of the commercial and public building sector (P&C) is critical for achieving China's carbon peak and carbon neutrality. Analyzing changes in CO₂ emissions and their driving factors from temporal and spatial perspective provides insights for developing equitable and effective decarbonization strategies. This study investigated the change in temporal trend and spatial distribution of CO₂ emissions of China's P&C during period of 2005–2018 according to the Kaya identify and Gravity Center model. Meanwhile, combined with the Logarithmic Mean Divisia Index, this study proposed a decomposed method to identify the driving factor of the movement of the gravity center. The results showed that: 1) in the temporal dimension, China's P&C has still not achieved its CO₂ emissions peak, arriving 820.68 MtCO₂. The most positive and negative driving factors were per capita add value of tertiary industry and energy efficiency, respectively; 2) in the spatial dimension, during the 13th Five Year Plan period, the gravity center moved southwestward, and the most positive and negative driving factors were energy consumption unit area and energy efficiency, respectively; Besides, to accelerate the decarbonization of China's P&C, this study reviewed the main decarbonization strategies, divided them into six categories and provided policy implications. In summary, this study provides a completed assessment on CO₂ emission changes of China's P&C, facilitating policy-makers to develop more reasonable implementation plans for emission mitigation.

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Understanding the imbalance of carbon emissions in the urban residential building (URB) sector is beneficial for equitable and effective emission reduction policies. However, carbon imbalance in URB and its major driving factors remain unclear. Therefore, according to the Kaya identity and Zenga index, this study aims to analyze the imbalance in carbon emissions and carbon emission unit area of URB from 2005 to 2019. The results represent the following: 1) Although the overall carbon emission unit area reached its peak value (36.17 kgCO₂/m²) in 2011, the overall carbon emission of URB did not reach the peak value, arriving at 0.86 BtCO₂ in 2019; 2) the obvious imbalance of carbon emission and carbon emission unit area was led by the population and energy consumption unit area, respectively; 3) Compared to the difference in economy, the difference in climate had a larger impact on inter-group imbalance of carbon emission unit area without heating. In summary, these results and provided policies facilitate future formulation of fair and effective provincial decarbonization responsibility and emission mitigation implementation policies.

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Mega infrastructure projects (MIPs) are exposed to numerous interdependent risks of various natures which pose difficulties in risk management. Thus far, the research on the risk interactions of MIPs has been focused on developing static risk networks within a single category of risks, at certain stages of the project. It is essential to understand the risk interactions at various stages of MIPs to identify the key risks and key risk relationships that jeopardise their success. This is especially relevant nowadays, as MIPs are expected to be delivered sustainably. Therefore, to analyse the dynamic risk interaction of MIPs, initially, through literature analysis and expert interviews, combined with the four dimensions of sustainable development and the four stages of MIPs, 98 risk factors of MIPs were identified. Subsequently, semi-structured interviews were conducted to determine risk relationships and weights. Risk networks were developed for each stage of MIPs, and improved social network analysis was applied to these risk networks. Finally, the key risks and key risk relationships in each stage of MIPs were identified by analysing the changes of multi-level network indicators. This aided in determining risk control strategies. The results demonstrate that the key risks and key risk relationships are different for each stage of MIPs. Furthermore, the risks of different dimensions of sustainable development have different relationships at different stages. This research is the first to identify the risk relationships involved in MIPs by taking into consideration the whole project life cycle and its sustainable development. This research provides theoretical support for the risk management of MIPs, and strategic suggestions for controlling the risks at each stage of the project.@en

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.

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