Buildings produce a large amount of carbon emissions in their life cycle, which intensifies greenhouse-gas effects and has become a great threat to the survival of humans and other species. Although many previous studies shed light on the calculation of carbon emissions, a systematic analysis framework is still missing. Therefore, this study proposes an analysis framework of carbon emissions based on building information modeling (BIM) and life cycle assessment (LCA), which consists of four steps: (1) defining the boundary of carbon emissions in a life cycle; (2) establishing a carbon emission coefficients database for Chinese buildings and adopting Revit, GTJ2018, and Green Building Studio for inventory analysis; (3) calculating carbon emissions at each stage of the life cycle; and (4) explaining the calculation results of carbon emissions. The framework developed is validated using a case study of a hospital project, which is located in areas in Anhui, China with a hot summer and a cold winter. The results show that the reinforced concrete engineering contributes to the largest proportion of carbon emissions (around 49.64%) in the construction stage, and the HVAC (heating, ventilation, and air conditioning) generates the largest proportion (around 53.63%) in the operational stage. This study provides a practical reference for similar buildings in analogous areas and for additional insights on reducing carbon emissions in the future.

Life cycle cost analysis (LCCA) plays an essential role in the economic sustainability assessment of buildings, and building information modeling (BIM) offers a potentially valuable approach to fulfilling its requirement. However, the state of LCCA based on BIM is unclear despite previously published works. Therefore, this paper aims to address this gap by reviewing 45 relevant peer-reviewed articles through a systematic literature search, selection, and assessment. The results show that three data exchange methods integrate BIM and LCCA through data input, calculation, and output. Precision management, optimization measures, and parameter analysis through BIM significantly improve the value of buildings. Also, a methodological framework is summarized that combines LCC with other indicators based on BIM to consider economic, environmental, and social impacts, which can be monetized to assess life cycle sustainability costs. These findings provide insights for scholars and practitioners.

To meet the growing demand for public facilities and services, many developing countries, including China, have adopted the concept of public–private partnership (PPP). However, there are many risks in PPP projects. Furthermore, these risks affect each other, which may lead to project failure. However, the existing research on the PPP risk relationship has not gone into sufficient detail. Therefore, in order to fill this literature gap, this study proposes a procedural method to analyze the correlation between PPP risks. Firstly, this study, identifies the risks of construction PPP projects in China by combining the literature review with a case study and interviews. Then, fuzzy interpretative structural modeling (FISM) is used to reflect the relationships between these risks and reveal the failure mechanisms of PPP projects. In addition, based on matrix impact cross-reference multiplication applied to a classification (MICMAC) analysis, the risk is divided into four clusters, according to the driving and dependence power, to show the relationship level of the risk. Finally, the paper compares and discusses the research results with other studies and puts forward some suggestions on PPP risks. The FISM-MICMAC method adopted in this study considers the fuzzy of the PPP risk relationship and improves upon previous studies. In addition, the method of FISM-MICMAC can provide a new risk assessment tool for risk management strategies in the field of construction engineering and management.