Construction management in China has embraced a new practice encompassing the evaluation criteria of green construction. Thus, greenhouse gas emissions produced during the construction period should not be overlooked anymore. The greenhouse gas emissions from construction projects are evaluated based on life cycle assessment theory, and on green construction evaluation and management techniques. A procedure for assessing the greenhouse gas emissions from construction projects is developed using the unit 'construction process, and by classifying and integrating the different components of construction projects. A segregation-integration method was established for calculating the greenhouse gas emissions of construction project. A mathematical model and framework to calculate the greenhouse gas emissions from construction projects have been established. The energy consumption and carbon dioxide emissions for earthwork, foundation work, masonry, and reinforced concrete during construction are calculated based on the example of a commercial building in a large-scale residential complex in the Pingshan New District of Shenzhen City. The greenhouse gas emissions were calculated as equivalent carbon dioxide emissions. High-rise buildings and villas have the highest unit carbon emissions of 54.51 lcg/m(2), and accoupt for 84% of the carbon dioxide emissions produced during the construction of the residential community. The unit carbon emissions for construction of the entire residential community are approximately 54.18 kg/m(2). The scientific value of this paper is that the carbon emissions during the construction stage of a residential community were quantitatively assessed. The unit carbon emissions of the buildings during construction can be used to calculate unit energy consumption of buildings during construction, which should be useful in realising energy savings, and can therefore provide management guidance for reducing energy consumption during the life cycle of building, especially consumption during construction. (C) 2016 Elsevier Ltd. All rights reserved.