Calculation of Energy Consumption and Carbon Emissions in the Construction Stage of Large Public Buildings and an Analysis of Influencing Factors Based on an Improved STIRPAT Model

Abstract

Compared to general public and residential buildings, large public buildings are often difficult to construct and have a long construction period, creating greater construction energy consumption and carbon emissions on the one hand, while generating a large amount and many types of difficult-to-track process data on the other. As such, it is difficult to measure carbon emissions and analyze various influencing factors. By realizing the simple calculation of energy consumption and carbon emissions, as well as discerning the degree of influence of various factors based on the results of influencing factors research, it is of considerable practical significance to propose energy savings and emission reductions in a targeted manner. In view of the above, this work aimed to establish a more practical calculation method to measure energy consumption and carbon emissions in the construction of large public buildings, as well as to identify the multiple influencing factors related to energy consumption and carbon emissions during the construction process. To demonstrate the practicality of our approach, quantitative calculations are carried out for a new terminal building in a certain place and from the perspective of sustainable urban construction; thus, the driving factors of the traditional STIRPAT model are extended to seven. Based on the calculation results, a modified STIRPAT model is used to analyze the comparative study of impact factors, such as population and construction machinery performance, on energy consumption and carbon emission intensity. The results show the following: (1) The energy consumption value per square meter of this terminal building is 3.43 kgce/m2, and the average carbon emission per square meter is about 13.88 kgCO2/m2, which is much larger than the national average of 6.96 kgCO2/m2, and (2) the type of energy used in the construction process has the greatest degree of influence on energy consumption and carbon emission, and the local GDP, population factor, construction machinery performance specifications, and shift usage also show a positive correlation with the growth of total energy consumption and carbon emissions. Moreover, while the government’s continuous investment in energy conservation and environmental protection has reduced the total energy consumption and carbon emissions in construction, there is still considerable room for improvement. Finally, according to the results, we provide theoretical references and constructive suggestions for the low-carbon construction of large public buildings in the construction stage. Thus, the results of our study will allow policy makers to formulate appropriate policies.

Life Cycle Assessment of the Construction Process in a Mass Timber Structure

“…The breakdown of carbon footprints across different construction activities, as illustrated in Figure 6, is valuable in distinguishing between areas of focus for enhancing sustainability. First, after steel works, earthwork emerges as the highest contributor, accounting for a substantial 41% of the total impact (Figure 6), which agrees with the findings of Chen et al [29]. This result is primarily due to the high-powered machinery used in earthwork.…”

“…EN 15978 [28], however, excludes emissions due to worker transportation to and from the building site. Another study by Chen et al [29] indicated the average carbon emissions during the construction phase of buildings in China to be 7 kg CO 2 eq/m 2 . The resulting metrics from the above-mentioned studies show wide variation, depending on the adopted assumptions and the consideration or exclusion of other factors.…”

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

“…Chen et al [40] calculated energy consumption and carbon emissions in the construction phase of large public buildings based on an improved STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model. Multiple influencing factors related to energy consumption and carbon emission during the construction process were identified, and the effects of population and engineering machinery performance on energy consumption and carbon emission intensity were analysed.…”