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

Hui Li (), Yanan Zheng, Guan Gong and Hongtao Guo
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Hui Li: College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China
Yanan Zheng: College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China
Guan Gong: College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China
Hongtao Guo: Financial Department, Xinyang Normal University, Xinyang 464000, China

Sustainability, 2023, vol. 15, issue 11, 1-20

Abstract: With the continuous development of the social economy, carbon emissions from various buildings are increasing. As the most important category of building carbon emissions, the rapid peaking of public buildings is an important part of achieving carbon peak and carbon neutrality. This paper is based on the industrial background of the energy consumption structure of Henan Province, a central province in the developing country of China. Firstly, the energy consumption intensity of buildings and public buildings in Henan Province from 2010 to 2020 was calculated according to the energy balance sheet. The Kaya–LMDI decomposition method was also used to analyse the carbon emissions of public buildings, determining the impact of each influencing parameter on public buildings. Secondly, the scenario prediction model Monte Carlo was run 100,000 times to set the stochastic parameters of the variables in the model to predict the time of carbon peak and carbon emissions. The analysis results indicated that: ① Carbon emissions in Henan Province have exhibited a steady growth trend, increasing from 1533 t in 2010 to 6561 t in 2020; ② The primary factors influencing carbon emissions of public buildings in Henan Province were urbanization rate, public floor area per capita, and energy intensity per unit of public floor area; and ③ Carbon emissions of public buildings in Henan Province followed an inverted U-shaped distribution and are expected to peak at approximately 7423 t by the year 2035. The research method in this paper can guide the simulation study of peak carbon emission prediction in Henan Province based on the influencing parameters of carbon emission from different types of buildings. Moreover, the results of this paper can provide a reference for a more precise study of building carbon reduction in similar regions of developing countries.

Keywords: Kaya–LMDI decomposition method; building energy consumption; public building carbon emissions; Monte Carlo simulation; peak prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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