Research on the Carbon Emission Baselines for Different Types of Public Buildings in a Northern Cold Areas City of China

Author:

Li Xiaoping1,Li Yitong23,Zhou Haizhu1,Fu Zheng4,Cheng Xionglei3,Zhang Wei3

Affiliation:

1. China Academy of Building Research, Beijing 100013, China

2. National Engineering Research Center of Building Technology, Beijing 100013, China

3. China Academy of Building Research Tianjin Institute, Tianjin 300380, China

4. School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China

Abstract

Global excessive CO2 emissions have caused serious environmental and health problems, such as global warming, melting glaciers, droughts, floods, and extreme temperatures, and have become a common challenge for the world. China has set a dual carbon goal, with the peak carbon emissions before 2030. In China, the building sector accounts for 50.9% of the country’s carbon emissions. In particular, public buildings are characterized by a high carbon emission intensity, accounting for 38.6% of carbon emissions in the building sector, which affects the achievement of the dual carbon goal in China’s building sector. Establishing a reasonable baseline of carbon emissions contributes to quota management and trading of carbon emissions for public buildings in Tianjin, China, and will ultimately contribute to the reduction of carbon emissions. This study investigates the operational energy consumption and carbon emissions of 721 public buildings in Tianjin (including electricity, natural gas, and district heating). The applicability of the Quartile method and the K-means clustering algorithm was compared to determine the carbon emission baseline of different types of public buildings, such as constraint value, guiding value, and advanced value, based on which the dynamic baseline from 2022 to 2030 was determined. The results show that the advanced value, guiding value, and constraint value of the Tianjin public building carbon emission baseline obtained using the Quartile method are more reasonable than those obtained by the K-means clustering algorithm. Furthermore, the carbon emission baseline in 2030 will be reduced by 3.4~9.2% compared to 2022. This study can guide the formulation of carbon emission trading schemes, and support Tianjin’s building sector to achieve the “carbon peak”.

Funder

Chinese Academy of Building Research

Publisher

MDPI AG

Subject

Building and Construction,Civil and Structural Engineering,Architecture

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