Exploring the Driving Factors and Their Spatial Effects on Carbon Emissions in the Building Sector
Jia Wei (),
Wei Shi,
Jingrou Ran,
Jing Pu,
Jiyang Li and
Kai Wang
Additional contact information
Jia Wei: School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China
Wei Shi: Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
Jingrou Ran: School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China
Jing Pu: Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
Jiyang Li: School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China
Kai Wang: Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
Energies, 2023, vol. 16, issue 7, 1-21
Abstract:
This study measured the lifecycle carbon emissions of buildings in 30 Chinese provinces from 2005 to 2020 and decomposed the drivers of carbon emissions in the materialization stage and operation stage of building, respectively, using the Stochastic Impacts with the Regression on Population, Affluence, and Technology (STIRPAT) model in order to investigate the drivers of carbon emissions and their spatial influence effects in the building sector. The spatial Durbin model (SDM) was used to thoroughly investigate the spatial effects of carbon emissions and their drivers in the building sector under geographic and economic distances. According to the findings, China’s building sector has a high concentration of carbon emissions in the east and a low concentration in the west. There is also a sizable spatial autocorrelation, and the spatial spillover effects in the materialization and operation stages shift in opposite directions. To help the building sector to achieve the carbon peaking and neutrality goals, specific policy recommendations are made based on the study’s findings.
Keywords: building sector; carbon emissions; driving factors; spatial autocorrelation; spatial spillover effect (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.mdpi.com/1996-1073/16/7/3094/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/7/3094/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:7:p:3094-:d:1110073
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().