Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China
With the rapid economic development in recent years, China has increased its investment in infrastructure construction, and the construction industry has become a significant contributor to China’s carbon dioxide (CO2) emissions. Therefore, carbon emission reduction in the construction industry is c...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.1057387/full |
| _version_ | 1797988888172560384 |
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| author | Tiantian Li Tiantian Li Haidong Gao Haidong Gao Jing Yu Jing Yu |
| author_facet | Tiantian Li Tiantian Li Haidong Gao Haidong Gao Jing Yu Jing Yu |
| author_sort | Tiantian Li |
| collection | DOAJ |
| description | With the rapid economic development in recent years, China has increased its investment in infrastructure construction, and the construction industry has become a significant contributor to China’s carbon dioxide (CO2) emissions. Therefore, carbon emission reduction in the construction industry is crucial to achieving the goal of “carbon peaking and carbon neutrality” as soon as possible. However, few studies have investigated the factors influencing CO2 emissions from the construction industry in terms of spatial and temporal differences. To address this gap, we first improve the calculation method for the construction industry’s life-cycle assessment (LCA). The geographically and temporally weighted regression (GTWR) model is then utilized to provide insight into the spatio-temporal heterogeneity of the various factors influencing CO2 emissions across other regions and times. The results show that: 1) CO2 emissions from the construction industry in China increased rapidly from 576.5 million tons (Mt) in 2004–3,230 Mt in 2012 and then gradually decreased to 1998.51 Mt in 2020; indirect CO2 emissions accounted for more than 90% of the total CO2 emissions after 2008. 2) There is a solid global positive correlation between CO2 emissions from the construction industry in China during most of the time, and the spatial distribution of CO2 emissions shows a northeast-southwest pattern, with the center of gravity gradually shifting from central China to the southwest. 3) Economic output and industrial agglomeration are positive factors for the increase of CO2 emissions from the construction industry; and urbanization level, production efficiency, and energy efficiency are inhibiting factors for the increase of CO2 emissions from the construction industry. But the contribution and trend of each influencing factor differed significantly across time and regions, showing substantial spatial and temporal heterogeneity. Our findings provide a scientific basis for the Chinese government to implement a regional carbon reduction strategy for the construction industry. |
| first_indexed | 2024-04-11T08:11:21Z |
| format | Article |
| id | doaj.art-3ec421c3ff0841ada5f7367aacc6a242 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-11T08:11:21Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-3ec421c3ff0841ada5f7367aacc6a2422022-12-22T04:35:21ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2022-11-011010.3389/fenvs.2022.10573871057387Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in ChinaTiantian Li0Tiantian Li1Haidong Gao2Haidong Gao3Jing Yu4Jing Yu5State Key Laboratory of Northwest Arid Zone Ecological Water Resources, Xi’an University of Technology, Xi’an, ChinaSchool of Civil Engineering and Construction, Xi’an University of Technology, Xi’an, ChinaState Key Laboratory of Northwest Arid Zone Ecological Water Resources, Xi’an University of Technology, Xi’an, ChinaSchool of Civil Engineering and Construction, Xi’an University of Technology, Xi’an, ChinaState Key Laboratory of Northwest Arid Zone Ecological Water Resources, Xi’an University of Technology, Xi’an, ChinaSchool of Civil Engineering and Construction, Xi’an University of Technology, Xi’an, ChinaWith the rapid economic development in recent years, China has increased its investment in infrastructure construction, and the construction industry has become a significant contributor to China’s carbon dioxide (CO2) emissions. Therefore, carbon emission reduction in the construction industry is crucial to achieving the goal of “carbon peaking and carbon neutrality” as soon as possible. However, few studies have investigated the factors influencing CO2 emissions from the construction industry in terms of spatial and temporal differences. To address this gap, we first improve the calculation method for the construction industry’s life-cycle assessment (LCA). The geographically and temporally weighted regression (GTWR) model is then utilized to provide insight into the spatio-temporal heterogeneity of the various factors influencing CO2 emissions across other regions and times. The results show that: 1) CO2 emissions from the construction industry in China increased rapidly from 576.5 million tons (Mt) in 2004–3,230 Mt in 2012 and then gradually decreased to 1998.51 Mt in 2020; indirect CO2 emissions accounted for more than 90% of the total CO2 emissions after 2008. 2) There is a solid global positive correlation between CO2 emissions from the construction industry in China during most of the time, and the spatial distribution of CO2 emissions shows a northeast-southwest pattern, with the center of gravity gradually shifting from central China to the southwest. 3) Economic output and industrial agglomeration are positive factors for the increase of CO2 emissions from the construction industry; and urbanization level, production efficiency, and energy efficiency are inhibiting factors for the increase of CO2 emissions from the construction industry. But the contribution and trend of each influencing factor differed significantly across time and regions, showing substantial spatial and temporal heterogeneity. Our findings provide a scientific basis for the Chinese government to implement a regional carbon reduction strategy for the construction industry.https://www.frontiersin.org/articles/10.3389/fenvs.2022.1057387/fullCO2 emissionconstruction industryLCAGTWRspatial -temporal heterogeneityinfluencing factor |
| spellingShingle | Tiantian Li Tiantian Li Haidong Gao Haidong Gao Jing Yu Jing Yu Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China Frontiers in Environmental Science CO2 emission construction industry LCA GTWR spatial -temporal heterogeneity influencing factor |
| title | Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China |
| title_full | Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China |
| title_fullStr | Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China |
| title_full_unstemmed | Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China |
| title_short | Analysis of the spatial and temporal heterogeneity of factors influencing CO2 emissions in China’s construction industry based on the geographically and temporally weighted regression model: Evidence from 30 provinces in China |
| title_sort | analysis of the spatial and temporal heterogeneity of factors influencing co2 emissions in china s construction industry based on the geographically and temporally weighted regression model evidence from 30 provinces in china |
| topic | CO2 emission construction industry LCA GTWR spatial -temporal heterogeneity influencing factor |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.1057387/full |
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