Spatiotemporal Analysis of Influencing Factors of Carbon Emission in Public Buildings in China

Du, Zhuoqun; Liu, Yi‐Sheng; Zhang, Zhidong

doi:10.3390/buildings12040424

Cited by 25 publications

(13 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Xiang et al (2022c) developed a carbon emission index decomposition tool for the construction industry-PyLMDI. Du et al (2022) discussed the spatiotemporal distribution of carbon emissions from public buildings in 30 provinces in China using the GTWR model and believed that there were east-west differences in the carbon emissions of public buildings in various provinces in China. Li G J. et al (2022) studied the commercial buildings in China from 2001 to 2016 changes in carbon emission reduction in the operation phase and established an evaluation framework for emission reduction intensity, emission reduction amount, and carbon emission reduction rate for the decomposition of carbon intensity.…”

Section: Introductionmentioning

confidence: 99%

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

Yong-kun

Yang²,

Shao³

2022

Front. Environ. Sci.

View full text Add to dashboard Cite

The rapid development of the tertiary industry has made the energy consumption of public buildings grow too fast during the operation stage, which has become a key area of energy conservation and emission reduction in China’s construction industry. This study uses the Minimum Distance to Strong effective Frontier function (MinDS) and Malmquist-Luenberger (ML) index analysis methods to measure the public building carbon emission efficiency (PBCEE) of 30 provincial-level units in China’s eight economic regions from 2010 to 2019, and analyze regional differences and evolution. Then, the influencing factors of PBCEE in different regions were analyzed using the fixed-effect panel data model. The results show that: 1) China’s PBCEE is generally low, with an average efficiency value of only 0.74, and there are great differences among regions, showing the spatial characteristics of “high in the east and low in the west.” 2) Relying on the positive impact of technological progress, the PBCEE in the eight regions increased year by year, with an annual growth rate of 1.82%. 3) The influence results and degrees of various factors on PBCEE are different in different economic zones, but increasing the proportion of electricity consumption has a certain positive effect on improving PBCEE. The same influencing factor has obvious threshold characteristics for PBCEE in different regions, so the government needs to consider the actual situation of the region when formulating carbon emission reduction policies for public buildings.

show abstract

Section: Introductionmentioning

confidence: 99%

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

Yong-kun

Yang²,

Shao³

2022

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…Zhang Peng implemented a detailed planning of material savings and material resource utilization for green construction and refined management, which not only improved construction speed but also produced considerable economic benefits [18]. Du Zhuoqun et al identified multiple influencing factors related to carbon emissions from operating public buildings by measuring carbon emissions during their operation, and then explored the relationship between each influencing factor and carbon emissions [19]. The most comprehensive analyses are still found in theoretical research, and there are fewer data related to the actual construction process [20].…”

Section: Introductionmentioning

confidence: 99%

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

Chen

et al. 2022

Buildings

View full text Add to dashboard Cite

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.

show abstract

“…To further understand the change mechanism of carbon emissions, some scholars began to explore the influencing factors of carbon emissions, and the studies involved the influencing factors mainly include economic growth, population size, industrial structure, gross national income, environmental quality, technological progress, and urbanization level (Xu et al, 2014;Shi et al, 2019;Meng et al, 2018;Li et al, 2011), and some studies further analyzed the spatial spillover effects of the influencing factors on carbon emissions (Xin et al, 2018;Gong et al, 2022). Theoretical studies are the basis of practical studies, and some scholars focus on the strong industry characteristics of carbon emissions, so they have gradually launched studies on carbon emissions from transportation (Xie et al, 2017;Zhu et al, 2020;Dujmovic et al, 2022), agriculture (Ali et al, 2022;Huang and Gao, 2022), aviation (Han et al, 2022), construction (Du et al, 2021;Du et al, 2022), logistics (Zhang Y. et al, 2021), and tourism. Further, related scholars have incorporated the topic of carbon reduction into the analysis of specific regional issues in order to improve the practical application value, and the carbon emission problems of some special regions have been widely studied, such as river basins (Sun et al, 2021;Wang et al, 2021), large cities (Qian et al, 2022), industrial cities (Zhang C. et al, 2021), urban agglomerations (Cui et al, 2020), metropolitan areas (Benjamin and Marilyn, 2009;Thomas, 2013), rural areas (Zhang et al, 2014), ports (Gian et al, 2020), etc.…”

Section: Introductionmentioning

confidence: 99%

County carbon emissions in the Yangtze River Delta region: Spatial layout, dynamic evolution and spatial spillover effects

Wei

Wang

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

The Yangtze River Delta region contributes nearly 16% of the national carbon emissions and is the key area for carbon emission reduction in China. Accurately grasping the spatial evolution characteristics of carbon emissions and the interaction between counties and regions is of great practical significance for precise and collaborative carbon reduction. This study firstly explores the spatial layout and dynamic evolution characteristics of county carbon emissions in the Yangtze River Delta region from 2000 to 2018 by using spatial statistical analysis, secondly identifies the influencing factors of county carbon emissions (CAR) in the Yangtze River Delta region from dynamic and static dimensions respectively by using static and dynamic Spatial Dubin Model, and finally judges the spatial spillover effects of each factor. We find that county carbon emissions are more complex and more diverse in non-synchronous state compared to provinces and cities. The high carbon areas in the Yangtze River Delta region are concentrated in Shanghai and its neighboring cities, as well as industrial counties under the jurisdiction of other sub-core cities, which are continuously clustered towards the center. We have made some theoretical discussions on the results of the spillover effects of various factors on carbon emissions, and concluded that economic of scale (ECO) and industrial structure (IND) have a “polarization effect”, population size (POP) is consistent with the Malthusian view, technological advance (TEC) has a “cumulative effect”, and environmental quality (ENV) The “pollution paradise effect” is mitigated. Finally, we believe that the main unit of precise carbon reduction can take the form of “city-county” combination, and the government should implement differentiated and coordinated carbon reduction policies.

show abstract

Spatiotemporal Analysis of Influencing Factors of Carbon Emission in Public Buildings in China

Cited by 25 publications

References 27 publications

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

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

County carbon emissions in the Yangtze River Delta region: Spatial layout, dynamic evolution and spatial spillover effects

Contact Info

Product

Resources

About