Evidence map›Paper›PMID 35102513›Full record

ArticleEnvironmental science and pollution research international2022

Energy-related carbon emissions and structural emissions reduction of China's construction industry: the perspective of input-output analysis.

Tangyang Jiang, Shuangqi Li, Yang Yu, Yufang Peng

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Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Tangyang JiangSchool of Internet, Anhui University, Hefei, 230039, Anhui, China.
Shuangqi LiSchool of Finance, Chongqing Technology and Business University, Chongqing, 400067, China.
Yang YuSchool of Economics, Hainan University, Haikou, 570228, Hainan, China. yuyang_0715@163.com.ORCID http://orcid.org/0000-0003-1641-135X
Yufang PengInstitute of Industrial Development, Tianjin Academy of Social Sciences, Tianjin, 300191, China.

Funding

Hainan Provincial Philosophy and Social Science Planning HNSK(JD)21-16
6 · The paper itself

Abstract

Excessive carbon emissions from energy consumption seriously restrict China's sustainable development and eco-environmental protection. Although the carbon emissions from the construction industry are less than that of the power, transportation, and manufacturing sectors, the carbon emissions released by the construction industry cannot be ignored due to its extensive development trend of high energy consumption and low efficiency. Based on this, this paper studies energy-related carbon emissions and emissions reduction of China's construction industry from 2007 to 2017 by adopting the input-output analysis method, energy consumption method, and structural decomposition model. The results show that within the sample range: (1) The optimization of the construction industry energy consumption structure has a significant reduction effect on the growth of energy carbon emissions from the construction industry in China, and the reduction effect has shown an increasing trend over time. However, it should be noted that in this sample range, the optimization of energy consumption structure in the construction industry is mainly reflected in the decrease of the proportion of high-carbon energy consumption such as raw coal, while low-carbon energy such as natural gas has not played a significant role. Therefore, the future energy optimization space of China's construction industry is still huge. (2) Energy intensity effect and input structure effect have a positive inhibitory effect on carbon emission growth of the construction industry, and the inhibitory effect of energy intensity effect is stronger than that of input structure effect. It shows that in the sample range, the generalized technological progress and energy efficiency of the construction industry have been better optimized and improved. (3) Except for 2015-2017, the final demand effect in other intervals has a positive effect on the growth of carbon emissions in the construction industry, and the secondary and tertiary industries play a major role in the final demand effect. It shows that the total demand for the construction industry in various industries still maintains a growth trend. This paper provides a theoretical analysis basis and practical guidance for China's construction industry to carry out more accurate and efficient emission reduction from the supply-side energy varieties and demand-side industry level, and further enriches the existing research on carbon emissions of the construction industry from the perspective of input-output analysis.

Indexed as

CarbonConstruction IndustryCarbon DioxideChinaCoalEconomic DevelopmentSustainable DevelopmentCarbonCarbon DioxideCoalCarbon emissionsConstruction industryEnergyInput–output

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.