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

Abstract

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.

Spatial Correlation Network Structure of Carbon Emission Efficiency in China’s Construction Industry and Its Formation Mechanism

“…Ratio of urban population to total population He [46] Energy-saving technology level Ratio of the total output value of the construction industry to energy consumption Hui [32], Li [51] Labor productivity Ratio of the total output value of the construction industry to the number of employees in the construction industry Li [51] Industrial agglomeration IA ij = q ij /q j /(q i /q), where q ij is the economic output of the i industry in the j region, q j is the total economic output of the j region, and, q i is the total output of i industry in the country, q is the country's total economic output.…”

“…Lu [1], Li [51] Industrial development level Ratio of the total output value of the construction industry to regional GDP Li [7], Huo [34] 3.5. Indicator Selection…”

“…In this paper, the total output value of the construction industry is selected as the expected output indicator. The CO 2 emissions of the construction industry are divided into direct CO 2 emissions and indirect CO 2 emissions, of which the calculation method of CO 2 emission is based on Li et al [51].…”

Calculation and prediction of carbon emissions in construction industry based on LMDI

“…Wang Jingwen [18] established a calculation model for the complete carbon emissions of the construction industry in five provinces (regions) in northwest China, estimated the carbon emissions of the construction industry in northwest China, and used LMDI to analyze the impact of four driving factors on the complete carbon emissions of the construction industry. Yan Hui et al [19] used data from the construction industry in China to establish a multiple regression model for the factors influencing carbon emission intensity in the construction industry and conducted empirical analysis. Based on this, although many scholars have explored the calculation and influencing factors of carbon emissions in the construction industry and predicted future carbon emissions, most of them focus on specific regions or provinces in China, and there is a lack of calculation of carbon emissions and prediction of future data for the national construction industry.…”