The Spatiotemporal Distribution Characteristics and Driving Factors of Carbon Emissions in the Chinese Construction Industry

Abstract

As a pillar industry of the national economy, the construction industry not only promotes urban development and social prosperity but also has an irreversible impact on the environment with the trend of high carbon emissions. Therefore, it is of great significance for the construction industry to take the lead in achieving carbon emissions reduction. This paper attempts to explore the spatiotemporal distribution characteristics and specific driving factors of carbon emissions in the construction industry in 30 provinces of China from 2011 to 2020 based on the spatial econometric analysis, so as to clarify the development trajectory and formation mechanism. The key findings are (1) there are obvious differences in carbon emissions across Chinese provinces, culminating in a distinct “Belt–Ring–Dot” spatial distribution; (2) the carbon emissions in the construction industry follow an inverted U-shaped pattern from south to north, with lower emissions in the west and higher emissions in the east, which means the pressure and potential of carbon emissions reduction coexist; (3) the Moran’s I index values from 2011 to 2020 were all greater than 0, with a maximum value of 0.284, indicating that there is a notable positive spatial correlation in carbon emissions in the construction industry between provinces; and (4) among the five factors, the number of employees displays the most pronounced spatial correlation, passing the test a total of eight times, and the mean test coefficient is the largest at 0.552. This factor positively influences carbon emissions alongside the gross product. On the other hand, the patents granted factor significantly inhibits carbon emissions with all test coefficients being negative with a maximum absolute value of 0.166. The impact of the technical equipment rate shows a characteristic of initial positive stimulation followed by later negative inhibition. In contrast, the urbanization rate exhibits the weakest spatial correlation with the minimum test coefficient being only 0.001.