Research on the Coupling Coordination Between the Development Level of China’s Construction Industry and Carbon Emissions

In the framework of global efforts to mitigate climate change and in alignment with the “Dual Carbon” objectives, the construction sector, a fundamental cornerstone of the national economy, has garnered significant attention concerning its development and carbon emissions. This study collected data from the construction sector across 30 Chinese provinces (including autonomous regions and municipalities) to develop an evaluation index system for assessing high-quality development. The random forest algorithm was utilized to assess the levels of high-quality development, whereas the carbon emission factor approach was used to quantify emissions at the provincial level. Subsequently, a coupling coordination model was employed to analyze the interrelationship between development levels and carbon emissions. Key findings indicate the following: (1) China’s construction sector has shown sustained improvement in high-quality development; however, significant regional disparities persist, with eastern provinces (e.g., Beijing, Jiangsu) outperforming their central and western counterparts (e.g., Guangxi, Guizhou). (2) Carbon emissions from the construction sector exhibited an M-shaped fluctuation pattern, characterized by an increase from 2013 to 2014, followed by a decline in 2015, a subsequent recovery from 2016 to 2019, a transient decrease in 2020, and an eventual rebound in 2021 and 2022. Spatially, the developed coastal provinces of Jiangsu and Zhejiang exhibited significantly higher carbon emissions compared to regions such as Hainan and Ningxia. (3) The coupling coordination degree indicated a gradual increase from 0.50 to 0.55 (mean values); however, 78% of provinces remained at the “barely coordinated” level (0.5 ≤ D < 0.6), leading to a notable spatial distribution that is marked by elevated values in the eastern and southern regions, while exhibiting reduced values in the western and northern areas. Regional divergence was observed through four characteristic evolutionary trajectories: eastern China exhibited a U-shaped recovery, western China maintained linear growth, central China experienced inverted V-shaped fluctuations, and northeast China displayed W-shaped oscillations.