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

Abstract

In the context of “carbon peak, carbon neutrality”, it is important to explore the spatial correlation network of carbon emission efficiency in the construction industry and its formation mechanism to promote regional synergistic carbon emission reduction. This paper analyzes the spatial correlation network of carbon emission efficiency in China’s construction industry and its formation mechanism through the use of the global super-efficiency EBM model, social network analysis, and QAP model. The results show that (1) the national construction industry’s overall carbon emission efficiency is steadily increasing, with a spatial distribution pattern of “high in the east and low in the west”. (2) The spatial correlation network shows a “core edge” pattern. Provinces such as Jiangsu, Zhejiang, Shanghai, Tianjin, and Shandong are at the center of the network of carbon emission efficiency in the construction industry, playing the role of “intermediary” and “bridge”. At the same time, the spatial correlation network is divided into four plates: “bidirectional spillover plate”, “main inflow plate”, “main outflow plate”, and “agent plate”. (3) Geographical proximity, regional economic differences, and urbanization differences have significant positive effects on the formation of a spatial correlation network. At the same time, the industrial agglomeration gap has a significant negative impact on the formation of such a network, while energy-saving technology level and labor productivity differences do not show any significant effect.

Study on the Spatial Structure and Drivers of Agricultural Carbon Emission Efficiency in Belt and Road Initiative Countries

“…Thirdly, in terms of the regional agricultural carbon emission efficiency spatial correlation network, many scholars have now not only analyzed the differences in agricultural carbon emission efficiency between different regions but also studied in depth the spatial aggregation and convergence of agricultural carbon emission efficiency and other issues involving the spatial correlation network of regional agricultural carbon emission efficiency. In this regard, scholars have conducted extensive studies [37][38][39][40] exploring spatial spillover effects, spatial correlation relationships, etc. Studies have shown that agricultural carbon emission efficiency exhibits significant spatial autocorrelation, and there is a mutual influence relationship between agricultural carbon emission efficiency in different regions.…”

Strategic Allocation of Building Carbon Emission Rights Within Urban Frameworks: A Case Study of Henan Province Under China’s Dual Carbon Objectives

“…Existing research on carbon emissions from buildings mainly focuses on carbon emission measurement [4,5], peak prediction [6], spatial correlation effect [7], and analysis of influencing factors [8,9]. Scholars measure the carbon emissions of each region based on the LCA theory [10,11], IPCC [12], MFA [13], etc., to further predict the peak situation through scenarios and models such as LEAP [14].…”