Urban land use carbon emission intensity in China under the "double carbon" targets: spatiotemporal patterns and...

In-depth research on the spatiotemporal patterns and evolution trend of urban land use carbon emission intensity (ULUCEI) can reveal the internal relationship between urban land use and carbon emissions, which is crucial for achieving carbon emission reduction and "double carbon" targets. This paper proposed a conceptual framework of ULUCEI; the methods of kernel density estimation (KDE), exploratory spatial data analysis (ESDA), and spatial Markov chains were adopted for exploring the spatiotemporal patterns and evolution trend of China's ULUCEI from 2000 to 2017. The following conclusions are drawn through research. (1) There was an increasing trend in ULUCEI in China from 0.102 in 2000 to 0.283 in 2017. From the regional perspective, the ULUCEI in the eastern region is markedly higher than that in the central and western regions. Moreover, the results of nuclear density estimation indicate that China's ULUCEI shows an obvious upward and polarized trend. (2) China's ULUCEI shows a positive spatial autocorrelation. The types of spatial agglomeration include "high-high" agglomeration, "high-low" polarization, "low-high" collapse, and "low-low" homogeneity, and there are obvious disparities in the distribution rules of cities with different spatial agglomeration forms. (3) China's ULUCEI presents strong stability and "club convergence" trend. Moreover, spatial factors significantly affect the dynamic transition of China's ULUCEI, and its effect on the shifting upwards gradually enhances with increasing lag type. This paper therefore suggests that policymakers should formulate differentiated urban land low-carbon use models and carbon emission reduction policies to reduce ULUCEI.