Spatial–Temporal Characteristics and Influencing Factors of Land-Use Carbon Emissions: An Empirical Analysis Based on the GTWR Model

Jie He and Jun Yang ()
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Jun Yang: School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430074, China

Land, 2023, vol. 12, issue 8, 1-23

Abstract: An in-depth comprehension of the spatial–temporal characteristics of land-use carbon emissions (LUCE), along with their potential influencing factors, is of high scientific significance for the realization of low-carbon land use and sustainable urban development. Academic investigations pertaining to LUCE predominantly encompass three key dimensions: assessment, optimization, and characterization research. This study aimed to investigate the spatial and temporal variations in LUCE within Zhejiang Province by analyzing data from 11 cities and identifying the key factors influencing these emissions. This research work employed the geographically and temporally weighted regression (GTWR) model to explore the patterns of variation in these factors across each city. The results reveal that (1) the temporal changes in LUCE display two predominant trends, while the spatial distribution exhibits a distinct “high in the northeast and low in the southwest” divergence; (2) the average intensity of each factor follows the order of economic level > government intervention > urban compactness > public facilities level > urban greening level > industrial structure > population density; (3) and the influencing factors exhibit significant spatial and temporal heterogeneity, with varying direction and intensity of effects for different cities at different stages of development. This study integrated the dimensions of time and space, systematically examining the evolutionary trends of influencing factors on LUCE within each region. Consequently, it contributes to the comprehension of the spatiotemporal effects associated with the driving mechanisms of LUCE. Moreover, it offers a foundation for formulating customized patterns and strategies to mitigate such emissions, taking into account specific local contexts.

Keywords: land-use carbon emissions; spatial–temporal characteristics; influencing factors; geographically and temporally weighted regression; Zhejiang Province (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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