Abstract
Road traffic has become one of the major sources of carbon dioxide emissions. However, there remains a lack of consensus on how urban land use influences these emissions. This study investigates the spatial distribution of municipal-level road traffic carbon dioxide emissions and their land use drivers in Japan’s Kanto region. Ordinary least squares (OLS), geographically weighted regression (GWR), and multi-scale geographically weighted regression (MGWR) models are employed to analyze the impacts of residential, industrial, and commercial land use on emissions, as well as to examine spatial heterogeneity in model residuals. The results reveal a clear spatial clustering pattern, with higher emissions in central Tokyo and lower emissions in peripheral areas. The MGWR model demonstrates the best fit and shows no spatial autocorrelation in residuals, highlighting the necessity of incorporating spatial heterogeneity. The MGWR results indicate that all three land use types significantly affect emissions, but their impacts vary spatially. Residential land use has the largest and most spatially heterogeneous effect, making it the most decisive factor. The findings underscore that effective low-carbon transportation policies cannot adopt a one-size-fits-all approach but must be tailored to locally dominant land-use–emission relationships. This study deepens the understanding of the spatial relationship between urban land use structure and road traffic carbon emissions and provides empirical support for sustainable urban development and low-carbon transportation policies.
Keywords:
Carbon Dioxide Emission, Road Traffic, Spatial Analysis, Spatial Heterogeneity, Urban Land UseReferences
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Copyright & License
This work is licensed under a Creative Commons Attribution 4.0 International License.