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- W4385301615 abstract "This study examines carbon emissions from European land transportation, considering spatial autocorrelation patterns. Using global and local Moran's I indices, we find evidence of positive spatial autocorrelation in the panel data of 26 European countries from 1995 to 2019. To adequately analyze the factors influencing transport emissions, we then employ the spatial Durbin model and integrate transport-specific regression models, extending the classic STIRPAT model. The regression models include parameters such as transport intensities, modal splits between road and rail, and infrastructure density. Understanding spatial patterns in transport emissions provides valuable insights for policymakers in developing more effective emissions reduction strategies. Our results emphasize the importance of close European cooperation due to significant spatial dependencies, urging reductions in transport intensities and a shift from road to rail services. Additionally, we identify a non-linear relationship between infrastructure development and carbon emissions, suggesting the existence of 'sustainability sweet spots' in future infrastructure planning." @default.
- W4385301615 created "2023-07-28" @default.
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- W4385301615 date "2023-08-01" @default.
- W4385301615 modified "2023-10-18" @default.
- W4385301615 title "Carbon emissions from European land transportation: A comprehensive analysis" @default.
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- W4385301615 doi "https://doi.org/10.1016/j.trd.2023.103851" @default.
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