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Estimating greenhouse gas emissions of European cities — Modeling emissions with only one spatial and one socioeconomic variable
Zitatschlüssel baur2015b
Autor Baur, A. H. and Lauf, S. and Förster, M. and Kleinschmit, B.
Seiten 49-58
Jahr 2015
DOI 10.1016/j.scitotenv.2015.03.030
Journal Science of the Total Environment
Jahrgang 2015
Nummer 520
Monat 07
Verlag Elsevier B.V.
Zusammenfassung Abstract Substantive and concerted action is needed to mitigate climate change. However, international negotiations struggle to adopt ambitious legislation and to anticipate more climate-friendly developments. Thus, stronger actions are needed fromother players. Cities, being greenhouse gasemission centers, play a key role in promoting the climate change mitigation movement by becoming hubs for smart and low-carbon lifestyles. In this context, a stronger linkage between greenhouse gas emissions and urban development and policy-making seems promising. Therefore, simple approaches are needed to objectively identify crucial emission drivers for deriving appropriate emission reduction strategies. In analyzing 44 European cities, the authors investigate possible socioeconomic and spatial determinants of urban greenhouse gas emissions. Multiple statistical analyses reveal that the average household size and the edge density of discontinuous dense urban fabric explain up to 86% of the total variance of greenhouse gas emissions of EU cities (when controlled for varying electricity carbon intensities). Finally, based on these findings, a multiple regression model is presented to determine greenhouse gas emissions. It is independently evaluated with ten further EU cities. The reliance on only two indicators shows that the model can be easily applied in addressing important greenhouse gas emission sources of European urbanites, when varying power generations are considered. This knowledge can help cities develop adequate climate change mitigation strategies and promote respective policies on the EU or the regional level. The results can further be used to derive first estimates of urban greenhouse gas emissions, if no other analyses are available.
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