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The efficient, the intensive, and the productive: Insights from urban Kaya scaling

Authors
/persons/resource/gudipudi

Gudipudi,  Ramana Venkata
Potsdam Institute for Climate Impact Research;

/persons/resource/Diego.Rybski

Rybski,  Diego
Potsdam Institute for Climate Impact Research;

/persons/resource/Matthias.Luedeke

Lüdeke,  Matthias K. B.
Potsdam Institute for Climate Impact Research;

/persons/resource/Bin.Zhou

Zhou,  Bin
Potsdam Institute for Climate Impact Research;

Liu,  Zhu
External Organizations;

/persons/resource/Juergen.Kropp

Kropp,  Jürgen P.
Potsdam Institute for Climate Impact Research;

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Citation

Gudipudi, R. V., Rybski, D., Lüdeke, M. K. B., Zhou, B., Liu, Z., Kropp, J. P. (2019): The efficient, the intensive, and the productive: Insights from urban Kaya scaling. - Applied Energy, 236, 155-162.
https://doi.org/10.1016/j.apenergy.2018.11.054


Cite as: https://publications.pik-potsdam.de/pubman/item/item_22766
Abstract
Urban areas play an unprecedented role in potentially mitigating climate change and supporting sustainable development. In light of the rapid urbanisation in many parts on the globe, it is crucial to understand the relationship between settlement size and CO2 emission efficiency of cities. Recent literature on urban scaling properties of emissions as a function of population size has led to contradictory results and more importantly, lacked an in-depth investigation of the essential factors and causes explaining such scaling properties. Therefore, in analogy to the well-established Kaya Identity, we develop a relation combining the involved exponents. We demonstrate that application of this Urban Kaya Relation will enable a comprehensive understanding about the intrinsic factors determining emission efficiencies in large cities by applying it to a global dataset of 61 cities. Contrary to traditional urban scaling studies which use Ordinary Least Squares (OLS) regression, we show that the Reduced Major Axis (RMA) is necessary when complex relations among scaling exponents are to be investigated. RMA is given by the geometric mean of the two OLS slopes obtained by interchanging the dependent and independent variable. We discuss the potential of the Urban Kaya Relation in mainstreaming local actions for climate change mitigation.