The efficient, the intensive, and the productive

  • 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 whenUrban 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.show moreshow less

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Author details:Venkata Ramana GudipudiORCiDGND, Diego RybskiORCiDGND, Matthias K. B. LüdekeGND, Bin Zhou, Zhu LiuORCiD, Jürgen Peter KroppORCiDGND
DOI:https://doi.org/10.1016/j.apenergy.2018.11.054
ISSN:0306-2619
ISSN:1872-9118
Title of parent work (English):Applied Energy
Subtitle (English):Insights from urban Kaya scaling
Publisher:Elsevier
Place of publishing:Oxford
Publication type:Article
Language:English
Year of first publication:2018
Completion year:2018
Release date:2021/04/07
Tag:Kaya Identity; Sustainable cities; Urban CO2 emissions; Urban Kaya relation; Urban scaling
Volume:236
Page number:8
First page:155
Last Page:162
Funding institution:European Community (EC) [308497]; National Natural Science Foundation of China [71874079, 41501605]; Green Talents Program by the German Federal Ministry of Education and Research (BMBF)
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert