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Abstract Urbanization as a migratory and transformative process brings changes to human activities that make a significant contribution to climate change. Carbon emissions have been steadily increasing because of rapid world population growth. This paper attempts to formulate an impact model of urbanization on carbon emissions by offering a breakdown of urban sector drivers of emissions: residential, commercial and industrial to elucidate the dynamics of variables' interaction. The model facilitates a comparative analysis of three groups of countries namely; High Income, Upper-Middle Income, and Lower-Middle Income. Key performance indicators measuring carbon emissions in each group of countries together with the EKC model were used and indicated an inverted U-shaped function between carbon emissions and GDP per capita and a linear relationship with urbanization. Further, the analysis revealed different carbon emissions and trends because of the interaction of urban sector drivers. The paper concludes with policy implications for each group of countries. [ABSTRACT FROM AUTHOR]

The low carbon city concept has surfaced over the past decade and has been increasingly integrated with urban planning. Likewise, assessment methods of Low Carbon Cities have been initiated. Of these, are the Entropy weight method, fuzzy comprehensive evaluation and multi-criteria evaluation. This paper attempts to propose a multi-criteria evaluation model for city performance using a set of criteria and a benchmark with a view to determining whether the city is low carbon or not. Ten pilot cities were selected for which twenty indicators were utilized for model calibration and testing. First, a standard entropy model was employed featuring three cities as low carbon namely; Stockholm, Vienna and Sydney. Second, with the modification of entropy model by adding relative weight to indicators, two more cities were quite rightly added to the list: London and São Paulo. Third, the proposed model was calibrated and tested, the result of which was compared with the results of both entropy and modified entropy models. Luckily, the proposed model showed great similarity to the modified entropy model. Moreover, the model was subsequently tested independently on five additional cities comprising Copenhagen, Bogota, New Delhi, Singapore and Seoul to ascertain results. Copenhagen and Bogota were low carbon cities, the others were not. When populated with relevant data, the proposed model can readily determine whether a particular city is low carbon or not thereby obviating the need for benchmarking and score adjustment every time a new city is added to the study list. [ABSTRACT FROM AUTHOR]