A model for urban sector drivers of carbon emissions

Azizalrahman, Hossny; Hasyimi, Valid

doi:10.1016/j.scs.2018.09.035

Cited by 68 publications

(24 citation statements)

References 27 publications

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“…For instance, as for the factor of economic development, Sharma (2011) [18] and [19] both found that GDP per capita had a significant positive effect on CO 2 emissions. However, Azizalrahman and Hasyimi (2019) [16] found that GDP per capita only presented positive correlations with CO 2 emissions in upper-middle and lower-middle income countries, and the correlation was negative in high income countries.…”

Section: Contributions Of This Papermentioning

confidence: 95%

“…The results showed that urbanization changed the consumption pattern, and the transportation sector became one of the largest emission sectors. Azizalrahman and Hasyimi (2019) [16] classified the urban sector drivers of CO 2 emissions into residential, commercial, and industrial factors and examined their different roles in different income-level countries.…”

Section: Contributions Of This Papermentioning

confidence: 99%

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Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

Xue

Ren

Bi³

2019

Sustainability

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The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO2 emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO2 emissions from 2015–2020. The results show that YRD’s CO2 emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO2 emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO2 emissions is higher than the population and urbanization rate, and its contribution rate for CO2 emissions is growing. The Kuznets curve does not exist in the current YRD.

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Section: Contributions Of This Papermentioning

confidence: 95%

Section: Contributions Of This Papermentioning

confidence: 99%

Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

Xue

Ren

Bi³

2019

Sustainability

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“…Because energy is central to smart city and low carbon cities, this section investigates the impact of urbanization on carbon emissions focusing on residential, commercial and industrial sectors, the major components of any city's land use. Azizalrahman and Hasyimi [7] have suggested a comparative analysis of low carbon cities in high income, upper-middle income and lower-middle income groups of countries. They have formulated an impact model of urban sector drivers on carbon emissions (USDM) to examine the relationship between urbanization, economic factors and carbon emissions and exposed urban dynamics of variables' interaction at city level.…”

Section: Smart City and Carbon Emissionsmentioning

confidence: 99%

Towards a Generic Framework for Smart Cities

Azizalrahman¹,

Hasyimi²

2020

Smart Urban Development

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Cities are formidable drivers of economic, social and cultural development but face a rising multitude of challenges: urban sprawl, transportation problems and climate change to mention but a few. Evolving concepts such as smart cities, sustainable communities and low carbon cities have been employed to formulate initiatives to tackle these challenges. Smart cities appear to address efficiency in reducing time, cost, and energy in delivering services-smart transportation, intelligent buildings, and green infrastructure with a view to reaching low carbon city development and eventually sustainability. This article attempts to construct a general framework for smart cities. First, the overall smart city system is depicted. Second, the dynamics of urban sector drivers in smart and low carbon cities are elucidated. Third, the performance of smart cities is measured in relation to low carbon development. By applying the smart city framework to the cities of Vienna, London, New York and Tokyo, the model proved robust and flexible. The investigation is concluded with policies to realign city plan and development policies.

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“…In fact, IPAT, STIRPAT, and EKC are common models to measure the impact of urbanization on carbon emissions [4,5]. These were supplemented by USDM to offer a breakdown of urban sector drivers of carbon emissions [6]. Multi-criteria evaluation models were built to measure low carbon using the entropy weight coefficient method [7][8][9].…”

Section: Literature Reviewmentioning

confidence: 99%

A Strategy-Based Model for Low Carbon Cities

Hasyimi

Azizalrahman

2018

Sustainability

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Low carbon cities are increasingly forming a distinct strand of sustainability literature. Models have been developed to measure the performance of low carbon cities. The purpose of this paper is to formulate a strategy-based model to evaluate current performance and predict future conditions of low carbon cities. It examines the dynamic interrelationships between key performance indicators (KPIs), induces changes to city plan targets, and then instantly predicts the outcome of these changes. Designed to be generic and flexible, the proposed model shows how low carbon targets could be used to guide the transformation of low carbon cities under four strategies: (1) Passive intervention, (2) problem solving, (3) trend modifying, and (4) opportunity seeking. Further, the model has been applied to 17 cities and then tested on five cities: London, New York, Barcelona, Dubai, and Istanbul. The paper concludes with policy implications to realign city plans and support low carbon innovation.

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A model for urban sector drivers of carbon emissions

Cited by 68 publications

References 27 publications

Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

Towards a Generic Framework for Smart Cities

A Strategy-Based Model for Low Carbon Cities

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