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Impact of urbanization on per capita energy use and emissions in India

Impact of urbanization on per capita energy use and emissions in India The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India.Design/methodology/approachThe present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use.FindingsEnergy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India.Research limitations/implicationsThe study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces.Originality/valueThere are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Energy Sector Management Emerald Publishing

Impact of urbanization on per capita energy use and emissions in India

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1750-6220
DOI
10.1108/ijesm-01-2021-0010
Publisher site
See Article on Publisher Site

Abstract

The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India.Design/methodology/approachThe present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use.FindingsEnergy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India.Research limitations/implicationsThe study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces.Originality/valueThere are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).

Journal

International Journal of Energy Sector ManagementEmerald Publishing

Published: Jan 3, 2022

Keywords: Urbanization; Energy intensity; Energy use; STIRPAT model; CO2 emission; Urban; Energy sector; Regression; Time series analysis

References