TY - JOUR
T1 - Reprint of: The impact of urbanization on carbon emissions in developing countries: a Chinese study based on the U-Kaya method
AU - Wu, Yuzhe
AU - Shen, Jiahui
AU - Zhang, Xiaoling
AU - Skitmore, Martin
AU - Lu, Wisheng
N1 - Publisher Copyright:
© 2016 Elsevier Ltd
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - Urbanization results in a considerable economic disparity between urban and rural areas in developing countries, which has had a consequent significant impact on CO2 emissions. To accommodate this directly, this paper presents a modified version of the Kaya Identity formula, U-Kaya, that includes a direct urbanization factor to determine the relationship between energy consumption intensity, population growth, urbanization rates, urban and rural GDP per capita and the volume of carbon emissions, for application in the dynamic forecasting of carbon emissions by Monte Carlo simulation. The method is demonstrated in forecasting China's likely carbon emissions in 2020 by three different modes of urbanization policy: the government-dominant mode, market-dominant mode and a hybrid government market-dominant mode. The results indicate that a higher urbanization rate, energy carbon emission coefficient and energy intensity will lead to increased carbon emissions. Finally, three policy implications are identified, comprising the narrowing of the economic gap between urban and rural areas, adjustments to the energy structure and technical innovation, which will provide a valuable reference for developing countries in their efforts to reduce carbon emissions.
AB - Urbanization results in a considerable economic disparity between urban and rural areas in developing countries, which has had a consequent significant impact on CO2 emissions. To accommodate this directly, this paper presents a modified version of the Kaya Identity formula, U-Kaya, that includes a direct urbanization factor to determine the relationship between energy consumption intensity, population growth, urbanization rates, urban and rural GDP per capita and the volume of carbon emissions, for application in the dynamic forecasting of carbon emissions by Monte Carlo simulation. The method is demonstrated in forecasting China's likely carbon emissions in 2020 by three different modes of urbanization policy: the government-dominant mode, market-dominant mode and a hybrid government market-dominant mode. The results indicate that a higher urbanization rate, energy carbon emission coefficient and energy intensity will lead to increased carbon emissions. Finally, three policy implications are identified, comprising the narrowing of the economic gap between urban and rural areas, adjustments to the energy structure and technical innovation, which will provide a valuable reference for developing countries in their efforts to reduce carbon emissions.
UR - http://www.scopus.com/inward/record.url?scp=85047640304&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2017.05.144
DO - 10.1016/j.jclepro.2017.05.144
M3 - Article
AN - SCOPUS:85047640304
SN - 0959-6526
VL - 163
SP - S284-S298
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
IS - Supplement 1
ER -