RT Journal Article
T1 CO2 emissions and causal relationships in the six largest world emitters
A1 Ortega Ruiz, Gregorio
A1 Mena Nieto, Ángel Isidro
A1 Golpe Moya, Antonio Aníbal
A1 García Ramos, José Enrique
AB This paper aims to analyse and compare the driving forces of the carbon dioxide emissions of the six highest emitters of the world, namely, China, the United States of America, the European Union, India, Russia, and Japan, which are responsible for more than the 67\% of the emissions, during the period 1990-2018. The analysis is based on an enlarged Kaya-LMDI decomposition, considering five driving forces and a Granger causality study. Both techniques allow us to disentangle the relationship among the different driving forces and how they change from country to country.  The main conclusion from the Kaya-LMDI analysis is that economic growth has been the main driving force that increases CO$_2$ emissions, and to a much lesser extent, the increase in population in most of the six analysed economies. On the other hand, energy intensity is the main factor for reducing CO$_2$ emissions. Surprisingly enough, the end-use fuel-mix term seldom contributes to the decrease of the emissions, which proves that the use of renewable energy should still be actively promoted. It is worth highlighting the different behaviour observed between the four developed countries and the two most populous developing ones, China and India.The Granger-causality analysis suggests that energy intensity Granger causes GDP in the developed countries, energy intensity also Granger cause CO$_2$ emissions in half of the countries and, GDP Granger causes CO$_2$ emissions only in one case, Japan.
YR 2022
FD 2022
LK http://hdl.handle.net/10272/20825
UL http://hdl.handle.net/10272/20825
LA eng
NO Ortega Ruiz, G., Mena Nieto, A.I., Golpe Moya, A.A., García Ramos, J.E. (2022): "CO2 emissions and causal relationships in the six largest world emitters". Renewable and Sustainable Energy Reviews  (Vol. 162, p. 112435). Elsevier BV. https://doi.org/10.1016/j.rser.2022.112435
NO This work has been partially supported by the Consejería de Economía, Conocimiento, Empresas y Universidad de la Junta de Andalucía (Spain), under Group FQM-370 and by European Regional Development Fund (ERDF), ref. SOMM17/6105/UGR. Resources supporting this work were provided by the CEAFMC and Universidad de Huelva High-Performance Computer (HPC@UHU) funded by ERDF/MINECO project UNHU-15CE-2848.
DS Repositorio Institucional de la Universidad de Huelva
RD 28 may 2026