Attaining sustainable development depends on closing the disparity between economic development and carbon dioxide emissions. The impact of energy transition, green growth, mineral resource rents, and technological innovation on rebalancing economic and environmental conditions is the subject of significant debate in certain discussion circles. Therefore, the primary objective of this study is to illustrate the efficacy of the indicators above in fostering sustainable development and mitigating carbon emissions in China by employing a wavelet coherence approach covering the period from 1990 to 2018. The outcomes obtained from the wavelet coherence approach demonstrate that non-renewable energy and carbon emissions had strong coherence from 1998 to 2014, with most scale values near 1; however, during 2014–2018, it declined to a moderate level at 16 to 24. Renewable energy indirectly correlates with carbon emissions on a scale of 1–20, suggesting its contribution to improving environmental quality in China. At the same time, green growth demonstrates a positive correlation from 1998 to 2002 and a substantial negative correlation after 2018 on a scale from 1 to 4. During 1998–2014, mineral resource rents and carbon emissions show a significant positive coherence; however, during 2014–2018, the coherence among both indicators is positive but not very high at a period scale of 16–24. The results from spectral causality analysis indicate that non-renewable energy, technological innovation, GDP, and mineral rents are strong predictors of carbon emissions, while green growth and renewable energy show an inverse and weaker relationship with emissions. Concisely, the findings reveal that the consumption of mineral rents, non-renewable energy, technological innovation, economic growth, increase carbon emissions while renewable energy and green growth mitigate carbon emissions in China. The study's findings provide valuable policy implications that are intended to promote the use of renewable energy, foster green growth, technological innovation, and the utilization of mineral resource rents in order to achieve environmental sustainability and emission reduction in China as part of a low-carbon economy. It is further suggested that the successful implementation of these strategies necessitates a sustained commitment and collaborative endeavors.
Amin, A., bte Mohamed Yusoff, N.Y., Peng, S., Magazzino, C., Sharif, A., Kamran, H.W. (2025). Driving sustainable development: The impact of energy transition, eco-innovation, mineral resources, and green growth on carbon emissions. RENEWABLE ENERGY, 238 [10.1016/j.renene.2024.121879].
Driving sustainable development: The impact of energy transition, eco-innovation, mineral resources, and green growth on carbon emissions
Magazzino, Cosimo;
2025-01-01
Abstract
Attaining sustainable development depends on closing the disparity between economic development and carbon dioxide emissions. The impact of energy transition, green growth, mineral resource rents, and technological innovation on rebalancing economic and environmental conditions is the subject of significant debate in certain discussion circles. Therefore, the primary objective of this study is to illustrate the efficacy of the indicators above in fostering sustainable development and mitigating carbon emissions in China by employing a wavelet coherence approach covering the period from 1990 to 2018. The outcomes obtained from the wavelet coherence approach demonstrate that non-renewable energy and carbon emissions had strong coherence from 1998 to 2014, with most scale values near 1; however, during 2014–2018, it declined to a moderate level at 16 to 24. Renewable energy indirectly correlates with carbon emissions on a scale of 1–20, suggesting its contribution to improving environmental quality in China. At the same time, green growth demonstrates a positive correlation from 1998 to 2002 and a substantial negative correlation after 2018 on a scale from 1 to 4. During 1998–2014, mineral resource rents and carbon emissions show a significant positive coherence; however, during 2014–2018, the coherence among both indicators is positive but not very high at a period scale of 16–24. The results from spectral causality analysis indicate that non-renewable energy, technological innovation, GDP, and mineral rents are strong predictors of carbon emissions, while green growth and renewable energy show an inverse and weaker relationship with emissions. Concisely, the findings reveal that the consumption of mineral rents, non-renewable energy, technological innovation, economic growth, increase carbon emissions while renewable energy and green growth mitigate carbon emissions in China. The study's findings provide valuable policy implications that are intended to promote the use of renewable energy, foster green growth, technological innovation, and the utilization of mineral resource rents in order to achieve environmental sustainability and emission reduction in China as part of a low-carbon economy. It is further suggested that the successful implementation of these strategies necessitates a sustained commitment and collaborative endeavors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.