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• We provide an overview of the dynamics between energy transition and COVID-19. • We identify the challenges and opportunities for energy transition under COVID-19. • We investigate the impact of global economic recovery stimulus on energy transition. • We propose a practical roadmap for the post-pandemic energy transition. • We enrich the framework on global low-carbon energy transition. The COVID-19 pandemic has created significant challenges for energy transition. Concerns about the overwhelming emphasis on economic recovery at the cost of energy transition progress have been raised worldwide. More voices are calling for "green" recovery scheme, which recovers the economy while not compromising on the environment. However, limited academic attention has been paid to comprehensively investigating the implications of COVID-19 for global energy transition. This study thus provides a comprehensive analysis of the dynamics between energy transition and COVID-19 around the world and proposes a low-carbon energy transition roadmap in the post-pandemic era. Using energy data from the International Energy Agency (IEA), we first summarized and reviewed the progress of energy transition prior to COVID-19. Building on prior progress, we identified the challenges for energy transition during the pandemic from the perspectives of government support, fossil fuel divestment, renewable energy production capacity, global supply chain, and energy poverty. However, the pandemic also generates opportunities for global energy transition. We hence also identified potential opportunities for energy transition presented by the pandemic from the perspectives of price competitiveness, policy implementation efficiency, and renewable energy strengths. We further provided an in-depth discussion on the impact of current worldwide economic recovery stimulus on energy transition. Based on the identified challenges and opportunities, we proposed the post-pandemic energy transition roadmap in terms of broadening green financing instruments, strengthening international cooperation, and enhancing green recovery plans. Our study sheds light on a global low-carbon energy transition framework and has practical implications for green recovery schemes in post-pandemic times. [ABSTRACT FROM AUTHOR]

[Display omitted] • Clean energy transitions based on the circular economy (CE) are analysed for a town in China. • This could reduce energy use, CO 2 emissions and PM 2.5 emissions compared to the BAU scenario. • COVID pandemic is a new opportunity to introduce circular economy measures. • Circular economy measures could accelerate clean energy transitions. This paper models the energy and emissions scenarios for a circular economy based clean energy transitions in a 140,000-population town in China, taking into account the new situation encountered by the COVID-19 pandemic. The modelled scenarios propose new clean energy transition roadmaps towards a sustainable urban system through the implementation of circular economy strategies. This is represented by the cascading use of industrial excess heat to form symbiosis between factories and to cover the growing building heat demand, as well as by the electrification of the transport sector and reusing the batteries for a second life as energy storage devices. The results show that for a circular economy scenario, during 2020–2040, an accumulated saving of 7.1 Mtoe final energy use (34%), a decline in 14.5 Mt CO 2 emissions (40%) and 592 t PM 2.5 emissions (43%) could be achieved compared with the business-as-usual scenario. The outcomes of the circular economy strategies are at least 7% better than the new policy scenario which simply has energy efficiency improvements. The outbreak of the COVID-19 tremendously impacts the socio-economic activities in the town. If taking the pandemic as an opportunity to enhance the circular economy, by 2040, compared with the scenario without introducing circular economy measures, the extra avoided final energy use, CO 2 emissions and PM 2.5 emissions could be 1.6 Mtoe (8%), 3.8 Mt (11%) and 229 t (17%) respectively. [ABSTRACT FROM AUTHOR]