Energy-socio-economic-environmental modelling for the EU energy and post-COVID-19 transitions

Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in con sumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability.All the authors belong and thank the support to the MENTES network on Energy Modelling for a Sustainable Energy Transition, by the Spanish Ministry of Science, Innovation and Universities (project/grant RED2018-102794-T). I.A. and I.C. thank the support of the Spanish Ministry of Science, Innovation and Universities (MALCON, RTI2018-099858-A-I00) , the Spanish State Research Agency through Maria de Maeztu Excellence Unit accreditation 2018-2022 (Ref. MDM-2017-0714) and Basque Gov-ernment BERC Programme. L.J.M., I.A. and I.C. gratefully acknowledge the project LOCOMOTION H2020-LC-CLA-2018-2 (No 821105) and L.J.M. MODESLOW, funded under the Spanish National Research, Development and Innovation Programme (Ministry of Economy and Competitiveness of Spain, ref. ECO2017-85110-R). I.C. and R.L thank the Spanish Ministry of Science, Innovation and Universities (PID2019-106822RB-I00). M.A.C., L.A.L. and J.Z. thank the support of the University of Castilla-La Mancha and the European Fund for Regional Development (FEDER) (Ref. 020-GRIN-29137). P.L. gratefully acknowledges the support of project RTI2018-093692-B-I00 by the Spanish Ministry of Science and Innovation (MCI), the National Research Agency (AEI) and the European Fund for Regional Development (FEDER). Y.L. and S.B. gratefully acknowledge the support of project MUSTEC, funded by the European Union's Horizon 2020 research and innovation programme under grant agreement no. 764626