The interplay among COVID-19 economic recovery, behavioural changes, and the European Green Deal: An energy-economic modelling perspective.

In the EU, COVID-19 and associated policy responses led to economy-wide disruptions and shifts in services demand, with considerable energy-system implications. The European Commission's response paved the way towards enhancing climate ambition through the European Green Deal. Understanding the interactions among environmental, social, and economic dimensions in climate action post-COVID thus emerged as a key challenge. This study disaggregates the implications of climate ambition, speed of economic recovery from COVID-19, and behavioural changes due to pandemic-related measures and/or environmental concerns for EU transition dynamics, over the next decade. It soft-links two large-scale energy-economy models, EU-TIMES and NEMESIS, to shed light on opportunities and challenges related to delivering on the EU's 2030 climate targets. Results indicate that half the effort required to reach the updated 55% emissions reduction target should come from electricity decarbonisation, followed by transport. Alongside a post-COVID return to normal, the European Green Deal may lead to increased carbon prices and fossil-fuel rebounds, but these risks may be mitigated by certain behavioural changes, gains from which in transport energy use would outweigh associated consumption increases in the residential sector. Finally, the EU recovery mechanism could deliver about half the required investments needed to deliver on the 2030 ambition.

COVID-19 recovery packages can benefit climate targets and clean energy jobs, but scale of impacts and optimal investment portfolios differ among major economies.

To meet the Paris temperature targets and recover from the effects of the pandemic, many countries have launched economic recovery plans, including specific elements to promote clean energy technologies and green jobs. However, how to successfully manage investment portfolios of green recovery packages to optimize both climate mitigation and employment benefits remains unclear. Here, we use three energy-economic models, combined with a portfolio analysis approach, to find optimal low-carbon technology subsidy combinations in six major emitting regions: Canada, China, the European Union (EU), India, Japan, and the United States (US). We find that, although numerical estimates differ given different model structures, results consistently show that a >50% investment in solar photovoltaics is more likely to enable CO2 emissions reduction and green jobs, particularly in the EU and China. Our study illustrates the importance of strategically managing investment portfolios in recovery packages to enable optimal outcomes and foster a post-pandemic green economy.

Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison.

Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO2 emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs.

Challenges in the harmonisation of global integrated assessment models: A comprehensive methodology to reduce model response heterogeneity.

Harmonisation sets the ground to a solid inter-comparison of integrated assessment models. A clear and transparent harmonisation process promotes a consistent interpretation of the modelling outcomes divergences and, reducing the model variance, is instrumental to the use of integrated assessment models to support policy decision-making. Despite its crucial role for climate economic policies, the definition of a comprehensive harmonisation methodology for integrated assessment modelling remains an open challenge for the scientific community. This paper proposes a framework for a harmonisation methodology with the definition of indispensable steps and recommendations to overcome stumbling blocks in order to reduce the variance of the outcomes which depends on controllable modelling assumptions. The harmonisation approach of the PARIS REINFORCE project is presented here to layout such a framework. A decomposition analysis of the harmonisation process is shown through 6 integrated assessment models (GCAM, ICES-XPS, MUSE, E3ME, GEMINI-E3, and TIAM). Results prove the potentials of the proposed framework to reduce the model variance and present a powerful diagnostic tool to feedback on the quality of the harmonisation itself.

The desirability of transitions in demand: Incorporating behavioural and societal transformations into energy modelling.

Quantitative systems modelling in support of climate policy has tended to focus more on the supply side in assessing interactions among technology, economy, environment, policy and society. By contrast, the demand side is usually underrepresented, often emphasising technological options for energy efficiency improvements. In this perspective, we argue that scientific support to climate action is not only about exploring capacity of "what", in terms of policy and outcome, but also about assessing feasibility and desirability, in terms of "when", "where" and especially for "whom". Without the necessary behavioural and societal transformations, the world faces an inadequate response to the climate crisis challenge. This could result from poor uptake of low-carbon technologies, continued high-carbon intensive lifestyles, or economy-wide rebound effects. For this reason, we propose a framing for a holistic and transdisciplinary perspective on the role of human choices and behaviours in influencing the low-carbon transition, starting from the desires of individuals and communities, and analysing how these interact with the energy and economic landscape, leading to systemic change at the macro-level. In making a case for a political ecology agenda, we expand our scope, from comprehending the role of societal acceptance and uptake of end-use technologies, to co-developing knowledge with citizens from non-mainstream and marginalised communities, and to defining the modelling requirements to assess the decarbonisation potential of shifting lifestyle patterns in climate change and action.

A predictive model and country risk assessment for COVID-19: An application of the Limited Failure Population concept.

This article provides predictions for the spread of the SARS-CoV-2 virus for a number of European countries and the United States of America, drawing from their different profiles, both socioeconomically and in terms of outbreak and response to the 2019-2020 coronavirus pandemic, from an engineering and data science perspective. Each country is separately analysed, due to their differences in populations density, cultural habits, health care systems, protective measures, etc. The probabilistic analysis is based on actual data, as provided by the World Health Organization (WHO), as of May 1, 2020. The deployed predictive model provides analytical expressions for the cumulative density function of COVID-19 curve and estimations of the proportion of infected subpopulation for each country. The latter is used to define a Risk Index, towards assessing the level of risk for a country to exhibit high rates of COVID-19 cases after a given interval of observation and given the plans of lifting lockdown measures.

A group decision making tool for assessing climate policy risks against multiple criteria.

Climate policy making is challenging primarily in that it involves the assessment of data and methods across a multitude of scientific fields and disciplines. In this respect, integrated assessment models are being used, the level of detail in which allows for modelling all relations between climate and human activity. As a result, their structure is usually significantly complex and their use often excludes stakeholders and their valuable knowledge. The aim of this paper is to assess how multiple criteria decision analysis can bridge the gap between climate policy studies and experts, by delving into the literature and reaching a methodological framework appropriate for solving complex problems of this particular problem domain, featuring multiple alternatives, criteria and decision makers. Based on the findings, the Multiple Alternatives-Criteria-Experts Decision Support System is developed and presented. Finally, the capacity of this spreadsheet-based tool is demonstrated by means of a two-stage case study, which includes assessing the importance of a number of exogenous policy risks, as well as evaluating different short-term policy instruments against these risks.