Christian Azar

It has been claimed that COVID-19 public stimulus packages could be sufficient to meet the short-term energy investment needs to leverage a shift toward a pathway consistent with the 1.5 °C target of the Paris Agreement. Here, we provide complementary perspectives to reiterate that substantial, broad, and sustained policy efforts beyond stimulus packages will be needed for achieving the Paris Agreement long-term targets. Low-carbon investments will need to scale up and persist over the next several decades following short-term stimulus packages. The required total energy investments in the real world can be larger than the currently available estimates from integrated assessment models (IAMs). Existing databases from IAMs are not sufficient for analyzing the effect of public spending on emission reduction. To inform what role COVID-19 stimulus packages and public investments may play for reaching the Paris Agreement targets, explicit modelling of such policies is required.

To achieve the climate goals of the Paris Agreement, greenhouse gas emissions from the electricity sector must be substantially reduced. We develop an agent-based model of the electricity system with heterogeneous agents who invest in power generating capacity under uncertainty. The heterogeneity is characterised by the hurdle rates the agents employ (to manage risk) and by their expectations of the future carbon prices. We analyse the impact of the heterogeneity on the transition to a low carbon electricity system. Results show that under an increasing CO₂ tax scenario, the agents start investing heavily in wind, followed by nuclear and to some extent in natural gas fired power plants both with and without carbon capture and storage as well as biogas fired power plants. However, the degree to which different technologies are used depend strongly on the carbon tax expectations and the hurdle rate employed by the agents. Comparing to the case with homogeneous agents, the introduction of heterogeneity among the agents leads to a faster CO₂ reduction. We also estimate the so called “cannibalisation effect” for wind and find that the absolute value of wind does not drop in response to higher deployment levels, but the relative value does decline.

It has been claimed that COVID-19 public stimulus packages could be sufficient to meet the short-term energy investment needs to leverage a shift toward a pathway consistent with the 1.5 °C target of the Paris Agreement. Here we provide complementary perspectives to reiterate that substantial, broad, and sustained engagements beyond recovery packages will be needed for achieving the Paris Agreement long-term targets. Low-carbon investments will need to scale up and persist over the next several decades following short-term stimulus packages. The required total energy investments in the real world can be larger than the currently available estimates from Integrated Assessment Models (IAMs). Existing databases from IAMs are not sufficient for analyzing the effect of public spending on emission reduction. To inform what role COVID-19 stimulus packages and public investments may play for reaching the Paris Agreement targets, explicit modelling of such policies is required.

The Dynamic Integrated Climate‐Economy (DICE) model is one of the most influential Integrated Assessment Models available. Its founder Professor William Nordhaus was recently awarded Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel due to his pioneering work on the economics of climate change. In a recent paper in American Economic Journal: Economic Policy, Nordhaus uses the model to conclude that a 2.5°C target is almost out of reach. In this paper, we update DICE 2016 R2 with state‐of‐the‐art models of the carbon cycle, heat uptake into the oceans, and the role of non‐CO₂ forcers. We find that the allowable remaining carbon budget (over the period 2015–2100) to meet a 2.5°C target to be 2,360 GtCO₂ whereas the estimate obtained using DICE 2016 R2 is about 460 GtCO₂. Nordhaus's estimate of the remaining carbon budget for this target is hence five times lower than estimates made by our updated DICE. We also compare our results with estimates by the Intergovernmental Panel on Climate Change (IPCC), and find our results to be in line with the carbon budgets presented in IPCC SR 1.5. We explain the reasons behind the difference between our result and that of Nordhaus and propose that an updated climate module in DICE is warranted.

The DICE model is one of the most influential Integrated Assessment Models available. Its founder Professor William Nordhaus was recently awarded Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel due to his pioneering work on the economics of climate change. In a recent paper in American Economic Journal: Economic Policy Nordhaus uses the model to conclude that a 2.5°C target is almost out of reach. In this paper we update DICE 2016 R2 with state-of-the art models of the carbon cycle, heat uptake into the oceans and the role of non-CO ₂ forcers. We find that the allowable remaining carbon budget (over the period 2015-2100) to meet a 2.5°C target to be 2360 GtCO ₂ whereas the estimate obtained using DICE 2016 R2 is about 460 GtCO ₂ . Nordhaus’s estimate of the remaining carbon budget for this target is hence five times lower than estimates made by our recalibrated version of DICE. We also compare our results with estimates by the Intergovernmental Panel on Climate Change (IPCC) and find our results to be in line with the carbon budgets presented in IPCC SR 1.5. We explain the reasons behind the difference between our result and that of Nordhaus and propose that an updated climate module in DICE is warranted.

Global net-negative carbon emissions are prevalent in almost all emission pathways that meet the Paris temperature targets. In this paper, we generate and compare cost-effective emission pathways that satisfy two different types of climate targets. First, the common approach of a radiative forcing target that has to be met by the year 2100 (RF2100), and, second, a temperature ceiling target that has to be met over the entire period, avoiding any overshoot. Across two integrated assessment models (IAMs), we found that the amount of net-negative emissions—when global net emissions fall below zero—depends to a large extent on how the target is represented, i.e. implemented in the model. With a temperature ceiling (no temperature overshoot), net-negative emissions are limited and primarily a consequence of trade-offs with non-CO₂ emissions, whereas net-negative emissions are significant for the RF2100 target (temperature overshoot). The difference becomes more pronounced with more stringent climate targets. This has important implications: more stringent near-term emission reductions are needed when a temperature ceiling is implemented compared to when an RF2100 target is implemented. Further, in one IAM, for our base case assumptions, the cost-effective negative carbon emissions (i.e. gross anthropogenic removals) do not depend to any significant extent on how the constraint is implemented, only, largely, on the ultimate stringency of the constraint. Hence, for a given climate target stringency in 2100, the RF2100 target and the temperature ceiling may result in essentially the same amount of negative carbon emissions. Finally, it is important that IAM demonstrate results for diverse ways of implementing a climate target, since the implementation has implications for the level of near-term emissions and the perceived need for net-negative emissions (beyond 2050).

We investigate how different global dietary scenarios affect the constraints on, and costs of, transforming the energy system to reach a global temperature stabilization limit of 2 °C above the pre-industrial level. A global food and agriculture model, World Food Supply Model (WOFSUM), is used to create three dietary scenarios and to calculate the CH₄ and N₂O emissions resulting from their respective food-supply chains. The diets are: (i) a reference diet based on current trends; (ii) a diet with high (reference-level) meat consumption, but without ruminant products (i.e., no beef, lamb, or dairy, only pork and poultry); and (iii) a vegan diet. The estimated CH₄ and N₂O emissions from food production are fed into a coupled energy and climate-system optimization model to quantify the energy system implications of the different dietary scenarios, given a 2 °C target. The results indicate that a phase-out of ruminant products substantially increases the emission space for CO₂ by about 250 GtC which reduces the necessary pace of the energy system transition and cuts the net present value energy-system mitigation costs by 25%, for staying below 2 °C. Importantly, the additional cost savings with a vegan diet––beyond those achieved with a phase-out of ruminant products––are marginal (only one additional percentage point). This means that a general reduction of meat consumption is a far less effective strategy for meeting the 2 °C target than a reduction of beef and dairy consumption.

Executive Summary The Global Energy Assessment (GEA) emphasizes the importance of energy to all societies, which explains a longstanding tendency for governments to be closely involved in the energy sector. The nature and extent of this involvement – the degree and types of energy-related policies – depends on a government's ideological orientation, the particular energy resource endowment in its jurisdiction, the development level of its economy, and specific concerns of its society with respect to energy access, energy security, and the environmental and human health impacts of energy supply and use. In every country, energy's critical role for the goal of sustainable development is widely acknowledged. This means that energy-related policies need to be assessed in terms of performance with respect to the social, economic, and environmental dimensions that are encompassed by the concept of sustainable development. Ideally, energyrelated policies will make advances with respect to all three of these critical sustainability dimensions. But frequently policymakers are faced with difficult trade-offs in which improvement in one dimension is at the cost of another. Thus, the first goal of energy-related policy design should be to seek win-win opportunities for simultaneously advancing social, economic, and environmental goals. When this is not possible, the goal should be to apply decision-support mechanisms that integrate diverse social objectives and values into the policy design process, such as the application of multi-criteria analysis as described by Munasinghe (1992; 2009).