The welfare properties of climate targets

Two approaches are predominant in climate models: cost-benefit and cost-effectiveness analysis. On the one hand, cost-benefit analysis maximises welfare, finding a trade-off between climate damages and emission abatement costs. On the other hand, cost-effectiveness analysis minimises abatement costs, omits damages but adds a climate constraint, such as a radiative forcing constraint, a temperature constraint or a cumulative emissions constraint. These constraints can be applied from today onwards or only from 2100 onwards, allowing to overshoot the target before 2100. We analyse the impacts of these different constraints on optimal carbon prices, emissions and welfare. To do so, we fit a model with abatement costs, capital repurposing costs (stranded assets) and technological change on IPCC and NGFS scenarios. The welfare-maximizing scenario reaching 1.5°C in 2100 has almost no net negative emissions at the end of the century (-2GtCO2/y). A constraint on cumulative emissions has the best welfare properties, followed by a temperature constraint with overshoot. A forcing constraint with overshoot has insufficient early abatement, leading to a substantial welfare loss of $29 Trillion, spread out over the century. As to the paths reaching 2°C, all cost-effectiveness analysis abate too late, but the welfare impact of this dynamic inefficiency is milder. Again, a forcing constraint with overshoot scores worst

Optimal climate policy under exogenous and endogenous technical change: making sense of the different approaches

Integrated assessment models (IAMs) provide key inputs to decision-makers on economically efficient climate policies, and technical change is one of the key assumptions in any IAM that estimates mitigation costs. We conduct a systematic survey of how technical change is currently represented in the main IAMs and find that a diversity of approaches continues to exist. This makes it important to conduct an up-to-date assessment of what difference technical change makes to IAM results. Here we attempt such an assessment, using an analytical IAM with a reduced-form representation of technical change, which we can calibrate on the relationship between abatement costs and the timing of abatement in 109 IAM scenarios from two major databases. We first show in theory how a range of technical-change mechanisms can be adequately captured in a reduced-form model, in which the key difference is whether technical change is a function of time, i.e., exogenous, or cumulative past emissions abatement, i.e., endogenous. We then derive analytical and quantitative results on the effect of technical change on optimal climate policy, for both cost-benefit and cost-effectiveness policy problems. Under cost-benefit analysis, technical change has a quantitatively large, negative effect on long-run emissions and temperatures. The effect on carbon prices differs markedly depending on whether technical change is exogenous or endogenous, and whether clean technology deployment is incentivised by carbon prices or a dedicated deployment subsidy. Under cost-effectiveness analysis, technical change has a small effect on transient emissions and temperatures, but it has a large, negative effect on carbon prices almost irrespective of the policy instruments available. We make several practical recommendations for how IAMs can better incorporate TC, particularly when facing computational constraints

Achieving −55% GHG emissions in 2030 in Wallonia, Belgium: Insights from the TIMES-Wal energy system model

peer reviewedThe Walloon Region has undertaken the ambitious engagement to reduce its greenhouse gases (GHG) emissions up to −55% in 2030. In this context, a regional model of the energy system is a useful tool to give insights to policy makers. We address the lack of an existing integrated tool by developing a technology-rich, bottom-up model for the region. The goal of this paper is twofold: we present the model and its functioning and then we analyse a cost-optimal way to reach the −55% regional target. Firstly, we describe the methodology, discussing how we build the sectors of our model and how the optimisation works. Secondly, we run the model with a constraint on GHG emissions to assess the impact of the mitigation target. We show that the total system cost of such an ambitious mitigation scenario is only ∼0.5% higher than the cost of an unconstrained reference scenario and that emissions reduction must start as soon as possible to stay on the cost-effective trajectory. Concerning technologies, windmills, photovoltaic (PV) panels and building renovations are cost-optimal solutions even with high discount rates

Scaling-up energy sufficiency on a European level through a bottom-up modelling approach : lessons and perspectives

The unprecedented challenge of reaching carbon neutrality before mid-century and a large share of it within 2030 in order to keep under the 1.5 or 2 °C carbon budgets, requires broad and deep changes in production and consumption patterns which, together with a shift to renewables and reinforced efficiency, need to be addressed through energy sufficiency. However, inadequate representations and obstacles to characterising and identifying sufficiency potentials often lead to an underrepresentation of sufficiency in models, scenarios and policies. One way to tackle this issue is to work on the development of sufficiency assumptions at a concrete level where various implications such as social consequences, environmental co-benefits, conditions for implementation can be discussed. This approach has been developed as the backbone of a collaborative project, gathering partners in 20 European countries at present, aiming for the integration of harmonised national scenarios into an ambitious net-zero European vision. The approach combines a qualitative discussion on the role of energy sufficiency in a "systemic" merit order for global sustainability, and a quantitative discussion of the level of sufficiency to be set to contribute to meeting 100 % renewables supply and net-zero emissions goals by 2050 at the latest. The latter is based on the use of a dashboard, which serves as a common descriptive framework for all national scenario trajectories and their comparison, with a view to harmonising and strengthening them through an iterative process. A set of key sufficiency-related indicators have been selected to be included in the dashboard, while various interrelated infrastructural, economic, environmental, social or legal factors or drivers have been identified and mapped. This paves the way for strengthening assumptions through the elaboration of "sufficiency corridors" defining a convergent, acceptable and sustainable level of energy services in Europe. The process will eventually inform the potential for sufficiency policies through a better identification of leverages, impacts and co-benefits

Optimal Climate Policy under Exogenous and Endogenous Technical Change: Making Sense of the Different Approaches

Integrated assessment models (IAMs) provide key inputs to decision-makers on economically efficient climate policies, and technical change is one of the key assumptions in any IAM that estimates mitigation costs. We conduct a systematic survey of how technical change is currently represented in the main IAMs and find that a diversity of approaches continues to exist. This makes it important to conduct an up-to-date assessment of what difference technical change makes to IAM results. Here we attempt such an assessment, using an analytical IAM with a reduced-form representation of technical change, which we can calibrate on the relationship between abatement costs and the timing of abatement in 109 IAM scenarios from two major databases. We first show in theory how a range of technical-change mechanisms can be adequately captured in a reduced-form model, in which the key difference is whether technical change is a function of time, i.e., exogenous, or cumulative past emissions abatement, i.e., endogenous. We then derive analytical and quantitative results on the effect of technical change on optimal climate policy, for both cost-benefit and cost-effectiveness policy problems. Under cost-benefit analysis, technical change has a quantitatively large, negative effect on long-run emissions and temperatures. The effect on carbon prices differs markedly depending on whether technical change is exogenous or endogenous, and whether clean technology deployment is incentivised by carbon prices or a dedicated deployment subsidy. Under cost-effectiveness analysis, technical change has a small effect on transient emissions and temperatures, but it has a large, negative effect on carbon prices almost irrespective of the policy instruments available. We make several practical recommendations for how IAMs can better incorporate TC, particularly when facing computational constraints

Optimal emissions under exogenous and endogenous learning

peer reviewedSome abatement technologies become cheaper over time due to spillover effects from other sectors. In a climate cost-benefit analysis, this process is “exogenous”, in the sense that it only depends on time. Other abatement technologies become cheaper only if they are deployed on a large scale. This “endogenous” process of learning by doing decreases abatement costs as a function of cumulative abatement. We aim to shed light on the differentiated impact of endogenous and exogenous learning on the optimal mitigation path. This is particularly important in a time when many models and scenarios are ignoring the dynamic characteristic of learning by doing. We develop a cost-benefit integrated assessment model which includes both types of learning dynamics as well as inertia. Theoretically, endogenous learning leads to a supplementary term in the optimality condition: the “learning gains”, whereas exogenous learning only creates an incentive to postpone climate action. We show analytically and numerically that including endogenous and exogenous learning steepens the abatement path. In a cost-benefit analysis, both types of learning leads to lower peak warming. Moreover, endogenous learning leads to negative emissions in the long run. Besides, the common practice of modelling endogenous learning as an exogenous process underestimates optimal abatement by 9% in 2050

Scaling-up energy sufficiency on a European level through a bottom-up modelling approach: lessons and perspectives

The unprecedented challenge of reaching carbon neutrality before mid-century and a large share of it within 2030 in order to keep under the 1.5 or 2 °C carbon budgets, requires broad and deep changes in production and consumption patterns which, together with a shift to renewables and reinforced efficiency, need to be addressed through energy sufficiency. However, inadequate representations and obstacles to characterising and identifying sufficiency potentials often lead to an underrepresentation of sufficiency in models, scenarios and policies. One way to tackle this issue is to work on the development of sufficiency assumptions at a concrete level where various implications such as social consequences, environmental cobenefits, conditions for implementation can be discussed. This approach has been developed as the backbone of a collaborative project, gathering partners in 20 European countries at present, aiming for the integration of harmonised national scenarios into an ambitious net-zero European vision. The approach combines a qualitative discussion on the role of energy sufficiency in a “systemic” merit order for global sustainability, and a quantitative discussion of the level of sufficiency to be set to contribute to meeting 100 % renewables supply and net-zero emissions goals by 2050 at the latest. The latter is based on the use of a dashboard, which serves as a common descriptive framework for all national scenario trajectories and their comparison, with a view to harmonising and strengthening them through an iterative process. A set of key sufficiency-related indicators have been selected to be included in the dashboard, while various interrelated infrastructural, economic, environmental, social or legal factors or drivers have been identified and mapped. This paves the way for strengthening assumptions through the elaboration of “sufficiency corridors” defining a convergent, acceptable and sustainable level of energy services in Europe. The process will eventually inform the potential for sufficiency policies through a better identification of leverages, impacts and co-benefits

Carbon monoxide and prognosis in smokers hospitalised with acute cardiac events: a multicentre, prospective cohort studyResearch in context

Summary: Background: Smoking cigarettes produces carbon monoxide (CO), which can reduce the oxygen-carrying capacity of the blood. We aimed to determine whether elevated expiratory CO levels would be associated with a worse prognosis in smokers presenting with acute cardiac events. Methods: From 7 to 22 April 2021, expiratory CO levels were measured in a prospective registry including all consecutive patients admitted for acute cardiac event in 39 centres throughout France. The primary outcome was 1-year all-cause death. Initial in-hospital major adverse cardiac events (MAE; death, resuscitated cardiac arrest and cardiogenic shock) were also analysed. The study was registered at ClinicalTrials.gov (NCT05063097). Findings: Among 1379 patients (63 ± 15 years, 70% men), 368 (27%) were active smokers. Expiratory CO levels were significantly raised in active smokers compared to non-smokers. A CO level >11 parts per million (ppm) found in 94 (25.5%) smokers was associated with a significant increase in death (14.9% for CO > 11 ppm vs. 2.9% for CO ≤ 11 ppm; p  11 ppm was associated with a significant increase in MAE in smokers during initial hospitalisation after adjustment for comorbidities (odds ratio [OR] 15.75, 95% CI [5.56–44.60]) or parameters of in-hospital severity (OR 10.67, 95% CI [4.06–28.04]). In the overall population, CO > 11 ppm but not smoking was associated with an increased rate of all-cause death (HR 4.03, 95% CI [2.33–6.98] and 1.66 [0.96–2.85] respectively). Interpretation: Elevated CO level is independently associated with a 6-fold increase in 1-year death and 10-fold in-hospital MAE in smokers hospitalized for acute cardiac events. Funding: Grant from Fondation Coeur & Recherche