Integrated assessment models are powerful tools for providing insight into the interaction between the economy and climate change over a long time horizon. However, knowledge of climate parameters and their behavior under extreme circumstances of global warming is still an active area of research. In this thesis we incorporated the uncertainty in one of the key parameters of climate change, climate sensitivity, into an integrated assessment model and showed how this affects the choice of optimal policies and actions. We constructed a new, multi-step-ahead approximate dynamic programing (ADP) algorithm to study the effects of the stochastic nature of climate parameters. We considered the effect of stochastic extreme events in climate change (tipping points) with large economic loss. The risk of an extreme event drives tougher GHG reduction actions in the near term. On the other hand, the optimal policies in post-tipping point stages are similar to or below the deterministic optimal policies. Once the tipping point occurs, the ensuing optimal actions tend toward more moderate policies. Previous studies have shown the impacts of economic and climate shocks on the optimal abatement policies but did not address the correlation among uncertain parameters. With uncertain climate sensitivity, the risk of extreme events is linked to the variations in climate sensitivity distribution. We developed a novel Bayesian framework to endogenously interrelate the two stochastic parameters. The results in this case are clustered around the pre-tipping point optimal policies of the deterministic climate sensitivity model. Tougher actions are more frequent as there is more uncertainty in likelihood of extreme events in the near future. This affects the optimal policies in post-tipping point states as well, as they tend to utilize more conservative actions. As we proceed in time toward the future, the (binary) status of the climate will be observed and the prior distribution of the climate sensitivity parameter will be updated. The cost and climate tradeoffs of new technologies are key to decisions in climate policy. Here we focus on electricity generation industry and contrast the extremes in electricity generation choices: making choices on new generation facilities based on cost only and in the absence of any climate policy, versus making choices based on climate impacts only regardless of the generation costs. Taking the expected drop in cost as experience grows into account when selecting the portfolio of generation, on a pure cost-minimization basis, renewable technologies displace coal and natural gas within two decades even when climate damage is not considered in the choice of technologies. This is the natural gas as a bridge fuel scenario, and technology advancement to bring down the cost of renewables requires some commitment to renewables generation in the near term. Adopting the objective of minimizing climate damage, essentially moving immediately to low greenhouse gas generation technologies, results in faster cost reduction of new technologies and may result in different technologies becoming dominant in global electricity generation. Thus today’s choices for new electricity generation by individual countries and utilities have implications not only for their direct costs and the global climate, but also for the future costs and availability of emerging electricity generation options.

Integrated Assessment Models (IAM)s play a key role in climate policy research; however, many IAMs are limited by their treatment of technological change. This is a particularly vexing limitation because technological change significantly affects the optimal carbon policy. We propose a means of incorporating technological change within the Dynamic Integrated Model of the Climate and Economy (DICE). We modify DICE to allow it to adjust the cost of CO2 abatement based on the demand for solar photovoltaic generating capacity. We find that deployment of solar photovoltaics (PV) is highly sensitive to returns to scale and the grid integration costs associated with PV intermittency. At low returns to scale integration costs cause PV to be deployed in steps, reducing the benefit of scale effects; at higher returns to scale PV is deployed smoothly but is arrested integration costs become significant; and when returns are high PV becomes so inexpensive that it’s deployed widely in spite of integration costs. The implication of this behavior is that the optimal allocation of research and development resources depends on returns to scale in the solar market: if returns to scale are low, R&D should focus on PV itself, while if they’re high, R&D should focus on reducing integration costs.

National access to modern energy is deemed by Malawi government as the driving force to attain social-economic development. To achieve this, optimal decisions in energy planning and investment are considered important. This study evaluates potential pathways that will inform better policy design and investment option in energy sector. The Integrated Assessment Modelling method has been used to integrate social, economic and environmental variables that affect energy systems, and further analyses potential energy pathways in relation to these earth systems. The Long-range Alternatives Energy Planning system (LEAP) has been used to run a continuous time series from 2008 to 2063 of the three energy policy pathways (scenarios) using: (1) the current Malawi National Policy and Strategies on Energy (MwNEP) (2) the United Nation’s Sustainable Energy for All strategy (SE4ALL) and (3) Business as Usual (REF) scenario. The analysis indicates an exponential growth in energy demand for both MwNEP and SE4ALL scenario with a slight higher demand in SEAll over MwNEP Scenario. In both cases Biomass remains an important energy source beyond the 2030. Thus, the SDG 7 will not be achieved by 2030. Similarly, energy demand trends in MwNEP and SE4ALL scenarios continue to grow beyond available energy stocks and generation capacity which will lead to a shortfall in energy supply. Environmentally, the GHGs emissions in MwNEP are higher than the SE4ALL scenario. This is reflected in the pro-environment policy objective pursued by SE4ALL scenario. In the medium-term LEAP analysis favours advancement of alternative renewable energies at household level like solar photovoltaic (PV) for lighting and sustainable biomass energy for cooking. In the long-run, scaling up the adoption of renewable energy in form of solar, wind and hydro-electricity to meet the energy gap. At the same time, designing and adhering to implementation of sustainable energy plans that cuts energy sources from fossil fuels and allow easy accesses to affordable renewable energies will result in a success of Malawi’s energy system.

With the election of President Trump, climate deniers feel emboldened and moved from the fringes to the centre of global policy making. We study how an agnostic approach to policy, based on Pascal's wager and allowing for subjective prior probability beliefs about whether climate deniers are right, prices carbon. Using the DICE integrated assessment model, we find that assigning a 10% chance of climate deniers being correct lowers the global price on carbon in 2020 only marginally: from $21 to $19 per ton of carbon dioxide if policymakers apply "Nordhaus discounting" and from $91 to $84 per ton of carbon dioxide if they apply "Stern discounting". Agnostics' reflection of remaining scientific uncertainty leaves climate policy essentially unchanged. The robustness of an ambitious climate policy also follows from using the max-min or the min-max regret principle. Letting the coefficient of relative ambiguity aversion vary from zero, corresponding to expected utility analysis, to infinity, corresponding to the max-min principle, we show how policy makers deal with fundamental climate model uncertainty if they are prepared to assign prior probabilities to different views of the world being correct. Allowing for an ethical discount rate and a higher market discount rate and for a wide range of sensitivity exercises including damage uncertainty, we show that pricing carbon is the robust response under rising climate scepticism. / Series: Ecological Economic Papers

The PhD thesis is composed of three chapters and discusses the policy choice under uncertainty and learning in the context of climate change.

Cette thèse met en perspective un ensemble d’éléments des scénarios socio-économiques sous l’angle de la modélisation du climat. Ces éléments contribuent à améliorer la compréhension de l’état actuel des sciences du climat en ce qui concerne les scénarios. En parallèle, ces éléments montrent le potentiel du récent modèle compact du système Terre OSCAR v2.2.Le premier élément concerne l’incertitude des émissions. Bien que les inventaires d’émissions soient incertains, nous ignorons dans quelle mesure ces incertitudes affectent les projections climatiques. Nous quantifions cet impact pour les émissions des énergies fossiles, la principale cause du changement climatique. Nous montrons que ces incertitudes dans les émissions sont amenées à augmenter avec l’utilisation des énergies fossiles non-conventionnelles, mais qu’elles n’augmentent pas de manière significative l’incertitude dans les projections climatiques. Ceci est vrai pour la majeure partie des variables, comme l’augmentation de la température moyenne de surface, mais pas pour certaines qui sont d’intérêt pour la qualité de l’air.Le second élément est une analyse climatique des récents scénarios Shared Socio-Economic Pathways. Nous identifions des failles dans la base de données, que nous comblons. Sur cette base, nous calculons les projections climatiques des scénarios SSP. Nous montrons la présence d’incohérence dans l’utilisation des émissions CO2 dues à l’utilisation des terres (LUC) calculées par les modèles intégrés (IAMs) et des variables associées à l’utilisation des terres. Nous identifions des compromis dans les réductions d’émissions pour l’atténuation du changement climatique. Nous réévaluons de manière plus robuste les budgets carbone. Les incertitudes dans les élévations de températures sont examinées en détail.Le troisième élément concerne les émissions négatives. La plupart des scénarios qui limitent le changement climatique bien en dessous de 2°C par rapport au préindustriel, respectant ainsi l’Accord de Paris, utilisent des émissions négatives. A l’aide d’une version développée de OSCAR v2.2, nous calculons les implications pour le système Terre de plusieurs aspects des techniques d’absorption de dioxyde de carbone (CDR). Nous identifions les réversibilités des différentes parties du système terre, et évaluons le potentiel de refroidissement de ces techniques. Nous montrons aussi que la reforestation pourrait être moins apte à atténuer le changement climatique, du fait du changement dans l’albedo de surface. Par ailleurs, le potentiel d’alcalinisation des eaux de surfaces pour atténuer le changement climatique pourrait être inférieur à celui initialement estimé.Dans l’ensemble, cette thèse identifie des défauts dans le développement actuel des scénarios. Certains ne constituent pas un problème pour les projections climatiques, comme les incertitudes dans le calcul des émissions. D’autres nécessitent une attention particulière, comme le calcul des émissions CO2 dues au LUC par les IAMs ou l’éventuelle surestimation des capacités des techniques de CDR. Ce travail renforce l’urgence du besoin d’atténuation du changement climatique. / This thesis puts into perspective different elements of socio-economic scenarios from a climate change modelling point of view. These elements contribute at improving the comprehension of the current state of climate sciences regarding the scenarios. In the meantime, these elements demonstrate the potential of the recent reduced-form Earth System Model OSCAR v2.2.The first element concerns the uncertainty of emissions. Although emission inventories are uncertain, we ignore what impact on climate change have these uncertainties. We quantify this impact for fossil-fuel emissions, the major contributor to climate change. We show that the uncertainties in emissions are expected to increase with the use of non-conventional fuels, but that they do not increase significantly the uncertainty from Earth system modelling in variables, such as the increase in global surface temperature.The second element is a climate assessment of the recent Shared Socio-economic Pathways (SSP) scenarios. We identify loopholes in the SSP database, and we complete it to calculate the climate projections under these scenarios. Our conclusions suggest inconsistencies in CO2 emissions from Land Use Change (LUC) calculated by the Integrated Assessment Models and in the associated land variables. We identify trade-offs between greenhouse gases in the mitigation of climate change. Using a robust assessment, new carbon budgets are proposed. The uncertainties in increases in global surface temperature are discussed.The third element concerns the negative emissions. Most climate scenarios limiting global warming well below 2°C above preindustrial levels, thus respecting the Paris Agreement, use negative emissions. Using a developed version of OSCAR v2.2, we evaluate the implications for the Earth system of different aspects of different Carbon Dioxide Removal (CDR) technologies. We identify the reversibility in the different components of the Earth system and calculate the cooling potential of carbon dioxide removal technologies. We also show that the potential of afforestation/reforestation techniques may be impeded by the change in albedo, and that the potential of oceanic enhanced weathering may be lower than expected.Overall, this thesis identifies loopholes in the current development of scenarios. Some do not hinder current conclusions regarding climate change, such as the uncertainties in emission inventories. Others call for further analysis, such as the inconsistencies in the use of CO2 emissions from LUC or the eventual overestimation of the potential of some CDR technologies. It emphasizes the need for an urgent mitigation of climate change.

In den letzten Jahren hat die Rolle naturbasierter Lösungen (Nature-based Solutions, NbS) –Aktivitäten, die in und mit der Natur arbeiten, um globale gesellschaftliche Herausforderungen zu bewältigen – bei der Abschwächung und Anpassung an den Klimawandel, dem Schutz der Artenvielfalt und der Verbesserung des menschlichen Wohlbefindens an Bedeutung gewonnen. Die Einführung von NbS verläuft jedoch weiterhin schleppend, und es besteht nach wie vor eine deutliche Kluft zwischen den langsamen Maßnahmen in großem Maßstab und den vielversprechenden Forschungsergebnissen und politischen Aussagen. Dies zeigt, dass es dringend notwendig ist, die Umsetzungsbedingungen für NbS besser zu verstehen. Derzeit ist die Evidenzbasis zu NbS noch unvollständig, insbesondere wenn es um die systematische Bewertung der Wirksamkeit und der Umsetzungsanforderungen geht. Insbesondere fehlen bei groß angelegten Bewertungen wichtige kontextbezogene Informationen über Kultur, Verhalten und andere soziale und institutionelle Faktoren. Auch die vielfältigen Vorteile von NbS werden nach wie vor unterschätzt oder in einigen Fällen überhaupt nicht gewürdigt. Ziel dieser Arbeit ist es daher, politikrelevante Forschung zu betreiben, die dazu beitragen kann, die Lücke zwischen dem großen Potenzial naturbasierter Lösungen zur Bewältigung globaler Herausforderungen, insbesondere der Eindämmung des Klimawandels, und der langsamen Umsetzung in der Praxis zu schließen. Ausgehend von der vorhandenen Literatur zu NbS argumentiere ich, dass drei Bausteine für die erfolgreiche Umsetzung jeder NbS-Aktivität, insbesondere in großem Maßstab, wesentlich sind: (1) Wissenssynthese; (2) Planung und Entscheidungsfindung; (3) Politik und Finanzierungsmechanismen. In dieser Arbeit untersuche ich diese Bereiche, indem ich Nachweise und Überlegungen zu theoretischen und methodischen Lücken in ihrer Bewertung sowie neue Perspektiven beisteuere. / Recent years have seen increased attention to the role that nature-based solutions (NbS) – activities that work in and with nature to address global societal challenges – can play in mitigating and adapting to climate change, protecting biodiversity, and improving human well-being. Natural climate solutions (NCS) – a subset of NbS – can contribute up to a third of the cost-effective carbon dioxide mitigation needed to hold global warming below 2 degrees Celsius. To have the biggest effect on reducing global temperatures, however, NbS must be scaled up now and designed for the long-term. Yet, uptake of NbS continues to be slow and there remains a clear gap between the lagging action at scale and the promising research and policy narratives. This demonstrates an urgent need to better understand the implementation conditions for NbS. Currently, the evidence base on NbS remains incomplete, especially when it comes to systematically assessing effectiveness and implementation requirements. In particular, important contextual information on culture, behavior, and other social and institutional factors are lacking in large-scale assessments. The multiple benefits of NbS also remain undervalued, or in some cases are not valued at all. As such, the objective of this thesis is to conduct policy-relevant research that can contribute to closing the gap between the high potential for nature-based solutions to address global challenges, particularly climate change mitigation, and the realities of slow implementation in practice. Drawing on the existing literature on NbS, I argue that three building blocks are essential to driving successful implementation of any NbS activity, in particular at scale: (1) knowledge synthesis; (2) planning & decision-making; (3) policy & financing mechanisms. I explore these in this thesis, contributing evidence and reflection on theoretical and methodological gaps in their assessment, as well as new perspectives.