Uncertainty Management and the Dynamic Adjustment of Deep Decarbonization Pathways
The energy system modeling community has extensively assessed the influence of technological and socioeconomic uncertainties with respect to low-carbon scenarios and associated costs. An extensive literature has developed on the choice of optimal low-carbon scenarios. These studies have primarily approached scenarios in a way that can be described as “static,” in that they are defined once and for all and no explicit plan is defined for adjusting them in the face of changing circumstances.
In the following, I argue that deep decarbonization pathways should be depicted as dynamic pathways. When choosing a long-term strategy as the most desirable option, it is important to keep in mind that each decarbonization option relies on the implementation of specific policies and instruments, as most climate mitigation strategies entail a number of innovative solutions (i.e., technologies, behavioral patterns, policy instruments, and institutional settings) for which implementation may face difficulties over time. To address this issue, long-term decarbonization strategy needs to build in stable long-term commitments (e.g., an increasing carbon tax) and dynamic and adaptive policy instruments.
Structural uncertainties in transitions: Policies and instruments
Examples of structural uncertainties in transitions are numerous and concern all mitigation options usually considered in decarbonization pathways, including energy efficiency, energy decarbonization, and end-use electrification. In discussing the capacity of different policies and economic instruments to achieve predefined quantified targets, I aim to demonstrate that uncertainties inherent to the effectiveness and efficiency of the policies and instruments addressing each decarbonization pillar lead to specific dynamic management issues.
With regard to reducing energy demand, the main issue is how to bridge the “energy efficiency gap.” Even if energy-efficiency improvements are justified from a standard cost-benefit analysis, such operations are difficult to trigger in real life, due to the short horizons of decision-makers, substantial transaction costs, and funding difficulties.
Uncertainties related to energy decarbonization concern all low-carbon technologies. Maintaining a high level of incentives for a rapid development of renewables can quickly become unsustainable unless cost-competitiveness is reached fairly rapidly. Focusing on nuclear energy would also require removing significant barriers. The increasing size and complexity of third-generation nuclear plants led to significant delays in the building of the first projects in Finland and France, delays already manifesting in the second generation’s steadily rising costs. Expected costs for future third-generation projects are rising and compare unfavorably to alternative power-generation options. These difficulties will have to be overcome while keeping the desired level of safety, notwithstanding the commonly raised issues of waste management, potential occurrence of large-scale accidents or terrorist attacks, and social acceptability. The development of carbon capture and storage (CCS) and, more particularly, bioenergy with CCS (BECCS) is also subject to major uncertainties. The risk that these technologies will not be ready on time or will prove incapable of ramping up to industrial deployment capability needs to be considered.
The third pillar concerns the electrification of end-uses, and particularly the diffusion of electric and hybrid vehicles. The introduction of incentives for electric vehicles may stimulate sales, but it may also endanger public finances if sales of electric vehicles take off rapidly. A substantial and lasting reduction in the payback period would thus require both technical advances and a steep rise in gasoline prices.
In this respect, most options for decarbonization and their respective policies are characterized by uncertainties about their capacity to reach an adequate deployment level: for example, R&D may fail to deliver next-generation nuclear reactors or CCS technologies at competitive costs or on time. For other options, including renewable development, electrification of end-uses, or final energy demand reduction, the main technologies are already available and supply-side uncertainty is therefore much smaller, but there is uncertainty about how quickly these technologies will be deployed, given the behavioral responses of consumers and firms. There is, however, a diversified portfolio of options here (including solar energy, wind energy, biomass, building retrofit, industrial efficiency, and lifestyle changes) to achieve overall targets even when a single element may fail to deliver to the expected extent. Relying on a large number of different strategies and technologies helps preserve future options. The performance of policies may also be limited by the economic burden that subsidies and incentives will represent if costs do not decrease fast enough, or by a lack of accompanying policies addressing noneconomic barriers. The specifics of each decarbonization option and its combinations need to be considered when integrating dynamic management issues into a decarbonization strategy.
Propositions for an adaptive long-term strategy
An adaptive pathway strategy designed to achieve a full deep decarbonization energy transition in only three or four decades should combine long-lived incentives and adaptive policies. If only adaptive policies are chosen, actors may modify their expectations in negative ways associated with a “wait and see” attitude.
Long-term regulatory certainty plays a major role in minimizing investment risks in low-carbon technologies. The implementation of a preestablished increasing economy-wide carbon tax as a central price signal allows consumers and investors to form stable expectations regarding the evolution of relative energy prices between fossil fuels and carbon-free energies.
The preestablished increasing trajectory of the carbon tax will be included in investment decisions for long-lived equipment and favor carbon-free solutions when households decide to buy a new car, or to encourage investment in renewable energy rather than thermal production facilities. This will pull and accelerate innovation in carbon-free technologies and favor the development of new infrastructure.
Beyond this economic signal, other sectoral instruments and policies will be needed to address capital costs, insurance premiums, certification of alternative technologies, structure of tax systems, land pricing, road pricing, and other transport regulations. Such policies will be deployed and adjusted under national constraints imposed by numerous non-energy-related objectives, such as reducing government debt levels, enhancing economic activity, and investing in the context of economic recession or depression, high unemployment, and stagnating or declining household purchasing power.
Given this general framework, uncertainty can be managed by distinguishing three categories of actions: (1) policies that are common to many pathways, at least during the initial launching phase; (2) policies that are constrained by severe inertia and delays in response or deployment, for which allowance must be made in the timing of decisions; and (3) policies that preserve future freedom of choice, yielding high option value.
Subject to these guidelines, all the scenarios involve rolling out policies to enhance energy efficiency and decarbonize final energy. Leading up to 2030, such policies must be deployed with approximately the same high level of intensity in most scenarios: they are thus robust options to be prioritized. For the energy-efficiency and distributed-renewable-energy solutions, the roll-out time is only one or two years, starting from the decision to invest. This makes it possible to follow effective ramp-up, which must be achieved with sufficient speed and volume. As a consequence, it is necessary to trigger a large number of investment decisions by a very large number of decision-makers. A bonus-malus tariff scheme to enhance the penetration of clean vehicles and discourage the purchase of high-CO2-emitting cars, or feed-in-tariff systems to support renewable energies are examples of such adaptive policies. The level of support can be adapted periodically to take into account the decrease in investment costs and the impact on public finance or on energy-service prices.
The supply-side options for large generating facilities and the development of networks and storage infrastructures pose a problem of a very different nature. Such investments are often very large and indivisible, with long lead and payback times. In addition, they are in many respects irreversible. The real-option approach can be a good methodology for exploring these issues. Real-options theory is an approach for economic valuation of projects under uncertainty. It focuses on the managerial flexibility (the “option”) value to optimally respond to a changing scenario characterized by uncertainty. Investment decisions should consequently take into account the capacity of actions to generate option value to acquire more information and broaden the scope of possible future outcomes. In the case of a trajectory in which CCS or third-generation nuclear power play a significant role, the option value methodology can be really useful, given uncertainties surrounding the availability and cost competitiveness of such technologies. it assesses the extent to which it is possible to postpone the decision on whether or not to keep these technologies as options in the decarbonization path, taking into account assumptions about the information that the future will provide on the cost and technical evolution not only of these technologies but also of other decarbonized technologies and decarbonization pillars.
Framework for a monitoring process
The implementation of the decarbonization trajectory and the possible need for an adjustment of the trajectory should rely on a monitoring process.
The trajectory considered the most desirable is characterized by structural (nuclear phaseout, X% renewables and Y% of final energy reduction in 2050, for example) and sectoral objectives. The monitoring process will make it possible to monitor the adequacy of the trajectory followed over the years with the sectoral objectives. To do so, it should rely on the translation of sectoral targets in a timetable of subsectoral targets (e.g., number of sales of electric vehicles, amount of additional capacity in photovoltaic power generation each year) and their induced GHG emission reductions.
The set of adaptive policies implemented will be periodically assessed (e.g., each year) according not only to their efficiency in reaching these subsectoral targets but also to a set of structural nonclimate priorities (e.g., energy security, energy poverty, industrial competitiveness, energy prices for consumers). Specific assessment indicators will be developed.
They will help identify whether additional actions are needed. These can be either corrective actions if an adjustment of the policy is considered enough, or a deeper reassessment if the policy is judged to need redesign or a new sectoral target needs to be defined.
This essay has proposed a framework for addressing dynamic management issues related to decarbonization pathways in order to limit the need for adjustment, and its cost, over time. When choosing a pathway as more desirable, it is important to keep in mind that each decarbonization option relies on the implementation of specific policies and instruments. However, given structural effectiveness and timing uncertainties specific to each policy option, they may fail to deliver the expected outcomes in time. The possibility of diverging from one decarbonization trajectory to another without incurring excessive costs should therefore be a strategic element in the design of an appropriate decarbonization strategy. Such an adaptive pathway strategy should combine long-lived incentives to form consistent expectations, as well as adaptive policies.
This essay has proposed the first elements of a monitoring process for addressing dynamic management issues (for more details, see Mathy et al. 2016). The framework for addressing such dynamic management issues in long-term decarbonization pathways needs further operational research. The closure of a decarbonization option’s window of opportunity must be foreseen early enough that other decarbonization options can be deployed. These research questions are of special interest and urgency following the Paris Agreement, which calls on all countries to monitor the implementation of their national contributions and review their ambition regularly.
Mathy, S., P. Criqui, K. Knoop, M. Fischedick, and S. Samadi. 2016. “Uncertainty Management and the Dynamic Adjustment of Deep Decarbonization Pathways.” Climate Policy 16 (supp. 1): S47–S62.
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