Expert views - and disagreements - about the potential of energy technology R&D

Mitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations.     

Economic consequences of the US withdrawal from the Kyoto/Bonn Protocol

Abstract

The US decision not to ratify the Kyoto Protocol and the recent outcomes of the Bonn and Marrakech Conferences of the Parties have important implications for both the effectiveness and the efficiency of future climate policies. Among these implications, those related with technical change and with the functioning of the international market for carbon emissions are particularly relevant, because these variables have the largest impact on the overall abatement cost to be borne by Annex B countries in the short and in the long run. This paper analyses the consequences of the US decision to withdraw from the Kyoto/Bonn Protocol both on technological innovation and on the price of emission permits (and, as a consequence, on abatement costs). In particular, the analysis highlights mechanisms and feedbacks related to technological innovation, technological spillovers and R&D which could be relevant and which modify some policy relevant conclusions. First, we identify two feedback effects which explain why our results lead to a less significant fall in the price of permits than in most empirical analyses recently circulated. We show that the US defection from the Kyoto Protocol, by inducing a decline in the demand and price of emission permits, lowers the incentives to undertake energy-saving R&D. As a consequence, emissions increase and feed back on the demand and supply of permits, thus implying a lower decline in the price of permits than previously estimated. At the same time, as a result of the reduced R&D investments and the augmented emissions, climate change damages intensify and require an increase in investments that are again coupled with a growth of emissions. By thus again increasing the demand for permits and reducing their supply, this effect enhances the previous mechanism. Notwithstanding the lower decline in the price of permits, the paper still identifies a smaller price than would occur with a US participation. Therefore, we emphasise in a second step the crucial role of Russia in climate negotiations due to a large increase in Russia's bargaining power.     

Economic consequences of the US withdrawal from the Kyoto/Bonn Protocol

The US decision not to ratify the Kyoto Protocol and the recent outcomes of the Bonn and Marrakech Conferences of the Parties have important implications for both the effectiveness and the efficiency of future climate policies. Among these implications, those related with technical change and with the functioning of the international market for carbon emissions are particularly relevant, because these variables have the largest impact on the overall abatement cost to be borne by Annex B countries in the short and in the long run. This paper analyses the consequences of the US decision to withdraw from the Kyoto/Bonn Protocol both on technological innovation and on the price of emission permits (and, as a consequence, on abatement costs). In particular, the analysis highlights mechanisms and feedbacks related to technological innovation, technological spillovers and R&D which could be relevant and which modify some policy relevant conclusions. First, we identify two feedback effects which explain why our results lead to a less significant fall in the price of permits than in most empirical analyses recently circulated. We show that the US defection from the Kyoto Protocol, by inducing a decline in the demand and price of emission permits, lowers the incentives to undertake energy-saving R&D. As a consequence, emissions increase and feed back on the demand and supply of permits, thus implying a lower decline in the price of permits than previously estimated. At the same time, as a result of the reduced R&D investments and the augmented emissions, climate change damages intensify and require an increase in investments that are again coupled with a growth of emissions. By thus again increasing the demand for permits and reducing their supply, this effect enhances the previous mechanism. Notwithstanding the lower decline in the price of permits, the paper still identifies a smaller price than would occur with a US participation. Therefore, we emphasise in a second step the crucial role of Russia in climate negotiations due to a large increase in Russia’s bargaining power.     

Engagement in the Third U.S. National Climate Assessment: commitment,capacity, and communication for impact

This paper examines the dynamics of energy investments and clean energy Research and Development (R&D) using a scenario-based modeling approach. Starting from the global scenarios proposed in the RoSE model ensemble experiment, we analyze the dynamics of investments under different assumptions regarding economic and population growth as well as availability of fossil fuel resources, in the absence of a climate policy. Our analysis indicates that economic growth and the speed of income convergence across countries matters for improvements in energy efficiency, both via dedicated R&D investments but mostly through capital-energy substitution. In contrast, fossil fuel prices, by changing the relative competitiveness of energy sources, create an economic opportunity for radical innovation in the energy sector. Indeed, our results suggest that fossil fuel availability is the key driver of investments in low carbon energy innovation. However, this innovation, by itself, is not sufficient to induce emission reductions compatible with climate stabilization objectives.     

Innovation benefits from nuclear phase-out: can they compensate the costs?

This paper investigates whether an inefficient allocation of abatement due to constraints on the use of currently available low carbon mitigation options can promote innovation in new technologies and have a positive impact on welfare. We focus on the case of a nuclear power phase-out and endogenous technical change in energy efficiency and alternative low carbon technologies. The research is inspired by the re-thinking about nuclear power deployment which took place in some countries, especially in Western Europe, after the Fukushima accident in March 2011. The analysis uses an Integrated Assessment Model, WITCH, which features multiple externalities related to greenhouse gas emissions and innovation market failures. Our results show that phasing out nuclear power stimulates R&D investments and deployment of technologies with large learning potential. The resulting technology benefits that would not otherwise occur due to intertemporal and international externalities almost completely offset the economic costs of foregoing nuclear power. The extent of technology benefits depends on the stringency of the climate policy and is distributed unevenly across countries.     

Modeling endogenous learning and imperfect competition effects in climate change economics

In this two-part paper we evaluate the effect of “endogenizing” technological learning and strategic behavior of agents in economic models used to assess climate change policies. In the first part we show the potential impact of R&D policies or demonstration and deployment (D&D) programs in the context of stringent stabilization scenarios. In the second part we show how game-theoretic methods can be implemented in climate change economic models to take into account three types of strategic interactions: (i) the market power of the countries benefiting from very low abatement costs on international markets for CO₂ emissions, (ii) the strategic behavior of governments in the domestic allocation of CO₂ emissions quotas, and (iii) the non-cooperative behavior of countries and regions in the burden sharing of CO₂ concentration stabilization. The two topics of endogenous learning and game-theoretic approach to economic modeling are two manifestations of the need to take into account the strategic behavior of agents in the evaluation of climate change policies. In the first case an R&D policy or a demonstration and deployment (D&D) program are put in place in order to attain a cost reduction through the learning effect; in the second case the agents (countries) reply optimally to the actions decided by the other agents by exploiting their strategic advantages. Simulations based on integrated assessment models illustrate the approaches. These studies have been conducted under the Swiss NCCR-Climate program.     

Optimal Technology R&D in the Face of Climate Uncertainty

This paper explores optimal near-term technology R&D in the face of uncertain damages caused by the buildup of greenhouse gases. The paper puts particular emphasis on understanding how optimal near-term R&D expenditures might vary based on the technologies pursued in the R&D program. The exploration is conducted in the context of varying impacts from R&D on the global abatement cost function. The R&D planning problem is considered first within a theoretical framework and is then pursued in a stylized application using the DICE model. The paper provides intuition into the circumstances under which near-term technology R&D might increase or decrease under uncertainty, thereby serving as a hedge against climate uncertainty.     

The influence of negative emission technologies and technology policies on the optimal climate mitigation portfolio

Combining policies to remove carbon dioxide (CO₂) from the atmosphere with policies to reduce emissions could decrease CO₂ concentrations faster than possible via natural processes. We model the optimal selection of a dynamic portfolio of abatement, research and development (R&D), and negative emission policies under an exogenous CO₂ constraint and with stochastic technological change. We find that near-term abatement is not sensitive to the availability of R&D policies, but the anticipated availability of negative emission strategies can reduce the near-term abatement optimally undertaken to meet 2°C temperature limits. Further, planning to deploy negative emission technologies shifts optimal R&D funding from ??carbon-free?? technologies into ??emission intensity?? technologies. Making negative emission strategies available enables an 80% reduction in the cost of keeping year 2100 CO₂ concentrations near their current level. However, negative emission strategies are less important if the possibility of tipping points rules out using late-century net negative emissions to temporarily overshoot the CO₂ constraint earlier in the century.     

Optimal carbon dioxide abatement and technological change: should emission taxes start high in order to spur R&;D?

Many European politicians argue that the EU should set tougher emission targets than what is required by the Kyoto protocol, and moreover, that emission trading with other countries outside EU should be limited so as to keep emission quota prices high. One of the arguments, frequently cited for such a policy, is the need for technological development. However, the literature on climate change and technological innovation does not unambiguously support the need for setting high emission taxes today. In this paper we investigate the relationship between emission taxes and technological change further by modeling innovation activity explicitly. In our model both the amount of R&D and the amount of carbon abatement are decided in a decentralized way by the market as a response to an emission tax. Moreover, we introduce several distinct failures in the market for new innovations, among others, insufficient patent protection and intertemporal knowledge spill-overs. Our findings suggest that governments should under some circumstances set a higher carbon tax today if we have technological change driven by R&D than if we have pure exogenous technological change. Based on numerical simulations these circumstances are (a) positive intertemporal knowledge spillovers and/or (b) weak patent protection.     

Strategies to adapt to an uncertain climate change

Many decisions concerning long-lived investments already need to take into account climate change. But doing so is not easy for at least two reasons. First, due to the rate of climate change, new infrastructure will have to be able to cope with a large range of changing climate conditions, which will make design more difficult and construction more expensive. Second, uncertainty in future climate makes it impossible to directly use the output of a single climate model as an input for infrastructure design, and there are good reasons to think that the needed climate information will not be available soon. Instead of optimizing based on the climate conditions projected by models, therefore, future infrastructure should be made more robust to possible changes in climate conditions. This aim implies that users of climate information must also change their practices and decision-making frameworks, for instance by adapting the uncertainty-management methods they currently apply to exchange rates or R&D outcomes. Five methods are examined: (i) selecting “no-regret” strategies that yield benefits even in absence of climate change; (ii) favouring reversible and flexible options; (iii) buying “safety margins” in new investments; (iv) promoting soft adaptation strategies, including long-term prospective; and (v) reducing decision time horizons. Moreover, it is essential to consider both negative and positive side-effects and externalities of adaptation measures. Adaptation–mitigation interactions also call for integrated design and assessment of adaptation and mitigation policies, which are often developed by distinct communities.     

Using Decision Analysis to Include Climate Change in Water Resources Decision Making

Is the prospect of possible climate change relevant to water resources decisions being made today? And, if so, how ought that prospect be considered? These questions can be addressed by decision analysis, which we apply to two investments in the Great Lakes region: a regulatory structure for Lake Erie, and breakwaters to protect Presque Isle State Park, PA. These two decisions have the elements that potentially make climate change relevant: long lived, "one shot" investments; benefits or costs that are affected by climate-influenced variables; and irreversibilities. The decision analyses include the option of waiting to obtain better information, using Bayesian analysis to detect whether climate change has altered water supplies. The analyses find that beliefs about climate change can indeed affect optimal decisions. Furthermore, ignoring the possibility of climate change can lead to significant opportunity losses—in the cases here, as much as 10% or more of the construction cost. Yet the consequences of climate uncertainty for Great Lakes management do not appear to be qualitatively different from those of other risks, and thus do not deserve different treatment. The methods of sensitivity analysis, scenario planning, and decision analysis, all of which are encouraged under US federal guidelines for water planning, are applicable. We recommend increased use of decision trees and Bayesian analysis to consider not only climate change risks, but also other important social and environmental uncertainties.     

R&D Subsidies and Climate Policy: Is There a “Free Lunch”?

Because of the long-term nature of the climate problem, technological advances are often seen as an important component of any solution. However, when considering the potential for technology to help solve the climate problem, two market failures exist which lead to underinvestment in climate-friendly R&D: environmental externalities and the public goods nature of new knowledge. As a result, government subsidies to climate-friendly R&D projects are often proposed as part of a policy solution. Using the ENTICE model, I analyze the effectiveness of such subsidies, both with and without other climate policies, such as a carbon tax. While R&D subsidies do lead to significant increases in climate-friendly R&D, this R&D has little impact on the climate itself. Subsidies address the problem of knowledge as a public good, but they do not address the environmental externality, and thus offer no additional incentive to adopt new technologies. Moreover, high opportunity costs to R&D limit the potential role that subsidies can play. While R&D subsidies can improve efficiency, policies that directly affect the environmental externality have a much larger impact on both atmospheric temperature and economic welfare.     

Making sense of the politics in the climate change loss & damage debate

The Warsaw International Mechanism for Loss and Damage (L&D) associated with Climate Change Impacts (WIM) was established in 2013 to advance i) knowledge generation; ii) coordination and iii) support to address losses and damages under the UNFCCC. So far, the work undertaken by the WIM Executive Committee (ExCom) has focused on enhancing understanding and awareness of the issue and promoting collaboration with relevant stakeholders. Delivering on the WIM’s third function on action and support has lagged behind, and ‘the political’ nature of L&D has often been blamed for this. Key terrains of contention among Parties have included the positioning of L&D governance vis-à-vis the adaptation space and struggles around state liability and compensation. As a way to facilitate discussion on implementation options, recent research has suggested de-politicising aspects of the L&D debate; yet we have very little insight into how the politics are understood within the realm of international L&D governance. This paper brings an analysis of ‘the political’ into the picture by identifying the complex and underlying issues that fuel contention within UNFCCC L&D negotiations. It gives centre stage to the way different framings of norms and material interests affect the debate, and challenges the tendency in current L&D literature to overlook the socio-historical and political underpinnings of this area of policy-making. We employ a qualitative multi-methods research design which draws on content analysis of 138 official Parties’ submissions and statements, 14 elite interviews with key current and former L&D negotiators and is built on a foundation of 3 years of participant observation at COPs and WIM meetings. We approach this data with a political ethnographic sensibility that seeks to explore how meanings are constructed within and across different sources of data. Our empirical results show that, rather than being a monolithic dispute, L&D catalyses different yet intertwined unresolved discussions. We identify five areas of contention, including continued disputes around compensation; conflicts on the legitimacy of L&D as a third pillar of climate action; tensions between the technical and political dimension of the debate; debates over accountability for losses and damages incurred; and the connection of L&D with other unresolved issues under the Convention.     

Adapting agriculture to climate change: a review

The agricultural sector is highly vulnerable to future climate changes and climate variability, including increases in the incidence of extreme climate events. Changes in temperature and precipitation will result in changes in land and water regimes that will subsequently affect agricultural productivity. Given the gradual change of climate in the past, historically, farmers have adapted in an autonomous manner. However, with large and discrete climate change anticipated by the end of this century, planned and transformational changes will be needed. In light of these, the focus of this review is on farm-level and farmers responses to the challenges of climate change both spatially and over time. In this review of adapting agriculture to climate change, the nature, extent, and causes of climate change are analyzed and assessed. These provide the context for adapting agriculture to climate change. The review identifies the binding constraints to adaptation at the farm level. Four major priority areas are identified to relax these constraints, where new initiatives would be required, i.e., information generation and dissemination to enhance farm-level awareness, research and development (R&D) in agricultural technology, policy formulation that facilitates appropriate adaptation at the farm level, and strengthening partnerships among the relevant stakeholders. Forging partnerships among R&D providers, policy makers, extension agencies, and farmers would be at the heart of transformational adaptation to climate change at the farm level. In effecting this transformational change, sustained efforts would be needed for the attendant requirements of climate and weather forecasting and innovation, farmer’s training, and further research to improve the quality of information, invention, and application in agriculture. The investment required for these would be highly significant. The review suggests a sequenced approach through grouping research initiatives into short-term, medium-term, and long-term initiatives, with each initiative in one stage contributing to initiatives in a subsequent stage. The learning by doing inherent in such a process-oriented approach is a requirement owing to the many uncertainties associated with climate change.     

Oil prices and energy technology innovation: An empirical analysis

To achieve environmental sustainability and reduce their vulnerability to oil shocks, countries can develop new energy technologies. Technological advances reduce the cost of structural changes in the energy economy, and thus also increase the political feasibility of such changes. But what explains international variation in the form and quality of energy technology innovation? We build on previous theories and offer an integrated account: increasing oil prices reinforce existing sectoral innovation systems, both politically and economically, thus allowing public policymakers and private entrepreneurs to profitably invest in new energy technologies. We test this theoretical argument against data on public R&D expenditures and patents in the domain of renewable energy technology for industrialized countries from 1989 to 2007. We find strong support for the interactive hypothesis. Thus, we contribute to literatures on (i) domestic responses to international shocks, (ii) environmental sustainability and energy security, and (iii) the political economy of technology innovation.     

Technology innovation and diffusion in “less than ideal” climate policies: An assessment with the WITCH model

This paper examines the dynamics of innovation in low-carbon energy technologies distinguishing between research and development and technology diffusion as a response to alternative climate policies. We assess the implications of second-best policies that depart from the assumption of immediate and global participation and of full technology availability. The analysis highlights the heterogeneous effects of climate policy on different energy R&D programs and discusses the contribution of important determinants such as carbon price and policy stringency, policy credibility, policy and technological spillovers and absorptive capacity.     

Mental models of sea-level change: A mixed methods analysis on the Severn Estuary,UK

Global average sea levels are expected to rise by up to a metre by the end of the century. This long-term rise will combine with shorter-term changes in sea level (e.g. high tides, storm surges) to increase risks of flooding and erosion in vulnerable coastal areas. As communities become increasingly exposed to these risks, understanding their beliefs and responses becomes more important. While studies have explored public responses to climate change, less research has focused on perceptions of the specific risks associated with sea-level change. This paper presents the results of a mental models study that addressed this knowledge gap by exploring expert and public perceptions of sea-level change on the Severn Estuary, a threatened coastal environment in the southwest of the United Kingdom. A model was developed from the literature and expert interviews (N = 11), and compared with public perceptions elicited via interviews (N = 20) and a quantitative survey (N = 359). Whilst we find a high degree of consistency between expert and public understandings, there are important differences that have implications for how sea level risks are interpreted and for what are perceived as appropriate mitigation and adaptation practices. We also find a number of potential barriers to engaging with the issue: individuals express low concern about sea-level change in relation to other matters; they feel detached from the issue, seeing it as something that will happen in future to other people; and many perceive that neither the causes of nor responses to sea-level change are their responsibility. We point to areas upon which future risk communications should therefore concentrate.     

What drives the success of reforestation projects in tropical developing countries? The case of the Philippines

In response to substantial deforestation over many decades, large scale reforestation programs are being implemented across many tropical developing countries. Examples include the United Nations Billion Trees Campaign, the National Greening Program in the Philippines, and the 5 million ha reforestation program in Vietnam. However, while substantial investments are being made in reforestation, little information exists on the drivers influencing reforestation success and how these interact to determine environmental and socio-economic outcomes. In this study we surveyed 43 reforestation projects on Leyte Island, The Philippines to identify the drivers that most influence reforestation success as measured by key indicators drawn from the literature, including interactions between drivers and between drivers and indicators. We investigated 98 potential success drivers, including technical and biophysical factors; socio-economic factors; institutional, policy and management factors; and reforestation project characteristics. We also measured 12 success indicators, including forest establishment, forest growth, environmental and socio-economic success indicators. Stepwise multiple regressions were used to identify significant relationships among drivers and indicators and this analysis was used to develop a system of driver and indicator relationships. Based on this we found that revegetation method, funding source, education and awareness campaigns, the dependence of local people on forests, reforestation incentives, project objectives, forest protection mechanisms and the condition of road infrastructure were highly connected drivers that influenced multiple success indicators either directly or indirectly. We conclude that policies targeting revegetation methods, socioeconomic incentives, forest protection mechanisms, sustainable livelihoods, diversification of funding and partnerships, technical support, and infrastructure development are likely to have a broad systemic and beneficial effect on the success of reforestation programs in tropical developing countries.     

Political orientation and climate concern shape visual attention to climate change

Despite the scientific consensus, there is widespread public controversy about climate change. Previous explanations focused on interpretations hampered by political bias or insufficient knowledge of climate facts. We propose that public views of climate change may also be related to an attentional bias at a more basic level of cognitive processing. We hypothesized that selective visual attention towards or away from climate-related information would be associated with climate concern. To test prioritization of climate-related stimuli under conditions of limited attention, we asked participants to identify climate-related and neutral words within a rapid stream of stimuli. Undergraduate students attended to climate-related words more readily than neutral words. This attentional prioritization correlated with self-rated climate concern. We then examined this relationship in a more diverse community sample. Principal component analysis of survey data in the community sample revealed a component indexing a relationship between climate concern and political orientation. That component was correlated with the degree of selective inattention to climate-related words. Our findings suggest that climate-related communications may be most effective if tailored in a manner accounting for how attentional priorities differ between audiences—particularly those with different political orientations.     

How to achieve the 2030 CO2 emission-reduction targets for China's industrial sector: Retrospective decomposition and prospective trajectories

The Chinese government actively follows the low-carbon development pattern and has set the definite targets of reducing carbon emissions by 2030. The industrial sector plays a significant role in China's economic growth and CO₂ emissions. This is the first study to present a specific investigation on the retrospective decomposition (1993–2014) and prospective trajectories (2015–2035) of China's industrial CO₂ emission intensity (ICEI) and industrial CO₂ emissions (ICE), aiming at China Industrial Green Development Plan 2016–2020 targets and China's 2030 CO₂ emission-reduction targets. We introduce process carbon intensity, investment and R&D factors into the decomposition model and make a combination of dynamic Monte Carlo simulation and scenario analysis to identify whether and how the targets would be realized from a sector-specific perspective. The results indicate that investment intensity is the primary driver for the increase in ICEI, while R&D intensity and energy intensity are the leading contributors to the reduction in ICEI. Under existing policies, it is very possible for the industrial sector to achieve the 2020 and 2030 intensity-reduction targets. However, the realization of 2030 emission-peak target has some uncertainties and needs extra efforts in efficiency improvement and structural adjustment. All the five scenarios would achieve the 2020 and 2030 intensity-reduction targets, except Scenario N4 for China Industrial Green Development Plan 2016–2020 target. Nonetheless, only three scenarios would realize the 2030 emission-peak target. With strong efficiency improvement and structural adjustment, ICE would hit the peak in 2025. In contrast, with high/low efficiency improvement and weak structural adjustment, ICE would fail to reach the peak before 2035. Both ICEI and ICE have substantial mitigation potentials with the enhancement of efficiency improvement and structural adjustment. Finally, we suggest that the Chinese government should raise the baseline requirements of efficiency improvement and structural adjustment for the industrial sector to achieve China’s 2030 targets.