Population, uncertainty, and learning in climate change decision analysis

The prospect of learning about various uncertainties relevant to analyses of the climate change issue is important because it can affect estimates of the costs of both damages and mitigation, and it can influence the optimal timing of emissions reductions. Baseline scenarios representing future emissions in the absence of mitigation are one of the major sources of uncertainty. Here we investigate how fast we might realistically expect to learn about the outlook for long-term population growth, as one determinant of future baseline emissions. That is, we estimate how long it might take to substantially revise current estimates of the likelihood of various population size outcomes over the twenty-first century. We draw on recent work showing that, because population growth is path dependent, we can learn about the long term outlook by waiting to observe how population changes in the short term. We then explore the implications of uncertainty and of this learning potential for mitigation costs and for optimal emissions. Using a simple model, we show that uncertainty in population growth translates into an uncertainty in the optimal tax rate of about $200/tC by 2050 for a range of stabilization levels. When learning is taken into account, it allows for mitigation strategies to change in response to new information, leading to a slight reduction in the expected value of mitigation costs, and a substantial reduction in the likelihood of high cost outcomes. We also find that while learning can lead to large revisions over the next few decades in anticipated population growth, this potential does not imply large changes in near-term optimal emissions reductions. Results suggest that further work on the potential for learning about other determinants of emissions could have larger effects on expected mitigation costs.     

Optimal mitigation strategies with negative emission technologies and carbon sinks under uncertainty

In recent years a body of literature has arisen on the topic of how to compose the optimal portfolio of mitigation options. The focus has been mainly on options involving shifts from high- to low- or even negative-carbon technologies. Natural sinks play an important role in any attempt to stabilize atmospheric CO₂ and usually enter as a constant term in the overall carbon budget. In this paper, we introduce natural sinks to the carbon management problem and analyze the implications for negative emission technology deployment and the overall mitigation strategy. Amongst other sensitivity analyses, we also investigate the impact of uncertainty in the carbon sink, which we find to raise the importance of negative emissions in the mitigation portfolio significantly lowering the cost of the policy mix.     

Preserving the Ocean Circulation: Implications for Climate Policy

Climate modelers have recognized the possibility of abrupt climate changes caused by a reorganization of the North Atlantic's current pattern (technically known as a thermohaline circulation collapse). This circulation system now warms north-western Europe and transports carbon dioxide to the deep oceans. The posited collapse of this system could produce severe cooling in northwestern Europe, even when general global warming is in progress. In this paper we use a simple integrated assessment model to investigate the optimal policy response to this risk. Adding the constraint of avoiding a thermohaline circulation collapse would significantly reduce the allowable greenhouse gas emissions in the long run along an optimal path. Our analysis implies that relatively small damages associated with a collapse (less than 1% of gross world product) would justify a considerable reduction of future carbon dioxide emissions.     

Economics and the ‘greenhouse effect’

There is growing scientific and public concern that increasing concentrations of greenhouse gases in the atmosphere will produce global warming and other climatic changes. Although economic activity is the main source of greenhouse gas emissions, information and incentive problems make it difficult to translate concern about global warming into economic behaviour and policy conducive to reducing emissions. The paper considers a set of near term (carbon tax), intermediate term (afforestation, energy efficiency) and long term (new non-fossil fuel technologies) strategies for reducing CO₂ in the atmosphere. Each strategy has useful attributes, but shortcomings or limitations too. While the near term and intermediate term strategies can slow and perhaps reverse the growth of CO₂ emissions, only a successful long term strategy of fostering the development of some promising non-fossil fuel technologies, such as solar and solar-hydrogen, can eventually halt the build-up of CO₂ in the atmosphere. Moreover, public investment in the development of new non-fossil fuel technologies would largely obviate the information and incentive problems that currently stand in the way of an economically viable greenhouse policy.     

The economics of inaction on climate change: a sensitivity analysis

Abstract

Economic models of climate change often take the problem seriously, but paradoxically conclude that the optimal policy is to do almost nothing about it. We explore this paradox as seen in the widely used DICE model. Three aspects of that model, involving the discount rate, the assumed benefits of moderate warming, and the treatment of the latest climate science, are sufficient to explain the timidity of the model's optimal policy recommendation. With modifications to those three points, DICE shows that the optimal policy is a much higher and rapidly rising marginal carbon price; and that higher carbon price has a greater effect on physical measures of climate impacts. Our modifications exhibit nonlinear interactions; at least at low discount rates, there is synergy between individual changes to the model. At low discount rates, the inherent uncertainty about future damages looms larger in the analysis, rendering long-run economic modelling less useful. Our analysis highlights the sensitivity of the model to three debatable assumptions; it does not, and could not, lead to a more reliably ‘optimal’ cost of carbon. Cost-effectiveness analysis, focusing on the generally shorter-term cost side of the problem, reduces the economic paradoxes of the long run, and may make a greater contribution than economic optimization modelling.     

Sensitivity Study of Optimal CO2 Emission Paths Using a Simplified Structural Integrated Assessment Model (SIAM)

A structurally highly simplified, globally integrated coupled climate-economic costs model SIAM (Structural Integrated Assessment Model) is used to compute optimal paths of global CO₂ emissions that minimize the net sum of climate damage and mitigation costs. The model is used to study the sensitivity of the computed optimal emission paths with respect to various critical input assumptions. The climate module is represented by a linearized impulse-response model calibrated against a coupled ocean-atmosphere general circulation climate model and a three-dimensional global carbon-cycle model. The cost terms are represented by strongly simplified expressions designed for maximal transparency with respect to sensitive input assumptions. These include the discount rates for mitigation and damage costs, the inertia of the socio-economic system, and the dependence of climate damages on the change in temperature and the rate of change of temperature. Different assumptions regarding these parameters are believed to be the cause of the marked divergences of existing cost-benefit analyses based on more sophisticated economic models. The long memory of the climate system implies that very long time horizons of several hundred years need to be considered to optimize CO₂ emissions on time scales relevant for a policy of sustainable development. Cost-benefit analyses over shorter time scales of a century or two can lead to dangerous underestimates of the long term climatic impact of increasing greenhouse-gas emissions. To avert a major long term global warming, CO₂ emissions need to be reduced ultimately to very low levels. However, the draw-down can be realized as a gradual transition process over many decades and even centuries. This should nevertheless not be interpreted as providing a time cushion for inaction: the transition becomes more costly the longer the necessary mitigation policies are delayed. However, the long time horizon provides adequate flexibility for later adjustments. Short term energy conservation alone is insufficient and can be viewed only as a useful measure in support of the necessary long term transition to carbon-free energy technologies. For standard climate damage cost expressions, optimal emission paths limiting long term global warming to acceptable sustainable development levels are recovered only if climate damage costs are not significantly discounted. Discounting of climate damages at normal economic rates yields emission paths that are only weakly reduced relative to business as usual scenarios, resulting in high global warming levels that are incompatible with the generally accepted requirements of sustainable development. The solutions are nevertheless logically consistent with the underlying discounting assumption, namely that the occurrence of global warming damages in the distant future as a result of present human activities is of negligible concern today. It follows that a commitment to long term sustainable development, if it in fact exists, should be expressed by an intertemporal relation for the value of the earth's future climate which does not degrade significantly over the time horizon relevant for climate change. Since the future climate is a common assett whose value cannot be determined on the market, the appropriate discount rate for future climate damages should be determined by an assessment of the public willingness to pay today for the mitigation of future climate change. To translate our general conclusions into quantitative cost estimates required by decision makers, the present exploratory study needs to be extended using more detailed disaggregated climate damage and mitigation cost estimates and more realistic socio-economic models, including multi-actor interactions, inherent variability, the role of uncertainty and adaptive control strategies.     

The safe carbon budget

Cumulative emissions drive peak global warming and determine the carbon budget needed to keep temperature below 2 or 1.5 °C. This safe carbon budget is low if uncertainty about the transient climate response is high and risk tolerance (willingness to accept risk of overshooting the temperature target) is low. Together with energy costs, this budget determines the optimal carbon price and how quickly fossil fuel is abated and replaced by renewable energy. This price is the sum of the present discounted value of all future losses in aggregate production due to emitting one ton of carbon today plus the cost of peak warming that rises over time to reflect the increasing scarcity of carbon as temperature approaches its upper limit. If policy makers ignore production losses, the carbon price rises more rapidly. If they ignore the peak temperature constraint, the carbon price rises less rapidly. The alternative of adjusting damages upwards to factor in the peak warming constraint leads initially to a higher carbon price which rises less rapidly.     

Carbon co-benefits of tighter SO2 and NOx regulations in China

Air pollution has been recognized as a significant problem in China. In its Twelfth Five Year Plan, China proposes to reduce SO₂ and NO_x emissions significantly, and here we investigate the cost of achieving those reductions and the implications of doing so for CO₂ emissions. We extend the analysis through 2050, and either hold emissions policy targets at the level specified in the Plan, or continue to reduce them gradually. We apply a computable general equilibrium model of the Chinese economy that includes a representation of pollution abatement derived from detailed assessment of abatement technology and costs. We find that China's SO₂ and NO_x emissions control targets would have substantial effects on CO₂ emissions leading to emissions savings far beyond those we estimate would be needed to meet its CO₂ intensity targets. However, the cost of achieving and maintaining the pollution targets can be quite high given the growing economy. In fact, we find that the near term pollution targets can be met while still expanding the use of coal, but if they are, then there is a lock-in effect that makes it more costly to maintain or further reduce emissions. That is, if firms were to look ahead to tighter targets, they would make different technology choices in the near term, largely turning away from increased use of coal immediately.     

Using the social cost of carbon to value earth observing systems

The goal of this study is to show how to quantify the benefits of accelerated learning about key parameters of the climatic system and use this knowledge to improve decision-making on climate policy. The US social cost of carbon (SCC) methodology is used in innovative ways to value new Earth observing systems (EOSs). The study departs from the strict US SCC methodology, and from previous work, in that net benefits are used instead of only damages to calculate the value of information of the enhanced systems. In other respects the US SCC methodology is followed closely. We compute the surfeit expected net benefits of learning the actionable information earlier, with the enhanced system, versus learning later with existing systems. The enhanced systems are designed to give reliable information about climate sensitivity on accelerated timescales relative to existing systems; therefore, the decision context stipulates that a global reduced emissions path would be deployed upon receiving suitable information on the rate of temperature rise with a suitable level of confidence. By placing the enhanced observing system in a decision context, the SCC enables valuing this system as a real option.

Policy relevance

Uncertainty in key parameters of the climatic system is often cited as a barrier for near-term reductions of carbon emissions. It is a truism among risk managers that uncertainty costs money, and its reduction has economic value. Advancing policy making under uncertainty requires valuing the reduction in uncertainty. Using CLARREO, a new proposed EOS,as an example, this article applies value of information/real option theory to value the reduction of uncertainty in the decadal rate of temperature rise. The US interagency social cost of carbon directive provides the decision context for the valuations. It is shown that the real option value of the uncertainty reduction, relative to existing observing systems, is a very large multiple of the new system's cost.     

Climate agreements based on responsibility for global warming: Periodic updating,policy choices,and regional costs

It has been suggested that calculations of historical responsibility for global warming should be used to distribute mitigation requirements in future climate agreements. For a medium-term mitigation scenario, we calculate regional mitigation costs resulting from global allocation schemes based on the Brazilian Proposal that solely incorporate historical responsibility as a burden sharing criterion. We find that they are likely to violate ability-to-pay principles. In spite of less stringent abatement requirements, developing country regions experience cost burdens (as a percentage of GDP) in the same range as those of developed countries. We also assess the policy options available for calculating historical responsibility. The periodic updating of responsibility calculations over time, concerns over the robustness and availability of emissions data, and the question of whether past emissions were knowingly harmful, may lead to policy choices that increase the relative historical responsibility attributed to developing countries. This, in turn, would increase their mitigation cost burden.     

Risk mitigation and the social cost of carbon

The social cost of carbon – i.e., the marginal present-value cost imposed by greenhouse gas emissions – is determined by a complex interaction between factual assumptions, modeling methods, and value judgments. Among the most crucial factors is society's willingness to tolerate potentially catastrophic environmental risks. To explore this issue, the present analysis employs a stochastic climate–economy model that accounts for uncertainties in baseline economic growth, baseline emissions, greenhouse gas mitigation costs, carbon cycling, climate sensitivity, and climate change damages. In this model, preferences are specified to reflect the high degree of risk aversion revealed by private investment decisions, signaled by the large observed gap between the average rates of return paid by safe and risky financial instruments. In contrast, most climate–economy models assume much lower risk aversion. Given high risk aversion, the analysis finds that investment in climate stabilization yields especially large net benefits by forestalling low-probability threats to long-run human well-being. Accordingly, the social cost of carbon attains the markedly high value of $25,700 per metric ton of carbon dioxide in a baseline scenario in which emissions are unregulated. This value falls to just $4 per ton as the stringency of control measures is successively increased. These results cast doubt on the idea that the social cost of carbon takes on a uniquely defined, objective value that is independent of policy decisions. This does not, however, rule out the use of carbon prices to achieve the benefits of climate stabilization using least-cost mitigation measures.     

Delayed action and uncertain stabilisation targets. How much will the delay cost?

Despite the growing concern about actual on-going climate change, there is little consensus on the scale and timing of actions needed to stabilise the concentrations of greenhouse gases. Many countries are unwilling to implement mitigation strategies, at least in the short term, and no agreement on an ambitious global stabilisation target has yet been reached. It is thus likely that international climate policies will be characterized by a high degree of uncertainty over the stringency of the climate objective, and that some countries might delay their participation to global action. What additional economic costs will this delay in the adoption of mitigation measures imply? What would the optimal short-term strategy be given the uncertainty surrounding the climate policy to come? Is there a hedging strategy that decision makers can adopt to cope with delayed action and uncertain targets? This paper addresses these questions by quantifying the economic implications of delaying mitigation action, and by computing the optimal abatement strategy in the presence of uncertainty about a global stabilisation target (which will be agreed upon in future climate negotiations). Results point to short-term inaction as the key determinant for the economic costs of ambitious climate policies. They also indicate that there is an effective hedging strategy that could minimise the cost of climate policy uncertainty over the global stabilisation target: a short-term moderate climate policy would be a good strategy to reduce the costs of delayed action and to cope with uncertainty about the outcome of future climate negotiations. By contrast, failing to curb emissions in the short term imposes rapidly increasing additional costs of compliance.     

Carbon capture and storage: combining economic analysis with expert elicitations to inform climate policy

The relationship between R&D investments and technical change is inherently uncertain. In this paper we combine economics and decision analysis to incorporate the uncertainty of technical change into climate change policy analysis. We present the results of an expert elicitation on the prospects for technical change in carbon capture and storage. We find a significant amount of disagreement between experts, even over the most mature technology; and this disagreement is most pronounced in regards to cost estimates. We then use the results of the expert elicitations as inputs to the MiniCAM integrated assessment model, to derive probabilistic information about the impacts of R&D investments on the costs of emissions abatement. We conclude that we need to gather more information about the technical and societal potential for Carbon Storage; cost differences among the different capture technologies play a relatively smaller role.     

Comparative assessment of Japan's long-term carbon budget under different effort-sharing principles

This article assesses Japan's carbon budgets up to 2100 in the global efforts to achieve the 2?°C target under different effort-sharing approaches based on long-term GHG mitigation scenarios published in 13 studies. The article also presents exemplary emission trajectories for Japan to stay within the calculated budget.

The literature data allow for an in-depth analysis of four effort-sharing categories. For a 450?ppm CO₂e stabilization level, the remaining carbon budgets for 2014–2100 were negative for the effort-sharing category that emphasizes historical responsibility and capability. For the other three, including the reference ‘Cost-effectiveness’ category, which showed the highest budget range among all categories, the calculated remaining budgets (20th and 80th percentile ranges) would run out in 21–29 years if the current emission levels were to continue. A 550?ppm CO₂e stabilization level increases the budgets by 6–17 years-equivalent of the current emissions, depending on the effort-sharing category. Exemplary emissions trajectories staying within the calculated budgets were also analysed for ‘Equality’, ‘Staged’ and ‘Cost-effectiveness’ categories. For a 450?ppm CO₂e stabilization level, Japan's GHG emissions would need to phase out sometime between 2045 and 2080, and the emission reductions in 2030 would be at least 16–29% below 1990 levels even for the most lenient ‘Cost-effectiveness’ category, and 29–36% for the ‘Equality’ category. The start year for accelerated emissions reductions and the emissions convergence level in the long term have major impact on the emissions reduction rates that need to be achieved, particularly in the case of smaller budgets.

Policy relevance

In previous climate mitigation target formulation processes for 2020 and 2030 in Japan, neither equity principles nor long-term management of cumulative GHG emissions was at the centre of discussion. This article quantitatively assesses how much more GHGs Japan can emit by 2100 to achieve the 2?°C target in light of different effort-sharing approaches, and how Japan's GHG emissions can be managed up to 2100. The long-term implications of recent energy policy developments following the Fukushima nuclear disaster for the calculated carbon budgets are also discussed.     

Public concern over global warming correlates negatively with national wealth

It has been shown previously that the awareness and concern of the general public about global warming is not only a function of scientific information. Both psychological and sociological factors affect the willingness of laypeople to acknowledge the reality of global warming, and to support climate policies of their home countries. In this paper, I analyse a cross-national dataset of public concern about global warming, utilising data from 46 countries. Based on earlier results at the national and regional level, I expect concern to be negatively correlated to national measures of wealth and carbon dioxide emissions. I find that gross domestic product is indeed negatively correlated to the proportion of a population that regards global warming as a serious problem. There is also a marginally significant tendency that nations’ per capita carbon dioxide emissions are negatively correlated to public concern. These findings suggest that the willingness of a nation to contribute to reductions in greenhouse gas emissions decreases with its share of these emissions. This is in accordance with psychological findings, but poses a problem for political decision-makers. When communicating with the public, scientists ought to be aware of their responsibility to use a language that is understood by laypeople.     

Trade-offs between mitigation costs and temperature change

This paper uses the MERGE integrated assessment model to identify the least-cost mitigation strategy for achieving a range of climate policies. Mitigation is measured in terms of GDP foregone. This is not a benefit-cost analysis. No attempt is made to calculate the reduction in damages brought about by a particular policy. Assumptions are varied regarding the availability of energy-producing and energy-using technologies. We find pathways with substantial reductions in temperature change, with the cost of reductions varying significantly, depending on policy and technology assumptions. The set of scenarios elucidates the potential energy system transformation demands that could be placed on society. We find that policy that allows for “overshoot” of a radiative forcing target during the century results in lower costs, but also a higher temperature at the end of the century. We explore the implications of the costs and availability of key mitigation technologies, including carbon capture and storage (CCS), bioenergy, and their combination, known as BECS, as well as nuclear and energy efficiency. The role of “negative emissions” via BECS in particular is examined. Finally, we demonstrate the implications of nationally adopted emissions timetables based on articulated goals as a counterpoint to a global stabilization approach.     

Learning about climate change and implications for near-term policy

Climate change is an issue of risk management. The most important causes for concern are not the median projections of future climate change, but the low-probability, high-consequence impacts. Because the policy question is one of sequential decision making under uncertainty, we need not decide today what to do in the future. We need only to decide what to do today, and future decisions can be revised as we learn more. In this study, we use a stochastic version of the DICE-99 model (Nordhaus WD, Boyer J (2000) Warming the world: economic models of global warming. MIT Press, Cambridge, MA, USA) to explore the effect of different rates of learning on the appropriate level of near-term policy. We show that the effect of learning depends strongly on whether one chooses efficiency (balancing costs and benefits) or cost-effectiveness (stabilizing at a given temperature change target) as the criterion for policy design. Then, we model endogenous learning by calculating posterior distributions of climate sensitivity from Bayesian updating, based on temperature changes that would be observed for a given true climate sensitivity and assumptions about errors, prior distributions, and the presence of additional uncertainties. We show that reducing uncertainty in climate uncertainty takes longer when there is also uncertainty in the rate of heat uptake by the ocean, unless additional observations are used, such as sea level rise.     

Optimal growth with adaptation to climate change

We find that approximately a quarter of the world’s productive capital could be sensitive to climate; therefore, this capital faces the risk of accelerated obsolescence in a world warming by an average of 0.2 °C per decade. We examine the question of optimal adaptation to climate change in a vintage capital growth model without uncertainty. Along the optimal pathway, adaptation is proactive with an anticipation period of approximately twenty years. While there is additional investment in this scenario compared with a no-climate-change baseline, the overall cost to adapt is low relative to the potential losses from maladaptation. Over-investment in protection capital allows the economy to be consistently well-adapted to climate; thus, such a policy prevents transient maladaptation costs. Sensitivity analysis with an integrated assessment model suggests that costs could be ten times larger if adaptation only begins after vulnerable sectors are impacted.     

Impact of climate change on Pacific Northwest hydropower

The Pacific Northwest (PNW) hydropower resource, central to the region’s electricity supply, is vulnerable to the impacts of climate change. The Northwest Power and Conservation Council (NWPCC), an interstate compact agency, has conducted long term planning for the PNW electricity supply for its 2005 Power Plan. In formulating its power portfolio recommendation, the NWPCC explored uncertainty in variables that affect the availability and cost of electricity over the next 20 years. The NWPCC conducted an initial assessment of potential impacts of climate change on the hydropower system, but these results are not incorporated in the risk model upon which the 2005 Plan recommendations are based. To assist in bringing climate information into the planning process, we present an assessment of uncertainty in future PNW hydropower generation potential based on a comprehensive set of climate models and greenhouse gas emissions pathways. We find that the prognosis for PNW hydropower supply under climate change is worse than anticipated by the NWPCC’s assessment. Differences between the predictions of individual climate models are found to contribute more to overall uncertainty than do divergent emissions pathways. Uncertainty in predictions of precipitation change appears to be more important with respect to impact on PNW hydropower than uncertainty in predictions of temperature change. We also find that a simple regression model captures nearly all of the response of a sequence of complex numerical models to large scale changes in climate. This result offers the possibility of streamlining both top-down impact assessment and bottom-up adaptation planning for PNW water and energy resources.