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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop 4 Driving Forces and Critical Uncertainties in Adaptation, Vulnerability, and Mitigation DRIVING FORCES AND CRITICAL UNCERTAINTIES IN SCENARIO CONSTRUCTION1 M. Granger Morgan Granger Morgan spoke on the role of driving forces in scenarios. He began by stating the assumption that in principle people really do treat scenarios as though they were forecasts or projections, and he asked how much detail is really needed and whether people would use it if they had it. It is very difficult, for example, to find examples of anyone who really uses all the detail in the Special Report on Emissions Scenarios (SRES). Commenting that representative concentration pathways (RCPs) are a step in the right direction, he emphasized that people are not good at predicting the future of basic parameters, such as primary energy consumption. He suggested thinking about three things: Model switching. Different models are of use for different parameters at different time scales. For example, computable general equilibrium models of the world’s economy might be reasonably believable for a decade or so into the future, but running them out for a century and believing the result is not reasonable. For the far future, doing a bounding analysis may be all that is reasonable. 1 Morgan’s presentation is available at http://www7.nationalacademies.org/hdgc/Importance_of_driving_forces_Presentation_by_Granger_Morgan.pdf [November 2010].
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop Morgan said that he and David Keith have critiqued scenarios on various grounds: detailed story lines fixate people on those particular stories, whereas there are other ways to get to the same end point. Overconfidence is ubiquitous; putting probabilities on scenarios is problematic; and path dependencies—the order in which different changes happen—can make a huge difference. Evidence indicates that consensus processes tend to understate the level of uncertainty, as indicated by individual experts’ judgments. The literature produces a range that is narrower than the judgments of the individual experts. Bounding analysis. An alternative to story lines is to ask people to suggest all the conditions that could lead to very high and very low values of a parameter of interest and have the list reviewed by experts to cull out infeasible conditions and suggest how the extreme values might come to pass. Working the problem backward. If one propagates probability distributions down the causal chain, the uncertainties get huge. An alternative is to go backward on the chain, from outcomes of interest to the paths that could produce them. What possible outcomes do people most care about, and how could they get there? Which things would be problems that need to be addressed and avoided? People have trouble with this method. Research has found stakeholders refusing to do it, because they saw it as unwarranted speculation about bad outcomes. Morgan said that methodological uncertainties in scenarios are often not appreciated. For example, time preference is modeled in ways that do not correspond to what people do, and important feedbacks in physical or socioeconomic systems are sometimes not taken into account. The uncertainties in the methodology can be larger than those that apply to the technical issues. Also, assumptions about who makes the decisions are sources of uncertainty. BRIEF PRESENTATIONS ON SPECIFIC DRIVERS Brian O’Neill spoke about the relationships of demographic drivers and emissions on climate outcomes.2 First, he noted that the relationships between story lines and demographic drivers are often thought to be much more solid than they are. Second, emission scenarios can be consistent with a wide range of demographic drivers. The A2 SRES 2 The presentation is available at http://www7.nationalacademies.org/hdgc/Population_Presentation_by_Brian_ONeill.pdf [November 2010].
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop scenario’s population assumption could as well have been a lot lower, based on O’Neill’s analysis of all the story lines that could produce the same results. One can have quite a lot of variation in emissions for a wide range of possible population levels, with the possible exception that high population may not be consistent with low emissions. His conclusion was that, although demography does matter to emissions, a full range of demographic changes is consistent with a wide range of emission pathways. Gary Yohe spoke about socioeconomic drivers of impacts, adaptation, and vulnerability (IAV).3 He emphasized that IAV is site-specific and path-dependent. He said it is desirable to preserve some degree of internal consistency of local exposure and sensitivity with global portraits and to explore complementarity or conflict between IAV futures and mitigation futures. However, he noted that it is difficult to describe the drivers of the capacity to mitigate or adapt, and it is even harder to describe the link from capacity to action. Yohe identified these determinants of adaptive capacity: availability of options; availability and distribution of resources; human and social capital, governance responsibility, and authority; ability to separate signal from noise; and access to risk-spreading mechanisms. He said that economic models assume the spreading of risk. This list is similar to lists in other fields (e.g., precursors for disease prevention, prerequisites for sustainable development conditions for efficient working of markets). Knowledge is still inadequate, although, for prediction of adaptations or evaluation of efficacy. He noted that there is never a unique sustainable pathway. Internal consistency is important in scenarios, but there are many ways to get to a single end point. Results should be as quantitative as possible and linked to consistent global futures and socioeconomic and climate trajectories. He noted that, even after concentrations peak and temperatures stabilize, some outcomes will continue to evolve. Nebojsa Nakičenovič spoke about technology as a driver. Assumptions about technology are fundamental to the outcomes of scenarios. He noted that technologies have changed lifestyles dramatically several times since the Industrial Revolution and that this is one of the biggest uncertainties there is. He cited Paul Raskin’s argument that technology is not fundamental but a derived driver of change that reflects transformations in culture, governance, etc. He said that the greatest impacts will depend on change in places with high population and low current levels of development, suggesting that it might be useful to map energy access statistics 3 The presentation is available at http://www7.nationalacademies.org/hdgc/Economy_and_Infrastructure_Presentation_by_Gary_Yohe.pdf [November 2010].
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop against population density. Technological learning, in terms of cost of a unit of energy capacity, is often very significant, with costs per unit falling by one or two orders of magnitude. The important changes are not in individual technologies, but in the system, in which the convergence of technologies is a major unknown. He noted that in very low emission scenarios, many energy technologies are treated as though they all will be extremely successful in their evolution, although the real world will be considerably different and messier. He concluded by noting two big gaps in knowledge and analysis: technological change on the adaptation side and the relationships between change in mitigation technology and in adaptation technology. Michael Replogle spoke about the transport sector and regional planning.4 This is perhaps the fastest growing area of greenhouse gas (GHG) emissions, now accounting for about 20 percent of emissions and growing fastest in countries outside the Organisation for Economic Co-operation and Development, particularly India and China. Replogle said that, in those countries, increased efficiency can offset growth in distance traveled. The context for growth in emissions from transport is rapid urbanization and urban income disparity: half the people in the world are still unable to afford vehicles, but vehicle ownership is closely associated with income, although there are differences due to policy and among continents. Most transportation analysis has focused almost entirely on technology strategies; little attention has been paid to strategies to avoid lock-in of motorization, even though it would produce huge benefits and huge negative costs per ton of carbon abatement. Replogle noted that GHG intensity per household is much lower in walkable neighborhoods, indicating that there are high and low carbon paths for urbanization, depending on subsidies for car use, road building, etc. The paradigm for mitigating emissions is to avoid and shorten vehicle trips, shift to more efficient modes, and improve the efficiency of each mode. He identified a series of key driving forces of change in transportation GHG emissions: the pattern of urbanization; growing mobility related to globalization; technological innovation (including the availability of lower carbon vehicles and fuels and advances in information, communication, and automation); energy security and prices; transport security and terrorism; public health and safety issues (e.g., changes in physical activity, air pollution, and traffic accidents); congestion, livability, and economic competitiveness issues; infrastructure and energy finance; and climate change and adaptation, including dislocation and infrastructure 4 The presentation is available at http://www7.nationalacademies.org/hdgc/Transportation_Including_Regional_Planning_Presation_by_Michael_Replogle.pd [November 2010].
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop loss. He noted that, in some countries, increased technical efficiency has been used to increase vehicle size and power rather than to lower emissions per distance. Replogle concluded by pointing out that market failures in transport abound (e.g., in the United States, free parking, $300 billion in motor fuel subsidies, fixed cost insurance pricing). The recent Moving Cooler study (Cambridge Systematics, 2009) concluded that the United States could reduce emissions by 25-40 percent at negative cost per ton, but he questioned whether its governance structures could move in that direction, for example, by following the Singapore model of urbanization and implementing user charges to reduce congestion and regulate vehicles for high performance. Frans Berkhout spoke about policy and institutions, which he defined as rules for collective action. Institutions embody ideas about what is right and codify practices. Berkhout said that there is a need to include political scientists, sociologists, and anthropologists in the Intergovernmental Panel on Climate Change (IPCC) to get these issues considered. Political scientists tend to avoid making predictions, and they are reinforced in this by prominent political surprises, such as the end of the cold war. He noted that putting policy into scenarios presents a dilemma, because the scenarios influence policy. Policy makers often insist on policy-poor scenarios because they want to choose the policies, but policy-poor scenarios look unrealistic. He noted that although policy institutions resist change, there is also huge global institutional diversity. There will be democracies and dictatorships, for example, but systems change from one form to the other at surprising times. There are also different national systems of innovation, but each results from its own history in ways people are unable to predict. He identified four drivers of institutional change: (1) the relative roles of governments and of businesses and other actors in governance; (2) the roles of knowledge, transparency, and accountability; (3) the interdependence of governance systems, including the possibility of learning across places; and (4) cultural norms on the value of nature and attitudes to risk. Each of these things is fairly stable but does undergo change, sometimes suddenly, for reasons that are not well understood. For example, novel institutional forms, such as carbon markets, do emerge. He suggested that the fifth IPCC report could bring expertise on institutions into the process. In a brief discussion, Ferenc Toth noted that climate vulnerability can vary a lot with the same level of economic activity, depending on institutional structure. As an example, he noted the adaptability of farmers in Thailand, who have a high level of autonomy in decision making.
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop Elmar Kriegler spoke about first- and second-best policies.5 A first-best policy removes all market failures, resulting in an economically optimal outcome. A second-best policy optimizes the outcome given the constraint that one (or some) of the market constraints or failures cannot be removed. In the integrated assessment modeling community, the idea of second-best policy is used in a slightly more general sense, to address not only market failures, but also limitations to technological change and adoption and other constraints. For example, if carbon capture and storage is taken off the table because of public opposition or an accident, what would the best policy be? What effect would limited or fragmented participation of some countries have on reaching climate targets? Kriegler presented results of some modeling studies of the costs and capability of reaching certain emissions targets if certain technologies are taken off the table. He noted that there are also market failures in adaptation. For example, there is underprovision of public goods, such as flood protection. Habiba Gitay spoke on ecosystem and water resource issues. She emphasized that drivers are linked, that single drivers can have many impacts, and that many of the drivers interact with climate change in nonlinear ways. Moreover, the ways they affect ecosystems are place-specific. The drivers of change in these systems are also affected by development pathways. The IPCC in the past has not incorporated ecosystem perspectives well. Gitay presented a list of drivers of ecosystem change: urbanization and coastal settlement, including water withdrawals; land use and land cover change; trade, including in cash crops; population distribution; conflict; migration and urbanization; technological changes; policy changes; behavioral change, including values, choices, and resource consumption patterns; and, finally, climate change itself. Gerald Nelson spoke on food, nutrition, and bioenergy issues. He said that increases in population of perhaps 50 percent and increases in income will imply a need for 70-100 percent more food on limited additional arable land. Agriculture also has a significant role in GHG emissions, accounting for 30 percent of emissions if forests are included. The mix of emissions matters. Increasing food production with the same ways of using nitrogen will increase GHG emissions, so there is a need to look to agricultural technology for managing emissions as well as for adaptation. He pointed out that development economists think of land the way they do capital and labor, as resources that can be added to, but that assumption is hitting its limits with respect to land. If land cannot be expanded, the analysis becomes more complicated, and the story changes. Also, the effect of technology is different for the different factors of production. The 5 The presentation is available at http://www7.nationalacademies.org/hdgc/First_and_Second_Best_Policies_Presentation_by_Elmar_Kriegler.pdf [November 2010].
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop private sector has a good incentive to improve the productivity of capital and, to some extent, of labor. But for land and water, it can be much more difficult to capture the returns to improved technology. Agriculturalists are incredibly adaptive, but some crop models give scary results about the effects of temperature increases when they include limits to adaptation in the form of crop growth. Nelson mentioned his recent chapter on biofuels, which argues that they are not a good use of sunlight (Nelson, 2010). He said that nutritionists are rarely concerned about the effects of climate change on nutrition and proposed that this is worth further examination. He concluded with a strong statement about the need for improved data. For example, climate models don’t provide information that is critical for the analysis of agriculture, such as about change in minimum nighttime temperature. Kristie Ebi spoke about health issues. She began by saying that, after age 5, the risk of death from chronic disease is the same worldwide. The big differences in life expectancy are from communicable diseases—upper respiratory infections, diarrheal diseases, malnutrition, and others. She said that these problems are intractable in some areas, and long-term change in gross domestic product (GDP) won’t necessarily solve them. There has been more than a century of malaria control in parts of Africa, with some short-term and local gains but long-term, systemic failure. These things are climate-sensitive, and the health effects mainly involve children. This does not change demography much, but malaria reduces GDP by about 10 percent in Africa. Ebi said that the consequences for health of changes in ecosystem services, water, and agriculture can be noticeable, but it is difficult to tease climate effects out from interacting multiple stresses. The best predictors of life expectancy are simple medical care, education, and access to clean water and adaptation—not GDP. How well countries do depends on the responses of institutions, including the World Health Organization and private nongovernmental organizations. She said that the health sector does not use scenarios, because they don’t show that the world is not reaching the Millennium Development Goals. The scenarios have not been realistic about the health sector. Public health is very different from health care delivery. She noted that in the Soviet Union, public health failed before the country dissolved; by contrast, Cuba has some of the best health care in the world.
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Describing Socioeconomic Futures for Climate Change Research and Assessment: Report of a Workshop DISCUSSION The following issues were raised in the discussion: interactions between mitigation and adaptation in agriculture (e.g., holding more carbon in the soil leads to better water retention, which increases productivity and diversifies sources of income); a need for serious thought to very different worlds with the same radiative forcing, such as one with the entire biosphere managed for biofuels, food, etc., and one in which biosphere performs more traditional ecological roles; the importance of the difficult-to-monetize quantities; large expenditures on cultivars in Africa without investments on agricultural extension to implement them; the need to construct adaptation scenarios in a multisector context (e.g., Can goals for technologically driven increases in crop yields be reached given expected changes in climate and flood regimes?); and the need to increase sophistication of scenarios related to adaptation to match the sophistication of scenarios leading to mitigation. The end of the afternoon was devoted to breakout discussions focused on long-term scenarios for adaptation and mitigation that could be used by the IPCC, the U.S. National Assessment, and other analyses.