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Chapter 20 - Perspectives on Climate Change and Sustainability | Disaster Risk Reduction | Sustainability
Chapter 20 - Perspectives on Climate Change and Su...
Gary W. Yohe (USA), Rodel D. Lasco (Philippines)
Qazi K. Ahmad (Bangladesh), Nigel Arnell (UK), Stewart J. Cohen (Canada), Chris Hope (UK), Anthony C. Janetos (USA), Rosa T. Perez (Philippines)
Antoinette Brenkert (USA), Virginia Burkett (USA), Kristie L. Ebi (USA), Elizabeth L. Malone (USA), Bettina Menne (WHO Regional Office for Europe/Germany), Anthony Nyong (Nigeria), Ferenc L. Toth (Hungary), Gianna M. Palmer (USA)
Robert Kates (USA), Mohamed Salih (Sudan), John Stone (Canada)
Yohe, G.W., R.D. Lasco, Q.K. Ahmad, N.W. Arnell, S.J. Cohen, C. Hope, A.C. Janetos and R.T. Perez, 2007: Perspectives on climate change and sustainability. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 811-841.
Perspectives on climate change and sustainable development
Executive summary .....................................................813 20.1 Introduction: setting the context ...................814 20.2 A synthesis of new knowledge relating to impacts and adaptation ...............................814 20.7 Implications for regional, sub-regional, local and sectoral development; access to resources and technology; equity .............826
20.7.1 Millennium Development Goals – a 2015 time slice ...................................................826 20.7.2 Sectoral and regional implications ........................827
20.3 Impacts and adaptation in the context of multiple stresses ............................................816
20.3.1 A catalogue of multiple stresses ...........................816 20.3.2 Factors that support sustainable development ....816
20.4 Implications for environmental quality .......819
20.3.3 Two-way causality between sustainable development and adaptive capacity .....................817
20.8 Opportunities, co-benefits and challenges for adaptation ................................832
20.8.1 Challenges and opportunities for mainstreaming adaptation into national, regional and local development processes...........832 20.8.2 Participatory processes in research and practice ..........................................................832 Box 20.1 Role of local and indigenous knowledge in adaptation and sustainability research..............833 20.8.3 Bringing climate-change adaptation and development communities together to promote sustainable development........................834
20.7.3 The complementarity roles of mitigation and enhanced adaptive capacity .................................827
20.5 Implications for risk, hazard and disaster management ........................................820 20.6 Global and aggregate impacts........................821
20.6.1 History and present state of aggregate impact estimates ..............................................................821 20.6.2 Spatially-explicit methods: global impacts of climate change ......................................................824
20.9 Uncertainties, unknowns and priorities for research .........................................................836 References......................................................................837
underestimate climate costs because they do not include significant impacts that have not yet been monetised [20.6.1, 20.6.2, 20.7.2, 20.8, Chapter 17 Section 17.2.3, Chapter 19]. It is virtually certain that aggregate estimates mask significant differences in impacts across sectors and across regions, countries and locally [20.6, 20.7, 20.8, Chapter 17 Section 17.3.3]. It is virtually certain that the real social cost of carbon and other greenhouse gases will rise over time; it is very likely that the rate of increase will be 2% to 4% per year [20.6, 20.7]. By 2080, it is likely that 1.1 to 3.2 billion people will be experiencing water scarcity (depending on scenario); 200 to 600 million, hunger; 2 to 7 million more per year, coastal flooding [20.6.2].
Reducing vulnerability to the hazards associated with current and future climate variability and extremes through specific policies and programmes, individual initiatives, participatory planning processes and other community approaches can reduce vulnerability to climate change [20.8.1, 20.8.2, Chapter 17 Sections 17.2.1, 17.2.2 and 17.2.3] (high confidence). Efforts to reduce vulnerability will be not be sufficient to eliminate all damages associated with climate change [20.5, 20.7.2, 20.7.3] (very high confidence). Climate change will impede nations’ abilities to achieve sustainable development pathways as measured, for example, by long-term progress towards the Millennium Development Goals [20.7.1] (very high confidence).
More than 100 estimates of the social cost of carbon are available. They run from US$-10 to US$+350 per tonne of carbon. Peer-reviewed estimates have a mean value of US$43 per tonne of carbon with a standard deviation of US$83 per tonne. Uncertainties in climate sensitivity, response lags, discount rates, the treatment of equity, the valuation of economic and noneconomic impacts and the treatment of possible catastrophic losses explain much of this variation including, for example, the US$310 per tonne of carbon estimate published by Stern (2007). Other estimates of the social cost of carbon span at least three orders of magnitude, from less than US$1 per tonne of carbon to over US$1,500 per tonne [20.6.1]. It is likely that the globallyaggregated figures from integrated assessment models
20.1 Introduction – setting the context
Consistent with the Bruntland Commission (WCED, 1987), the Third Assessment Report (TAR) (IPCC, 2001b) defined sustainable development as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. There are many alternative definitions, of course, and none is universally accepted. Nonetheless, they all emphasise one or more of the following critical elements: identifying what to develop, identifying what to sustain, characterising links between entities to be sustained and entities to be developed and envisioning future contexts for these links (NRC, 1999). Goals, indicators, values and practices can also frame examinations of sustainable development (Kates et al., 2005). The essence of sustainable development throughout is meeting fundamental human needs in ways that preserve the life support systems of the planet (Kates et al., 2000). Its strength lies in reconciling real and perceived conflicts between the economy and the environment and between the present and the future (NRC, 1999). Authors have emphasised the economic, ecological and human/social dimensions that are the pillars of sustainable development (Robinson and Herbert, 2001; Munasinghe et al., 2003; Kates et al., 2005). The economic dimension aims at improving human welfare (such as real income). The ecological dimension seeks to protect the integrity and resilience of ecological systems, and the social dimension focuses on enriching human relationships and attaining individual and group aspirations (Munasinghe and Swart, 2000), as well as addressing concerns related to social justice and promotion of greater societal awareness of environmental issues (O’Riordan, 2004). The concept of sustainable development has permeated mainstream thinking over the past two decades, especially after the 1992 Earth Summit where 178 governments adopted Agenda 21 (UNDSD, 2006). Ten years later, the 2002 World Summit on Sustainable Development (WSSD, 2002) made it clear that sustainable development had become a widely-held social and political goal. Even though, as illustrated in Asia by the Institute for Global Environmental Strategies (IGES, 2005), implementation remains problematic, there is broad international agreement that development programmes should foster transitions to paths that meet human needs while preserving the Earth’s life-support systems and alleviating hunger and poverty (ICSU, 2002) by integrating these three dimensions (economic, ecological and human/social) of sustainable development. Researchers and practitioners in merging fields, such as ‘sustainability science’ (Kates et al., 2000), multi-scale decision analysis (Adger et al., 2003) and ‘sustainomics’ (Munasinghe et al., 2003), seek to increase our understanding of how societies can do just that. Climate change adds to the list of stressors that challenge our ability to achieve the ecologic, economic and social objectives that define sustainable development. Chapter 20 builds on the assessments in earlier chapters to note the potential for climate change to affect development paths themselves. Figure 20.1 locates its key topics schematically in the context of the three pillars of sustainable development. Topics shown in the centre of
the triangle (the ‘three-legged stool’ of sustainable development) are linked with all three pillars. Other topics, placed outside the triangle, are located closer to one leg or another. The arrows leading from the centre indicate that adaptation to climate change can influence the processes that join the pillars rather than the individual pillars themselves. For example, the technical and economic aspects of renewable resource management could illustrate efforts to support sustainable development by working with the economy-ecology connection – all nested within a decision space of other global development pressures, including poverty. Section 20.2 begins with a brief review of the current understanding of impacts and adaptive capacity as described earlier (see Chapter 17). Section 20.3 assesses impacts and adaptation in the context of multiple stresses. Section 20.4 focuses on links to environmental quality and explores the notion of adding climate-change impacts and adaptation to the list of components of environmental impact assessments. Section 20.5 addresses implications for risk, hazards and disaster management, including the challenge of reducing vulnerability to current climate variability and adapting to long-term climate change. Section 20.6 reviews global and regionally-aggregated estimates of economic impacts. Section 20.7 assesses the implications for achieving sustainable development across various time-scales. Section 20.8 considers opportunities, cobenefits and challenges for climate-change adaptation, and for linking (or mainstreaming) adaptation into national and regional development planning processes. Section 20.9 finally identifies research priorities. This entire chapter should be read with the recognition that the first 19 chapters of this volume assess the regional and global impacts of climate change and the opportunities and challenges for adaptation. Chapters 17 and 19 in this volume offer synthetic overviews of this work that focus specifically on adaptation and key vulnerabilities. Chapter 20 in this volume expands the discussion to explore linkages with sustainable development, as do Chapters 2 and 12 in IPCC (2007a). Sustainable development was addressed in IPCC (2001b), but not in IPCC (2001a).
20.2 A synthesis of new knowledge relating to impacts and adaptation
Recent work at the intersection of impacts and adaptation has confirmed that adaptation to climate change is, to a limited extent, already happening (Chapter 17, Section 17.2). Perhaps more importantly for this chapter, recent work has also reconfirmed the utility of the prescription initially presented in Smit et al. (2001) that (1) any system’s vulnerability to climate change and climate variability could be described productively in terms of its exposure to the impacts of climate and its baseline sensitivity to those impacts and that (2) both exposure and sensitivity can be influenced by that system’s adaptive capacity (Chapter 17, Section 17.3.3). The list of critical determinants of adaptive capacity was described in Smit et al. (2001) and has been explored subsequently by, for example, Yohe and Tol (2002), Adger and Vincent (2004), Brenkert and Malone (2005)
and Brooks and Adger (2005) – a list that includes access to economic and natural resources, entitlements (property rights), social networks, institutions and governance, human resources and technology (Chapter 17, Section 17.3.3). It is, however, important to note that recent work has also emphasised the fundamental distinction between adaptive capacity and adaptation implementation. There are significant barriers to implementing adaptation (Chapter 17, Section 17.3.3) and they can arise almost anywhere. The description offered by Kates et al. (2006) of the damages and costs caused by Hurricane Katrina in New Orleans, denominated in economic and human terms, provides a seminal example of this point. Notwithstanding the widely accepted assertion that the United States has high adaptive capacity, the impacts of Hurricane Katrina were fundamentally the result of a failure of adaptive infrastructure (improperly constructed levées that led to a false sense of security) and planning (deficiencies in evacuation plans, particularly in many of the poorer sections of the cities). The capacity provided by public and private investment over the past
few decades was designed to handle a hurricane like Katrina; it was the anticipatory efforts to provide protection prior to landfall and response efforts after landfall that failed. Nothing in the recent literature has undermined a fundamental conclusion in Smit et al. (2001) that “current knowledge of adaptation and adaptive capacity is insufficient for reliable prediction of adaptations; it is also insufficient for rigorous evaluation of planned adaptation options, measures and policies of governments.” (page 880). This conclusion is often supported by noting the uneven distribution of adaptive capacity across and within societies (Chapter 17, Section 17.3.2), but strong support can also be derived from the paucity of estimates of the costs of adaptation (Chapter 17, Section 17.2.3). While many adaptations can be implemented at low costs, comprehensive estimates of costs and benefits of adaptation currently do not exist except, perhaps, for costs related to adapting to sea-level rise and changes in the temporal and spatial demand for energy (heating versus cooling). Global diversity is one problem in this regard, but there are others. Anticipating the discussion of multiple stresses that
appears in the next section of this chapter, it is now understood that climate change poses novel risks that often lie outside the range of past experience (Chapter 17, Section 17.2.1) and that adaptation measures are seldom undertaken in response to climate change alone (Chapter 17, Sections 17.2.2 and 17.3.3).
20.3.1 A catalogue of multiple stresses The current literature shows a growing appreciation of the multiple stresses that ecological and socio-economic systems face, how those stresses are likely to change over the next several decades, and what some of the net environmental consequences are likely to be. The Pilot Analysis of Global Ecosystems prepared by the World Resources Institute (WRI, 2000) conducted literature reviews to document the state and condition of forests, agroecosystems, freshwater ecosystems and marine systems. The Millennium Ecosystem Assessment (MA) comprehensively documented the condition and recent trends of ecosystems, the services they provide and the socio-economic context within which they occur. It also provided several scenarios of possible future conditions (MA, 2005). For reference, the MA offered some startling statistics. Cultivated systems covered 25% of Earth’s terrestrial surface in 2000. On the way to achieving this coverage, global agricultural enterprises converted more area to cropland between 1950 and 1980 than in the 150 years between 1700 and 1850. As of the year 2000, 35% of the world’s mangrove areas and 20% of the world’s coral reefs had been lost (with another 20% having been degraded significantly). Since 1960, withdrawals from rivers and lakes have doubled, flows of biologically available nitrogen in terrestrial ecosystems have doubled, and flows of phosphorus have tripled. At least 25% of major marine fish stocks have been overfished and global fish yields have actually begun to decline. MA (2005) identified major changes in land cover, the consequences of which were explored by Foley et al. (2005). The MA (2005) recognised two different categories of drivers of change. Direct drivers of ecosystem change affect ecosystem characteristics in specific, quantifiable ways; examples include land-cover and land-use change, climate change and species introductions. Indirect drivers affect ecosystems in a more diffuse way, generally by affecting one or more direct drivers; here examples are demographic changes, socio-political changes and economic changes. Both types of drivers have changed substantially in the past few decades and will continue to do so. Among direct drivers, for example, over the past four decades, food production has increased by 150%, water use has doubled, wood harvests for pulp and paper have tripled, timber production has doubled and installed hydropower capacity has doubled. On the indirect side, global population has doubled since the 1960s to reach 6 billion people while the global economy has increased more than six fold. Table 20.1 documents expectations for how several of the direct drivers of ecosystem change are likely to change in
magnitude and importance over time. With the exception of polar regions, coastal ecosystems, some dryland systems and montane regions, climate change is not, today, a major source of stress; but climate change is the only direct driver whose magnitude and importance to a series of regions, ecosystems and resources is likely to continue to grow over the next several decades. Table 20.1 illustrates the degree to which these ecosystems are currently experiencing stresses from several direct drivers of change simultaneously. It shows that potential interactions with climate change are likely to grow over the next few decades with the magnitude of climate change itself. 20.3.2 Factors that support sustainable development A brief excursion into some of the recent literature on economic development is sufficient to support the fundamental observation that the factors that determine a country’s ability to promote (sustainable) development coincide with the factors that influence adaptive capacity relative to climate change, climate variability and climatic extremes. The underlying prerequisites for sustainability in specific contexts are highlighted in italics in the discussion which follows. The point about coincidence in underlying factors is made by matching the terms in italics with the list of determinants of adaptive capacity identified above (Chapter 17, Section 17.3.3): access to resources, entitlements (property rights), institutions and governance, human resources (human capital in the economics literature) and technology. They are all reflected in one or more citations from the development literature cited here, and they conform well to the “5 capital” model articulated by Porritt (2005) in terms of human, manufactured, social, natural and financial capital. Lucas (1988) concluded early on that differences in human capital are large enough to explain differences between the longrun growth rates of poor and rich countries. Moretti (2004), for example, showed that businesses located in cities where the fraction of college graduates (highly educated work force) grew faster and experienced larger increases in productivity. Guiso et al. (2004) explored the role of social capital in peoples’ abilities to successfully take advantage of financial structures; they found that social capital matters most when education levels are low and law enforcement is weak. Rozelle and Swinnen (2004) looked at transition countries in central Europe and the former Soviet Union; they observed that countries growing steadily a decade or more after economic reform had accomplished a common set of intermediate goals: achieving macroeconomic stability, reforming property rights, and creating institutions to facilitate exchange. Order and timing did not matter, but meeting all of these underlying objectives was critical. Winters et al. (2004) reviewed a wide literature on the links between trade liberalisation and poverty reduction. They concluded that a favourable relationship depends on the existence and stability of markets, the ability of economic actors to handle changes in risk, access to technology, resources, competent and honest government, policies that promote conflict resolution and human capital accumulation. Shortfalls in any of these underpinnings make it extremely difficult for the most disadvantaged citizens to see any advantage from trade. Finally, Sala-i-Martin et al. (2004) explained economic growth by variation in national
participation in primary school education (human capital), other measures of human capital (e.g., health measures), access to affordable investment goods and the initial level of per capita income (access to resources). 20.3.3 Two-way causality between sustainable development and adaptive capacity
It has become increasingly evident, especially since the TAR (IPCC, 2001b), that the pace and character of development influences adaptive capacity and that adaptive capacity influences the pace and character of development. It follows that development paths, and the choices that define them, will affect the severity of climate impacts, not only through changes in
exposure and sensitivity, but also through changes in the capacities of systems to adapt. This includes local-scale disaster risk reduction and resource management (e.g., Shaw, 2006; Jung et al., 2005), and broader social dimensions including governance, societal engagement and rights, and levels of education (Haddad, 2005; Tompkins and Adger, 2005; Brooks et al., 2005; Chapter 17, Section 17.3). Munasinghe and Swart (2005) and Swart et al. (2003) argued that sustainable development measures and climate-change policies, including adaptation, can reinforce each other; Figure 20.2 portrays some of the texture of the interaction that they envisioned. Although scholarly papers on adaptation began to appear in the 1980s, it was not until the 2001 Marrakech Accords that a policy focus on adaptation within the United Nations
Framework Convention on Climate Change (UNFCCC) developed (Schipper, 2006). Klein et al. (2005) suggest that adaptation has not been seen as a viable option, in part because many observers see market forces creating the necessary conditions for adaptation even in the absence of explicit policies and, in part, because understanding of how future adaptation could differ from historical experience is limited. Efforts to promote alternative development pathways that are more sustainable could include measures to reduce nonrenewable energy consumption, for example, or shifting construction of residential or industrial infrastructure to avoid high-risk areas (AfDB et al., 2004). The MA (2005) attempted to describe a global portrait of such a pathway in its “Techno Garden” scenario. In this future, an inter-connected world promotes expanded use of innovative technology, but its authors warned that technology may not solve all problems and could lead to the loss of indigenous cultures. Climate-change measures could also encounter such limitations. Gupta and Tol (2003) describe various climate-policy dilemmas including competition between human rights and property rights. Adaptation measures embedded within climate-change policies could, by design, try to reduce vulnerabilities and risks by enhancing the adaptive capacity of communities and economies. This would be consistent with sustainability goals. Researchers and practitioners should not equate vulnerability to poverty, though, and they should not consider adaptation and adaptive capacity in isolation. Brooks et al. (2005) conclude that efforts to promote adaptive capacity should incorporate aspects of education, health and governance and thereby extend the context beyond a particular stress (such as climate change) to include factors that are critical in a broader development context. Haddad (2005) noted the critical role played here by general rankings of economic development performance and general reflections of national and local goals and aspirations, and
explained how different people might choose different development from the same set of alternatives even if they had the same information. Past adaptation and development experience displays mixed results. Kates (2000) described several historic climate adaptations (e.g., drought in the Sahel) and development measures (e.g., the Green Revolution) and argued that development measures that were generally consistent with climate adaptation often benefited some groups (e.g., people with access to resources) while harming others (e.g., poor populations, indigenous peoples). Ford et al. (2006) showed that unequal acquisition of new technologies can, under some circumstances, increase vulnerability to external stresses by weakening social networks and thereby altering adaptive capacity within communities and between generations. Belliveau et al. (2006) makes the link to climate explicit by observing that adaptation to non-climatic forces, without explicitly considering climate, can lead to increased vulnerability to climate because adapting previous adaptations can be expensive. Future links between sustainable development and climate change will evolve from current development frameworks; but recognising the exposure of places and peoples to multiple stresses (Chapter 17; Chapter 19; Section 20.3.1) and accepting the challenge of mainstreaming adaptation into development planning will be critical in understanding what policies will work where and when. For example, in the Sudan, there is a risk that development efforts focusing on short-term relief can undermine community coping capacity (Elasha, 2005). In the mitigation realm, incentives for carbon sequestration could promote hybrid forest plantations and therefore pose a threat to biodiversity and ecosystem adaptability (Caparrós and Jacquemont, 2003; Chapter 18). Development decisions can also produce cumulative threats. In the Columbia River Basin, for
Figure 20.2. Two-way linkages between climate and sustainable development. Source: Swart et al. (2003). 818
instance, extensive water resource development can influence basin management with multiple objectives within scenarios of climate change because climate impacts on stream-flow cause policy dilemmas when decision-makers must balance hydroelectricity production and fisheries protection (Hamlet, 2003; Payne et al., 2004). Restoring in-stream flow to presentday acceptable (but sub-optimum) levels could, in particular, cause hydroelectricity production to decline and production from fossil fuel sources to rise. Interactions of this sort raise important questions on the analysis of the causes of recent climate-related disasters. For example, are observed trends in injuries/fatalities and property losses (Mileti, 1999; Mirza, 2003; MA, 2005; Munich Re, 2005) due to unsustainable development policies, climate change or a mixture of different factors? Could policy interventions reduce these losses in ways that would still meet broader objectives of sustainable development? Some proposed responses for Africa are described in Low (2005) and AfDB et al. (2004). Globalisation also adds complexity to the management of common-pool resources because increased interdependence makes it more difficult to find equitable solutions to development problems (Ostrom et al., 1999). Increases in the costs associated with various hazards and the prospects of cumulative environmental/economic threats have been described as syndromes. Schellnhuber et al. (1997) identified three significant categories: over-utilisation (e.g., over-cultivation of marginal land in the Sahel), inconsistent development (e.g., urban sprawl and associated destruction of landscapes) and hazardous sinks (e.g., large-scale diffusion of long-lived substances). Schellnhuber et al. (2002) and Lüdeke et al. (2004) describe possible future distributions of some of these syndromes. They suggest how mechanisms of mutual reinforcement, including climate change and development drivers, can help to identify regions where syndromes may expand and others where they might contract.
The inseparability of environment and development has been widely recognised ever since the Brundtland Commission (WCED, 1987). In the United Nations’ Millennium Development Goals (MDGs), for example, environmental considerations are reflected in the 7th goal and the operative target, among others, is to reverse loss of environmental resources by 2015. Overall, how to meet the target of integrating the principles of sustainable development in national policy and reversing the loss of environmental resources remains a partially answered question for most countries (Kates et al., 2005). Interest in environmental indicators and performance indices to monitor change has increased recently. A compilation of different sustainable development indicators by Kates et al. (2005) showed that most implicitly or explicitly build from reflections of the health of environmental and ecological resources and/or the quality of environmental and ecological services. This is relevant in both developed and developing countries, but the drivers encouraging sustainable management
are arguably strongest in the developed world. Huq and Reid (2004) and Agrawala (2004) have noted, though, that climate change is being increasingly recognised as a key factor that could affect the (sustainable) development of developed and developing countries alike. The Philippine Country Report (1999) identified 153 sustainable development indicators; some pertain to climate-change variables such as level of greenhouse gas emissions, but none refer explicitly to adaptation. There is, for example, no mention within the MDGs of potential changes in climate-related disasters or of the need to include climatechange adaptation within development programmes (Reid and Alam, 2005). This is not unusual, because links between sustainable development and climate change have historically been defined primarily in terms of mitigation. Promoting environmental quality is about more than encouraging sustainable development or adaptive capacity. It is also about transforming use practices for environmental resources into sustainable management practices. In many countries and sectors, stakeholders who manage natural resources (such as individual farmers, small businesses or major international corporations) are susceptible, over time, to variations in resource availability and hazards; they are currently seeking to revise management practices to make their actions more sustainable. Hilson (2001), for example, describes efforts in the mineral extraction industry where the relevant players include public agencies operating at many scales (from local to national to international). Definitions of sustainability vary across sectors, but their common theme is to change the way resources are exploited or hazards are managed so that adverse impacts downstream or for subsequent generations are reduced. Climate change is, however, seldom listed among the stressors that might influence sustainability. Arnell and Delaney (2006) note, though, that water management in the United Kingdom is an exception. Published literature on the links between sustainable management of natural resources and the impacts of and adaptation to climate change is extremely sparse. Most focuses on engineering and management techniques which achieve management objectives, such as a degree of protection against flood hazard or a volume of crop production, while having smaller impacts on the environment. Turner (2004) and Harman et al. (2002) speak to this point, but very few engineering analyses consider explicitly how the performance of these measures is affected by climate change or how suitable they would be in the face of a changing climate. Kundzewicz (2002) demonstrated how non-structural flood management measures can be sustainable adaptations to climate change because they are relatively robust to uncertainty. On the other hand, as shown in Clark (2002) and Kashyap (2004), much of the literature on integrated water management in the broadest sense emphasises adaptation to climatic variability and change through the adoption of sustainable and integrated approaches. Several studies have highlighted the benefits of adopting more sustainable practices, in terms of reduced costs, increased efficiency or financial performance more broadly interpreted. Johnson and Walck (2004) offer an example from forestry while Epstein and Roy (2003) are illustrative of a more expansive context. None of these studies explicitly consider the effects of
climate change on the benefits of adopting more sustainable practices; and none of the literature on mechanisms for incorporating sustainable behaviour into organisational practice and monitoring its implementation (e.g., Jasch, 2003; Figge and Hahn, 2004) consider how to incorporate the effects of climate change into mechanisms or monitoring procedures. Clark (2002) and Bansal (2005) identified several drivers behind moves to become more sustainable. First, altered legal or regulatory requirements may have an effect. Many governments have adopted legislation aimed at encouraging the sustainable use of the natural environment, and some explicitly include reference to climate change. For example, Canada and some EU member states have begun to incorporate climate change in their environmental policies, particularly in the structures of required environmental impact assessments. The hope is that the impact of present and future climates on development projects might thereby be reduced (EEA, 2006; Barrow and Lee, 2000). Ramus (2002) and Thomas et al. (2004) have observed that internallygenerated efforts to improve procedures (e.g., following an ethical position held by an influential champion, responding to the desire to reduce costs or risks, or attempting to attract potential clients) can push systems toward sustainability. Of course, stakeholder expectations may change over time. While these dynamic drivers may encourage sustainable management, they may not in themselves be directly related to concerns over the impacts of and adaptation to climate change. Kates et al. (2005) noted that the principles, goals and practices of sustainability are not fixed and immutable; they are ‘works in progress’ because the tension between economic development and environmental protection has been opened to reinterpretation from different social and ecological perspectives.
The International Decade for Natural Disaster Reduction (1990 to 1999) led to a fundamental shift in the way disasters are viewed: away from the notion that disasters were temporary disruptions to be managed by humanitarian responses and technical interventions and towards a recognition that disasters are a function of both natural and human drivers (ISDR, 2004; UNDP, 2004). The concept of disaster risk management has evolved; it is defined as the systematic management of administrative decisions, organisations, operational skills and abilities to implement policies, strategies and coping capacities of society or individuals to lessen the impacts of natural and related environmental and technological hazards (ISDR, 2004). This includes measures to provide not only emergency relief and recovery, but also disaster risk reduction (ISDR, 2004); i.e., the development and application of policies, strategies and practices designed to minimise vulnerabilities and the impacts of disasters through a combination of technical measures to reduce physical hazards and to enhance social and economic capacity to adapt. Disaster risk reduction is conceived as taking place within the broad context of sustainable development (ISDR, 2004).
20.5 Implications for risk, hazard and disaster management
In practice, however, there has been a disconnect between disaster risk reduction and sustainable development, due to a combination of institutional structures, lack of awareness of the linkages between the two, and perceptions of ‘competition’ between hazard-based risk reduction, development needs and emergency relief (Yamin, 2004; Thomalla et al., 2006). The disconnect persists despite an increasing recognition that natural disasters seriously challenge the ability of countries to meet targets associated with the Millennium Development Goals (Schipper and Pelling, 2006). A disconnect also exists between disaster risk reduction and adaptation to climate change, again reflecting different institutional structures and lack of awareness of linkages (Schipper and Pelling, 2006; O’Brien et al., 2006). Disaster risk reduction, for example, is often the responsibility of civil defence agencies, while climate-change adaptation is often covered by environmental or energy departments (Thomalla et al., 2006). Disaster risk reduction tends to focus on sudden and short-lived disasters, such as floods, storms, earthquakes and volcanic eruptions, and has tended to place less emphasis on ‘creeping onset’ disasters such as droughts. Many disasters covered by disaster risk reduction are not affected by climate change. However, there is an increasing recognition of the linkages between disaster risk reduction and adaptation to climate change, since climate change alters not only the physical hazard but also vulnerability. Sperling and Szekely (2005) note that many of the impacts associated with climate change exacerbate or alter existing threats, and adaptation measures can benefit from practical experience in disaster risk reduction. However, some effects of climate change are new within human history (such as the effects of sea-level rise), and there is little experience to tackle such impacts. Sperling and Szekely (2005) therefore state that co-ordinated action to address both existing and new challenges becomes urgent. There is great opportunity for collaboration in the assessment of current and future vulnerabilities, in the use of assessment tools (Thomalla et al., 2006) and through capacity-building measures. Incorporating climate change and its uncertainty into measures to reduce vulnerability to hazard is essential in order for them to be truly sustainable (O’Hare, 2002), and climate change increases the urgency to integrate disaster risk management into development interventions (DFID, 2004). There are, effectively, two broad approaches to disaster risk reduction, and adaptation to climate change can be incorporated differently into each. The top-down approach is based on institutional responses, allocation of funding and agreed procedures and practices (O’Brien et al., 2006). It is the approach followed in most developed countries, and adaptation to climate change can be implemented by changing guidelines and procedures. In the United Kingdom, for example, design flood magnitudes can be increased by 20% to reflect possible effects of climate change (Richardson, 2002). However, institutional inertia and strongly embedded practices can make it very difficult to change. Olsen (2006), for example, shows how major methodological and institutional changes are needed before flood management in the USA can take climate change (and its uncertainty) into account. The bottom-up approach to disaster risk reduction is based on enhancing the capacity of
local communities to adapt to and prepare for disaster (see, for example, Allen, 2006; Blanco, 2006). Actions here include dissemination of technical knowledge and training, awareness raising, accessing local knowledge and resources, and mobilising local communities (Allen, 2006). Climate change can be incorporated in this approach through awareness raising and the transmission of technical knowledge to local communities, but bridging the gap between scientific knowledge and local application is a key challenge (Blanco, 2006). Reducing vulnerability to current climatic variability can effectively reduce vulnerability to increased hazard risk associated with climate change (e.g., Kashyap, 2004; Goklany, 2007; Burton et al., 2002; Davidson et al., 2003; Robledo et al., 2004). To a large extent, adaptation measures for climate variability and extremes already exist. Measures to reduce current vulnerability by capacity building rather than distribution of disaster relief, for example, will increase resilience to changes in hazard caused by climate change (Mirza, 2003). Similarly, the implementation of improved warning and forecasting methods and the adoption of some land-use planning measures would reduce both current and future vulnerability. However, many responses to current climatic variability would not in and of themselves be a sufficient response to climate change. For example, a changing climate could alter the design standard of a physical defence, such as a realigned channel or a defence wall. It could alter the effectiveness of building codes based on designing against specified return period events (such as the 10year return period gust). It could alter the area exposed to a potential hazard, meaning that development previously assumed to be ‘safe’ was now located in a risk area. Finally, it could introduce hazards previously not experienced in an area. Burton and van Aalst (2004), in their assessment of the World Bank Country Strategic Programmes and project cycle, identify the need to assess the success of current adaptation to present-day climate risks and climate variability, especially as they may change with climate change.
remains in the atmosphere – a process which requires a model of atmospheric residence time and a means of discounting economic values back to the year of emission. This section provides a brief discussion of the historical and current status of efforts to produce aggregate estimates of the impacts of climate change. The first sub-section focuses attention on economic estimates and the second begins to expand the discussion by reporting estimates calibrated in alternative metrics. It is in this expansion that the implications of spatial and temporal diversity in systems’ exposures and sensitivities to climate change begin to emerge. 20.6.1 History and present state of aggregate impact estimates
Three types of aggregate impacts are commonly reported. In the first, impacts are computed as a percent of gross domestic product (GDP) for a specified rise in global mean temperature. In the second, impacts are aggregated over time and discounted back to the present day along specified emissions scenarios such as those documented in Nakićenović and Swart (2000) under specified assumptions about economic development, changes in technology and adaptive capacity. Some of these estimates are made at the global level, but others aggregate a series of local or regional impacts to obtain a global total. A third type of estimate has recently attracted the most attention. Called the social cost of carbon (SCC), it is an estimate of the economic value of the extra (or marginal) impact caused by the emission of one more tonne of carbon (in the form of carbon dioxide) at any point in time; it can, as well, be interpreted as the marginal benefit of reducing carbon emissions by one tonne. Researchers calculate SCC by summing the extra impacts for as long as the extra tonne
20.6 Global and aggregate impacts
Most of the aggregate impacts reported in IPCC (1996) were of the first type; they monetised the likely damage that would be caused by a doubling of CO2 concentrations. For developed countries, estimated damages were of the order of 1% of GDP. Developing countries were expected to suffer larger percentage damages, so mean global losses of 1.5 to 3.5% of world GDP were therefore reported. IPCC (2001a) reported essentially the same range because more modest estimates of market damages were balanced by other factors such as higher non-market impacts and improved coverage of a wide range of uncertainties. Most recently, Stern (2007) took account of a full range of both impacts and possible outcomes (i.e., it employed the basic economics of risk premiums) to suggest that the economic effects of unmitigated climate change could reduce welfare by an amount equivalent to a persistent average reduction in global per capita consumption of at least 5%. Including direct impacts on the environment and human health (i.e., ‘non-market’ impacts) increased their estimate of the total (average) cost of climate change to 11% GDP; including evidence which indicates that the climate system may be more responsive to greenhousegas emissions than previously thought increased their estimates to 14% GDP. Using equity weights to reflect the expectation that a disproportionate share of the climate-change burden will fall on poor regions of the world increased their estimated reduction in equivalent consumption per head to 20%. Figure 20.3 compares the Stern (2007) relationship between global impacts and increases in global mean temperature with estimates drawn from earlier studies that were assessed in IPCC (2001b). The Stern (2007) trajectories all show negative impacts for all temperatures; they reflect the simple assumptions of the underlying PAGE2002 model and a focus on risks associated with higher temperatures. The Mendelsohn et al. (1998) estimates aggregate regional monetary damages (both positive and negative) without equity weighting. The two Nordhaus and Boyer (2000) trajectories track aggregated regional monetary estimates of damages with and without population-based equity weighting; they do include a ‘willingness to pay (to avoid)’ reflection of the costs of abrupt change. The two Tol (2002) trajectories track aggregated regional monetary estimates of damages with and without utility-based equity weighting. The various relationships depicted in Figure 20.3 therefore differ in their treatment of equity weighting, in their efforts to capture the potential of beneficial climate change (in, for example,
Figure 20.3. (a) Damage estimates, as a percent of global GDP, as correlated with increases in global mean temperature. Source: IPCC (2001b). (b) Damage estimates, as a percent of global GDP, are correlated with increases in global mean temperature. Source: Stern (2007).
agriculture for small increases in temperature; see Chapter 5, Section 5.4.7) and in their treatment of the risks of catastrophe for large increases in temperature. Early calculations of the SCC (IPCC (1996) estimates ranged from US$5 to $125 per tonne of carbon in 1990 dollars) stimulated recurring interest, as part of wider post-Kyoto considerations, in the economic benefits of climate-change policy (Watkiss et al., 2005). After surveying the literature, Clarkson and Deyes (2002) proposed a central value of US$105 per tonne of carbon (in year 2000 prices) for the SCC, with upper and lower values of US$50 and $210 per tonne. Pearce (2003) argued that 3% is a reasonable representation of a social discount rate so the probable range of the SCC in 2003 should have been in the region of US$4 to 9 per tonne of carbon. Tol (2005) gathered over 100 estimates of the SCC from 28 published studies and combined them to form a probability density function; it displayed a median of US$14 per tonne of carbon, a mean of US$93 per tonne and a 95th percentile estimate equal to US$350 per tonne. Peer-reviewed studies generally reported lower estimates and smaller uncertainties than those which were not; their mean was US$43 per tonne of carbon with a standard deviation of US$83. The survey showed that 10% of the estimates were negative; to support these estimates, the climate sensitivity was assumed to be low and small increases in global mean temperature brought benefits (as suggested by the Tol (2002) trajectories in Figure 20.3). Notwithstanding the differences in damage sensitivity to temperature reflected in Figure 20.3, the effect of the discount rate (see glossary) on estimates of SCC is most striking. The 90th percentile SCC, for instance, is US$62/tC for a 3% pure rate of time preference, $165/tC for 1% and $1,610/tC for 0%. Stern (2007) calculated, on the basis of damage calculations described above, a mean estimate of the SCC in 2006 of US$85 per tonne of CO2 (US$310 per tonne of carbon). Had it been included in the Tol (2005) survey, it would have fallen well above the 95th percentile, in large measure because of their adoption of a low 0.1% pure rate of time preference. Other estimates of the SCC run from less than US$1 per tonne to over US$1,500 per tonne of carbon. Downing et al. (2005) argued that this range reflects uncertainties in climate and impacts, coverage of sectors and
extremes, and choices of decision variables. Tol (2005) concluded, using standard assumptions about discounting and aggregation, that the SCC is unlikely to exceed US$50/tC. In contrast, Downing et al. (2005) concluded that a lower benchmark of US$50/tC is reasonable for a global decision context committed to reducing the threat of dangerous climate change and including a modest level of aversion to extreme risks, relatively low discount rates and equity weighting. Climate change is not caused by carbon dioxide alone, and integrated assessment models can calculate the social cost of each greenhouse gas under consistent assumptions. For instance, the mean estimate from the PAGE2002 model for the social cost of methane is US$105 per tonne emitted in 2001, in year 2000 dollars, with a 5 to 95% uncertainty range of US$25 to $250 per tonne. The estimate for the social cost of SF6 is US$200,000 per tonne emitted in 2001 with a 5 to 95% range of US$45,000 to $450,000 per tonne. These are all higher than the corresponding US$19 per tonne estimate for SCC that is surrounded by a 5 to 95% range of US$4 to $50 per tonne (Hope, 2006b). It has been known since IPCC (1996) that the SCC will increase over time; current knowledge suggests a 2.4% per year rate of growth. The social cost of methane will grow 50% faster because of its shorter atmospheric lifetime. Unlike later emissions, any extra methane emitted today will have disappeared before the most severe climate-change impacts occur (Watkiss et al., 2005). Tol (2005) finds that much of the uncertainty in the estimates of the SCC can be traced to two assumptions: one on the discount rate and the other on the equity weights that are used to aggregate monetised impacts over countries. In most other policy areas, the rich do not reveal as much concern for the poor as is implied by the equity weights used in many models. Downing et al. (2005) state that the extreme tails of the estimates of the SCC depend as much on decision values (such as discounting and equity weighting) as on the climate forcing and uncertainty in the underlying impact models. Integrated models are always simplified representations of reality. To be comprehensive, other social and cultural values need to be given comparable weights to economic values, and there are prototype integrated assessment models to demonstrate this (Rotmans and de Vries, 1997).
Table 20.2 shows the six major influences calculated by PAGE2002 and reported in Hope (2005). That the list can be divided into two scientific and four socio-economic parameters is another strong argument for the building of integrated assessment models (IAMs); models that are exclusively scientific, or exclusively economic, would omit parts of the climate-change problem which still contain profound uncertainties. The two top influences are the climate sensitivity and the pure rate of time preference. Climate sensitivity is positively correlated with the SCC, but the pure time preference rate is negatively correlated with the SCC. Non-economic impact ranks third and economic impact ranks sixth (Hope, 2005). A few models have existed for long enough to trace the changes in their estimates of the SCC over time. Table 20.3 shows how the results from three integrated assessment models have evolved over the last 15 years. The DICE and PAGE estimates have not changed greatly over the years, but this gives a misleading impression of stability. The values from PAGE have changed little because several quite significant changes have approximately cancelled each other out. In the later studies, lower estimates for market-sector impacts in developed countries are offset by higher non-market impacts, equity weights and inclusion of estimates of the possible impacts of large-scale discontinuities (Tol, 2005). Hitz and Smith (2004) found that the relationships between global mean temperature and impacts of the sort displayed in Figure 20.3 are not consistent across sectors for modest amounts of warming. Beyond an approximate 3 to 4°C increase in global mean temperature above pre-industrial levels, all sectors (except possibly forestry) show increasingly adverse impacts. Tol (2005) found that few studies cover non-market damages, the risk of potential extreme weather, socially contingent effects, or the potential for longer-term catastrophic events. Therefore, uncertainty in the value of the SCC is derived not only from the
‘true’ value of impacts that are covered by the models, but also from impacts that have not yet been quantified and valued. As argued in Watkiss et al. (2005) and displayed in Figure 20.4, existing estimates of SCC are products of work that spans only a sub-set of impacts for which complete estimates might be calculated. Nonetheless, current estimates do provide enough information to support meaningful discussions about reducing the emissions of CO2, methane and other greenhouse gases, and the appropriate trade-off between gases. Nonetheless, estimates of SCC offer a consistent way to internalise current knowledge about the impacts of climate change into development, mitigation and/or adaptation decisions that the private and public sector will be making over the near term (Morimoto and Hope, 2004). According to economic theory, if the social cost calculations were complete and markets were perfect, then efforts to cut back the emissions of greenhouse gases would continue as long as the marginal cost of the cutbacks were lower than the social cost of the impacts they cause. If taxes were used, then they should be set equal to the SCC. If tradable permits were used, then their price should be the same as the SCC. If their price turns out to be lower than the social cost, then the total allocation of permits would have been too large and vice versa. In any comparison between greenhouse gases, according to Pearce (2003), the SCC is the correct figure to use. For reference, spot prices for permits in the European Carbon Trading Scheme since its inception early in 2005 started out towards the bottom end of the range of the SCC, but they rose quickly to around US$100 per tonne of carbon before falling by about 50% in the early summer of 2006 amid concerns that the carbon allowances allocated by the European Commission at the start of the scheme had been too generous. In the real world, markets are not perfect, calculations of the SCC are far from complete, and both mask significant differences between regions and types of impacts.
Table 20.2. Major factors causing uncertainty in the social cost of carbon. Relative importance is measured by the magnitude of the partial rank correlation coefficient between the parameter and the SCC, with the most important indexed to 100. A + sign shows that an increase in this parameter leads to an increase in the SCC and vice versa. Source: Hope (2005). Parameter Climate sensitivity PTP rate Non-economic impact Equity weight Economic impact Definition Equilibrium temperature rise for a doubling of CO2 concentration Pure time preference for consumption now rather than in 1 year’s time Valuation of non-economic impact for a 2.5°C temperature rise Negative of the elasticity of marginal utility with respect to income Valuation of economic impact for a 2.5°C temperature rise Sign + + + Range 1.5 to 5°C 1 to 3% /yr 0 to 1.5% of GDP 0.5 to 1.5 25 to 75 years -0.1 to 1.0% of GDP Importance 100 66 57 50 35 32
Climate change half life Half life in years of global response to an increase in radiative forcing
Note: non-economic and economic impact ranges apply to Europe; impacts in other regions are expressed as a multiple of this.
Table 20.3. Estimates of the social cost of carbon over time from three models (in constant 2000 US$). Sources: DICE best guesses of Nordhaus and Boyer (2000) are from Pearce (2003); FUND estimates are from Tol (1999), and 25 to 75% range with green book discounting and equity weights from Downing et al. (2005); PAGE 5th and 95th percentile ranges from Plambeck and Hope (1996), rebased to year 2000, and Hope (2006a). Date of estimate DICE FUND PAGE 1990 $10 1995 $7 $12 to $60 2000 $6 $9 to $23 2005
-$15 to $110 $4 to $51 823
Figure 20.4. Coverage of studies that compute estimates of the social cost of carbon against sources of climate-related risk. Coverage of most studies is limited to market-based sectors, and few of them move beyond the upper left corner to include bounded risks and abrupt system change. Source: Watkiss et al., 2005.
20.6.2 Spatially-explicit methods: global impacts of climate change
Warren (2006) and Hitz and Smith (2004) observe that most impact assessments are conducted at the local scale. It is therefore extremely difficult to estimate impacts across the global domain from these localised studies. A small number of studies have used geographically-distributed impacts models to estimate the impacts of climate change across the global domain. The “Fast Track” studies (Arnell, 2004; Nicholls, 2004; Arnell et al., 2002; Levy et al., 2004; Parry et al., 2004; Van Lieshout et al., 2004) used a consistent set of scenarios and assumptions to estimate the effects of scenarios based on the HadCM3 climate model on water resource availability, food security, coastal flood risk, ecosystem change and exposure to malaria. Schroeter et al. (2005) used a similar approach in the ATEAM project to tabulate impacts across Europe using scenarios constructed from a larger number of climate models.
Both these sets of studies used a wide range of metrics that varied across sectors. Table 20.4 summarises some of the global-scale impacts of defined climate-change scenarios. Although the precise numbers depend on the climate model used and some key assumptions (particularly the effect of increased CO2 concentrations on crop productivity), it is clear that the future impacts of climate change are dependent not only on the rate of climate change, but also on the future social, economic and technological state of the world. Impacts are greatest under an A2 world, for example, not because the climate change is greatest but because there are more people to be impacted. Impacts also vary regionally and Table 20.5 summarises impacts by major world region. The assumed effect of CO2 enrichment on crop productivity has a major effect on estimated changes in population at risk of hunger (Chapter 5, Section 5.4.7). Table 20.6 compares the global impacts of a 1% annual increase in CO2 concentrations (i.e., the IS92a scenario, see IPCC, 1992) with the impacts of emissions trajectories stabilising at 750 (S750) and 550 (S550) ppm (Arnell et al., 2002). The results are not directly comparable to those reported in Table 20.4, because different population assumptions, methodologies and indicators were employed in their preparation. Nevertheless, the results suggest that aiming for stabilisation at 750 ppm has a relatively small effect on impacts in most sectors in comparison with 550 ppm stabilisation. The S550 pathway has a greater apparent impact on exposure to hunger because higher CO2 concentrations under S750 result in a greater increase in crop productivity (but again, note that CO2enrichment effects are highly uncertain). Each of these tables present indicators of impact which ignore adaptations that will occur over time. They can therefore be seen as indicative of the challenge to be overcome by adaptations to offset some of the impacts of climate change. Incorporating adaptation into global-scale assessments of the impacts of climate change is currently difficult for a number of reasons (including diversity of circumstances, diversity of potential objectives of adaptation, diversity of ways of meeting adaptation objectives and uncertainty over the effectiveness of adaptation options) and remains an area where more research is needed.
Table 20.4. Global-scale impacts of climate change by 2080. Climate and socio-economic scenario A1FI Global temperature change (°C difference from the 1961-1990 period) Millions of people at increased risk of hunger (Parry et al., 2004); no CO2 effect Millions of people at increased risk of hunger (Parry et al., 2004); with maximum direct CO2 effect Millions of people exposed to increased water resources stress (Arnell, 2004) Additional numbers of people (millions) flooded in coastal floods each year, with lagged evolving protection (Nicholls, 2004) 3.97 263 28 1256 7 A2 3.21 to 3.32 551 -28 to -8 2583 to 3210 29 B1 2.06 34 12 1135 2 B2 2.34 to 2.4 151 -12 to +5 1196 to 1535 16
Note: change in climate derived from the HadCM3 climate model. Impacts are compared to the situation in 2080 with no climate change. The range of impacts under the SRES A2 and B2 scenarios (Nakićenović and Swart, 2000) represents the range between different climate simulations. The figures for additional millions of people flooded in coastal floods assumes a low rate of subsidence and a low rate of population concentration in the coastal zone.
Table 20.5. Regional-scale impacts of climate change by 2080 (millions of people). Population living in watersheds with an increase in waterresources stress (Arnell, 2004) Additional population at risk of hunger (Parry et al., 2004)1 Figures in brackets assume maximum direct CO2-enrichment effect Clim a t e a n d s oc io-e c on om ic s c e n a r io: B2 A1 A2 B1 B2 A1 A2 B1 B2 172-183 1.6 0.3 0.2 0.3 0 0 0 0 327-608 1.3 14.7 0.5 1.4 78 (6) 266 (-21) 7 (2) 47 (-3) 9-63 0.1 0.1 0 0 0 0 0 0 130-186 0.6 0.4 0 0.1 27 (1) 85 (-4) 5 (2) 15 (-1) 492-559 0 2.8 0 12.8 0 0.6 0 13.6 0 157 (21) 0 200 (-2) 0 23 (8) 0 89 (-8) 0 Increase in average annual number of coastal flood victims (Nicholls, 2004)
Europe Asia North America South America Africa Australasia
A1 270 289 127 163 408 0
A2 382-493 812-1197 110-145 430-469 691-909 0
B1 233 302 107 97 397 0
Note: change in climate derived from the HadCM3 climate model. Impacts are compared to the situation in 2080 with no climate change. The range of impacts under the SRES A2 and B2 scenarios (Nakićenović and Swart, 2000) represents the range between different climate simulations. The figures for additional millions of people flooded in coastal floods assumes a low rate of subsidence and a low rate of population concentration in the coastal zone. 1 Analysis of project results carried out for this table.
Table 20.6. Global-scale impacts under unmitigated and stabilisation pathways. Source: Arnell et al., 2002. 2050 Scenario: S750 485 1.3 2 2100 13 7 2050 Scenario: S750 565 1.7 3.5 2920 21 16
Unmitigated Approximate equivalent CO2 concentration (ppm) Approximate global temperature change (°C difference from 1961 to 1990) Area potentially experiencing vegetation dieback (million km2) Millions of people exposed to increased water stress Additional people flooded in coastal floods (millions/year) Population at increased risk of hunger (millions) 520 2.0 1.5 to 2.7 200 to 3200 20 -3 to 9
S550 458 1.1 0.7 1700 10 5
Unmitigated 630 2.9 6.2 to 8 2830 to 3440 79 to 81 69 to 91
S550 493 1.2 1.3 760 5 43
Note: climate scenarios based on HadCM2 simulations: the range with unmitigated emissions reflects variation between ensemble simulations.
Aggregation of impacts to regional and global scales is another key problem with such geographically-distributed impact assessments. Tables 20.4 to 20.6, for example, keep track of people living in watersheds who will face increased waterrelated stress. Of course, many people live in watersheds where climate change increases runoff and therefore may apparently see reduced water-related stress (if they see increased risk of flooding). Simply calculating the ‘net’ impact of climate change, however, is complicated, particularly where ‘winners’ and ‘losers’ live in different geographic regions, or where ‘costs’ and ‘benefits’ are not symmetrical. Watersheds with an increase in runoff, for example, are concentrated in east Asia, while watersheds with reduced runoff are much more widely distributed. Similarly, the adverse effects felt by 100 million people exposed to increased water stress could easily outweigh the ‘benefits’ of 100 million people with reduced stress.
The Defra Fast Track and ATEAM studies both describe impacts along defined scenarios, so it is difficult to infer the effects of different rates or degrees of climate change on different socio-economic worlds. A more generalised approach applies a wide range of climate scenarios representing different rates of change to estimate impacts for specific socio-economic contexts. Leemans and Eickhout (2004), for example, show that most species, ecosystems and landscapes would be impacted by increases of global temperature between 1 and 2°C above 2000 levels. Arnell (2006) showed that an increase in temperature of 2°C above the 1961 to 1990 mean by 2050 would result in between 550 and 900 million people suffering an increase in water-related stress in both the SRES (Special Report on Emissions Scenarios, Nakićenović and Swart, 2000) A1 and B1 worlds. In this case, the range between estimates represents the effect of different changes in rainfall patterns for a 2°C warming.
The first sub-section here addresses issues of equity and access to resources as measured by the likelihood of meeting Millennium Development Targets by 2015 and Millennium Development Goals until the middle of this century. Vulnerability to climate change is unlikely to be the dominant cause of trouble for most nations as they try to reach the 2015 Targets. However, an assortment of climate-related vulnerabilities will seriously impede progress in achieving the mid-century goals. The second sub-section considers the range of these vulnerabilities across regions and sectors in 2050 and 2100 before the last offers portraits of the global distribution of vulnerability with and without enhanced adaptive capacity and/or mitigation efforts. 20.7.1 Millennium Development Goals – a 2015 time slice
20.7 Implications for regional, sub-regional, local and sectoral development; access to resources and technology; equity
The Millennium Development Goals (MDGs) are the product of international consensus on a framework by which nations can assess tangible progress towards sustainable development; they are enumerated in Table 20.7. UN (2005) provides the most current documentation of the 8 MDGs, the 11 specific targets for progress by 2015 or 2020 and the 32 quantitative indicators that are being used as metrics. This chapter has made the point that sustainable development and adaptive capacity for coping with climate change have common determinants. It is easy, therefore, to conclude that climate change has the potential to affect the progress of nations and societies towards sustainability. MA (2005) supports this conclusion. Climatechange impacts on the timing, flow and amount of available freshwater resources could, for example, affect the ability of developing countries to increase access to potable water: Goal #7, Target #10, Indicator #30 (UN, 2005). It is conceivable that climate change could have measurable consequences, in some parts of the world at least, on the indicators of progress on food security: Goal #1, Target #2, Indicators #4 and #5 (UN, 2005). Climate-change impacts could possibly affect one indicator in Goal #6 (prevalence and death rates associated with malaria), over the medium term (UN, 2005). The list can be extended. The anthropogenic drivers of climate change, per se, affect MDG indicators directly in only two ways: in terms of energy
Table 20.7. The Millennium Development Goals. 1. Eradicate extreme poverty and hunger 2. Achieve universal primary education 3. Promote gender equality and empower women 4. Reduce child mortality 5. Improve maternal health 6. Combat HIV/AIDS, malaria and other diseases 7. Ensure environmental sustainability 8. Develop a global partnership for development Source: http://www.un.org/millenniumgoals/documents.html 826
use per dollar GDP and CO2 emissions per capita. While climate change may, with high confidence, have the potential for substantial effects on aspects of sustainability that are important for the MDGs, the literature is less conclusive on whether the metrics themselves will be sensitive to either the effects of climate change or to progress concerning its drivers, especially in the near term. The short-term targets of the MDGs (i.e., the 2015 to 2020 Targets) will be difficult to reach in any case. While climate impacts have now been observed with some levels of confidence in some places, it will be difficult to blame climate change for limited progress towards the Millennium Development Targets. In the longer term, Arrow et al. (2004) argue that adaptation decisions can reduce the effective investment available to reach the MDGs. They thereby raise the issue of opportunity costs: perhaps investment in climate adaptation might retard efforts to achieve sustainable development. Because the determinants of adaptive capacity and of sustainable development overlap significantly; however, (see Section 20.2) it is also possible that a dollar spent on climate adaptation could strengthen progress towards sustainable development. Whether synergistic effects or trade offs will dominate interactions between climate impacts, adaptation decisions and sustainable development decisions depend, at least in part, on the particular decisions that are made. Decisions on how countries will acquire sufficient energy to sustain growing demand will, for example, play crucial roles in determining the sustainability of economic development. If those demands are met by increasing fossil fuel combustion, then amplifying feedbacks to climate change should be expected. There are some indications that this is now occurring. Per capita emissions of CO2 in developing countries rose from 1.7 tonnes of CO2 per capita in 1990 to 2.1 tonnes per capita in 2002; they remained, though, far short of the 12.6 tonnes of CO2 per capita consumed in developed countries (UN, 2005). Resources devoted to expanding fossil fuel generation could, therefore, be seen as a source of expanded climate-change impacts. On the other hand, investments in forestry and agricultural sectors designed to preserve and enhance soil fertility in support of improved food security MDGs (e.g., Goal #1) might have synergies for climate mitigation (through carbon sequestration) and for adaptation (because higher economic returns for local communities could be invested in adaptation). It is simply impossible to tell, a priori, which effect will dominate. Each situation must be analysed qualitatively and quantitatively. These complexities make it clear that not all development paths will be equal with respect to either their consequences for climate change or their consequences for adaptive capacity. Moreover, the Millennium Ecosystem Assessment (MA, 2005) and others (e.g., AfDB et al., 2004) argue that climate change will be a significant hindrance to meeting the MDGs over the long term. There is no discrepancy here because stresses from climate change will grow over time. Some regions and countries are already lagging in their progress towards the MDGs and these tend to be in locations where climate vulnerabilities over the 21st century are likely to be high. For example, the proportion of land area covered by forests fell between 1990 and 2000 in sub-Saharan Africa, South-East Asia and Latin America and the Caribbean, while it appeared to stabilise in developed
countries (UN, 2005). Energy use per unit of GDP fell between 1990 and 2002 in both developed and developing regions, but developed regions remained approximately 10% more efficient than developing regions (UN, 2005). In short, regions where ecosystem services and contributions to human well-being are already being eroded by multiple external stresses are more likely to have low adaptive capacity. 20.7.2 Sectoral and regional implications The range of increase in global mean temperature that could be expected over the next several centuries is highly uncertain. The compounding diversity in the regional patterns of temperature change for selected changes in global mean temperature is depicted elsewhere in IPCC (2007b, Figure SPM.6); so, too, are illustrations of geographic diversity in changes in precipitation and model disagreement about even the sign of this change (IPCC, 2007b, Figure SPM.7). Earlier sections of this chapter have also underscored the difficulty in anticipating the development of adaptive capacity and the ability of communities to take advantage of the incumbent opportunities. Despite all of this complexity, however, it is possible to offer some conclusions about vulnerability across regions and sectors as reported throughout this report. Locating the anticipated impacts of climate change on a map is perhaps the simplest way to see this point. Figure 9.5, for example, shows the spatial distribution of the projected impacts that are reported for Africa in Chapter 9. The power of maps like this lies in their ability to show how the various manifestations of climate change can be geographically concentrated. It is clear, as a result, that climate change can, by virtue of its multiple dimensions, be its own source of multiple stresses. It follows immediately that vulnerability to climate change can easily be amplified (in the sense that total vulnerability to climate change is greater than the sum of vulnerabilities to specific impacts) in regions like the southeastern coast of Africa and Madagascar. Maps of this sort do not, however, capture sensitivities to larger indices of climate change (such as increases in global mean temperature); nor do they not offer any insight into the timing of increased vulnerabilities. Tables 20.8 and 20.9 address these deficiencies by summarising estimated impacts at global and regional scales against a range of changes in global average temperature. Each entry is drawn from earlier chapters in this report, and assessed levels of confidence are indicated. The entries have been selected by authors of the chapters and the selection is intended to illustrate impacts that are important for human welfare. The criteria for judging this importance include the magnitude, rate, timing and persistence/irreversibility of impacts, and the capacity to adapt to them. Where possible, the entries give an indication of impact trend and its quantitative level. In a few cases, quantitative measures of impact have now been estimated for different amounts of climate change, thus pointing toward different levels of the same impact that might be avoided by not exceeding given amounts of global temperature change. The time dimension is captured by the bars drawn at the top of Table 20.8; they indicate the range of global average
temperature increase that could be expected during the 2020s, the 2050s and the 2080s among the SRES collection of unmitigated scenarios as well as a range of alternative stabilisation pathways (Nakićenović and Swart, 2000). The real message to be drawn from their inclusion is that no temperature threshold associated with any subjective judgment of what might constitute ‘dangerous’ climate change can be guaranteed by anything but the most stringent of mitigation interventions, at least not on the basis of current knowledge. Moreover, there is an estimated commitment to warming of 0.6°C due to past emissions, from which impacts must be expected, regardless of any future efforts to reduce emissions in the future. 20.7.3 The complementarity roles of mitigation and enhanced adaptive capacity
IPCC (2001a) focused minimal attention on the co-benefits of mitigation and adaptation, but this report has added a chapterlength assessment of current knowledge at the nexus of adaptation and mitigation. An emphasis on constructing a “portfolio of adaptation and mitigation actions” has emerged (Chapter 18, Sections 18.4 and 18.7). Moreover, the capacities to respond in either dimension are supported by ‘similar sets of factors’ (Chapter 18, Section 18.6). These factors are, of course, themselves determined by underlying socio-economic and technological development paths that are location and time specific. Yohe et al. (2006a, b) offer suggestive illustrations of potential synergies within the adaptation/mitigation portfolio; complementarity in the economic sense that one makes the other more productive. Figures 20.5 and 20.6 display the geographic distribution of these synergies in terms of a national vulnerability index with and without mitigation, and with and without enhanced adaptive capacity by 2050 and 2100, respectively. Vulnerabilities that were assigned to specific countries on the basis of a vulnerability index derived from national estimates of adaptive capacity provided by Brenkert and Malone (2005) and the geographic distribution of temperature change derived from a small ensemble of global circulation models. The upper left panels of Figures 20.5 and 20.6 present geographical distributions of vulnerability in 2050 and 2100, respectively, along the SRES A2 emissions scenario with a climate sensitivity of 5.5°C under the limiting assumption that adaptive capacities are fixed at current levels; global mean temperature climbs by 1.6°C and 4.9°C above 1990 levels by 2050 and 2100, respectively. These two panels are benchmarks of maximum vulnerability against which other options can be assessed. Notice that most of Africa plus China display the largest vulnerabilities in 2050 and that nearly every nation displays extreme vulnerability by 2100. A2 was chosen for illustrative clarity with reference to temperature change only. Moreover, none of the interpretations depend on the underlying storyline of the A2 scenario; Yohe et al. (2006b) describes comparable results for other scenarios. The upper right panels present comparable geographic distributions under the assumption that adaptive capacity improves everywhere with special emphasis on developing countries; their capacities are assumed to advance to the current global mean by 2050 and 2100 for Figures 20.5 and 20.6,
Table 20.8. Examples of global impacts projected for changes in climate (and sea level and atmospheric CO2 where relevant) associated with different amounts of increase in global average surface temperature in the 21st century. This is a selection of some estimates currently available. All entries are from published studies in the chapters of the Assessment. (Continues below Table 20.9) 828
Table 20.9. Examples of regional impacts. See caption for Table 20.8. Table 20.8. (cont.) Edges of boxes and placing of text indicate the range of temperature change to which the impacts relate. Arrows between boxes indicate increasing levels of impacts between estimations. Other arrows indicate trends in impacts. All entries for water stress and flooding represent the additional impacts of climate change relative to the conditions projected across the range of SRES scenarios A1FI, A2, B1 and B2. Adaptation to climate change is not included in these estimations. For extinctions, ‘major’ means ~40 to ~70% of assessed species. The table also shows global temperature changes for selected time periods, relative to 1980-1999, projected for SRES and stabilisation scenarios. To express the temperature change relative to 1850-1899, add 0.5°C. More detail is provided in Chapter 2 [Box 2.8]. Estimates are for the 2020s, 2050s and 2080s, (the time periods used by the IPCC Data Distribution Centre and therefore in many impact studies) and for the 2090s. SRES-based projections are shown using two different approaches. Middle panel: projections from the WGI AR4 SPM based on multiple sources. Best estimates are based on AOGCMs (coloured dots). Uncertainty ranges, available only for the 2090s, are based on models, observational constraints and expert judgement. Lower panel: best estimates and uncertainty ranges based on a simple climate model (SCM), also from WGI AR4 (Chapter 10). Upper panel: best estimates and uncertainty ranges for four CO2-stabilisation scenarios using an SCM. Results are from the TAR because comparable projections for the 21st century are not available in the AR4. However, estimates of equilibrium warming are reported in the WGI AR4 for CO2equivalent stabilisationa. Note that equilibrium temperatures would not be reached until decades or centuries after greenhouse gas stabilisation. Table 20.8. Sources: 1, 3.4.1; 2, 3.4.1, 3.4.3; 3, 3.5.1; 4, 4.4.11; 5, 4.4.9, 4.4.11, 6.2.5, 6.4.1; 6, 4.4.9, 4.4.11, 6.4.1; 7, 4.2.2, 4.4.1, 4.4.4 to 4.4.6, 4.4.10; 8, 4.4.1, 4.4.11; 9, 5.4.2; 10, 6.3.2, 6.4.1, 6.4.2; 11, 6.4.1; 12, 6.4.2; 13, 8.4, 8.7; 14, 8.2, 8.4, 8.7; 15, 8.2, 8.4, 8.7; 16, 8.6.1; 17, 19.3.1; 18, 19.3.1, 19.3.5; 19, 19.3.5 Table 20.9. Sources: 1, 9.4.5; 2, 9.4.4; 3, 9.4.1; 4, 10.4.1; 5, 6.4.2; 6, 10.4.2; 7, 11.6; 8, 11.4.12; 9, 11.4.1, 11.4.12; 10, 11.4.1, 11.4.12; 11, 12.4.1; 12, 12.4.7; 13, 13.4.1; 14, 13.2.4; 15, 13.4.3; 16, 14.4.4; 17, 5.4.5, 14.4.4; 18, 14.4.8; 19, 14.4.5; 20, 15.3.4, 21, 15.4.2; 22, 15.3.3; 23, 16.4.7; 24, 16.4.4; 25, 16.4.3
Best estimate and likely range of equilibrium warming for seven levels of CO2-equivalent stabilisation from WGI AR4 are: 350 ppm, 1.0°C [0.6–1.4]; 450 ppm, 2.1°C [1.4–3.1]; 550 ppm, 2.9°C [1.9–4.4]; 650 ppm, 3.6°C [2.4–5.5]; 750 ppm, 4.3°C [2.8–6.4]; 1,000 ppm, 5.5°C [3.7–8.3] and 1,200 ppm, 6.3°C [4.2–9.4].
Figure 20.5. Geographical distribution of vulnerability in 2050 with and without mitigation along an SRES A2 emissions scenario with a climate sensitivity of 5.5°C. (a) portrays vulnerability with a static representation of current adaptive capacity. (b) shows vulnerability with enhanced adaptive capacity worldwide. (c) displays the geographical implications of mitigation designed to cap effective atmospheric concentrations of greenhouse gases at 550 ppm. (d) offers a portrait of the combined complementary effects of mitigation to the same 550 ppm concentration limit and enhanced adaptive capacity. Source: Yohe et al., 2006b.
Figure 20.6. Geographical distribution of vulnerability in 2100 with and without mitigation along an SRES A2 emissions scenario with a climate sensitivity of 5.5°C. (a) portrays vulnerability with a static representation of current adaptive capacity. (b) shows vulnerability with enhanced adaptive capacity worldwide. (c) displays the geographical implications of mitigation designed to cap effective atmospheric concentrations of greenhouse gases at 550 ppm. (d) offers a portrait of the combined complementary effects of mitigation to the same 550 ppm concentration limit and enhanced adaptive capacity. Source: Yohe et al., 2006b.
respectively. Significant improvement is seen in 2050, but adaptation alone still cannot reduce extreme vulnerability worldwide in 2100. The lower panels present the effect of limiting atmospheric concentrations of greenhouse gases to 550 ppm along least-cost emissions trajectories; global mean temperature is 1.3°C and 3.1°C higher than 1990 levels by 2050 and 2100 in this case. In the lower left panels, adaptive capacity is again held constant at current levels. Mitigation reduces vulnerability across much of the world in 2050, but extreme vulnerability persists in developing countries and threatens developed countries in 2100. Mitigation alone cannot overcome climate risk. Finally, the lower right panels show the combined effects of investments in enhanced adaptive capacity and mitigation. Climate risks are substantially reduced in 2050, but significant vulnerabilities reappear by 2100. Developing countries are still most vulnerable. Developed countries are also vulnerable, but they see noticeable benefits from the complementary effects of the policy portfolio. These results suggest that global mitigation efforts up to 2050 would benefit developing countries more than developed countries when combined with enhanced adaptation. By 2100, however, climate change would produce significant vulnerabilities ubiquitously even if a relatively restrictive concentration cap were implemented in combination with a programme designed to enhance adaptive capacity significantly.
This section extends some of the ideas outlined in Najam et al. (2003); they focus on mainstreaming climate-change adaptation into planning and development decisions with particular emphasis on participatory processes. 20.8.1 Challenges and opportunities for mainstreaming adaptation into national, regional and local development processes
20.8 Opportunities, co-benefits and challenges for adaptation
be and can be done can be documented, but action on the ground to mainstream adaptation to climate change remains limited, particularly in the least developed countries. National policy making in this context remains a major challenge that can only be met with increased international funding for adaptation and disaster management (Ahmad and Ahmed, 2002; Jegillos, 2003; Huq et al., 2006). Socio-economic and even environmental policy agendas of developing countries do not yet prominently embrace climate change (Beg et al., 2002) even though most developing countries participate in various international protocols and conventions relating to climate change and sustainable development and most have adopted national environmental conservation and natural disaster management policies. Watson International Scholars of the Environment (2006) has offered some suggestions for improved mainstreaming within multilateral environmental agreements; they include fostering links with poverty reduction and increasing support designed to engage professionals, researchers and governments at local levels in developing countries more directly. Even as economic growth is pursued, progress towards health, education, training and access to safe water and sanitation, and other indicators of social and environmental progress including adaptive capacity remains a significant challenge. It can be addressed through appropriate policies and commitment to ending poverty (WSSD, 2002; Sachs, 2005). Strengthened linkages between government and people, and the consequent capacity building at local levels, are key factors for robust progress towards sustainability at the grassroots (Jegillos, 2003). Social and environmental (climate change) issues are, however, often left resource-constrained and without effective institutional support when economic growth takes precedence (UNSEA, 2005). 20.8.2 Participatory processes in research and practice
An international opportunity for mainstreaming adaptation into national, regional and local development processes has recently emerged with the community approach to disaster management adopted by the World Conference on Disaster Reduction held in Kobe, Hyogo, Japan in January 2005 (Hyogo Declaration, 2005). This approach is described in, for example, UNCRD (2003). The results of an action research and pilot activity undertaken during 2002 to 2004 (APJED, 2004) have been reported, albeit on a limited scale in Bangladesh, India and Nepal, with support from World Meteorological Organization (WMO) and Global Water Partnership (GWP). The pilot activity focused on community approaches to flood management, and found that a community flood management committee formed in a local area, working in co-operation with the relevant local government and supported by national government policy, can significantly reduce adverse consequences of floods. There are, however, many challenges. Progress in carrying out analyses and identifying what needs to
Participatory processes can help to create dialogues that link and mutually instruct researchers, practitioners, communities and governments. There are, however, challenges in applying these processes as a methodology for using dialogue and narrative (i.e., communication of quantitative and qualitative information) to influence social learning and decision-making, including governance. Knowledge about climate-change adaptation and sustainable development can be translated into public policy through processes that generate usable knowledge. The idea of usable knowledge in climate assessments stems from the experiences of national and international bodies (academies, boards, committees, panels, etc.) that offer credible and legitimate information to policymakers through transparent multidisciplinary processes (Lemos and Morehouse, 2005). It requires the inclusion of local knowledge, including indigenous knowledge (see Box 20.1), to complement more formal technical understanding generated through scientific research and the consideration of the role that institutions and governance play in the translation of scientific information into effective action.
Research on indigenous environmental knowledge has been undertaken in many countries, often in the context of understanding local oral histories and cultural attachment to place. A survey of research during the 1980s and early 1990s was produced by Johnson (1992). Reid et al. (2006) outline the many technical and social issues related to the intersection of different knowledge systems, and the challenge of linking the scales and contexts associated with these forms of knowledge. With the increased interest in climate change and global environmental change, recent studies have emerged that explore how indigenous knowledge can become part of a shared learning effort to address climate-change impacts and adaptation, and its links with sustainability. Some examples are indicated here. Sutherland et al. (2005) describe a community-based vulnerability assessment in Samoa, addressing both future changes in climate-related exposure and future challenges for improving adaptive capacity. Twinomugisha (2005) describes the dangers of not considering local knowledge in dialogues on food security in Uganda. A scenario-building exercise in Costa Rica has been undertaken as part of the Millennium Ecosystem Assessment (MA, 2005). This was a collaborative study in which indigenous communities and scientists developed common visions of future development. Two pilot five-year storylines were constructed, incorporating aspects of coping with external drivers of development (Bennett and Zurek, 2006). Although this was not directly addressing climate change, it demonstrates the potential for joint scenario-building incorporating different forms of knowledge. In Arctic Canada, traditional knowledge was used as part of an assessment which recognised the implications of climate change for the ecological integrity of a large freshwater delta (NRBS, 1996). In another case, an environmental assessment of a proposed mine was produced through a partnership with governments and indigenous peoples. Knowledge to facilitate sustainable development was identified as an explicit goal of the assessment, and climate-change impacts were listed as one of the long-term concerns for the region (WKSS, 2001). Vlassova (2006) describes results of interviews of indigenous peoples of the Russian North on climate and environmental trends within the Russian boreal forest. Additional examples from the Arctic are described in ACIA (2005), Reidlinger and Berkes (2001), Krupnik and Jolly (2002), Furgal et al. (2006) and Chapter 15.
Social learning of complex issues like climate change emerges through consensus that includes both scientific discourse and policy debate. In the case of climate change, participatory processes encourage local practitioners from climate-sensitive endeavours (water management, land-use planning, etc.) to become engaged so that past experiences can be included in the study of (and the planning for) future climate change and development pressures. Processes designed to integrate various dimensions of knowledge about how regional resource systems operate are essential; so is understanding of how resource systems are affected by biophysical and socioeconomic forces including a wide range of possible future changes in climate. This requirement has led to increased interest in a number of participatory processes like participatory integrated assessment (PIA) and participatory mapping (using, for example, specially designed geographic information systems – GIS). PIA is an umbrella term describing approaches in which nonresearchers play an active role in integrated assessment (Rotmans and van Asselt, 2002). Participatory processes can be used to facilitate the integration of biophysical and socioeconomic aspects of climate-change adaptation and
development by creating opportunities for shared experiences in learning, problem definition and design of potential solutions (Hisschemöller et al., 2001). Van Asselt and Rijkens-Klomp (2002) identify several approaches, including methods for mapping diversity of opinion (e.g., focus groups, participatory modelling) and reaching consensus (e.g., citizens’ juries, participatory planning). Kangur (2004) reported on a recent exercise on water policy that employed citizens’ juries. PIA has also been used to facilitate the development of integrated models (e.g., Turnpenny et al., 2004) and to use models to facilitate policy dialogue (e.g., van de Kerkhof, 2004). Participatory mapping is a process by which local information, including indigenous knowledge, is incorporated into information management systems (Corbett et al., 2006). Ranging from paper to GIS, it is becoming more popular, and it has contributed to the increased application of Participatory Rural Appraisal (PRA) and Rapid Rural Appraisal (RRA) as techniques to support rural development (Chambers, 2006). Maps have displayed natural resources, social patterns and mobility, and they have been used to identify landscape changes, tenure, boundaries and places of cultural significance (Rambaldi et al., 2006). With the advent of modern GIS technologies,
concerns have been raised regarding disempowerment of communities from lack of training. Questions related to who owns the maps and to who controls their use have also been raised (Corbett et al., 2006; Rambaldi et al., 2006). The long-term sustainability of dialogue processes is critical to the success of participatory approaches. For PIA, PRA, participatory GIS and similar processes to be successful as shared learning experiences, they have to be inclusive and transparent. Haas (2004) describes examples of experiences in social learning on sustainable development and climate change, noting the importance of sustaining the learning process over the long term, and maintaining distance between science and policy while still promoting focused science-policy interactions. Applications of focus group and other techniques for stakeholder engagement are described for several studies in Europe (Welp et al., 2006) and Africa (Conde and Lonsdale, 2004). However, there has been particular concern regarding its application within development processes and hazard management in poor countries. Cooke and Kothari (2001) and Garande and Dagg (2005) document some problems, including hindering empowerment of local scale interests, reinforcing existing power structures and constraining how local knowledge is expressed. Barriers include uneven gains from cross-scale interactions (Adger et al., 2005; Young, 2006) and increased responsibility without increased capacity (Allen, 2006). There can be difficulties in reaching consensus on identifying and engaging participants (Bulkeley and Mol, 2003; Parkins and Mitchell, 2005), and in interpreting the results of dialogue within variations in cultural and epistemological contexts (e.g., Huntington et al., 2006). There are also challenges in measuring the quality of dialogue (debate, argument), particularly the transparency of process, promotion of learning and indicators of influence (van de Kerkhof, 2004; Rowe and Frewer, 2000). Participatory governance is part of a growing global movement to decentralise many aspects of natural resources management. Hickey and Mohan (2004) offer several examples of the convergence of participatory development and participatory governance with empowerment for marginalised communities. Other examples include agrarian reform in the Philippines, the Popular Participation Law in Bolivia (Schneider, 1999; Iwanciw, 2004) and the appointment of an ‘exploratory committee’ for addressing water resources concerns in Nagoya, Japan (Kabat et al., 2002). In each case, the point is to improve access to resources and enhance social capital (Larson and Ribot, 2004a and 2004b). Unfortunately, broadening decision-making can work to exacerbate vulnerabilities. For example, there have been cases emerging from Latin America describing difficulties in building national adaptive capacity as national and local institutions change their roles in governance. Although the language of sustainability and shared governance is widely accepted, obtaining benefits from globalisation in enhanced adaptive capacity is difficult (Eakin and Lemos, 2006). Dialogue processes in assessment and appraisal are becoming important tools in the support of participatory processes. Although they may be seen as relatively similar activities, PIA and PRA have different mandates. The latter is directly within a policy process (selecting among development options), while the former is a research method that assesses complex problems
(e.g., environmental impact of development, climate-change impacts/adaptation), producing results that can have policy implications. This chapter’s discussion on PIA is offered as a complement to integrated modelling results reported in Sections 20.6 and 20.7 to suggest that PIA may assist in providing regional-scale technical support to match the scale of information needs of decentralised governance. An agricultural example of a PIA of climate-change adaptation can be found in the eastern United Kingdom (Lorenzoni et al., 2001). Adaptation options are identified (e.g., shifting cultivation times, modifying soil management to improve water retention and avoid compaction), but questions about how a climate component can be built into the way nonclimate issues are currently addressed emerge. Long-term strategies may have to include greater fluctuations in crop yields across a region; as a result, farm operations may have to diversity if they are to maintain incomes and employment. The compartmentalisation of regional decision-making is seen as a barrier to encouraging more sustainable land management over the periods in which climate change evolves. In an example from Canada, Cohen and Neale (2006) and Cohen et al. (2004) illustrate the linkages between water management and scenarios of population growth and climate change in the Okanagan region (see also Chapter 3, Box 3.1). Planners in one district have responded by incorporating adaptation to climate change into long-term water plans (Summit Environmental Consultants Ltd., 2004) even though governance-related obstacles to proactive implementation of innovative measures to manage water demand have appeared in the past (Shepherd et al., 2006). A comprehensive understanding of the implications of extreme climate change requires an in-depth exploration of the perceptions and reactions of the affected stakeholder groups and the lay public. Toth and Hizsnyik (2005) describe how participatory techniques might be applied to inform decisions in the context of possible abrupt climate change. Their project has studied one such case, the collapse of the West Antarctic Ice Sheet and a subsequent 5 to 6 m sea-level rise. Possible methods for assessing the societal consequences of impacts and adaptations include simulation-gaming techniques, a policy exercise approach, as well as directed focus-group conversations. Each approach can be designed to explore adaptation as a local response to a global phenomenon. As a result, each sees adaptation being informed by a fusion of topdown descriptions of impacts from global climate change and bottom-up deliberations rooted in local, national and regional experiences (see Chapter 2, Section 2.2.1). 20.8.3 Bringing climate-change adaptation and development communities together to promote sustainable development
The Millennium Development Goals (MDGs) are the latest international articulation of approaching poverty eradication and related goals in the developing world (see Section 20.7.1). Economic growth is necessary for poverty reduction and promoting other millennium goals; but, unless the growth achieved is equitably distributed, the result is a lopsided development where inequality increases. Many countries face
intensifying poverty and inequality predicaments in the wake of undertaking free market policies (UNDP, 2003; UNSEA, 2005). As noted above, however, climate change is represented in the Millennium goals solely by indicators of changes in energy use per unit of GDP and/or by total or per capita emissions of CO2. Tracking indicators of protected areas for biological diversity, changes in forests and access to water all appear in the goals, but they are not linked to climate-change impacts or adaptation; nor are they identified as part of a country’s capacity to adapt to climate change. Other issues of particular concern include ensuring energy services, promoting agriculture and industrialisation, promoting trade and upgrading technologies. Sustainable natural-resource management is a key to sustained economic growth and poverty reduction. It calls for clean energy sources; and the nature and pattern of agriculture, industry and trade should not unduly impinge on ecological health and resilience. Otherwise, the very basis of economic growth will be shattered through environmental degradation, more so as a consequence of climate change (Sachs, 2005). Put another way by Swaminathan (2005), developing and employing ’eco-technologies‘ (based on an integration of traditional and frontier technologies including biotechnologies, renewable energy and modern management techniques) is a critical ingredient rooted in the principles of economics, gender, social equity and employment generation with due emphasis given to climate change. For environmentally-sustainable economic growth and social progress, therefore, development policy issues must inform the work of the climate-change community such that the two communities bring their perspectives to bear on the formulation and implementation of integrated approaches and processes that recognise how persistent poverty and environmental needs exacerbate the adverse consequences of climate change. In this process, science has a critical role to play in assessing the prevailing realities and likely future scenarios, and identifying policies and cost-effective methods to address various aspects of development and climate change; and it is important that all relevant stakeholders are involved in science-based dialogues (Welp et al., 2006). In order to go down this integrated and participatory road, a strong political will and public commitment to promoting sustainable development is needed, focusing simultaneously on economic growth, social progress, environmental conservation and adaptation to climate change (World Bank, 1998; AfDB et al., 2003). It is also important that private and public sectors work together within a framework of identified roles of each, with economic, social and climatechange perspectives built into the process. Further, co-ordination among national development and climate-change communities, as well as co-ordination among appropriate national and international institutions, is imperative. This raises an important question regarding the process for bringing climate change and sustainable development together. Growing interest in these linkages is evident in a series of recent publications, including Toth (1999), Yamin (2004), Collier and Löfstedt (1997), Jepma and Munasinghe (1998), Munasinghe and Swart (2000, 2005), Abaza and Baranzini (2002), Markandya and Halsnaes (2002), Cohen et al. (1998), Kok et al. (2002), Swart et al. (2003). A number of themes that are
particularly relevant to adaptation run through this literature. They include the need for equity between developed and developing countries in the delineation of rights and responsibilities within any climate-change response framework. Shue (1999), Thomas and Twyman (2004) and Paavola and Adger (2006) point, as well, to the need for equity across vulnerable groups that are disproportionately exposed to climate-change impacts. Hasselman (1999), Gardiner (2004) and Kemfert and Tol (2002) identify some examples from economics which raise concerns for intergenerational ethics; i.e., the degree to which the interests of future generations are given relatively lower weighting in favour of short-term concerns. Intergenerational justice implications, for individuals and collectives (e.g., indigenous cultures) are described in Page (1999). Masika (2002) specifically outlines gender aspects of differential vulnerabilities. Swart et al. (2003) identify the need to describe potential changes in vulnerability and adaptive capacity within the SRES storylines. Although linkages between climate-change adaptation and sustainable development should appear to be self evident, it has been difficult to act on them in practice. Beg et al. (2002) identify potential synergies between climate change and other policies that could facilitate adaptation, such as those that address desertification and biodiversity. Ethical guidance from various spiritual and religious sources is reviewed in Coward (2004). However, an ‘adaptation deficit’ exists. Burton and May (2004) identify this as the gap between current and optimal levels of adaptation to climate-related events (including extremes); it is expected that climate change and poor development decisions will lead to an increased adaptation deficit in the future. While mitigation within the UNFCCC includes clearly defined objectives, measures, costs and instruments, this is not the case for adaptation. Agrawala (2005) indicates that much less attention has been paid to how development could be made more resilient to climate-change impacts, and identifies a number of barriers to mainstreaming climate-change adaptation within development activity (see, as well Chapter 17, Section 17.3). The existence of these barriers does not mean that the development community does not recognise the linkage between development and climate-change adaptation. Climate change is identified as a serious risk to poverty reduction in developing countries, particularly because these countries have a limited capacity to cope with current climate variability and extremes not to mention future climate change (Schipper and Pelling, 2006). Adaptation measures will need to be integrated into strategies of poverty reduction to ensure sustainable development, and this will require improved governance, mainstreaming of climate-change measures, and the integration of climate-change impacts information into national economic projections (AfDB et al., 2003; Davidson et al., 2003). Brooks et al. (2005) offer an extensive list of potential proxy indicators for national-level vulnerability to climate change, including health, governance and technology indicators. Agrawala (2005) describes case studies of natural resources management in Nepal, Bangladesh, Egypt, Fiji, Uruguay and Tanzania, and recommends several priority actions for overcoming barriers to mainstreaming, including project screening for climate-related
risk, inclusion of climate impacts in environmental impact assessments , and shifting emphasis from creating new plans to better implementation of existing measures. Approaches for integration of adaptation with development are outlined for East Africa (Orindi and Murray, 2005). The Commission for Africa (2005) explicitly links the need to address climate-change risks with achievement of poverty reduction and sustainable growth. In recent years, new mechanisms have been established to support adaptation, including the Lesser Developed Countries (LDC) Fund, Special Climate Change Fund and the Adaptation Fund (Huq, 2002; Brander, 2003; Desanker, 2004; Huq, 2006; Huq et al., 2006). They have provided visibility and opportunity to mainstream adaptation into local/regional development activities. However, there are technical challenges associated with defining adaptation benefits for particular actions within UNFCCC mechanisms such as the Global Environmental Facility (GEF). For example, Burton (2004) and Huq and Reid (2004) note that the calculation of costs of adapting to future climate change (as opposed to current climate variability), as well as the local nature of resulting benefits, are both problematic vis-à-vis GEF requirements for defining global environmental benefits. On the other hand, there are opportunities. Dang et al. (2003) illustrate how including “adaptation benefits of mitigation” in Vietnam offers a way of linking both criteria in the analysis of potential projects for inclusion in the Clean Development Mechanism. Bouwer and Aerts (2006) and Schipper and Pelling (2006) identify opportunities for integrating climate-change adaptation and disaster risk management through insurance mechanisms, official development assistance and ongoing risk management programmes. Niang-Diop and Bosch (2004) outline methods for linking adaptation strategies with sustainable development at national and local scales, as part of National Adaptation Programmes of Action (NAPAs). As of the autumn of 2006, the LDC Fund was operational in its support of NAPAs in LDCs and both the Conference of Parties (COP) and GEF were in the process of defining how the implementation of adaptation activities highlighted in NAPAs could be funded (Huq et al., 2006).
Uncertainties, unknowns and priorities for research illuminate the confidence statements that modify scientific conclusions delivered to members of the policy community. For the research community, however, they can be translated into tasks designed to improve understanding and elaborate sources confidence. This section is therefore organised as a series of tasks. Expand understanding of the synergies in and/or obstacles to simultaneous progress in promoting enhanced adaptive capacity and sustainable development. The current state of knowledge in casting adaptive capacity and vulnerability into the future is primitive. More thorough understandings of the process by which adaptive capacity and vulnerability evolve over time along specific development pathways are required.
Commonalities exist across the determinants of adaptive capacity, mitigative capacity and the factors that support sustainable development, but current understanding of how they can be recognised and exploited is minimal. Integrate more closely current work in the development and climate-change communities. Synergies exist between practitioners and researchers in the sustainable development and climate-change communities, but there is a need to develop means by which these communities can integrate their efforts more productively. The relative efficacies of dialogue processes and new tools required to promote this integration, and the various participatory and/or model-based approaches required to support their efforts must be refined or developed from scratch. Opportunities for shared learning should be identified, explored and exploited. Search for common ground between spatially explicit analyses of vulnerability and aggregate integrated assessment models. Geographical and temporal scales of development and climate initiatives vary widely. The interaction and intersection between spatially explicit and aggregate integrated assessment models has yet to be explored rigorously. For example, representations of adaptive capacities and resulting vulnerabilities in aggregate integrated assessment models are still rudimentary. As progress is encouraged in improving their abilities to depict reality, research initiatives must also recognise and work to overcome difficulties in matching the scales at which models are constructed and exercised with the scales at which decisions are made. New tools are required to handle these differences, particularly between the local and national, short-to-medium-term scales of adaptation and development programmes and projects and the global, medium-to-long-term scale of mitigation. Recognise that uncertainties will continue to be pervasive and persistent, and develop or refine new decision-support mechanisms that can identify robust coping strategies even in the face of this uncertainty. Significant uncertainties in estimating the social cost of greenhouse gases exist, and many of their sources have been identified; indeed many of their sources reside in the research needs listed above. Reducing these uncertainties would certainly be productive, but it cannot be guaranteed that future research will make much progress in this regard. It follows that concurrent improvement in our ability to use existing decision-support tools and to design new approaches to cope with uncertainties and associated risks that will be required over the foreseeable future is even more essential. In short, identify appropriate decision-support tools and clarify the criteria that they can inform in an uncertain world. Characterise the full range of possible climate futures and the paths that might bring them forward. The research communities in both climate and development must, along with practitioners and decision-makers, be informed not only about the central tendencies of climate change and its ramifications, but also about the outlier possibilities about which the naturalscience community is less sanguine. It is simply impossible to comprehend the risks associated with high-consequence outcomes with low probabilities if neither their character nor their likelihood has been described.
This chapter has offered a glimpse into where to turn for guidance in confronting and managing the risks associated with climate change and climate variability. Indeed, the climate problem is a classic risk management problem of the sort with which decision-makers are already familiar. It is critical to see risk as the product of likelihood and consequence, to recognise that the likelihood of a climate impact is dependent on natural and human systems, and to understand that the consequence of that impact can be measured in terms of a multitude of numeraires (currency, millions at risk, species extinction, abrupt physical changes and so on). These expressions of risk are determined fundamentally by location in time and space. This chapter also points to synergies that exist at the nexus of sustainable development and adaptive capacity, primarily by noting for the first time that many of the goals of sustainable development match the determinants of adaptive capacity (and, for that matter, mitigative capacity). Planners in the decisionintensive ministries around the world are therefore already familiar with the generic mechanisms by which including climate change into their risk assessments of development programmes can complicate their decisions. Adding climate to the list of multiple stresses which can impede progress in meeting their goals in their specific context is thus not a new problem. Climate change, even when its impacts are amplified by the effects of other stresses, is just one more thing: one more problem to confront, but also one more reason to act in ways that promote progress along multiple fronts. Exploitation of the synergies is not automatic, so care must be taken to avoid development activities that can exacerbate climate change or impacts just as care must be taken to take explicit account of climate risks. The United Nations Framework Convention on Climate Change commits governments to avoiding “dangerous anthropogenic interference with the climate system”, but governments will be informed in their deliberations of what is or is not ‘dangerous’ only by an approach that explicitly reflects the rich diversity of climate risk across the globe and into the coming decades instead of burying this diversity into incomplete aggregate indices of damages. Risk management techniques have been designed for such tasks; but it is important to note that risk-based approaches require exploration of the implications of not only the central tendencies of climate change that are the focus of consensus-driven assessments of the literature, but also the uncomfortable (or more benign) futures that reside in the ‘tails’ of current understanding. Viewing the climate issue from a risk perspective can offer climate policy deliberations and negotiations new insight into the synergies by which governments can promote sustainable development, reduce the risk of climate-related damages and take advantage of climate-related opportunities.
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