IPCC Fourth Assessment Report, Working Group II: Chapter 18

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April 5, 2010, 12:00 am
July 30, 2012, 1:44 pm
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Originally published by our Content Partner: Intergovernmental Panel on Climate Change (other articles)

Table of Contents

Executive summary

18.1 Introduction

18.1.1 Background and rationale
Box 18.1. Definitions of terms
18.1.2 Differences, similarities and complementarities between adaptation and mitigation
18.1.3 Structure of the chapter

18.2 Summary of relevant knowledge in the IPCC Third Assessment Report

18.3 Decision processes, stakeholder objectives and scale

18.3.1 The nature of the decision problem
18.3.2 Stakeholder roles and spatial and temporal scales

18.4 Inter-relationships between adaptation and mitigation and damages avoided

18.4.1 Trade-offs and synergies in global-scale analysis
18.4.2 Consideration of costs and damages avoided and/or benefits gained
18.4.3 Inter-relationships within regions and sectors
Box 18.2. Analysis of stabilisation scenarios

18.5 Inter-relationships in a climate policy portfolio

18.6 Response capacity and development pathways

18.7 Elements for effective implementation

18.7.1 Climate policy and institutions
Box 18.3. Mainstreaming
18.7.2 Inter-relationships in practice

18.8 Uncertainties, unknowns and priorities for research

Contributors Terms of Use Print Version References (IPCC Fourth Assessment Report, Working Group II: Chapter 18)

Inter-relationships between adaptation and mitigation

This chapter should be cited as:

Klein, R.J.T., S. Huq, F. Denton, T.E. Downing, R.G. Richels, J.B. Robinson, F.L. Toth, 2007: Inter-relationships between adaptation and mitigation. 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, 745-777.

Executive summary

This chapter identifies four types of inter-relationships between adaptation and mitigation:

  • Adaptation actions that have consequences for mitigation,
  • Mitigation actions that have consequences for adaptation,
  • Decisions that include trade-offs or synergies between adaptation and mitigation,
  • Processes that have consequences for both adaptation and mitigation.

The chapter explores these inter-relationships and assesses their policy relevance. It is a new chapter compared to the IPCC Third Assessment Report and is based on a relatively small, albeit growing, literature. Its key findings are as follows.

Effective climate policy aimed at reducing the risks of climate change to natural and human systems involves a portfolio of diverse adaptation and mitigation actions (very high confidence).

Even the most stringent mitigation efforts cannot avoid further impacts of climate change in the next few decades (Working Group I Fourth Assessment Report, Working Group III Fourth Assessment Report), which makes adaptation unavoidable. However, without mitigation, a magnitude of climate change is likely to be reached that makes adaptation impossible for some natural systems, while for most human systems it would involve very high social and economic costs (see Chapter 4, Section 4.6.1 and Chapter 17, Section 17.4.2).Adaptation and mitigation actions include technological, institutional and behavioural options, the introduction of economic and policy instruments to encourage the use of these options, and research and development to reduce uncertainty and to enhance the options’ effectiveness and efficiency 18.5. Opportunities exist to integrate adaptation and mitigation into broader development strategies and policies [18.6].

Decisions on adaptation and mitigation are taken at different governance levels and inter-relationships exist within and across each of these levels (high confidence).

The levels range from individual households, farmers and private firms, to national planning agencies and international agreements. Effective mitigation requires the participation of major greenhouse-gas emitters globally, whereas most adaptation takes place from local to national levels. The climate benefits of mitigation are global, while its costs and ancillary benefits arise locally. In most cases, both the costs and benefits of adaptation accrue locally and nationally 18.4, 18.5. Consequently, mitigation is primarily driven by international agreements and ensuing national public policies, possibly complemented by unilateral and voluntary actions, whereas most adaptation involves private actions of affected entities, public arrangements of impacted communities, and national policies 18.7.

Creating synergies between adaptation and mitigation can increase the cost-effectiveness of actions and make them more attractive to stakeholders, including potential funding agencies (medium confidence).

Analysis of the inter-relationships between adaptation and mitigation may reveal ways to promote the effective implementation of adaptation and mitigation actions together [18.5]. However, such synergies provide no guarantee that resources are used in the most efficient manner when seeking to reduce the risks to climate change [18.7]. In addition, the absence of a relevant knowledge base and of human, institutional and organisational capacity can limit the ability to create synergies. Opportunities for synergies are greater in some sectors (e.g., agriculture and forestry, buildings and urban infrastructure) but are limited in others (e.g., coastal systems, energy, health). A lack of both conceptual and empirical information that explicitly considers both adaptation and mitigation makes it difficult to assess the need for and potential of synergies in climate policy 18.4, 18.8.

It is not yet possible to answer the question as to whether or not investment in adaptation would buy time for mitigation (high confidence).

Understanding the specific economic trade-offs between the immediate localised benefits of adaptation and the longer-term global benefits of mitigation requires information on the actions’ costs and benefits over time. Integrated assessment models provide approximate estimates of relative costs and benefits at highly aggregated levels, but only a few models include feedbacks from impacts. Intricacies of the inter-relationships between adaptation and mitigation become apparent at the more detailed analytical and implementation levels 18.5, 18.6. These intricacies, including the fact that specific adaptation and mitigation options operate on different spatial, temporal and institutional scales and involve different actors with different interests, beliefs, value systems and property rights, present a challenge to designing and implementing decisions based on economic trade-offs beyond the local scale. In particular the notion of an ‘optimal mix’ of adaptation and mitigation is difficult to make operational, because it requires the reconciliation of welfare impacts on people living in different places and at different points in time into a global aggregate measure of well-being. 18.7

People’s capacities to adapt and mitigate are driven by similar sets of factors (high confidence).

These factors represent a generalised response capacity that can be mobilised for both adaptation and mitigation. Response capacity, in turn, is dependent on the societal development path chosen. Enhancing society’s response capacity through the pursuit of sustainable development is therefore one way of promoting both adaptation and mitigation [18.6]. This would facilitate the effective implementation of both options, as well as their mainstreaming into sectoral planning and development. If climate policy and sustainable development are to be pursued in an integrated way, then it will be important not simply to evaluate specific policy options that might accomplish both goals but also to explore the determinants of response capacity that underlie those options as they relate to underlying socioeconomic and technological development paths 18.7.

18.1 Introduction

The United Nations Framework Convention on Climate Change (UNFCCC) identifies two responses to climate change: mitigation of climate change by reducing greenhouse-gas emissions and enhancing sinks, and adaptation to the impacts of climate change. Most industrialised countries have committed themselves, as signatories to the UNFCCC and the Kyoto Protocol, to adopting national policies and taking corresponding measures on the mitigation of climate change and to reducing their overall greenhouse-gas emissions (United Nations, 1997). An assessment of current efforts aimed at mitigating climate change, as presented by the Working Group III Fourth Assessment Report (WGIII AR4), Chapter 11 (Barker et al., 2007), shows that current commitments would not lead to a stabilisation of atmospheric greenhouse-gas concentrations. In fact, according to the Working Group I Fourth Assessment Report (WGI AR4), owing to the lag times in the global climate system, no mitigation effort, no matter how rigorous and relentless, will prevent climate change from happening in the next few decades (Christensen et al., 2007; Meehl et al., 2007). Chapter 1 in this volume shows that the first impacts of climate change are already being observed.

Adaptation is therefore unavoidable (Parry et al., 1998). Chapter 17 (see Section 17.2 and Section 17.4) presents examples of adaptations to climate change that are currently being observed, but concludes that there are limits and barriers to effective adaptation. Even if these limits and barriers were to be removed, however, reliance on adaptation alone is likely to lead to a magnitude of climate change in the long run to which effective adaptation is no longer possible or only at very high social, economic and environmental costs. For example, Tol et al. (2006) show what would be the difficulties in adapting to a five-metre rise in sea level in Europe. It is therefore no longer a question of whether to mitigate climate change or to adapt to it. Both adaptation and mitigation are now essential in reducing the expected impacts of climate change on humans and their environment.

18.1.1 Background and rationale

Traditionally the primary focus of international climate policy has been on the use and production of energy. This policy focus was reflected in the Second Assessment Report (SAR), which, in discussing mitigation, paid relatively little attention to greenhouse gases other than CO2 and to the potential for enhancing carbon sinks. Likewise, it paid little heed to adaptation. Since the publication of the SAR, the international climate policy community has become aware that energy policy alone will not suffice in the quest to control climate change and limit its impacts. Climate policy is being expanded to consider a wide range of options aimed at sequestering carbon in vegetation, oceans and geological formations, at reducing the emissions of non-CO2 greenhouse gases, and at reducing the vulnerability of sectors and communities to the impacts of climate change by means of adaptation. Consequently, the Third Assessment Report (TAR) provided amore balanced treatment of adaptation and mitigation.

Figure 18.1. A schematic overview of inter-relationships between adaptation, mitigation and impacts, based on Holdridge’s life-zone classification scheme (Holdridge, 1947, 1967; M.L. Parry, personal communication).

The TAR demonstrated that the level of climate-change impacts, and whether or not this level is dangerous (see Article 2 of the UNFCCC), is determined by both adaptation and mitigation efforts (Smith et al., 2001).Adaptation can be seen as direct damage prevention, while mitigation would be indirect damage prevention (Verheyen, 2005). However, only recently have policy-makers expressed an interest in exploring interrelationships between adaptation and mitigation. Recognising the dual need for adaptation and mitigation, as well as the need to explore trade-offs and synergies between the two responses, they are faced with an array of questions (GAIM Task Force, 2002; Clark et al., 2004; see also Figure 18.1). How much adaptation and mitigation would be optimal, when, and in which combination? Who would decide, and based on what criteria? Are adaptation and mitigation substitutes or are they complementary to one another? When and where is it best to invest in adaptation, and when and where in mitigation? What is the potential for creating synergies between the two responses? How do their costs and effectiveness vary over time? How do the two responses affect, and how are they affected by, development pathways? These are some of the questions that have led the IPCC to include this chapter on inter-relationships between adaptation and mitigation in its Fourth Assessment Report (AR4).

The relevant literature to date does not provide clear answers to the above questions. Research on adaptation and mitigation has been rather unconnected to date, involving largely different communities of scholars who take different approaches to analyse the two responses. The mitigation research community has focused strongly, though not exclusively, on technological and economic issues, and has traditionally relied on ‘top-down’ aggregate modelling for studying trade-offs inherent in mitigation (see the WGIII AR4 (IPCC, 2007)). After a period of conceptual introspection, the adaptation research community has put its emphasis on local and place-based analysis: a research approach it shares with scholars in development studies and disaster risk reduction (Adger et al., 2003; Pelling, 2003; Smith et al., 2003; see also Chapter 17). In addition, adaptation is studied at the sectoral level (see Chapters 3 to 8).

One important research effort that does consider both adaptation and mitigation is integrated assessment modelling. Integrated assessment models (IAMs) typically combine energy models and sectoral impact models with climate, land use and socio-economic scenarios to analyse and compare the costs and benefits of climate change and climate policy to society (see also Chapter 2). However, climate policy in IAMs to date is dominated by mitigation; adaptation, when considered, is either represented as a choice between a number of technological options or else it follows from assumptions in the model about social and economic development (Schneider, 1997; Corfee-Morlot and Agrawala, 2004; Fisher et al., 2007).

New research on inter-relationships between adaptation and mitigation includes conceptual and policy analysis, as well as ‘bottom:up’ studies that analyse specific inter-relationships and their implications for sectors and communities. The latter studies often place the implementation of adaptation and mitigation within the context of broader development objectives (e.g., Tompkins and Adger, 2005; Robinson et al., 2006; Chapters 17 and 20). They complement integrated assessment modelling by studying the factors and processes that determine if and when adaptation and mitigation can be synergistic in climate policy. Owing to it being a new research field, the amount of literature is still small, although it is growing fast. At the same time, the literature is very diverse: there is no consensus as to whether or not exploiting interrelationships between adaptation and mitigation is possible, much less desirable. Some analysts (e.g., Venema and Cisse, 2004; Goklany, 2007) see potential for creating synergies between adaptation and mitigation, while others (e.g., Klein et al., 2005) are more sceptical about the benefits of considering adaptation and mitigation in tandem.

The differences in approaches between adaptation and mitigation research, and between integrated assessment modelling and ‘bottom:up’ studies, can create confusion when findings published in the literature appear to be inconsistent with one another. In assessing the literature on inter-relationships between adaptation and mitigation, this chapter does not hide any differences and inconsistencies that may exist between relevant publications. As artefacts of the research approaches that have emerged as described above, these differences and inconsistencies reflect the current state of knowledge. To provide as much clarity as possible from the outset definitions of important concepts are provided in Box 18.1. Next, Section 18.1.2 summarises important differences, similarities and complementarities between adaptation and mitigation.

Box 18.1. Definitions of terms

This box presents chapter-specific definitions of a number of (often related) terms relevant to the assessment of inter-relationships between adaptation and mitigation. Unless indicated otherwise, the definitions are specialisations of standard definitions found in reputable online dictionaries (e.g., http://www.m-w.com/, http://www.thefreedictionary.com/).

Trade-off: A balancing of adaptation and mitigation when it is not possible to carry out both activities fully at the same time (e.g., due to financial or other constraints).

Synergy: The interaction of adaptation and mitigation so that their combined effect is greater than the sum of their effects if implemented separately.

Substitutability: The extent to which an agent can replace adaptation by mitigation or vice versa to produce an outcome of equal value.

Complementarity: The inter-relationship of adaptation and mitigation whereby the outcome of one supplements or depends on the outcome of the other.

Optimality: The condition of being the most desirable that is possible under an expressed or implied restriction.

Portfolio: A set of actions to achieve a particular goal. A climate policy portfoliomay include adaptation,mitigation, research and technology development, as well as other actions aimed at reducing vulnerability to climate change.

Mainstreaming: The integration of policies and measures to address climate change in ongoing sectoral and development planning and decision-making, aimed at ensuring the sustainability of investments and at reducing the sensitivity of development activities to current and future climatic conditions (Klein et al., 2005).

18.1.2 Differences, similarities and complementarities between adaptation and mitigation

The TAR used the following definitions of climate change mitigation and adaptation.

  • Mitigation: An anthropogenic intervention to reduce the sources or enhance the sinks of greenhouse gases (IPCC, 2001a).
  • Adaptation: Adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities (IPCC, 2001a).

It follows from these definitions that mitigation reduces all impacts (positive and negative) of climate change and thus reduces the adaptation challenge, whereas adaptation is selective; it can take advantage of positive impacts and reduce negative ones (Goklany, 2005).

The two options are implemented on the same local or regional scale, and may be motivated by local and regional priorities and interests, as well as global concerns. Mitigation has global benefits (ancillary benefits might be realised at the local/regional level), although effective mitigation needs to involve a sufficient number of major greenhouse-gas emitters to foreclose leakage. Adaptation typically works on the scale of an impacted system, which is regional at best, but mostly local (although some adaptation might result in spill-overs across national boundaries, for example by changing international commodity prices in agricultural or forest-product markets). Expressed as CO2-equivalents, emissions reductions achieved by different mitigation actions can be compared and if the costs of implementing the actions are known, their cost-effectiveness can be determined and compared (Moomaw et al., 2001). The benefits of adaptation are more difficult to express in a single metric, impeding comparisons between adaptation efforts. Moreover, as a result of the predominantly local or regional effect of adaptation, benefits of adaptation will be valued differently depending on the social, economic and political contexts within which they occur (see Chapter 17).

The benefits of mitigation carried out today will be evidenced in several decades because of the long residence time of greenhouse gases in the atmosphere (ancillary benefits such as reduced air pollution are possible in the near term), whereas many adaptation measures would be effective immediately and yield benefits by reducing vulnerability to climate variability. As climate change continues, the benefits of adaptation (i.e., avoided damage) will increase over time. Thus there is a delay between incurring the costs of mitigation and realising its benefits from smaller climate change, while the time span between expenditures and returns of adaptation is usually much shorter. This difference is augmented in analyses adopting positive discount rates. These asymmetries have led to a situation whereby the initiative for mitigation has tended to stem from international agreements and ensuing national public policies (sometimes supplemented by community-based or private-sector initiatives), whereas the bulk of adaptation actions have historically been motivated by the self-interest of affected private actors and communities, possibly facilitated by public policies.

There are a number of ways in which adaptation and mitigation are related at different levels of decision-making. Mitigation efforts can foster adaptive capacity if they eliminate market failures and distortions, as well as perverse subsidies that prevent actors from making decisions on the basis of the true social costs of the available options. At a highly aggregated scale, mitigation expenditures appear to divert social or private resources and reduce the funds available for adaptation, but in reality the actors and budgets involved are different. Both options change relative prices, which can lead to slight adjustments in consumption and investment patterns and thus to changes in the affected economy’s development pathway, but direct trade-offs are rare. The implications of adaptation can be both positive and negative for mitigation. For example, afforestation that is part of a regional adaptation strategy also makes a positive contribution to mitigation. In contrast, adaptation actions that require increased energy use from carbon-emitting sources (e.g., indoor cooling) would affect mitigation efforts negatively.

18.1.3 Structure of the chapter

Based on the available literature and our current understanding of differences, similarities and complementarities between adaptation and mitigation (see Section 18.1.2), this chapter distinguishes between four types of inter-relationships between adaptation and mitigation:

  • Adaptation actions that have consequences for mitigation,
  • Mitigation actions that have consequences for adaptation,
  • Decisions that include trade-offs or synergies between adaptation and mitigation,
  • Processes that have consequences for both adaptation and mitigation.

The chapter is structured as follows. Section 18.2 summarises the knowledge relevant to this chapter that was presented in the TAR. Section 18.3 frames the challenge of deciding when, how much, and how to adapt and mitigate as a decision-theoretical problem, and introduces the differing roles and responsibilities of stakeholders and the scales on which they operate. Section 18.4 then assesses the existing literature on trade-offs and synergies between adaptation and mitigation, including the potential costs of and damage avoided by adaptation and mitigation, as well as regional and sectoral aspects. Following the above typology of inter-relationships, Section 18.5 provides examples of complementarities and differences as they appear from the literature, thus providing an assessment of possible elements of a climate policy portfolio. Section 18.6 presents adaptation and mitigation within the context of development pathways, thus providing the background against which policymakers and practitioners operate when acting on climate change. Section 18.7 assesses the literature on elements for effective implementation of climate policy that relies on interrelationships between adaptation and mitigation. Finally, Section 18.8 outlines information needs of climate policy and priorities for research.

18.2 Summary of relevant knowledge in the IPCC Third Assessment Report

Compared to the SAR, two of the Working Groups preparing the TAR were restructured. The scope assigned to Working Group II (WGII) was limited to impacts of climate change on sectors and regions and to issues of vulnerability and adaptation, while Working Group III (WGIII) was commissioned to assess the technological, economic, social and political aspects of mitigation. Whereas there were concerted efforts to assess links of both adaptation and mitigation to sustainable development (see Chapter 20, Section 20.7.3), there was little room to consider the direct relationships between these two domains. The integration of results and the development of policy oriented synthesis were therefore difficult (Toth, 2003).

The attempt to establish the foundations of the TAR Synthesis Report (IPCC, 2001a) in the final chapters of WGII and WGIII did not shed light on inter-relationships between adaptation and mitigation. The WGII TAR in Chapter 19 presented “reasons for concern about projected climate change impacts” in a summary figure that outlines the risks associated with different magnitudes of warming, expressed in terms of the increase in global mean temperature. Largely based on IAMs, the WGIII TAR in Chapter 10 summarised the costs of stabilising CO2 concentrations at different levels. These two summaries are difficult to compare because questions as to what radiative-forcing and climate sensitivity parameters should be used to bridge the concentration-temperature gap remain unanswered. Moreover, many statements in the two Working Group Reports were themselves distilled from a large number of reviewed studies. Yet the generic assumptions underlying the methods, the specific assumptions of the applications, the selected baseline values for the scenarios, incompatible discount rates, economic growth assumptions and many other postulations implicit in the parameterisation of adaptation and mitigation assessments were largely ignored or remained hidden in the Synthesis Report.

Nonetheless, the TAR presented new concepts for addressing inter-relationships between adaptation and mitigation. Local adaptive and mitigative capacities vary significantly across regions and over time. Superficially they appear to be strongly correlated because they share the same list of determinants. However, aggregate representation across nations or social groups of both adaptation and mitigation is misleading because the capacity to reduce emissions of greenhouse gases and the ability to adapt to it can deviate significantly. As the TAR pointed out: “one country can easily display high adaptive capacity and low mitigative capacity simultaneously (or vice versa)” (IPCC, 2001b; see also Yohe, 2001). In a wealthy nation, damages of climate change may fall on a small but influential social group and the costs of adaptation can be distributed across the entire population through the tax system. Yet, in the same country, another small group might be hurt by mitigation policies without the possibility to spread this burden. In addition to the conceptual deliberations, the TAR discussed inter-relationships between adaptation and mitigation at two levels: at the aggregated, global and national levels, and in the context of economic sectors and specific projects.

The WGII report pointed out that “adaptation is a necessary strategy at all scales to complement climate change mitigation efforts” (IPCC, 2001c), but also elaborates the complex relationships between the two domains at various levels. Some relationships are synergistic, while others are characterised by trade-offs. The report noted the arguments in the literature about the trade-off between adaptation and mitigation because resources committed to one are not available for the other, and also noted that this is “debatable in practice because the people who bear emissions reduction costs or benefits often are different from those who pay for and benefit from adaptation measures” (IPCC, 2001c). From the dynamic perspective, “climatic changes today still are relatively small, thus there is little need for adaptation, although there is considerable need for mitigation to avoid more severe future damages. By this logic, it is more prudent to invest the bulk of the resources for climate policy in mitigation, rather than adaptation” (IPCC, 2001c).Yet, as the WGIII TAR noted, one has to bear in mind the intergenerational trade-offs. The impacts of today’s climate change investments on future generations’ opportunities should also be considered. Investments might enhance the capacity of future generations to adapt to climate change, but at the same time may displace investments that could create other opportunities for future generations (IPCC, 2001b).

Chapter 10 of the WGIII TAR outlined the iterative process in which nations balance their own mitigation burden against their own adaptation and damage costs. “The need for, extent and costs of adaptation measures in any region will be determined by the magnitude and nature of the regional climate change driven by shifts in global climate. How global climate change unfolds will be determined by the total amount of greenhouse-gas emissions that, in turn, reflects nations’ willingness to undertake mitigation measures. Balancing mitigation and adaptation efforts largely depends on how mitigation costs are related to net damages (primary or gross damage minus damage averted through adaptation plus costs of adaptation). Both mitigation costs and net damages, in turn, depend on some crucial baseline assumptions: economic development and baseline emissions largely determine emissions reduction costs, while development and institutions influence vulnerability and adaptive capacity” (IPCC, 2001b).

Discussions of inter-relationships between adaptation and mitigation are sparser at the sector/project level. Some chapters in the WGII TAR noted the link to mitigation when discussing climate-change impacts and adaptation in selected sectors, primarily those related to land use, agriculture and forestry. Chapter 5 noted that “afforestation in agroforestry projects designed to mitigate climate change may provide important initial steps towards adaptation” (Gitay et al., 2001). Chapter 8 emphasised sustainable forestry, agriculture and wetlands practices that yield benefits in watershed management and flood/mudflow control but involve trade-offs such as wetlands restoration helping to protect against flooding and coastal erosion, but in some cases increasing methane release (Vellinga et al., 2001).

The WGII TAR in Chapter 12 observed the complexities in land management in Australia and New Zealand “where control of land degradation through farm and plantation forestry is being considered as a major option, partly for its benefits in controlling salinisation and water-logging, and possibly as a new economic option with the advent of incentives for carbon storage as a greenhouse mitigation measure” (IPCC, 2001c). Chapter 15 mentioned soil conservation practices (e.g., no tillage, increased forage production, higher cropping frequency) implemented as mitigation strategies in North America (Cohen et al., 2001). It observed that the Kyoto Protocol mentions human-induced land use changes and forestry activities (afforestation, reforestation, deforestation) as sinks of greenhouse gases for which sequestration credits can be claimed, and that agricultural sinks may be considered in the future. The market emerging in North America to enhance carbon sequestration leads to land management decisions with diverse effects. The negative consequences of reduced tillage implemented to enhance soil carbon sequestration include the increased use of pesticides for disease, insect and weed management; capturing carbon in labile forms that are vulnerable to rapid oxidation if the system is changed; and reduced yields and cropping management options and increased risk for farmers. The beneficial consequences of reduced tillage (especially no-till) are reduced input costs (e.g., fuel) for farmers, increased soil moisture and hence reductions in crop-water stress in dry areas, reduction in soil erosion and improved soil quality (IPCC, 2001c).

In chapters dealing with other sectors affected by climate change impacts and mitigation, less attention was paid to their inter-relationships. The WGII TAR in Chapter 8 mentioned energy end-use efficiency in buildings having both adaptation and mitigation benefits, as improved insulation and equipment efficiency can reduce the vulnerability of structures to extreme temperature episodes and emissions. An example of the more remote inter-relationships between adaptation and mitigation across space and time was provided by Chapter 17. Small island states are recognised to be vulnerable to climate change and tourism is a major source of income for many of them. While, over the long term, milder winters in their current markets could reduce the appeal of these islands as tourist destinations, they could be even more severely harmed by increased airline fares “if greenhouse gas mitigation measures (e.g., levies and emissions charges) were to result in higher costs to airlines servicing routes between the main markets and small island states” (IPCC, 2001c).

Finally, the WGII TAR in Chapter 8 drew attention to a link between adaptation and mitigation in the Kyoto Protocol that establishes a surcharge (‘set-aside’) on mitigation activities implemented as Clean Development Mechanism (CDM) projects. “One key issue is the size of the ‘set-aside’ from CDM projects that is dedicated to funding adaptation. If this set-aside is too large, it will make otherwise viable mitigation projects uneconomic and serve as a disincentive to undertake projects. This would be counterproductive to the creation of a viable source of funding for adaptation” (IPCC, 2001c).

18.3 Decision processes, stakeholder objectives and scale

A portfolio of actions is available for reducing the risks of climate change, within which each option requires evaluation of its individual and collective merits. Decision-makers at all levels need to decide on appropriate near-term actions in the face of the many long-term uncertainties and competing pressures, goals and market signals. Section 18.1 identified four types of interrelationships between adaptation and mitigation. Investments in mitigation may have consequences for adaptation; and investments in adaptation may have consequences for the emission of greenhouse gases. At the highest level of aggregation, adaptation and mitigation are both policy substitutes and policy complements, and may compete for finite resources. However, this need not be the case: both adaptation and mitigation may be considered in a policy process without invoking trade-offs, often in the context of broader considerations of sustainable development. This section introduces the nature of the decision problem followed by a review of stakeholder objectives, risk and scales.

18.3.1 The nature of the decision problem

It is difficult, and perhaps counterproductive, to explore the pay-offs from various types of investments without a conceptual framework for thinking about their interactions. Decision analysis provides one such framework (Raiffa, 1968; Keeney and Raiffa, 1976) that allows for the systematic evaluation of near-term options in light of the careful consideration of the potential consequences (see Lempert et al., 2004; IPCC, 2007; Keller et al., 2007; Nicholls et al., 2007; Chapter 20). The next several decades will require a series of decisions on how best to reduce the risks from climate change. There will be, no doubt, opportunities for learning and mid-course corrections. The immediate challenge facing policy-makers is to find out which actions are currently appropriate and likely to be robust in the face of the many long-term uncertainties.

The climate-policy decision tree can be represented as points at which decisions are made, and the reduction of uncertainty in the outcomes (if any) in a wide range of possible decisions and outcomes. The first decision node represents some of today’s investment options. How much should we invest in mitigation, how much in adaptation? How much should be invested in research? Once we act, we have an opportunity to learn and make mid-course corrections. The outcomes include types of learning that will occur between now and the next set of decisions. The outcomes are uncertain; the uncertainty may not be resolved but there will be new information which may influence future actions. Hence the expression: “act, then learn, and then act again” (Manne and Richels, 1992).

The ‘act, then learn, then act again’ framework is used here solely to lay out the elements of the decision problem and not as an alternative to the many analytical approaches discussed in this Report. Indeed, it can be used to parse various approaches for descriptive purposes, such as deterministic versus probabilistic approaches and cost-effectiveness analysis versus cost-benefit analysis. Decision analysis has been more widely applied to mitigation than to adaptation, although a robust decision framework is suitable for analysing the array of future vulnerabilities to climate change (Lempert and Schlesinger, 2000; Lempert et al., 2004).

18.3.2 Stakeholder roles and spatial and temporal scales

Climate change engages a multitude of decision-makers, both spatially and temporally. The UNFCCC, its subsidiary bodies and Member Parties have largely focused on mitigation. More recently, an increasing interest at the grassroots level has yielded additional local mitigation activities. Adaptation decisions embrace both the public and private sector, as some decisions involve large construction projects in the hands of public-sector decision-makers while other decisions are localised, involving many private-sector agents.

The roles of various stakeholders cover different aspects of inter-relationships between adaptation and mitigation. Stakeholders may be characterised according to their organisational structure (e.g., public or private), level of decision-making (e.g., policy, strategic planning, or operational implementation), spatial scale (e.g., local, national or international), time-frame of concern (e.g., near term to long term), and function within a network (e.g., single actor, stakeholder regime or multi-level institution).Decisions might cover adaptation only, mitigation only, or link adaptation and mitigation. Relatively few public or corporate decision-makers have direct responsibility for both adaptation and mitigation (e.g., Michaelowa, 2001). For example, adaptation might reside in a Ministry of Environment while mitigation policy is led by a Trade, Energy or Economic Ministry. Local authorities and land-use planners often cover both adaptation and mitigation (ODPM, 2004).

Stakeholders are exposed to a variety of risks, including financial, regulatory, strategic, operational, or to their reputations, physical assets, life and livelihoods (e.g., IRM et al., 2002). Decision-making may be motivated by climatic risks or climate change (e.g., climate-driven, climate-sensitive, climate-related) although many decisions related to adaptation and mitigation are not driven by climate change (Watkiss et al., 2005). Risk is commonly defined as the probability times the consequence, while uncertainty is often taken to represent structural and behavioural factors that are not readily captured in probability distributions (e.g., Tol, 2003; Stainforth et al., 2005). Although this distinction between risk and uncertainty is simplistic (see Dowie, 1999), stakeholder decision-making takes account of many factors (Newell and Pizer, 2000; Bulkeley, 2001; Clark et al., 2001; Gough and Shackley, 2001; Rayner and Malone, 2001; Pidgeon et al., 2003; Kasperson and Kasperson, 2005; Moser, 2005): values, preferences and motivations; awareness and perception of climate change issues; negotiation, bargaining and social norms; analytical frameworks, information and monitoring systems; and relationships of power and politics.

Faced with the deep uncertainty of climate change (Manne and Richels, 1992), stakeholders may adopt a precautionary approach with the intention of stimulating technological (if not social) change, rather than seeking to explicitly balance costs and benefits (Harvey, 2006). For instance, estimates of the social cost of carbon, one measure of the benefits of mitigation, are sensitive to the choice of decision framework (including equity weighting, risk aversion, sustainability considerations and discount rates for future damages) (Downing et al., 2005; Tol, 2005b; Watkiss et al., 2005; Guo et al., 2006; Fisher et al., 2007; see also Section 18.4.2; Chapter 20).

Criteria relating to either mitigation or adaptation, or both, are increasingly common in decision-making. For example, local development plans might screen housing developments according to energy use, water requirements and preservation of green belt (e.g., CAG Consultants and Oxford Brookes University, 2004). Development agencies have begun to screen their projects for relevance to adaptation and mitigation (e.g., Burton and van Aalst, 1999;Klein, 2001; Eriksen and Næss, 2003). Many stakeholders link climate, development and environmental policies by, for example, linking energy efficiency (related to mitigation) to sustainable communities or poverty reduction (related to adaptation). For example, the World Bank’s BioCarbon Fund and Community Development Carbon Fund include provision for buyers to ensure that carbon offsets also achieve development objectives (World Bank, undated). The Gold Standard for CDM projects also ensures that projects support sustainable development (Carbon International, undated). Preliminary work suggests that there may be a modest trade-off between cost-effective emissions reductions and the achievement of other sustainable development objectives; that is, more expensive projects per emissions reduction unit tend to contribute more to sustainable development than cheaper projects (Nagai and Hepburn, 2005).

The nature of adaptation and mitigation decisions changes over time. For example, mitigation choices have begun with relatively easy measures such as adoption of low-cost supply and demand side options in the energy sector (such as passive solar) (see Levine et al., 2007). Through successful investment in research and development, low-cost alternatives should become available in the energy sector, allowing for a transition to low-carbon venting pathways. Given the current composition of the energy sector, this is unlikely to happen overnight but rather through a series of decisions over time. Adaptation decisions have begun to address current climatic risks (e.g., drought early-warning systems) and to be anticipatory or proactive (e.g., land-use management). With increasing climate change, autonomous or reactive actions (e.g., purchasing air-conditioning during or after a heatwave) are likely to increase. Decisions might also break trends, accelerate transitions and mark substantive jumps from one development or technological pathway to another (e.g., Martens and Rotmans 2002; Raskin et al., 2002a, b).

Inter-relationships between adaptation and mitigation also vary according to spatial and social scales of decision-making. Adaptation and mitigation may be seen as substitutes in a policy framework at a highly aggregated, international scale: the more mitigation is undertaken, the less adaptation is necessary and vice versa. Resources devoted to mitigation might impede socioeconomic development and reduce investments in adaptive capacity and adaptation projects (e.g., Kane and Shogren, 2000). This scale is inherent in the analysis of global targets (see Section 18.4).

National and sub-national decision-making is often a mixture of policy and strategic planning. The adaptation-mitigation tradeoff is problematic at this scale because the effectiveness of mitigation outlays in terms of averted climate change depends on the mitigation efforts of other major greenhouse-gas emitters. However, adaptation criteria can be applied to mitigation projects or vice versa (Dang et al., 2003). A national policy example of synergies might be a new water law that requires metered use, enabling water companies to adjust their charges in anticipation of scarcity and conserve energy through demand-side measures. This policy would then be implemented in strategic plans by water companies and environment agencies at a sub-national level.

On the operational scale of specific projects, there may be trade-offs or synergies between adaptation and mitigation. However, the majority of projects are unlikely to have strong links, although this remains as a key uncertainty. Certainly there are many adaptive actions that have consequences for mitigation, and mitigation actions with consequences for adaptation.

The inter-relationships between adaptation and mitigation also cross scales (Rosenberg and Scott, 1995; Cash and Moser, 2000; Young, 2002). A policy framework is often seen as essential in driving strategic investment and operational projects (e.g., Grubb et al., 2002; Grubb, 2003) for technological innovation. Operational experience can be a precursor to developing sound strategies and policies (one of the motivations for early corporate experiments in carbon trading). In many cases the results of action at one scale have implications at another scale (e.g., local adaptation decisions that increase greenhouse-gas emissions, or national carbon taxes that change local resource use).

18.4 Inter-relationships between adaptation and mitigation and damages avoided

This section presents the main insights emerging from global integrated assessments implemented in different decision analytical frameworks on trade-offs and synergies between adaptation and mitigation and on avoided damages. This is complemented by lessons from regional and sectoral studies. Principles and technical details of the methods used by the studies reported here are presented in Chapter 2.

18.4.1 Trade-offs and synergies in global-scale analysis

Analysts working on global-scale climate analyses remain apart in their formulation of the inter-relationships between adaptation and mitigation. Some consider them as substitutes and seek the optimal policy mix, while others emphasise the diversity of impacts (with little scope for adaptation in some sectors) and the asymmetry of social actors who need to mitigate versus those who need to adapt (Tol, 2005a). Yet others maintain that adaptation is the only available option for reducing climate change impacts in the short to medium term, while the long term has a mix of adaptation and mitigation (Goklany, 2007). Note that these positions are not contradictory; they just emphasise different aspects of the same problem.

Cost-benefit analyses (CBAs) are phrased as the trade-off between mitigation costs, on the one hand, and adaptation costs and residual damages on the other. As a recent example, Nordhaus (2001) estimates the economic impact of the Kyoto-Bonn Accord with the RICE-2001model.Without the participation of the USA, the resulting emissions path remains below the efficient reduction policy (which equates estimated marginal costs and benefits of emissions reductions) whereas the original Kyoto Protocol implied abatement that is more stringent than would be suggested by this CBA. Note that RICE-2001, like all models, has assumptions, simplifications and abstractions that affect the results. Nonetheless, this is a common finding in the cost-benefit literature, driven primarily by relatively low estimates of the marginal damage costs (Tol, 2005b). Cost-benefit models are recognised by many as sources of guidance on the magnitude and rate of optimal climate policy (for a wide range of definitions of what is ‘optimal’ see Azar, 1998; Brown, 1998; Tol, 2001, 2002; Chapter 2), while others criticise them for ignoring the sectoral (economic and social), spatial and temporal distances between those who need to mitigate versus those who need to adapt to climate change. CBA requires conversion of many different damages to a common metric through monetisation, for example, by polling people’s values of different benefits, and the use of discount rates, which is controversial over long time-scales like those of climate change but common practice for other issues. Discounting implies that long-time-scale Earth-system transitions, such as melting of ice sheets, slowdown of the thermohaline circulation or the release of methane, have small weight in a CBA and therefore tend to attach little weight to adaptation costs (see also Chapter 17).

CBA is a special form of multi-criteria analysis. In both cases, policies are judged on multiple criteria, but in CBA all are monetised, while multi-criteria analyses use a range of mathematical methods to make trade-offs explicit and resolve them. Multi-criteria analysis has relatively few applications to climate policy (e.g., Bell et al., 2003; Borges and Villavicencio, 2004), although it is more common for adaptation (e.g., the National Adaptation Programmes of Action).

The Tolerable Windows Approach (TWA) adopts a different approach to integrating mitigation and impact/adaptation concerns and deals with adaptation indirectly in the applications. The ICLIPS (Integrated assessment of CLImate Protection Strategies) model identifies fields of long-term greenhouse-gas emissions paths that prevent rates and magnitudes of climate change leading to regional or sectoral impacts without imposing excessive mitigation costs on societies, either of which stakeholders might consider unacceptable or intolerable. This ‘relaxed’ cost-benefit framework can be used to explore trade-offs between climate change or impact constraints, on the one hand, and mitigation cost limits in terms of the existence and size of long-term emissions fields, on the other hand. For any given impact constraint, increasing the acceptable consumption loss due to emissions abatement expenditures increases the emissions field and allows higher near-term emissions but involves higher mitigation rates and costs in later decades. Conversely, for any given mitigation cost limit, increasing the tolerated level of climate impact also enlarges the emissions field and allows higher near-term emissions (Toth et al., 2002, 2003a, b). This formulation allows the exploration of side-payments for enhancing adaptation in order to tolerate impacts from larger climate change. The TWA is helpful in exploring the feasibility and implications of crucial social decisions (acceptable impacts and mitigation costs) but, unlike CBA, it does not propose an optimal policy.

Cost-effectiveness analyses (CEAs) depict a rather remote relationship between adaptation and mitigation. They implicitly assume that some sort of a global climate change target can be agreed upon that would keep all climate-change impacts at the level that can be managed via adaptation or taken as ‘acceptable losses’. Or, cost-effectiveness analyses consider a range of hypothetical targets, but remain silent on the appropriateness of these targets. Global CEAs have proliferated since the publication of the TAR (e.g., Edmonds et al., 2004). In addition to exploring least-cost strategies to stabilise CO2 concentrations, CEAs are applied to analysing the stabilisation of radiative forcing (e.g., Van Vuuren et al., 2006) and global mean temperature (Richels et al., 2004). While most analyses are deterministic in the sense that they implicitly assume that we know the true state of the world, there is also a body of literature that models the ‘act, then learn, then act again’ nature of the decision problem, but primarily for mitigation decisions. See the WGIII AR4 Chapter 3 for details (Fisher et al., 2007).

The competition of adaptation measures, mitigation measures and non-climate policies for a finite budget has not been studied in much detail. Schelling (1995) questions whether the money that developed countries’ governments plan to spend on greenhouse gas emissions reduction, ostensibly to the benefit of the children and grandchildren of the people in developing countries, cannot be spent to greater benefit. As a partial answer to that question, Tol (2005c) concluded that development aid is a better mechanism to reduce climate-change impacts on infectious disease (e.g., malaria, the best-studied health impact) than is emissions abatement. This analysis implies that the concern about increases in these infectious diseases is not a valid argument for greenhouse gas emissions reduction (there are of course other arguments for abatement). The same study also shows that this result does not carry over to other impacts. More broadly, Goklany (2003, 2005) shows that the contribution of climate change to hunger, malaria, coastal flooding and water stress (as measured by the population at risk for these hazards) is usually small compared with the contribution of non-climate-change-related factors. He argues that, through the 2080s at least, efforts to reduce vulnerability would be far more cost-effective in reducing these problems than would any mitigation scheme. Other studies estimate the change in vulnerability to climate change due to emissions abatement; for instance, a shift to wind and water power or biofuels would reduce carbon dioxide emissions, but increase exposure to the weather and climate (e.g., Dang et al., 2003).

Some studies estimate the change in greenhouse-gas emissions due to adaptation to the impacts of climate change (Berrittella et al., 2006, for tourism; Bosello et al., 2006, for health). They find that emissions increase in some places and some sectors (making mitigation harder), and decrease elsewhere (making mitigation easier). The disaggregated effects are small compared with the projected growth in emissions, while the net effect is negligible. Similarly, Fankhauser and Tol (2005) show that the impact of climate change on the growth of the economy and greenhouse gas emissions is small compared with the economy as a whole and because economic adjustment processes would dampen the impact. Note that they only include those climate-change impacts that affect economic performance; they do not use monetisation techniques. Fisher et al. (2006) reach a similar conclusion for population projections, because the net increase in mortality is small. As there are so few studies, focusing on a few sectors only, these conclusions are preliminary.

Although some industries (e.g., wind farm and solar panel manufacturing)may benefit, emissions reduction is likely to slow economic growth, but this effect is probably small if smart abatement policies are used (Weyant, 2004; Barker et al., 2007; Fisher et al., 2007). However, small economic losses in the member states of the Organisation for Economic Co-operation and Development (OECD)may be amplified in poor exporters of primary products (i.e., many African countries). Tol and Dowlatabadi (2001) use this mechanism to demonstrate an interesting trade-off between adaptation and mitigation. Taking malaria as a climate-related disease, they observe that countries with an average annual income per capita of US$3,000 or more do not report significant deaths from malaria and that all world regions surpass this threshold by 2085 in most IPCC IS92 scenarios (IPCC, 1992). Progressively more ambitious emissions reductions in OECD countries gradually decrease the cumulative malaria mortality if one considers only the impact side; that is, the biophysical effects of climate-change mitigation on malaria prevalence. However, if the economic effects of mitigation efforts (i.e., the slower rate of economic growth) are also taken into account, then, according to the FUND model, the malaria mortality improvements due to slower global warming will be gradually eliminated and eventually surpassed by the losses due to the reduced rate of income growth, unless health care expenditures are decoupled from economic growth. Note that FUND has somewhat high costs of emissions reduction (see the SAR), and also assumes a large impact of slowed growth in the OECD on the rest of the world. Barker et al. (2002), Weyant (2004), Edenhofer et al. (2006), Köhler et al. (2006) and Van Vuuren et al. (2006) show that there is a wide range of estimates of mitigation impacts on economic growth, but these studies did not explore the link between mitigation and vulnerability. In fact, the impact of mitigation on adaptive capacity has not been studied with any other model. More generally, the capacity to adapt to climate change is related to development status, although the two are not the same (Yohe and Tol, 2002; Tompkins and Adger, 2005). The earlier studies used ‘adaptive capacity’ and ‘development’ in a generic and broad sense. Tol and Yohe (2006) use more specific indicators of adaptive capacity and development without changing the general conclusion. Emissions reduction policies that hamper development would increase vulnerability and could increase impacts (Tol and Yohe, 2006). Based on this contingency, Goklany (2000b) argues that aggressive mitigation would fall foul of the precautionary principle.

The literature assessed in this sub-section indicates that initial studies tended to focus on the relationship between mitigation and damages avoided, but our knowledge of this subject is still limited and more research needs to be undertaken. More recently, the literature has begun to focus on the relationship between adaptation and damages avoided. Ultimately, better knowledge about the interaction between adaptation and mitigation actions in terms of damages avoided would be useful. However, such research is at a very rudimentary stage. Moreover, large-scale modelling of adaptation-mitigation feedbacks is needed but still lacking. A necessary first step will be improved modelling of feedbacks from impacts, which is currently immature in most long-term global integrated assessment modelling. Adaptation modelling can follow with modelling structures that permit the reallocation of production factors and budgets in response to the changing climate. The adaptation responses therefore redefine the circumstances for mitigation. However, current impact modelling capability is undeveloped and modelling of adaptation responses to climate-change impacts has only just begun. In the above assessment we do not distinguish adaptation by actors (e.g., individuals, government departments) as the conclusions generally hold for all types of adaptation.

18.4.2 Consideration of costs and damages avoided and/or benefits gained

Various approaches have been taken since the TAR to estimate the size of climate change damages that can be avoided by emissions reduction. Among the global integrated assessments reviewed in the previous sub-section, cost effectiveness models (by far the most widely used decision analysis framework) do not include impacts, hence they cannot measure avoided damages either. In contrast, CBAs of greenhouse-gas emissions reduction (e.g., Nordhaus, 2001) necessarily estimate the avoided damages of climate change but rarely report them. Economic assessments of marginal damage costs (e.g., the incremental impact of an additional tonne of carbon emissions) provide a means of comparing damages avoided with marginal abatement costs. Such studies typically cover a range of sectors and report damage functions and estimates for scenarios of climate change, and increasingly reference scenarios of socio-economic vulnerability.

Tol (2005b) reviewed the avoided-damage literature, including 103 estimates from 28 papers published from 1991 to 2003. Some of the reviewed estimates include only a few impacts; other estimates include a wide range of impacts, including low-probability/high-impact scenarios (see Chapter 20 for further discussion). Tol (2005b) finds that most studies (72% when quality-weighted) point to a marginal damage cost of less than US$50 per tonne carbon (/tC). He also finds a systematic, upward bias in the grey literature. For instance, the 95th percentile falls from US$350/tC to US$245/tC if estimates that were not peer-reviewed are excluded. For a 5% discount rate, a value used by many governments (Evans and Sezer, 2004), the median estimate is only US$7/tC; for a 3% discount rate, it is US$33/tC.

Downing et al. (2005) updated the Tol (2005b) analysis to a 2005 base year: the very likely range of estimates runs from −US$10 to +US$350/tC; peer-reviewed estimates have a mean value of US$43/tC with a standard deviation of US$83/tC. Incorporating results from FUND (2005 version) and PAGE2002, Downing et al. (2005) find that £35/tC (at year 2000 values, or US$56/tC) is a credible lower benchmark for the social cost of carbon (as identified by the UK Government in Clarkson and Deyes, 2002). In FUND, with the Green Book discounting scheme and equity weighting, there is about a 40% chance that the social cost of carbon exceeds £35/tC. Estimates of the central tendency (whether the average or median) or upper benchmark were not agreed in that assessment, due to the limitations in our knowledge of climate impacts and the critical role of the decision perspective (see Section 18.5).

Stern (2007), including a higher level of risk of adverse impacts that are poorly represented in existing models and accepting a public policy framework that includes low discounting of the future, reports a social cost of carbon of US$304/tC (US$85/tCO2, at pounds sterling 2005 values) from the PAGE2002 model. The range of estimates is quite large and Stern (2007) acknowledges that his central estimate is higher than most studies and is “keenly aware of the sensitivity of estimates to the assumptions that are made”.

Note that the estimates of avoided damages are highly uncertain. A survey of fourteen experts in estimating the social cost of carbon rated their estimates as low confidence, due to the many gaps in the coverage of impacts and valuation studies, uncertainties in projected climate change, choices in the decision framework and the applied discount rate (Downing et al., 2005).

The marginal damage cost only gives the value of the last unit of the damage avoided, not the total avoided damage, which is seldom estimated (see the literature review and papers in Corfee- Morlot and Agrawala, 2004). Nonetheless, as a first approximation of the avoided damages, one should multiply the tonnes of carbon emissions reduced by the marginal damage cost.

Several studies have attempted to calculate total economic damages from disparate impact studies. Warren (2006) reports a long list of ecosystem impacts at 2°C warming and below, billions of people at risk from water stress (without adaptation) and political tension in Russia. As the impact estimates are taken from different studies, with different models and different scenarios, this method introduces additional uncertainties: the difference in impact may be due to different warming scenarios, but also due to differences in models, data, economic scenarios and even subject and area of study. Furthermore, it is difficult to compare how impacts change with additional degrees of climate change, although the work does suggest that there are an increasing number of negative impacts at higher temperatures. Warren’s (2006) study is often qualitative and it is unclear whether the studies are representative of the literature (or the population of affected sectors), or whether adaptation is included. On avoidable damage, this study paints a bleak picture. At 2°C warming, which may be difficult to avoid, 97%of coral reefs and 100% of Arctic sea ice would be lost. Avoided damage is therefore less than 3% of coral reefs, and no Arctic sea ice. Hare (2006) also offers impact estimates for various warming scenarios, with the same limitations as for Warren (2006). Hitz and Smith (2004) review damage functions related to global mean temperature but do not aggregate to overall damages. Arnell et al. (2002) and Parry et al. (2004) use internally consistent models and scenarios, and report numbers for avoided damages, measured in millions of people at risk. Water resources and malaria dominate their results, but the underlying models do not account for adaptation and keep socio-economic development at 1990 levels, although populations grow.

Relatively few studies have documented damages avoided in terms of specific mitigation scenarios. Bakkenes et al. (2006) study the implications of different stabilisation scenarios on European plant diversity. Mitigation is not considered, even though biofuels and carbon plantations would substantially affect vegetation. Under theA1B scenario, plants would lose on average 29% of their current habitat by 2100, with a range between species from 10% to 53%. Stabilisation at 650 ppm would limit this to 22% (6-42%), and at 550 ppm to 18% (5- 37%). With unmitigated climate change, nine plant species would disappear from Europe, but eight new ones would appear. Stabilisation would limit the number of plant disappearances from nine to eight species. In all five studies, adaptation (except in some parts of the Parry study) and the effects of mitigation on impacts are not included (see Section 18.4.1). Nicholls and Lowe (2004) estimate the avoided impact of sea-level rise due to mitigation. Because sea level responds so slowly to global warming, avoided impacts are small, at least over the 21st century. Nicholls and Lowe (2004) ignore the costs of emissions reduction; Tol (2007) shows that the bias is negligible for coastal-zone impacts. Nicholls and Lowe (2004, 2006) argue that adaptation and mitigation should be applied together for coastal zones, with mitigation to minimise the future commitment to sea-level rise and adaptation to adapt to the inevitable changes. Nicholls and Tol (2006) and Nicholls et al. (2007) also explore the economic impacts of sea-level rise.

Tol and Yohe (2006), using the integrated assessment model, Climate Framework for Uncertainty, Negotiation and Distribution (FUND), conclude that the most serious impacts of climate change can be avoided at an 850 ppm CO2-equivalent stabilisation target for greenhouse-gas concentrations, and that incrementally avoided damages get smaller and smaller as one moves to more stringent stabilisation targets. For a 450 ppm CO2-equivalent stabilisation target, climate-change impacts may actually increase as the reduction of sulphur emissions may lead to warming and as abatement costs slow growth and increase vulnerability. However, FUND includes a wide range but not all impacts, represents impacts in a reduced form, does not capture discontinuities or interactions between impacts, models climate change as being smooth, and does not include the ancillary benefits of reductions in sulphur. Other models also find that climate policy would reduce sulphur emissions to levels below what is required for acidification policy (e.g., Van Vuuren et al., 2006). Other integrated assessment models have yet to produce comparable analyses.

Abatement may, but need not, reduce the probability of extreme climate scenarios, such as a shut-down of the thermohaline circulation (Gregory et al., 2005) and a collapse of the West Antarctic ice sheet (Vaughan and Spouge, 2002). The few studies on the effects of drastic sea-level rise show large impacts (Schneider and Chen, 1980; Nicholls et al., 2005; Tol et al., 2006) but opinions on the impacts of a thermohaline circulation shut-down are divided (Rahmstorf, 2000; Link and Tol, 2004).

Additional assessments of damages avoided by mitigation are also provided in other chapters of this report. Chapter 20 finds that estimates of the social cost of carbon expand over at least three orders of magnitude and notes that globally aggregated figures are likely to underestimate the full costs, masking differences in impacts across sectors and regions/countries. It concludes that “it is very likely that climate change will result in net costs into the future, aggregated across the globe and discounted to today; it is very likely that these costs will grow over time”. The WGIII AR4 in Chapter 3 (Fisher et al., 2007) observes that most (but not all) analyses which use monetisation suggest that social costs of carbon are positive, but the range of values is wide and is strongly dependent on modelling methodology, value judgements and assumptions. It concludes that large uncertainties persist, related to the cost of mitigation, the efficacy of adaptation, and the extent to which the negative impacts of climate change, including those related to rate of change, can be avoided. See Box 18.2 for a summary of the WGIII AR4 conclusions on damages avoided with different stabilisation scenarios.

Overall, there are only a few studies that estimate the avoided impacts of climate change by emissions reduction. Some of these studies ignore adaptation and mitigation costs. Many published studies of damages in sectors that are quantified in economic models (but mostly market-based costs and related to incremental projections of temperature) and with discount rates commonly used in economic decision-making (e.g., 3% or higher) lead to low estimates of the social cost of carbon. In general, confidence in these estimates is low. The paucity of evidence is disappointing, as avoiding impacts is presumably a major aim of climate policy. CBAs of climate change implicitly estimate avoided damages and suggest that these do not warrant very stringent emissions reduction (see Section 18.4.1). Similarly, although ecosystem impacts may be large, avoidable impacts may be much smaller. With few high quality studies, confidence in these findings is low. This is a clear research priority. The use of the social cost of carbon in decision-making on mitigation also warrants further exploration.

18.4.3 Inter-relationships within regions and sectors

Considering the details of specific adaptation and mitigation activities at the level of regions and sectors shows that adaptation and mitigation can have a positive and negative influence on each other’s effectiveness. The nature of these inter-relationships (positive or negative) often depends on local conditions. Moreover, some inter-relationships are direct, involving the same resource base (e.g., land) or stakeholders, while others are indirect (e.g., effects through public budget allocations) or remote (e.g., shifts in global trade flows and currency exchange rates). This section focuses on direct inter-relationships. Broader inter-relationships between adaptation and mitigation are discussed in other parts of this chapter and in Chapter 20 related to sustainable development.

Mitigation affecting adaptation

Land-use and land-cover changes involve diverse and complex inter-relationships between adaptation and mitigation. Deforestation and land conversion have been significant sources of greenhouse-gas emissions for decades while often resulting in unsustainable agricultural production patterns. Abating and halting this process by incentives for forest conservation and increasing forest cover would not only avoid greenhouse-gas emissions, but would also result in benefits for local climate, water resources and biodiversity.

Carbon sequestration in agricultural soils offers another positive link from mitigation to adaptation. It creates an economic commodity for farmers (sequestered carbon) and makes the land more valuable by improving soil and water conservation, thus enhancing both the economic and environmental components of adaptive capacity (Boehm et al., 2004; Butt and McCarl, 2004; Dumanski, 2004). The stability of these sinks requires further research, and effective monitoring is also a challenge.

Afforestation and reforestation have been advocated for decades as important mitigation options. Recent studies reveal a more differentiated picture. Competition for land by mitigation projects would increase land rents, and thus commodity prices, thereby improving the economic position of landowners and enhancing their adaptive capacity (Lal, 2004). However, the implications of reforestation projects for water resources depend heavily on the species composition and the geographical and climatic characteristics of the region where they are implemented. In regions with ample water resources even under a changing climate, afforestation can have many positive effects, such as soil conservation and flood control. In regions with few water resources, intense rainfalls and long spells of dry weather, forests increase average water availability. However, in arid and semi-arid regions, afforestation strongly reduces water yields (UK FRP, 2005). This has direct and wide-ranging negative implications for adaptation options in several sectors such as agriculture (irrigation), power generation (cooling towers) and ecosystem protection (minimum flow to sustain ecosystems in rivers, wetlands and on river banks).

Bioenergy crops are receiving increasing attention as a mitigation option. Most studies, however, focus on technology options, costs and competitiveness in energy markets and do not consider the implications for adaptation. For example, McDonald et al. (2006) use a global computed general equilibrium model and find that substituting switchgrass for crude oil in the USA would reduce the gross domestic product (GDP) and increase the world price of cereals, but they do not investigate how this might affect the prospects for adaptation in the USA and for world agriculture. This limitation in scope characterises virtually all bioenergy studies at the regional and sectoral scales, but substantial literature on adaptation-relevant impacts exists at the project level (e.g., Pal and Sharma, 2001; see Section 18.5 and Chapter 17).

Another possible conflict between adaptation and mitigation might arise over water resources. One obvious mitigation option is to shift to energy sources with low greenhouse-gas emissions such as small hydropower. In regions where hydropower potentials are still available, and also depending on the current and future water balance, this would increase the competition for water, especially if irrigation might be a feasible strategy to cope with climate-change impacts in agriculture and the demand for cooling water by the power sector is also significant. This reconfirms the importance of integrated land and water management strategies to ensure the optimal allocation of scarce natural resources (land, water) and economic investments in climate-change adaptation and mitigation and in fostering sustainable development.

Box 18.2. Analysis of stabilisation scenarios

The WGIII AR4, in Chapter 3 (Section 3.5.2), looks across findings of the WGI and WGII AR4 to relate the long-term emissions scenarios literature to climate-change impact risks at different levels of global mean temperature change based on key vulnerabilities (as defined in Chapter 19). It builds on the WGI AR4 findings, which outline the probabilities of exceeding various global mean temperatures at different concentration levels (Tables 3.9 and 3.10 in Fisher et al., 2007). The relationships are based on a key finding of the WGI AR4 that there is at least an 83%probability for climate sensitivity to be at or below 4.5°C, while the best estimate is for climate sensitivity to be 3°C. The WGIII AR4 organises the stabilisation scenarios literature by the level of stringency of the scenario, setting out six groups (I-VI) that cover the full range ofmore to less stringent global warming objectives, in the form of concentrations (ppm) or radiative forcing (W/m2). Table 3.9 uses the WGI AR4 findings to relate increases in global mean temperature to concentration targets, while Table 3.10 relates these outcomes to the emissions pathways associated with alternative stabilisation scenarios. (An important caveat is that these relationships do not consider possible additional CO2 and CH4 releases from Earth-system feedbacks and thus may underestimate required emissions reductions.)

Regarding climate-change impact risks and key vulnerabilities, this literature is organised around increase in global mean temperature. Chapter 19 shows that the following benefits would accrue from constraining temperature rise to 2°C above 1990:

  • lowering the risk of widespread deglaciation of the Greenland ice sheet**;
  • avoiding large-scale transformation of ecosystems and degradation of coral reefs***;
  • preventing terrestrial vegetation becoming a carbon source*/**, constraining species extinction to between 10% and 40%*, and preserving many unique habitats (see Chapter 4, Table 4.1 and Figure 4.5);
  • preventing flooding, drought and water-quality declines***, global net declines in food production*/•, and more intense fires**.

Other benefits of this constraint include reducing the risks of extreme weather events**, and of at least partial deglaciation of the West Antarctic ice sheet (WAIS)* (see Chapter 19, Section 19.3.7). By comparison, constraining temperature change to not more than 3°C above 1990 levels will still avoid commitment to widespread deglaciation of theWAIS* and commitment to possible shut-down of the Meridional Overturning Circulation/• but results in significantly lower avoided risks and impacts in most other areas (Chapter 19, Section 19.3.7).

(Confidence ratings are as provided by WGII Chapter 19 authors: /• = low confidence, * = medium, ** = high, and *** = very high confidence.)


Hydropower leads to the key area of mitigation: energy sources and supply, and energy use in various economic sectors beyond land use, agriculture and forestry. Direct implications of mitigation efforts on adaptation in the energy, transport, residential/commercial and industrial sectors have been largely ignored so far. Yet, to varying degrees, energy is an important factor in producing goods and providing services in many sectors of the economy, as outlined in the discussion about the importance of energy to achieve the Millennium Development Goals in the WGIII AR4, Chapter 2 (Halsnaes et al., 2007). Reducing the availability or increasing the price of energy therefore has inevitable negative effects on economic development and thus on the economic components of adaptive capacity. The magnitude of this effect is uncertain. Peters et al. (2001) find that high-level carbon charges (US$200/tC in 2010) affect U.S. agriculture modestly if they are measured in terms of consumer and producer surpluses (reductions by less than half a percent relative to baseline values). However, the decline of net cash returns is more significant (4.1%) and the effects are rather uneven across field crops and regions. Recent studies on the implications for adaptation (capacity and options) indicate that such changes may imply larger policy shifts; for example, towards protection of the most vulnerable (Adger et al., 2006).

The most important indirect link from mitigation to adaptation is through biodiversity, an important factor influencing human well-being in general and the coping options in particular (see MEA, 2005). After assessing a large number of studies, IPCC (2002) concluded that the implications for biodiversity of mitigation activities depend on their context, design and implementation, especially site selection and management practices. Avoiding forest degradation implies in most cases both biodiversity (preservation) and climate (non-emissions) benefits. However, afforestation and reforestation may have positive, neutral or negative impacts, depending on the level of biodiversity of the ecosystems that will be replaced. By using an optimal-control model, Caparros and Jacquemont (2003) find that putting an economic value on carbon sequestered by forest management does not induce much negative influence on biodiversity, but incentives to sequester carbon by afforestation and reforestation might harm biodiversity due to the over plantation of fast-growing alien species.

These studies demonstrate the intricate inter-relationships between adaptation and mitigation, and also the links with other environmental concerns, such as water resources and biodiversity, with profound policy implications. The land-use and forestry mitigation options in the Marrakesh Accords may provide new markets for countries with abundant land areas but may alter land allocation to the detriment of the landless poor in regions where land is scarce. They present an opportunity for soil and biodiversity protection in regions with ample water resources but may reduce water yields and distort water allocation in water-stressed regions. Accordingly, depending on the regional conditions and the ways of implementation, these implications can increase or reduce the scope for adaptation to climate change by promoting or excluding effective, but more expensive, options due to increased land rents, by supporting or precluding forms and magnitudes of irrigation due to, for example, higher water prices.

Adaptation affecting mitigation

Many adaptation options in different impact sectors are known to involve increased energy use and hence interfere with mitigation efforts if the energy is supplied from carbon-emitting sources. Two main types of adaptation-related energy use can be distinguished: one-time energy input for building large infrastructure (materials and construction), and incremental energy input needed continuously to counterbalance climate impacts in providing goods and services. Furthermore, rural renewable electrification can have both huge emissions implications (WEA, 2000) and adaptation implications (Venema and Cisse, 2004).

The largest amount of construction work to counterbalance climate-change impacts will be in water management and in coastal zones. The former involves hard measures in flood protection (dykes, dams, flood control reservoirs) and in coping with seasonal variations (storage reservoirs and inter-basin diversions), while the latter comprises coastal defence systems (embankment, dams, storm surge barriers). Even if these construction projects reach massive scales, the embodied energy, and thus the associated greenhouse-gas emissions, is likely to be merely a small proportion of the total energy use and energy related emissions in most countries (adaptation-related construction comprises only a small part of total annual construction, and the construction industry itself represents a small part in the annual energy balances of most countries).

The magnitude and relative share of sustained adaptation related energy input in the total energy balance depends on the impact sector. In agriculture, the input-related (CO2 in manufacturing) and the application-related (N2O from fields) greenhouse-gas emissions might be significant if the increased application of nitrogen fertilisers offers a convenient and profitable solution to avoid yield losses (McCarl and Schneider, 2000). Operating irrigation works and pumping irrigation water could considerably increase the direct energy input, although, where available, the utilisation of renewable energy sources onsite (wind, solar) can help avoid increasing greenhouse-gas emissions.

Adaptation to changing hydrological regimes and water availability will also require continuous additional energy input. In water-scarce regions, the increasing reuse of wastewater and the associated treatment, deep-well pumping, and especially large-scale desalination, would increase energy use in the water sector (Boutkan and Stikker, 2004). Yet again, if provided from carbon-free sources such as nuclear desalination (Misra, 2003; Ayub and Butt, 2005), even energy-intensive adaptation measures need not run counter to mitigation efforts.

Ever since the early climate impact studies, shifts in space heating and cooling in a warming world have been prominent items on the list of adaptation options (see Smith and Tirpak, 1989). The associated energy requirements could be significant but the actual implications for greenhouse-gas emissions depend on the carbon content of the energy sources used to provide the heating and cooling services. In most cases, it is not straightforward to separate the adaptation effects from those of other drivers in regional or national energy-demand projections. For example, for the U.S. state of Maryland, Ruth and Lin (2006) find that, at least in the medium term up to 2025, climate change contributes relatively little to changes in the energy demand. Nonetheless, the climate share varies with geographical conditions (changes in heating and cooling degree days), economic (income) and resource endowments (relative costs of fossil and other energy sources), technologies, institutions and other factors. Such emissions from adaptation activities are likely to be small relative to baseline emissions in most countries and regions, but more in-depth studies are needed to estimate their magnitude over the long term.

Adaptation affects not only energy use but energy supply as well. Hydropower contributed 16.3% of the global electricity balance in 2003 (IEA, 2005) with virtually zero greenhouse-gas emissions. Climate-change impacts and adaptation efforts in various sectors might reduce the contribution of this carbon-free energy source in many regions as conflicts among different uses of water emerge. Hayhoe et al. (2004) show that emissions even in the lowest SRES (IPCC Special Report on Emissions Scenarios; Naki?enovi? and Swart, 2000) scenario (B1) will trigger significant shifts in the hydrological regime in the Sacramento River system (California) by the second half of this century and will create critical choices between flood protection in the high-water period and water storage for the low-flow season. Hydropower is not explicitly addressed but will probably be affected as well. Payne et al. (2004) project conflicts between hydropower and stream flow targets for the Columbia River. Several studies confirm the unavoidable clashes between water supply, flood control, hydropower and minimum stream flow (required for ecological and water quality purposes) under changing climatic and hydrological conditions (Christensen et al., 2004; Van Rheenen et al., 2004).

Possibly the largest factor affecting water resources in adaptation is irrigation in agriculture. Yet studies in this domain tend to ignore the repercussions for mitigation as well. For example, Döll (2002) estimates significant increases in irrigation needs in two-thirds of the agricultural land that was equipped for irrigation in 1995, but she does not assess the implications for other water uses such as hydropower and thus for climate-change mitigation. In general, adaptation implies that people do something in addition to or something different from what they would be doing in the absence of emerging or expected climate-change impacts. In most cases, additional activities involve additional inputs: investments (protective and other infrastructure), material (fertilisers, pesticides) or energy (irrigation pumps, air conditioning), and thus may run counter to mitigation if the energy originates from greenhouse-gas-emitting sources. Changing practices in response to climate change offer more opportunities to account for both adaptation and mitigation needs. Besides the opportunities in land-related sectors discussed above, new design principles for commercial and residential buildings could simultaneously reduce vulnerability to extreme weather events and energy needs for heating and/or cooling. Nonetheless, there are path dependencies from past technology choices and infrastructure investments.

In summary, many effects of adaptation on greenhouse-gas emissions and their mitigation (energy use, land conversion, agronomic techniques such as an increased use of fertilisers and pesticides, water storage and diversion, coastal protection) have been known for a long time. The implications of some mitigation strategies for adaptation and other development and environment concerns have been recognised recently. As yet, however, both effects remain largely unexplored. Information on interrelationships between adaptation and mitigation at regional and sectoral levels is rather scarce. Almost all mitigation studies stop at identifying the options and costs of direct emissions reductions. Some of them consider indirect effects of implementation and costs on other sectors or the economy at large but do not deal with the implications for adaptation options of sectors affected by climate change. Similarly, in most cases, climate impact and adaptation assessments do not go beyond taking stock of the adaptation options and estimating their costs, and thus ignore possible repercussions for emissions. One understandable reason is that adaptation and mitigation studies are already complex enough and expanding their scope would increase their complexity even further. Another reason may well be that, as indicated by the few available studies that looked at these inter-relationships, the repercussions from mitigation for adaptation and vice versa are between adaptation and mitigation might be significant but, in most other sectors, the adaptation implications of any mitigation project are small and, conversely, the emissions generated by most adaptation activities are only small fractions of total emissions, even if emissions will decline in the future as a result of climate-protection policies.

18.5 Inter-relationships in a climate policy portfolio

A wide range of inter-relationships between adaptation and mitigation have been identified through examples in the published literature. Taylor et al. (2006) present an inventory of published examples including full citations (available in an abbreviated form on the CD-ROM accompanying this volume as supplementary material to support the review of this chapter). The many examples have been clustered according to the type of linkage and ordered according to the entry point and scale of decision-making (Figure 18.2). Table 18.1 lists all of the types of linkages documented. The categories are illustrative; some cases occur in more than one category, or could shift over time or in different situations. For example, watershed planning is often related to managing climatic risks in using water. But if hydroelectricity is an option, then the entry point may be mitigation, and both adaptation and mitigation might be evaluated at the same time or even with explicit trade-offs.

In Figure 18.2 and Table 18.1, many of the examples are motivated by either mitigation or adaptation, with largely unintended consequences for the other (e.g., Tol and Dowlatabadi, 2001). Where adaptation leads to effects on mitigation, the linkage is labelled A→M. The categories of linkages include:

  • individual responses to climatic hazard that increase or decrease greenhouse-gas emissions. For example, a common adaptation to heatwaves is to install air-conditioning, which increases electricity demand with consequences for mitigation when the electricity is produced from fossil fuels;
  • more efficient community use of water, land, forests and other natural resources, improving access and reducing emissions (e.g., conservation of water in urban areas reduces energy used in moving and heating water);
  • natural resources managed to sustain livelihoods;
  • tourism use of energy and water, with outcomes for incomes and emissions (generally to increase both welfare and emissions);
  • resources used in adaptation, such as in large-scale infrastructure, increases emissions.

Similarly, mitigation actions might affect the capacity to adapt or actual adaptation actions (M→A). These categories include:

  • more efficient energy use and renewable sources that promote local development;
  • CDM projects on land use or energy use that support local economies and livelihoods, perhaps by placing a value on their management of natural resources;
  • urban planning, building design and recycling with benefits for both adaptation and mitigation;
  • health benefits of mitigation through reduced environmental stresses;
  • afforestation, leading to depleted water resources and other ecosystem effects, with consequences for livelihoods;
  • mitigation actions that transfer finance to developing countries (such as per capita allocations) that stimulate investment with benefits for adaptation;
  • effects of mitigation, e.g., through carbon taxes and energy prices, on resource use (generally to reduce use) that affect adaptation, for example by reducing the use of tractors in semi-subsistence farming due to higher costs of fuels.
Figure 18.2. Typology of inter-relationships between climate change adaptation and mitigation. MEA = Multilateral Environmental Agreements.

As noted in Section 18.4.3, the effect of increased emissions due to adaptation is likely to be small in most sectors in relation to the baseline projections of energy use and greenhouse-gas emissions. Land and water management may be affected by mitigation actions, but in most sectors the effects of mitigation on adaptation are likely to be small. At least some analysts are concerned with the explicit trade-offs between adaptation and mitigation (labelled adaptation or mitigation, ∫(A,M)). Categories include:

  • public-sector funding and budgetary processes that allocate funding to both adaptation and mitigation;
  • strategic planning related to development pathways, for example scenario and visioning exercises with urban governments that include climate responses (mainstreaming responses in sectoral and regional planning);
  • allocation of funding and setting the agenda for UNFCCC negotiations and funds (e.g., the Special Climate Change Fund);
  • stabilisation targets that include limits to adaptation (e.g., tolerable windows);
  • analysis of global costs and benefits of mitigation to inform targets for greenhouse-gas concentrations (see Section 18.4.2);
  • large-scale mitigation (e.g., geo-engineering) with effects on impacts and adaptation.

Some actions result from the simultaneous consideration of adaptation and mitigation. These concerns may be raised within the same decision framework or sequential process but without explicitly considering their trade-offs or synergies (labelled adaptation and mitigation, A M). Examples include:

  • perception of impacts and the limits to adaptation (see Chapter 17) motivates action on mitigation, conversely the perception of limits to mitigation reinforces urgent action on adaptation;
  • watershed planning where water is allocated between hydroelectricity and consumption without explicitly addressing mitigation and adaptation;
  • cultural values that promote both adaptation and mitigation, such as sacred forests (e.g., Satoyama in Japan);
  • management of socio-ecological systems to promote resilience;
  • ecological impacts, with some human element, drive further releases of greenhouse gases,
  • legal implications of liability for climate impacts motivates mitigation;
  • national capacity-building increases the ability to respond to both adaptation and mitigation (such as through the National Capacity-Building Self Assessment);
  • insurance spreads risk and assists with adaptation, while managing insurance funds has implications for mitigation;
  • trade liberalisation may have economic benefits (increasing adaptive capacity) but also increases emissions from transport;
  • monitoring systems and reporting requirements may cover indicators of both adaptation and mitigation;
  • management of multilateral environmental agreements may benefit both adaptation and mitigation.

Table 18.1. Types of inter-relationships between climate change adaptation and mitigation.

A→M M→A ∫(A,M) A∩M
Individual responses to climatic hazards that increase or decrease greenhouse-gas emissions More efficient energy use and renewable sources that promote local development Public-sector funding and budgetary processes that allocate funding to both A and M Perception of impacts (and limits to A) motivates M; perception of limits to M motivates A
More efficient community use of water, land, forests CDM projects on land use or energy use that support local economies and livelihoods Strategic planning related to development pathways (scenarios) to mainstream climate responses Watershed planning: allocation of water between hydroelectricity and consumption
Natural resources managed to sustain livelihoods Urban planning, building design and recycling with benefits for both A and M Allocation of funding and setting the agenda for UNFCCC negotiations and funds Cultural values that promote both A and M, such as sacred forests (e.g., Satoyama in Japan)
Tourism use of energy and water, with outcomes for incomes and emission Health benefits of mitigation through reduced environmental stresses Stabilisation targets that include limits to adaptation (e.g., tolerable windows) Management of socio-ecological systems to promote resilience
Resources used in adaptation, such as large-scale infrastructure, increase emissions Afforestation, leading to depleted water resources and other ecosystem effects, with consequences for livelihoods Analysis of global costs and benefits of M to inform targets Ecological impacts, with some human element, drive further releases of greenhouse gases
M schemes that transfer finance to developing countries (such as a per capita allocation) stimulate investment that may benefit A Large scale M (e.g., geoengineering) with effects on impacts and A Legal implications of liability for climate impacts motivates M
Effect of mitigation, e.g., through carbon taxes and energy prices, on resource use National capacity-building increases ability to respond to both A and M
Insurance spreads risk and assists with A; managing insurance funds has implications for M
Trade liberalisation with economic benefits (A) increases transport costs (M)
Monitoring systems and reporting requirements that cover indicators of both A and M
Management of multilateral environmental agreements benefits both A and M


Inter-relationships between adaptation and mitigation will vary with the type of policy decisions being made, for example on different scales from local project analysis to global analysis. As discussed in Section 18.4.3, there will be clear M→A linkages in many mitigation projects, for example ensuring that adaptation is built into the project design (e.g., considering and adjusting for water availability for longer-term hydroelectric renewable or bioenergy/biofuels projects). Similarly, in the design or appraisal of adaptation projects, A→M, the consideration of mitigation options can be brought in, for example in considering reduced energy use in project design. These linkages might be considered through an extension of project risk analysis as part of the appraisal process, but can also be included in cost-benefit analysis explicitly in an economic appraisal framework.

At the policy level (e.g., portfolios, funding, strategies), the same M→A and A→M issues apply, but the wider potential for cross-sectoral linkages makes simultaneous consideration of adaptation and mitigation, A M, more important. For example, the shift up to a major (country level) energy policy towards mitigation might need to assess demand changes from adaptation across a wide range of sectors. There may be a need to consider some explicit trade-offs between adaptation and mitigation, ∫(A,M).

At the global level, the potential for ∫(A,M) becomes possible within a theoretical framework (see Section 18.4). There has been discussion of the potential for adaptation and mitigation as substitutes within narrow economic analysis (cost-benefit frameworks), and some studies have tried to assess the optimal policy balance of mitigation and adaptation using CBA-based on IAMs. However, recent reviews (e.g., Watkiss et al., 2005) have shown that policy-makers are uncomfortable with the use of CBA in longer-term climate policy, because of the range of uncertainty over the relevant economic parameters of marginal mitigation costs and marginal social costs and damages avoided, but also because of the significant lack of data on the costs of adaptation. Instead, wider frameworks are considered to be more informative, using multiple aspects and risk-based approaches, for example iterative decision-making and tolerable windows (see also the risk matrix in Chapter 20). Stern (2007) explicitly adopted a risk-based framework appropriate for guiding policy from analysing the marginal costs and benefits at the project level to determination of public policy that affects future economic paths. He recognised that adaptation plays an important role, but not in an explicit tradeoff against mitigation, in long-term policy.

18.6 Response capacity and development pathways

As outlined in the TAR (IPCC, 2001c, Chapter 18 and IPCC, 2001b, Chapter 1) and discussed at more length in Chapter 17 of this volume and in the WGIII AR4, Chapter 12 (Sathaye et al., 2007), the ability to implement specific adaptation and mitigation measures is dependent upon the existence and nature of adaptive and mitigative capacity, which makes such measures possible and affects their extent and effectiveness. In that sense, specific adaptation and mitigation measures are rooted in their respective capacities (Yohe, 2001;Adger et al., 2003;Adger and Vincent, 2005; Brooks et al., 2005).

Adaptive capacity has been defined in this volume (see Chapter 17) as “the ability or potential of a system to respond successfully to climate variability and change.” In a parallel way, mitigative capacity has been defined as the “ability to diminish the intensity of the natural (and other) stresses to which it might be exposed” (see Rogner et al., 2007). Since this definition suggests that a group’s capacity to mitigate hinges on the severity of impacts to which it is exposed, Winkler et al. (2007) have suggested that capacity be defined instead as “a country’s ability to reduce anthropogenic greenhouse gases or enhance natural sinks”. Clearly these two categories are closely related although, in accordance with the differences between adaptation and mitigation measures discussed in Section 18.1, capacities also differ somewhat. In particular, since adaptation measures tend to be both more geographically dispersed and smaller in scale than mitigation measures (Dang et al., 2003; Ruth, 2005), adaptive capacities refer to a slightly broader and more general set of capabilities than mitigative capacities. Despite these minor differences, however, adaptive and mitigative capacities are driven by similar sets of factors.

The term response capacity may be used to describe the ability of humans to manage both the generation of greenhouse gases and the associated consequences (Tompkins and Adger, 2005). As such, response capacity represents a broad pool of resources, many of which are related to a group or nation’s level of socio-technical and economic development, which may be translated into either adaptive or mitigative capacity. Socio-cultural dimensions such as belief systems and cultural values, which are often not addressed to the same extent as economic elements (Handmer et al., 1999), can also affect response capacity (see IPCC, 2001b; Sathaye et al., 2007).

Although the concept of response capacity is new to the IPCC and has yet to be sufficiently investigated in the literature, efforts have been made to define the nature and determinants of its conceptual components: adaptive and mitigative capacity. With regard to mitigative capacity, Yohe (2001) has suggested the following list of determinants, which play out at the national level:

  • range of viable technological options for reducing emissions;
  • range of viable policy instruments with which the country might affect the adoption of these options;
  • structure of critical institutions and the derivative allocation of decision-making authority;
  • availability and distribution of resources required to underwrite the adoption of mitigation policies and the associated broadly-defined opportunity cost of devoting those resources to mitigation;
  • stock of human capital, including education and personal security;
  • stock of social capital, including the definition of property rights;
  • a country’s access to risk-spreading processes (e.g., insurance, options and futures markets);
  • the ability of decision-makers to manage information, the processes by which these decision-makers determine which information is credible, and the credibility of decision makers themselves.

In the context of developing countries, many of which possess limited institutional capacity and access to resources, mitigative and adaptive capacity could be fashioned by additional determinants. For instance, political will and the intent of decision-makers, and the ability of societies to form networks through collective action that insulates them against the impacts of climate change (Woolcock and Narayan, 2000), may be especially important in developing countries, especially in societies where policy instruments are not fully developed and where institutional capacity and access to resources are limited.

Yohe suggests a similar set of determinants for adaptive capacity, but adds the availability of resources and their distribution across the population. Recent research has sought to offer empirical evidence that demonstrates the relative influence of each of these determinants on actual adaptation (Yohe and Tol, 2002). In particular, this research indicates that the influence of each determinant of capacity is highly location specific and path-dependent, thus revealing the importance of investigations into micro- and macro-scale determinants that influence capacity across multiple stressors (Yohe and Tol, 2002). These determinants of both adaptive and mitigative capacity expand on those identified in the TAR and agree closely with those offered by Moss et al. (2001) and Adger et al. (2004). The linkages between adaptive and mitigative capacity are demonstrated by the striking similarities between these sets of determinants, which show that both the ability to adapt and the ability to mitigate depend on a mix of social, biophysical and technological constraints (Tompkins and Adger, 2005). Recent research has pointed to the necessity of broadening these lists of determinants to include other important factors such as sociopolitical aspirations (Haddad, 2005), risk perception, perceived adaptive capacity (Grothmann and Patt, 2005) and political will (Winkler et al., 2007).

These discussions of determinants indicate the close connection that exists between response capacities and the underlying socio-economic and technological development paths that give rise to those capacities. In several important respects, the determinants listed above are important characteristics of such development paths. Those development paths, in turn, underpin the baseline and stabilisation emissions scenarios discussed in the WGIII AR4, Chapter 3 (Fisher et al., 2007) and used to estimate emissions, climate change and associated climate-change impacts. As a result, the determinants of response capacity can be expected to vary across the underlying emissions scenarios reviewed in this report. The climate change and climate-change impact scenarios assessed in this report will be primarily based on the SRES storylines, which define a spectrum of different development paths, each with associated socio-economic and technological conditions and driving forces (for an extended discussion of emissions pathways and climate policies, see Fisher et al., 2007). Each storyline will therefore give rise to a different set of response capacities, and thus to different likely, or even possible, levels of adaptation and mitigation.

Adaptation and mitigation measures, furthermore, are rooted in adaptive and mitigative capacities, which are in turn contained within, and strongly affected by, the nature of the development path in which they exist. The concept of development paths is discussed at more length in the WGIII AR4 in Chapters 2 (Halsnaes et al., 2007), 3 (Fisher et al., 2007) and 12 (Sathaye et al., 2007). Here, it is sufficient to think of a development path as a complex array of technological, economic, social, institutional and cultural characteristics that define an integrated trajectory of the interaction between human and natural systems over time at a particular scale. Such technological and socio-economic development pathways find their most common expression in the form of integrated scenarios (Geels and Smit, 2000; Grubb et al., 2002; Swart et al., 2003; see also WGIII AR4, Chapter 3), but are also incorporated into studies of technological diffusion (Foray and Grubler, 1996; Dupuy, 1997;Andersen, 1998; Grubler, 2000; Berkhout, 2002; Rogers, 2003), socio-technical systems (Geels, 2004) and situations in which large physical infrastructures and the requisite supportive organisational, cultural and institutional systems create conditions of quasi-irreversibility (Arthur, 1989; Sarkar, 1998; Geels, 2005; Unruh and Carrillo-Hermosilla, 2006). Technological and social pathways co-evolve through a process of learning, coercion and negotiation (Rip and Kemp, 1998), creating integrated socio-technical systems that strongly condition responses to risks such as climate change.

In the climate-change context, the TAR noted that “climate change is thus a potentially critical factor in the larger process of society’s adaptive response to changing historical conditions through its choice of developmental paths” (Banuri et al., 2001). Later in the same volume, the following typology of critical components of development paths is presented (Toth et al., 2001):

  • technological patterns of natural resource use, production of goods and services and final consumption,
  • structural changes in the production system,
  • spatial distribution patterns of population and economic activities,
  • behavioural patterns that determine the evolution of lifestyles.

The influence of economic trajectories and structures on the adaptability of a nation’s development path is important in terms of the patterns of carbon-intensive production and consumption that generate greenhouse gases (Smil, 2000; Ansuategi and Escapa, 2002), the costs of policies that drive efficiency gains through technological change (Azar and Dowlatabadi, 1999), and the occurrence of market failures which lead to unsustainable patterns of energy use and technology adoption (Jaffe and Stavins, 1994; Jaffe et al., 2005).

In addition to these components, scholars from widely varying disciplines and backgrounds have noted the importance of institutional structures and trajectories (Olsen and March, 1989; Agrawal, 2001; Pierson, 2004; Adger et al., 2005; Ruth, 2005) and cultural factors such as values (Stern and Dietz, 1994; Baron and Spranca, 1997), discourses (Adger et al., 2001) and social rules (Geels, 2004), as elements of development paths that help determine the ability of a system to respond to change.

The importance of the connection between measures, capacities and development paths is threefold. First, as pointed out in the TAR, a full analysis of the potential for adaptation or mitigation policies must also include some consideration of the capacities in which these policies are rooted. This is increasingly being reflected in the literature being assessed in both regional/sectoral and conceptual chapters of this assessment. Second, such an analysis of response capacities should, in turn, encompass the nature and potential variability of underlying development paths that strongly affect the nature and extent of those capacities. This suggests the desirability of an integrated analysis of climate policy options that assesses the linkages between policy options, response capacities and their determinants, and underlying development pathways. Although such an integrated assessment was proposed in the Synthesis Report of the TAR (IPCC, 2001a), this type of assessment is still in its infancy.

Third, the linkages between climate policy measures and development paths described here suggest a potential disconnection between the degree of adaptation and/or mitigation that is possible and that which may be desired in a given situation. On the one hand, the development path will determine the response capacity of the scenario. On the other, the development path will strongly influence levels of greenhouse-gas emissions, associated climate change, the likely degree of climate-change impacts and thus the desired mitigation and/or adaptation in that scenario (Naki?enovi? and Swart, 2000; Metz et al., 2002; Swart et al., 2003).

However, there is no particular reason that the response capacity and desired levels of mitigation and/or adaptation will change in compatible ways. As a result, particular development paths might give rise to levels of desired adaptation and mitigation that are at odds with the degree of adaptive and mitigative capacity available. For example, particular development path scenarios that give rise to very high emissions might also be associated with a slower growth, or even a decline, in the determinants of response capacity. Such might be the case in scenarios with high degrees of military activity or a collapse of international co-operation. In such cases, climate-change impacts could increase, even as response capacity declines.

The linkages between climate policy, response capacities and development paths suggested above help us to understand the nature of the relationship between climate policy and sustainable development. There is a small but growing literature on the nature of this relationship (Cohen et al., 1998;Markandya and Halsnaes, 2000; Munasinghe and Swart, 2000; Schneider et al., 2000; Banuri et al., 2001; Robinson and Herbert, 2001; Smit et al., 2001; Beg et al., 2002; Metz et al., 2002; Najam et al., 2003; Swart et al., 2003; Wilbanks, 2003). Much of this literature emphasises the degree to which climate-change policies can have effects, sometimes called ancillary benefits or co-benefits, that will contribute to the sustainable development goals of the jurisdiction in question (Van Asselt et al., 2005). This amounts to viewing sustainable development through a climate-change lens. It leads to a strong focus on integrating sustainable development goals and consequences into the climate policy framework, and on assessing the scope for such ancillary benefits. For instance, reductions in greenhouse-gas emissions can reduce the incidence of death and illness due to air pollution and benefit ecosystem integrity – both of which are elements of sustainable development (Cifuentes et al., 2001). These co-benefits, furthermore, are often more immediate rather than long term in nature and can be significant. Van Harmelen et al. (2002) find that to comply with agreed upon or future policies to reduce regional air pollution in Europe, mitigation costs are significant, but these are reduced by 50-70% for SO2 and around 50% for NOx when combined with greenhouse-gas policies.

The challenge then becomes one of ensuring that actions taken to address environmental problems do not obstruct regional and local development (Beg et al., 2002). A variety of case studies demonstrates that regional and local development can in fact be enhanced by projects that contribute to adaptation and mitigation. Urban food-growing in two UK cities, for example, has resulted in reduced crime rates, improved biodiversity and reduced transport-based emissions (Howe and Wheeler, 1999). As such, these cities have both enhanced resilience to future climate fluctuations and have made strides towards the mitigation of climate change. Similarly, agro-ecological initiatives in Latin America have helped to preserve the natural resource base while empowering rural communities (Altieri, 1999). The concept of networking and clustering used mainly in entrepreneurial development and increasingly seen as a tool for the transfer of skills, knowledge and technology represents an interesting concept for countries that lack the necessary adaptive and mitigative capacities to combat the negative impacts of climate change.

An alternative approach is based on the findings in the TAR that it will be extremely difficult and expensive to achieve stabilisation targets below 650 ppm from baseline scenarios that embody high-emissions development paths. Low-emissions baseline scenarios, however, may go a long way towards achieving low stabilisation levels even before climate policy is included in the scenario (Morita et al., 2001). This recognition leads to an approach to the links between climate policy and sustainable development – equivalent to viewing climate change through a sustainable development lens – that emphasises the need to study how best to achieve low-emissions development paths (Metz et al., 2002; Robinson et al., 2003; Swart et al., 2003).

It has further been argued that sustainable development might decrease the vulnerability of developing countries to climate change impacts (IPCC, 2001c), thereby having implications for the necessary amount of both adaptation and mitigation efforts. For instance, economic development and institution building in low-lying, highly-populated coastal regions may help to increase preparedness to sea-level rise and decrease vulnerability to weather variability (McLean et al., 2001). Similarly, investments in public health training programmes, sanitation systems and disease vector control would both enhance general health and decrease vulnerability to the future effects of climate change (McMichael et al., 2001). Framing the debate as a development problem rather than an environmental one helps to address the special vulnerability of developing nations to climate change while acknowledging that the driving forces for emissions are linked to the underlying development path (Metz et al., 2002). Of course it is important also to acknowledge that climate change policy cannot be considered a substitute for sustainable development policy even though it is determined by similar underlying socio-economic choices (Najam et al., 2003).

Both approaches to linking climate change to sustainable development suggest the desirability of integrating climate policy measures with the goals and attributes of sustainable development (Robinson and Herbert, 2001; Beg et al., 2002; Adger et al., 2003; Van Asselt et al., 2005; Robinson et al., 2006). This suggests an additional reason to focus on the interrelationships between adaptation, mitigation, response capacity and development paths. If climate policy and sustainable development are to be pursued in an integrated way, then it will become important not simply to evaluate specific policy options that might accomplish both goals, but also to explore the determinants of response capacity that underlie those options and their connections to underlying socio-economic and technological development paths (Swart et al., 2003). Such an integrated approach might be the basis for productive partnerships with the private, public, non-governmental and research sectors (Robinson et al., 2006).

There is general agreement that sustainable development involves a comprehensive and integrated approach to economic, social and environmental processes (Munasinghe, 1992; Banuri et al., 1994; Najam et al., 2003; see also Sathaye et al., 2007). However, early work tended to emphasise the environmental and economic aspects of sustainable development, overlooking the need for analysis of social, political or cultural dimensions (Barnett, 2001; Lehtonen, 2004; Robinson, 2004). More recently, the importance of social, political and cultural factors (e.g., poverty, social equity and governance) has increasingly been recognised (Lehtonen, 2004), especially by the global environmental change policy and climate change communities (Redclift and Benton, 1994; Banuri et al., 1996; Brown, 2003; Tonn, 2003; Ott et al., 2004; Oppenheimer and Petonsk, 2005) to the point that social development, which also includes both political and cultural concerns, is now given equal status as one of the ‘three pillars’ of sustainable development. This is evidenced by the convening of the World Summit on Social Development in 1995 and by the fact that the Millennium Summit in 2000 highlighted poverty as fundamental in bringing balance to the overemphasis on the environmental aspects of sustainability. The environment-poverty nexus is now well recognised, and the link between sustainable development and achievement of the Millennium Development Goals (MDGs) (United Nations, 2000) has been clearly articulated (Jahan and Umana, 2003). In order to achieve real progress in relation to the MDGs, different countries will settle for different solutions (Dalal-Clayton, 2003), and these development trajectories will have important implications for the mitigation of climate change.

In attempting to follow more sustainable development paths, many developing nations experience unique challenges, such as famine, war, social, health and governance issues (Koonjul, 2004). As a result, past economic gains in some regions have come at the expense of environmental stability (Kulindwa, 2002), highlighting the lack of exploitation of potential synergies between sustainable development and environmental policies. In the water sector, for instance, response capacity can be improved through co-ordinated management of scarce water resources, especially since reduction in water supply in most of the large rivers of the Sahel can affect vital sectors such as energy and agriculture, which are dependent on water availability for hydroelectric power generation and agricultural production, respectively (Ikeme, 2003). Technology, institutions, economics and socio-psychological factors, which are all elements of both response capacity and development paths, affect the ability of nations to build capacity and implement sustainable development, adaptation and mitigation measures (Nederveen et al., 2003).

18.7 Elements for effective implementation

This section considers the literature assessment of the previous sections with respect to its implications for policy and decision-making. It reviews the policy and institutional contexts within which adaptation and mitigation can be implemented and discusses inter-relationships in practice.

18.7.1 Climate policy and institutions

As explained and illustrated in the previous sections of this chapter, effective climate policy would involve a portfolio of adaptation and mitigation actions. These actions include technological, institutional and behavioural options, the introduction of economic and policy instruments to encourage the use of these options, and research and development to reduce uncertainty and to enhance the options’ effectiveness and efficiency. However, the actors involved in the implementation of these actions operate on a range of different spatial and institutional scales, representing different sectoral interests. Policies and measures to promote the implementation of adaptation and mitigation actions have therefore been targeted primarily on either adaptation or mitigation; rarely have they been given similar priority and considered in conjunction (see Section 18.5 for more detail).

On the global scale, the UNFCCC and its Kyoto Protocol are at present the principal institutional frameworks by which climate policy is developed. The ultimate objective of the UNFCCC, as stated in Article 2, is:

“to achieve... stabilisation of greenhouse-gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system…within a time-frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner.”

Initially, this objective was often interpreted as having relevance only or primarily to mitigation: reducing greenhouse-gas emissions and enhancing sinks such that atmospheric concentrations are stabilised at a non-dangerous level. However, whether or not anthropogenic interference with the climate system will be dangerous does not depend only on the stabilisation level; it depends also on the degree to which adaptation can be expected to be effective in addressing the consequences of this interference. In other words, the greater the capacity of ecosystems and society to adapt to the impacts of climate change, the higher the level at which atmospheric greenhouse-gas concentrations may be stabilised before climate change becomes dangerous (see also Chapter 19). Adaptation thus complements and can, in theory and until the limits of adaptation are reached, substitute for mitigation in meeting the ultimate objective of the UNFCCC (Goklany, 2000a, 2003).

The possibility of considering adaptation and mitigation as substitutes on a global scale does not feature explicitly in the UNFCCC, the Kyoto Protocol or any decisions made by the Conference of the Parties to the UNFCCC. This is so because any global agreement on substitution would, in practice, be unable to account for the diverse, and at times conflicting, interests of all actors involved in adaptation and mitigation and for the differences in temporal and spatial scales between the two alternatives (see Section 18.3). Mitigation is primarily justified by international agreements and the ensuing national public policies, but most adaptation is motivated by private interests of affected individuals, households and firms, and by public arrangements of impacted communities and sectors. The fact that decisions on adaptation are often made at sub-national and local levels also presents a challenge to the organisation of funding for adaptation in developing countries under the UNFCCC, the Kyoto Protocol and any future international climate policy regimes (Schipper, 2006).

Yet there is one way in which adaptation and mitigation are connected at the global policy level, namely in their reliance on social and economic development to provide the capacity to adapt and mitigate. Section 18.6 introduced the concept of response capacity, which can be represented as adaptive capacity and mitigative capacity. Response capacity is often limited by a lack of resources, poor institutions and inadequate infrastructure, among other factors that are typically the focus of development assistance. People’s vulnerability to climate change can therefore be reduced not only by mitigating greenhouse-gas emissions or by adapting to the impacts of climate change, but also by development aimed at improving the living conditions and access to resources of those experiencing the impacts, as this will enhance their response capacity.

The incorporation of development concerns into climate policy demonstrates that climate policy involves more than decision-making on adaptation and mitigation in isolation. Accordingly, Klein et al. (2005) identified three roles of climate policy under the UNFCCC: (i) to control the atmospheric concentrations of greenhouse gases; (ii) to prepare for and reduce the adverse impacts of climate change and take advantage of opportunities; and (iii) to address development and equity issues. Although climate change is not the primary reason for poverty and inequality in the world, addressing these issues is seen as a prerequisite for successful adaptation and mitigation in many developing countries. In a paper produced by a number of development agencies and international organisations, Sperling (2003) made the case for linking climate policy and development assistance, which would promote opportunities for mainstreaming considerations of climate change into development on the national, sub-national and local scales (Box 18.3).

With the first commitment period of the Kyoto Protocol ending in 2012, a range of proposals have been prepared that lay out a post-2012 international climate policy regime (e.g., Den Elzen et al., 2005; Michaelowa et al., 2005). The majority of current proposals focus only or predominantly on mitigation; some proposals consider adaptation and mitigation in concert. However, few proposals have been appraised in terms of, for example, their effectiveness, efficiency and equity.

On the regional scale, climate policies and institutions do not tend to consider inter-relationships between adaptation and mitigation. In the European Union, for example, mitigation policy is conducted separately from adaptation strategies that are being developed or studied for water management, coastal management, agriculture and public health. Most Least- Developed Countries are concerned primarily with adaptation and its links with development. The Asia-Pacific Partnership on Clean Development and Climate only refers to mitigation.

Organisations such as the World Trade Organization (WTO) and the European Union can, through specific mechanisms, integrate environmental policy into their economic rationales. In addition, there is a need to address contradictions between existing policies (e.g., policies relevant to the reduction of greenhouse-gas emissions and agricultural trade policies). Energy remains a crucial input in agro-processing, transportation and packaging, and the combined effects of increases in energy consumption in the agricultural sector and impacts of agricultural trade policies are typically not considered within the context of climate change.

Regional co-operation could create ‘win-win’ opportunities in both economic integration and in addressing the adverse effects of climate change (Denton et al., 2002). Initiatives such as the New Partnership for Africa’s Development (NEPAD) and the African Ministerial Conference on the Environment conducted a number of consultative processes in order to prepare an Environmental Action Plan for the Implementation of the Environment Initiative of NEPAD. One of the proposed projects is to evaluate synergistic effects of adaptation and mitigation activities, including on-farm and catchment management of carbon with sustainable livelihood benefits. Organisations such as the West African Monetary Union (WAMU) are actively engaged in energy development to address the perennial problem of energy poverty in the continent. They focus on how to exploit the CDM and other mechanisms to mitigate present and future emissions, especially with the use of renewable energy. WAMU countries are vulnerable to drought and desertification and, while mitigation may not be their main concern, it does offer opportunities also to reduce the negative impacts of deforestation and land-use change. Equally, links between the UNFCCC and the UN Convention to Combat Desertification offer opportunities to exploit both adaptation and mitigation within the context of promoting sustainable livelihoods and environmental management. A number of sub-regional institutions have action plans to address desertification, such as the Arab Maghreb Union in northern Africa, the Intergovernmental Authority on Development in eastern Africa, the Southern African Development Community in the south, the Economic Community of Western African States and the Permanent Interstate Committee for Drought Control in the Sahel for the west, and the Economic Community of Central African Countries in central Africa.

Countries belonging to these and other regional groupings can identify projects that have net adaptation and mitigative benefits. Studies (e.g., Greco et al., 1994) have predicted a reduction in water supply in most of the large rivers of the Sahel, thus affecting vital sectors such as energy and agriculture, both of which are dependent on water availability for hydroelectric power generation and agricultural production. Seventeen countries in West Africa share 25 trans-boundary rivers and many countries within the region have a water-dependency ratio of around 90% (Denton et al., 2002). Water resources and watershed management in trans-boundary river basins are possible ways in which countries in West Africa can co-operate on a regional basis to build institutional capacity, strengthen regional networks and institutions to encourage co-operation, flow of information and transfer of technology. The construction of the Manantali Dam in Mali as part of the Senegal River Basin Initiative is to a large extent able to produce hydropower electricity and enable riparian communities to practice irrigation agriculture, especially since Senegal and Mauritania remain highly dependent on agriculture and suffer deficits in staple cereal crops. These initiatives have global sustainable development benefits since they are able to offer both adaptation and mitigative benefits as well as accelerate the economic development of countries sharing the river (namely Senegal, Mali and Mauritania) (Venema et al., 1997).

Box 18.3. Mainstreaming

The links between greenhouse-gas emissions, mitigation of climate change and development have been the subject of intense study (for an overview see Markandya and Halsnæs, 2002). More recently the links between climate-change adaptation and development have been brought to light (Section 18.6). As these links have become apparent, the term ‘mainstreaming’ has emerged to describe the integration of policies andmeasures that address climate change into development planning and ongoing sectoral decision-making. The benefit of mainstreaming would be to ensure the long-term sustainability of investments as well as to reduce the sensitivity of development activities to both today’s and tomorrow’s climate (Beg et al., 2002; Klein, 2002; Huq et al., 2003; OECD, 2005).

Mainstreaming is proposed as a way of making more efficient and effective use of financial and human resources than designing, implementing and managing climate policy separately from ongoing activities. By its very nature, energy-based mitigation (e.g., fuel switching and energy conservation) can be effective only when mainstreamed into energy policy. For adaptation, however, this link has not appeared as self-evident until recently (see Chapter 17). Mainstreaming is based on the premise that human vulnerability to climate change is reduced not only when climate change ismitigated or when successful adaptation to the impacts takes place, but also when the living conditions for those experiencing the impacts are improved (Huq and Reid, 2004).

Although mainstreaming is most often discussed with reference to developing countries, it is just as relevant to industrialised countries. In both cases it requires the integration of climate policy and sectoral and development policies. The institutional means by which such linking and integration is attempted or achieved vary from location to location, from sector to sector, as well as across spatial scales. For developing countries, the UNFCCC and other international organisations could play a part in facilitating the successful integration and implementation of adaptation and mitigation in sectoral and development policies. Klein et al. (2005) see this as a possible fourth role of climate policy, in addition to the three presented earlier in this section.

In April 2006 the OECD organised a ministerial-level meeting of the OECD Development Assistance Committee (DAC) and the Environment Policy Committee (EPOC). Themeeting served to launch a process to work in partnership with developing countries to integrate environmental factors efficiently into national development policies and poverty reduction strategies. The outcomes of the meeting were an agreed Framework for Common Action Around Shared Goals, as well as a Declaration on Integrating Climate Change Adaptation into Development Co-operation (OECD, 2006). These outcomes are evidence of the importance that is now being attached to mainstreaming adaptation into Official Development Assistance (ODA) activities. The OECD framework and declaration are expected to provide an impetus to all development agencies to consider climate change in their operations and thus facilitate mainstreaming.

To facilitate mainstreaming would require increasing awareness and understanding among decision-makers and managers, and creating mechanisms and incentives for mainstreaming. It would not require developing synergies between adaptation and mitigation per se, but rather between building adaptive and mitigative capacity, and thus with development (see Section 18.6). This fourth role of climate policy highlights the importance of involving a greater range of actors in the planning and implementation of adaptation and mitigation, including sectoral, sub-national and local actors, and the private sector (Robinson et al., 2006, see also Section 18.3).

The above may give the impression that a broad consensus has emerged that mainstreaming adaptation into ODA is the most desirable way of reducing the vulnerability of people in developing countries to climate change. There is indeed an emerging consensus among development agencies, as reflected in the OECD declaration. However, concerns about mainstreaming have been voiced within developing countries and among academics. On the one hand, there is concern that scarce funds for adaptation in developing countries could be diverted into more general development activities, which offer little opportunity to evaluate, at least quantitatively, their benefits with respect to climate change (Yamin, 2005). On the other hand, there is concern that funding for climate policy would divertmoney fromODA that ismeant to address challenges seen as beingmore urgent than climate change, including water and food supply, sanitation, education and health care (Michaelowa and Michaelowa, 2005).


The Convention on Biological Diversity has acknowledged the potential win-win opportunities between biodiversity management, on the one hand, and adaptation and mitigation to climate change, on the other. There is particular scope for this in large-scale regional biodiversity programmes such as the Mesoamerican Biological Corridor Project, in which reforestation and avoided deforestation can help to mitigate climate change through the creation of carbon sinks, while creating livelihood benefits for local communities, thus increasing their capacity to adapt to climate change. In addition, the creation of large biological corridors will help ecological communities to migrate and adapt to changing environmental conditions (CBD, 2003).

The national, sub-national and local scales are where most adaptation and mitigation actions are implemented and where most inter-relationships may be expected. However, there is little academic literature that describes or analyses policy and institutions at these levels with respect to inter-relationships of adaptation and mitigation. The literature does provide a growing number of examples and case studies (see Section 18.5) but, unlike the emerging literature on global policy and institutions, it does not yet discuss the role of policies and institutions vis-à-vis inter-relationships between adaptation and mitigation, nor does it discuss the implications of potential inter-relationships on policy and institutions. A research field is emerging that builds on studies carried out for adaptation or for mitigation. For example, the AMICA project (Adaptation and Mitigation: an Integrated Climate Policy Approach) aims to identify synergies between adaptation and mitigation for selected cities in Europe (http://www.amica-climate.net/).

In the Niayes region of central Senegal, the government has sought to promote irrigation practices and reduce dependence on rain-fed agriculture with the planting of dense hedges to act as windbreaks. These have enhanced agricultural productivity. Windbreaks have been effective in combating soil erosion and desiccation and have also provided fuel wood for cooking, thus reducing the need for women and girls to travel long distances in a rapidly urbanising area in search of wood. The windbreaks have carbon sequestration benefits but, most of all, they have helped to intensify agricultural production, especially with commercial products, thus boosting the economic livelihoods of poor communities. Thus, what started off as an adaptation strategy has had substantial integrated development benefits by easing deforestation and reducing carbon emissions, as well as addressing gender and livelihood issues (Seck et al., 2005).

Effective implementation of climate change adaptation and mitigation is often dependent on the support from local nongovernmental organisations, private sector and public government authorities. Market-based policy instruments (e.g., pollution taxes and different types of tradable permits) have been successfully implemented to provide incentives in both industrialised and developing countries. The use of tax credits and financial assistance in India has opened up the electricity market to the private sector, which has resulted in a ‘wind energy boom’ (Sawin and Flavin, 2004). Similarly, incentives for the uptake of biofuels and energy-efficiency programmes in Brazil have considerably reduced carbon emissions (Pew Center, 2002). Although these programmes have typically not been designed with the purpose of creating synergies between adaptation and mitigation, they do provide net adaptation and mitigation benefits, as well as addressing sustainable development priorities of communities. In addition, the private sector is increasingly becoming involved in environmental governance. For example, transnational corporations are being drawn into partnerships and networks to help managing the global environment.

A special role can be played by international funding agencies and climate change funds. For example, the World Bank BioCarbon Fund and Community Development Carbon Fund provide financing for reforestation projects to conserve and protect forest ecosystems, community afforestation activities, mini- and micro-hydro and biomass fuel projects. These projects are focused specifically on extending carbon finance to poorer countries and contribute not only to the mitigation of climate change but also to reducing rural poverty and improving sustainable management of local ecosystems, thereby enhancing adaptive capacity.

18.7.2 Inter-relationships in practice

In practice, adaptation and mitigation can be included in climate-change strategies, policies and measures at different levels, involving different stakeholders (see Section 18.3). For example, the European Union previously emphasised policies to focus on reducing greenhouse-gas emissions in line with Kyoto targets. However, it is increasingly acknowledging the parallel need to deal with the consequences of climate change. In 2005 the European Commission launched the second phase of the European Climate Change Programme (ECCP), which now also includes impacts and adaptation as one of its working groups. They recognise the value of win-win strategies that address climate-change impacts but also contribute to mitigation objectives (EEA, 2005).

Examples at the national level include the UK Climate Change Programme, which includes adaptation and mitigation (DETR, 2000). The UK also addresses adaptation through its Adaptation Policy Framework, the UK Climate Impacts Programme (UKCIP) and a Cross-Regional Research Programme led by the Department for Environment, Forestry and Rural Affairs (Defra). Malta identified in its first National Communication to the UNFCCC a range of win-win adaptation options, including efficiency in energy production, improving farming and afforestation (Ministry for Rural Affairs and the Environment Malta, 2004). The CzechRepublic has agreed to give priority to win-win measures, due to financial constraints (EEA, 2005).

Relevant to the sub-national and local level in the UK is the planning policy and advice released by the Office of the Deputy Prime Minister for the benefit of regional planning bodies (ODPM, 2005). It includes advice to planners on how to integrate climate change adaptation and mitigation into their policy planning decisions. ODPM (2004) encourages an integrated approach to ensure that adaptation initiatives do not increase energy demands and therefore conflict with greenhouse-gas mitigation measures. Adaptation measures would include decisions about the location of new settlements and not creating an unsustainable demand for water resources, by taking into account possible changes in seasonal precipitation.

Other examples of projects which incorporate ‘climate proofing’ include the Cities for Climate Protection Campaign, a worldwide movement of local governments working together under the umbrella of the International Council for Local Environmental Initiatives to reduce greenhouse-gas emissions, improve air quality and enhance urban sustainability. Local governments following this programme develop a baseline of their emissions, set targets and agree on an action plan to reach the targets through a sustainable development approach focusing on local quality of life, energy use and air quality (ICLEI, 2006). For example, Southampton City Council has developed a climate change strategy in conjunction with its air quality strategy and action plan, seeing close links between the two. The strategy includes measures for the council and partners to reduce net emissions of greenhouse gases and other pollutants through integrated energy systems and continued air quality monitoring. The mitigating measures are supported by improved management of the likely impacts of future climate change and the impacts on air quality through better planning and adaptation, such as coastal defence, transport infrastructure, planning and design, and flood risk mapping (Southampton City Council, 2004).

18.8 Uncertainties, unknowns and priorities for research

Many of the inter-relationships between adaptation and mitigation have been described in previous assessments of climate policy, and the literature is rapidly expanding. Nevertheless, well-documented studies at the regional and sectoral level are lacking. Adaptation and mitigation studies tend to focus only on their primary domains, and few studies analyse the secondary consequences (e.g., of mitigation on impacts and adaptation options or of adaptation actions on greenhouse-gas emissions and mitigation options). Experiences with climate change adaptation are relatively recent and large-scale, and global actions, such as insurance, adaptation protocols or issues of liability and compensation, have not been tested.

Learning from the expanding case experience of interrelationships is a priority. Reviews, syntheses and meta-analyses should become more common in the next few years. An analytical and institutional framework for monitoring the inter-relationships and organising periodic assessments needs to be developed. At present, no organisation appears to have a leading role in this area. The experiences of stakeholders in making decisions concerning both adaptation and mitigation should be compared. The experience of the research on land-use and land-cover change would be insightful (e.g., Geist and Lambin, 2002). Effective institutional development, use of financial instruments, participatory planning and risk-management strategies are areas for learning from the emerging experience (Klein et al., 2005).

A key research need is to document which stakeholders link adaptation and mitigation. Decisions oriented towards either adaptation or mitigation might be extended to evaluate unintended consequences, to take advantage of synergies or explicitly evaluate trade-offs. Yet, the constraints of organisational mandates and administrative capacity, finance and linking across scales and sectors (e.g., Cash and Moser, 2000) may outweigh the benefits of integrated decision-making. Formulation of policies that support renewable energy in developing countries is likely to meet fiscal, market, legal, knowledge and infrastructural barriers that may limit uptake.

The effects on specific social and economic groups need to be further documented. For example, development of hydroelectricity may reduce water availability for fish farming and irrigation of home gardens, potentially adversely affecting the food security of women and children (Andah et al., 2004; Hirsch and Wyatt, 2004). Linking carbon sequestration and community development could generate new opportunities for women and marginal socio-economic groups, but this will depend on many local factors and needs to be evaluated with empirical research.

The links between a broad climate-change response capacity, specific capacities to link adaptation and mitigation, and actual actions are poorly documented. Testing and quantification of the relationship between capacities to act and actual action is needed, taking into account sectoral planning and implementation, the degree of vulnerability, the range of technological options, policy instruments and information including experience of climate change.

Analytical frameworks for evaluating the links between adaptation and mitigation are inadequate, or in some cases competing. A suite of frameworks may be necessary for particular stakeholders and levels of decision-making. Decision frameworks relating adaptation and mitigation (separately or conjointly) need to be tested against the roles and responsibilities of stakeholders at all levels of action. Global optimising models may influence some decisions, while experience at the project level is important to others. The suitability of IAMs needs to be evaluated for exploring multiple metrics, discontinuities and probabilistic forecasts (Mastrandrea and Schneider, 2001, 2004; Schneider, 2003). Global cost-benefit models should include clear analyses of uncertainty in the use of valuation schemes and discounting as well as the assumptions inherent in climate impacts models (including the role of adaptation in reducing impacts). Hybrid approaches to integrated assessments across scales (top-down and bottom:up) should be further developed (Wilbanks and Kates, 2003). Representations of risks and uncertainties need to be related to decision frameworks and processes (Dessai et al., 2004; Kasperson and Kasperson, 2005; Lorenzoni et al., 2005). Climate risk, current and future, is only one aspect of adaptation-mitigation decision-making; the relative importance and effect of other drivers needs to be understood.

The magnitude of unintended consequences is uncertain. The few existing studies (e.g., Dang et al., 2003) indicate that the repercussions from mitigation for adaptation and vice versa are mostly marginal at the global level, although they may be significant at the regional scale. The effects on demand or total emissions are likely to be a small fraction of the global baseline. However, in some domains, such as water and land markets, and in some locales, the inter-relationships might affect local economies. Quantitative evaluation of direct trade-offs is missing: the metrics and methods for valuation, existence of thresholds in local feedbacks, behavioural responses to opportunities, risks and adverse impacts, documentation of the baseline and project scenarios, and scaling up from isolated, local examples to systemic changes are part of the required knowledge base.

At a global or international level, defining a socially, economically and environmentally justifiable mix of mitigation, adaptation and development remains difficult and a research need. While IAMs are relatively well developed, they can only provide approximate estimates of quantitative inter-relationships at a highly aggregated scale. Fourteen experts in estimating the social cost of carbon rated their estimates as low confidence, due to the many gaps in the coverage of impacts and valuation studies, uncertainties in projected climate change, choices in the decision framework and the applied discount rate (Downing et al., 2005). Estimates of the marginal abatement cost range from −2% to +8% of GDP, while estimates of the marginal damages avoided span three orders of magnitude (see Chapter 20). The marginal cost of adaptation has not been calculated, although some estimates assume a reduction in impacts due to adaptation (see [[17). Combining the marginal abatement cost, marginal damages avoided and the marginal cost of adaptation into an optimal strategy for climate response is subject to considerable uncertainty that is unlikely to be effectively reduced in the near term (see Harvey, 2006).

A systematic assessment with a formal risk framework that guides expert judgement and grounded case studies, and interprets the sample of published estimates, is required if policy-makers wish to identify the benefits of climate policy (e.g., Downing et al., 2005). Existing estimates of damages avoided are based on a sample of sectors exposed to climate change and a small range of climate stresses. Better understanding across a matrix of climate change and exposure is required ( 20; Fisher et al., 2007). Socio-economic conditions and locales that are likely to experience early and significant impacts (often called ‘hotspots’) should be a high priority for additional studies. The extent to which targets that are set globally are consistent with national or local mixes of strategies requires a concerted effort. The distributional effects would be an important factor in evaluating tolerable windows and trade-offs between adaptation and mitigation. The lack of high-quality studies of the benefits of mitigation, and the social cost of carbon, limits confidence in setting targets for stabilisation.

The relationship between development paths and adaptation-mitigation inter-relationships requires further research. Unintended consequences, synergies and trade-offs might be unique to some development paths; equally, they might be possible in many different paths. Existing scenarios of development paths are particularly inadequate in framing some of the major determinants of vulnerability and adaptation (Downing et al., 2003). Exogenous projections of GDP are a particular obstacle for modelling the inter-relationships between adaptation and mitigation. Few global scenarios address local food security in realistic ways (Downing and Ziervogel, 2005, but see related discussion of Millennium Development Goals in s 9 and 20). Scenarios of abrupt climate change, streams of extreme events, and realistic social, economic and political responses would add insight into adaptive management (the ‘act, then learn, then act again’ approach). Few reference scenarios explicitly frame issues related to inter-relationships between adaptation and mitigation (e.g., from the extent to which a global decision-maker makes optimising judgements to the institutional setting for local projects to exploit synergies). While the direct energy input in large infrastructure projects may be small, including a shadow price for climate change externalities may shift adaptation portfolios. An assessment of actual shifts in energy demand and ways to reduce emissions is desirable. Most integrated assessments are at the large scale of regions to world views, although local dialogues are beginning to explore synergies (Munasinghe and Swart, 2005).

The feasibility and outcome of many of the inter-relationships depend on local conditions and management options. A systematic assessment and guidance for mitigating potentially adverse effects would be helpful. The nature of links between public policy and private action at different scales, and prospects for mainstreaming integrated policy, are worth evaluating. Many of the consequences depend on environmental processes that may not be well understood; for example, the resilience of systems to increased interannual climate variability and long-term carbon sequestration in agro-forestry systems.

Contributors Coordinating Lead Authors: Richard J.T. Klein (The Netherlands/Sweden), Saleemul Huq (UK/Bangladesh) Lead Authors: Fatima Denton (The Gambia), Thomas E. Downing (UK), Richard G. Richels (USA), John B. Robinson (Canada), Ferenc L. Toth (IAEA/Hungary) Contributing Authors: Bonizella Biagini (GEF/Italy), Sarah Burch (Canada), Kate Studd (UK), Anna Taylor (South Africa), Rachel Warren (UK), Paul Watkiss (UK), Johanna Wolf (Germany) Review Editors: Michael Grubb (UK), Uriel Safriel (Israel), Adelkader Allali (Morocco) (IPCC Fourth Assessment Report, Working Group II: 18)

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References

  • Adger,W.N. and K.Vincent, 2005: Uncertainty in adaptive capacity. C. R. Geosci., 337, 399-410.
  • Adger, W.N., T.A. Benjaminsen, K. Brown and H. Svarstad, 2001: Advancing a political ecology of global environmental discourses. Dev. Change, 32, 687-715.
  • Adger,W.N., S. Huq, K. Brown, D. Conway and M. Hulme, 2003: Adaptation to climate change in the developing world. Prog. Dev. Stud., 3, 179-195.
  • Adger, W.N., N. Brooks, M. Kelly, S. Bentham and S. Eriksen, 2004: New indicators of vulnerability and adaptive capacity. Technical Report 7. Tyndall Centre for Climate Research, Norwich, 126 pp.
  • Adger,W.N., T.P.Hughes, C. Folke, S.R. Carpenter and J. Rockström, 2005: Socialecological resilience to coastal disasters. Science, 309, 1036-1039.
  • Adger,W.N., J. Paavola, S.Huq andM.J.Mace, Eds., 2006: Fairness in Adaptation to Climate Change.MIT Press, Cambridge,Massachusetts, 335 pp.
  • Agrawal, A., 2001: Common property institutions and sustainable governance of resources. World Dev., 29, 1649-1672.
  • Altieri, M.A., 1999:Applying agroecology to enhance the productivity of peasant farming systems in LatinAmerica. Environ. Dev. Sustain., 1, 197-217.
  • Andah,W., N. van de Giesen,A. Huber-Lee and C. Biney, 2004: Can we maintain food security without losing hydropower? The Volta Basin. Climate Change in Contrasting River Basins: Adaptation Strategies for Water, Food and Environment, J. Cayford, Ed., CABI Publishing, Wallingford, 181-194.
  • Andersen, B., 1998: The evolution of technological trajectories 1890-1990. Struct. Change Econ. Dynam., 9, 5-34.
  • Ansuategi, A. and M. Escapa, 2002: Economic growth and greenhouse gas emissions. Ecol. Econ., 40, 23-37.
  • Arnell, N., M.G.R. Cannell, M. Hulme, R.S. Kovats, J.F.B. Mitchell, R. Nicholls, M. Parry, M. Livermore and A. White, 2002: The consequences of CO2 stabilization for the impacts of climate change. Climatic Change, 53, 413-446.
  • Arthur, W.B., 1989: Competing technologies, increasing returns, and lock-in by historical events. Econ. J., 99, 116-131.
  • Ayub, M.S. and W.M. Butt, 2005: Nuclear desalination: harnessing the seas for development of coastal areas of Pakistan. Int. J. Nucl. Desalination, 1, 477-485.
  • Azar, C., 1998: Are optimal CO2 emissions really optimal? Four critical issues for economists in the greenhouse. Environ. Resour. Econ., 11, 301-315.
  • Azar, C. and H. Dowlatabadi, 1999: A review of technical change in assessment of climate policy. Annu. Rev. Energ. Env., 24, 513-545.
  • Bakkenes, M., B. Eickhout and R. Alkemade, 2006: Impacts of different climate stabilization scenarios on plant species in Europe. Global Environ. Chang., 16, 19-28.
  • Banuri, T., G. Hyden, C. Juma and M. Rivera, 1994: Sustainable Human Development: From Concept to Operation. A Guide for the Practitioner. United Nations Development Programme, New York.
  • Banuri, T., K. Goran-Maler, M. Grubb, H.K. Jacobson and F. Yamin, 1996: Equity and social considerations. Climate Change 1995: Economic and Social Dimensions of Climate Change. Contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change, J.P. Bruce, H. Lee and E.F. Haites, Eds., Cambridge University Press, Cambridge, 79-124.
  • Banuri, T., J. Weyant, G. Akumu, A. Najam, L. Pinguelli Rosa, S. Rayner, W. Sachs, R. Sharma and G. Yohe, 2001: Setting the stage: climate change and sustainable development. Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, R. Swart and J. Pan, Eds., Cambridge University Press, Cambridge, 73-114.
  • Barker, T., J. Koehler and M. Villena, 2002: The costs of greenhouse gas abatement: a meta-analysis of post-SRES mitigation scenarios. Environ. Econ. Policy Stud., 5, 135-166.
  • Barker, T., and Co-authors, 2007: Mitigation from a cross-sectoral perspective. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK, in press.
  • Barnett, J., 2001: The Meaning of Environmental Security: Ecological Politics and Policy in the New Security Era. Zed Books, London, 192 pp.
  • Baron, J. and M. Spranca, 1997: Protected values. Organ. Behav. Hum. Dec., 70, 1-16.
  • Beg, N., J. Corfee Morlot, O. Davidson, Y.Arfrane-Okesse, L. Tyani, F. Denton, Y. Sokona, J.P. Thomas, E.L. Rovere, J. Parikh, K. Parikh and A. Rahman, 2002: Linkages between climate change and sustainable development. Clim. Policy, 2, 129-144.
  • Bell, M.L., B.F. Hobbs and H. Ellis, 2003: The use of multi-criteria decision-making methods in integrated assessment of climate change: implications for IA practitioners. Socio-Econ. Plan. Sci., 37, 289-316.
  • Berkhout, F., 2002: Technological regimes, path dependency and the environment. Global Environ. Chang., 12, 1-4.
  • Berrittella, M., A. Bigano, R. Roson and R.S.J. Tol, 2006: A general equilibrium analysis of climate change impacts on tourism. Tourism Manage., 27, 913-924.
  • Boehm, M., B. Junkins, R. Desjardins, S. Kulshreshtha and W. Lindwall, 2004: Sink potential of Canadian agricultural soils. Climatic Change, 65, 297-314.
  • Borges, P. C. and A. Villavicencio, 2004: Avoiding academic and decorative planning in GHG emissions abatement studies with MCDA: the Peruvian case. Eur. J. Oper. Res., 152, 641-654.
  • Bosello, F., R. Roson and R.S.J. Tol, 2006: Economy-wide estimates of the implications of climate change: human health. Ecol. Econ., 58, 579-591.
  • Boutkan, E. and A. Stikker, 2004: Enhanced water resource base for sustainable integrated water resource management. Nat. Resour. Forum, 28, 150-154.
  • Brooks, N., W.N. Adger and P.M. Kelly, 2005: The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Global Environ. Chang., 15, 151-163.
  • Brown, P., 1998: Climate, Biodiversity, and Forests. Issues and Opportunities Emerging from the Kyoto Protocol. World Resources Institute, Washington, District of Columbia.
  • Brown, D.A., 2003: The importance of expressly examining globalwarming policy issues through an ethical prism. Global Environ. Chang., 13, 229-234.
  • Bulkeley, H., 2001: Governing climate change: the politics of risk society? T. I. Brit. Geogr., 26, 430-447.
  • Burton, I. and M. van Aalst, 1999: Come Hell or High Water: Integrating Climate Change Vulnerability and Adaptation into Bank Work. World Bank, Washington, District of Columbia, 60 pp.
  • Butt, T.A. and B.A. McCarl, 2004: Farm and forest sequestration: can producers employ it to make some money? Choices, Fall 2004, 27-33.
  • CAG Consultants and Oxford Brookes University, 2004: Planning Response to Climate Change: Advice on Better Practice. Office of the Deputy Prime Minister, London, 108 pp.
  • Caparros, A. and F. Jacquemont, 2003: Conflicts between biodiversity and carbon sequestration programmes: economic and legal implications. Ecol. Econ., 46, 143-157.
  • Carbon International, undated: The Gold Standard: Premium Quality Carbon Credits. Cash, D.W. and S. Moser, 2000: Linking global and local scales: designing dynamic assessment and management processes. Global Environ. Chang., 10, 109-120.
  • CBD, 2003: Climate Change and Biodiversity: Executive Summary of the Report on the Interlinkages Between Biological Biodiversity and Climate Change. CBD Technical Series No. 10. Convention on Biological Diversity.
  • Christensen, J.H. and Co-authors, 2007: Regional climate projections. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller, Eds., Cambridge University Press, Cambridge, 847- 940.
  • Christensen, N.S., A.W. Wood, N. Voisin, D.P. Lettenmaier and R.N. Palmer, 2004: The effects of climate change on the hydrology and water resources of the Colorado River Basin. Climatic Change, 54, 269-293.
  • Cifuentes, A.L., V.H. Borja-Aburto, N. Gouveia, G. Thurston and D.L. Davis, 2001: Hidden health benefits of greenhouse gas mitigation. Science, 293, 1257-1259.
  • Clark, W.C., J. Jaeger, J. van Eijndhoven and N. Dickson, 2001: Learning to Manage Global Environmental Risks: A Comparative History of Social Responses to Climate Change, Ozone Depletion, and Acid Rain. MIT Press, Cambridge, Massachusetts, 361 pp.
  • Clark, W.C., P.J. Crutzen and H.-J. Schellnhuber, 2004: Science for global sustainability: toward a new paradigm. Earth System Analysis for Sustainability, H.-J. Schellnhuber, P.J. Crutzen, W.C. Clark, M. Claussen and H. Held, Eds., MIT Press, Cambridge, Massachusetts, 1-28.
  • Clarkson, R. and K. Deyes, 2002: Estimating the social cost of carbon emissions. Government Economic Service Working Paper 140. HM Treasury and Defra, London.
  • Cohen, S., D. Demeritt, J. Robinson and D. Rothman, 1998: Climate change and sustainable development: towards dialogue. Global Environ. Chang., 8, 341-373.
  • Cohen, S., K. Miller, K. Duncan, E. Gregorich, P. Groffman, P. Kovacs, V. Magaña, D. McKnight, E. Mills and D. Schimel. 2001: North America. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 735-800.
  • Corfee-Morlot, J. and S. Agrawala, 2004: The Benefits of Climate Change Policies: Analytical and Framework Issues. OECD, Paris, 323 pp.
  • Dalal-Clayton, B., 2003: The MDGs and Sustainable Development: The Need for a Strategic Approach. IIED, London, 73-91.
  • Dang, H.H., A. Michaelowa and D.D. Tuan, 2003: Synergy of adaptation and mitigation strategies in the context of sustainable development: the case of Vietnam. Clim. Policy, 3, S81-S96.
  • Den Elzen, M., P. Lucas and D. van Vuuren, 2005:Abatement costs of post-Kyoto climate regimes. Energ. Policy, 33, 2138-2151.
  • Denton, F., Y. Sokona and J.P. Thomas, 2002: Climate Change and Sustainable Development Strategies in the Making: What Should West African Countries Expect? OECD, Paris, 27 pp.
  • Dessai, S., W.N. Adger, M. Hulme, J. Turnpenny, J. Kohler and R. Warren, 2004: Defining and experiencing dangerous climate change. Climatic Change, 64, 11- 25.
  • DETR, 2000: Climate Change Programme. DETR, London, 3 pp.
  • Döll, P., 2002: Impact of climate change and variability on irrigation requirement: a global perspective. Climatic Change, 54, 269-293.
  • Dowie, J., 1999: Against risk. Risk Decision Policy, 4, 57-73.
  • Downing, T.E., M. Munasinghe and J. Depledge, 2003: Introduction to special supplement on climate change and sustainable development. Clim. Policy, 3, 3-8.
  • Downing, T.E. and G. Ziervogel, 2005: Food system scenarios: exploring global/local linkages. Working Paper, SEI Poverty and Vulnerability Report. Stockholm Environment Institute, Stockholm, 35 pp.
  • Downing, T.E., D. Anthoff, R. Butterfield, M. Ceronsky, M. Grubb, J. Guo, C. Hepburn, C. Hope, A. Hunt, A. Li, A. Markandya, S. Moss, A. Nyong, R.S.J. Tol and P. Watkiss, 2005: Scoping uncertainty in the social cost of carbon. Final Project Report, Social Cost of Carbon: A Closer Look at Uncertainty (SCCU). Defra/SEI, Oxford.
  • Dumanski, J., 2004: Carbon sequestration, soil conservation, and the Kyoto Protocol: summary of implications. Climatic Change, 65, 255-261.
  • Dupuy, D., 1997: Technological change and environmental policy: the diffusion of environmental technology. Growth Change, 28, 49-66.
  • Edenhofer, O., K. Lessmann and N. Bauer, 2006: Mitigation strategies and costs of climate protection: the effects of ETC in the hybrid model MIND. Energy Journal Special Issue: Endogenous Technological Change and the Economics of Atmospheric Stabilization, 207-222.
  • Edmonds, J., J. Clarke, J. Dooley, S.H. Kim, S.J. Smith, 2004: Stabilization of CO2 in a B2 world: insights on The Roles of Carbon Capture and Disposal, Hydrogen, and Transportation Technologies. Energy Economics, 26, 517-537.
  • EEA, 2005: Vulnerability and adaptation to climate change in Europe. EEA Technical Report No. 7/2005. EEA, Copenhagen.
  • Eriksen, S. and L.O. Næss, 2003: Pro-Poor Climate Adaptation: Norwegian Development Cooperation and Climate Change Adaptation – An Assessment of Issues, Strategies and Potential Entry Points. Centre for International Climate and Environmental Research Oslo, UniversityOslo, Oslo. of
  • Evans, D. and H. Sezer, 2004: Social discount rates for six major countries. Appl. Econ. Lett., 11, 557-560.
  • Fankhauser, S. and R.S.J. Tol, 2005: On climate change and economic growth. Resour. Energy Econ., 27, 1-17.
  • Fisher, B.S., G. Jakeman, H.M. Pant, M. Schwoon and R.S.J. Tol, 2006: CHIMP: a simple population model for use in integrated assessment of global environmental change. Integr. Assess. J., 6, 1-33.
  • Fisher, B.S. and Co-authors, 2007: Issues related to mitigation in the long-term context. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • Foray, D. and A. Grubler, 1996: Technology and the environment. Technol. Forecast. Soc., 53, 3-13.
  • GAIM Task Force, 2002: GAIM’s Hilbertian questions. Research GAIM: Newsletter of the Global Analysis, Integration and Modelling Task Force, 5, 1-16.
  • Geels, F.W., 2004: From sectoral systems of innovation to socio-technical systems: insights about dynamics and change from sociology and institutional theory. Res. Policy, 33, 897-920.
  • Geels, F.W., 2005: Processes and patterns in transitions and system innovations: refining the co-evolutionary multi-level perspective. Technol. Forecast. Soc., 72, 681-696.
  • Geels, F.W. and W.A. Smit, 2000: Failed technology futures: pitfalls and lessons from a historical survey. Futures, 32, 867-885.
  • Geist, H.J. and E.F. Lambin, 2002: Proximate causes and underlying driving forces of tropical deforestation. BioScience, 52, 143-150.
  • Gitay H. and Co-authors, 2001: Ecosystems and their goods and services. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 235-342.
  • Goklany, I.M., 2000a: Potential consequences of increasing atmospheric CO2 concentration compared to other environmental problems. Technology, 7S, 189-213.
  • Goklany, I.M., 2000b: Applying the Precautionary Principle to Global Warming. Weidenbaum Center Working Paper, PS 158.WashingtonUniversity, St. Louis, Missouri.
  • Goklany, I.M., 2003: Relative contributions of global warming to various climate sensitive risks, and their implications for adaptation and mitigation. Energ. Environ., 14, 797-822.
  • Goklany, I.M., 2005: A climate policy for the short and medium-term: stabilization or adaptation? Energ. Environ., 16, 667-680.
  • Goklany, I.M., 2007: Integrated strategies to reduce vulnerability and advance adaptation, mitigation, and sustainable development. Mitigation and Adaptation Strategies for Global Change, 12, 755-786.
  • Gough, C. and S. Shackley, 2001: The respectable politics of climate change: the epistemic communities and NGOs. Int. Aff., 77, 329-346.
  • Greco, S., R.H. Moss, D. Viner and R. Jenne, 1994: Climate Scenarios and Socio-Economic Projections for IPCC WGII Assessment. Intergovernmental Panel on Climate Change, Washington, District of Columbia, 67 pp.
  • Gregory, J.M., K.W. Dixon, R.J. Stouffer, A.J. Weaver, E. Driesschaert, M. Eby, T. Fichefet, H. Hasumi, A. Hu, J.H. Jungclaus, I.V. Kamenkovich, A. Levermann, M. Montoya, S. Murakami, S. Nawrath, A. Oka, A.P. Sokolov and R.B. Thorpe, 2005: A model intercomparison of changes in the Atlantic thermohaline circulation in response to increasing atmospheric CO2 concentration. Geophys. Res. Lett., 32, L12703, doi:10.1029/2005GL023209.
  • Grothmann, T. and A. Patt, 2005: Adaptive capacity and human cognition: the process of individual adaptation to climate change. Global Environ. Chang., 15, 199-213.
  • Grubb, M., 2003: The economics of the Kyoto Protocol. World Econ., 4, 143-189.
  • Grubb, M., J. Kohler and D. Anderson, 2002: Induced technological change in energy and environmental modelling: analytic approaches and policy implications. Annu. Rev. Energy Env., 21, 271-308.
  • Grubler, A., 2000: Technology and Global Change. Cambridge University Press,
  • Cambridge, 462 pp.
  • Guo, J., C. Hepburn, R.S.J. Tol and D. Anthoff, 2006: Discounting and the social cost of carbon: a closer look at uncertainty. Environ. Sci. Policy, 9, 205-216.
  • Haddad, B., 2005: Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit. Global Environ. Chang., 15, 165-176.
  • Halsnaes, K. and Co-authors, 2007: Framing issues. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • Handmer, J.W., S. Doers and T.E. Downing, 1999: Societal vulnerability to climate change and variability. Mitigation and Adaptation Strategies for Global Change, 4, 267-281.
  • Hare, B., 2006: Relationship between increases in global mean temperature and impacts on ecosystems, food production, water and socio-economic systems. Avoiding Dangerous Climate Change, H.-J. Schellnhuber, W. Cramer, N. Naki?enovi?, T. Wigley and G. Yohe, Eds., Cambridge University Press, Cambridge, 177-185.
  • Harvey, L.D.D., 2006: Uncertainties in global warming science and near-term emission policies. Clim. Policy, 6, 573-584.
  • Hayhoe, K., D. Cayan and C.B. Field, 2004: Emissions pathways, climate change, and impacts on California. P. Natl. Acad. Sci. USA, 101, 12422-12427.
  • Hirsch, P. and A. Wyatt, 2004: Negotiating local livelihoods: scales of conflict in the Se San River Basin. Asia Pac. Viewpoint, 45, 51-68.
  • Hitz, S. and J. Smith, 2004: Estimating global impacts from climate change. Global Environ. Chang. 14, 201-218.
  • Holdridge, L.R., 1947: Determination of world plant formations from simple climatic data. Science, 105, 367 – 368.
  • Holdridge, L. R., 1967: Life Zone Ecology. Tropical Science Centre, San Jose, Costa Rica.
  • Howe, J. and P. Wheeler, 1999: Urban food growing: the experience of two UK cities. Sustain. Dev., 7, 13-24.
  • Huq, S. and H. Reid, 2004: Mainstreaming adaptation in development. IDS Bull., 35, 15-21.
  • Huq, S., A. Rahman, M. Konate, Y. Sokona and H. Reid, 2003: Mainstreaming Adaptation to Climate Change in Least Developed Countries (LDCs). IIED, London, 40 pp.
  • ICLEI, 2006: Climates for City Protection (CCP) Campaign, http://www.iclei.org/.
  • IEA (International Energy Agency), 2005: Electricity Information 2005. Organisation for Economic Cooperation and Development, Paris, 783 pp.
  • Ikeme, J., 2003: Climate change adaptation deficiencies in developing countries: the case of sub-Saharan Africa. Mitigation and Adaptation Strategies for Global Change, 8, 29-52.
  • IPCC, 1992: Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment. J.T. Houghton, B.A. Callander and S.K. Varney, Eds., Cambridge University Press, Cambridge, 200 pp.
  • IPCC, 2001a: Climate Change 2001: Synthesis Report. A Contribution of Working Groups I, II, III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, R.T. Watson and the Core Team, Eds., Cambridge University Press, Cambridge and New York, 398 pp.
  • IPCC, 2001b: Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, R. Swart and J. Pan, Eds., Cambridge University Press, Cambridge, 760 pp.
  • IPCC, 2001c: Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press., Cambridge, 1032 pp.
  • IPCC, 2002: Climate Change and Biodiversity, H. Gitay, A. Suárez, R.T. Watson and D.J. Dokken, Eds., IPCC, Geneva, 85 pp.
  • IPCC, 2007: Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • IRM, AIRMIC and ALARM, 2002: A Risk Management Standard. AIRMIC, IRM, ALARM, London, 17 pp.
  • Jaffe, A.B. and R.N. Stavins, 1994: The energy-efficiency gap: what does itmean? Energ. Policy, 22, 804-810.
  • Jaffe, A.B., R.G. Newell and R.N. Stavins, 2005: A tale of two market failures: technology and environmental policy. Ecol. Econ., 54, 164.
  • Jahan, S. and A. Umana, 2003: The environment–poverty nexus. Dev. Policy J., 3, 53-70.
  • Kane, S. and J.F. Shogren, 2000: Linking adaptation and mitigation in climate change policy. Climatic Change, 45, 75-102.
  • Kasperson, J.X. and R.E. Kasperson, 2005: The Social Contours of Risk. Earthscan, London, 578 pp.
  • Keeney, R.L. and H. Raiffa, 1976: Decisions with Multiple Objectives: Preferences and Value Trade-offs. John Wiley and Sons, New York, 600 pp.
  • Keller, K., G. Yohe and M. Schlesinger, 2007: Managing the risks of climate thresholds: uncertainties and information needs. Climatic Change, doi:10.1007/s10584-006-9114-6. http://www.geosc.psu.edu/~kkeller/Keller_cc_07.pdf.
  • Klein, R.J.T., 2001: Adaptation to Climate Change in German Official Development Assistance: An Inventory of Activities and Opportunities, With a Special Focus on Africa. Deutsche Gesellschaft für Technische Zusammenarbeit, Eschborn, 44 pp.
  • Klein, R.J.T., 2002: Climate change, adaptive capacity and sustainable development. Paper presented at an Expert Meeting on Adaptation to Climate Change and Sustainable Development, Organisation for Economic Co-operation and Development, Paris, 13–14March 2002, 8 pp.
  • Klein, R.J.T., E.L. Schipper and S. Dessai, 2005: Integrating mitigation and adaptation into climate and development policy: three research questions. Environ. Sci. Policy, 8, 579-588.
  • Köhler, J., M. Grubb, D. Popp and O. Edenhofer, 2006: The transition to endogenous technical change in climate-economy models. Energy Journal Special Issue: Endogenous Technological Change and the Economics of Atmospheric Stabilization, 17-55.
  • Koonjul, J., 2004: The special case of Small Island States for sustainable development. Nat. Resour. Forum, 28, 155-156.
  • Kulindwa, K., 2002: Economic reforms and the prospect for sustainable development in Tanzania. Dev. S. Afr., 19, 389-404.
  • Lal, R., 2004: Soil carbon sequestration impacts on global climate change and food security. Science, 304, 1623-1627.
  • Lehtonen, M., 2004: The environmental–social interface of sustainable development: capabilities, social capital, institutions. Ecol. Econ., 49, 199-214.
  • Lempert, R. and M.E. Schlesinger, 2000: Robust strategies for abating climate change. Climatic Change, 45, 387- 401.
  • Lempert, R.J., S.W. Popper and S.C. Bankes, 2004: Shaping the Next One Hundred Years: New Methods for Quantitative, Long-term Policy Analysis. Rand, Santa Monica, California, 170 pp.
  • Levine, M. and Co-authors, 2007: Residential and commercial buildings. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • Link, P.M. and Tol, R.S.J., 2004: Possible economic impacts of a shutdown of the thermohaline circulation: an application of FUND. Port. Econ. J., 3, 99-114.
  • Lorenzoni, I., N.F. Pidgeon and R.E. O’Connor, 2005: Dangerous climate change: the role for risk research. Risk Anal., 25, 1387-1398.
  • Manne, A.S. and R.G. Richels, 1992: Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits. MIT Press, Cambridge, Massachusetts, 194 pp.
  • Markandya, A. and K. Halsnaes, 2000: Climate Change and its Linkages with Development, Equity and Sustainability. Intergovernmental Panel on Climate Change, Geneva.
  • Markandya, A. and K. Halsnæs, 2002: Climate Change and Sustainable Development: Prospects for Developing Countries. Earthscan, London, 291 pp.
  • Martens, P. and J. Rotmans, Eds., 2002: Transitions in a Globalising World. Swets and Zeitlinger, Lisse, 135 pp.
  • Mastrandrea, M.D. and S.H. Schneider, 2001: Integrated assessment of abrupt climate change. Clim. Policy, 1, 433-449.
  • Mastrandrea, M.D. and S.H. Schneider, 2004: Probabilistic integrated assessment of “dangerous” climate change. Science, 304, 571-575.
  • McCarl, B.A. and U.A. Schneider, 2000: Agriculture’s role in a greenhouse gas emission mitigation world: an economic perspective. Rev. Agr. Econ., 22, 134-159.
  • McDonald, S., S. Robinson and K. Thierfelder, 2006: Impact of switching production to bioenergy crops: the switchgrass example. Energ. Econ., 28, 243-265.
  • McLean, R.F., A. Tsyban, V. Burkett, J.O. Codignotto, D.L. Forbes, N. Mimura, R.J. Beamish, V. Ittekkot, L. Bijlsma and I. Sanchez-Arevalo, 2001: Coastal zones and marine ecosystems. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 343-379.
  • McMichael, A., A. Githeko, R. Akhtar, R. Carcavallo, D. Gubler, A. Haines, R. Kovats, P. Martens, J. Patz and A. Sasaki, 2001: Human health. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 453-478.
  • MEA (Millennium Ecosystem Assessment), 2005: Ecosystems and Human Wellbeing: Synthesis. Island Press, Washington, District of Columbia, 160 pp.
  • Meehl G. and Co-authors, 2007:Global climate projections. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller, Eds., Cambridge University Press, Cambridge, 747-846.
  • Metz, B., M. Berk, M. den Elzen, B. de Vries and D. van Vuuren, 2002: Towards an equitable global climate change regime: compatibility with Article 2 of the Climate Change Convention and the link with sustainable development. Clim. Policy, 2, 211-230.
  • Michaelowa, A., 2001: Mitigation versus adaptation: the political economy of competition between climate policy strategies and the consequences for developing countries. HWWA Discussion Paper No. 153,University of Hamburg, Hamburg.
  • Michaelowa, A. and K. Michaelowa, 2005: Climate or development: is ODA diverted from its original purpose? HWWI Research Paper 2, Hamburg, 32 pp.
  • Michaelowa, A., K. Tangen and H. Hasselknippe, 2005: Issues and options for the post-2012 climate architecture: an overview. Int. Environ. Agreements, 5, 5-24.
  • Ministry for Rural Affairs and the Environment Malta, 2004: The First Communication of Malta to the UNFCCC.
  • Misra, B.M., 2003: Advances in nuclear desalination. Int. J. Nucl. Desalination, 1, 19-29.
  • Moomaw, W.R., J.R. Moreira, K. Blok, D.L. Greene, K. Gregory, T. Jaszay, T. Kashiwagi, M. Levine, M. McFarland, N. Siva Prasad, L. Price, H.-H. Rogner, R. Sims, F. Zhou and P. Zhou, 2001: Technological and economic potential of greenhouse gas emissions reduction. Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, R. Swart and J. Pan, Eds., Cambridge University Press, Cambridge, 167-299.
  • Morita, T., J. Robinson, J. Adegulugbe, J. Alcamo, D. Herbert, E. La Rovere, N. Naki?enovi?, H. Pitcher, P. Raskin, K. Riahi, A. Sankovski, V. Sokolov, B. de Vries and D. Zhou, 2001: Greenhouse gas emission mitigation scenarios and implications. Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, R. Swart and J. Pan, Eds., Cambridge University Press, Cambridge, 115-166.
  • Moser, S.C., 2005: Impacts assessments and policy responses to sea-level rise in three U.S. states: an exploration of human dimension uncertainties. Global Environ. Chang., 15, 353-369.
  • Moss, R., A. Brenkert and E. Malone, 2001: Vulnerability to Climate Change: A Quantitative Approach. Pacific Northwest National Laboratory (PNNL-SA-33642).
  • Munasinghe, M., 1992: Environmental Economics and Sustainable Development. World Bank., Washington District of Columbia, 111 pp.
  • Munasinghe, M. and R. Swart, Eds., 2000: Climate Change and its Linkages with Development, Equity and Sustainability. Intergovernmental Panel on Climate Change, Geneva.
  • Munasinghe, M. and R. Swart, 2005: Primer on Climate Change and Sustainable Development. Cambridge University Press, Cambridge, 458 pp.
  • Nagai, H. and C. Hepburn, 2005:Howcost-effective are carbon emission reductions under the Prototype Carbon Fund? MSc Environmental Change and Management, Oxford University, Oxford, 132 pp.
  • Najam, A., A. Rahman, S. Huq and Y. Sokona, 2003: Integrating sustainable development into the Fourth Assessment Report of the IPCC. Clim. Policy, 3, S9-S17.
  • Naki?enovi?, N. and R. Swart, Eds., 2000: IPCC Special Report on Emissions Scenarios: A Special Report of IPCC Working Group III. Cambridge University Press, Cambridge, 599 pp.
  • Nederveen, A., J. Konings and J. Stoop, 2003:Globalization, international transport and the global environment: technological innovation, policy making and the reduction of transport emissions. Transport. Plan. Technol., 26, 41-67.
  • Newell, R.G. and W.A. Pizer, 2000: Regulating stock externalities under uncertainty. Discussion Paper 99-10-REV. Resources for the Future, Washington, District of Columbia.
  • Nicholls, R.J. and J.A. Lowe, 2004: Benefits of mitigation of climate change for coastal areas. Global Environ. Chang., 14, 229-244.
  • Nicholls R.J. and J.A. Lowe, 2006: Climate stabilisation and impacts of sea-level rise. Avoiding Dangerous Climate Change, H.-J. Schellnhuber, W. Cramer, N. Naki?enovi?, T. Wigley and G. Yohe, Eds., Cambridge University Press, Cambridge, 195-202.
  • Nicholls, R.J. and R.S.J. Tol, 2006: Impacts and responses to sea-level rise: a global analysis of the SRES scenarios over the twenty-first century. Philos. T. Roy. Soc. A, 364, 1073-1095.
  • Nicholls, R.J., R.S.J. Tol and A.T. Vafeidis, 2005: Global Estimates of the Impact of a Collapse of the West Antarctic Ice Sheet: An Application of FUND. Working Paper FNU-78, Research Unit on Sustainability and Global Change, Hamburg University and Centre for Marine and Atmospheric Science, Hamburg.
  • Nicholls R.J., R.S.J. Tol and J.W. Hall, 2007: Assessing impacts and responses to global-mean sea-level rise. Human-Induced Climate Change: An Interdisciplinary Assessment, M. Schlesinger, J. Reilly, H. Kheshgi, J. Smith, F. de la Chesnaye, J.M. Reilly, T. Wilson and C. Kolstad, Eds., Cambridge University Press, Cambridge.
  • Nordhaus, W.D., 2001: Global warming economics. Science, 294, 1283-1284. ODPM, 2004: The Planning Response to Climate Change: Advice on Better Practice. Office of the Deputy Prime Minister, London.
  • ODPM, 2005: Planning Policy Statement I: Delivering Sustainable Development. Office of the Deputy Prime Minister, London.
  • OECD, 2005: Bridge over Troubled Waters: Linking Climate Change and Development. Organisation for Economic Cooperation and Development, S. Agrawala, Ed., OECD Publications, Paris, 153 pp.
  • OECD, 2006: Declaration on Integrating Climate Change Adaptation into Development Co-operation Adopted by Development and Environment Ministers of OECD Member Countries. OECD Publications, Paris.
  • Olsen, J.P. and J.G. March, 1989: Rediscovering Institutions: The Organizational Basis of Politics. The Free Press, New York.
  • Oppenheimer, M. and A. Petsonk, 2005: Article 2 of the UNFCCC: historical origins, recent interpretations. Climatic Change, 73, 195-226.
  • Ott, H.E., H. Winkler, B. Brouns, S. Kartha, M. Mace, S. Huq, Y. Kameyama, A.P. Sari, J. Pan, Y. Sokona, P.M. Bhandari, A. Kassenberg, E.L. La Rovere and A.A. Rahman, 2004: South-North Dialogue on Equity in the Greenhouse: A Proposal for an Adequate and Equitable Global Climate Agreement. GTZ, Eschborn.
  • Pal, R.C. and Sharma, A., 2001: Afforestation for reclaiming degraded village common land: a case study. Biomass Bioenerg., 21, 35-42.
  • Parry, M., N. Arnell, M. Hulme, R. Nicholls and M. Livermore, 1998: Adapting to the inevitable. Nature, 395, 741.
  • Parry, M.L., C.A. Rosenzweig, A. Iglesias, M. Livermore and G. Fisher, 2004: Effects of climate change on global food production under SRES emissions and socioeconomic scenarios. Global Environ. Chang., 14, 53-67.
  • Payne, J.T., A.W. Wood, A.F. Hamlet, R.N. Palmer and D.P. Lettenmaier, 2004: Mitigating the effects of climate change on the water resources of the Columbia River Basin. Climatic Change, 62, 233-256.
  • Pelling, M., 2003: The Vulnerability of Cities: Natural Disaster and Social Resilience. Earthscan, London, 212 pp.
  • Peters, M., R. House, J. Lewandrowski and H. McDowell, 2001: Economic impacts of carbon charges on U.S. agriculture. Climatic Change, 40, 445-473. Pew Center, 2002: Climate change mitigation in developing countries: Brazil, China, India, Mexico, South Africa, and Turkey. Pew Center Global Warming Research Reports, October 24, 2002. Pew Center on Global Climate Change, Arlington, Virginia.
  • Pidgeon, N., R.E. Kasperson and P. Slovic, Eds., 2003: The Social Amplification of Risk. Cambridge University Press, Cambridge, 464 pp.
  • Pierson, P., 2004: Politics in Time: History, Institutions and Social Analysis. Princeton University Press, Princeton, New Jersey, 208 pp.
  • Rahmstorf, S., 2000: The thermohaline ocean circulation: a system with dangerous thresholds? Climatic Change, 46, 247-256.
  • Raiffa, H., 1968: Decision Analysis: Introductory Lectures on Choices Under Uncertainty. Addison-Wesley, Reading, Massachusetts, 310 pp.
  • Raskin, P. ,G. Gallopin, P. Gutman, A. Hammond and R. Swart, 2002a: Bending the Curve: Toward Global Sustainability. A Report of the Global Scenario Group. SEI PoleStar Series Report No. 8. Stockholm Environment Institute, Stockholm, 144 pp.
  • Raskin, P., T. Banuri, G. Gallopin, P. Gutman, A. Hammond, R. Kates and R. Swart. 2002b: Great Transition: The Promise and Lure of the Times Ahead. A Report of the Global Scenario Group. SEI PoleStar Series Report No. 10. Stockholm Environment Institute, Boston, Massachusetts.
  • Rayner, S. and E.L. Malone, Eds., 2001: Climate change, poverty, and intragenerational equity: the national level. Int. J. Global Environ. Iss., 1, 175-202.
  • Redclift, M. and T. Benton, Eds., 1994: Social Theory and the Global Environment. Routledge, London and New York, 280 pp.
  • Richels, R.G., A.S. Manne and T.M.L. Wigley, 2004: Moving beyond concentrations: the challenge of limiting temperatures change. AEI-Brookings Joint Center Working Paper 04-11,April 2004.
  • Rip, A. and R. Kemp, 1998: Technological change. Human Choice and Climate Change: Volume 2: Resources and Technology, E.L. Malone and S. Rayner, Eds., Batelle Press, Columbus, Ohio.
  • Robinson, J., 2004: Squaring the circle? Some thoughts on the idea of sustainable development. Ecol. Econ., 48, 369-384.
  • Robinson, J. and D. Herbert, 2001: Integrating climate change and sustainable development. Int. J. Global Environ. Iss., 1, 130-149.
  • Robinson, J.,M. Bradley, P. Busby, D. Connor, A. Murray and B. Sampson, 2003: Climate Change and Sustainable Development: Realizing the Opportunity at the World Climate Change Conference, Moscow, 30 September–4 October.
  • Robinson, J., M. Bradley, P. Busby, D. Connor, A. Murray, B. Sampson and W. Soper, 2006: Climate change and sustainable development: realizing the opportunity. Ambio, 35, 2-8.
  • Rogers, E.M., 2003: Diffusion of Innovations, 5th ed., Free Press, New York, 384pp.
  • Rogner, H.-H.,D. Zhou and Co-authors, 2007: Introduction. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • Rosenberg, N.J. and M.J. Scott, 1995: Implications of policies to prevent climate change for future food security. Climate Change and World Food Security: Proceedings of the NATO Advanced Research Workshop “Climate Change and World Food Security”, Oxford, 11-15 July 1993, T.E. Downing, Ed., Springer, Berlin, 551-589.
  • Ruth, M., 2005: Future socioeconomic and political challenges of global climate change. From Resource Scarcity to Ecological Security: Exploring New Limits to Growth, D.C. Pirages and K. Cousins, Eds., MIT Press, Cambridge, Massachusetts, 145-164.
  • Ruth, M. and A.-C. Lin, 2006: Regional energy demand and adaptations to climate change: methodology and application to the state of Maryland, USA. Energ. Policy, 34, 2820-2833.
  • Sarkar, J., 1998: Technological diffusion: alternative theories and historical evidence. J. Econ. Surv., 12, 131-176
  • Sathaye, J. and Co-authors, 2007: Sustainable development and mitigation. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, P. Bosch, R. Dave and L. Meyer, Eds., Cambridge University Press, Cambridge, UK.
  • Sawin, J. and C. Flavin, 2004: Policy Lessons for the Advancement and Diffusion of Renewable Energy Technologies around the World. Thematic background paper prepared for The Energy Research Institute, New Delhi, India. Presented at the International Conference for Renewable Energies, Bonn, Germany.
  • Schelling, T.C., 1995: Intergenerational discounting. Energ. Policy, 23, 395-401.
  • Schipper, E.L.F., 2006: Conceptual history of adaptation in the UNFCCC process. Review of European Community and International Environmental Law, 15, 82-92.
  • Schneider, S.H., 1997: Integrated assessment modelling of global climate change: transparent rational tool for policy making or opaque screen hiding value-laden assumptions? Environ. Model. Assess., 2, 229-249.
  • Schneider, S.H., 2003: Abrupt Non-linear Climate Change, Irreversibility, and Surprise. OECD, Paris, 32 pp.
  • Schneider, S.H. and R.S. Chen, 1980: Carbon dioxide flooding: physical factors and climatic impact. Annu. Rev. Energy, 5, 107-140.
  • Schneider, S.H., W. Easterling and L. Mearns, 2000: Adaptation: sensitivity to natural variability, agent assumptions and dynamic climate changes. Climatic Change, 45, 203-221.
  • Seck, M., N.A. Mamouda and S. Wade, 2005: Senegal adaptation and mitigation through produced environments: the case for agricultural intensification in Senegal. Vulnerability, Adaptation and Climate Disasters: A Conceptual Overview, F. Yamin, A. Rahman and S. Huq, Eds., IDS Bull., 36, 71-86.
  • Smil, V., 2000: Energy in the 20th century: resources, conversions, costs, uses and consequences. Annu. Rev. Energ. Env., 25, 21-51.
  • Smit, B., O. Pilifosova, I. Burton, B. Challenger, S. Huq, R.J.T. Klein and G. Yohe, 2001: Adaptation to climate change in the context of sustainable development and equity. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 879-906.
  • Smith, J. and D. Tirpak, Eds., 1989: The Potential Impacts of Global Climate Change on the United States. Environmental Protection Agency, Washington, District of Columbia.
  • Smith, J.B., H.-J. Schellnhuber, M. Mirza, S. Fankhauser, R. Leemans, Lin Erda, L. Ogallo, B. Pittock, R. Richels, C. Rosenzweig, U. Safriel, R.S.J. Tol, J. Weyant and G. Yohe, 2001: Vulnerability to climate change and reasons for concern: a synthesis. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 914-967.
  • Smith, J.B., R.J.T. Klein and S. Huq, Eds., 2003: Climate Change, Adaptive Capacity and Development. Imperial College Press, London, 347 pp.
  • Southampton City Council, 2004: Climate Change, Air Quality Strategy and Action Plan.
  • Sperling, F., Ed., 2003: Poverty and Climate Change: Reducing the Vulnerability of the Poor through Adaptation. AfDB, ADB, DFID, ECDG Development, BMZ, DGIS, OECD, UNDP, UNEP and the World Bank, Washington, District of Columbia, 43 pp.
  • Stainforth, D.A., T. Aina, C. Christensen, M. Collins, N. Faull, D.J. Frame, J.A. Kettleborough, S. Knight, A. Martin, J.M. Murphy, C. Piani, D. Sexton, L.A. Smith, R.A. Spicer, A.J. Thorpe and M.R. Allen, 2005:Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433, 403-405.
  • Stern, N., 2007: The Economics of Climate Change: The Stern Review. Cambridge University Press, Cambridge, 692 pp.
  • Stern, P.C. and T. Dietz, 1994: The value basis of environmental concern. J. Soc. Issues, 50, 65-84.
  • Swart, R., J. Robinson and S. Cohen, 2003: Climate change and sustainable development: expanding the options. Clim. Policy, 3, S19-S40.
  • Taylor, A., B. Hassan, J.A. Downing and T.E. Downing, 2006: Toward a typology of adaptation–mitigation inter-relationships. Stockholm Environment Institute, Oxford. http://www.vulnerabilitynet.org/.
  • Tol, R.S.J., 2001: Equitable cost–benefit analysis of climate change. Ecol. Econ., 36, 71-85.
  • Tol, R.S.J., 2002: Welfare specifications and optimal control of climate change: an application of fund. Energ. Econ., 24, 367-376.
  • Tol, R.S.J., 2003: Is the uncertainty about climate change too large for expected cost-benefit analysis? Climatic Change, 56, 265-289.
  • Tol, R.S.J., 2005a: Adaptation and mitigation: trade-offs in substance and methods. Environ. Sci. Policy, 8, 572-578.
  • Tol, R.S.J., 2005b: The marginal damage cost of carbon dioxide emissions: an assessment of the uncertainties. Energ. Policy, 33, 2064-2074.
  • Tol, R.S.J., 2005c: Emission abatement versus development as strategies to reduce vulnerability to climate change: an application of FUND. Environ. Dev. Econ., 10, 615-629.
  • Tol, R.S.J., 2007: The double trade-off between adaptation and mitigation for sea level rise: an application of FUND. Mitigation and Adaptation Strategies for Global Change, 12, 741-753.
  • Tol, R.S.J. and H. Dowlatabadi, 2001: Vector-borne diseases, climate change, and economic growth. Integr. Assess., 2, 173-181.
  • Tol, R.S.J. and G. Yohe, 2006: Of dangerous climate change and dangerous emission reduction. Avoiding Dangerous Climate Change, H.-J. Schellnhuber, W. Cramer, N. Naki?enovi?, T. Wigley and G. Yohe, Eds., Cambridge University Press, Cambridge, 291-298.
  • Tol, R.S.J., M. Bohn, T.E. Downing, M.-L. Guillerminet, E. Hizsnyik, R. Kasperson, K. Lonsdale, C. Mays, R.J. Nicholls, A.A. Olsthoorn, G. Pfeifle, M. Poumadère, F.L. Toth, A.T. Vafeidis, P.E. van der Werff and I.H. Yetkiner, 2006: Adaptation to five metres of sea level rise. J. Risk Res., 9, 467-482.
  • Tompkins, E. and W.N. Adger, 2005: Defining a response capacity for climate change. Environ. Sci. Policy, 8, 562-571.
  • Tonn, B., 2003: An equity first, risk-based framework for managing global climate change. Global Environ. Chang., 13, 295-306.
  • Toth, F.L., 2003: State of the art and future challenges for integrated environmental assessment. Integr. Assess., 4, 250-264.
  • Toth, F.L., M. Mwandosya, C. Carraro, J. Christensen, J. Edmonds, B. Flannery, G. Gay-Garcia, H. Lee, K.M. Meyer-Abich, E. Nikitina, A. Rahman, R. Richels, R. Ye, A. Villavicencio, Y. Wake and J. Weyant, 2001: Decision-making frameworks. Climate Change 2001: Mitigation. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O. Davidson, R. Swart and J. Pan, Eds., Cambridge University Press, Cambridge, 601-688.
  • Toth, F.L., T. Bruckner, H.-M. Füssel, M. Leimbach, G. Petschel-Held and H.-J. Schellnhuber, 2002: Exploring options for global climate policy in an inverse integrated assessment framework. Environment, 44, 23-34.
  • Toth, F.L., T. Bruckner, H.-M. Füssel, M. Leimbach and G. Petschel-Held, 2003a: Integrated assessment of long-term climate policies. Part 1. Model presentation. Climatic Change, 56, 37-56.
  • Toth, F.L., T. Bruckner, H.-M. Füssel,M. Leimbach and G. Petschel-Held, 2003b: Integrated assessment of long-term climate policies. Part 2. Model results and uncertainty analysis. Climatic Change, 56, 57-72.
  • UK FRP (United Kingdom Forestry Research Programme), 2005: From the Mountain to the Tap: How Land Use and Water Management can Work Together for the Rural Poor. UK FRP, London, 54 pp.
  • United Nations, 1997: Kyoto Protocol to the United Nations Framework Convention on Climate Change. http://unfccc.int/resource/docs/convkp/kpeng.pdf.
  • United Nations, 2000: United Nations Millennium Declaration: Resolution adopted by the General Assembly, 55th Session, 18 September. A/RES/55/22. United Nations.
  • Unruh, G. and J. Carrillo-Hermosilla, 2006: Globalizing carbon lock-in. Energ. Policy, 34, 1185-1197.
  • Van Asselt, H., J. Gupta and F. Biermann, 2005: Advancing the climate agenda: exploiting material and institutional linkages to develop a menu of policy options. Rev. Eur. Community Int. Environ. Law, 14, 255-263.
  • Van Harmelen, T., J. Bakker, B. de Vries, D. van Vuuren, M. den Elzen and P. Mayerhofer, 2002: Long-Term Reductions in Costs of Controlling Regional Air Pollution in Europe Due to Climate Policy. Environ. Sci. and Policy, 5, 349-365.
  • Van Rheenen, N.T., A.W. Wood, R.N. Palmer and D.P. Lettenmaier, 2004: Potential implications of PCM climate change scenarios for Sacramento-San Joaquin River Basin hydrology and water resources. Climatic Change, 62, 257-281.
  • Van Vuuren, D.P., B. Eickhout, P.L. Lucas and M.G.J. den Elzen, 2006: Long-term multi-gas scenarios to stabilise radiative forcing: exploring costs and benefits within an integrated assessment framework. Energ. J., 27, 201-233.
  • Vaughan, D.G. and J.R. Spouge, 2002: Risk estimation of collapse of the West Antarctic Ice Sheet. Climatic Change, 52, 65–91.
  • Vellinga, P. and Co-authors, 2001: Insurance and other financial services. Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, J.J. McCarthy, O.F. Canziani, N.A. Leary, D.J. Dokken and K.S. White, Eds., Cambridge University Press, Cambridge, 417-450.
  • Venema, D.H. and M. Cisse, 2004: Seeing the Light: Adapting to Climate Change with Decentralized Renewable Energy in Developing Countries. IISD, Canada, 174 pp.
  • Venema, D.H., E.J. Schiller, K. Adammowski and J.M. Thizy, 1997: A water resource planning response to climate change in Senegal River basin. J. Environ. Manage., 49, 125-155.
  • Verheyen, R., 2005: Climate Change Damage and International Law: Prevention, Duties and State Responsibility. Martinus Nijhoff, Netherlands, 418 pp.
  • Warren, R., 2006: Impacts of global climate change at different annual mean global temperature rises. Avoiding Dangerous Climate Change, H.-J. Schellnhuber, W. Cramer, N. Naki?enovi?, T. Wigley and G. Yohe, Eds., Cambridge University Press, Cambridge, 93-131.
  • Watkiss, P., D. Anthoff, T. Downing, C. Hepburn, C. Hope, A. Hunt and R. Tol, 2005. The Social Costs of Carbon (SCC) Review: Methodological Approaches for Using SCC Estimates in Policy Assessment, Final Report. Department for Environment, Food and Rural Affairs (Defra), London, 121 pp. http://www.defra.gov.uk/environment/climatechange/research/carboncost/pdf/aeat-scc-report.pdf.
  • WEA, 2000: World Energy Assessment. UN Development Program, UN Department of Economic and Social Affairs, and the World Energy Council, New York, 500 pp.
  • Weyant, J.P., 2004: Introduction and overview. Special Issue: EMF19 Alternative Technology Strategies for Climate Change Policy. Energ. Econ., 26, 501-515.
  • Wilbanks, T., 2003: Integrating climate change and sustainable development in a place-based context. Clim. Policy, 3, S147-S154.
  • Wilbanks, T. and R. Kates, 2003: Making the global local: responding to climate change concerns from the bottom up. Environment, 45, 12-23.
  • Winkler, H., K. Baumert, O. Blanchard, S. Burch and J. Robinson, 2007: What factors influence mitigative capacity? Energ. Policy, 35, 15-28.
  • Woolcock, N. and D. Narayan, 2000: Social capital: implications for development theory, research, and policy. World Bank Res. Obser., 15, 225-249.
  • World Bank, undated: Community Development Carbon Fund and BioCarbon Fund. World Bank, Washington, District of Columbia, http://carbonfinance.org/Router.cfm?Page=CDCF, http://carbonfinance.org/Router.cfm?Page=BioCF.
  • Yamin, F., 2005: The European Union and future climate policy: is mainstreaming adaptation a distraction or part of the solution? Clim. Policy, 5, 349–361.
  • Yohe, G., 2001: Mitigative capacity: the mirror image of adaptive capacity on the emissions side. Climatic Change, 49, 247-262.
  • Yohe, G. and R.S.J. Tol, 2002: Indicators for social and economic coping capacity: moving toward a working definition of adaptive capacity. Global Environ. Chang., 12, 25-40.
  • Young, O., 2002: The Institutional Dimensions of Environmental Change: Fit, Interplay, and Scale. MIT Press, Cambridge, Massachusetts, 237 pp.


This is a chapter from IPCC Fourth Assessment Report Working Group II.
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Change, I. (2012). IPCC Fourth Assessment Report, Working Group II: Chapter 18. Retrieved from http://editors.eol.org/eoearth/wiki/IPCC_Fourth_Assessment_Report,_Working_Group_II:_Chapter_18