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1 Climate Change Mitigation and Adaptation: From Separation to Integration

1 Climate Change Mitigation and Adaptation: From Separation to Integration

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“capacity to adapt was considered something inherent in ecosystems and society,

therefore not requiring explicit policy”.

The 1990s saw adaptation gradually become established as a viable and legitimate policy option. This slow progress has been explained in various ways:

Negotiators from states with high emissions were reluctant to propose adaptation

measures because this could be seen as an admission of responsibility, while some

refused to discuss adaptation strategies because they did not acknowledge that

climate change was actually taking place. Adaptation was also considered a ‘defeatist’ option, and a possible hindrance for establishing a mitigation framework,

rendering climate policy a choice between mitigation and adaptation (Parry et al.

1998; Schipper 2006).

The Kyoto Protocol was agreed at the UNFCCC’s third conference in 1997, as

an achievement of long-lasting mitigation focus. The following year, Parry et al.

(1998) argued that implementation of the Kyoto targets hardly would affect projected impacts of climate change, and the authors therefore urged the international

society to embrace adaptation strategies to reduce impacts of inevitable climate

change. They deemed ignoring adaptation as both ‘unrealistic and perilous’ (op

cit.). Similar calls combined with delays in the implementation of the Kyoto

Protocol prepared the ground for a dedicated adaptation policy, as it became clear

that mitigation would not suffice and that adaptation was a necessity.

The advent of adaptation policy seems to have been accompanied with a considerable shift in the approach to the term. While adaptation initially was seen as “a

spontaneous adjustment that would determine the limits of how much climate

change could be tolerated, and hence how much mitigation was necessary”, it was

gradually transformed to a policy strategy for sustainable development (Schipper

2006: 91). Since COP-6 in 2000, adaptation has increasingly been associated with

capacity building, technology transfer and equity. In 2001, adaptation received a

more prominent role in the Third Assessment Report (TAR) of the IPCC compared

to earlier assessment reports, and in 2004 an important step was made by COP-10 in

Buenos Aires, when a work program for adaptation was adopted (UNFCCC 2005).

This appreciation of adaptation as a climate change policy on par with mitigation

does not automatically imply that the strategies are treated in an integrated manner.

Mitigation and adaptation are still to a large degree kept apart, as seen in the IPCC

working group structure, which maintains a division between mitigation and

adaptation responses (IPCC 2014a, b). However, there are calls for greater integration between the two policy fields (e.g. Wilbanks and Sathaye 2007; Biesbroek

et al. 2009), and some achievements have been made in this respect.

An increasing number of studies suggest that mitigation and adaptation are

complexly interrelated (Ayers and Hug 2009; Warren 2011), and thus advocate the

need to handle the challenges of mitigating and adapting to climate change in

context and not separately. Some argue that this is important in order to achieve a

more cost effective climate policy (Kane and Shogren 2000). Others state the

importance of such an integral approach in particular for the case of poor countries

in order to avoid climate policies that undermine sustainable development goals

(Laukkonena et al. 2009; Hall 2015). It has also been suggested that, if treated



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separately, there is a danger that adaptation policies may trigger increases in GHG

emissions and mitigating policies may trigger increases in societal vulnerability to

climate change (Klein et al. 2007; Bizikova et al. 2007; Corfee-Morlot et al. 2009;

Warren 2011). These insights are highlighted in the summary for policy-makers by

the IPCC (2014b: 89): “Significant co-benefits, synergies, and trade-offs exist

between mitigation and adaptation and among different adaptation responses;

interactions occur both within and across regions. Increasing efforts to mitigate and

adapt to climate change imply an increasing complexity of interactions, but tools to

understand and manage these interactions remain limited”.

The prefix ‘mal’ has been linked in the literature to both ‘adaptation’ and

‘mitigation’ in order to coin a situation with less-then-anticipated effective adaptation or mitigation policies. In both cases this may also relate to the existence of

co-benefits, synergies and trade-offs between mitigation and adaptation.

The term ‘maladaptation’ has been given different interpretations (Juhola et al.

2016). It could mean less effective adaptation than anticipated, but most frequently

it is used to describe a situation in which adaptation efforts leads to increased, rather

than decreased, vulnerability (Smit 1993; Burton 1997; IPCC 2001). Scheraga and

Grambsch (1998) provide an even broader definition and describe maladaptation as

a situation whereby negative impacts of all sorts (not merely that of increasing

climate vulnerabilities) are caused by adaptation decisions. Barnett and O’Neil

(2010) elaborates on this perspective and identify five distinct types or pathways

through which maladaptation arises. Namely actions that, relative to alternatives:

Increase GHG emissions; disproportionately burden the most vulnerable; have high

opportunity costs; reduce incentives to adapt; and set paths that limit the choices

available to future generations. This latter pathway is similar to the concept of

‘lock-in’ in sustainable transitions research. According to Geels (2004), path

dependence and lock-in occur because socio-technical systems, rules and actors and

organizations provide stability through different mechanisms such as networks and

mutual dependence. In seeking to synthesize the various approaches towards

maladaptation Juhola et al. (2016) developed a typology of the outcomes of maladaptation: Rebounding vulnerability (i.e. adaptation action that increases current or

future climate change vulnerability of the implementing actor or the targeted actor

(s) if implemented by, e.g. a local government); shifting (or ‘spill-over’) vulnerability (i.e. adaption action at one specific location that may cause an increase in

climate change vulnerability at a different location); and eroding sustainable

development (i.e. adaptation action that increases GHG emissions, negatively

impacts environmental conditions and/or social and economic values). The literature also discusses a number of sources for maladaptation, many of which focus on

short-term profit maximization or institutional path dependency (Barnett and O’Neil

2010; Granberg and Glover 2012a, b). From this perspective maladaptation can be

the results of how society organizes its adaptation governance and if and how this

governance is coordinated and steered.

The term ‘malmitigation’ is noted in international literature to a much lesser

extent, but is given a similar meaning as its twin term—i.e. ineffective mitigation,

mitigating leading to an increased vulnerability for climate change, or the wider



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definition that mitigation may lead to a large variety of negative environmental

side-effects (Corfee-Morlot et al. 2009; Nurhadi et al. 2013; Scrieciua et al. 2013;

Kongsager et al. 2015).

The task of integrating adaptation and mitigation seems to have gained most

weight in a local policy context (Schreurs 2008). This is illustrated, for example, by

a comprehensive Canadian handbook on local climate change adaptation from 2007

(Bizikova et al. 2008) and the Proceedings from the World Congress on Resilient

Cities arranged by the International Council of Local Environmental Initiatives

(Sidi 2012)—both of which present several concrete examples of (mostly) negative

interactions between adaptation and mitigation. These interactions are structured in

accordance with a two-axis model: Increasing/decreasing GHG emissions and

increasing/decreasing climate change vulnerabilities (cf. Fig. 12.1). An example of

an antagonistic relationship between adaptation and mitigation which is currently

attaining increased attention in research is that of densifying versus diluting

land-use patterns in urban areas. The densification strategy is developed in order to

reduce GHG emissions from urban transportation and heating of residential houses,

whereas the dilution strategy is developed in order to reduce vulnerability towards

urban flooding by means of creating more ‘space’ for water (Groven 2015).



ADAPTATION

Vulnerabilities

increased

New Vulnerabilities, e.g. shift from

fossil fuels to hydro-electric power



Unsustainability, e.g. removal of

mangroves for resort development



Emissions

increased

MITIGATION



Emissions

decreased



Integrated Adaptation and Mitigation,

e.g. water security improved by demand

and supply side management;

improvements in recycling and waste

management and minimisation



Adaptive emissions, e.g. use of air

conditioning in accommodation;

construction of concrete sea walls



Vulnerabilities

decreased

Fig. 12.1 Linkages between adaptation and mitigation (adapted from Cohen and Waddell 2009)



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12.2



Modelling Malmitigation, Maladaptation

and the Relationship Between the Two



Whilst the IPCC highlights the urgency of focusing on the negative consequences

of adaptation, their definition of maladaptation does not go far in making it analytically distinct or to operationalize it for further research and practice to avoid

negative outcomes (Juhola et al. 2016). The same seems to be the case for climate

change mitigation. Thus, a comprehensive framework to understand why both

mitigation and adaptation ineffectiveness occurs, which in turn can inform us on

how to reduce such ineffectiveness, is missing. As illustrated in a number of articles

in this book, the rebound effect is basically about that the actual effect of a specific

effort proves to be less than expected due to counterproductive processes or actions

—termed ‘rebound effects’—which are caused by carrying out the effort in question. Thus, the rebound concept may offer a framework for a comprehensive

understanding of ineffectiveness traps embedded in the policy domain in question;

be it ‘energy’ or (as for the case of this article) ‘climate’. In the figure below we

have presented a model that aims at doing this. The model differentiates between

three main categories of rebound effects, here illustrated with such effects taking

place within the climate policy domain (see Fig. 12.2):



Intra rebound effects:

Causing ineffectiveness within mitigation and

adaptation policies



Cross rebound effects:

Causing ineffectiveness between and within

mitigation and adaptation



Inter rebound effects:

Causing ineffectiveness between mitigation and

adaptation



No rebound effects:

Full effect climate change adaptation and

mitigation efforts



Fig. 12.2 A suggested model for identifying categories of climate change mitigation and

adaptation rebound effects



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• Intra rebound effects: The situation in which net GHG reduction is lower than

anticipated, or the net effect of climate change adaptation is lower than

anticipated.

• Inter rebound effects: The situation in which climate change mitigation efforts

increases climate change vulnerabilities, or climate change adaptation increases

GHG emissions.

• Cross rebound effects: The situation in which intra and inter rebound effects

takes place at the same time.

The fourth alternative in Fig. 12.2 is the case in which none of these three

categories of rebound effects come into action.

It is important to note that when expanding the application of the concept of

rebound effects from the classical context (termed ‘intra rebound effects’ in

Fig. 12.2) to a situation which involves two different resource categories (cf. the

categories ‘inter’ and ‘cross’ rebound effects, involving the two resource categories

‘GHG emissions’ and ‘climate vulnerability’) we must face the challenge of to a

certain degree comparing ‘apples and oranges’. Although adaptation and mitigation

could—and should—be noted as ‘two sides of the same coin’, it still remains a

challenge to compare the two in the sense that adaptation actions are more of a

‘qualitative’ nature than mitigation actions. While mitigation can be measured in

one quantitative dimension (e.g. kg of GHG emissions) there is no single yardstick

that is widely accepted when discussing the outcomes of adaptation. Thus, it will be

impossible to analyze intra rebound effects in the same quantitative way as for inter

rebound effects within the energy policy domain, e.g. to assess in any meaningful

way a percentage increase in climate change vulnerability due to the implementation of a specific mitigation effort. Instead we have to apply a combined quantitative

and qualitative approach when describing the behavioural and systemic relationships between adaptation and mitigation efforts.



12.3



The Case of Tourism



We have selected tourism to illustrate the potential of applying the model presented

above. We have selected tourism as an illustrative case because it is a particularly

GHG-emission intensive economic sector (Gössling 2010); because it for the last

decades has in fact and are (by representatives of the sector) expected to experiense

for the coming years a particularly strong increase in GHG emissions (Gössling

et al. 2013; Scott et al. 2016), and at the same time it is extremely susceptible to

major adaptation challenges due to climate change (Scott et al. 2012). Below we

will present examples of intra and inter rebound effects relating to climate policy

efforts currently taking place within the tourism sector.

Although intra rebound effects have been recognized in relation to natural

resource use since the 19th century, their implications have been not received much

attention in tourism (Hall 2009, 2010). There have been significant concerns



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