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2 Modelling Malmitigation, Maladaptation and the Relationship Between the Two

2 Modelling Malmitigation, Maladaptation and the Relationship Between the Two

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Tourism: Applying Rebound Theories and Mechanisms …


• 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


• 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.


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


C. Aall et al.

expressed about the extent of intra rebound effects in mitigating GHG emissions

from aviation, which is the largest sectoral contributor to tourism emissions (Scott

et al. 2016). Sorrell (2010) observed that increased consumption of air travel and

tourism would potentially be driven by increases in macroeconomic efficiency gains

as sustained increases in per-capita consumption outweigh efficiency gains. Indeed,

in the highly competitive airline industry the efficiency gains may serve to fuel the

low pricing that exists on some air routes. Barker et al. (2009) modelled the

rebound effects resulting from the global energy efficiency measures incorporated

into the IPCC’s Fourth Assessment Report and estimated that for transport there

would be a worldwide direct rebound of 9.1 % in 2020 and 9.1 % in 2030, and a

macroeconomic rebound of 26.9 % in 2020 and 43.1 % in 2030. Therefore, leading

to a total economy wide rebound of 36.0 % in 2020 and 52.2 % in 2030. This

compares to an estimated rebound for all sectors of 31 % of the projected energy

savings potential by 2020, rising to 52 % by 2030 (Barker et al. 2009). Hall et al.

(2013) argue that if this scale of rebound was applied to World Tourism

Organisation (UNWTO 2008) and World Economic Forum (2009) estimates of

emissions then, even allowing for the estimated greater use of low-carbon fuels, the

actual increase in emissions allowing for rebound effects would likely be over

200 % in absolute terms despite greater per tourist fuel efficiencies given the extent

to which growth in tourist trips and speed and distance travelled outweighs

increased efficiencies. This means that by 2030 the impacts of forecast energy

efficiencies on proposed tourism emissions reduction will potentially be more than

halved and that the reduction in the potential gain in energy efficiencies over the

period to 2035 cut by more than 35 % (Gössling et al. 2013).

Installing artificial snow-making facilities is a commonly selected strategy for

adapting to an anticipated reduction in snow reliability (Demiroglu et al. 2013) even

though this is also frequently done as an economic measure to extend the skiing

season under current climate conditions (Aall and Høyer 2005). Still, installing such

facilities may all other factors alike introduce new climate change vulnerabilities in

the way that the ski resort will become more dependent on an abundant supply of

fresh water in order to produce snow (Gössling et al. 2012). Climate change may

also lead to decreased water availability during periods when artificial snow is

required (Matasci et al. 2014). Looking at this from the consumer-side, adapting to

reduced snow reliability is to a large extent a question of ‘chasing for snow’; i.e. to

increase the level of transport involved in skiing. Also here we can in principle

point at the possibility of this producing new climate change vulnerabilities, like

increased exposure to climate-related natural hazard events on roads and railways.

Studies of possible inter rebound effect specifically aimed at the tourism sector

are limited, and they mostly analyzes the extent to which adaptation together with

mitigation takes place (see e.g. Becken 2005; Gössling et al. 2013) and to a very

limited extent discusses the potential of antagonistic effects taking place between

these two modes of climate policy-areas, nor say discusses the strategies required to

avoid such effects.

According to Barnett and O’Neil (2010) the most often-cited example of maladaptation is that of the increased use of GHG-emission intensive air-conditioners


Tourism: Applying Rebound Theories and Mechanisms …


in order to adapt to the increased rate of heat waves (Kovats et al. 2006), an issue of

significance for many accommodation providers in tourism destinations. The

growing use of water for pools and spas in water scarce regions, sometimes via

energy intensive desalination plants (McEvoy and Wilder 2012) is another example

that is frequently cited in tourism research (Gössling et al. 2015).

Tourism is a major economic user of alpine regions that are increasingly prone to

the impacts of climate change, not just on snow availability but also on landscape

geomorphology and slope stability. Although winter tourism lower altitude/lower

latitude winter resorts are coming under increased pressure from climate change,

growing consumer demand means that higher altitude/high-latitude resorts in alpine

regions which can provide greater snow security can continue to expand. However,

localized erosion may be promoted by construction of second homes, hotels and

resorts, and ski areas and the roads needed to access them (Kurtaslan and Demirel

2011). Furthermore, the expansion of alpine areas formerly regarded as marginal for

development can create new climate-related natural hazard risks. Snow can be

stabilized with structures that retain or redirect it to avoid avalanches. However, as

Walker and Shiels (2013, p. 10) point out, “physical structures lead to a false sense

of security and additional development in landslide-prone terrain, [providing] … an

illustration of Jevon’s paradox (increased efficiency in resource use leads to

increased use)”.

Another example of inter rebound effects of climate change adaptation is that of

desalination in the Canary Islands, a major tourism destination for which desalination is critical with respect to maintaining a sufficient level of water supply in the

face of climate change and the danger of reduced levels of precipitation. Even

today, the fresh water supply of the Island of Lanzarote is entirely dependent upon

this technology (von Medeazza and Moreau 2007). First implemented in 1964,

desalination provided the fresh water that enabled Lanzarote’s tourism industry to

develop. Between 1986 and 2002 fresh water production grew by 425 %, while the

resident population grew by 108 % and tourists by 250 %. In 2001 the net water

consumption per permanent resident was 120 litres per person per day; while

tourists consumed 460 litres, although luxurious hotels required over 1000 litres per

tourist per day. As von Medeazza and Moreau (2007, p. 1030) commented, “it

seems that increasing supplies will always be insufficient because they increase

demands even faster and that ultimately, supplies will always be fully used up…

Decreasing production energy costs seem indeed to trigger a rebound effect on

water consumption”. Significantly, seawater desalination is the island’s greatest

individual energy consumer so there is a close coupling between energy, water and

emissions and the level of use of water in the tourism industry. As von Medeazza

and Moreau (2007) conclude ‘hydraulic structuralism’ produced the perception

from many stakeholders that water scarcity problems could be entirely solved by

increasing supplies. However, the creation of additional supplies appears to have

created a diffusion of responsibility effect “in which a ‘water squander’ culture—

subsequently triggering socially constructed water calamities—increasingly

emerge” (2007, p. 1030).


C. Aall et al.

Another candidate of an inter rebound effect of climate change mitigation and

adaptation is the process of making destinations more dependent of single climatic

‘powered’ renewable energy sources like hydro-power and wind—which, all other

factors alike, may lead to some destinations being more vulnerable to climatic

variability, e.g. less water availability for hydro-power generation or wind availability especially at times of peak seasonal demand (and thus, more vulnerable to

climate change). One option for mitigating this kind of malmitigation would be to

combine the change from fossil energy to renewable energy sources with that of

reducing the total end-use of energy as part of a destination sustainable transition

strategy. Also significant where appropriate is to ensure that there is a mix of

renewable power sources rather than being reliant on a single source.

Still, the perhaps most obvious candidate for illustrating inter rebound effects

involved in climate policy is that of adapting to an anticipated reduction in snow

reliability. As already mentioned, a consumer adaptation strategy is that of ‘chasing

for snow’ which obviously will lead to an increase in transport-related GHG

emissions. A web-survey of 224 visitors to the three Norwegian alpine summer ski

canters (Stryn, Folgefonna and Juvasshytta) showed that a large share of the skiers

would choose long trips by air if the summer snow-conditions in Norway would be

to poor. When asked on how the respondents would react, taking a realistic account

of their time and budget limits, should negative perceptions on the effect of climate

change hold, activity substitution in the form of top-touring came out to be the most

favoured alternative (Demiroglu et al. 2015). On a scale of 1–5 for ‘very little’ to

‘very much’ this alternative had a mean score of 3.84, followed by temporal substitution to the same ski centre in summer (3.67), and medium tendency towards

spatial substitution to the other two centres within Norway (2.98). The least

favoured alternatives were spatial substitution to the summer centres in the Alps

(2.45), North America (1.89), and Japan (1.66), the winter resorts in South America

(2.44), Australia and New Zealand (2.21), and South Africa (1.72), and an activity

substitution in the forms of skiing at dry (1.52) and indoor slopes (1.57) and

replacing summer skiing for good with other leisure activities (2.23).

Examples of producer-related inter rebound effects in winter tourism are even

more profound. Here, we may identify a ‘ladder’ of climate change adaptation

ranging from adjustments to transformative efforts:

• Installation of artificial snow-making facilities at existing ski resorts

• Extension of existing ski slopes to higher altitudes

• Supplementation of existing ski resorts with new and more snow reliable ski

resorts within the same ski destination

• Establishment of new ski destinations in more snow reliable areas.

• Construction of outdoor artificial (mostly snowflex) or hybrid (articifial + natural

snow) ski slopes.

• Construction of ‘roofs’ over natural ski slopes making them a semi-indoor arena.

• Construction of a 100 % indoor skiing arenas with 100 % controlled climate



Tourism: Applying Rebound Theories and Mechanisms …


In all of these examples, although to a varying degree, we might experience inter

rebound effects in the form of increased energy use (and accompanying GHG

emissions) from constructing, maintaining and running of the different installations.

For the case of moving skiing facilities or developing new facilities we may also

experience increased energy use from transportation due to the fact that many

traditional and old skiing locations are often located in connection with major

public transportation hubs (in particular, railroad hubs), whereas new locations

often are located farther away from such hubs—thus resulting in an increase in car

use at the expense of public transportation.


How to Avoid Rebound Effects in Climate Change

Adaptation and Mitigation: A Suggested Agenda

for Policymaking and Further Research

Høyer (2010) claims that the contemporary discourse on climate change is dominated by what he calls CO2 reductionism, in which complex phenomena interconnecting both nature and society are reduced to one singular issue: emissions of

CO2. This kind of misconception will, according to Høyer, inevitably lead to

suboptimal and even contra productive policies—e.g. what we above have defined

as intra rebound effects leading to mitigation ineffectiveness. The solution to this

situation is according to Høyer to reunite CO2 with the other factors from which it

has become disconnected during the last two decades, namely that of greenhouse

gases, fossil energy, energy, consumption, economic growth, sustainable development and the post-carbon society. For example, in urban design and planning, a

great deal of attention has been given to encouraging compact and denser cities in

order to reduce local mobility and encourage greater use of public transport without

considering its effects on individual’s broader mobility lifestyles (see also the

contribution of Petter Næss, this volume). Strandell and Hall (2015) found that,

even after controlling for demographic and socio-economic factors, the denser the

residential area the more people use second homes. Similarly, and also in Finland,

Ottelin et al. (2014) found that GHG emissions from flying can offset the gain from

reduced private driving in dense urban areas. These findings are important because

they emphasize that tourism, as well as emissions in general, need to be understood

within the totality of individual lifestyles and consumption practices.

Similar to what Høyer (2010) describes regarding the mitigation part of the

climate change discourse, it could be claimed that the contemporary discourse on

climate change adaptation is dominated by what we could call resilience-reductionism, in which the complex options for society on how to respond to climate

change is reduced to the one task: To protect society from the negative effects of

climate in order to maintain society as it is today (Amundsen 2014). Even if climate

change adaptation may include large-scale efforts and lead to at least some sort of

societal change, it is not evident that such changes also may lead to the qualitative


C. Aall et al.

societal changes envisioned in the IPCC Special Report “Managing the Risks of

Extreme Events and Disasters to Advance Climate Change Adaptation” and their

definition of the concept of transformation (IPCC 2012: 2): “The altering of fundamental attributes of a system (including value systems; regulatory, legislative, or

bureaucratic regimes; financial institutions; and technological or biological systems)”. This definition is contrasted to that of adaptation (op. cit): “The process of

adjustment to actual or expected climate and its effects, in order to moderate harm

or exploit beneficial opportunities”. So, for instance, instead of questioning the

logic of letting air mobility continue to increase due to GHG mitigation concerns, a

traditional approach to that of adapting to climate change would focus on how to

protect new airports from, e.g. sea level rise—thus enabling aviation to continue to

increase; whereas a transformative approach would combine the two ideas to ‘reduce GHG emissions’ and ‘protect society’—and therefore perhaps come up with

the transformative solution to enable society simply to demand for less travelling.

Thus, there is a danger that the traditional modus operandi for climate change

adaptation may—through what we have denoted as inter rebound effects—lead to

the continuation of those structures that initially are the causes of man-induced

climate change and, therefore, also to obstruct the need for society to enter into a

level of transformative changes (Pelling 2011; O’Brien 2012).

A static or equilibrium model of resilience in human-ecological systems dominates in disaster management, economics and engineering (Groven et al. 2012). In

contrast, dynamic resilience predominates in studies related to complexity (Meerow

and Newell 2015), e.g. ecological systems and socio-ecological systems. Such

considerations are important in considering the pre and post states of a system

following a major disturbance, such as climate change-related events or the challenge to transform into a post-carbon society, as they frame how resilience is

understood. Hall (2016) suggests that a number of important considerations emerge

from the original grounding of resilience thinking in ecological system dynamics as

a means to understanding how complex socio-ecological systems, which would

include the tourism system for example, self-organize and change over time. This

includes a need to be better aware of the ontological and epistemological dimensions of systems, i.e. how systems are conceptualized, especially with respect to

emergent properties, as more reductionist approaches may not be sufficient to

explain such properties. A further issue is that if resilience is concerned with the

dynamic relationships within a system, that is ‘adaptive renewal’, then the survival

(sometimes termed resilience) of a particular organization or member of a specific

species may not be particularly relevant. It is necessarily neither a positive nor a

negative to the system per se. Instead, what is significant is transformation and

self-organization in the system as it moves between states (Hall 2016). For

example, in commenting on the relationship between resilience and disturbance,

including in relation to post-disaster management, Hall (2016) argued that there is

no intrinsic relationship between organizational survival and improving the resilience of a community per se. Instead, at the community level, the issues for

resilience becomes more which organizations need to survive and what organizations will be born with what characteristics and values to replace those that have

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