Energy Transition and Inequality
Public support for wind energy
Towards gas-free housing
Think tank Climate Change & Inequality 2019 – 2020
Liedeke Bestebreur Kirsten Bisschops Koen van Boxel Shreya Dubey Thomas Emonds Lara Janssen Thijs Smudde Sylvain Thöni Julian van Vugt
Interdisciplinary Honours Programme for Master’s Students
The Radboud Honours Academy offers talented and motivated students at Radboud University the opportunity to take an additional, challenging study programme. Students are selected based on their ambition, potential and study results.
Participants of the Interdisciplinary Honours Programme for Master's Students are stimulated to look beyond the borders of their own field of study. They work together in interdisciplinary think tanks and conduct research on a socially-relevant issue. Their final report is addressed to an external organisation. The extra knowledge and skills that students acquire during the programme are of great value to their personal and academic development, and for their further career. The extra study load is equivalent to 15 ECs.
© Authors and Radboud Honours Academy, 2020 www.ru.nl/honoursacademy
Table of content
List of tables... 4
List of figures... 4
Introduction... 5
Research questions...7
General Theoretical Framework... 8
(In)Equality...8
Environmental and Climate Justice...9
Theoretical framework [Wind Energy]... 10
Property value loss...13
Co-ownership...14
Participatory budgeting...14
Methodology [Wind Energy]... 17
Experimental design...17
Results [Wind Energy]... 19
Compensation schemes...19
Predispositions...20
Climate change belief...20
Gender...21
Age...21
Education...21
Socio-economic status (SES)...22
Political affiliation...22
Proximity to windmills...22
Discussion [Wind Energy]... 23
Theoretical Framework [Gas-free Housing]... 26
Transition theory in the Dutch energy transition...26
Gas-free housing...27
Methodology [Gas-free Housing]... 29
Results [Gas-free Housing]... 30
Citizens...31
Government & municipalities...33
Conclusion... 34
Energy transition to gas-free housing [Case 2]...35
Concluding remarks...36
References... 38
Jurisprudence... 43
About the Authors... 44
Appendices... 45
Appendix A: Survey-flow...45
Appendix B: Qualtrics Questionairre...46
Appendix C: Frequency tables...55
Appendix D: Interview format...58
Appendix E: Overview interviews...61
Appendix F: Interview reports...63
Appendix G: Focus group format...147
Appendix H: Focus group reports...150
List of tables
Table 1: Results overview table [Citizens]...32Table 2: Results overview table [Government & Municipalities]...33
Table 3: Gender distribution across treatment groups...56
Table 4: Public support for wind farm siting...56
Table 5: Age...56
Table 6: Education...57
Table 7: Socio-economic status...57
Table 8: Political party preference...58
Table 9: Climate beliefs...58
Table 10: Interview format...61
Table 11: Overview of interviews...63
List of figures
Figure 1: Overview of the questionnaire...18Figure 2: Transition theory framework for the Dutch national energy transition...27
Figure 3: Schematic representation of recommendations I...33
Introduction
Through the application of science and novel modes of production during and after the industrial revolution, humanity has recently made a great escape from early death, mass-famines, and ubiquitous poverty (Deaton, 2013; Norberg, 2017; Ridley, 2010). In agriculture, inventions such as crop rotation, mechanization, and artificial fertilization have ensured a relative abundance of food the like of which has never existed before (Brand, 2009; DeFries, 2014). A number of extremely disheartening warnings during the late 1960s, stating that humanity would face mass-starvation within a decade (Ehrlich, 1968; Paddock & Paddock, 1967), have fortuitously never materialized. Additionally, nearly all other circumstances, both material and immaterial, have greatly improved over the last century thus ensuring that an increasingly large number of people can live in relative luxury, especially when compared to standards of living at for instance the turn of the previous century (Pinker, 2018).
All of these extraordinary improvements have however come at a steep price. The modes of production that came into being during and after the industrial revolution have put an extreme reliance on fossil-fuel based energy. This, in turn, has spawned high levels of anthropogenic carbon emissions, which have resulted in the process of global warming. The industrial revolution started approximately
250 years ago; meanwhile the mean temperature on earth has increased by 1.0 ℃ and is likely to reach
an increase by 1.5 ℃ between 2030 and 2052 (IPCC, 2018, p. 6). Such a temperature increase would
have severe consequences for a large number of lifeforms on earth, including humans themselves. Possible consequences include but are not limited to the rise of sea levels, which will threaten small islands and coastal deltas, more sporadic droughts in some places and greater precipitation in other places, and a large loss of biodiversity, both on land and in the sea (IPCC, 2018, pp. 9-10). To lessen the direct impact of these events, far-reaching efforts in climate change adaptation are called for. However, in order to ensure that temperature increases remain within a relatively safe bandwidth, in which climate change adaption would still be largely viable, there is a need to ensure that global carbon emissions quickly decrease. By signing and ratifying the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) most of the world’s states have signalled their intent to “holding the increase in the global average temperature to well below 2°C above industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels” (UNFCCC, 2015).
The Netherlands is also a signatory to the Paris Agreement (United Nations Treaty Collection, 2015) which has conferred a legal duty on the Dutch government through recent rulings in the Urgenda climate case (Hoge Raad, December 20th 2019, ECLI:NL:HR:2019:2007; Hof Den Haag, October 9th 2018, ECLI:NL:RBDHA:2015:7145; Rb. Den Haag, June 24th 2015, ECLI:NL:GHDHA:2018:2591). To meet this obligation the Dutch government has set ambitious targets for the reduction of the country’s greenhouse gas emissions. In 2030, emissions are to be reduced by 49% compared to emissions in 1990; for 2050, the goal is a 95% reduction (Rijksoverheid, 2019, p. 11). In order to
achieve these targets, a transition from energy mainly generated using fossil fuels to energy from less polluting sources will be crucial. Two important components of this transition will be the construction of additional windmills and solar panels, in order to generate a larger amount of wind and solar energy, and the switch from heating based on natural gas in Dutch houses to completely gas-free housing
Both of these components, however, will give rise to certain problems in terms of inequality between different societal groups. Within the first case, a large problem that arises from the decarbonization of the energy sector is that the spatial spread of renewable energy generators (e.g. windmills, photovoltaic panels) does not necessarily match the spatial distribution of the nation’s energy users. This is of special concern for building new windmills, which are placed in areas where they can generate most electricity or where land is relatively widely and cheaply available. However, most of the consumers of the newly generated electricity live elsewhere, often in the densely populated Randstad. Thus, inhabitants of more sparsely populated areas bear the burden of living with the windmills, while others mostly profit from access to clean energy that is very cheap at the margin. The unequal spatial distribution is reflected in the agreements that the Dutch federal government made with provincial governments to ensure that in 2020 wind energy accounts for 6000 Megawatt of annual energy production (SER, 2013, p. 68). In these agreements, the wind parks that need to be built to achieve the aforementioned capacity have been divided between the provinces. The resulting distribution is fairly unequal; notably, Flevoland is responsible for providing nearly a quarter of the total capacity while Utrecht is responsible for just over a hundredth part (RVO, 2019). The agreement seems to be set in stone, however, which is likely due to the fact that the spatial distribution of renewable energy generation is arranged in such a fashion that it is impossible to gain more energy without prejudicing any other part of the Netherlands. As such it might be more worthwhile to enquire into possible measures that can be taken in order to ensure that everyone benefits equally from the installation of additional windmills, instead of attempting to obtain a spatially equal yet less efficient distribution of the wind parks.
The transition from gas-based heating to less carbon-intensive heating methods may also potentially increase inequalities between house owners. To achieve the goals for the reduction of emissions as mentioned before (49% reduction by 2030 and 95% reduction by 2050), housing will need to be made more sustainable (Rijksoverheid, 2019, p. 11 and p. 15). The investment of transforming the heating system of a house can have social (psychologically, people like to know they are helping the environment) and financial advantages. For instance, implementing sustainable measures will eventually cause households to save money, since the operational costs of heat pumps and heat networks are significantly lower than gas, especially when renewable energy is used (Milieucentraal, 2020). Also, houses that are better isolated require less energy for heating (Milieucentraal, 2020). Unfortunately, transforming the heating system of a house is a costly affair that not everyone can
afford. This means that without the right measures, lower-income groups will not be able to make the transition, increasing inequality on different levels.
In the Netherlands, the housing sector can be divided into three categories; privately-owned houses, rented houses on the private market and rented houses from housing cooperatives. Since the responsibility for the housing transition lies with the landlords of rented houses, and with the housing cooperatives for their buildings, we decided to aim our research at the private house owners. More specifically, we aim our research at the 15% who is according to Ecorys (2019) not able to pay for the transition right now, with the current financial measures. This research project aims to find a way in which the transition towards CO2-neutral housing can be made feasible and attractive for this target group. The transition for this group is difficult in general, because house owners can decide for themselves whether they want to make the transition and when they want to do this. It is a group that still needs convincing and needs clear incentives as to why they should transition to a CO2-neutral house. 420.000 people will not be able to afford the investment of transitioning to a CO2-neutral house and are additionally not eligible for the currently existing financial measures (building-related funding) (Ecorys, 2019) or are simply unwilling to participate in the transition for other practical reasons (Elderly simply not wanting any hassle) . It is thus especially in the interest of this group of house owners that they are able to make the transition too and the energy transition will not increase inequality.
The Scientific Bureau of the Dutch Green party has asked a think tank consisting of ten master’s students from different disciplines at Radboud University to study the inequalities that can arise regarding these topics. What measures could be adopted to ensure that the energy transition in these two cases decreases inequalities in Dutch society? This background document outlines our research process, leading up to the end product; the two policy briefs. The report starts with our research questions and theoretical framework, as well as case-specific theory, methods and results sections. The first case concerns the questions regarding public support for wind energy (referred to as Wind Energy), whereas the second case concerns the fair transition towards gas-free housing (referred to as Gas-free housing). Afterwards, information on process, planning, task distribution and budget will be provided.
Research questions
The overarching question that we will address in our research is What measures can be adopted by the Dutch national government, in order to ensure that the energy transition decreases inequalities in Dutch society?
Our research will focus on the two cases outlined above, addressing the following research questions: ● What attitudinal and socio-demographic variables determine public support for wind energy
● What schemes can be identified that provide adequate compensation for damages incurred by people living near future renewable energy generators, while promoting greater equality?
● How can the transition towards gas-free in privately-owned houses be arranged, so that it additionally decreases inequality between income groups?
● What is the current situation? What existing approaches are in place or thought of? ● What problems are caused by the existing approach in terms of inequality?
● What are the benefits and drawbacks of possible measures to ensure that the transition to gas-free housing is enabled for house owners, in a manner that decreases income inequality?
General Theoretical Framework
This section provides a general framework for both cases, explaining the concepts of
(in)equality and environmental and climate justice as they are used in this paper.
(In)Equality
Political philosophers have long debated whether an unequal distribution of talents, abilities, wealth, resources, and power can be justified in any society. The doctrines of the natural right and the social contract asserted that all men, being born equal in the state of nature, ought to enjoy equality when they would be governed under civil laws (Hobbes, 2010, pp. 119-121; Locke, 1948, pp. 4-5; Rousseau, 1994, p. 55) In contemporary political philosophy, a well-known publication regarding (in)equality is John Rawls’ seminal work A Theory of Justice (1971). Rawls placed the need for equality at the heart of his essay and argued that “social and economic inequalities are to be arranged so that they are … to the greatest benefit of the least advantaged” (Rawls, 1971, p. 266). Many contemporary political philosophers have responded to Rawls’ writings in the last half century, either reinforcing, adapting or refuting his central claims. The debate around equality remains an important theme in contemporary political philosophy. Ronald Dworkin even argued that any plausible and serious political theory post-Rawls has as its ultimate value equality; if not in the direct distribution of income then in the chances that each ought to be allotted in her life (Kymlicka, 2002, pp. 4-5). While there is naturally plenty of disagreement and discussion within the field of contemporary political philosophy around the idea of equality, we believe that from the perspective of many contemporary philosophers striving for equality can be perceived as a laudable goal.
Moreover, in addition to the theoretical writings from political philosophers on the demerits of inequality, a number of publications have been made regarding the empirical negative effects that inequality can have on society. Researchers have concluded that higher inequality carries direct social costs, such as lower social mobility (Corak, 2013), lower educational scores on mathematical and linguistic subjects (Wilkinson & Picket, 2009, pp. 103-118), higher number of murders (Elgar &
Aitken, 2011), lower levels of physical health and life expectancy (Vogli, Mistry, Gnesotto & Cornia, 2005), and lower degrees of trust in society (Gustavsson & Jordahl, 2008).
Furthermore, research in behavioural economics has generally concluded that most people are instinctively averse to inequality. This is self-calculating, since if the person at the wrong end of the unequal situation is the self, one has a material interest to regret inequality. This aversion to inequality is so strong that participants to laboratory experiments are generally willing to forego additional gains themselves if this means that they can ‘destroy’ a greater part of the gains of other participants if they believe that an unequal initial distribution of gains has been reached unjustly (Beckmann, Formby, Smith & Zheng, 2002; Bosman & Winden, 2002; Fehr, 2000; Zizzo & Oswald, 2001). An even more surprising finding is that people are generally also averse to inequality when they are not the subject of such inequality themselves (Fehr & Schmidt, 1999).
Based on the philosophical and empirical findings discussed above, we believe that the furtherance of equality in society is a worthy endeavour. Our paper will mostly be focusing on either spatial (in)equality or income (in)equality. However, it should be noted that different kinds of inequality intersect. Intersectionality is the idea that, in this case climate change, can have an effect on inequality regarding gender, ethnicity and disability (Acker, 2006). Considering this, climate change policies as they are now can be regarded as an inequality regime, meaning that they reinforce practices and processes that result and maintain class, gender and racial inequalities (ibid.).
At the very minimum, in this research we will be content with policy interventions that do not deteriorate the current inequalities in the Dutch society while always striving to find those measures that further the cause of equality.
Environmental and Climate Justice
This research report largely follows the scientific and political framework of environmental justice, or climate justice more specifically. Environmental justice is concerned with the unequal impacts that environmental problems and associated policies have on different groups in society, and with possibilities to reduce such unequal impacts. Climate justice narrows the concept of environmental justice down to climate change-related inequalities specifically. Since this research focuses on (exacerbation of) inequality due to climate change mitigation measures (i.e., the transition to renewable sources of energy and gas-free housing), the climate justice framework is a good fit. Schlosberg (2004) and Walker (2012, ch. 3) distinguish three aspects of environmental justice that are now widely accepted within the field, and that can also be applied to climate justice: distributional justice, procedural justice and recognition as justice. Distributional justice is concerned with the equal distribution of the burdens of environmental problems and policies, meaning, for example, equality in the direct material and/or financial impacts of climate change on one’s direct environment or livelihood. This is the aspect of environmental justice that is most readily visible in most cases of
environmental injustice. In the case of our research, this could, for example, mean the equal or progressive division of the costs of the transition to gas-free housing over different income groups. A distributional injustice here would be a division where the finances of poorer households are affected to a greater extent than those of wealthier households (i.e., the current situation). The second commonly distinguished aspect of environmental justice is procedural justice. This signifies the equal access for different groups to decision-making regarding environmental problems and policy. A procedural injustice in our case could, for example, be a lack of consultation of those living near a future location of windmills/solar panel fields prior to the development of these energy sources. Procedural justice here might be the option for these people to have a vote in the decision. The last aspect of environmental justice is recognition as justice, meaning the recognition of and respect for cultural values and livelihoods of those affected by environmental problems and/or policy. This aspect of environmental justice is generally more visible in societies were cultural differences between groups are greater than in the Netherlands, especially in cases where there are cultural groups that have more influence on policy than other groups. However, there might be cases of recognition injustice in our research, for example, if the development of renewable energy facilities impacts cultural values of a community, for example through the development of windmills in a beloved nature area. Our research will include all three aspects of environmental injustice where applicable, with a focus on distributional and procedural justice, since these two aspects are more readily linkable to energy policy than recognition as justice.
Of course, one’s understanding of justice and injustice heavily impacts the way one would understand the different aspects of environmental justice, mainly distributional justice. For instance, if one understands an ‘equal division of burdens’ in an absolute sense, this would entail that everyone would be impacted directly to the same extent. This means something very different to a more relative understanding of equality, where everyone would be impacted to such an extent that those with larger capacity carry a larger part of the burden. In our research, we adopt a progressive understanding of justice, meaning that we understand justice and inequality in a relative sense. Justice is understood as a situation where inequality in a relative sense is minimised, meaning that a just situation is one where every group in society carries burdens of climate mitigation policy according to their capacity. Procedural justice is similarly understood as a situation where those impacted to a greater extent by climate mitigation policy have a larger say in the development of this policy. From this point the paper will be divided in Wind Energy and Gas-free Housing, until the conclusion. Meaning that there is a separate theoretical framework, methodology and results section for Wind Energy and Gas-free Housing.
Theoretical framework [Wind Energy]
Due to the inherent reliance on fossil fuels, economic production as it is currently being realized cannot be sustained if the aforementioned decrease in carbon emissions is to be achieved. Instead,
there is a need to introduce radical changes in energy generating methods. A transition away from fossil fuel-based sources of energy towards sustainable and renewable energy is seemingly called for. One such a renewable energy generator that is important in making this transition is wind energy, which can be captivated by using windmills to gain electricity. The technological use of wind energy is often strongly supported, since wind energy can be classified as a low carbon technology (Nugent & Sovacool, 2014). Moreover, wind energy is a relatively safe technology (Sovacool et al, 2016; Sovacool, Kryman & Laine, 2015). Although it does generate a large number of incidents it represents only 0.07% of the fatalities and 0.3% of property damages incurred by renewable energy technologies (Sovacool et al., 2016, p. 3959). While the number of fatalities for wind energy are quite high when comparing fatalities per terawatt hours (TWh) energy produced, at 0.35 per TWh, they pale in
comparison to fatalities per TWh of fossil fuel technologies.1 Finally, the use of wind energy does not
produce any wastage, as is the case when using nuclear energy. As such, non-nuclear sources of renewable energy are often seen as preferable ceteris paribus due to not generating “public concern about storage of nuclear waste, the potential for catastrophic accident or terrorist attack, and the diversion of fissionable material for weapons production” (Markandya & Wilkinson, 2007, p. 979). The technical advantages of wind energy are thus strongly established and generally not debated as such. This begs the question as to why wind farms have not been universally adopted already as one of the main sources of clean, safe, and cheap energy. This is likely due to the fact that energy generators are more than the mere application of technology devoid of any interaction with society. Instead, the adoption of renewable energy generators is a socio-technical process, “a term that encompasses the technological, social, political, regulatory, and cultural aspects of electricity supply and use” (Sovacool, 2009, p. 4501). Existing configurations of the socio-technical system in a state can lock in the use of certain technologies or impede the adoption of new technologies. For instance, while fossil fuel-based energy generators produce enormous amounts of damages in the United States, even when excluding damages arising from carbon emissions, these damages happen to commonly owned environments (e.g. rivers, lakes, the atmosphere) and are thus not included in the price of generated electricity. Were these damages to be internalized into the price and thus paid for, the fair prices for each KWh of fossil fuel-based energy would skyrocket. Meanwhile, the prices of renewable energy generators, specifically those of wind power, would scarcely increase since its external costs are negligible (Sovacool, 2009, p. 4505). Since the external costs are however never internalized under the current socio-technical system, the competition between fossil fuel-based energy and renewable energy is inherently skewed; resulting in the situation that the former is still more widely used than the latter (Sovacool, 2009, pp. 4504-4506).
1
For instance, the generation of energy through the use of lignite, coal, oil, biomass, and gas incur 32.72, 24.62, 18.43, 4.63, and 2.82 fatalities per TWh respectively (Markandya & Wilkinson, 2007, p. 981). It should be noted however that the use of fossil fuel technologies mainly incurs fatalities through air pollution, and not so much in energy generation.Another important source of socio-technical impediments to the adoption of wind energy are behavioural impediments. Most people have come to rely so heavily on the instant, cheap and easy availability of electricity at home, at work or even while travelling, that they are entirely divorced from knowing how electricity is generated in the first place. In earlier times, this was incontrovertibly not the case; in the absence of high-quality power grids that supplied power to every home in the state, decentralised forms of energy generation were necessary. As such, people used to generate energy themselves at home, through for instance the burning of wood, oil or coal. A centralized network of energy production and distribution is indubitably preferred to this situation but did result in moving the physical production of energy outside the direct sight and consciousness of most people. This is due to the fact that power plants are often spatially located in sparsely inhabited areas, away from major urban centres. In most contemporary societies people thus do not see the physical means necessary to produce electricity and therefore increasingly come to see it as an abstract, abundant and sometimes even infinite source of energy. When these production processes are however moved back into the direct spatial proximity of urban centres, for instance by building wind farms close to towns and cities, the result is that people do not fully appreciate that these structures are necessary in order to have the direct and instant access to electricity that is so often taken for granted. This problem occurs mostly with renewable energy generators, and especially with windmills, since nearly all of their externalities (e.g. horizon pollution, sound pollution) are located in the very spatial area in which they are constructed (Sovacool, 2009, p. 4510). Nor is it possible to locate these generators to sparsely inhabited areas, since they inherently need more land than fossil-fuel based sources of energy do. Especially in the populous areas of Western Europe, constructing wind farms will nearly always happen next to some urban areas.
In effect there is thus a marked tension between the technical merits of windfarms on the one hand and the societal impediments on the other. This leads to the interesting situation in which people generally are supportive of wind energy in the abstract (Thayer & Freeman, 1987; Wolsink, 1988; Wolsink, 1989; Söderholm & Pettersson, 2007; Krohn & Damborg, 1999) but see wind farms sited near their own residential areas as obnoxious (Ladenburg & Dalhgaard, 2012). People generally object to local siting of wind farms due to the visual interference (Wolsink, 2007; Tsoutsos et al., 2009) and the auditory pollution (Pierpont, 2009, p. 107; Gippe, 1998).
For instance, when wind farms are subsequently built next to urban centres, this leads to incomprehension and sometimes to resentment. While it may be easy to deride these responses as being logically inconsistent and therefore irrational, they should be taken highly seriously as they form part of the socio-technological impediments to the widespread adoption of renewable energy. Public support for the construction of renewable energy generators is of the utmost importance, even more since the grievances felt by local residents are to a certain degree valid. Reasonably assuming that renewable energy generators cannot be built simultaneously next to all urban centres in the state or
that it is not necessary to do so altogether, it follows that there are some people that have to live next to the wind farms, having to experience number of inconveniences due to it, while some others can continue to access clean, cheap, and safe energy without experiencing any of the disadvantages associated with its generation.
Given then that there is at least some merit in preferring not to live next to newly built renewable energy generators from a perspective of equity, and that, in any event, sufficient public support for the constructions of these generators is necessary to remove an important socio-technological impediment, it is interesting to assess how this public support can be increased. A logical and often suggested solution is to provide those affected by the building of the renewable generators some form of compensation. In the remainder of this paper, we have further researched this possibility by identifying a number of compensation schemes, and testing the effects thereof through a between-subjects experimental questionnaire.
Property value loss
There is evidence that close proximity to disamenities could decrease housing prices in an area. Such disamenities that negatively influence housing prices include cell phone base stations (Brandt & Maennig, 2012), landfills (Hite, Chern, Hitzhusen & Randall, 2001), industrial sites (Havlicek, Richardson & Davies, 1971; De Vor & De Groot, 2011), hazardous waste site (Kohlhase, 1991;
Michaels & Smith, 1990) and nuclear power plants (Gamble & Downing, 1981).2 Recently, a number
of authors have extended the work on disamenities to include the siting of wind farms. While windmills are often not seen as a disamenity as such, due to the benefits that they confer through generating renewable energy, they might nevertheless depress housing prices in the close physical proximity. While a sizeable number of authors was unable to find a statistically significant impact of windmill construction on housing prices (Atkinson-Palombo & Hoen, 2015; Hoen et al., 2009, 2011, 2013; Lang et al., 2014; Sims & Dent, 2007, 2008) more recent work hints at a relatively strong negative effect (Gibbons, 2015; Heintzelman & Tuttle, 2012; Sunak & Madlener, 2016, 2017). Sunak & Madlener (2016, pp. 80-81) criticize the aforementioned earlier authors for simply proxying the visual impact of a windmill by its distance to the property under investigation. Instead they themselves offer a more sophisticated technique to measure the visual impact of the wind farms, in order to better
estimate its effect on housing and land prices.3 It would thus seem reasonable to assume that siting
wind farms would negatively affect housing prices, and that it would at least be difficult to guarantee beyond any doubt that living next to a newly constructed windmill park would not have any effect on housing prices. As such, even though there exists the possibility that housing prices will not be automatically depressed due to nearby wind farm siting, the fear that such an effect would materialize
2
For an extensive literature overview on disamenities and residential property prices see Farber (1998).3
Land prices were used as proxies for housing prices by Sunak and Madlener (2016) due to the unavailability of reliable data on housing prices.seems to provide a reasonable reason, from the perspective of nearby residents, for regarding this aspect of wind farm siting as problematic.
If wind farms were indeed to have a depressing effect on housing prices in their close proximity, then it would seem fair to offer nearby residents a form of compensation for this loss. An intuitive solution to provide such a compensation is the property value-loss scheme, which directly reimburses nearby residents the monetary damages caused by the construction of the wind farm. The amount of damages compensated is based on a number of environmental factors, including for instance the visual interference of the wind farm (Jørgensen, Anker & Lassen, 2020; Rønne, 2016, p. 189; Olsen & Anker, 2014). The scheme has been applied before in Denmark, where a Valuation Authority was tasked with assessing the claims brought forwards by local residents. The awarded compensation could be sizable, ranging between 2% and 40% of the property value (Rønne, 2016, p. 189). Since the property value-loss scheme aims to compensate residents for personal damages, it would be expected that the existence of such a scheme would positively affect public support for the wind farm vis à vis a situation in which the scheme would be absent, by addressing an important cause for dissent. As such the first hypothesis can be offered:
H1: Compensating residents living in the physical proximity of a wind farm for incurred damages,
through the property value-loss scheme, will positively affect their public support for siting the wind farm.
Co-ownership
Offering the possibility of sharing more directly in the benefits that the wind farm confers is another method of providing redress to those affected by the construction of wind farms. Specifically, this could be achieved by setting up a co-ownership scheme as means of compensating nearby residents (instead of providing outright monetary compensation). Under this scheme, all affected residents would be offered the possibility to buy shares in the wind farm at cost price instead of at the market price. The latter would necessarily include a (hefty) mark-up for the contractor, which the nearby resident would hence not need to pay in order to receive a stake in the wind farm. This scheme averts the possibility of large companies or wealthy individuals building wind farms anywhere where they deem it profitable, thus making considerable profits, without experiencing the (local) disadvantages that the siting of the wind farm generates. Instead, nearby residents, that would otherwise be left without indemnity for the siting of the wind farm, would be able to share in its fruits, and could therefore be expected to cope better with the negative effects. As such the second hypothesis can be offered:
H2: Offering residents living in the physical proximity of a wind farm the possibility to buy
Participatory budgeting
A third method for compensating residents living near wind farms is through offering community benefits. Until now we have based the rationale for the aforementioned property value-loss and co-ownership schemes on the tacit assumption that damages arising from the construction of wind farms are commensurable; that is for instance to assume that degradation of the view or nuisance due to noise, can be offset in full by offering monetary indemnities.
These compensation schemes rely on a strong belief in Coasian reasoning. Coase’s theorem rests on the assumption that any disagreements surrounding property rights and economic activities can be settled through extensive negotiation resulting in mutual agreement. For example, people living next to a particularly noisy airport might negotiate with the owners of said airport to find an agreeable solution, either through changing the economic activities conducted (e.g. flying less or muffling the sound of the airplanes) or through compensating the disadvantaged party for their problems. Thus, in the Coasian framework, any damages arising from economic externalities might be effectively internalized by using monetary compensation. This view has enjoyed strong support in the past (Burton & Pushchak, 1983, 1984; Clinch, O’Neill & Russell, 2008; O’Hare 1977; Randall, 1983). Specifically, Randall (1983) offers the prospect of holding an auction on the siting of an obnoxious waste facility, in which “the low bidding community would become the fully compensated and, therefore, happy-host of an invading force which would otherwise be resented” (Randall, 1983 , pp. 145-146).
This Coasian line of reasoning has been extensively questioned (Cowell, Bristow, Munday, 2011, pp. 541-545). Negotiations surrounding the siting of wind farms may work relatively well in a situation in which there is an even-handed negotiation between a contractor and nearby residents, in which the latter have the genuine possibility to veto the construction of the wind farm. However, post hoc compensation necessarily leaves the possibility of not satisfying the residents at all since they were not offered the possibility of rejecting the siting. This is the difference between using property rules or liability rules, of which the latter is not based on universal a priori acceptance of the construction in question (Bromley, 1989, p. 210). Compensation might then merely be used as a symbolic reparation payment, in which the real damages are not paid for at all, due to either resource constraints or the inherent impossibility of repairing irreplaceable losses (Goodin, 1989). It is then not so much economic compensation as well as (partial) control, and a potential veto over construction, that fosters the social acceptance of wind farm construction. This notion is confirmed by Toke (2002) who found that locally managed institutions in Denmark produced far better results in fostering social acceptance to wind energy vis à vis the situation in the United Kingdom, in which large remote companies entered bidding processes in order to determine who would be able to build where.
It would thus seem that the need to provide compensation would be wholly superseded by the need to provide meaningful participation in the negotiation processes before wind farms are sited anywhere. Such a stance is admirable and would under ideal circumstances necessarily be adopted. However, there may be a national or international problem that can legitimately override the preferences of local inhabitants towards either constructing or foregoing the construction on wind farms in their proximity. It might be argued that the need to transition towards renewable energy generators in the near future, so as to drastically curb carbon emissions, constitutes such an overriding need and therefore justifies building wind farms where they would otherwise, under property rules, not be constructed. In this scenario, it would simply be unworkable to grant every local community a potential veto over wind farm siting, thus in a sense imposing it top-down. Still, it would seem preferable to have a method of post hoc compensation that does more than provide a symbolic gratification.
If it would not be possible to concern local residents on the construction and localisation of wind farms, they might instead be actively engaged in the process of deciding how to award compensation to the community at large, instead of merely being given financial compensation as a form of lip service to their damages. Such a process might be set up through the use of participatory budgeting. Participatory budgeting is a form of democratic deliberation that seeks to directly extend democratic oversight to the creation of public budgets and hence the allocation of public funds. The budgeting technique is typically adopted at a low-level governance structure (e.g. a municipality) in which the entirety or a part of the budget is made available to public oversight and thus to ultimate public discretion. Citizens involvement is an important aspect of new collaborative approaches to public administration (one of the main advantages of public budgeting is allowing for the inclusion of disenfranchised residents of the governance structure (Weber, 2015, p. 50). Moreover, the process might help in educating participants about “conditions in their neighbourhoods, the budgeting process, and the services that the government can and cannot provide” (ibid.). As such, it allows for greater transparency and understanding in the budgeting process, which might provoke greater support for the process as such. Others believe that “participatory budgeting rendered possible a more efficient government, a reallocation of resources in favour of the most disadvantaged and a democratization of politics” (Sintomer, Herzberg & Rocke, 2008, p. 166)
Participatory budgeting could thus be used to decide how compensatory benefits to a community in general might be allocated. In providing residents with the possibility to be closely involved in the distribution of the compensation, they are more involved and invested in the project, compared to the situation in which they would simply be offered a lump-sum for incurred damages or partial ownership in the wind farm. While this method of compensation does not foresee the possibility of inviting local residents in the decision-making process on the wind farm as such, on the basis of property rules, it does arguably provide more than the bare minimum symbolic compensation that would be afforded to them according to the logic of liability rules. Thus, the advantage of using
participatory budgeting to dispense community benefits is double-edged, allowing both for the compensation of damages incurred through tangible benefits in the local community, and allowing the resident itself the possibility of co-decision-making on the distribution of compensation. As such the third hypothesis can be offered:
H3: Offering residents living in the physical proximity of a windmill park the possibility of becoming
involved in the distribution of community benefits, through a process of participatory budgeting, will positively affect their public support for the windmill park.
Methodology [Wind Energy]
In order to assess the research question, a between-subject experimental survey was used. In this, different participants were presented with one randomly assigned treatment condition. In each treatment they can either be informed on one of the three aforementioned compensation schemes or no compensation scheme at all. The latter group of participants formed the control group, in which the base support and perceived fairness for the construction of a wind farm were assessed. We distinguished between house owners and renters. Both groups were offered the same compensation schemes, save for the co-ownership scheme for the renters. Moreover, the wordings of the scenarios and treatments were adjusted to suit the situation from the perspective of either a house owner or a renter.
By virtue of presenting different treatments to different groups of participants, and only differing the questionnaires in this regard, it becomes possible to attribute any differences in support for the wind farms or perceived fairness of the construction to the different compensation scheme presented. The use of this experimental design thus has the advantage of allowing relative certainty with regard to the flow of causality, as opposed to other methods of quantitative analysis.
The data collection itself proceeded through the use of the online programme Qualtrics, in which participants could easily complete the questionnaire on either a computer or a mobile device. The
questionnaire was distributed to 758 different respondents, through the research agency Panelinzicht.4
The use of a research agency for distributing the questionnaire offered a dual advantage. Firstly, the research agency could quickly deliver a relatively large number of respondents, which allowed for having seven different treatments, with a sizable number of respondents in each treatment. This relatively large number of respondents in each treatment will subsequently allow for the use of parametric tests in the statistical analysis. Secondly, the research agency could ensure through it’s respondent selection that the sample only included adult Dutch residents. This would subsequently allow for asking demographic questions that were specific to the Netherlands, such as for instance the preference for a political party. As such, the possibility of having a systematic bias in the data, due to
for instance presenting the survey only to like-minded people or people in the same demographic group (e.g. students) is to some extent lessened but cannot necessarily be wholly excluded. The necessary funding to allow the use of a research company was provided by the Think Tank of the Dutch Green party (Wetenschappelijk Bureau GroenLinks; WBGL).
Experimental design
The survey itself was structured as follows. Participants were first shown an informed consent screen in which they were informed of the topic and aims of the research, as well as their rights as respondents. Specifically, this information included that all data collected would be gathered confidentially and anonymously, and would solely be used for this research project. After this, they were shown a fictional scenario, which corresponded to either being a house owner or renter near a prospective wind farm site. Subsequently, participants were asked to evaluate a number of statements on wind farms in general. Following this scenario and the statements, all respondents were randomly allocated to one, and only one, of the different treatments in which they were confronted with either the property value-loss scheme (for both house owners and renters), the co-ownership scheme (only for house owners), the participatory budgeting scheme (for both house owners and renters) or no compensation scheme at all. Subsequently, all respondents were asked to indicate on a seven-point Likert scale how strongly they would support the siting of the wind farm, and how fair they judged the received compensation (if any) to be. Finally, they were asked to provide information on a set of demographic questions, such as gender, age, occupation, education level, political orientation, and beliefs about climate change. These demographics served as control variables to exclude the possibility that any differences between different treatment groups are due to these demographics instead of the treatments. An overview of the experimental design is presented in Figure 1. An overview of the questionnaire’s flow is presented in Appendix A, and the entire questionnaire is shown is reprinted in Appendix B.
Figure 1: Overview of the questionnaire
In order to safeguard the internal validity of our findings, we included a factual manipulation check (FMC) in the survey. Immediately after the outcome measurement, respondents were asked to recognize the type of compensation they had been offered. The FMC is stricter than the instructional manipulation check (IMC) which merely checks for attention by asking respondents to perform a certain action in a lengthy block of text. The passage rate for our FMC was 63.58%, which is comparable to passage rates in studies with a similar experimental design (Kane & Barabas, 2019). As such, especially given the strict nature of the FMC, the passage rate seemed adequate. In order to best analyze our data, we excluded all respondents who failed to pass the FMC, which reduced the final sample from 758 to 482 respondents.
Results [Wind Energy]
Compensation schemesAll analyses were conducted using two subsets of the data allowing us to compare each compensation scheme to the appropriate control group. More specifically, one dataset was created with only the data from the homeowner scenarios: Direct compensation for house owners (n = 71), Co-ownership shares (n = 69), Participatory budgeting for house owners (n = 60) and the no compensation control group for house owners (n = 76) for a total of 276 participants. The other dataset was created using the data from the renter scenarios: Direct compensation for renters (n = 65), Participatory budgeting for renters (n = 73) and the no compensation control group for renters (n = 69) for a total of 207 participants. An overview of the different treatment groups is presented in Table 3.
Within the subset of the data containing only the homeowner scenarios, a one-way between-subjects ANOVA was conducted to compare the three compensation scenarios (direct, co-ownership shares, participatory budgeting) to the no compensation control group on the amount of public support for the construction of the windmill park. However, there was no effect of compensation scenarios on the
amount of public support (p = .360) and none of the compensation schemes significantly differed from the control group on the amount of public support (p = .335, p = .307 and p = .588 respectively). Furthermore, there was no significant effect of compensation scenarios on the extent to which the siting of the windmill park was perceived to be fair (p = .471).
Within the subset of the data containing only the renter scenarios, a one-way between-subjects ANOVA was conducted to compare the two compensation scenarios (direct, participatory budgeting) to the no compensation control group on the amount of public support for the construction of the windmill park. There was a marginally significant effect of compensation scenarios on the amount of public support, F (2,204) = 2.901, p = .057). Upon closer inspection, pairwise comparisons of the group means showed that participants reported more public support for the siting of the windmill park when they received direct compensation (M = 3.57, SD = 1.65) compared to receiving no
compensation (M = 4.17, SD = 1.59)5, t (204) = -2.06, p = .041.). There was no significant difference
in public support between the participatory budgeting for renters scenario and the no compensation control group (p = .950).
Since public support and perceived fairness were found to be highly positively correlated (r = .79, p < .001), we found a similar pattern for the relationship between the compensation scenarios and perceived fairness. There was a marginally significant effect of compensation scenarios on how fair the siting of the windmill park was perceived to be, F (2,204) = 2.789, p = .064). Pairwise comparisons of the group means showed that participants reported higher levels of perceived fairness when they received direct compensation (M = 3.72, SD = 1.63) compared to receiving no compensation (M = 4.29, SD = 1.42), t (204) = -2.10, p = .037. There was no significant difference in perceived fairness between the participatory budgeting for renters scenario and the no compensation control group (p = .910).
Predispositions
A multiple linear regression analysis was performed to examine whether the four distinct predispositions towards windmills (i.e. (1) belief that windmills degrade the visual landscape, (2) expected irritation from hearing the nearby windmills, (3) belief in the necessity of windmills to a successful transition towards renewable sources of energy, and (4) the amount of negative press about windmills that was seen) predicted public support for the siting of the windmill park. We removed participants who answered that they did not know an answer on any of the four statements, leaving a total sample of 428 respondents. This analysis explained 49.4% of the variance on public support. Public support decreased when participants more strongly believed the placement of the windmill park would degrade the landscape (b = 0.436, p < .001) and more strongly expected it would cause sound
irritation (b = 0.400, p < .001). Public support increased when participants more strongly believed windmills are a necessity in the transition towards renewable sources of energy (b = -0.326, p < .001). A second multiple linear regression analysis was performed to examine the effect of the four predispositions on perceived fairness of the siting of the windmill park. This analysis explained 37.5% of the variance on perceived fairness. Perceived fairness of the siting of the windmill park decreased when participants more strongly believed the placement of the windmill park would degrade the landscape (b = 0.332, p < .001), more strongly expected it would cause sound irritation (b = 0.276, p < .001 and when participants had seen more negative press about windmills (b = 0.123, p = .031). Perceived fairness increased when participants more strongly believed windmills are a necessity in the transition towards renewable sources of energy (b = -0.253, p < .001).
Climate change belief
A linear regression analysis was performed to examine whether climate belief predicted public support for the siting of the windmill park. This analysis explained 3.6% of the variance on public support. A higher level of belief in climate change increased the amount of public support for the windmill park (b = -0.114, p < .001).
A second linear regression analysis was performed to examine the effect of climate belief on perceived fairness of the siting of the windmill park. This analysis explained 4.5% of the variance on perceived fairness. A higher level of belief in climate change increased the amount of perceived fairness (b = -0.439, p < .001).
Gender
A one-way between-subjects ANOVA was conducted to compare male and female participants on the amount of public support for the construction of the windmill park. The gender distribution of the sample is shown in Table 3. We removed a single participant from this analysis that had not indicated their gender, leaving a sample of 481. There was no significant effect of gender on the amount of public support, F(1,479) = 0.85, p = .36. There was also no significant effect of gender on perceived fairness, F(1,479) = 0.42, p = .515.
Age
Age was measured on a scale consisting of eight different age ranges (i.e. 18-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75-84 and 85+). The distribution of this variable is presented in Table 5. A one-way between-subjects ANOVA was conducted to compare the eight age ranges on the amount of public support for the construction of the windmill park. This analysis and all those that follow from this point were conducted with the full sample of 482 respondents (i.e. the dataset containing all of the scenarios for both the renters and the house owners). There was a marginally significant effect of age group on the amount of public support, F(6,475) = 1.89, p = .081. Pairwise comparisons with sum to
zero contrasts (with the 85+ age group coded as -1) revealed that the youngest age group (i.e. 18-24) (M = 3.29, SD = 1.58) reported significantly more public support than average (M = 3.92, SD = 1.82), t(475) = -2.56, p = .011; while participants in the 55-64 age range (M = 4.44, SD = 1.58) reported significantly less public support than average, t(475) = 2.44, p = .015.
Again, a similar pattern was found for the relationship between age and perceived fairness. There was a marginally significant effect of age group on perceived fairness, F(6,475) = 2.00, p = .064. Pairwise comparisons with sum to zero contrasts (with the 85+ age group coded as -1) revealed that the youngest age group (i.e. 18-24) (M = 3.43, SD = 1.31) perceived the siting of the windmill park to be more fair than average (M = 3.99, SD = 1.62), t(475) = -2.45, p = .015; while participants in the 55-64 age range (M = 4.42, SD = 1.55) perceived the siting of the windmill park to be less fair than average, t(475) = 2.21, p = .028.
Education
A one-way between-subjects ANOVA was conducted to examine the effect of different educational backgrounds on the amount of public support for the construction of the windmill park. The distribution of education level across the sample is shown in Table 6. There was no significant effect of education on the amount of public support, F(6,475) = 1.39, p = .215.
There was, however, a significant effect of education on the perceived fairness of the siting of the windmill park, F(6,475) = 2.62, p = .017. Pairwise comparisons with sum to zero contrasts (with primary school education coded as -1) revealed that the siting of the windmill park was perceived to be more fair than average (M = 3.93, SD = 3.42) when participants had finished or were currently enrolled in a PhD (M = 3.00, SD = 1.50), t(475) = -2.05, p = .041. It should however be noted that there were only a total of 9 participants in the sample that had the education level of PhD, which is why we cannot be confident about this result.
Socio-economic status (SES)
A one-way between subjects ANOVA was conducted to compare different income groups on the amount of public support for the construction of the windmill park. The distribution of Socio-Economic status in the sample is shown in Table 7. We removed participants from this analysis that indicated they did not prefer to answer the question (n = 66) or did not know the height of their annual income (n = 25), leaving a sample of 391. There was no significant effect of socio-economic status on the amount of public support, F(5,385) = 0.93, p = .46. There was also no significant effect of socio-economic status on perceived fairness, F(5,385) = 0.26, p = .937.
Political affiliation
A one-way between-subjects ANOVA was conducted to compare voters of different political parties on the amount of public support for the construction of the windmill park. An overview of political
party orientation is shown in Table 8. There was a significant effect of voting for a certain political party on the amount of public support, F(14,467) = 3.79, p < .001. Pairwise comparisons with sum to zero contrasts (with the group that answered: “Prefer not to say”, coded as -1) revealed that there was significantly more public support than average (M = 4.03, SD = 1.94) when participants would vote for D66 (M = 3.33, SD = 1.63), t(467) = -2.48, p =.014, GroenLinks (M = 3.03, SD = 1.60), t(467) = -3.66, p <.001 or Partij van de Arbeid (M = 3.49, SD = 1.45), t(467) = -2.16, p = .031. There was significantly less public support than average when participants would vote for Forum voor Democratie (M = 5.24, SD = 1.62), t(467) = 4.38, p <.001.
Again, a similar pattern was found for the relationship between political affiliation and perceived fairness. There was a significant effect of political affiliation on perceived fairness, F(14,467) = 3.03, p < .001. Pairwise comparisons with sum to zero contrasts (with the group that answered: “Prefer not to say”, coded as -1) revealed that the siting of the windmill park was perceived to be more fair than average (M = 4.05, SD = 1.75) when participants voted for D66 (M = 3.55, SD = 1.42), t(467) = -2.00, p = .047 or for GroenLinks (M = 3.31, SD = 1.51), t(467) = -2.99, p = .002. The siting of the windmill park was perceived to be less fair than average when participants would vote for Forum voor Democratie (M = 5.09, SD = 1.46), t(467) = 4.17, p <.001.
Proximity to windmills
An independent-samples t-test was conducted to compare the amount of public support for the siting of the windmill park between participants who reported living near a windmill (i.e. within two kilometers) and those who did not. We removed participants from this analysis that answered they did not know whether they lived near a windmill or not, leaving a sample of 463 (i.e. of which 73 reported to live near a windmill and 390 reported they did not). There was no significant difference in the amount of public support between those who lived near a windmill and those who did not (p = .087). There was also no significant difference in the amount of perceived fairness between those who lived near a windmill and those who did not (p = .812).
Discussion [Wind Energy]
Wind energy will play a major role in the Netherlands’ strive for decreased GHG emission in the near future. For this, it is important to harness the potential of windmill parks that can be installed both on-shore and off-on-shore. As studies in the literature review show, despite overall support for the need to transition to renewable energy, local citizens refuse to allow for land-based wind energy projects to be situated in their neighborhoods.
The aim of this study was to explore whether providing certain types of compensation can increase public support and perceived fairness for installation of windmill parks in the Netherlands. Based on the literature review, we decided to specifically compare house owners and house renters are likely to support windmill parks when offered direct monetary transfers, participatory budgeting for improving
local public services, and co-ownership of the windmill park (only house-owners). We also studied which of these compensation schemes were perceived as the fairest, if any.
The current study found that compensation schemes may not work to increase public support in all cases. The results indicate that only one compensation scenario led to increased public support when compared with a neutral control group: direct monetary transfer increased public support for windmill park among house renters. Overall, participants did not perceive any of the compensation scenarios significantly fairer as compared to control scenarios where no compensation was offered. We found that renters perceived direct monetary transfer as being fairer than no compensation, but same was not true for renters who were offered participatory budgeting. Earlier studies have found that monetary compensation is perceived as unfair when it fails to take into account the non-monetary burden of wind energy projects, thereby increasing resistance among local residents (Cass & Devine-Wright, 2010).
This finding has two key implications for ensuring social acceptance of transition to wind energy in the Netherlands. First, it cautions against adopting a one solutions fits all approach in providing compensation to secure public support. It is possible that the compensation type and amount may be perceived differently by house owners and house renters, thereby leading to different reactions. Second, monetary compensation itself may not be sufficient to increase public support for windmill parks. As such, it could be that house owners did not respond positively to any of the compensation schemes because the amount offered was lower than expected, or because monetary compensation by itself could be considered as a bribe to secure support, as noted in earlier studies (Burtan & Pushchak, 1983; Walker, Wiersma, & Bailey, 2014). Indeed, previous studies have demonstrated that frustrations about wind energy projects also involve dissatisfaction with the overall decision-making process relating to planning and siting as well as implementation of wind-energy projects (Ellis et al., 2007; Pepermans & Loots, 2013; Aitken et al., 2016; Bergek, 2010).
Another important finding in this study was that individuals’ pre-existing attitudes towards windmills affected both public support and perceived fairness towards windmills to a large extent. We found that public support was lower among those who expected more visual and auditory annoyance, as well as believed that windmills were not necessary for the energy transition towards renewable sources. Furthermore, people perceived the construction of windmill parks in their neighbourhood as being less fair when they expected greater visual and auditory annoyance, had seen negative press about windmills, and believed that windmills were not necessary for the energy transition towards renewable sources. This finding is in line with research conducted across the European Union and UK that highlights the role of visual impact of windmills as a major driver for resistance to their siting (Maffei et al., 2013; Molnarova et al., 2012; Jobert et al., 2007).
Our findings for the effect of noise on public support are also supported by previous research (Maffei et al., 2013; van Kamp & van den Berg, 2018). It is also clear that the media and press may play a role
in shaping people’s attitudes towards wind-energy projects, and there is some concern that the popular media narrative could well be contradictory to scientific literature (Knopper & Olsen, 2011). Additional research can also tap into the role (social) media plays in shaping people’s attitudes to renewable energy in general, as well as their expectation of discomforts due to windmill siting in their neighborhoods.
Several studies have explored the link between acceptance of renewable energies and socio-demographic status such as age, gender, and social status (Devine-Wright, 2007; Hobman & Ashworth, 2013). We also found that age was a significant predictor for both public support and perceived fairness. Specifically, we found that youngest participants (18-24 years) expressed greater public support and perceived the wind farm siting to be more fair. On the contrary, participants aged between 55-64 years showed less public support as well as perceived wind farm siting to be less fair. However, education, socio-economic status, gender did not predict public support.
Political affiliation also predicted public support, with those indicating that they will vote for D66, , Greenleft party, or PvdA showing greater public support for windmills compared with those intending to vote for Forum for Democracy showing lesser public support. This is in line with previous research suggesting that political party preferences are correlated with the acceptance of alternative or low-carbon sources of energy (Devine-Wright, 2007; Karlstrøm & Ryghaug, 2014).
Contrary to expectations, living closer to a windmill park also did not affect public support and perceived fairness. Our results were similar to those reported by Jones & Eiser (2010), who also found that opposition to windmill was a result of anticipated visibility concerns rather than proximity to a windmill park.
The present study adds important insights in the Netherlands’ transition towards wind-energy projects. In this research, we have presented an overview of the factors that affect public support towards and perceived fairness of the construction of windmill parks among Dutch residents. Additionally, we have provided a preliminary understanding of the effect of compensation schemes in garnering public support, and have concluded that financial compensation in form of direct monetary transfer, participatory budgeting, and even co-ownership is not a stand-alone solution to the local community’s resistance to wind-energy projects. Finally, we have also been able to demonstrate that perceived fairness compensation might vary depending on residents’ living situation.
Our study is not without some limitations. Firstly, a relatively large number of responses had to be discarded, due to incorrect factual manipulation checks. Secondly, due to a large exclusion rate, our sample was restricted to a relatively smaller sample. Finally, we used a hypothetical scenario in which we asked participants to imagine that they were either house owners or house renters. While the use of such vignettes is common in academic research, more robust results can be obtained by including actual house owners and house renters in future studies.
Theoretical Framework [Gas-free Housing]
This section will provide an explanation of two case-specific concepts for case 2, these being transition theory in the Dutch energy transition, and gas-free housing. Afterwards, this section concludes with an explanation of the methods that will be applied in case 2.
Transition theory in the Dutch energy transition
To analyse the position of relevant stakeholders, the actions to be undertaken, and their proposed solutions, we will employ a Transition theory framework. As Gaziulusoy & Öztekin (2019) argue, sustainability transition literature has grown significantly over the last decades and has been integrated with numerous other theories, causing a large divergence and broad outlook. Hence, we believe this corroborates our interdisciplinary research and of course fits in with the matter of energy transition. Loorbach (2010) elaborates on a Transition theory framework for the Dutch national energy transition in which complexity, management, and implementation play an important role.
Firstly, with regards to complexity, the term ‘governance’ plays a key role, where all societal actors exert influence and thereby social change (Loorbach, 2010). Hence, it makes sense to carefully identify our actors, their actions, interests, and responsibilities (Mees, 2014). A list can be found in the methods section, where one may see that house owners, energy corporations, social movement groups, municipalities, and more can all play roles and needs to be analysed carefully.
Secondly, there are four different types of governance activities important in societal transitions: strategic, tactical, operational, and reflexive (Loorbach, 2010). These four different types of governance activities can be captured in a multi-level process model, as depicted in figure 1. Strategic activities focus on culture and long term outcomes. Tactical activities focus on dominant structures of a societal system and mid-term outcomes. Operational activities are activities and experiments that focus on short term outcomes. Finally, reflexive activities focus on monitoring, evaluating policies and learning, and are therefore related to the former three.
With regards to management, one should also make sure that the planning is successfully implemented. Thus, this reflexive dimension is added on top of the three mentioned management styles. Klein, Mäntysalo, & Juhola (2016) elaborate on the importance of legitimacy through means of planning theory, with attempts to find a clear rationale for climate change adaptation, or in our case, energy transition. Hence, implementation will require careful planning and examination of the previously mentioned framework.
Tigchelaar et al. (2019) argue that awareness and creating demand for energy transition are essential; an operational management issue. Yet, Tigchelaar et al. (2019) also focus on having all housing gas-free in 2050; which can be related to tactical and strategic management approaches. Ernst et al. (2016) describe the framework concerning these approaches quite extensively. Hence, it will not be discussed
