The effects of ecolabels on environmentally-and health-friendly cars: an online survey and two experimental studies

Abstract

Purpose
Given the increasing importance of political decision-making to reduce emission targets, the main purpose of the current paper is to identify and test the considerations that would nudge consumers towards an environmentally and health-friendly motor vehicle.

Methods
An online survey was conducted to assess public responses and the role of public authorities to a voluntary emission standard for passenger cars. In addition, two online experiments were conducted to test incentives in the design of ecolabels (e.g. price, safety, performance) for optimization. A random sample of 6400 individuals was drawn from eight countries: Germany, Ireland, Italy, the Netherlands, Spain, UK, Czech Republic and Lithuania. An online survey was conducted among 3200 respondents, 400 in each of the 8 countries, and 2 online experiments with 3200 subjects, 400 in each of the 8 countries, allowing for 200 respondents for each experiment in each country.

Results and discussion
The survey shows that Europeans are aware of the health and environmental impact of cars. The findings also confirm the gap between self-reported attitudes/intentions and actual behaviours. In influencing car purchase decisions, health and environmental concerns are less important than other attributes such as price, safety and performance. The experiments show that all these attributes have a significant effect on consumers’ choices. However, message content was found to have the strongest effect. Respondents are more likely to choose European Union Low Emitting carS (EULES)-friendly cars when the label shows information on lower costs or lower taxes and less likely to be influenced by health-related benefits, convenient parking or access fees. Finally, combinations of one message with other elements—EULES logo, CO2 logo or both—within the same label have a small but positive effect on respondents’ choices.

Conclusions
The findings of this study assist governmental decision-making processes by identifying those issues that have the greatest impact on consumers’ car purchasing decisions. Furthermore, the results will help to guide environmentally conscious customers towards the purchase of vehicles with clean emission profiles.

Full text

THE FUTURE OF ECOLABELS
The effects of ecolabels on environmentally- and health-friendly cars:
an online survey and two experimental studies
Frans Folkvord
1,2,3,4
&Giuseppe A. Veltri
5
&Francisco Lupiáñez-Villanueva
6
&Pietro Tornese
7
&
Cristiano Codagnone
6,8
&George Gaskell
9
Received: 15 June 2018 /Accepted: 28 May 2019
#The Author(s) 2019
Abstract
Purpose Given the increasing importance of political decision-making to reduce emission targets, the main purpose of the current paper
is to identify and test the considerations that would nudge consumers towards an environmentally and health-friendly motor vehicle.
Methods An online survey was conducted to assess public responses and the role of public authorities to a voluntary emission
standard for passenger cars. In addition, two online experiments were conducted to test incentives in the design of ecolabels (e.g.
price, safety, performance) for optimization. A random sample of 6400 individuals was drawn from eight countries: Germany,
Ireland, Italy, the Netherlands, Spain, UK, Czech Republic and Lithuania. An online survey was conducted among 3200
respondents, 400 in each of the 8 countries, and 2 online experiments with 3200 subjects, 400 in each of the 8 countries, allowing
for 200 respondents for each experiment in each country.
Results and discussion The survey shows that Europeans are aware of the health and environmental impact of cars. The findings
also confirm the gap between self-reported attitudes/intentions and actual behaviours. In influencing car purchase decisions,
health and environmental concerns are less important than other attributes suchas price, safetyand performance. The experiments
show that all these attributes have a significant effect on consumers’choices. However, message content was found to have the
strongest effect. Respondents are more likely to choose European Union Low Emitting carS (EULES)-friendly cars when the
label shows information on lower costs or lower taxes and less likely to be influenced by health-related benefits, convenient
parking or access fees. Finally, combinations of one message with other elements—EULES logo, CO
2
logo or both—within the
same label have a small but positive effect on respondents’choices.
Conclusions The findings of this study assist governmental decision-making processes by identifying those issues that have the
greatest impact on consumers’car purchasing decisions. Furthermore, the results will help to guide environmentally conscious
customers towards the purchase of vehicles with clean emission profiles.
Keywords Behavioural economics .Consumers’choice .Ecolabels .Environmental benefits .Experiment
Responsible editor: Fabio Iraldo
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s11367-019-01644-4) contains supplementary
material, which is available to authorized users.
*Frans Folkvord
ffolkvord@open-evidence.com
1
Tilburg School of Humanities and Digital Sciences, Department
Communication and Cognition Warandelaan 2, Dante Building,
room D 428 5037 AB, Tilburg, The Netherlands
2
Open Evidence Research, Universitat Oberta de Catalunya,
Barcelona, Spain
3
Behavioral Science Institute, Radboud University,
Nijmegen, The Netherlands
4
Communication Science, University of Amsterdam,
Amsterdam, The Netherlands
5
Department of Sociology and Social Research, University of Trento,
Trento, Italy
6
Department of Information and Communication Science, Open
Evidence, Universitat Oberta de Catalunya, Barcelona, Spain
7
Open Evidence Research, Barcelona, Spain
8
Dipartimento di Scienze Sociali e Politiche, Universitá degli Studi di
Milano, Milan, Italy
9
London School of Economics and Political Science, London, UK
https://doi.org/10.1007/s11367-019-01644-4
The International Journal of Life Cycle Assessment (2020) 25:883–899
/Published online: 1 July 2019
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1 Introduction
The Paris Agreement, ratified globally by practically every
country, except the USA and North Korea (UNFCCC 2018),
states that economy-wide decisions should be introduced to
achieve absolute emission reduction targets. Road transporta-
tion in Europe is a significant contributor to CO
2
emissions, as
well as air pollutants such as particulate matter and nitrogen
oxides (EEA 2015; Davis et al. 2010). The greenhouse gas
emissions from road transportation have significant impact on
the environment and on human health (Woodcock et al. 2009).
Furthermore, exposure to air pollutants has been identified as
a significant risk factor in a number of health conditions in-
cluding respiratory infections, heart disease, stroke and lung
cancer (EEA 2015;WHO2018). Greenhouse gas emissions
still remain above agreed levels and would need to fall dra-
matically in order to meet international agreements (UNFCCC
2018). In order to comply with the directives of the Paris
Agreement, European member states will be obliged to take
green initiatives (e.g. fiscal incentives, local access restrictions
for particular vehicles, local environmental zones differentiat-
ing vehicle access according to emission classes or ecolabels)
to reduce air pollution in cities and highly trafficked areas
(Kushwaha and Sharma 2016). Ecolabels are viewed as vol-
untary environmental and consumer policy instruments and
taken to be a simple and pragmatic option.
Increasingconcern about climate change has led to calls for
labelling to allow consumers to differentiate between more or
less sustainable purchasing options (Teisl et al. 2008). It is
assumed that with appropriate labelling information, some
consumers will be motivated to purchase cars that are more
sustainable (Thøgersen et al. 2010). Ecolabelling is seen an
important way of enhancing transparency and consumer trust
in environmental claims. It is also viewed as a method for
improving the sustainability of consumption patterns without
compromising freedom of choice and at the same time reduc-
ing consumers’information search costs (Grunert and Wills
2007). The elaboration likelihood model (ELM; Petty and
Cacioppo 1986) describes different ways of processing stimuli
and how these affect outcomes, such as attitude change and
eventually consumption behaviour. The ELM proposes two
major routes that are used to process messages: the central
and the peripheral routes. The central route involves an active
consideration of the arguments presented in the message. By
contrast, the peripheral route makes use of a simple heuristics
about the merits of the advocated position, such as the credi-
bility or attractiveness of the message. In the context of an
ecolabel, the likelihood of elaboration with the central route
is determined by an individual’s motivation and ability to
evaluate the information presented. With the purchase of a
costly product such as a car, it is assumed that consumers will
adopt the ‘high-effort’central path (Thøgersen et al. 2010)in
their assessment of ecolabels.
Importantly, Thøgersen et al. highlight the importance of con-
structs such as ‘environmental involvement’, the credibility of
ecolabels and the extent to which consumers understand the
information in choice behaviour (Bamberg 2003; Gadenne
et al. 2011; Thøgersen 2000,2002,2005; Thøgersen et al.
2012; Thøgersen and Noblet 2012). For example, the credibility
of labels can be influenced also by consumers’prior beliefs with
regard to sustainable products (Teisl et al. 2003). The perceived
effectiveness regarding their own behaviour and faith in the be-
haviour of others appear to be positively associated with in-
creased effectiveness of labels as sources of information
(Berger and Corbin 1992;Bougherara et al. 2005). As regards
the labels as such, their effectiveness apparently increases when
consumers can adequately rank competing products by key attri-
butes (Teisl and Roe 2005), consumers’prior beliefs (Teisl 2003)
or when consumers are educated about the presence and meaning
of ecolabels (Song et al. 2019). Comparative labels are also con-
sidered a potentially effective way of rendering complex numer-
ical information into simple categorical scales (Peters et al. 2009).
However, the use of ecolabels has been criticised because they
are based on the assumption that consumers and firms behave
irrationally, such as the absence of evidence of an energy-
efficiency gap (Gayer and Viscusi 2013) and on the assumption
that labels influence consumer to over-value energy consumption
in the purchase of goods (Sahoo and Sawe 2015). Making use of
ecolabels must therefore be based on robust evidence
(Codagnone et al. 2016).
To encourage consumers to purchase less polluting vehi-
cles, the European Commission is considering a voluntary
emission standard, called European Union Low Emitting
carS (EULES) with three complementary strategies
(Ntziachristos et al. 2016): first, to promote clean transporta-
tion by providing a benchmark for local or national authorities
in their development of financial or in green procurement
projects; second, to provide an incentive for manufacturers
to produce vehicles that deliver significant emission reduc-
tions; and third, by guiding environmentally conscious cus-
tomers towards the purchase of vehicles with ‘clean’emission
profiles (low real-world driving emissions) by ecolabelling
cars. The main focus of the present study is on this third
strategy, the effect of ecolabelling cars.
Broadly defined ecolabelling is a signalling method to en-
courage future consumers towards forms of sustainable con-
sumption (Thøgersen et al. 2010). In comparison to the more
general literature on ecolabels, and especially to that focusing
on white goods and food, studies examining the effects of car
labelling are scarce, with a small number of scientific articles
and a few policy reports (Choo and Mokhtarian 2004; Kurani
and Turrentine 2002;LaneandPotter2007; Loureiro et al.
2012; Noblet et al. 2006; Teisl et al. 2008; Teisl and Roe
2005). Therefore, it is necessary to establish which factors
are associated with the effectiveness of labelling cars and to
examine causal effects on consumption choices.
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To date, there is no single experimental study on the effect
of car ecolabels on consumers’decision-making. Teisl et al.
(2008) argue that rather than focusing on either the correlation
between individual characteristics and environmental friendly
behaviour (eco-behaviour) or between labels’characteristics
and eco-behaviour, it is important to test a model linking in-
dividual characteristics and labels characteristics. They found
that both label design and underlying psychological factors
need to be taken into account. More specifically, if the label
is well-designed, it can affect individuals’perceptions of the
eco-friendliness of a product.
Findings concerning consumers’preferences and the car pur-
chase process are reported by Achtnicht (2012), COWI (2002),
Lane and Potter (2007), Noblet et al. (2006), Teisl et al. (2008),
and Codagnone et al. (2013). These studies show that purchasing
decisions are dominated by attributes such as price, performance
and safety with eco-friendly attributes playing a secondary role.
Secondly, the purchase of a car is found to be a two-stage pro-
cess. Purchasers first determine the class of car they want to buy.
It is only when they move to select the model that eco-friendly
and fuel economy features are more seriously considered.
Achtnicht (2012) finds that people in Germany say they are
willing to pay more for a car that has lower CO
2
emissions and
that willingness to pay decreases for those who reported lower
price ranges for a future car purchase and that differences were
found by age, gender and educational level. Younger individuals,
women and individuals with a higher education entrance quali-
fication have a significantly higher willingness to pay.
Related with the debate in environmental behavioural eco-
nomics is the legitimate question whether ‘nudges’based on
information supply differ from various forms of informational
instruments (Kosters and Van der Heijden 2015). According to
Ölander and Thøgersen (2014), ecolabels play the role of infor-
mation provision at the point of sale but change the choice archi-
tecture of consumers when (if) consumers become familiar with
and consider them as credible. Following the work of Peters et al.
on label that performs well in summarizing complex numerical
information (Peters et al. 2009), Johnson et al. (2012) consider
‘good labels’(as opposed to bad ones) as an instrument of attri-
bute parsimony to reduce attribute overload and as such they
qualify them as a nudge for they alter the choice architecture.
A further element for considering ‘ecolabels’as a nudge is the
evidence that their design affects consumers’perceptions
(Heinzle and Wüstenhagen 2012).
In this study
1
, the main purpose is to identify and test the
elements that would nudge consumers towards a preference
for an environmentally and health-friendly EULES car. The
study focusses on two separate objectives: first, mapping the
contours of public responses and the role of public authorities
to a voluntary emission standard for passenger cars that would
deliver real-world emission levels below the current limits;
second, experimentally testing the impact of different incen-
tives designed to support the EULES policy. The outcomes of
the research will:
1. Extend the knowledge base about car ecolabels.
2. Support governmental decision-making process on the
successful introduction of the EULES labels.
3. Assess the differential impact on consumers’preferences
between the CO
2
label and the EULES label.
4. Help guide environmental conscious customers towards
the purchase of vehicles with clean emission profiles.
5. Provide a benchmark for local or national authorities
when developing financial or access and demand policies
to promote clean transportation and to integrate footprint
approaches into effective ecolabels.
2Methods
To assess public responses to a voluntary emission standard for
passenger cars, an online survey was conducted. In addition, two
online experiments tested incentives for optimal message impact
(see also Fig. 1). A random sample of 6400 individuals was
drawn from 8 countries Germany, Ireland, Italy, the
Netherlands, Spain, UK, Czech Republic and Lithuania. The
sample was divided and allocated to (i) an online survey with
3200 respondents, 400 per each of the 8 countries, and (ii) two
online experiments with 3200 respondents, 400 per each of the 8
countries, giving 200 respondents for each experiment and coun-
try. The randomization was ensured at the country level, such that
each country was equally represented in the survey (n= 400) and
1
This study is part of a larger study conducted for the European Commission
(No. ENV.C.3/FRA/2013/0013, Service No. 8, EC DG ENV). The principal
objective of the project was to provide the background on the potential of a
voluntary low-emission standard for passenger cars in order to deliver real-
world emission levels below the most stringent current emission limits, as well
as to develop the technical and legal background for its implementation
8 countries
N = 6,400
Survey
(N= 3,200; 400/country)
To identify general attitudes towards
low-polluting cars
Experiment 1: Small cars
(N= 1,600; 200/country)
To assess impact of selected car
attributes during a purchase decision
Experiment 2: Large cars
(N= 1,600; 200/country)
To assess impact of selected car
attributes during a purchase decision
Random
allocation
Fig. 1 Overview of the research design
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in the experiments (n= 200). Gathering the data across countries
made it possible to ensure the validity and possibility to general-
ize findings on awareness, understanding and attitudes regarding
the EULES standard as well as the comparison between EULES
and CO
2
emissions.
2.1 Survey
The online survey was designed to explore the level of under-
standing of, and the attitudes towards, EULES-related issues
(Annex 1—Electronic Supplementary Material). The survey
questionnaire was structured as follows:
Block A: Self-reported purchase process: Questions
assessed self-reported steps and factors that the
respondent would take into account in the car
purchasing process (class and model, dynamics
of purchase process, main attributes considered,
information sources).
Block B: Contextual factors: Questions assessing environ-
mental attitudes through consolidated scales, re-
spondents’faith in the eco-behaviours of others
and in the effectiveness of their behaviours as con-
sumers, and perceived trade-offs between, for ex-
ample choosing eco-friendly and performance.
Block C: Questions assessing the awareness of the environ-
mental and health impacts of car usage.
Block D: Questions assessing awareness, trust and the effect
of labels.
Block E: Questions assessing socio-demographic profile
(e.g. sex, age, possession and usage car).
2.2 Experiments
The online experiments were designed to examine the effect of
ecolabels on car purchasing. The experiments used the discrete
choice methodology to simulate a car purchasing decision and to
Fig. 2 Choice set no. 2 for small
car
Fig. 3 Choice set no. 1 for large
car
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assess the relative impact of different attributes of the cars on
respondents’choices. Briefly, it is assumed that when choosing
between several cars, consumers consider a range of attributes—
number of seats, engine size, price, etc.—prior to making a pur-
chase. The literature reports that price is the most influential
attribute; it dominates other attributes. To assess the relative im-
portance of non-price attributes, in our case an EULES or CO
2
label, we offer respondents a series of binary choice between
versions of the same model that differ with respect to the pres-
ence or absence of environmental information. This is the tech-
nique of discrete choice modelling. From a series of choices
between cars with different ‘environmental profiles’, it is possible
to estimate whether the presence or absence of a particular attri-
bute increases the probability of choosing a car that features that
attribute.
There were two experiments, one featuring small cars and
the other large cars. Respondents were shown a picture of two
visually identical cars—option A and option B. The two op-
tions differed with respect to four attributes or features—the
price (baseline or baseline plus a few hundred Euros), the
EULES label (present or absent), the EULES message (pres-
ent or absent) and the CO
2
label (present or absent).
The small and large cars differed in terms of prices and the
level of CO
2
emissions. For the small car, the price was either
10,000 or 10,700 Euros; for the larger car, it was 25,000 or
26,200 Euros. The rationale behind the price differential was
the estimated additional cost of introducing the EULES stan-
dard that might be passed on to consumers. The small car was
associated with a lower level of CO
2
emissions (i.e. in the
categories B and C) and the large car was associated with a
higher level of CO
2
emissions (i.e. in the category D). In the
experimental design, the label either was present or absent,
depending on the choice set.
Figures 2and 3below illustrate the choice sets for each car
type. In Fig. 2, the respondents had to choose between the
small car that had the EULES label and the CO
2
label and
the same car that had no labels. In Fig. 3, the respondents
chose between a large car with the EULES label and without
11%
14%
18%
39%
48%
0%
3%
1%
38%
63%
Electric
A
lternat ive fuel
Hyb rid
Diesel
Gasoline
Owned Desired
Fig. 4 Type of car, by engine
Fig. 5 Attributes considered in
the car purchasing process
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it;inbothcases,theCO
2
label was present. In addition, the
EULES messages and the prices differed in all the choice sets.
To avoid any experimental biases and priming issues the re-
spondents were not given an explanation about the meaning of
the EULES label. Respondents were presented with three impli-
cations of EULES-friendly cars, including health effects (cleaner
air in cities), city accessibility (access to low-emission zones,
preferential parking in low-emission zones) and financial impacts
(lower taxes, lower annual costs). These were captured in three
simple messages to the respondents and appeared beside the
EULES label, the CO
2
label or as stand-alone in those conditions
without any environmental information. Respondents were
asked to make choices between 10 pairs of cars with differing
attributes. The study sampling errors (overall and by quotas) are
calculated for a probability no greater than 95.5% and for the
least desired context, i.e. a maximum indeterminate probability
(p=q= 50%) for the reference population.
The fieldwork was conducted between February and
March 2015. A pilot study was conducted in the UK, followed
by the full launch went ahead in the UK. Finally, after the
translation of the questionnaire in the other languages, a joint
launch took place in the remaining countries.
3 Results from the survey
3.1 Decision-making: describing the purchase process
In order to gain an indication of the decision-making process
behind car purchases, survey respondents were initially asked
to report the size of their current car. The most popular car
class appears by far to be the small-family car (such as Ford
Focus, Volkswagen Golf, Citroën C4) owned by 39% of re-
spondents. About 19% of subjects own at least one large-
family car (such as Renault Laguna, Volkswagen Passat or
Ford Mondeo). Supermini cars—Peugeot 208, Volkswagen
Polo and Renault Clio—come a close third having been se-
lected by 11% of respondents. In terms of current and future
car purchase decisions (Fig. 4), it is worth noting that while
Fig. 6 Assessment of statements
related to the car purchase process
(%)
Table 1 Profiles of car purchasers
Factor Cluster
1. Non-sensitive 57% (n= 1815) 2. Sensitive 43% (n= 1385) ANOVA
Emphasis on environmental and health issues −0.22 0.29 201.52*
Emphasis on cost 0.41 −0.54 699.54*
Emphasis on the present 0.51 −0.67 1106.73*
Emphasis on the future −0.14 0.19 86.28*
*p<0.05
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few respondents reported owning environmentally friendly
cars,manymoresaidtheywouldbuyoneinthefuture.
About 18% of the subjects reported planning to buy a hybrid
car. Cars that run on alternative fuels, such as CNG and LPG,
were mentioned by 14% of the respondents (as opposed to 3%
of current owners). About 11% plan to buy an electric car,
currently owned by less than 1% of current owners.
In terms of car usage, one in two respondents (47%)
reported driver to work on a daily basis. Almost all
subjects drive for shopping, although only 10% do so
daily. About 18% drive their children to and from
school every day. Finally, most respondents use their
car for weekend getaways (more than 90%) and holi-
days (more than 80%) at least once a year.
Individuals were then asked to identify what were the main
attributes considered during the purchase decision.
Respondents were asked to rate each attribute on a 1–7impor-
tance scale, with 7 being ‘very important’. As Fig. 5shows, a
car’s environmental performance is considered as ‘very im-
portant’by less than one in five respondents (19%). Likewise,
local air quality is a very important attribute for only 15% of
respondents. On the other hand, about half of the subjects
consider price (50%), road safety (47%) and fuel consumption
(46%) followed by maintenance cost (40%) and type of en-
gine (28%) as very important attributes. After price and road
safety, attributes pertaining to the broadly defined ‘Fuel
Economy’score fairly high in importance.
In addition to car’s attributes, individuals were asked to
report about the process followed in choosing a car (Fig. 6).
From the responses, it can be seen that individuals favour
price and its range (24% and 39%, respectively), along with
size and engine (25% and 26%, respectively). Environment
and health effects are less important. While one third of re-
spondents (32%) are aware that less polluting cars, ceteris
paribus, lower the level of pollution, statements on environ-
mentally friendly attitudes in car purchasing yield very low
percentages of full agreement. Health consequences would
convince only 12% of respondents to select a different class
of car (e.g. from sport utility vehicle to midsize car). The
environmental effects are also not particularly important when
Fig. 7 Present-future attitudes
Fig. 8 Profiles of car purchasers, by age group (left) and education (right)
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choosing the car’s class (12%). Finally, a mere 11% of the
sample is ready to pay for a more environmentally friendly
model.
The responses to the purchase process show that features such
as price, type of engine and class of car drive decisions and are
likely to have been determined before selecting a particular mod-
el. As such, it is likely that environmental and health-related
attributes are something of an afterthought. To investigate this
further, we can look at answers to questions about respondents’
attitudes towards taking current or future consequences into the
decision-making process (see Fig. 6).
To examine and summarize these attitudes, a principal compo-
nent analysis was performed on the questions concerning taking
account of the current or future consequences of choices. Two
factors emerged: (i) emphasis on the immediate issues (34.43%
of variance explained) and (ii) a focus on how future impacts on
health and the environment affect current behaviour (25.58% of
variance explained). To develop a typology of consumers’under-
standing and attitudes towards health and environmental issues in
the car purchase process, a cluster analysis of K-means was car-
ried out (Table 1). Cluster 1 consists of respondents who place a
greater emphasis on a car’s price and maintenance costs, whose
behaviour is likely to be influenced by the immediate outcomes of
their actions, and who are less likely to sacrifice their current well-
being for future gains. This group is referred to ‘eco-insensitive
consumers’(57% of respondents). The label is used descriptively
in order to capture the sense that, for these respondents, environ-
mental and health issues are not important. By contrast, cluster 2 is
characterised by a notably different syndrome of attitudes. Here,
respondents place a notable emphasis on environmental and
health issues. They are more likely to say that they will pay more
for an environment-friendly car. They place more emphasis on the
future and are more likely to engage in behaviours with long-term
outcomes. Members of cluster two are labelled ‘eco -sensitive
consumers’(43% of respondents).
Comparing those who score highly on clusters 1 and 2, we find
no statistically significant gender differences. However, the eco-
sensitives are more likely to be younger, highly educated and with
a slightly higher self-attributed socioeconomic status than the‘eco-
insensitives’, see also Fig. 7.
We investigated how these two clusters view the impor-
tance given to attributes of cars (see Figs. 8and 9). As might
Note: *p<0.05
Fig. 9 Profiles of car purchasers
by cars’attributed importance (%)
Fig. 10 Profiles of car purchasers
by next car’sengine(%)
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be expected, the ‘eco-sensitives’are slightly more oriented
towards environmental performance and local air quality than
the ‘eco-insensitives’. Price, maintenance costs and size are
considered slightly less important by the ‘eco-sensitives’than
the ‘eco-insensitives’.Thischaracterizationsuggeststhatthe
post-materials might be in favour of paying a slightly higher
price/cost for less polluting cars as they value positively the
environmental and health consequences of the car selected.
3.2 Perceptions and understanding of the health
and environmental issues
Respondents were asked about contextual factors and about
their health attitudes and awareness. Only 5% of respondents
agreed that ‘most people are willing to pay higher prices to
protect the environment’and ‘most people do their parts to
protect the environment’. This indicates that assumptions
about the eco-friendly motivation and commitment of others
are low. This may reduce the perceived effectiveness of one’s
behaviour as a consumer and induce a sense of rationalised
apathy—if others are doing nothing, why should I bother?
However, the data shows (see Fig. 10)thatlackoffaithin
others does not prevent 61% of respondents from agreeing
with the statement ‘my lifestyle can have an impact on the
environment’and 43% from disagreeing with the statement
‘it’s hard for someone like me to do much about the environ-
ment’. So, despite the lack of faith in others, respondents do
not feel that this exempts them from their individual
responsibility.
Another constraint to opting for environmentally more sus-
tainable cars is the widespread perception that less polluting
and/or lower fuel consumption vehicles are more costly and
give poorer performance. We find evidence that many con-
sumers perceive buying eco-friendly car as entailing losses
and a sacrifice. Such perceptions suggest that there is not a
complete understanding of the connection between CO
2
emis-
sions, fuel efficiency, performance and prices.
In this regard, the characterization of the two profiles pre-
viously identified reveals that ‘non-sensitive consumers’put
more responsibility on others (‘most people…’) than them-
selves (‘my lifestyle…’)incomparisonwith‘sensitive con-
sumers’(see also Fig. 11).
Around 7 out of 10 respondents (68%) understand that high
pollution emissions could make them ill and 1 in 2 (50)% are
concerned about how choices today may lead to future health
problems. Nevertheless, whereas general awareness about the
environmental impact of car usage is fairly high, 43% of the
respondents say they are not worried about getting ill due to
Fig. 12 Profiles of car purchasers
by contextual factors (%)
Fig. 11 Contextual factors (%)
Int J Life Cycle Assess (2020) 25:883–899 891
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high levels of pollution. Moreover, when asked about infor-
mation on levels of pollution in their cities, just 8% said they
feel ‘well informed’(see also Fig. 12).
Again, the analysis of the profiles reveals slightly different
patterns (see Fig. 13). ‘Sensitive consumers’are generally
more aware than ‘non-sensitive consumers’about the health
consequences of car usage, even though they stated that they
are less well informed about the level of air pollution (Fig. 14).
3.3 Incentives to influence the purchase process
Respondents were asked for their opinion on a number of
policy-related issues, including incentives forthe environmen-
tally friendly choices. Around 30% of subjects believe that
higher financial incentives (such as tax breaks and subsidies)
for low-emitting products would be a very effective strategy to
tackle air pollution. This policy option ranks second, after
‘applying stricter pollution controls on industrial and energy
production activities’. The option of requiring the application
of best available technology was selected by 38% of respon-
dents. Overall, while there is support for a range of policies to
promote low-emitting vehicles, there is no clear preference for
between financial or non-financial incentives. As Fig. 15
shows, around 3 in 10 respondents consider a number of pol-
icies as diverse as exemptions for registration and road taxes,
schemes for scrapping old vehicles and charging points for
electric cars as ‘very important’. On the other hand, cheaper
parking options and road taxes for low-emitting car owners
gain less support (‘very important’only by 16% and 15%,
respectively).
Responses to the eight measures were later grouped into the
two broader categories of ‘financial incentives’, which in-
cludes tax breaks and subsidies, and ‘non-financial incen-
tives’, such as access and parking options. Overall respon-
dents tend to consider financial incentives as ‘more important’
(mean = 5.24, using a 1–7 importance scale) than non-
financial incentives (mean = 4.71).
The impression that priority access and parking options are
not as attractive as tax breaks and subsidies finds further sup-
port when respondents were asked to react to different non-
financial incentives. When posed a scenario of a ban on high-
emitting cars from being used during high pollution days, for
example, more people stated that they would switch to public
transport, bike or foot (23% of respondents ‘totally agree’),
rather than buy a low-emitting car (18%). Likewise, if low-
emitting cars got ‘substantially cheaper parking places in the
city centre’, more respondents would rather commute (18% of
full agreement) than buy (14%). The only scenario where
respondents said they would buy a low-emitting car, although
by a small margin (20% ‘buy’, 19% ‘switch to another
mode’), is the introduction of a low-emission zone in the city
centre (see Fig. 16).
These results point to the conclusion that non-financial
incentives (low-emission zones, driving restrictions, cheap
parking fees) might not be effective in moving consumers
towards low-emitting cars. However, it may be the case that
01234567
I make a link between heal th and the environment. I
unders tand that high pollut ion emiss ions c ould m ake
me sick*
I am co ncerned abo ut negati ve f uture conseq uences
to my health d ue to my d aily cho ices*
I am afraid of getting seriously sick because of the
high levels o f pollutio n*
I feel very well inf ormed abo ut the level of air po lluti on
in my city*
Sensitive Non-sensitive
Fig. 14 Profiles of car purchasers
by health awareness (%)
Fig. 13 Health awareness (%)
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892
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the attractiveness of non-financial incentives varies across
consumer groups. For example, cheaper parking fees are like-
ly to be less attractive for those with a residential garage.
Similarly, low-emission zones are likely to affect commuters
more than city centre residents. In order to investigate such
differences, we split the sample into those who drive to work
daily (commuters) and the rest (others). Almost half the sam-
ple (47%) fall into the commuter category. Do commuters
have different views compared to the others about non-
financial incentives? The comparison is shown in Fig. 17
which shows that non-commuters are more likely to switch
mode of transport in all three scenarios, while commuters
would buy a low-emitting car when faced with low-emission
zones (23%) or cheaper parking fees (18%). For commuters,
buying is also almost as popular as switching to public trans-
port (both at 21%) in case of driving restrictions.
3.4 Attitudes and perception towards labels
In the last section of the survey, respondents were presented
with several questions on car labels. Existing car labels do not
score particularly well if judged by the level of agreement/
disagreement with the statements depicted in Fig. 18.As
many as 43% of the sample agree with the statement that they
are unfamiliar with car labels and almost the same percentage
of respondents agree (38%) and disagree (39%) on their
familiarity with car labels. These percentages agreeing
(39%) and disagreeing (37%) are similar when respondents
were asked about the recognition of car labels.
It is notable that percentage of respondents who do not trust
the information in car labels (39%) is higher than for those
who trust this information (33%). However, 38% of the sam-
ple agree with the statement that car labels are a symbol of a
product’s trustworthiness (27% disagree) and as many as 37%
believe (agree) that information contained in car labels is
truthful and 34% that the information is sufficient (32% dis-
agree to both statements). When asked to react to the state-
ment concerning how they use labels when they buy a car,
35% of the respondents state (agree) that they base their deci-
sion upon a (or several) car label (29% disagree) (Fig. 19).
4 Results from the experiment
In the online experiments, respondents were asked to choose
between one of two car options. Each option consisted in the
picture of the car and additional information. The first exper-
iment featured two versions of the same small car, and the
second featured two versions of a large car. Additional infor-
mation featured a designed combination of one of the two
conditions for the four car attributes.
Fig. 16 Respondents who
consider ‘very important’the
following policies
Fig. 15 Strategies to tackle air-
related problems (%)
Int J Life Cycle Assess (2020) 25:883–899 893
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1. The car’s base price or with a surcharge to fund
ecolabelling (either 10,000 EUR or 10,700 EUR for small
cars and either 25,000 EUR or 26,200 EUR for large cars)
2. A label on the car’sCO
2
emissions (present or absent)
3. A hypothetical EULES label (present or absent)
4. Amessageonthecar’s positive features in terms of (i)
‘Taxes’, i.e. lower costs, (ii) ‘Access’, i.e. urban accessi-
bility or (iii) ‘Health’, i.e. health benefits
The experimental data was analysed using a conditional
logistic regression to estimate the increase in the probability
of selecting a car when each of the attributes described above
was added to the car label.
For each of the four attributes, the tables show coefficients,
odds ratios, standard errors, 95% confidence intervals, and the
outcome of the effect likelihood ratio tests expressed by the L-
R chi-square (the value of the likelihood ratio chi-square sta-
tistic for a test of the corresponding effect; DF, the degrees of
freedom for the chi-square test Prob > ChiSq, the pvalue for
the chi-square test). We also report the models likelihood,
AICc and BIC
2
. In discrete choice models, each coefficient
is a ‘part-worth’estimate or the utility associated with that
attribute. In the analysis, the ‘Taxes’message was used as a
reference point for the categorical variable ‘EULES Message’
and therefore does not appear in the output tables. ‘Taxes’is
used as a reference. ‘Access’yields a negative part-worth
compared to ‘Taxes’,while‘Health’has a positive part-worth.
By default, estimates are based on the Firth bias-corrected
maximum likelihood estimators (MLEs) and therefore are
considered to be more accurate than MLEs without bias
correction.
The result ofthe statistical analysis for thetwo experiments
shows that all four attributes considered have a significant
impact (P< 0.05) on the participants’choices (see Tables 2
and 3). The presence of logos, either EULES or on CO
2
emis-
sions, has a small negative effect, 12% less likely for both
logos for small cars and 7% (EULES) and 6% (CO
2
) for large
cars. For small and large cars, the additional price had a mar-
ginal positive effect in terms of increasing probabilities of
selection by respondents (17% for small cars and 38% for
large cars). The effect of the added messages is slightly posi-
tive in the case of ‘health’, increasing odds of selection of 13%
for small cars and 11% for large cars while negative for ‘ac-
cess’, decreasing odds of selection by 50% for small cars and
40% for large cars.
Of significance is the finding that the single most important
predictor affecting choices is the message conveying the ben-
efits of a low-emission car that accompany the logo. Tables 4
and 5show how the different benefits captured in the mes-
sages (taxes, urban access and health) impact on choices.
Table 5, focusing on larger cars, is based on the same anal-
ysis as Table 1. The odds ratio was 2.48 versus urban access
and 1.34 versus health benefits. This means that information
about the tax advantages of low-emission cars makes the
choice of selection 1.48 times more likely than the urban ac-
cess benefit and 0.30 more likely than a health benefit.
Overall, this shows that information attached to a low-
emission logo is the most important attribute in in increasing
the likelihood of choice. But, crucially a message about tax
advantages has considerably more impact than messages
about the benefits of urban access and health. This effect is
particularly strong for those choosing small cars and to a lesser
extent for those choosing large cars.
5 Discussion
In order to comply to the Paris Agreement (UNFCCC 2018),
greenhouse gas emissions have to reduce significantly.
Current levels of air pollution are above international agree-
ments and an important factor that contributes to air pollution
is road transportation (Davis et al. 2010; EEA 2015). It is
2
This technique seeksto estimate the parameters of a model, which we denote
generically by (β), by maximizing the likelihood function. The likelihood
function, denoted L(β), is the product of the probability density functions (or
probability mass functions for discrete distributions) evaluated at the observed
data values. Given the observed data, maximum likelihood estimation seeks to
find values for the parameters, β,thatmaximizeL(β). Rather than maximize
the likelihood function L(β), it is more convenient to work with the negative of
the natural logarithm of the likelihood function, −Log L(β). The problem of
maximizing L(β) is reformulated as a minimisation problem where you seek to
minimize the negative log-likelihood (−LogLikelihood =−Log L(β)).
Therefore, smaller values of the negative log-likelihood or twice the negative
log-likelihood (−2LogLikelihood) indicate better model fits.
10%
13%
9%
19%
23%
18%
20% 18%
14%
Low-emission zone Drivin
g
restriction Cheap parkin
g
Stop (park outside) Switch (to public transport, bike, foot) Buy low-em itting car
Fig. 17 Respondents’reaction to
different incentives
Int J Life Cycle Assess (2020) 25:883–899
894
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therefore of great importance to examine effectiveness of be-
havioural techniques that might improve consumers’choices
when buying cars. The main objectives of the current study
were (1) to assess and explore public responses and the role of
public authorities to a EULES in order to deliver real-world
emission levels below the most stringent current emission
limits and to (2) experimentally test the incentives for this
optimization.
First, as the results from the survey show, Europeans are
aware of the health and environmental impact of cars. The
survey points to a general understanding of the adverse health
effects of pollution. Results showed that the respondents rec-
ognize that there is a link between the environmental protec-
tion and human health. Second, people think that the pollution
in their cities or neighbourhoods is rather high. Third, the
result also shows respondents are aware of the environmental
impact of polluting vehicles. More than half of respondents
(54%) believe that ‘cars contribute significantly to the air pol-
lution’in their city or neighbourhood. Despite the high envi-
ronmental awareness, the main factor that subjects take into
account when buying a car is price (50% of respondents),
followed by road safety (48%) and fuel consumption (46%).
Most importantly, only 1 in 10 (11%) is ready to pay more for
a more environment-friendly car. Finally, results also confirm
the gap between self-reported attitudes/intentions and actual
behaviours: health and environmental concerns come only
after many other attributes (price, safety, performance, etc.)
in terms of importance in influencing car purchase decisions.
10%
14%
9%
18%
21%
16%
23%
21%
18%
Low-em ission zone Driv ing restriction Cheap park ing
Commuters only
Stop
(
park outside
)
Switch
(
to public transport, bike, foot
)
Bu
y
low-emittin
g
car
10%
13%
9%
20%
25%
20%
16% 16%
10%
Low-emission zone Driv ing restriction Cheap park ing
Non-commutersonly
Fig. 18 Respondents’reaction to
different incentives
Fig. 19 Existing awareness and
perception on car labels
Int J Life Cycle Assess (2020) 25:883–899 895
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In fact, many consumers perceive buying an eco-friendly car
as entailing a loss/sacrifice in terms of performance. There is a
quite widespread perception that less polluting or lower con-
sumption vehicles are associated with higher prices and that,
to some extent, also compromise performance, which is in line
with previous research (Gould and Golob 1998;Zhangetal.
2015). In this regard, citizens do not clearly understand the
difference between air pollution and greenhouse gas emissions.
Nearly half of the respondents (47%) agree with the statement
‘Vehicles that produce less pollution consume less fuel’.
Financial incentives are the most likely to change consumers’
behaviour towards low-emission cars. According to 30% of
survey respondents, providing higher financial incentives for
low-emission products would be an effective strategy to tackle
air pollution. Financial measures (tax breaks, subsidies) are
more likely to nudge consumers towards low-emission cars than
are non-financial incentives. Among the latter, low-emission
zones seem more appealing, especially for those consumers
who drive to work on a daily basis. Citizens are likely to prefer
tax exemptions and subsidies rather than environmental taxes or
road pricing. We draw this conclusion from the survey, in which
respondents believe they are paying already too much of envi-
ronmental taxes for their car and are not in favour of applying
‘road pricing’(e.g. road tax, registration tax) for major metro-
politan areas (e.g. cities with over 100,000 inhabitants and their
suburbs). At the same time, they welcome proposals in which
the government would provide either tax exemptions or subsi-
dies for those purchasing a low-emitting car. European con-
sumers are not too acquainted with car labels. More than 43%
of respondents admit to be ‘unfamiliar with’existing car labels.
Around 37% disagree with the statement that labels are ‘easily
recognizable’. As many as 39% do not trust the information
displayed, and reportedly, the most common use of labels is
‘to check if what said in the advertisement is true’.Manyeven
misunderstand their purpose: nearly 38% believes that labels
symbolize a product’s reliability. In any case, the element of
car labels that most attracts the attention of candidate buyers is
the message.
To find that out, we ran a series of experiments in which
individuals were asked to choose a car between two options.
Each option consisted in a label depicting a car and a series of
additional elements—logos, price tags and a series of mes-
sages. As the results show, all attributes are significant, and
they all contribute to the choice. However, the strongest utility
is given by the messages. Respondents were more likely to
choose EULES-friendly cars when they the label shows infor-
mation on lower costs or lower taxes. When it comes down to
one car purchase decision, consumers are less interested in
knowing about health-related benefits, convenient parking or
access fees. A minor increase in price has a negligible effect.
Finally, combinations of one message with other elements—
EULES logo, CO
2
logo or both—within the same label have a
small but positive effect on participants’choices.
Ecolabelling is considered an effective strategy to encour-
age future consumers towards forms of sustainable consump-
tion (Thøgersen et al. 2010). Compared to the more general
literature on ecolabels and especially to that focusing on white
goods and food, the study of car labelling is considerably less
Table 2 Parameter estimates SMALL CARS
Term Estimate Odds ratios Std error Lower 95% Upper 95% L-R chi-square DF Prob>ChiSq
Price 0.17 1.1752 0.00 0.00 0.00 251.796 1 < 0.0001*
EULES Message Access −0.65 0.5219 0.01 −0.68 −0.62 2169.130 2 < 0.0001*
EULES Message Health 0.12 1.1287 0.01 0.09 0.15 < 0.0001*
Absence of EULES Logo −0.13 0.8779 0.01 −0.15 −0.11 167.296 1 < 0.0001*
CO
2
Logo [NO_CO
2
_L] −0.13 0.8764 0.01 −0.15 −0.11 203.018 1 < 0.0001*
*p<0.05
Table 3 Parameter estimates—large cars
Term Estimate Odds
ratios
Std
error
Lower
95%
Upper
95%
L-R chi-square DF Prob>ChiSq
Price 0.32 1.3858 0.00 0.00 0.00 1286.676 1 < 0.0001*
EULES_Message[Access] −0.51 0.6019 0.01 −0.53 −0.48 1555.362 2 < 0.0001*
EULES_Message[Health] 0.11 1.1114 0.01 0.08 0.14 < 0.0001*
EULES_Logo[NO_EULES_L] −0.08 0.9231 0.01 −0.10 −0.06 73.718 1 < 0.0001*
CO
2
_Logo[NO_CO
2
_L] −0.06 0.9436 0.01 −0.08 −0.04 39.794 1 <.0001*
AICc 18,949.468, BIC 18987.866, −2 × Loglikelihood = 18,939.464, −2×Firth LogLikelihood = 18,894.23
*P <0.05
Int J Life Cycle Assess (2020) 25:883–899
896
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developed with only a limited amount of studies conducted to
examine its effects (Choo and Mokhtarian 2004;Kuraniand
Turrentine 2002; Lane and Potter 2007; Loureiro et al. 2012;
Noblet et al. 2006; Teisl et al. 2008; Teisl and Roe 2005). The
first strength of the current study is that it established which
factors are associated with the effectiveness of labelling cars.
Ecolabels are consideredas voluntary environmental and con-
sumer policy instruments and therefore considered as a prag-
matic option for policy developers. It is a form of choice
architecture that does not affect the perceived autonomy of
consumers, being an ideal example of a ‘nudge’. The second
strength ofthe study is that we are the first that experimentally
examined causal effects on consumption choices. Until now,
there has been no experimental study conducted on the effects
of car labels on consumers’decision-making, although it is of
great importance to reduce the negative health consequences
of road transport (EEA 2015). Teisl et al. (2008)showedthatit
is important to test a model linking individual characteristics
and label characteristics in order to create effective ecolabels
that affect individuals’perceptions of the eco-friendliness of
products. Existing studies on ecolabels have been focusing on
the relationship between individual characteristics and eco-
behaviour or between label characteristics and eco-behaviour
but not on the interaction between these two factors. It is
therefore important to extend this knowledge by examining
both individual characteristics and the manipulation of
ecolabels simultaneously and test the effectiveness of the
ecolabels. As Teisl et al. (2008) already have shown, it is
highly relevant to examine underlying psychological factors
and individuals’priors of the product and of the
environmental problem, because it plays a strong role for the
long-run provision of eco-information, in particular in context
where individual consumers hold incorrect perceptions.
One limitation of the current study is that participants con-
ducted the survey and experiment online, whereby we did not
control the situation in which they participated. This is a poten-
tial harm of internal validity. However, it could also be argued
that such settings could reflect the real purchasing decisions to a
larger extent. One could imagine that a typical consumer usually
chooses its vehicle on the basis of a number of attributes by
browsing the Internet, and subsequently, the person visits a car
dealer to obtain further details. Additionally, future research
could investigate the effects of ecolabels on consumption be-
haviour in real-life car shops. Secondly, only a limited amount
of car types were used in the experiments so it is difficult to
generalize the results to other type of cars. Nonetheless, the
same mechanism that we have found in the current study seems
to be applicable to other cars as well, in particular because we
assessed public responses to possible incentives in general that
might affect the perception of the ecolabels.
6 Conclusions
The current study is of great importance because it will pro-
vide the standard that could be presented to consumers either
in a form of a label, a message or both. In this study, our
research goal was to identify and test the elements which
would nudge consumers towards an environmentally and
health-friendly EULES car. Our findings will support
Table 4 Small cars: messages and odds ratio comparison
Compared 1 Compared 2 Probability 1 Probability 2 Odds ratio 1 Odds ratio 2
EULES_Message=Access EULES_Message=Health 0.312 0.68 0.46 2.16
EULES_Message=Access EULES_Message=Taxes 0.24 0.76 0.31 3.25
EULES_Message=Health EULES_Message=Access 0.68 0.32 2.16 0.46
EULES_Message=Health EULES_Message=Taxes 0.40 0.60 0.67 1.50
EULES_Message=Taxes EULES_Message=Access 0.76 0.24 3.25 0.31
EULES_Message=Taxes EULES_Message=Health 0.60 0.40 1.50 0.67
Table 5 Large cars: messages and odds ratio comparison
Compared 1 Compared 2 Probability 1 Probability 2 Odds ratio 1 Odds ratio 2
EULES_Message=Access EULES_Message=Health 0.35 0.65 0.541 1.85
EULES_Message=Access EULES_Message=Taxes 0.29 0.71 0.40 2.48
EULES_Message=Health EULES_Message=Access 0.65 0.35 1.85 0.54
EULES_Message=Health EULES_Message=Taxes 0.43 0.57 0.74 1.34
EULES_Message=Taxes EULES_Message=Access 0.71 0.29 2.48 0.40
EULES_Message=Taxes EULES_Message=Health 0.57 0.43 1.34 0.74
Int J Life Cycle Assess (2020) 25:883–899 897
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governmental decision-making process with respect to the
EULES format that should have the greatest impact on con-
sumer purchasing decisions. In addition, we also assessed the
likely consumers’preference between the CO
2
label and the
EULES label. The results will help to guide environmental
conscious customers towards the purchase of vehicles with
clean emission profiles. Furthermore, it will provide a bench-
mark for local or national authorities when developing finan-
cial or access and demand policies to promote clean transpor-
tation. Finally, it will provide an incentive for manufacturers
to produce vehicles that deliver significant emission reduc-
tions on the road.
Acknowledgements F. Folkvord, G. Veltri, F. Lupiáñez-Villanueva, P.
Tornese and C. Codagnone developed the study concept and contributed
to the study design. G. Veltri, F. Lupiáñez-Villanueva, P. Tornese and C.
Codagnone collected, tested and analysed the data. F. Folkvord
interpreted the data under supervision of F. Lupiáñez-Villanueva, C.
Codagnone, F. Bogliacino, G. Veltri and G. Gaskell. F. Folkvord drafted
the manuscript. G. Veltri, F. Lupiáñez-Villanueva, P. Tornese, C.
Codagnone and G. Gaskell provided critical revisions. All authors ap-
proved the final version of the manuscript for submission.
This study has been funded by the European Commission (No.
ENV.C.3/FRA/2013/0013, Service No. 8, EC DG ENV). The content
of this study represents the views of the authors and is its sole responsi-
bility; it can in no way be taken to reflect the views of the European
Commission and/or CHAFEA or any other body of the European
Union. The European Commission and/or CHAFEA do not guarantee
the accuracy of the data included in this report nor do they accept respon-
sibility for any use made by third parties thereof.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a link
to the Creative Commons license, and indicate if changes were made.
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