Innovative Energy Technologies in Road Transport in Selected EU Countries

Abstract

The primary aim of this study was to assess and classify selected EU countries to groups differing in terms of the degree of implementation of innovative energy technologies to alleviate adverse externalities in road transport. This aim was realised using three groups of research methods: collection of empirical data, data processing and presentation of study outcomes. When collecting the research material, the authors used the method of critical literature review and the documentation method. The research material was processed using the agglomerative clustering technique, which was one of the hierarchical clustering methods. The distance between objects (here, selected EU countries) was determined based on the Euclidean distance. The outcome of this analysis was a dendrogram, which constitutes a graphical interpretation of obtained results. The study was conducted on 21 EU countries. The analyses covered the years 2013–2019. The sources of materials included literature on the subject and the Eurostat data. The problem of innovative energy technologies in road transport is presently of considerable importance. This results from the current situation related to human activity. As a result of the conducted cluster analysis, groups were distinguished based on differences in the use of innovative energy technologies alleviating negative externalities generated by road transport. The first group comprised Sweden, the Netherlands and Finland. Compared to the other groups, this group was distinguished by the highest values of four indexes, i.e., the share of renewable energy sources used in transport in 2019, the share in the market of electric passenger vehicles in 2019, the share in the market of electric lorries in 2019, as well as the share in the market of hybrid automobiles in 2019. Countries which participated the least in the elimination of negative externalities generated by road transport included Romania, Hungary, Greece, Poland, Latvia and Estonia.

1. Introduction

Innovations in the energy sector are necessary for a variety of reasons, including climate change, increasing the availability of safe and affordable energy and the growing use of renewable energy sources. Transport is a unique sector of the economy, contributing to socio-economic development, but also generating external costs. The increasing number of vehicles used in road transport in the EU, depletion of fossil fuel resources and environmental concerns have all contributed to the search for alternative solutions to be implemented as innovative energy technologies in road transport. This type of transport in the European Union countries is one of the most dynamically developing sectors of the economy and, as a result, is also the one with the greatest environmental impact.

The problem of innovative energy technologies in road transport has been investigated by numerous researchers. These analyses typically concerned the use of renewable energy sources in road transport [1,2,3,4,5], implementation of innovative energy technologies by selected countries [6,7], various directions of development of innovative energy technologies, e.g., use of electric vehicles [8,9], hydrogen vehicles [10,11] and connected and autonomous vehicles [12,13]. Very few publications are available in the literature on the subject concerning comparisons of this problem at the international scale.

The aim of this paper is to assess and classify selected EU countries into groups differing in terms of the use of innovative energy technologies to alleviate negative externalities in road transport. In order to realise this aim, a set of the following research tasks was established: (1) to conduct a review of Polish and foreign literature concerning innovative energy technologies limiting negative externalities in road transport, (2) to present changes in the use of renewable energy sources in road transport in the EU countries in the years 2013–2019; (3) to identify leaders among the EU countries in the use of innovative energy technologies in road transport.

The authors also undertook verification of the following research hypothesis:

Hypothesis 1 (H1). 

Only a few EU member countries can be described as leaders in the use of innovative energy technologies in road transport.

This paper is composed of five parts. The first chapter, constituting the Introduction, presents a justification for the selection of the study subject, the main aim and research tasks. The next chapter gives information on the material and adopted research methods. The third part provides a review of literature on innovative energy technologies alleviating negative externalities in road transport. The fourth part presents the results of conducted analyses, along with the discussion concerning results reported by other authors. The final part of the paper comprises concluding remarks together with the presentation of limitations of this study, while also suggesting proposals for further directions of research on the subject.

2. Literature Review

Innovations are a concept that was introduced for the first time in economic sciences by J.A. Schumpeter in 1912. He distinguished [14]:

• Manufacturing novel products or improvement of existing products;
• Use of new production methods;
• Opening of a new sales market;
• Development of a novel type of product;
• Acquisition of new sources of raw materials or intermediate goods;
• Creation of a new branch organisation.

In the approach proposed by that author, we deal with technological, organisational and economic changes in the phenomenon of entrepreneurship, as indicated by both the process and the innovative character of these actions [15]. Innovations were also discussed by [16,17,18]. The best known and most commonly used definition of innovation is that published in the Oslo Manual in 2005 [19,20], in which innovations are defined as introducing new or considerably improved products on the market or finding better ways to launch new products on the market. Innovation is related to innovativeness [21]. Innovative activity is a process of developing innovations through scientific, technological, organisational, financial and marketing activities. Some of those mentioned above are innovative by themselves, or they are not novelties, but they constitute an indispensable element for the implementation of an innovation. For innovations to be feasible, research and development activity is required [22].

Both technological and systemic innovations play a considerable role in the process of energy transition. Priorities need to be innovations in the use of transport, industry and the construction sectors. Particular attention should be focused on the application of advanced technologies in energy storage, smart charging systems for electric vehicles, or establishment of small, local grids. Innovations in the energy sector are necessary in view of climate change, increased availability of safe and affordable energy, as well as the growing use of renewable energy sources (…) [23]. Innovative energy technologies in the transport sector are related to increased energy efficiency provided by advanced technical solutions consisting of the use of alternative fuels. At present, the focus is on the implementation of zero-emission solutions in transport, i.e., the use of electric energy and hydrogen to power vehicles [24]. Similar solutions are used, e.g., in China (development of electric vehicle (EV) technology [25]. The discussed problem is of paramount importance and of topical interest [26]. It has been presented by numerous authors [27,28].

Transport plays a highly important and ever-increasing role in many aspects of functioning of contemporary societies, as it facilitates transport of humans and goods within countries and regions, as well as between them [29]. Transport is developed mainly thanks to the growing domestic and international trade. In turn, passenger transport is connected primarily by commuting and business trips, as well as domestic and international tourism. Within the last several decades, people have spent on average from 1 to 1.5 h daily commuting or travelling [30]. However, increasing income levels and growing accessibility of passenger transport at higher speeds, along with its increasing affordability, have all contributed to the development of societies in which people travel on business and for pleasure over ever-growing distances. The development of passenger transport related to business activity and transport of goods has been considerably facilitated by processes of economic globalisation. Obviously, the impact of these processes on transport is multifaceted. The limiting factor for passenger transport connected with commuting is connected to the increasingly common online work. This phenomenon was markedly intensified during the COVID-19 pandemic. Additionally, events termed black swans and grey rhinos also exert a considerably impact on globalisation processes, contributing to economic slowdown and limiting trade, thus reducing the scale of transport, particularly transport of goods.

In the EU in 2018, transport accounted for approx. 6.3% of gross domestic product (GDP), employing almost 13 million people whilst also acting as the main source of income in several EU member countries [31]. In 2019, the EU road systems were used by 242 million passenger cars (which corresponds to more than one automobile per every two people). The car ownership index was highest in Luxembourg (681 cars per 1000 inhabitants), followed by Italy, Cyprus, Finland and Poland (all with over 600), while in Hungary it was fewer than 400 per 1000 inhabitants (390), similar to Latvia (381) and Romania (357) [32].

Land transport in the EU (excluding pipelines) in 2019 is estimated at approx. 2300 billion tonnes/kilometres. A vast proportion of this number (76.3%) was connected with road transport, with railways at 17.6% and inland waterways accounting for 6.1%. Rail transport accounted for most inland transport of goods in Latvia and Lithuania (73.6% and 67.4%, respectively), while inland waterways accounted for 42.7% freight in the Netherlands [32]. The outbreak of the COVID-19 pandemic contributed to a marked decline in road transport. This was particularly evident in the case of public transport, which dropped by as much as 80–90% in major European cities in the middle of 2021 [33]. Nevertheless, in the long-term perspective, transport—including road transport, will continue to develop and its volume will increase.

Although mobility provides a variety of advantages for its users, it is also connected to social costs. T. Kamińska [34] indicated the social benefits and costs of transport (Figure 1).

According to the OECD, the effects of transport may be divided into [35]:

(1)

Benefits for users:

• Changes in the duration of travel;
• Change in the maintenance costs of vehicles;
• Effect on traffic safety.

(2)

Effects of transport networks:

• Creation of new traffic options;
• Intrasector shifts in demand;
• Improved reliability of transport;
• Quality of transport services.

(3)

Socio-economic effects:

• Changes in availability;
• Changes in employment within the region;
• Changes in efficiency and production;
• Changes in social integration;
• Changes in property value.

(4)

Environmental effects.

In terms of sustainable development for the economy, costs incurred by society in relation to provision of transport costs are essential. They are termed social costs, and are divided into two categories: internal and external (Figure 3). Internal costs result from transport activity and are incurred by the users who generate them. Costs are also incurred by society, i.e., time losses; health problems resulting from air pollution or noise; and carbon dioxide emissions, which lead to climate change [36]. They are defined as externalities or negative external effects. In terms of sustainable development, costs incurred by society in relation to transport services, defined as externalities or negative externalities, are crucial for the economy. This problem has been widely discussed in economic literature [37,38,39,40,41]. According to W. Rothengatter, externalities include, among other things, “involuntary interactions between entities jointly using a given resource, to which ownership right has not been established” [35,41], while E. Mishan clarified that they are generated unconsciously and constitute unintentional or accidental by-products of purposeful activity [35,42]. J. Poliński indicated that they are “all costs related to the execution of a transport service, which are not incurred by the provider of this service, or by the purchaser, but by a third party, here it is the society” [43,44]. Literature on the subject presents many divisions of external costs of road transport. Most typically, they are divided into four categories (Figure 2).

The greatest share in external costs of transport comprises environmental costs, which make up approx. 58%. They include costs related to the elimination of air pollution, changes in the natural environment and landscape, climate change associated with CO₂ emission, costs related to alleviation of environmental damage, and costs of actions aiming to reduce noise. The second item comprises costs related to accidents, which make up 29% of costs. These are costs not covered by insurance premiums, e.g., material losses, medical costs, administrative costs, etc. The share of infrastructure costs accounts for 12%, while that of congestion is 1% (Figure 3).

The latter include greenhouse gas emissions, air and water pollution, as well as noise. Road transport, next to heating, is the primary factor responsible for the low air quality in European cities, and it ranks second as the source of greenhouse gases in Europe. In view of the above, it is obvious that reaching sustainable social development goals requires addressing the challenges related with the transport system as a whole, particularly road transport [46]. Many researchers point to the need to rationalize the energy consumption of road transport towards sustainable development [47,48]. For many years, the European Union has undertaken actions for sustainable development in the energy sector. This sector has been the most important issue since the beginning of integration processes in Europe [49]. In the following years, the European Union initiated works on the establishment of the single energy market, identifying priorities for this policy [50,51]. The EU defined goals related to climate and energy, within which the member countries declared that they would reduce greenhouse gas emissions by 2030, increase the share of renewable energy sources, and improve energy efficiency and the potential to transfer electricity generated within the EU to the other EU countries using the system of interconnections [52]. The recently announced EU Green Deal assumes that the EU countries are to become zero emitters, i.e., climate neutral, by 2050 [53]. In the Strategy for Sustainable and Smart Mobility—European transport on the road to the future, announced in 2020 [54], it was shown that environmentally friendly mobility has to become a new licence for the development of the transport sector. This Strategy indicates that a 90% reduction in emissions from the transport sector by 2050 is the primary goal. EU countries have to implement comprehensive transformation towards a sustainable and smart future: (1) make all types of transport more sustainable, (2) ensure extensive availability of sustainable alternative solutions in the system of multimodal transport, and (3) implement adequate incentives promoting such a transformation [53]. The following were indicated as intermediate goals:

(1)

By 2030:

• A minimum of 30 million zero-emission vehicles will be introduced onto European roads;
• 100 European cities will be climate neutral;
• High-speed rail transport will increase twofold;
• Regular public transport up to 500 km should be CO₂ emission neutral within the EU;
• Extensive implementation of automated mobility;
• Preparation for zero-emission ships to be on the market.

(2)

By 2035:

• Preparation for launching of zero-emission large aircraft onto the market.

(3)

By 2050:

• Almost all passenger vehicles, transport vehicles, buses and new heavy-duty lorries will be zero emission;
• Rail freight will increase twofold;
• Traffic of high-speed trains will increase threefold;
• Multimodal Trans-European Transport Network (TEN-T) will be equipped for sustainable and smart transport, ensuring fast connections.

It will operate within the comprehensive network.

The goals established for the EU transport sector are challenging. A reduction in greenhouse gas emissions by the European transport may be attained by:

(1)

Limiting the energy demand of transport, e.g., modal shifts (individual private transport towards public transport, air transport towards high-speed rail, road transport towards waterway transport), through remote work, changes in prices, operational improvements or other solutions related to demand.

(2)

Improvement of efficiency through electrification, hybrid systems and upgraded engines.

(3)

Transition to energy carriers with lower carbon dioxide emissions, such as renewable energy or sustainable biofuels, e.g., bioethanol, biodiesel, biomethane, hydrogenated vegetable oil (HVO) and fatty acid methyl esters (FAME) [55].

As a result, decision makers face challenges requiring them to pressure this sector to reduce its externalities, while simultaneously maintaining the economic model it helps to support [56]. In this context, it is clear that top-level strategic actions aiming to regulate road transport typically promote implementation of innovative technological solutions, which may contribute to attaining both these aims. Digital solutions based on connectivity and automation of vehicles, as well as the paradigm of the sharing economy together with the transition to low-emission vehicle technologies (particularly electric vehicle and hydrogen vehicle technologies) are central elements of the European vision of smart and more eco-friendly transport [57]. Innovativeness in transport is related with the search for methods to more efficiently utilise financial, management and organisational resources. This is a particularly important problem in view of the growing transport needs and limited resources. According to forecasts in Poland and the European Union, in the near future, innovativeness in transport should focus on the following problems [58]:

• Transport methods and technologies;
• Planning, organisation and management of transport systems;
• Financing of transport in relation both to the maintenance and modernisation of existing resources, as well as new infrastructure, vehicle fleets and other resources.

One of the innovation priorities in road transport may include development of battery electric vehicles (BEV) [59], which are becoming increasingly important, particularly in the privately owned automobile market. A battery electric vehicle (BEV) is an electric vehicle (EV), which is powered solely by the energy stored in batteries, with no other source (e.g., hydrogen, an internal combustion engine, etc.). Vehicles of the BEV type use an engine and an electric system instead of the internal combustion engine (ICE). These vehicles collect all the power from batteries and use it to power their engines, which additionally aids in powering their wheels [60]. A significant component of costs in these vehicles is generated by batteries. Innovative designs for batteries on the one hand aim at reducing the adverse environmental impact, especially at the stage of their production and decommissioning, while on the other hand, innovative solutions focus on increasing the energy density and power of batteries, particularly in vehicles of medium and large load-carrying capacity. In the near future, this may be reached thanks to upgrades in existing lithium-ion technologies. Over a longer time, prospective new chemical technologies may replace lithium-ion batteries, ensuring further reduction of costs and improvement of their efficiency [61].

An important role in the decarbonisation of the lorry segment may be played by flexible-fuel vehicles (FFV). In view of doubts related to the possible zero-emission technologies for lorries of large load-carrying capacity, it is crucial to develop options for combustion engines. Key innovations in this respect are related to improved fuel savings and reduction in harmful emissions. A limited hybrid type (e.g., the 48 V system, regenerative braking, also called recuperation) is particularly effective at reducing both high emissions and fuel consumption in vehicles equipped with combustion engines, which frequently stop and start to move again [61]. At present, various types of dual-fuel vehicles are produced. Among them, we may distinguish, e.g., vehicles using petrol and LPG, hydrogen and petrol or petrol and diesel oil. Dual-fuel vehicles are low-cost burdens for the development of the hydrogen infrastructure prior to the introduction of fuel-cell-powered vehicles. They are considered to be a transition stage for vehicles powered with these cells, since they use the same fuel storage systems, safety systems, valves, safety system controls, etc. Moreover, this technology may be replicated on various engine platforms while incurring relative low costs [62].

Novel engine architecture designs may bring about a greater increase in performance and efficiency parameters, although they are presently in their preliminary stages. Moreover, further integration of components is required in exhaust after-treatment systems to improve both their energy efficiency and effective removal of pollutant emissions.

In the near future, a particularly important role may be played by electric vehicles equipped with fuel cells. Vehicles with fuel cells powered by pure hydrogen are zero-emission vehicles, as in reality, the only local emission is water vapour. However, in this case, it is important to consider the complete fuel cycle, i.e., emissions related to the production, transport and supply of fuel. The basic primary source for the production of hydrogen is crucial for vehicles to be considered environmentally friendly. Hydrogen produced from renewable energy (e.g., wind or solar energy combined with electrolysis) and used in fuel cells may considerably reduce emissions. The latest studies concerning alternative fuels indicate that vehicles powered with fuel cells using hydrogen are the most promising technology in terms of reducing pollutant emissions in the fuel cycle [63]. Fuel cells are considered increasingly promising, particularly as a solution limiting pollutant emissions by lorries. They offer a similar range of distance covered as conventional diesel engine vehicles; however, the high costs of its implementation are the main drawback of such a solution. For this reason, it is also necessary to implement innovations aiming at decreasing costs of fuel cells and the hydrogen tank, since these elements are, to a considerable degree, responsible for the total cost of fuel-cell-powered vehicles. These costs may be decreased by developing large-scale production, applying greater automation. In turn, fuel cells may play an increasingly important role in the decarbonisation of vehicles of medium and large load-carrying capacity, considering the relatively high ratio of generated energy to the mass of hydrogen in comparison to batteries. This aspect was also discussed by [64,65]. It was stated that Poland has huge potential for the use of hydrogen as an alternative to conventional fuels used in the transport sector [66]. This innovative application in transport has been described by many authors [67].

A considerable challenge which may possibly change the entire infrastructure of land transport and travel is related to innovations leading to introduction of connected and autonomous vehicles. New vehicle technologies in this respect promise solutions in which sensors and specialist software will replace people as drivers [68]. A priority in the development of CAV vehicles is to create safety foundations based on this technology. Innovative technologies, validation and testing procedures are crucial for the establishment of safety standards and lowering of implementation costs for this technology [63]. Connected Autonomous Vehicles, i.e., those which are both combined and autonomous, are a technologically powerful area of potential great importance in the future, which has been shown in the publications of many authors [69,70,71,72].

3. Material and Methods

Objects for this study were selected based on purposive sampling. They are countries of the European Union (EU), for which necessary data were available, i.e., Austria (AT), Belgium (BE), Czechia (CZ), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (GE), Greece (GR), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (SE) and Sweden (SW). Thus, the population sample consisted of 21 out of the 27 EU member countries. For the remaining six, the relevant variables (x₁, x₂, x₃, x₄, x₅, x₆, x₇) were not available. These variables will be described later in this section.

When selecting diagnostic variables, the authors used their experience gained in the course of previous studies [44,73], as well as availability of current data (2019 was the last year for which a complete set of data was available). Since this article concerns the use of innovative energy technologies contributing to externalisation of negative externalities in road transport, this study included:

• x₁—the share of renewable energy sources used in transport in 2019 (in %);
• x₂—the share in the market of electric passenger vehicles in 2019 (in %);
• x₃—the share in the market of electric lorries in 2019 (in %);
• x₄—the share in the market of hybrid passenger vehicles in 2019 (in %);
• x₅—the share in the market of hybrid lorries in 2019 (in %);
• x₆—average CO₂ (carbon dioxide) emission from new automobiles in 2019 (in g CO₂/km);
• x₇—average CO₂ emission from new lorries in 2019 (in g CO₂/km).

In order to assess the selected variables, a Pearson correlation matrix for these variables was established (

Table 1. A Pearson correlation matrix for the investigated variables.

Variable	x1	x2	x3	x4	x5	x6	x7
x1	1.00	0.81 *	0.76 *	0.60 *	0.37	0.10	0.28
x2	0.81 *	1.00	0.76 *	0.53 *	0.34	−0.27	0.27
x3	0.76 *	0.76 *	1.00	0.38	0.37	−0.04	0.24
x4	0.60 *	0.53 *	0.38	1.00	0.29	0.15	0.22
x5	0.37	0.34	0.37	0.29	1.00	0.02	0.01
x6	0.10	−0.27	−0.04	0.15	0.02	1.00	0.56 *
x7	0.28	0.27	0.24	0.22	0.01	0.56 *	1.00

* Correlation coefficients are significant with p < 0.0500. Source: own study.

). An excessively high correlation between characteristics may indicate multicollinearity. For this reason, the threshold for the correlation coefficient was set at (r* = 0.9) [74]. Due to the low values of coefficients in this study, no variable was eliminated.

It should be mentioned here that the authors made an attempt at a comprehensive approach to the analysed phenomenon. In previous studies, no division was made into types of vehicles (passenger cars vs. lorries) or types of engines. In view of the above, the authors believe that the presented analysis will fill the gap in current knowledge on the subject.

Within this study, three groups of research methods were applied: (1) collection of empirical material, (2) data processing, as well as (3) presentation of research results.

When collecting research material, the authors used the method of critical literature review and the documentation method. This article presents results of both Polish and foreign studies concerning negative externalities generated by road transport, as well as innovations introduced by the energy sector aiming at their externalisation. Selected legal regulations were also presented in relation to the investigated problem. In turn, the documentation method consisted of the use of reports produced, e.g., by the OECD (Organisation for Economic Cooperation and Development) or ACEA (the European Automobile Manufacturers Association) in order to collect required data.

When processing the research material, the authors applied the agglomerative clustering technique, which is a representative of the hierarchical method. The distance between the objects (here, selected EU countries) was determined based on the Euclidean distance. In turn, to estimate the distance between clusters, the Ward method was used. This method differs from the others, as it uses the analysis of variance approach, i.e., it attempts minimisation of the sum of squares of deviations within the clusters. The Ward method is considered to be efficient, although its application leads to the formation of small-sized clusters [75]. The analysis provided a dendrogram, constituting a graphical interpretation of obtained results. The method adopted has previously been used to solve similar problems, see: Gostkowski et al. [76], Kacperska et al. [73].

It needs to be stressed here that the variables included in this study were expressed in different units. For this reason, prior to their analysis, the clusters were normalised. It results from the analysis of literature on the subject that the best formal properties among the normalisation methods are found for zero unitisation [77]. Normalisation formulas for the variables are stimulants, i.e., those for which the higher the value, the better, and the variables are destimulants, i.e., those for which the lower the value, the better, took the following form:

$${\mathrm{Z}}_{\mathit{ij}}=(x_{\mathit{ij}}-{\min }_{\mathit{i}}{x}_{\mathit{ij}})/({\max }_{\mathit{i}}{x}_{\mathit{ij}}-{\min }_i{x}_{\mathit{ij}}),x_j\in S$$

(1)

$${\mathrm{Z}}_{\mathit{ij}}=({\max }_i{x}_{\mathit{ij}}-x_{\mathit{ij}})/({\max }_i{x}_{\mathit{ij}}-{\min }_i{x}_{\mathit{ij}}),x_j\in D$$

(2)

where:

• Z_ij—normalised value of j-th variable for i-th object (here, an EU country).
• x_ij—value of j-th variable in i-th object;
• max_i x_ij–min_i x_ij—range of j-th variable.

The set of stimulants was denoted as S, while that of destimulants was denoated as D. The former set comprised variables x₁, x₂, x₃, x₄ and x₅, while the latter set consisted of x₆ and x₇.

Using the formulas given above, the normalised values from the range of <0;1> were obtained. In this case, for variables which were stimulants, the value of 1.0 was given for the EU countries, in which case, the following variables—the share of use of renewable energy sources in transport in 2019, the share in the market of electric passenger vehicles in 2019, the share in the market of electric lorries in 2019, the share in the market of hybrid passenger vehicles in 2019 and the share in the market of hybrid lorries in 2019—were the highest. In turn, in the case of destimulants, the value of 1.0 was given to the EU countries, for which the variables: average CO₂ emission from new passenger vehicles in 2019 and average CO₂ emission from new lorries in 2019 were the lowest.

The results of these analyses are presented applying the descriptive, table and graphical methods. All calculations were made with the use of the MS Office 365 package and STATISTICA software.

4. Results and Discussion

As was observed earlier, the most significant innovations contributing to the elimination of negative externalities of road transport (e.g., g CO₂/km) include renewable energy sources, as well as low-emission vehicles (electric and hybrid cars).

It needs to be mentioned here that in recent years, the use of renewable energy sources in transport in the EU countries increased (in 2013 the average share of use of renewable energy sources was 6.89%, while in 2019 it was 9.22%) (

Table 2. Changes in the use of renewable energy sources in transport in selected EU countries in the years 2013–2019.

Country	2014	2015	2016	2017	2018	2019	2014 = 100
AT	10.98	11.41	10.58	9.70	9.93	10.05	91.51
BE	5.85	3.92	6.03	6.64	6.71	6.82	116.63
CZ	7.00	6.54	6.50	6.62	6.56	7.84	112.06
DK	6.56	6.43	6.73	6.94	6.92	7.11	108.45
EE	0.42	0.41	0.43	0.42	3.32	6.24	1493.54
FI	24.12	24.56	8.81	18.67	14.77	14.32	59.36
FR	8.25	8.37	8.41	8.77	8.96	9.25	112.11
GE	6.90	6.57	7.01	7.03	7.94	7.63	110.58
GR	1.33	1.10	1.62	4.00	4.11	4.05	305.35
HU	7.00	7.17	7.77	7.73	7.75	8.06	115.08
IE	5.20	5.94	5.16	7.44	7.19	8.92	171.35
IT	5.02	6.51	7.41	6.48	7.66	9.05	180.22
LV	4.08	3.64	2.45	2.27	4.73	4.55	111.75
NL	6.56	5.60	4.76	5.84	9.48	12.33	187.81
PL	6.32	5.69	3.97	4.23	5.72	6.20	98.12
PT	3.67	7.43	7.65	7.91	9.04	9.09	247.86
RO	4.68	5.49	6.17	6.56	6.34	7.85	167.83
SK	7.95	8.63	7.77	6.95	6.99	8.31	104.49
SI	2.88	2.24	1.60	2.57	5.48	7.98	277.57
SE	1.02	1.09	5.17	5.80	6.94	7.61	743.16
SW	18.83	21.49	26.56	26.84	29.70	30.31	160.95
Min.	0.42	0.41	0.43	0.42	3.32	4.05	59.36
Average	6.89	7.15	6.79	7.59	8.39	9.22	241.70
Max.	24.12	24.56	26.56	26.84	29.70	30.31	1493.54

Source: own study.

). In the analysed period, the greatest increment in the consumption of renewable energy sources in transport was recorded in Estonia, Portugal, Spain and Greece. The countries in which a decrease was observed in this respect included Austria, Finland and Poland.

In the case of the petrol market (including the market of low-emission automobiles) in the years 2014–2019, the following changes could be observed (

Table 3. New cars registered in the EU depending on the type of fuel in the years 2013–2019.

Engine Type	2014	2015	2016	2017	2018	2019	2014 = 100
Petroleum	5,358,452	6,036,564	6,800,116	7,563,739	8,521,418	8,964,034	167.29
Diesel	6,599,462	7,039,611	7,175,630	6,617,051	5,402,079	4,650,558	70.47
Electrically charged including:	69,958	148,027	155,634	218,083	300,258	458,915	655.99
• Electric batteries;	37,517	59,165	63,479	97,667	147,428	284,812	759.15
• Plug-in hybrids.	32,441	88,862	92,155	120,416	152,830	174,103	536.68
Hybrid Electric Vehicles	176,525	218,755	278,729	426,769	598,462	896,785	508.02
Fuel cell	38	176	123	253	266	535	1407.89
Natural gas (CNG)	97,214	78,511	57,609	49,553	65,023	68,581	70.55
Other (LPG + E85)	141,452	140,321	118,430	156,710	164,270	187,378	132.47

Source: own study.

):

• This market increased by 3.6 million cars, reaching 9 million cars in 2019;
• In the same period, the number of sold diesel engine automobiles dropped by almost 2 million;
• The number of electric cars within the 6-year period increased to 458,915 vehicles;
• In 2019, the number of sold hybrid electric vehicles was 720,260 higher compared to the year 2014.

The further part of this study presents the results of a cluster analysis, which was conducted based on values of variables concerning the year 2019. In the first step of these analyses, the variables were subjected to zero unitisation. Its results are given in

Table 4. Normalised values of variables included in this study.

Country	x1	x2	x3	x4	x5	x6	x7
AT	0.23	0.22	0.36	0.15	0.00	0.23	0.10
BE	0.11	0.20	0.16	0.04	0.07	0.34	0.35
CZ	0.14	0.01	0.04	0.03	0.00	0.13	0.07
DK	0.12	0.27	0.28	0.15	1.00	0.61	0.55
EE	0.08	0.00	0.00	0.49	0.00	0.09	0.47
FI	0.39	0.45	0.12	1.00	0.07	0.52	0.23
FR	0.20	0.17	0.64	0.19	0.29	0.56	0.64
GE	0.14	0.18	0.84	0.24	0.07	0.06	0.06
GR	0.00	0.01	0.00	0.28	0.00	0.51	0.48
HU	0.15	0.11	0.08	0.28	0.00	0.05	0.43
IE	0.19	0.26	0.48	0.55	0.00	0.55	0.51
IT	0.19	0.04	0.20	0.27	0.50	0.40	0.55
LV	0.02	0.01	0.00	0.44	0.00	0.16	0.33
NL	0.32	1.00	0.64	0.34	0.00	1.00	0.04
PL	0.08	0.01	0.04	0.39	0.00	0.04	0.12
PT	0.19	0.37	0.20	0.13	0.00	0.69	1.00
RO	0.14	0.04	0.04	0.17	0.00	0.26	0.47
SK	0.16	0.01	0.08	0.13	0.00	0.00	0.00
SI	0.15	0.04	0.12	0.00	0.00	0.28	0.21
SE	0.14	0.07	0.32	0.54	0.21	0.35	0.69
SW	1.00	0.75	1.00	0.53	0.00	0.39	0.40

Source: own study.

. On their basis the following conclusions may be drawn:

• Sweden was the country characterised by the highest share (in %) of use of renewable energy sources in transport and the share (in %) in the market of electric lorries.
• The greatest share (in %) in the market of electric passenger vehicles was recorded in the Netherlands, while it was lowest in Estonia.
• In as many as 14 countries (AT, CZ, EE, GR, HU, IE, LV, NL, PL, PT, RO, SK, SI, SW), the share (in %) in the market of hybrid lorries was 0.00.
• The lowest average CO₂ emissions (in g CO₂/km) from new passenger cars were recorded in the Netherlands, while from new lorries the lowest emissions were recorded in Portugal.

The aim of the conducted cluster analysis was to classify selected EU countries into groups differing in the degree of use of innovative energy technologies alleviating negative externalities generated by road transport. The distinguished groups should meet the criteria of internal cohesion, i.e., homogeneity and external isolation (heterogeneity). Figure 4 presents a dendrogram showing the obtained hierarchy of clusters. The horizontal axis represents countries constituting the study sample, while the vertical axis indicates the distance of the linkage, in this case the Euclidean distance.

In order to determine the optimal number of clusters, the graph of agglomeration was used, which presents the distance between clusters at the time of their grouping (Figure 5). The cut-off point was established at the point of a sudden increase in the distance of linkage. In the analysed case, it was between step 18 and 19. Their ordinate corresponds to the distance between linkages amounting to approx. 1.40. For this reason, it was possible to distinguish four clusters (see the broken red line in Figure 4). Their characteristics are given in

Table 5. Mean values of variables included in this study at the cross-section of four clusters (legend: green colour marks the highest values for stimulants and the lowest for destimulants; red colour denotes the lowest values for stimulants and the highest values for destimulants).

Variable	Cluster 1	Cluster 2	Cluster 3	Cluster 4
x1	18.98%	8.50%	6.16%	8.11%
x2	11.07%	3.18%	0.75%	1.92%
x3	1.57%	0.98%	0.17%	0.77%
x4	9.53%	6.07%	6.47%	3.85%
x5	0.03%	0.47%	0.00%	0.03%
x6	111.13 g CO2/km	114.95 g CO2/km	126.95 g CO2/km	127.33 g CO2/km
x7	166.13 g CO2/km	150.50 g CO2/km	160.40 g CO2/km	169.53 g CO2/km

Source: own study.

.

Cluster 1 comprises three countries: Sweden, the Netherlands and Finland. Compared to the others, this group was characterised by the highest values of four indexes, i.e., the share of use of renewable energy sources in transport in 2019 (on average, 18.98%), the share in the market of electric passenger vehicles in 2019 (on average, 11.07%), the share in the market of electric lorries in 2019 (on average, 1.57%), as well as the share in the market of hybrid passenger vehicles in 2019 (on average, 9.53%). Moreover, in those countries in 2019, new lorries emitted the lowest amounts of g CO₂/km, i.e., 111.13. Thus, it may be stated that this cluster consists of the countries which used innovative energy technologies to the greatest degree to alleviate negative externalities generated by road transport. It needs to be stressed here that in particular, Sweden and Finland, as a rule, are superior to the other EU countries in the realisation of the Green Deal policies. Based on the study conducted by Kisielińska et al. (2021) using the TOPSIS analysis Luxembourg, Austria and Sweden were definite leaders in the use of renewable energy sources in road transport. High values of these indexes were also observed in Finland, France and Germany. This may result, e.g., from the fact that by 2040, Sweden intends to use 100% renewable energy sources [78]. In turn, in Finland, the National Energy and Climate Strategy has been in force since 2017 [79], supporting transition to renewable energy sources (RES). Based on the results obtained, the authors’ hypothesis was confirmed.

In turn, cluster 3 was the cluster which was distinguished by the lowest values of variables x₁, x₂, x₃, x₅ and the highest value of variable x₅, and it was formed by Romania, Hungary, Greece, Poland, Latvia and Estonia. It may be stated that these are the countries which were least involved in the alleviation of negative externalities generated by road transport. For example, in 2019, Greece was distinguished by the lowest share of renewable energy sources used in transport (4.05%), Estonia by the lowest share in the market of electric passenger vehicles (0.30%), while Latvia, similar to Greece and Estonia, had the lowest share in the market of electric lorries (0.10%).

We also need to stress the fact that in 2019, countries such as Germany, Slovakia, Czechia, Slovenia, Belgium and Austria (cluster 4) recorded the highest CO₂ emissions from new passenger cars and from lorries in (g CO₂/km). In the case of Slovakia, it was 133.4 g CO₂/km for new passenger vehicles and 174.3 g CO₂/km for new lorries. At the same time, these were the highest values of these indexes for the analysed group of EU countries.

5. Conclusions

The use of innovative energy technologies in road transport became one of the main goals realised by individual EU countries. The number of cars is growing from year to year, resulting in increasing environmental pollution, while deposits of fossil fuels are being depleted.

The aim of the article was to assess and divide selected EU countries into groups differing in the degree of use of energy innovations offsetting negative externalities in road transport. In pursuit of the objective, the national and international literature on energy innovations mitigating negative externalities in road transport was reviewed, changes in the use of renewable energy sources in road transport in EU countries between 2013 and 2019 were presented, and leaders among EU countries in the use of energy innovations in road transport were identified.

This article based on the conducted cluster analysis classified selected EU countries to groups differing in the degree of use of innovative energy technologies alleviating negative externalities generated by road transport. Three countries proved to be leaders—Sweden, the Netherlands and Finland. Compared to the other groups, this group was distinguished by the highest values of four indexes, i.e., the share of use of renewable energy sources in transport in 2019 (on average, 18.98%), the share in the market of electric passenger vehicles in 2019 (on average, 11.07%), the share in the market of electric lorries in 2019 (on average, 1.57%), and the share in the market of hybrid passenger vehicles in 2019 (on average, 9.53%). Countries which had the lowest indexes of the clusters included Romania, Hungary, Greece, Poland, Latvia and Estonia. Thus, the hypothesis stating that only a few EU member countries can be described as leaders in the use of innovative energy technologies in road transport was confirmed.

Based on the conducted study, it may be stated that (1) at present, introduction of innovative energy technologies in road transport is the most advantageous option in terms of alleviating negative externalities generated by road transport, (2) based on the analyses, four groups of clusters were distinguished, (3) a small number of countries (Sweden, the Netherlands and Finland—cluster 1) use innovative solutions (electric passenger vehicles, hybrid passenger vehicles), (4) in 2019, some countries (cluster 4) (Germany, Slovakia, Czechia, Slovenia, Belgium and Austria) were distinguished by the highest CO₂ emissions from new passenger cars and from new lorries, and (5) in order to increase the use of innovative energy technologies in road transport, it is necessary to present their advantages both for humans and the environment.

Despite the realisation of the aim of this article, it needs to be stressed that our study nevertheless has some limitations. The analysis applying cluster analysis was conducted on only three indexes, which were selected based on available data (purposive sampling). Moreover, the division into five groups was applied; as a result, the range between relative closeness indexes between the groups was not identical. Several limitations of the method used should also be borne in mind. Hierarchical clustering methods do not require a prior indication of the number of clusters, but they do require a lot of computing power. The clusters are usually not formed on the basis of any theoretical part. The clusters are rather formed at random. Furthermore, deciding on the right number of clusters is very difficult. Indicating the correct intersection point of a dendrogram requires great precision.

Despite certain limitations, our study constitutes an interesting starting point for future studies. The methodology used in this article may be used to assess the investigated phenomenon in a few or more than a dozen years. Another suggestion would be to use our approach but apply different methods in order to compare obtained results.