Scenarios of Carbon Capture and Storage Importance in the Process of Energy System Transformation in Poland

Abstract

One of the most important issues in the coming years will be the decarbonisation of the European Union member states’ energy systems. The majority of the abstract requires modification. I propose that the first sentence of the abstract in the manuscript should better emphasize the formulation of the problem. The remaining part and any corrections were made by the author. Scenarios of the importance of CCS in the process of transformation of energy systems in Poland. One of the most important issues in the coming years will be the transformation of the energy systems of the European Union’s member states, which will require the development of appropriate technological solutions. The research presented here analyses the importance of CCS in energy transformation. This article proposes adapting the energy transformation method to the structure of the energy mix and conditions prevailing in a specific country. Poland was adopted as an example for analysis due to its exceptionally complicated situation, taking into account the structure of energy production. For this purpose, an expert opinion survey was conducted. Both measurable variables, such as the volume of CO₂ emissions and EU ETS prices, and a qualitative variable, i.e., the impact of the political environment on the development of CCS, were introduced to the constructed model. The model allowed us to construct three scenarios describing alternative visions for the future development of CCS: optimistic, pessimistic, and neutral, taking into account different conditions in which CCS can develop. The use of fuzzy sets allowed us to eliminate the most serious drawback of planning scenarios based on expert knowledge, which is the subjectivity of their judgments. This research showed that stable conditions of the political environment and predictable legal regulations will be crucial for the application of CCS in the Polish energy sector. The prepared scenarios will enable a quick response and accurate decisions under various conditions of the turbulent environment. This will facilitate the preparation of energy strategies. The scenarios indicate what combinations of variables, under given environmental conditions, of CCS will be of great importance in the energy transformation, and when it may give way to other technologies. In addition, the scenarios, and especially their visualisation, are extremely valuable for stakeholders, because they will allow them to observe the potential development of the situation under known conditions of the political environment, prices, and CO₂ emissions. They enable understanding the dependence of the importance of CCS in the changing environment. They also enable the detection of critical points for the development of CCS, which, as a result of recent geopolitical events, may be of key importance in the near future for ensuring the energy and military security of Poland and the EU.

1. Introduction

Energy transformation is one of the greatest challenges facing countries around the world and, in particular, the European Union. The European Union has set itself extremely ambitious goals by implementing the provisions of the Kyoto Protocol [1], the Paris Agreement [2,3], and ultimately, the European Green Deal. All EU countries are to achieve a 35% reduction in greenhouse gas emissions by 2030, an increase in the share of renewable energy in the energy mix to at least 40%, and decarbonisation of the energy sector. EU countries are to achieve climate neutrality by 2050. This means the complete phasing out of fossil fuels, the development of a circular economy, and generating energy only from renewable sources. All EU countries must achieve the same results by the set deadlines, despite the fact that they are starting from completely different levels and their energy mixes are completely different. Countries such as Sweden, Finland, and Denmark already have a very high share of renewable energy in their energy mixes. In the case of Sweden, it is close to 70%, and in Denmark and Finland, around 45%. For comparison, in Eastern European countries, it is only 16% in the case of Poland and 15% in the case of Hungary [4]. Sweden, first of all, has been consistently implementing its energy policy of promoting renewable energy sources since the 1970s, but it also has favourable natural conditions that allow for the use of primarily stable renewable sources, such as hydropower. In addition, it is working on the potential of wind energy, for the development of which the country also has excellent conditions. Sweden, in addition, is focusing on developing modern technologies adapted to its capabilities, resources, and natural conditions [5]. Additionally, it has nuclear energy, which contributes about 30% of electricity production. All this makes Sweden an undeniable leader in the energy transition, which sets trends and may be able to achieve energy neutrality as early as 2040 [6]. At the other end of the ranking are the Eastern European countries that are expected to reach the level of the old EU countries, which requires making up for 40 years of neglect in a short period of time, using the same solutions and mechanisms as countries that are privileged in terms of time, technology, and geography. It is beyond dispute that the energy systems of EU countries should not have a negative impact on the natural environment, and thus on the health and life of residents. However, it is not obvious whether each of them must reach the designated goal by taking the same route.

Despite significant changes in the energy mixes of EU countries, coal still constitutes the basis of the energy systems of many of them, as in Poland, where it supplies 60% of electricity (Figure 1).

Since coal replacement cannot happen immediately, CCS should be a bridge to building fully stable energy systems based on renewable energy sources. Additionally, CO₂ is also produced during the cement or steel production processes, and in the chemical and refinery industries. Also, in this case, CCS is a way of decarbonising the economies of EU countries [8].

The European Union is taking action to develop CCS in its member states, as it is seen as a solution to the problems in the EU’s efforts to decarbonise energy systems. The CCS Directive 2009/31/EC [9] defines the legal framework for the process of carbon capture and storage. The assumptions contained in the European Green Deal also emphasise the role of CCS in achieving a zero-emission economy. For this purpose, the European Union has also built the EU ETS Emissions Trading System, which is intended to motivate EU countries to reduce their emissions. In 2023, the European Union adopted the Net-Zero Industry Act (NZIA), which supports the development of CCS, recognising it as a strategic technology, which should translate into financial, administrative, and procedural support for CCS projects [10]. EU member states are to achieve a CO₂ injection capacity of 100 million Mg CO₂ per year by 2030. Individual countries are already conducting research on CCS. In the Netherlands, the Porthos project has been implemented since 2021 [11]; in Denmark, the Greensand project was implemented, the pilot phase of which ended in 2023 [12]. Pilot projects supporting the development of CCS have also been implemented, such as ALIGN-CCUS implemented by Germany, the Netherlands, Romania, Norway and the United Kingdom [13], C4U implemented by partners from the Netherlands, Denmark, the United Kingdom, and Germany, among others [14], or Strategy CCUS implemented, among others, in France, Spain, Portugal, Croatia, Poland, Greece, and Romania [15]. In Poland, pilot projects have also been implemented in recent years, such as Orlen projects [16] and Kujawy Go4ECOPlanet, under which the Kujawy Cement Plant is to become the first zero-emission cement plant in Poland [17]. However, the leader in the development of CCS in Europe is Norway, which has been successfully storing carbon dioxide in the Sleipner deposit in saline aquifers off the coast of Norway since the end of the 20th century [18]. The impetus for starting the project was the CO₂ tax imposed by the Norwegian state. In this way, Norway became the first country in the world to use CCS on an industrial scale. Another project started in Norway in 2008 was Snøhvit [19]. Both of them allowed the storage of 22 Mg of CO₂ by 2017.

This article presents the results of the authors’ research on the importance of carbon capture and storage (CCS) for the energy transformation in Poland, i.e., a solution consistent with the specificity of the energy system of this country, which is in the least favourable situation considering the structure of energy production, natural conditions, and historical events. The scientific goal of the research was to develop a tool that supports decision-making crucial for energy security. The proposed tool enables to make decisions in changing, turbulent conditions of the political and economic environment. This will be of great importance in the near future, because the energy strategy of the European Union will have to be re-evaluated and adapted to the most important goal at present, which is to ensure energy and military security for the EU. The authors proposed the use of a scenario analysis of CCS development, but one that takes into account both measurable and immeasurable factors. This made it possible to combine all variables taken into account in the conducted research in one forecasting model. For this purpose, fuzzy models were used, which have not been implemented so far in the analysis of CCS development in Poland. The article is organised as follows. The literature review section presents a case study of Poland and justifies the selection of this particular country from the EU-27. Section 3 characterises the fuzzy sets that were used to build scenarios of possible energy transformation paths in Poland. The Results chapter describes the results of the obtained studies, and the Discussion chapter contains the results of the conducted analyses. This article ends with conclusions drawn from the analysis.

2. Literature Review

Is a uniform path to the transformation of EU energy systems the correct and optimal solution, or is it advisable to develop a decarbonisation strategy tailored to each EU country separately? It is necessary to find the answer to this question as soon as possible, because it will affect the successful achievement of the goals set by the European Green Deal. In order to analyse the extreme case, which is the opposite of the transformation leader, i.e., as already mentioned in the introduction, Sweden, the focus was on Poland. Poland is one of the representatives of the new EU countries, its energy mix is mainly based on coal, it has average natural conditions for the development of renewable energy sources RES, and, in addition, it will be forced to give up domestic coal fuel, thus becoming energy dependent on energy carrier suppliers, losing its high level of energy security, and at the same time, exposing itself to serious social problems in coal mining regions.

The structure of energy production in Poland is specific and shaped by the country’s centuries-old mining tradition [20]. Poland has rich deposits of hard coal and lignite, which constitute about 5% of the world’s hard coal resources. In Poland, hard coal deposits are located mainly in the Upper Silesian, Lublin, and Lower Silesian Coal Basins [21]. In 2023, these resources amounted to 64,596.29 million Mg, and it should be noted that this number increases every year (about a 7% increase compared with 2017). In turn, lignite resources in 2023 amounted to 23,041.32 million Mg [22]. Taking into account the demand for hard coal in Poland, only developed resources that constitute about 40% of total resources would enable the Polish energy system to be supplied for the next 700 years. In 2023, 60% of the electricity consumed in Poland was generated on the basis of coal. The demand for energy in Poland is growing every year [23]. In the case of electricity, the increase in demand is mainly influenced by the services sector and households. This is caused by the increase in the use of devices powered by electricity and the improvement in living standards. This trend will most likely continue in the coming years, but as of today, there are energy shortages in the Polish energy balance, which are compensated by imports from other countries of the European Union, such as Germany, Slovakia, and the Czech Republic [24]. At the same time, in cases of reduced renewable energy supplies, Poland supplies its neighbours with coal-based energy, which happened in Germany in 2024. Due to unfavourable weather conditions and the lack of access to nuclear energy, Germany was forced to obtain energy through import, thus preventing a blackout [25,26].

Climate neutrality involves achieving a zero balance of greenhouse gas emissions [27]. The measures that will lead to this primarily include balancing emissions and the possibilities of mechanisms for their absorption or elimination of emissions by increasing energy efficiency, using technologies for separating, capturing, and storing gases (mainly CO₂), increasing the share of renewable energy sources in energy production, afforestation, and protection of forest areas, and developing a circular economy [28,29]. The EU wants to achieve climate neutrality by 2050, which means that the entire EU economy is to be organised in such a way as to not increase the amount of greenhouse gases in the atmosphere [30]. One of the ways to achieve EU goals is the European Union Emissions Trading System EU ETS. It constitutes the world’s largest market for greenhouse gas emission allowances [31]. It is a tool to combat climate change and supports the achievement of EU neutrality by 2050. EU ETS is intended to motivate companies to invest in low-emission technologies. The EU ETS covers industries such as energy, heavy industry, and aviation [32]. The market operates on a cap and trade basis. The EU sets a limit on CO₂ that can be emitted by industries covered by the system every year. Companies can buy or receive free European Union Allowances (EUAs). If they manage to emit a smaller amount of CO₂, they can sell allowances, otherwise, they are obligated to purchase EUA [33].

The climate neutrality goal based on closed-loop waste from coal-based energy production and the elimination of emissions can be also achieved using clean coal technologies (CCTs) [34]. They constitute a wide range of possible technological solutions that can be implemented in the stage of fuel extraction, its processing, combustion, and at the stage of waste management [35,36].

The authors assumed that a beneficial solution in the case of Poland, which would enable the achievement of the goals set by the EU and, at the same time, continue to rely on coal, is to clean the exhaust gases generated in the combustion process of this fuel. One category of CCTs includes technologies used to separate CO₂ from exhaust gases in order to prevent its emission into the atmosphere and store the separated gas. CO₂ obtained using a selected technology, for example, membrane techniques, can also be used (carbon capture and utilisation, CCU) [37], e.g., in the process of exploitation of crude oil and natural gas, supporting the process of obtaining these fuels, or for food production [38,39]. There are also technologies where CO₂ can serve as a medium in the system of storing and transferring renewable energy [40]. CO₂ storage, in turn, requires the use of appropriate geological structures, such as exploited oil and gas deposits, coal seams, brine formations, or the bottom of the ocean [41]. One of the possible solutions in the field of sequestration is the use of membrane techniques. The membrane is a selective barrier separating the selected gas (e.g., CO₂, NO_x, or SO_x) from the atmospheric air. Each of the CO₂ sequestration methods is an opportunity to develop a low-emission energy system based on fossil fuels. CCS is a number of technologies, some of them are well-known, while others need to be refined [42]. Their great advantage is the possibility of integration with existing energy units, power plants, or heating plants; the disadvantage is usually additional energy consumption [43]. Once the gas has been captured, it is transported to a storage location, for example, in liquid form [44]. Then, the gas is injected, for example, into geological formations [45]. Storage is associated with financial outlays that can be avoided by using the CO₂ obtained. After collection, the gas is subjected to appropriate processing for further use, e.g., production of fuels—methanol, synthesis of chemical substances, etc. [46].

The use of CCS or CCU therefore seems to be justified, also considering their possibilities in terms of usability, availability of technology, and ease of adaptation to the existing energy system. However, the future strategy of Poland’s energy transformation will depend, to a large extent, on political influence. Therefore, to analyse the potential future of CCS during the energy transformation, the authors took into account the size of future CO₂ emissions, CO₂ emission costs, and the influence of the political environment on shaping the strategy of decarbonisation of the Polish energy sector.

CO₂ emissions in Poland have been systematically decreasing since the 1990s (Figure 2). However, after a period of intensive declines, emissions stabilised at around 8000 kg/capita at the beginning of the twentieth century. The current pace of declines may not be sufficient to achieve the assumptions of the Green Deal without the use of additional measures and solutions. CCS may be crucial in industrial sectors that emit large amounts of CO₂, such as the chemical and cement industries. The implementation of CCS is being held up, mainly due to significant technological and economic challenges. However, the profitability of their use will be directly affected by EU ETS prices.

EU ETS emission prices have increased almost 10 times over the last 10 years (Figure 3). In 2015, the price was less than EUR 7 per Mg of CO₂, and at the end of 2024, it was already over EUR 60. This rapid increase indicates that prices will continue to grow in the coming years, and in 2031, it is predicted that they may reach more than EUR 200 per Mg of CO₂ [47]. This may be a strong incentive for the development of CCS, because higher emission costs may encourage entrepreneurs to invest in technologies that are key to maintaining their competitiveness. On the other hand, when CCS is implemented, an increase in energy demand is expected. Therefore, it is necessary to develop low-energy techniques, such as membrane techniques.

An additional factor that will determine the success of CCS implementation in Poland on an industrial scale will be the issue of economic justification of the investment. However, as shown by numerous studies, investments in CCS will be economically justified with the increase in the prices of EU ETS emission allowances to the level of approximately EUR 90–140 per Mg [49,50]. Analyses of the economic profitability of the CCS project conducted in Poland as part of the EU GeoCapacity project showed that the largest contribution to the total cost of CCS is made by CO₂ capture, which accounts for 90%, followed by gas compression, at 8%, storage, at 1%, and gas transport, at 0.2% [51]. Therefore, the cost of CCS also depends on the CO₂ concentration in the gas stream, and the total cost of CCS may range from USD 20/Mg to USD 120/Mg [52]. However, it is expected that the costs of building CCS installations and operating costs will decrease as a result of technological progress [53]. The profitability of investments may be influenced by funds and subsidies provided by the EU and Poland, as was the case with renewable energy sources, the development of which is also often not economically justified in the initial development phase. Legislative solutions and the process of obtaining permits for CO₂ storage will also have a huge impact on the development of CCS. CCS support programs have been implemented outside the EU, for example, in Canada and the USA, and the European Union, wanting to compete in global markets, should also consider such analogous solutions [54]. In the case of Poland, developing alternative strategies for ensuring access to energy is extremely difficult. Currently, renewable energy sources cover only 16% of demand, and it should be remembered that, in recent years, they have been developing very dynamically. In order for them to take over the role of coal, further development of the RES infrastructure is necessary, but even assuming that the demand for energy will not increase in the coming years, it will take decades to build the necessary RES production potential. It should also be remembered that most of the infrastructure built so far was developed by prosumers. The implementation of nuclear energy has been planned in Poland since the 1980s, but no action has been undertaken to date.

In order to verify the importance of CCS in the energy transition process, taking into account both quantitative factors, i.e., emission volume and EU ETS price, and the impact of the political environment, which is a qualitative factor, an expert opinion survey was used.

Political environment refers to political actions and decisions that will shape, i.e., support or hinder the implementation and development of CCS. The political environment will primarily include energy and climate policy, commitments to international organisations such as the UN, strategic government documents, i.e., in the case of Poland, the Energy Policy PEP2040, or the National Energy and Climate Plan, as well as the legal framework enabling CCS storage, regulating the expansion of infrastructure, financial support programs, tax relief, subsidies, and public opinion. Additionally, the stability of the political environment in terms of the durability of the changes introduced and maintaining the chosen direction of CCS development will translate into investor confidence stimulating the development of CCS, which is crucial in the case of technology requiring a strategic horizon of action and significant investments.

The survey included three forms containing factors to analyse the importance of the role of CCS in the process of decarbonisation of energy systems in Poland, if the legal regulations in force in Poland have the following impact: neutral N, negative Z, and positive P.

The weight takes values from the set: low, average, high, where low means a negative rating, high means a positive rating, and average means neutral.

Factors considered in the survey:

EU ETS price—the cost of a CO₂ emission unit within the European emissions trading. It is a tool of the EU in the fight against greenhouse gas emissions and climate change. It was assumed that the ETS can be as follows:

• Low, e.g., due to increased energy efficiency, use of energy-efficient machines and devices in industry, economic slowdown, and increased share of renewable energy sources;
• Average—as a result of the balance achieved between demand and supply of EUA allowances and macroeconomic stability;
• High—due to increased demand for energy caused by, for example, dynamic economic growth, natural increase, and reduction of available allowances due to tightening of EU energy policy, taking into account new sectors, e.g., construction.

Greenhouse gas emissions—an excessive concentration of greenhouse gases in the atmosphere, mainly CO₂, leads to an increase in its temperature. Anthropogenic sources of greenhouse gases are mainly the combustion of fossil fuels, industry, and agriculture. The amount of gas emissions accepted in the survey can be:

• Low, e.g., due to high energy efficiency, increasing amount of renewable energy in the energy mix, reduced energy demand, use of low-emission technologies, and rising EU ETS prices;
• Average—moderate pace of modernisation and implementation of low-emission technologies, and moderate economic development;
• High—which may be caused by increased demand for energy, low energy efficiency, economic development, and high prices for fuels and energy from alternative sources;
• Ten experts participated in the survey, which was anonymous. The experts invited to the study were selected based on their knowledge of the analysed phenomenon. These were scientists engaged in research in the field of CCS, clean coal technologies, energy, economics, energy security, and energy transformation. The experts were professors (60%) and PhDs (40%). The group of experts included 60% women, and their age range was 40–64 years.

In expert surveys, there is no minimum number of respondents that should take part in the study. As experts are specialists in a given field, the number of opinions obtained is not important, but rather, gaining a representative picture is important. In the literature on the subject, many examples of expert opinion studies can be found, where their number varies from a few to a dozen respondents [55,56,57,58]. Data saturation is also important, i.e., the state in which subsequent opinions no longer bring any significant observations. In the case of expert research, this state can be achieved with just a few experts.

The results of the survey are presented in

Table 1. Survey results under the neutral scenario.

CCS Weight			Experts
Variable state combination	EU ETS prices	CO2 emissions	1	2	3	4	5	6	7	8	9	10
1	M	M	N	N	N	W	N	N	N	N	N	N
2	M	S	N	N	N	W	N	N	N	N	N	N
3	M	D	S	S	N	W	S	S	S	S	S	S
4	S	M	N	N	N	W	S	S	S	N	N	S
5	S	D	S	S	N	W	S	S	S	S	S	S
6	D	M	S	S	N	W	S	N	W	S	S	S
7	D	D	W	W	N	W	W	W	S	W	W	W
8	S	S	S	S	N	W	S	S	W	W	S	S
9	D	S	W	S	N	W	W	S	W	W	S	S

Symbols in tables: weight: M—low, S—average, D—high; impact of CO₂ emissions and EU ETS prices: N—low, S—average, W—high.

,

Table 2. Survey results under the optimistic scenario.

CCS Weight			Experts
Variable state combination	EU ETS prices	CO2 emissions	1	2	3	4	5	6	7	8	9	10
1	M	M	S	S	N	W	N	S	S	S	N	N
2	M	S	S	S	S	W	N	S	S	S	N	S
3	M	D	W	W	S	W	S	S	W	W	N	S
4	S	M	S	S	N	W	S	S	S	S	N	S
5	S	D	W	W	W	W	W	W	W	W	S	S
6	D	M	W	W	S	W	W	S	W	S	N	S
7	D	D	W	W	W	W	W	W	W	W	W	W
8	S	S	S	W	S	W	W	W	W	S	S	S
9	D	S	W	W	W	W	W	W	W	W	S	S

Symbols in tables: weight: M—low, S—average, D—high; impact of CO₂ emissions and EU ETS prices: N—low, S—average, W—high.

and

Table 3. Survey results under the pessimistic scenario.

CCS Weight			Experts
Variable state combination	EU ETS prices	CO2 emissions	1	2	3	4	5	6	7	8	9	10
1	M	M	N	N	N	W	S	N	N	N	N	N
2	M	S	N	N	S	W	S	N	N	N	S	N
3	M	D	S	N	S	W	S	S	N	N	W	S
4	S	M	N	N	N	W	S	N	N	N	S	N
5	S	D	S	S	W	W	W	S	S	S	W	S
6	D	M	S	S	S	W	W	S	S	S	S	S
7	D	D	W	S	W	W	W	S	S	W	W	S
8	S	S	S	S	S	W	W	S	S	S	S	S
9	D	S	S	S	W	W	W	S	S	S	W	S

Symbols in tables: weight: M—low, S—average, D—high; impact of CO₂ emissions and EU ETS prices: N—low, S—average, W—high.

.

The changing environmental conditions that affect the future of CCS will determine whether they will be widely used in energy systems not only in Poland, the European Union, but all over the world. The complexity of the environment, the lack of full information, and, above all, consistent information, limit the possibilities of making accurate decisions and building an optimal energy strategy. In such a situation, scenario planning is a useful tool that supports decision-making. It was first used in the USA after World War II for military purposes. A group of experts was asked to prepare a set of different versions of events with regard to the possibility of another world war breaking out [59]. The results of the research conducted were published by the authors in 1967 [60]. The effectiveness of the method is appreciated and is used, among others, by many companies around the world, such as Shell [61,62], thanks to which the company emerged unscathed from the oil crises of the 1970s, as well as by General Motors and IBM [63].

Since the process of shaping the country’s energy policy is very unstable and is influenced by many factors, it is impossible to create a reliable forecast of the importance of CCS in the energy transformation. Therefore, based on the results obtained from the survey and the use of the fuzzy model, scenarios were created for the development of CCS and its role in the energy transformation process. The scenarios make it possible to predict the future under unstable and turbulent conditions, in which the energy transformation of Poland will certainly take place [64]. They allow for predicting the future in the form of many potential parallel images of the future, taking into account various trends shaping the analysed phenomenon [65]. It is considered that heuristic forecasting based on expert knowledge may be more effective in turbulent conditions. However, on the other hand, these methods are difficult to verify, and there is no evidence of their effectiveness. The fuzzy model is a solution that allows for the transfer of expert knowledge to a formalised mathematical notation. The results obtained from the survey were used as data for the model with two inputs ETS and CO₂, which were described by three fuzzy sets with three rule bases taking into account the qualitative parameter, i.e., variable legal conditions (Lr) of the energy systems environment. The models used are described in Section 3.

3. Materials and Methods

Fuzzy sets are a tool that has been developed for 60 years [66], during which time they have evolved and found application in modelling uncertain, incomplete, and subjective information [67,68]. Fuzzy sets were proposed by L.A. Zadeh in 1965. In the 1970s, they were used in control systems, e.g., Shinkansen trains [69], and after 2000, in artificial intelligence [70,71,72]. They were applied in economics [73,74], medicine [75], as well as energy and environmental protection [76,77]. In the theory of fuzzy sets, it is assumed that it is possible to gradate the membership of an element in a set. It is not unambiguous, as in the classical set theory, where an element belongs to the set (1) or does not belong (0) [78]. In fuzzy sets, membership is in the range of 0 to 1 [79].

Fuzzy sets are a tool that allows for the transformation of the knowledge of experts into formalised mathematical notation [80]. Based on the experience and competence of experts, knowledge about the ongoing processes can be obtained [81]. An expert is not able to convey all of their intuitive knowledge. Subconscious knowledge can be acquired by observing the expert’s reaction to the course (changes) occurring in the process. The expert’s knowledge about the process is called a mental model [82]. Fuzzy models with satisfactory accuracy can be constructed for processes with at most two inputs, even in cases of limited information about the process or the influence of one quantity on another. The advantages of fuzzy modelling were used to develop the dependence of EU ETS prices and CO₂ emission on CCS weight for three different scenarios. In the traditional sense, they constitute visions of the future, not forecasts. They are a set of visions of how the factors taken into account affect each other under specific environmental conditions. Scenarios are considered unscientific methods, constituting experts’ thoughts on a given topic. However, a well-constructed scenario should be based on elements that can be clearly determined. Therefore, the authors used a fuzzy model, which allowed for the introduction of both qualitative and quantitative variables to the model, as well as the construction of a whole set of intermediate model responses between the opinions expressed by experts. This eliminates the subjectivity factor of the obtained assessments. In the research proposed by the authors, scenarios were built based on measurable factors, such as EU ETS prices and the volume of CO₂ emissions in a given year. The time period taken into account covered the years 2010–2024. An unmeasurable element in the investigation was the conditions of the impact of the political environment on the importance of CCS in the energy transition of the Polish energy system. This enabled the use of the scientific method, because fuzzy models allow the translation of expert knowledge into the mathematical notation CCSI = f(ETS, CO₂)/Lr. Three scenarios were built, i.e., pessimistic, optimistic, and most probable.

A block diagram of the fuzzy model is shown in Figure 4. It consists of a normalisation block, in which independent (input) variables are rescaled to the range [−1,1]. Normalised values are subject to the so-called fuzzification, i.e., the degree of membership in the input fuzzy sets is determined. In the inference block, the membership function of the model output is determined, and the calculation of the normalised sharp value is carried out in the defuzzification block. The output value is determined after performing the operation reverse to normalisation in the denormalisation block.

The construction of a fuzzy model describing the static dependence of CCS importance as a function of EU ETS prices and CO₂ emissions was carried out in several steps, taking into account the adopted model structure. The fuzzification of variables, i.e., construction of a fuzzy set described by the membership function [83,84] (triangular functions) is described by the formula:

$$\begin{gathered} {\mu }_{ei}\left({{CO}_2}^N\right)=\left\{\begin{array}{ccc}0& for& {{CO}_2}^N<e{L}^N\\ ({{CO}_2}^N-e{L}^N)/(e{S}^N-e{L}^N)& for& e{L}^N\le {{CO}_2}^N\le e{S}^N\\ (e{P}^N-{{CO}_2}^N)/(e{P}^N-e{S}^N)& for& e{S}^N\le {{CO}_2}^N\le e{P}^N\\ 0& for& {{CO}_2}^N>e{P}^N\end{array}\right. \\ {\mu }_{pj}\left({ETS}^N\right)=\left\{\begin{array}{ccc}0& for& {ETS}^N<q{L}^N\\ ({ETS}^N-p{L}^N)/(p{S}^N-p{L}^N)& for& p{L}^N\le {ETS}^N\le p{S}^N\\ (p{P}^N-{ETS}^N)/(p{P}^N-p{S}^N)& for& p{S}^N\le {ETS}^N\le p{P}^N\\ 0& for& {ETS}^N>p{P}^N\end{array}\right. \end{gathered}$$

(1)

where: CO₂^N—normalised CO₂ emission rate, ETS^N—EU ETS standardised price, $\mu$_ui,j (U^N)—membership function for the i-th or j-th input fuzzy set, uS^N—normalised modal value of the fuzzy set, uL^N—values of the input fuzzy set on the left and right side of the normalised modal value, respectively, for which membership is 0, u^N—e^N or p^N, U^N—CO₂^N, or ETS^N.

Singleton functions are assumed as output fuzzy sets. The membership function in this case takes the form:

$${\mu }_{ji}\left({CCSI}^N\right)=\left\{\begin{array}{c}1 for {CCSI}^N=b_{ji} \\ 0 for {CCSI}^N\ne b_{ji}\end{array}\right.$$

(2)

Based on the membership degree $\mu$_e,j(CO₂N), $\mu$_p,j(ETSN), the membership function $\mu$(CCSI^N) is determined. For this purpose, it was necessary to determine the database of “if” rules for legal provisions, which is the most important element of the fuzzy model. This database stores knowledge about the modelled input and output dependencies in a qualitative form [85]. The rule is described by the formula:

$$\underset{\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{c}\mathrm{e}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{t}\hspace{0.33em}\left(\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{m}\mathrm{i}\mathrm{s}\mathrm{e}\mathrm{s}\right)}{\underbrace{\left(e^N=S_{1i}\hspace{0.33em}I\hspace{0.33em}{p}^N=S_{2j}\right)}}\hspace{0.33em}\hspace{0.33em}\hspace{0.33em}\hspace{0.33em}T\hspace{0.33em}\underset{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{l}\mathrm{u}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}}{\underbrace{\left({CCSI}^N=b_{ji}\right)}}$$

(3)

In the proposed fuzzy model, three scenarios were created for legal regulations: the most likely (Lr = 0), optimistic (Lr = 1), and pessimistic (Lr = −1). Expert knowledge obtained through anonymous surveys for these three scenarios was mapped in the form of three rule bases. The selection of the rule base for a given scenario is represented by conventional connectors (Figure 3). If the legal regulations change from neutral (Lr = 0) to favourable (Lr = 1), then for the purpose of determining the sharp value of the CCSI importance coefficient in the fuzzy model, a transition takes place from one (middle) rule base to the lower rule base, corresponding to a given legal state.

Then, the interference mechanism [86,87] was characterised in order to aggregate the premises using an operator that allows for smoothing the surface of the fuzzy set:

$$m_k=PROD\left({\mu }_{ei}\left({{CO}_2}^N\right),{\mu }_{pj}\left(ZWE{P}^N\right)\right)={\mu }_{ei}\left({{CO}_2}^N\right)\cdot {\mu }_{pj}\left({ETS}^N\right)$$

(4)

where: m_k—the degree of satisfaction of the premise of the k-th rule.

The inference was obtained using the MAX-MIN method [88]:

$${\mu }_{ji\mathrm{*}}\left({CCSI}^N\right)=MIN\left(m_k,{\mu }_{ji}\left({CCSI}^N\right)\right)$$

(5)

In the next step, the output membership function of the fuzzy model was determined using the height method:

$${CCSI}^N={\displaystyle \frac{{\sum }_1^r{b}_{ji}\cdot {\mu }_{Vji\mathrm{*}}}{{\sum }_1^r{\mu }_{Vji\mathrm{*}}}}$$

(6)

where: r—the number of rules.

The finally determined value of the CCSI coefficient was denormalised, and the modal values of the output sets were obtained using a weighted average [89]:

$$b_{ij}={\displaystyle \frac{{\displaystyle \sum _{q=1}^5{B}_q\cdot E_q}}{{\displaystyle \sum _{q=1}^5{E}_q}}}$$

(7)

where: E_q—q-th expert, B_q—absolute value of the energy security indicator determined by the q-th expert for the linguistic data of the ETS and CO₂ input values and the qualitative factor.

The lack of consistency in the conduct of energy policy in Poland and its high dependence on the decisions of politicians means that the future of CCS development is additionally complicated and obscured. This instability will be reflected in the decisions made by potential investors. Theoretically, in recent years, Poland has undertaken a number of activities for the development of CCS, such as initiating projects aimed at creating a CCS strategy and developing CCS technology, i.e., the GO4ECOPLANET project [90], changes in geological and mining law in favour of the possibility of storing CO₂ on land [91], determining Poland’s potential for CO₂ storage [54]. At the same time, only pilot installations operate in Poland to this day, and full-scale industrial CCS installations have not yet been implemented, apart from two installations from the end of the 20th and beginning of the 21st centuries [92,93]. Therefore, it is valuable that the scenarios will provide the opportunity to build different variants of CCS development, which will allow for preventive responses to threats to appear in the environment of energy systems in Poland. The constructed scenarios are presented in Figure 3, Figure 4 and Figure 5.

4. Results

The survey results were used as input data for the fuzzy model and then to build graphs presenting the decision surface. The graphical presentation of the obtained results in the form of surface graphs will facilitate the decision-making process. They show how the importance of CCS changes depending on the size of emissions and the price of the EU ETS under specific environmental conditions. Surface graphs and their colour allow for easy visualisation of the conditions under which CCS becomes the right solution (red colour), and to what level of explanatory variables it is not recommended (blue colour). The combination of the three factors influencing the development of CCS allows for the verification of specific values of variables for which under given political conditions the implementation of CCS will be desirable and advisable. The graphs also facilitate tracing the threshold values at which the profitability of CCS increases or decreases intensively. The graphs can be used to establish financial support thresholds for regions and countries that should implement CCS. This allows for securing CCS support funds for the future. The proposed model presents the static dependence of the impact of two Emission CO₂ and Prices EU ETS on the weight of CCS based on expert knowledge. It should be emphasised here that one of the main advantages of using fuzzy logic is the possibility of developing a model for strongly non-linear dependencies, difficult to describe in an analytical form and based solely on expert knowledge, often of a qualitative nature.

Table 1, Table 2 and Table 3 contain a representation of the knowledge of 10 experts in the field of the impact of Emission CO₂ and Prices EU ETS on the weight of CCS in qualitative terms for three scenarios: positive (Table 1), neutral (Table 2), and negative (Table 3). They constitute the basis for building the rule bases of the designed fuzzy model, whereby the modal values of the fuzzy input sets in the form of Emission CO₂ and Prices EU ETS in qualitative terms (M, S, and D) represent the first two columns of Table 1, Table 2 and Table 3 (for three scenarios). On the other hand, the modal values of the output bij are determined based on the experts’ answers (columns “Experts” from 1 to 10—Table 1, Table 2 and Table 3) in accordance with the relationship (7). Table 1, Table 2 and Table 3 enable the development of rule bases for the fuzzy model in the case of three scenarios and are the basic starting point for the development of the final fuzzy model. Thus, the expert knowledge obtained through a survey, the results of which are included in Table 1, Table 2 and Table 3 using fuzzy logic, was converted into a formalised mathematical notation in the form of a fuzzy model for three scenarios, which are presented below.

4.1. Neutral Likely Scenario

In the neutral scenario (Figure 5), the influence of the CCS of the political environmental conditions is assumed to be neutral. The CCS weight reaches a maximum value of 0.85, while its minimum value is 0.1. An intensive increase in the importance of the CCSI indicator occurs when EU ETS prices exceed EUR 80 and the per capita CO₂ emission volume is above 9000 kg. Under neutral environmental conditions, the CCS weight increases above 0.5 only at high emission values and emission fees. The trend of the EU ETS indicator value is partially parallel to the x axis, which means that up to EUR 60/Mg CO₂ will have no effect on the CCS weight. Some CCS support mechanisms are used, but they are not so favourable that CCS obtains a weight above 0.5 at the mean CO₂ and EU ETS indicator values.

4.2. Pessimistic Scenario

The surface of the chart (Figure 6) in this case is much flatter at the highest values of CO₂ prices and EU ETS. The entire surface of the graph is placed lower than in the other cases, because the highest weight in the pessimistic scenario is 0.8. It should be noted that, even with increasing emission prices and volumes, CCS will not always be sufficiently profitable. The importance of CCS is highest in a very narrow range of CO₂ and EU ETS factors, where CCSI reaches a weight of 0.7 at their maximum values. The increase in the importance of CCS occurs only after exceeding the average values of EU ETS and CO₂ factors; up to this point, their course is almost parallel to the x and z axes. Legislative uncertainty, lack of clear strategic regulations, and lack of a CCS support mechanism may discourage investors.

4.3. Optimistic Scenario

Under the optimistic scenario (Figure 7), a strong upward trend in the importance of CCS can be observed, and the maximum CCSI reaches a value of 1. The minimum value of CCSI is 0.35. Under the optimistic scenario with favourable political conditions, the possibility of using CCS financing programmes and tax benefits stimulate their development. At the same time, restrictive emission standards and high EU ETS prices are a strong motivation to invest in CCS. Government support translates into access to mature CCS technologies, a developed CO₂ transport, and storage network.

5. Discussion

The analysis carried out showed that it is incorrect to assume that the energy transformation can be carried out in all EU countries in one way that could be equally effective, despite the differences in the energy mixes of individual countries. In the case of Poland, transferring solutions used by transformation leaders such as Sweden may bring negative economic and social consequences. It is necessary to ensure a transition period to enable an effective and fair departure from coal, which will translate into a safe energy transformation in terms of its success, but also ensuring energy security. One of the solutions in this area is CCS technologies. The results of the conducted scenario studies based on fuzzy sets indicate that in a politically neutral scenario, the importance of CCS is growing, and its use becomes realistic at an emission allowance price above EUR 80/Mg and CO₂ emissions above 9000 kg per capita. However, it should be noted that the effectiveness of CCS implementation will depend on economic factors, technological factors, and the predictability of the country’s energy policy.

The constructed surface graphs illustrate the relationship between emission allowance prices, CO₂ emission volume, and the importance of CCS technology. Local extremes indicate that this relationship is non-linear, and the impact of explanatory variables on the importance of CCS is complex and dependent on the specific scenario. Each scenario allows for determining the combination of factors in which CCS plays a key role and when it can be replaced by another, more advisable technology. The relationships between the analysed data may seem obvious and intuitive, but the use of the proposed solution, i.e., the fuzzy logic model, allows for a systematic, quantitative analysis of expert assessments. Additionally, the analysis of intermediate CO₂ emission values and EU ETS prices is a tool for planning activities within the energy transformation. Analysis of the graphs will allow for identifying critical points for the development of CCS and the dynamics of the political and economic environment. In addition to political decision-makers, the stakeholders of the CCS implementation process also include representatives of the industry and local communities. The main concerns of investors are the profitability of CCS investments, regulatory risks, lack of CO₂ storage and transport infrastructure, and logistical and organisational barriers. In turn, social resistance appears mainly as a result of a lack of knowledge and trust in new technologies. The proposed scenarios and their graphical presentation can help investors assess under what conditions CCS is an economically justified solution. Social acceptance can be a significant factor influencing the ultimate success of CCS implementation. Support during social negotiations can certainly be provided by a transparent decision-making process that takes into account the opinions of stakeholders and clear communication of the obtained results. Therefore, the presented scenarios can increase social trust and improve acceptance of planned activities.

6. Conclusions

As studies conducted have shown, CCS technology can be crucial for the energy transition in Poland. The use of CCS can contribute to maintaining coal in the energy mix, which will significantly translate into the country’s energy security level. Under the neutral scenario, CCS can only be important at a specific price and a CO₂ emission threshold. It can be used as one of many decarbonisation solutions supporting the energy transformation process. In the pessimistic scenario, the importance of CCS is the lowest, even in the case of high emission values and EU ETS prices. Under such conditions, CCS can be a solution implemented in specific conditions, where other solutions are impossible to use for technological or financial reasons.

This research was focused on CCS as the basic technology for reducing CO₂ emissions included in EU regulations and directives. The presented analysis is basic and universal, and can be applied to CCS, as well as CCU and CCUS; however, for these two modified forms of CO₂ elimination, specific factors should be added.

Despite the European Union’s current energy policy of phasing out fossil fuels from the energy mixes of member states, factors are emerging in the EU’s environment that will change the EU’s view of the further use of coal. The war in Ukraine and the need for the EU to build its own military potential may lead to a shift in the EU’s energy policy. However, even under such conditions, the EU should not forget about the need to take care of the natural environment, health, and quality of life of citizens. In this case, CCS is an excellent solution, capable of combining such extreme solutions. Stable political conditions and predictable legal regulations will be crucial to the profitability of CCS use in the Polish energy sector.

Analysing the impact of many factors simultaneously on the importance of CCS for energy transformation can be a problem for decision-makers. The proposed model makes it possible to build surface charts that graphically present the relationships between these factors and enable easy identification of the importance of CCS under specific conditions analysed. It also allows for the observation of weak signals, which are difficult to observe without such a tool. The tools used enable the mathematical representation of expert knowledge, allowing for the elimination of errors that may occur in the case of purely intuitive assessments.

The prepared scenarios will enable a quick response and optimal decisions under various conditions of turbulent environments. This will facilitate the preparation of energy strategies. The scenarios will allow for the identification of optimal conditions for the implementation of CCS, as well as the evaluation of when CCS can be a key element of transformation and when only an additional solution can be considered, tracking how environmental factors affect the potential of CCS. The use of fuzzy sets allowed us to eliminate the most serious disadvantage of scenario planning based on expert knowledge, namely the subjectivity of their judgments. The model also allowed for combining qualitative and quantitative variables, which is its main advantage, because it enables all important factors to be taken into account, regardless of their nature. The limitation of the applied method is that scenarios constitute a simplified model of reality, and it is necessary to update them systematically so that they can constitute a possibly faithful reflection of reality. Therefore, the authors plan to build a tool for the dynamic analysis of the environment in further research, also extended with additional independent variables.

It is also very important to obtain information on what happens to the weight of CCS with intermediate values of EU ETS and CO₂ factors. This will enable decision-makers and investors to properly and accurately plan and construct energy transformation strategies. Additionally, the scenarios, and especially their visualisation, are extremely valuable for stakeholders, because they allow for the potential development of the situation to be observed with known political conditions, prices, and CO₂ emissions. They allow for an understanding of the dependence of CCS importance on the changing environment. Scenarios enable critical points for CCS development to be captured.