Polish Farmers′ Perceptions of the Benefits and Risks of Investing in Biogas Plants and the Role of GISs in Site Selection

Abstract

In the past decade, agricultural biogas plants have become one of the key tools driving the energy transition in rural areas. Nevertheless, their development in Poland still lags behind that in Western European countries, suggesting the existence of barriers that go beyond technological or regulatory issues. This study aims to examine how Polish farmers perceive the risks and expected benefits associated with investing in biogas plants and which of these perceptions influence their willingness to invest. The research was conducted in the second quarter of 2025 among farmers planning to build micro biogas plants as well as owners of existing biogas facilities. Geographic Information System (GIS) tools were also used in selecting respondents and identifying potential investment sites, helping to pinpoint areas with favorable spatial and environmental conditions. The findings show that both current and prospective biogas plant operators view complex legal requirements, social risk, and financial uncertainty as the main obstacles. However, both groups are primarily motivated by the desire for on-farm energy self-sufficiency and the environmental benefits of improved agricultural waste management. Owners of operational installations—particularly small and medium-sized ones—tend to rate all categories of risk significantly lower than prospective investors, suggesting that practical experience and knowledge-sharing can effectively alleviate perceived risks related to renewable energy investments.

1. Introduction

The dynamic increase in global energy demand—projected by the International Energy Agency (IEA) to rise by 45% between 2010 and 2030—combined with escalating environmental challenges, particularly greenhouse gas emissions, has made energy production and transmission critical issues for modern energy systems. The use of renewable energy sources and the development of distributed energy generation—defined as the local production of electricity and heat from regionally available resources, independent of centralized power systems—are gaining increasing importance in contemporary energy policy and practice [1,2].

According to the IEA, limiting global warming to below 2 °C requires reducing CO₂ emissions to the levels recorded in the year 2000 by 2050. This entails improving energy efficiency, accelerating the deployment of renewable energy sources, and implementing carbon capture and sequestration technologies [3].

Table 1. The evolution of biogas utilization for energy production measured in GJ per capita [3].

Country	2010	2014	2018	2022
Australia	0.50	0.65	0.60	0.74
Austria	0.75	1.3	1.20	0.71
Belgium	0.50	0.56	0.68	0.89
Brazil	0.05	0.12	0.18	0.21
Canada	0.30	0.42	0.37	0.34
China	0.18	0.22	0.19	0.18
Denmark	0.75	0.94	2.16	4.91
Finland	0.28	0.76	1.37	1.30
France	0.24	0.37	0.55	1.12
Germany	2.41	3.58	3.76	4.12
India	0.14	0.21	0.47	0.72
Ireland	0.45	0.38	0.36	0.40
Italy	0.35	1.41	1.30	1.48
Japan	0.0	0.00	0.00	0.00
Korea	0.19	0.21	0.17	0.22
The Netherlands	0.71	0.76	0.78	0.13
New Zealand	0.55	0.58	0.60	1.15
Norway	0.24	0.21	0.38	0.54
South Africa	0.00	0.00	0.00	0.00
Sweden	0.45	0.61	0.70	0.78
Switzerland	0.27	0.51	0.63	0.74
UK	1.18	1.31	1.78	1.55
USA	0.31	0.51	0.44	0.33
UE 27	0.67	1.28	1.36	1.58

shows the evolution of biogas use in various European and global countries.

Until recently, Germany had been the most advanced in the production and use of biogas (reaching almost 4 GJ per capita), but in recent years, Denmark has taken on a major challenge at the national level, surpassing Germany’s per capita level in 2022. Thanks to highly favorable policies for the construction and operation of biogas plants, Denmark has seen a significant increase in the production of biogas from manure, energy crops, and industrial raw materials. Previously, biogas was mainly used for energy generation in CHP systems, but now the raw gas is being upgraded to biomethane and injected into the national gas network.

In this context, agricultural investments in biogas plants are becoming increasingly relevant as an example of distributed energy systems and a practical means of utilizing local renewable energy sources. The aim of this article is to examine how Polish farmers perceive the risks and benefits associated with the development and operation of agricultural biogas plants.

Main Research Question:

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How do farmers in Poland perceive the risks and benefits associated with agricultural biogas plants?

Specific Research Questions:

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What types of risks are perceived by farmers in relation to the operation of biogas plants?

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What benefits do farmers associate with the construction and operation of such installations?

Hypothesis H1.

Farmers who own biogas plants perceive greater benefits and lower levels of risk associated with such investments compared to those who do not own such facilities.

2. The Use of Biomass and Agricultural Biogas in the Context of the Circular Economy

The development of the renewable energy sector significantly contributes to mitigating the environmental impact of the energy industry. This is particularly evident in the use of wind energy, where optimized turbine placement helps minimize the risk of social conflicts [4,5]. The utilization of solar radiation yields tangible benefits, including zero-waste production of electricity and heat within distributed energy systems. Moreover, the application of hybrid energy systems enhances the efficiency of energy generation and consumption, particularly through the integration of energy storage technologies [6,7]. A similar pattern is observed in hydropower generation, which provides added value by improving both energy availability and flood protection; additionally, it enables energy storage in pumped-storage reservoirs [8,9].

Among locally available renewable resources, biomass has the highest development potential. Biomass refers to organic material derived from living organisms, including phytomass (plant biomass), zoomass (animal biomass), and microbial biomass. Primary-producer biomass is generated via photosynthesis, while consumer and decomposer organisms derive their biomass by utilizing the organic matter produced by primary producers. These processes involve both biomass harvested directly from natural ecosystems and biomass classified as waste, which originates from agriculture, municipal services, and various sectors of the processing industry [10,11].

The conversion of such biomass into energy results in the production of energy carriers in the form of solid fuels (e.g., energy wood, wood chips, sawdust), liquid biofuels (used as components in internal combustion engines), and gaseous fuels, including agricultural biogas, municipal biogas, landfill gas, and biogas from sewage sludge [12,13].

Within the Polish legal framework, the Act on Renewable Energy Sources defines biogas and its potential types. One such type is agricultural biogas, which is produced through anaerobic digestion of waste generated during agricultural production. This includes both liquid and solid animal manure, as well as by-products of agricultural origin [14]. The anaerobic digestion of biodegradable waste derived from agriculture and the food industry can be carried out using a variety of technological approaches. Key factors include the type and preparation of input substrates, as well as the technologies employed for biowaste processing. This pertains not only to the production of biogas in fermentation chambers, where methane—a combustible gas—typically constitutes 50 to 70 percent of the total volume of agricultural biogas [15,16], but also to the necessary purification and drying processes that prepare the gas for energy use.

Raw biogas contains harmful impurities such as hydrogen sulfide and siloxanes, which must be removed before the gas can be used as an energy source [17,18]. Technological solutions for the conversion of agricultural biogas into electricity and heat should be both innovative and energy-efficient. The primary method for utilizing agricultural biogas involves its combustion in cogeneration (combined heat and power) systems. In these systems, purified biogas is combusted in gas engines. The electricity produced is primarily used to meet the internal energy demand of the biogas facility; any surplus electricity is fed into external power grids. The heat recovered from the engine and exhaust system is predominantly used for technological processes within the plant itself [19,20].

Cogeneration is not the only available method of utilizing agricultural biogas for energy purposes. Technologies for upgrading biogas to biomethane are gaining increasing attention. Biomethane can be injected into natural gas distribution networks, stored, or used as a renewable transportation fuel for vehicles powered by compressed natural gas (CNG) or liquefied natural gas (LNG) [21,22].

The European Union’s strategy to increase the share of renewable energy in the energy portfolios of member states aims to reduce greenhouse gas emissions, particularly methane and carbon dioxide. In this context, the sustainable management of biowaste aligns with the principles of the circular economy. The production of biogas, followed by its conversion into biomethane, contributes to the broader goals of energy transition by promoting diversification of energy sources and improving energy-use efficiency [23,24].

3. Risks and Constraints Associated with the Expansion of Agricultural Biogas Plants in Poland

In recent years, there has been a modest increase in the number of biogas installations operating in Poland, including those of agricultural origin. According to data from the Energy Regulatory Office (ERO), as of 31 March 2025, a total of 330 biogas plants were in operation across the country, collectively utilizing 415 cogeneration units [25]. Of these, 151 were agricultural biogas plants, equipped with a total of 179 generation units. These figures are consistent with data from the Agricultural Biogas Producers Registry (ABPR), maintained by the National Agricultural Support Centre (NASC), which recorded 181 agricultural installations owned by 151 entities as of 24 March 2025. These facilities include both installations equipped with their own cogeneration units and smaller fermentation lines operating without such systems [26].

To ensure the continued expansion of the biogas sector in Poland, it is essential to identify the risks encountered by investors and develop effective countermeasures through a range of management instruments. These instruments should be interpreted broadly as a set of measures, methods, techniques, and tools used to perform management functions and to achieve defined objectives [27].

The academic literature identifies several principal categories of risk associated with the construction and operation of agricultural biogas plants. For the purposes of this study, these risks have been classified into five main categories:

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Economic and financial risks;

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Technological, operational, and feedstock-related risks;

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Social risks;

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Environmental and health-related risks;

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Regulatory and legal risks, including those of a political nature.

3.1. Economic and Financial Risks and Constraints

As noted by Kusz et al. [28], two primary barriers to the development of biogas plants in Poland are economic and financial in nature: high investment costs and low economic efficiency of agricultural biogas plants. Specifically, the construction of such installations is associated with substantial capital expenditures, high operational costs, low profitability, and, consequently, extended investment payback periods [28]. Economic and financial risk also includes high sensitivity to market fluctuations, which is why Klimek et al. [29] advocate systemic financial support for these investments during their development phase. According to these authors, such support would shorten the payback period and encourage potential investors to engage in biogas plant construction.

Another economic risk inherent in these types of projects is the potential decline in revenue. According to Igliński et al. [30], key revenue streams for agricultural biogas plants in Poland include the sale of generated electricity, the trading of certificates or guarantees of origin, distribution of process heat from cogeneration, sale of digestate as fertilizer, and fees for accepting and processing organic waste. Economic and financial risks are therefore linked not only to energy prices, the value of green certificates, and fees for agricultural waste disposal, but also to the operating costs of the biogas plant.

Among the most significant constraints and risks in this area are the volatility of agricultural feedstock prices and the lack of supply chain stability [31], which may be caused, for example, by the closure of agro-processing plants supplying substrates to the biogas plant or by recurring natural disasters such as droughts, floods, or epidemics [32]. Although this instability represents an economic risk, it also intersects with technological, operational, and feedstock-related aspects.

3.2. Technological, Operational and Raw Material Risks and Limitations

A critical aspect within this category is the siting of biogas plants, particularly their proximity to feedstock sources and the ease and continuity of access to those materials. In Poland, agricultural biogas plants are most commonly located near large-scale livestock farms [33]. Another limiting factor is the complex and multi-stage process to construct such facilities [34]. In addition, appropriate design, structural adaptation to local needs and conditions, and technical expertise related to the daily operation and maintenance of biogas installations are of considerable importance [35]. Proper design and the attainment of stable operational parameters are fundamental for achieving consistent and efficient biogas production [36].

This is particularly important because, in practice, the actual electricity output from cogeneration systems in biogas plants often falls below the projected levels and may be comparable only to the calorific value of the substrate used [37]. The efficiency of anaerobic digestion depends on various factors, including the type of feedstock, the settings of process parameters, the method of biogas utilization, the strategy for digestate management, the scale of the installation, and the technology employed [37].

Nsair et al. [36] point out that the effectiveness of fermentation in a biogas reactor depends on a range of key technological factors that should be taken into account at the design or equipment selection stage. The most important of these include the following:

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Dry matter (DM) content of the substrate, which determines the choice of fermentation technology. The process may proceed as wet fermentation (DM < 12%) or dry fermentation (DM > 12%).

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Substrate dosing system, which may be implemented in three ways: batch feeding (no input during downtimes), semi-continuous feeding (material added at least once daily), or continuous feeding (a constant inflow of substrate).

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Number of fermentation stages, distinguishing between single-phase systems, in which all reactions occur in one reactor, and two-phase systems, in which hydrolysis and methanogenesis occur in separate chambers, allowing for improved control of individual stages.

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Temperature range of the process, which can be adapted to operating conditions: psychrophilic (below 25 °C), mesophilic (37–42 °C), or thermophilic (50–60 °C).

The anaerobic digestion process comprises four successive phases, each involving distinct groups of microorganisms responsible for specific biological transformations. Ensuring high efficiency and stability of this process requires continuous monitoring and appropriate management of environmental conditions at each stage [38]. This, in turn, necessitates specialized knowledge and technical solutions, which contribute to the complexity of both operation and maintenance. The latter aspect is inherently linked to the risk of equipment failure, which is indirectly influenced by the technological solutions applied.

As noted by Singh [39], the mixing system within an anaerobic digestion reactor plays a crucial role in maintaining process stability and achieving high performance. However, it is also frequently identified as a primary source of technical problems and system failures. Additionally, technical and operational risks are closely related to the safety of biogas plant infrastructure during operation.

According to Gadirli et al. [40], biogas plants are considered high-risk investments due to several factors. Such risks may include exposure to toxic substances generated during fermentation processes, work conducted in confined spaces, the potential for electric shock, and the hazard of falling from heights. These researchers [40] also emphasized that biogas infrastructure is exposed to hydrogen sulfide—a gas with toxic and highly corrosive properties. Its presence leads to the deterioration of storage tanks, pipelines, and engine components, ultimately accelerating technical degradation and shortening the overall service life of the system.

3.3. Social Risks and Constraints

Another significant constraint and risk associated with the construction and operation of biogas plants pertains to social aspects. As reported by Piechota et al. [33], nearly half of biogas-related investments in Poland face social opposition. This underscores the need for effective social-risk management, including procedural transparency, dialog with stakeholders, trust-building, and appropriate site selection [41]. Negative perceptions of such investments, poor communication with stakeholders—particularly local residents—proximity to residential areas, and distrust from local authorities can significantly delay or even halt a project [41].

Numerous documented cases of biogas plant development indicate the frequent presence of the so-called NIMBY (Not In My Back Yard) syndrome within local communities [42]. This attitude is characterized by general support for renewable energy technologies in principle, but opposition to their implementation in the immediate vicinity of one’s residence. Community resistance and the NIMBY effect in the context of renewable energy development are often driven by concerns about odor, noise, potential health impacts, visual disruption of the landscape, and possible reductions in property values [43].

For this reason, Dima et al. [44] propose that biogas plant feasibility analyses should incorporate Geographic Information Systems (GISs). In the era of growing automation and digitalization, GISs support human decision-making, serving as an advanced system for managing, analyzing, and visualizing spatial data [45,46,47]. The integration of GISs with other information sources enables the modeling and simulation of environmental phenomena, providing a more accurate understanding of spatial patterns and processes [48,49,50].

GISs are applied in many fields—from public health, where it supports the monitoring of disease spread [51], to economics, where it enables spatial market analysis [52], to urban and engineering planning, where it assists in spatial development and infrastructure management [53], as well as environmental governance [54,55,56]. In the context of this study, GISs are particularly relevant for identifying appropriate locations for energy infrastructure projects such as agricultural biogas plants [57,58], potentially reducing or eliminating opposition from local communities.

A serious challenge to the development of agricultural biogas plants lies not only in localized resistance to individual projects but also in the generally negative public perception of such facilities. As noted by Martinát et al. [59], biogas plants are often viewed unfavorably due to their association with environmental nuisances such as unpleasant odors, noise, and the perceived loss of tourism potential in a given area. Moreover, the allocation of high-quality arable land for energy crop cultivation is controversial, as it may limit food production and thus intensify resistance among rural populations.

Public mistrust is also exacerbated by the lack of transparency in investment processes, the limited scope of public consultations (often reduced to a formal procedure), and the concealment of potential environmental and social impacts of planned installations. All these factors highlight the necessity of actively shaping a positive image of biogas plants—both in general public discourse and in relation to specific investments.

Social acceptance and a favorable public reception of such projects are essential and should be treated as key instruments in the planning, construction, and operation of biogas plants. These aspects have a direct impact on stakeholder relations and the overall success of the investment [60].

3.4. Environmental and Health-Related Risks and Constraints

Naturally, efforts to shape a positive image of the biogas sector must not overlook the environmental and health risks associated with such activities. Some health hazards have already been discussed above, as they intersect with operational risks; however, the scope of these threats is broader, since the industrial processes carried out in biogas plants also pose risks to the health of both plant workers and nearby communities [61].

As noted by Tamburini et al. [61], working environments in biogas plants exhibit elevated concentrations of particulate matter (PM), microbiological agents, endotoxins, and volatile organic compounds (VOCs). These authors pointed out that both employees and local residents are potentially exposed to various pollutants, including PM₁₀ and PM₂.₅, ozone, nitrogen dioxide, sulfur dioxide, selected bacteria and fungi, endotoxins, and certain VOCs.

In their assessment of the environmental and climate impacts of agricultural biogas production, Møller and his research team [62] acknowledged the environmental benefits of biogas but also identified several potential threats. These include, in particular, an increased potential for ammonia emissions from digestate used as fertilizer, which may exceed the emissions from untreated cattle and pig slurry. Methane leakage—given its high global warming potential—was also identified as a critical risk, capable of significantly undermining the overall climate balance of the project and weakening its ecological value. High ammonia emissions additionally contribute to air quality deterioration and environmental acidification.

A reliable environmental impact assessment of biogas plants requires comparative research into the composition of exhaust gases emitted during biogas combustion in relation to those produced from natural gas combustion. Such studies were conducted by Macor and Benato [63], who found that engines powered by biogas, when operated without appropriate purification systems, can pose significant environmental and health hazards. These include emissions of nitrogen oxides (NOₓ) and, in some cases, sulfur oxides (SOₓ) and toxic micro-contaminants.

Other environmental risks associated with the operation of agricultural biogas plants include odor nuisance [64]; emergency incidents and risks of leakage, explosion, or fire [65]; the promotion of monoculture energy crops and potential deforestation for their cultivation [66]; human exposure to pathogens and bioaerosols [61]; increased transport traffic, noise, and adverse landscape changes around the facility; and alterations in soil chemistry following the application of digestate, such as heavy metal accumulation and elevated pH levels.

3.5. Regulatory and Legal Risks and Constraints, Including Political Factors

A significant barrier to the development of agricultural biogas plants is the complexity and ambiguity of legal regulations governing the construction process and its various stages [67,68,69]. Siwkowska [70] emphasizes that the scope of the required procedures and permits depends on the type and capacity of the renewable energy installation, which determines the need to obtain specific administrative decisions in accordance with applicable legislation.

Table 2. Analysis of the investment process for agricultural biogas plants—legal regulations and risks.

Stage of the Construction Process	Applicable Legal Acts	Threats and Constraints
Concept and feasibility study	Energy law [72] Renewable Energy Sources Act [14,73]	Low profitability, financing uncertainty, and limited expertise
Investment location	Act on Spatial Planning and Development [74], Act on the Protection of Agricultural and Forest Land [75]	Difficulties in obtaining a suitable location, social conflicts, and planning restrictions
Environmental impact assessment	Providing access to environmental information [76], Regulation of the Council of Ministers of 9 November 2004 [77], Regulation of the Minister of the Environment of 9 December 2014 on the Waste Catalogue [78], Environmental Protection Law [79]	The risk of having to prepare an Environmental Impact Assessment report, lengthy procedures, and the possibility of public opposition
Zoning decision, development plan	Act on Spatial Planning and Development [74]	Plan non-compliance and zoning issues
Installation design	Regulation of the Minister of Agriculture and Rural Development of 20 April 2023 [80] Renewable Energy Sources Act [14,73]	Human resource or technological deficiencies and challenges in complying with technical and environmental regulations
Notification of construction works—building permit procedure	Construction Law [81] Act of 13 July 2023 on Facilitating the Preparation and Implementation of Investments in Agricultural Biogas Plants and Their Operation [82]	Lengthy decision-making timelines and complicated administrative procedures
Environmental and waste management decisions	Act of 14 December 2012 on Waste [83] Regulation of the Minister of the Environment of 9 December 2014 on the Waste Catalogue [78]	Stringent waste management and emission regulations, along with high compliance costs
Construction of an installation	Act of 13 July 2023 on Facilitating the Preparation and Implementation of Investments in Agricultural Biogas Plants and Their Operation [82]	Implementation delays, increased construction costs, and contractor-related issues
Notification of construction completion occupancy permit	Act of 13 July 2023 on Facilitating the Preparation and Implementation of Investments in Agricultural Biogas Plants and Their Operation [82]	Obligation to comply with technical standards and the risk of denial of use permit (occupancy approval)

presents an analysis of the investment and construction process of an agricultural biogas plant, along with the corresponding legal acts. Kochanek et al. [71] outline a framework describing the planning, design, and construction stages of a biogas plant, based on the relevant legislative instruments.

The construction of a biogas plant requires obtaining the necessary permits and approvals from local authorities. Depending on the type of activity and the specific location, approvals must also be secured from government agencies, environmental protection bodies, and other competent institutions [84]. Every agricultural biogas plant must be registered in the national registry maintained by the National Agricultural Support Centre. Investors often encounter difficulties in acquiring key administrative decisions, such as environmental permits, construction permits, and waste processing authorizations—all of which are essential to commence operations [85]. An additional challenge lies in the absence of coherent guidelines regarding the siting of biogas plants within the framework of local spatial development plans. This frequently leads to delays or requires changes to the initially proposed investment location.

The use of dedicated geospatial data techniques [86] enables a more detailed and informed approach to planning new construction projects [87]. This applies to facilities such as wastewater treatment plants and waste landfills [88], as well as photovoltaic farms [89] and agricultural biogas plants [71].

4. Benefits of Constructing and Operating Agricultural Biogas Plants

The construction and operation of agricultural biogas plants generate multidimensional benefits that can be classified according to various criteria. In this study, the authors adopt a division into four principal yet overlapping categories: economic, social (including local), environmental and climatic, and energy-related.

Operating an agricultural biogas plant provides numerous economic advantages for farms. It enables on-site generation of electricity and heat, significantly reducing energy purchase costs and, under certain conditions, even achieving full energy self-sufficiency [89]. In addition, surplus energy sold to the grid provides a stable income stream, while the utilization of by-products such as heat and digestate as fertilizer reduces heating expenses and agricultural input costs [90]. Experience from existing installations shows that the profitability of biogas plants largely depends on prevailing energy prices, which are in turn shaped by political and regulatory conditions. Under favorable tariffs and high self-consumption, such systems can reach an acceptable payback period for individual agricultural holdings [91].

As observed by Dębicka et al. [92], biogas plants are a distinctive form of renewable energy as they enable energy storage in the form of biogas. This energy can be released during peak demand periods through electricity production in cogeneration units, thereby optimizing the economic performance of the plant. Furthermore, the biogas can be upgraded to purified methane and either injected into the distribution grid or liquefied and sold as bio-LNG [92].

Another key benefit of operating a biogas plant on a farm is the ability to process agricultural waste, significantly reducing the costs associated with organic waste disposal [93]. In this way, waste becomes a valuable resource for energy and fertilizer production. Moreover, the generation of green, self-produced energy makes it possible to avoid carbon emission charges, providing a safeguard against rising regulatory costs. Biogas investments also support local economic development and job creation in rural areas [93]. Employment in this sector generates a multiplier effect—each job in a biogas plant leads to the creation of additional jobs in the surrounding local economy [94].

The example of Danish biogas plants, which often operate under a cooperative model, shows that local involvement and shared decision-making foster the development of the social economy and strengthen the long-term integration of such projects within rural communities. It also supports the development of human capital in those communities [94]. Naturally, the social impact of biogas development varies between countries, depending on their level of economic development [95]. In lower-income countries, biogas plants can serve as tools for combating energy poverty and unemployment, contributing to societal modernization and improved quality of life [95]. In economically developed countries, the social effects may be less transformative but still offer tangible benefits to local communities [95].

Another important advantage of agricultural biogas plant development in Poland is its contribution to achieving climate neutrality [92]. As Muradin and Foltynowicz [96] point out, biogas installations using waste from the agri-food sector combine stable electricity and heat production with effective waste management. They also support local industry and agriculture, and with adequate legislative support, they can substantially reduce greenhouse gas emissions while delivering real economic benefits to rural communities.

From an environmental protection perspective, the biomass fermentation process reduces the negative impacts of improper waste management by minimizing the harmful effects of organic waste on the natural environment [97]. Anaerobic digestion stabilizes and deodorizes raw manure [97], significantly reducing odor emissions and the risk of surface and groundwater contamination. At the same time, the process enables efficient utilization of organic agricultural waste for biogas production. Rather than allowing methane to escape into the atmosphere during natural decomposition in landfills, it is captured and converted into energy. This contributes to the reduction in greenhouse gas emissions, improves the energy balance of farms, and supports the transition toward a more sustainable and low-emission energy system [98].

The benefits of agricultural biogas plant development extend beyond direct economic gains. They improve resource management within farms and enhance the energy resilience of rural areas. Integrating energy production with local material cycles promotes more efficient waste utilization and the development of more sustainable agricultural models. In this way, biogas plants become not only instruments of energy transition but also catalysts for the development of rural communities and the agriculture of the future.

5. Materials and Methods

The aim of the study was to explore the opinions of Polish farmers regarding their concerns and perceived benefits related to agricultural biogas investments. The main research problem and specific research questions were formulated.

The main research problem was, “How do Polish farmers assess the risks and benefits associated with launching agricultural biogas plants?”

The specific research questions were as follows:

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What types of risks do Polish farmers perceive in the operation of agricultural biogas plants?

What benefits do they identify in the construction and operation of such facilities?

To properly fulfill the research objective, the following hypothesis was adopted for verification: Farmers who own a biogas plant perceive more benefits and lower risk associated with such investments compared to those who do not own such facilities.

In order to achieve the research objective and answer the formulated questions, a survey was conducted using a questionnaire. The study population included farmers who were owners or co-owners of biogas plants, as well as those without such infrastructure, including those planning to build an agricultural biogas plant.

The subject of the study was the perception of biogas plants by farmers, taking into account the entire investment process (planning, implementation, and operation). The research was conducted in the second quarter of 2025 using the CAWI and CATI methods, through an electronic questionnaire distributed via email to active biogas plants in Poland and through the social media of associations, groups and institutions supporting farmers (including the Foundation for the Development of Polish Agriculture (1800 members), Biogas Plants Poland (1500 members), Polish Association of Cereal Producers (1700 members), Union of Biogas and Biomethane Industry Producers and Employers (492 members), Polish Corn Producers Association (1100 members), Polish Federation of Cattle Breeders and Dairy Producers (4700 members), Independent Association of Polish Cattle Breeders (772 members), Polish Agricultural Association (1400 members), Polish Farmers’ Union (184 members), Polish Association of Pig Breeders and Producers Polsus (1700 members), Biogas Plants (43 members).

Contact was made with 11 independent collective entities with the potential to reach 15,391 interested individuals, who were invited to participate in the study, either as individual farmers or as affiliated agricultural operators.

Due to difficulties in acquiring respondents, purposive sampling was applied, with greater emphasis on the qualitative nature of the study, while also employing statistical analysis methods, including descriptive statistics and measures of central tendency.

In selecting potential investment locations, Geographic Information System (GIS) tools were used to conduct a comprehensive spatial analysis. A multi-criteria approach was applied, taking into account a range of key factors influencing the profitability and feasibility of biogas plant construction.

Preselection of plots was carried out based on the conjunction of datasets obtained through the extraction and transformation of multi-layer spatial information using GISs and ETL (Extract, Transform, Load). This process included the processing, normalization, and scaling of data to values consistent with the assumed algorithm schema. Subsequently, during the analysis phase, plots that met the initially defined criteria were identified using both classical segmentation methods and machine learning algorithms. This enabled the selection of plots for further stages of research (Figure 1).

In order to increase the precision of the analysis and to take into account the diverse factors influencing the value and development potential of individual areas, a set of evaluation criteria has been developed, with appropriate weights assigned to reflect their relative importance in the decision-making process.

The defined criteria together with their assigned weights are as follows:

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Land development—weight 0.05 (indicates existing land use, which affects the development potential of the area);

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Distance to watercourses—weight 0.2 (proximity to watercourses may limit building possibilities and increase flood risk, thereby reducing land value);

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Distance to high-voltage power lines—weight 0.1 (a factor important from the perspective of safety and access to utilities);

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Distance to roads—weight 0.1 (better transport accessibility positively influences the attractiveness of the plot);

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Distance to surface water bodies (PTWP)—weight 0.2;

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Distance to forests—weight 0.05 (esthetic and environmental aspects can constitute an additional advantage of the location);

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Land slope (inclination)—weight 0.1 (affects the possibilities of land development and structural stability).

The determination of the assigned weights makes it possible to prioritize the relevant variables, which in turn leads to generating more precise forecasts regarding optimal locations in the context of spatial analysis.

Establishing assigned weights allows for the prioritization of significant variables, which in turn leads to generating more accurate forecasts regarding optimal locations in the context of spatial analysis.

Based on the data collected and the analysis conducted, areas were identified, primarily at the municipal level, that offered particularly favorable conditions for the location of biogas plants. Respondents were then selected from these areas using stratified sampling, to include both farmers with operational experience in biogas and those still considering such an investment. This approach made it possible to gather a diverse research dataset, reflecting the perspectives of both practitioners and potential investors.

A total of 130 farmers participated in the study, including 49 who owned a biogas plant and operated it actively and 80 who did not own one, regardless of their future investment intentions. The questionnaire consisted of 18 questions, including 8 demographic questions and 10 relating to farmers’ opinions on biogas plants.

Demographic questions addressed the size of the farm, production profile, farm location, legal form of the business, current use of clean energy sources and plans in this area, as well as the size of any existing biogas installation. In expressing their opinions on biogas plants, farmers assessed economic and financial risks (e.g., investment costs, payback period), technological risks (e.g., possibility of breakdowns, operational complexity), operational and feedstock risks, social risks (e.g., local community acceptance, impact on the neighborhood), environmental risks (e.g., odor emissions, water contamination), regulatory and legal risks, including political issues related to planning, design, construction and operation of agricultural biogas plants, as well as the benefits (defined as the best ratio of inputs to gains) resulting from biogas plant ownership, such as economic (e.g., additional income from energy sales, fertilizer savings, subsidies), environmental (e.g., reduction in greenhouse gas emissions, improved agricultural waste management), social and local (e.g., job creation, development of local infrastructure, increased income for local farms, improved household well-being), and energy-related (e.g., energy savings, energy independence).

Process of Data Analysis from the Survey Study

The analysis of the empirical material began with the Shapiro–Wilk test to determine whether the data followed a normal distribution, which is necessary for the appropriate selection of statistical methods. In the next stage, descriptive statistics were used to present measures of central tendency, standard error, and variance, as well as frequency and percentage distributions.

Due to the observed slight skewness and kurtosis indicating mild flattening—most distributions showed negative skewness, meaning that higher ratings prevailed (i.e., more responses in the 4 and 5 range), while kurtosis values were negative or close to zero, indicating that the distributions were slightly flatter than a normal distribution—it was decided to apply nonparametric statistical methods in the in-depth analysis. The analysis also included the use of the bootstrap method with 1000 resamples and a 95% confidence level to increase the accuracy of the analysis, given the relatively small sample size.

In the second stage, statistical significance was tested using Kendall’s tau-b rank correlation and Spearman’s rank correlation in order to identify relationships between variables characterizing the surveyed farms—such as farm size, main type of agricultural activity, or size of the biogas plant—and the perceived risks and benefits associated with renewable energy investments. Additionally, the bootstrap resampling method [99] was applied to improve the accuracy of nonparametric estimators in small samples.

To verify the methodological validity of the selected approach, a parallel analysis using the traditional Kendall’s tau-b method without bootstrapping was also conducted, and the results were compared with those obtained through the bootstrap method. This comparison confirmed the comparability of both methods and the justification for using the latter. In conclusion, the bootstrap method did not alter the pattern of relationships between variables, indicating that both the Kendall’s tau-b correlation coefficients, their statistical significance, and the inter-variable relationships remained essentially the same across both methods. However, the bootstrap approach improved the precision of estimation and the reliability of the results. To specify the results and calculated effects (w) from the Kruskal–Wallis analysis, an additional post hoc analysis was performed using the Dunn-Bonferroni test, and the effect (r) was calculated for statistically significant results. In the final stage, the Kruskal–Wallis test was used to analyze differences in perceived levels of risk and benefit from biogas investments among five groups of farms: those with biogas plants (distinguished by scale) and those without.

The statistical analysis was conducted using PS IMAGO PRO 10.0 based on IBM SPSS Statistics 29.

6. Results

A total of 130 farmers participated in the study, including individuals representing biogas sector corporate entities (e.g., company presidents), which implies that the effective representation of the biogas plant population is greater than the actual number of respondents. The sizes of the farms operated by the surveyed farmers are presented in Figure 2. The distribution of the main production profile among the surveyed farmers is presented in Figure 3. The survey only took into account the general dominant nature of agricultural activity in a given farm: breeding, cultivation or the mixed nature of the farm. No detailed characteristics of agricultural activity were taken into account due to the high fragmentation of farms in Poland and the rather complex characteristics of their activities. In Poland, the largest share is held by cattle, poultry, pig breeding, or, less frequently, sheep and goats. In the case of agricultural cultivation, cereals occupy the significant majority of the cultivated area, followed by industrial plants (rapeseed and sugar beets), potatoes, fodder plants, and fruit (mainly apples). In this survey, two predominant categories were identified: mixed agricultural production (both crop and livestock), reported by 50.8% of respondents, and crop-only production, indicated by 42.3%. A small proportion (6.2%) specialized exclusively in livestock farming. One respondent (0.85%) declined to answer this question.

The majority of respondents (68.5%) operated small farms with an area of up to 5 hectares, which corresponds to the general structure of land ownership in Poland, characterized by high fragmentation and heterogeneity. A considerably smaller share of farmers (18.5%) managed farms between 6 and 15 hectares, while 6.9% owned farms ranging from 21 to 50 hectares. The two smallest groups, accounting for 4.6% and 1.5% of the sample, respectively, operated farms with an area of 16 to 20 hectares and over 50 hectares.

The largest share of agricultural holdings was located in rural municipalities—82.3% of those surveyed and 12.3%. The vast majority (83.8%) of them operated as individual farms, while the remaining 16.2% were owned by capital companies operating in the biogas sector.

The analysis of farms in terms of the renewable energy sources (RESs) used revealed substantial variation. Farmers employed both individual RES technologies and combinations of multiple sources to improve energy and heat efficiency. This approach is characteristic of Poland’s transitional temperate climate, which is marked by considerable variability in weather conditions throughout the year. Such seasonal fluctuations may influence agricultural energy strategies by affecting the availability and effectiveness of renewable energy technologies on farms. Therefore, the selection of RES technologies must take into account local climatic conditions, such as solar irradiance, wind frequency and strength, and the availability of biomass.

Within the surveyed group, 27.7% of farmers did not use any form of renewable energy. The second-largest group consisted of those utilizing various RES combinations. The most frequently used RES technology was photovoltaics (23.1%), often integrated with other RES systems, including biogas plants (12.3%), heat pumps (11.8%), and wind energy (1.5%). Additionally, 6.2% of farms employed photovoltaic systems in combination with several other RES technologies.

The second most common category in terms of single-source RES use comprised farmers relying exclusively on biogas plants—8.5% of respondents. However, when including mixed energy and heat strategies combining biogas with other RES technologies (e.g., heat pumps, solar panels, and wind turbines), biogas plant users represented the second-largest group overall (19.2%) in terms of diversified RES usage.

Only 35.4% of the surveyed farmers indicated that they did not plan to invest in biogas or other RES technologies. The remaining participants expressed interest in a variety of future RES investments. For instance, 23.1% planned to establish a biogas plant, while an additional 4.6% intended to develop biogas systems integrated with other RES technologies. A total of 13.1% reported plans to install photovoltaic systems, and another 4.6% expressed interest in mixed RES setups involving photovoltaics. Exclusive interest in heat pumps was reported by 11.5%, and 3.8% of respondents planned to invest in wind power. When considering hybrid strategies involving wind turbines along with other RES systems (e.g., heat pumps, biogas, photovoltaics), 2.3% of respondents expressed a preference for such integrated solutions. The total percentages do not sum to 100% because respondents were able to indicate multiple planned RES investment combinations. Grouping certain RES categories was intended to provide a general overview of respondent preferences.

In addition to the mean values used to distinguish perceived risk among the respondents,

Table 3. Descriptive statistics: mean, standard error, standard deviation, variance.

Risks and Benefits of Owning a Biogas Plant	N	Range	Mean	Median	Mode	Std. Error	Std. Dev.	Variance
Economic and financial risk associated with investing in a biogas plant (e.g., investment costs, payback period)?	129	4	2.64	3	3	0.098	1.110	1.231
Technological, operational and raw material risks of the biogas plant (e.g., potential failure, complexity of operation)?	130	4	2.47	2	2	0.100	1.136	1.290
Social risk associated with a biogas plant (e.g., acceptance by the local community, impact on the neighborhood)?	130	4	2.77	3	3	0.096	1.096	1.202
Environmental risks associated with a biogas plant (e.g., odor emissions, water pollution)?	130	4	2.38	2	1	0.103	1.176	1.384
Regulatory and legal risks (including political): planning, design, construction and operation of an agricultural biogas plant?	130	4	2.79	3	3	0.094	1.069	1.143
Economic benefits of owning a biogas plant (e.g., additional income from energy sales, savings on fertilizers, subsidies)?	129	4	3.62	4	4	0.106	1.200	1.441
Environmental benefits of a biogas plant (e.g., reduced greenhouse gas emissions, better management of agricultural waste)?	129	4	3.78	4	5	0.108	1.226	1.504
Social and local benefits of biogas plants (e.g., creation of new jobs, development of local infrastructure, increase in income of local farms, improvement of household well-being)?	129	4	3.61	4	5	0.109	1.233	1.520
Energy benefits of biogas plants (saving energy costs, energy independence)?	128	4	3.84	4	5	0.103	1.169	1.367

presents basic descriptive statistics.

An analysis of respondents’ response frequency (Figure 4) clearly indicates that the greatest perceived benefits and risks are associated with investments in biogas plants.

As shown in Figure 4, biogas is definitely in first place in the perception of the most profitable and least risky RES technology, with low variability of opinions of the surveyed farmers. Photovoltaics also enjoys great trust. Other technologies (wind, heat pumps) have lower indications and greater differences in assessments, which may indicate less experience or investment uncertainty.

This is consistent with the farmers’ assessment of the risks associated with investing in biogas plants, which they evaluated using a five-point scale (1–5), where (1) indicated the lowest and (5) the highest level of perceived risk (Figure 4). Overall, these concerns were rated as low to moderate, with mean scores ranging from 2.38 to 2.79 and medians from 2.0 to 3.0.

The lowest perceived risk was attributed to environmental factors (mean = 2.38; median = 2.0), suggesting that biogas plants are viewed as posing minimal environmental threat, followed by technological risk (mean = 2.47; median = 2.0) and economic-financial risk (mean = 2.64; median = 3.0), although the latter was characterized by considerable variation in responses (standard deviation = 1.11).

The highest levels of concern—though still within the moderate range—were associated with regulatory and legal risks (including political factors), which encompass processes such as planning, design, construction, and operation of agricultural biogas plants (mean = 2.79; median = 3.0), as well as with social risk (mean = 2.77; median = 3.0), related to issues such as lack of community acceptance or perceived adverse effects on neighborhood well-being. The presented results regarding the perceived risk of investing in biogas plants by the surveyed farmers (Figure 5 and Table 3) show that the respondents are unanimous in their opinions. Taking into account additionally the trends, it can be indicated that the risk is perceived by them as moderate at most.

The surveyed farmers rated the benefits of owning a biogas plant significantly higher (Figure 5). The highest-rated advantages were energy-related (mean = 3.84; median = 4.0), particularly those linked to energy security and financial savings. Environmental benefits were also rated highly (mean = 3.78; median = 4.0), including the reduction in greenhouse gas emissions and improved management of agricultural waste.

Economic benefits—such as additional income from energy sales, savings on fertilizers, and access to subsidies—received slightly lower ratings (mean = 3.62; median = 4.0), as did social benefits (mean = 3.61; median = 4.0), understood to include job creation, development of local infrastructure, increased income for rural households, and improved overall household well-being (Figure 6). The results of the assessment of the benefits of investing in biogas plants are clearly high, and, taking into account the standard deviation and standard error (Table 2), they show a certain homogeneity of the respondents’ opinions, although slightly smaller than in the case of the risk assessment. The greatest diversity of opinions was noted in the case of the perception of social and environmental benefits; perhaps extending the research with in-depth interviews could increase the precision of the obtained results.

The results of the analysis using Kendall’s tau-b and Spearman’s rank correlation for the following variables—farm size, biogas plant capacity (kW), main agricultural production profile, most beneficial type of investment, lowest perceived risk, plans for investing in RES, and preferences regarding the development of the biogas sector—revealed several statistically significant relationships.

In addition to Kendall’s tau-b and Spearman’s rho coefficients, two-tailed significance tests were applied (p < 0.05 and p < 0.01), along with 95% confidence intervals, using a bootstrap method with 1000 samples. The analysis was conducted with full methodological rigor and includes both the direction and strength of the observed correlations.

A statistically significant negative correlation was found between the size of a biogas plant and the perception of RES investments as “low-risk” (Kendall’s tau-b = −0.24, p = 0.025; Spearman’s rho ≈ −0.26, p = 0.024), both satisfying the p < 0.05 criterion. The negative direction indicates that farmers operating larger biogas installations are more likely to view RES investments as relatively low-risk.

A significant positive correlation was also identified between the perceived benefits of biogas plants and farmers’ willingness to invest in RES. The correlation with the variable “most beneficial clean energy investment” yielded Kendall’s tau-b ≈ 0.36 (p < 0.01) and Spearman’s rho ≈ 0.40 (p = 0.001), suggesting that farmers who recognize greater benefits—economic, environmental, or social—are more inclined to invest in other renewable energy technologies.

The analysis also showed a significant association between RES investment plans and the main agricultural production profile (Kendall’s tau-b ≈ −0.30, p < 0.01; Spearman’s rho ≈ −0.35, p < 0.01), both meeting the p < 0.01 significance threshold. Cross-tabulation results indicate that farmers involved in mixed production (crop and livestock) were most likely to plan biogas investments (36.4%) or reported no investment plans (37.9%). In contrast, crop-oriented farmers were more likely to plan investments in photovoltaics (25.5%) and heat pumps (18.2%), with only 10.9% intending to invest in biogas. Additionally, 29.1% of this group reported no current plans for RES investment. Among livestock-oriented farmers (the smallest subgroup), 25% expressed an interest in biogas investments, while 37.5% had no such plans.

The relatively high proportion of farmers not planning any RES investment highlights the need for more targeted outreach strategies and promotional efforts. These should emphasize the tangible benefits of biogas to foster development in this segment of the RES sector.

A significant positive correlation was also found between farm size and production profile (Kendall’s tau-b = 0.34, p = 0.001; Spearman’s rho = 0.37, p = 0.001), indicating a moderately strong relationship. Cross-tabulations revealed that smaller farms (up to 5 hectares) predominantly engaged in crop production (49.5%) or mixed farming (43.8%), while only 5.6% focused on livestock. Farms of 6–15 hectares mostly practiced mixed production (62.5%), with 25% engaged in crops and 12.5% in livestock. Medium-sized farms (16–20 ha) preferred mixed production (66.6%) and less commonly crop-only (33.3%). Farms sized 21–50 ha were also mostly mixed (66.7%), and all farms larger than 50 ha (100%) practiced mixed production.

Animal husbandry was generally less common across the surveyed sample, which was dominated by small farms: 62.5% had an area of up to 5 ha, and 37.5% between 6 and 15 ha. This may reflect higher investment thresholds or a broader decline in livestock production.

No statistically significant correlations were found for some hypothesized relationships, such as the size of the biogas plant and plans for further RES investment, or the link between plant size and perceptions of the most beneficial RES technologies.

Apart from its relationship with plant size, risk perception was not significantly correlated with other variables, such as perceptions of the most beneficial type of RES investment (both Kendall’s tau-b and Spearman’s rho ≈ 0; p > 0.4).

Several other seemingly intuitive relationships also lacked statistical support. For instance, farm size was not significantly associated with plans for RES investment (Kendall’s tau-b = 0.13; Spearman’s rho = 0.22; p = 0.2), failing to meet the p < 0.05 threshold. This suggests that farmers’ declared investment intentions are not necessarily tied to the size or scale of agricultural operations but may instead be influenced by more complex factors.

Similarly, no significant correlation was found between farm size and farmers’ preferences regarding the development of the biogas sector.

The absence of such correlations may indicate the presence of more nuanced mechanisms shaping farmers’ attitudes and motivations toward investing in RES, particularly in the biogas segment. These insights may inform future support programs by suggesting that such initiatives can be effectively directed at all interested parties, regardless of farm size or production scale.

An interesting aspect of the analysis is the comparison of perceived benefits and risks among biogas plant owners, visualized using a Kendall’s tau-b correlation heat map (Figure 7). In this map, τ ≈ 0 indicates no correlation, τ ≈ 1 denotes a strong positive correlation, and τ ≈ −1 indicates a strong negative correlation. The color scale represents the strength and direction of correlations: green indicates a strong positive relationship, light green means positive moderate correlation, yellow indicates weak or no significant correlation, orange means negative moderate correlation, and red indicates quite strong or strongly negative correlation.

The results clearly show that the perception of economic benefits is strongly positively correlated with energy benefits (τ = 0.656), social benefits (τ = 0.657), and environmental benefits (τ = 0.655). This suggests that farmers who identify economic and financial advantages from owning a biogas plant are also more likely to perceive associated social, environmental, and energy-related benefits.

The perception of benefits appears to be inversely related to the perception of risk. The analysis revealed a strong negative correlation between perceived economic benefits and financial risk (τ ≈ −0.325), as well as between energy benefits and financial risk (τ ≈ −0.265). In other words, the greater the perceived financial risk of biogas investment, the less likely farmers are to acknowledge its economic and energy benefits—and vice versa.

Financial risk is moderate and negatively correlated with environmental benefits (τ ≈ −0.282), indicating that farmers who perceive investing in a biogas plant as financially risky are less likely to see its environmental benefits. Additionally, the analysis found moderate positive correlations between perceived social and environmental risks (τ = 0.424), as well as between environmental and technological risks (τ = 0.405).

In summary, the application of Kendall’s tau-b and Spearman’s rank correlation methods provided a coherent and complementary view of the relationships among the studied variables. Kendall’s tau-b generally indicated stronger associations, while Spearman’s rho revealed somewhat weaker relationships in certain cases. Together, these methods strengthened the reliability of the analysis and enhanced confidence in the findings.

To further explore group differences, the Kruskal–Wallis H test was used to determine whether evaluations of different types of risks and benefits associated with biogas investments varied depending on the size of the biogas installation operated by the farm (

Table 4. The size of the biogas plant owned by the farm and the assessment of the types of risks and benefits—Kruskal–Wallis test (grouping variable: biogas plant size).

Title 1	Economic and Financial Risk Assessment	Technology Risk Assessment	Social Risk Assessment	Environmental Risk Assessment	Regulatory and Legal Risk Assessment	Assessment of Economic Benefits	Assessment of Environmental Benefits	Assessing Social Benefits	Assessment of Energy Benefits
H Kruskal–Wallis	19.194	33.850	1.155	10.705	2.545	14.722	11.487	6.889	10.886
df	4	4	4	4	4	4	4	4	4
Asymptotic Significance	0.001	0.000	0.885	0.030	0.637	0.005	0.022	0.142	0.028

).

The study found that the size of a biogas plant significantly affects the assessment of economic and financial risk (H = 19.194; p < 0.001), technological risk (H = 33.850; p < 0.001), and environmental risk (H = 10.705; p = 0.030), as well as the perceived economic (H = 14.722; p = 0.005), environmental (H = 11.487; p = 0.022), and energy-related benefits (H = 10.886; p = 0.028) associated with such investments.

By contrast, no statistically significant associations were found with social risk, regulatory and legal risk, or perceived social benefits (all p > 0.05). These results suggest that the evaluation of regulatory risk and social benefits is driven by factors other than the size—or even the presence—of a biogas installation.

When interpreting the results presented in Table 4, it is important to note that higher mean ranks indicate higher perceived levels of risk or benefit within each biogas plant size group.

The Kruskal–Wallis rank test (

Table 5. The size of the biogas plant owned or its absence on the farm and the assessment of the types of risks and benefits—Kruskal–Wallis ranks.

Risks	Size of the Biogas Plant	N	Average Rank	Benefits	Size of the Biogas Plant	N	Average Rank
Economic and financial risk assessment	0	80	72.55	Assessment of economic benefits	0	80	56.47
	1	16	58.03		1	16	76.16
	2	21	36.55		2	21	86.14
	3	9	62.78		3	9	58.67
	4	2	95.50		4	2	91.50
	Total	128			Total	128
Technology risk assessment	0	81	75.77	Assessment of environmental benefits	0	80	57.19
	1	16	47.81		1	16	68.41
	2	21	29.24		2	21	81.26
	3	9	74.11		3	9	74.56
	4	2	100.75		4	2	104.50
	Total	129			Total	128
Social risk assessment	0	81	66.65	Assessing social benefits	0	80	59.14
	1	16	56.78		1	16	69,06
	2	21	64.05		2	21	79,60
	3	9	64.94		3	9	62,94
	4	2	74.00		4	2	91.00
	Total	129			Total	128
Environmental risk assessment	0	81	65.86	Assessment of energy benefits	0	79	57.32
	1	16	46.13		1	16	73.13
	2	21	64.31		2	21	80.19
	3	9	80.00		3	9	60.22
	4	2	120.75		4	2	102.00
	Total	129			Total	127
Regulatory and legal risk assessment	0	81	65.30	Legend:
	1	16	56.53	0—no biogas plant
	2	21	71.76	1—up to 50 kW
	3	9	66.94	2—from 50 to 150 kW
	4	2	41.00	3—from 150 to 500 kW
	Total	129		4—over 500 kW

) showed that farmers operating the largest biogas plants perceive significantly higher technological risk compared to those with smaller installations.

Larger biogas plants were perceived as more technologically risky due to the greater complexity of processes and the scale of operations. At the same time, they exhibited lower financial risk, which stemmed from economies of scale, greater revenue stability (as most large biogas plants belong to capital groups operating in the biogas sector), and easier access to financing. These factors translated into higher financial benefits. Farmers without biogas plants also assessed the investment risk as relatively high, though slightly lower than those operating large-scale plants of 500 kW. Perceptions of technological risk were highest in these two groups.

Calculation of effects (w) for the Kruskal–Wallis test indicated the validity of conducting a post hoc Dunn analysis with Bonferroni correction and calculation of the effect size to emphasize the significance of the observed differences. The strongest differences between groups occurred for technological risk (w = 0.512), indicating a very large effect, and financial risk and economic benefits (w = 0.39–0.34, respectively), indicating a medium effect. Small effects were noted for most of the remaining variables and no effect only in the case of social risk. In this case, the assessments were similar regardless of the group.

Dunn’s post hoc analysis with Bonferroni correction revealed that respondents with small biogas plants (up to 50–150 kW) assessed the benefits significantly higher than those without biogas plants (p = 0.011). A statistically significant difference was also found in relation to technological risk between small biogas plants and medium biogas plants (0.0269, p < 0.05) when compared with the results of the Kruskal–Wallis test: small biogas plant—mean rank = 29.24—and medium biogas plant—mean rank = 74.11—which means that owners of small biogas plants perceive significantly lower technological risk than owners of medium installations. A difference close to significance was also observed in the assessment of environmental benefits between respondents without biogas plants and owners of small biogas plants (p ≈ 0.083). This may indicate a trend of higher environmental awareness or experience in the group of owners, but this is not a statistically confirmed difference. The situation is similar in the case of technological risk, where the difference in its assessment between the owners of micro-biogas plants and those who do not have such an installation was close to statistical significance (p ≈ 0.071). This may suggest that users with practical experience perceive technological risk as lower, although the result does not meet the strict criterion of significance. In turn, there is a significant difference (p < 0.001) in the perception of economic and financial risk. This may indicate that owners of small biogas plants (50–150 kW) perceive this risk as significantly lower than those who do not have a biogas plant, and this in turn may result from investment experience, better understanding of operating costs, or subsidies obtained for such an investment. In other cases, post hoc analysis did not show statistically significant differences or trends approaching such significance.

The calculated effect sizes (r) for the Dunn test results revealed several significant and near-significant differences between the respondent groups depending on the size of the biogas plant owned. All comparisons, both significant and borderline in terms of p-values, were characterized by at least a small r effect (0.15–0.22). The largest effect (r = 0.22) was noted for the difference in the assessment of economic benefits between owners of small biogas plants and those without installations. Also, the perception of technological risk and environmental benefits (r = 0.195) showed noticeable differences between small (50–150 kW) and medium biogas plants (from 150 to 500 kW). Despite the fact that not all differences between the studied groups reached the level of statistical significance, such as environmental benefits—small biogas plant vs. no biogas plant (p = 0.83, r = 0.153)—and technological risk—micro-biogas plant vs. no biogas plant (p = 0.071; r = 0.159); the r effect values indicate the presence of clear trends in the perception of risks and benefits, which may have practical and interpretative significance. Regarding environmental risk, the greatest concerns were reported by farmers managing the largest biogas installations—specifically those ranging from 150 to 500 kW and above 500 kW. In contrast, farmers without biogas plants rated environmental risk at a moderate level.

On the other hand, the economic benefits of biogas investment were rated highest by farmers operating plants over 500 kW, while those without biogas plants gave the lowest ratings. This may reflect a lack of operational experience and a correspondingly lower awareness of the potential benefits. The same group also rated energy-related benefits significantly lower compared to owners of large biogas plants, who assessed such benefits as very high.

7. Discussion

The conducted study provided valuable insights into how Polish farmers perceive the risks and benefits associated with investments in agricultural biogas plants. The results indicate that despite the multidimensional nature of these risks, such investments are generally viewed as beneficial—particularly in terms of energy production and environmental impact.

In Section 5, a research hypothesis was proposed: farmers who own a biogas plant perceive more benefits and less risk associated with such investments compared to farmers who do not. The analysis provides partial confirmation of this hypothesis: owners of biogas plants do perceive significantly more benefits from their operation. However, a lower level of perceived risk is reported primarily by owners of small and medium-sized installations; in the case of very large biogas plants, the perception of risk tends to increase.

Thus, the size of the installation influences how both potential benefits and threats are evaluated. Larger biogas plants are considered more profitable and environmentally friendly, but they are also associated with greater operational concerns. In contrast, regulatory and social risks are assessed similarly across all plant sizes, suggesting that these issues are more context-specific than systemic.

The potential for biogas plant development in Poland remains considerable, though unevenly distributed. The findings indicate that this potential is particularly evident among smaller farms, where the adoption of renewable energy sources is still limited. Moreover, the production profile—rather than the size of the farm—emerges as the decisive factor influencing investment decisions. This suggests the possibility of designing universal support programs that are independent of land area.

Owners of biogas plants tend to perceive more advantages from their operation compared to non-owning farmers. This positive evaluation is linked to a greater willingness to invest further in renewable energy, which may be explained by the psychological principle of commitment and consistency, as well-documented in the literature [100].

At the same time, farmers identified regulatory and legal, as well as social risks as the most significant barriers to sector development. These are perceived as more burdensome than economic, technological, or environmental risks. Therefore, simplifying administrative procedures and fostering local acceptance of such investments remain crucial.

Importantly, operational experience with biogas installations—especially larger ones—tends to reduce the overall perception of risk associated with renewable energy investments. The exchange of knowledge and experience between current operators and prospective investors could play a critical role in overcoming cognitive barriers and accelerating sectoral growth.

In conclusion, the further development of agricultural biogas plants in Poland requires strategic measures: simplifying regulations, conducting public awareness campaigns, providing advisory and financial support for small farms, and establishing platforms for knowledge exchange. Effective risk management and the promotion of tangible, well-documented benefits of biogas as a component of sustainable agricultural development are essential to the sector’s advancement.

8. Conclusions

In the context of growing interest in the energy transition of agriculture, this study offers valuable insight into the risk perceptions associated with investments in agricultural biogas plants. Although the purposive sampling strategy and relatively small sample size (approximately 130 respondents) do not allow for broad generalization, the study succeeded in capturing the views of a key group of practitioners directly engaged in investment decision-making. These findings gain additional relevance in light of the estimated national biomethane production potential—reported at 5 billion m³ annually by the President of the Polish Biogas Employers’ Association [101]—and Poland’s notable delay compared to countries such as Germany and France. Bridging this gap will require systemic support, including stable legal frameworks, efficient administrative procedures, appropriate financial instruments, and the dissemination of good investment practices.

The use of nonparametric rank tests and the bootstrap procedure represents an appropriate methodological response to minor deviations from normality, aiming to limit their influence on analytical validity. However, treating the Likert scale as an interval scale remains a known interpretative limitation. In this case, the treatment of the 1–5 Likert scale as interval-level data reflects a widely accepted compromise in social science research. As noted in the literature [102,103], when a Likert scale includes five or more categories, it is often considered acceptable to approximate it as interval data, thereby allowing the computation of means and variances. Therefore, the use of means in the present study is methodologically justified, particularly given the absence of extreme skewness in the data.

It is important to highlight the key limitations of the conducted study as well as possible directions for future research.

Regardless of the statistical findings and the benefits associated with agricultural biogas plants, several limitations of the study should be acknowledged. First, the limited sample size (N = 130) constrains the ability to generalize the results, especially in the context of unavoidable comparison groups. To reduce the risk of Type I error, Dunn’s post hoc test with a conservative Bonferroni correction should be applied. An increase in the observed effects may also result from the presence of additional bias, i.e., not accounting for actual additional benefits. The statistical power of the Kruskal–Wallis tests was moderate to high with respect to key factors (e.g., electrical and economic-financial risk), but a more comprehensive power analysis is recommended, particularly for comparisons between groups including controls. In subsequent stages of the research, it would be advisable to replicate the analyses on a larger and more regionally diverse sample and to consider a longitudinal study design that would enable the examination of changes in the perception of risks and benefits over time. Complementing quantitative analyses with a qualitative component (e.g., interviews with biogas plant users) could help to deepen the interpretation of the results, especially regarding perceptions of the social and environmental aspects of the investment. Additionally, comparative studies involving countries with more developed biogas markets (e.g., Germany, Denmark) could enrich the conclusions by providing a broader international perspective.

It is worth highlighting that the authors conducted a novel analysis of risk perception differentiated by plant capacity, revealing clear disparities in how operational risks are perceived depending on the scale of the biogas installation. The findings emphasize the need to support the biogas sector not only through financial investment, but also through regulatory and educational initiatives. This is consistent with the European Union’s climate policy and the goals of the circular economy, as biogas plants have the potential to become a vital component of sustainable rural development—both in terms of energy cogeneration and biomethane injection into gas distribution networks.

Future research should focus on institutional and regulatory barriers from the perspectives of both investors and public administration, particularly the challenges identified by farmers, who report a lack of clear guidelines and inefficiencies in administrative procedures as key obstacles to sector growth. The proposed risk typology and the compiled dataset form a robust starting point for more in-depth, longitudinal, and representative studies that could provide decision-makers and practitioners with the necessary evidence to effectively support the advancement of the biogas sector in Poland.