1. Introduction
The main direction of agricultural development in Poland is the pursuit of sustainable development [1,2,3]. Next is rational management of material resources [4]. Last but not least is striving for energy self-sufficiency, while maintaining low greenhouse gas emissions. It is an good alternative to con-stantly supported coal solutions [5,6]. Sustainable development as politics, in the sense of processes taking place in enterprises affects many key areas of their activity [7]. Biorefineries play a special role in shaping the new energy reality [8], being a system that connects various devices and biomass conversion processes to produce energy, fuel, and other valuable products [9,10]. The essence of the functioning of biorefineries is as value chains; that is, a series of interrelated activities of specific importance and market value [11,12]. Very important is to know, which can allows one to demonstrate the effectiveness of the implementation of technology using renewable energy sources [13], according to the concept of sustainable development and the implementation of the direc-tion of the circular economy. According to Michael Porter and other researchers [14,15,16], the value chain is a conceptual term of added value, focusing on activities ranging from raw materials to processing into final goods or services. The author divides the organization into two main areas of activity—“basic activities” and “supporting activities”. The former directly relates to creating and delivering a product or service and is linked to the latter in helping improve its effectiveness or efficiency, e.g., through technology development or a management system. The transporting of biomass to biorefineries is a very important element in the value chain. Logistic efficiency consists of the type of biomass, cargo volume, cargo weight, distance, and cost for each kilometer of travel.
Authors made a calculation of the costs of transporting solid biomass to analyze the logistic efficiency of biomass used in the power industry.
The authors carried out a thought process regarding the supply chain and developed research and calculations of the necessary part, which is supply logistics and transport.
The concept of the value chain helps to determine cost behavior [17,18]. Based on a detailed analysis, strategic and traceable directions of action can be determined. The value chain can be an important tool for a company in diagnosing and explaining how management aims at achieving a competitive advantage [19,20]. The interrelationship between elements of the value chain is an important explanation for the competitiveness nature—an advantage in large and complex organizations [21,22,23].
Based on the sustainable development principles, Figure 1 show the added value of the value chain can be recorded in the following form:
In Poland, according to a project called Roadmap for transformation towards a circular economy, adopted by the RM resolution in 2019, it is important to build local value chains in areas focused around local biorefineries that will be able to produce high-quality raw materials of biological nature in quantities consistent with the entrepreneurs’ expectations. In this context, the bioeconomy represents a great opportunity for the development of local communities in rural municipalities. Cooperation between the different actors in value chains can create new and financially attractive jobs.
As an integrated system that combines different biomass conversion processes and biomass processing equipment in one production plant, a biomass refinery requires an optimized selection of value chain transformations, depending on the raw material type, conversion technology, and obtained products [24]. The products of biorefinery processes can be final or intermediate—for using in other processes.
Biorefining gives a chance to extract the potential of biomass in Poland without competing with food production in any way.
Various biorefinery systems can be distinguished due to the types of raw materials, agricultural and from other sources, such as wood, food, or the tech industry [25,26,27]:
Refineries from whole crops—the substrate is the whole plant, e.g., oil refinery, in which oilseeds (rapeseed, sunflower, soybeans) are used;
‘green’ refineries with inedible ‘green’ parts of plants or whole energy crops (e.g., wet biomass, green grass, alfalfa, clover, unripe grain, unsuitable for agriculture, and food industry plants or their parts);
Lignocellulosic refineries, based on lignocellulosic biomass (e.g., straw, forestry waste, wood, paper);
Two-platform refineries (producing syngas and sugars in one product in the first technology platform with simultaneous fuel production in the second platform), based on renewable raw materials (waste from agriculture, forestry, food industry, biodegradable municipal waste).
In recent years, the Ligno Cellulosic Feedstock Biorefineries (LCFBR) has become particularly important. It uses fractionating lignocellulose-rich biomass sources into intermediate cellulose, hemicellulose, and lignin output streams, from which bio-based end products, chemicals, fuels, electricity, and heat can then be obtained. Biomass rich in lignocellulose is expected to become the most important source of biomass in the future, as it is widely available at a moderate cost, and its cultivation and use will compete less with food and feed crops [28,29]. Process of research is show on the Figure 2.
Focusing on agriculture, the concept of a biorefinery is based on the use of materials of agricultural origin in conversion processes, including:
Biomass from crop production.
Biodegradable waste products of plant or animal origin.
Dedicated plants grown for energy purposes.
Thus, there are many concepts of biorefinery systems, depending on the type of raw material, the employed technological processes, and the final products. However, each of them requires the analysis of individual processes, including pre-treatment and biomass conversion of produced products.
The assessment of the efficiency of biorefinery value chains can be carried out using various criteria, i.e., considering, for instance, the use of biomass, costs resulting from the value chain, the processes implementation time, the type of technologies, etc.
2. Analysis of the Processes That Make up Value Chains in an Agricultural Biorefinery
2.1. Supplying Raw Materials (Input)
In an agro-biorefinery, three basic processes forming the value chain can be distinguished (Figure 3):
In the value chain, this stage concerns the supply of biomass to refineries. The profitability of supply is related to the acquisition costs, the substrate quality and properties, the certainty of supply over several years, and the farms’ proximity and substrates production [30,31,32]. Myczko (2011) reports that substrates availability should not exceed a distance of 10–30 km from the biorefinery. The local use of biomass is beneficial due to protecting the natural environment, resulting from the reduction of CO2 emissions during transport, reducing delivery costs, using wastelands, and creating new jobs [33,34].
Due to the different forms of transported biomass, an appropriate means of transport should be used. Liquid biomass can be transported by traditional slurry tankers and barrel trucks; similarly, fixed biomass with the help of spreaders or trailers. Dry biomass can be supplied in the following forms: pressed (cubes. straw bales), loose (husks, sawdust, wood chips, bran), solid (willow rods, boards, sawmill cuts), or packed on europallets (Euro standard packaging 80 × 120 cm, 24 europallets on one truck) of different weights (briquettes, pellets) [35].
It is considered that the size and power of energy equipment in biomass refineries should depend on the availability of substrates as close as possible from the installation. In the case of a short distance from the installation, it is rational to obtain substrates with low efficiency, low bulk mass, and low dry matter content. On the other hand, the supply of substrates from longer distances is economically justified, provided that their high biogas productivity is high [36,37].
Currently, the supply of biomass is most often carried out by road. Vehicles with a small capacity (up to 8 t) can be used to transport loose biomass in light local transport, while large-size trailers are used to transport straw or hay. For long distances, low-tonnage (7–16 t) or high-tonnage (24–28 t payload) vehicles are used. Biomass transport can also be carried out by dump trucks, cars with self-unloading devices, or in containers [35].
The researcher Zarębski in his research, showed the importance of waste availability. Among the surveyed biogas plants in Poland, in 30 of them the average spatial availability of biogas from fertilizers, i.e., the potential accumulated per 17 km from the biogas plant, was above 200 TJ (terajoules). In 17 biogas plants, the annual biogas capacity was 2–4 million m3; in 10, it was 6–8 million m3; and in three, it was at the level of 8–10 million m3.
The method of settling biomass supplies depends on the contract concluded between the supplier and the recipient. Companies ordering biomass calculate the price per GJ of energy depending on the amount of energy contained in biomass, the weight of supply, calorific value, and humidity [38].
2.2. Refining (Pre-Treatment and Biomass Conversion)
Pre-treatment is an important process that affects the course of further activities related to the production of bioenergy. Carrying out this process results from the characteristic structure and properties of lignocellulose, contained in the biomass of plant origin. One of the polymers of lignocellulose is lignin, which in a special way reduces the efficiency of fermentation processes. For this reason, the use of pre-treatment is primarily aimed at the disintegration of lignin, subsequently reducing the crystallinity of cellulose, increasing the available, active surface for methane bacteria, and thus increasing the biogas efficiency of the substrate [39,40,41,42].
Many technological processes of biomass delignification (physical, chemical, physicochemical, biological) are known, but not all methods increase the efficiency of biogas. For this reason, a technical and economic analysis of pre-treatment is necessary, which is an important tool for studying the profitability and efficiency of the lignocellulosic biomass process [42,43,44]. Ekman, Wallberg, Joelsson, and Börjesson [45,46] report that the analysis makes it possible to benchmark different pre-treatment methods in terms of optimization by reducing energy consumption and increasing biomethanol efficiency.
Biomass processing technologies in agricultural biorefineries are generally reduced to producing heat and electricity, which can be used for own needs and sale. Until the present moment, conversion in Poland takes place only through combustion in boilers and furnaces and anaerobic fermentation. The others are the subject of laboratory research or used in experimental installations. The threats that inhibit developing and implementing biomass conversion installations are primarily economic reasons (high installation costs), the lack of analyses in the value chain of individual stages in biomass refineries, as well as low public awareness and lack of knowledge related to this type of equipment operation principle [47].
In the world, there are many other solutions, such as biomass gasification, pyrolysis, or electrochemical processing [48,49,50,51,52,53]. Each of these methods have different efficiency, which should be considered in assessing value chains.
Fuels can be obtained depending on the type of biorefinery and processed substrates. They constitute the added value of biomass conversion, which determines the profitability of production to the greatest extent [26].
The energy carriers produced from biomass are biogas, syngas, and liquid and solid fuels [54,55,56]. Biogas is produced in a reactor for the anaerobic digestion of biomass, from which energy can be produced using an internal combustion engine, gas turbine or fuel cell [57]. Moreover, biogas after purification and treatment can be used as fuel for the propulsion of vehicles or injected into the natural gas network [53].
2.3. Selling Conversion Products (Output)
The last element in the value chain is the sale of products obtained in biorefining processes. Depending on the installation and end-use, intermediate and by-products may be created. During methane fermentation, the produced biogas can be either the final product constituting a source of heat during combustion in boilers, or an intermediate product used to produce electricity using a generator coupled with an internal combustion engine. In turn, the by-products produced in the currently operating biomass refineries (single-module processing plants) are: digestate formed in the biogas installation during anaerobic fermentation, distillery decoction derived from alcoholic fermentation, and glycerin, which is a by-product of the transesterification reaction of vegetable oil (fresh or used cooking) with methanol.
In the biomass gasification, the produced hydrogen can be the final product for the propulsion of fuel cell vehicles, or an intermediate product intended in chemical reactions for producing end products, e.g., biodiesel in the Fischer–Tropsch reaction with carbon monoxide.
3. Sustainable Development Determinants in Biomass Processing
Sustainable development is a concept that in recent years has played a key role in the energy sector of many countries [58]. For distributed energy, responsible for biomass processing, this is an important challenge, as it fits directly in developing this segment. Therefore, considering the digital economy or Industry 4.0, the environment of the energy sector becomes more demanding and forces managers of these types of entities to constantly adjust their goals, i.e., increased and continuous measurement of various indicators aimed at improving the scope of efficiency of activities of entities involved in biomass processing. In the long term, it is an opportunity for developing investments in RES on the energy market, including heat producers or capacity market participants, who are currently facing profound forced changes, such as opening and merging markets, changes on the balancing market, or GreenDeal and FIT455 [59].
As one of the RES methods, biomass processing fits well into the concept of sustainable development, because it allows for the achievement of not only an economic or investment goal, but also has a strong positive impact on the natural environment.
That is why renewable energy sources slowly become increasingly profitable. Of course, they use various support systems [60]. Increasingly, sources of small power are being created in individual households. The energy consumer becomes a prosumer [61], and their activity begins to be competitive in relation to the classic (coal) energy generation market [62,63].
Therefore, the model of the energy market and the supply chain on the energy market change as well (Figure 4). Where, on the one hand, there are modern technologies, new sources and possibilities of keeping up with regulation, and, on the other hand, formal and legal solutions, such as trade agreements, market models covering the area of prosumer, storage, or demand and supply management.
4. Resource Assessment (Waste Valorization)
Waste valorization is the process of reusing, recycling, or composting waste materials and turning them into more useful products, including materials, chemicals, fuels, and other energy sources. Its essence is to increase the value of products beneficial to the Polish economy. However, valorization requires a high involvement of many scientific communities, technology providers, enterprises, and administration (mainly local), who share a common aspiration to protect the natural environment by introducing eco-innovation and obtaining high profitability in the production process. It also provides the right direction on the road to a circular economy and effective resource management [64,65].
The potential of biomass in Poland is very large. In 2020, more than 4.4 million tons of raw materials were used for producing agricultural biogas. The largest amount of used material was post-distillation decoction of approx. 921 thousand tons, slurry 760 thousand tons and residues from fruit and vegetables over 700 thousand tons [66].
5. Social Significance of Agro-Biorefinery Development
The sociological dimension of bioenergy development in the aspect of biorefineries is poorly understood. The essence of the creation and operation of biomass refineries in rural areas is primarily to ensure energy security for the local communities, use available resources, raise living standards of residents, create new jobs, and reduce pollution of the natural environment [25,67,68].
Job creation is particularly important. According to the Statistical Yearbook of Labor 2019 (data from 2020), in Poland in 2018, almost 970,000 people were registered as unemployed, of which 46.2% were rural residents [69,70,71,72,73,74]. However, it is satisfactory that the number of people employed in the renewable energy sector increases every year, which may have an impact on socio-economic issues, such as the emergence of specialized professions in rural areas and the promotion of entrepreneurship in local communities [75,76].
The report on the state of renewable energies in Europe [68] shows that the largest number of employees (directly and indirectly) employed in RES in 2018 was in Germany (263,700 people), of which 14,500 people were involved the production of biofuels and 30,800 people in biogas. There was also large employment found in Spain, France, Great Britain, and Italy. Poland occupied sixth position, where a total of people employed in RES was 80,800, of which 41,200 were in the production of biofuels and 2700 in biogas.
6. Environmental Assessment of Biomass Refineries
The environmental benefits of building a biorefining plant are considerable. They result from such activities as:
Waste management.
Use of targeted biomass.
Use of surplus biomass.
Reduction of greenhouse gas emissions.
Reduction of acidifying impurities.
Use of products resulting from biorefining.
The environmental impact of biomass refineries in terms of the value chain requires a broad view due to the multi-stage nature of the occurring processes. Currently, environmental impact assessment can be carried out using Life Cycle Assessment (LCA), based on the ISO 14040 and 14044 methodology [24,77,78,79,80]. The LCA is considered an objective and accurate method of environmental assessment. This is due to its multifaceted and comprehensiveness, and thus, the actual determination of the impact of various solutions on the environment and the choice of the least burdensome way. Assessment with the LCA consists of several stages [81,82,83]. At the beginning, the purpose and scope of the research is determined, and an inventory of potential environmental impacts—the inputs (raw materials, energy, water, etc.) to the system and the outputs (product, waste, emissions, etc.) from the product system is made. The product system consists of elements, such as extraction of raw materials, their processing and production of goods, transport and distribution of products, the phase of product use, and waste management. In subsequent stages, an assessment of the environmental impact of individual elements of the system, the impact in relation to the objectives of the research, and the interpretation of the results of the analysis of the set, are carried out. Based on LCA analyses, it is possible to determine the most environmentally beneficial production system for the product.
Various computer methods and tools can be used to assess the impact of a product’s lifecycle [78], for example:
CLM method—a method of intermediate points, in which the following indicators are used: depletion of abiotic resources (ADP), global warming potential (GWP), reduction of stratospheric ozone resources (ODP), soil toxicity potential, soil acidification (AP), eutrophication potential, and resource perceptibility potential (OTV).
Umberto program—allows for analyzing the energy and materials flow in companies, production installations, or facilities, calculating operating costs and lifecycle, choosing an ecologically optimal version of the product, etc.
SimaPro program—uses the eco-indicator method for assessing the damage caused to the environment by the adverse impact of a process or product.
In order to implement the principles of sustainable development, the LCA method should be supported by ‘lifecycle cost calculation (LCC)’, considering the conventional (LCC), environmental (eLCC), and social (sLCC) analyses. The LCC method provides the opportunity to analyze all costs occurring in the lifecycle of a product or plant, including, for instance, the costs of recycling or waste management [84,85,86,87]. The eLCC employs the analysis of internal costs, i.e., stages of production, use and management of products, and external costs, such as costs incurred by entities outside the production and consumer system. The sLCC, in turn, includes analyses of peoples’ behaviors, and decisions they make to influence human, cultural, and social capital [88,89,90,91]. Extremely important issues in air quality measurements include their reliability and quality. In accordance with the requirements of Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe (OJ L 152 of 11.06.2008, p. 1) and the Act on the Inspectorate of Environmental Protection, the National Reference and Calibration Laboratory (KLRiW), with its registered seat in Cracow, which was established in 2011 at the Chief Inspectorate of Environmental Protection, there is a responsibility to ensure the correct operation of the management system in air monitoring networks, approving measurement systems and coordinating quality assurance systems in Poland.
As part of its routine activities, KLRiW provided the air quality measurement networks with the possibilities of calibrating individual analyzers, e.g., following their malfunction, and checking cylinders holding gas mixtures, calibrators and mass flow controllers.
In order to confirm its competences and to expand its knowledge of the state-of-the-art monitoring systems, KLRiW participated in international comparative studies and meetings of the National Reference Laboratories associated in the AQUILA (AQUILA—the European Network of National Reference Laboratories operating as part of the Joint Research Centre of the European Commission) European network.
The CIEP took action to unify the measurement methods at the national scale, participated in the introduction of new measurement and analysis methods and disseminated knowledge of new standards on air quality measurements.
In order to strengthen the capacity of KLRiW, in the period from 2016 to 2018, as part of the Operational Programme Infrastructure and Environment, its calibration and adjustment infrastructure was modernized and expanded by purchases of a calibration bench, calibration lines for the purposes of adjustment and comparative testing of analyzers for surveys of gaseous pollutants in the air and specialized equipment, among others, for the weighing room.
The surveys were carried out in the period from 2003 to 2020. Table 1 provides basic descriptions of selected measured data.
The LCA study of biorefineries often is more complex than the LCA of a single product. Although many life cycle analyses of bioenergy systems have been carried out over the years, in the case of biorefineries, problems may be encountered regarding basic methodological choices, e.g., choice of functional unit, allocation, data, and system boundaries. A biorefinery system produces many high-value products with different functions, so it is not always possible to determine one main product [46]. Therefore, Ahlgren and other co-authors recommend performing a series of well-chosen sensitivity analyses and including a comprehensive interpretation phase of the results. Due to many methodological choices, all of them should be clarified when performing biorefinery LCA.
7. Value Chain Efficiency
7.1. Logistic Efficiency of Biomass
Transporting biomass to biorefineries is a very important element in the value chain. Logistic efficiency consists of the type of biomass, cargo volume, cargo weight, distance, and cost for each kilometer of travel.
Duda-Kękuś [35] made a calculation of the costs of transporting solid biomass to analyze the logistic efficiency of biomass used in the power industry. For the calculation, she used the following formula:
(1)
where:Staryfy(d. s)—the cost of transport according to the basic tariff for a given vehicle s and distance d.
ks/km—rate in PLN/km for vehicle s.
upowr—negotiated discount of the return fee.
Ks post—additional fee for parking after exceeding 4 h of driving (we assume that it will be added for each subsequent 250 km of the route).
Ks difficulties—additional fee for difficulties specific to a given route (driving through large cities, poor road conditions).
According to the author, the basic criterion for choosing a means of transport is the cost of transporting 1 GJ of energy contained in the transported biomass. It depends on the weight of the load or the payload of the vehicle or the volume of the cargo hold space, The cost calculation takes into account: the threshold distance (threshold 1), to which a flat fee (fee 1) applies, including loading and unloading costs, specific to a given type of vehicle, the limit distance (distance 2), to which the first rate (PLN/km) applies, such that reaching this distance, provides a certain cost of transport (cost 2). At a longer distance, the surcharge for the distance above threshold 2 is calculated at the second rate, proportionally to the distance. Duda-Kękuś [35] emphasizes that in order to guarantee the profitability of operating heavy vehicles, the net rate per 1 km, i.e., the tariff rate minus the cost of fuel (diesel fuel) should be higher for heavier vehicles with a lower ratio of the total weight of the vehicle to the maximum weight of the load.
Based on the analysis, an exemplary calculation of transport costs and a percentage increase depending on exceeding the threshold of 2, cargo volume, cargo weight, and the adopted rate per kilometer was made (Table 2). This analysis demonstrates that the adopted rate per km causes a significant increase in transport costs with the lowest cargo volume and cargo weight. In the case of heavier vehicles exceeding threshold 2, the share of transport costs is much lower. It can be concluded that for medium distances it is best to use low-tonnage vehicles, and for longer distances (over 100 km) high-tonnage. It would be reasonable to integrate the indicators of social, environmental and economic efficiency into a single indicator. Based on which it is possible to make a conclusion about the level of sustainable development determinants in biomass processing. In addition, based on the integral indicator, it would be possible to choose the optimal biorefinery technology.
7.2. Biomass Energy Efficiency
Energy efficiency is defined as the ratio of the amount of energy consumption (inputs) to the amount of obtained useful energy.
The analysis of using biomass energy efficiency can be performed in several stages. In the first stage, the amount of energy in the generated biomass is calculated, which is the difference between the biomass yield and the material and energy expenditure incurred for the production of biomass, i.e., fertilizers, cultivation, harvesting, storage, and transport to the places of production. The second stage considers the energy inputs related to processing biomass (including grinding, drying, mixing, transmission) and the expenditure incurred on conversion with possible energy losses. At this stage, the final amount of energy obtained from biomass is calculated by the difference between the final amount of energy obtained from biomass and the input. In turn, in the third stage, it is possible to calculate biomass processing energy efficiency (conversion) as the quotient of the amount of energy produced in biomass to the final amount of energy obtained from biomass [92].
Witaszek, Pilarska, and Pilarski [42] carried out a technical and economic analysis of pre-treatment, an important tool for testing the profitability and effectiveness of processes. Based on calculations of the amount of clean electricity from biomass and the consumption of electricity by the machine, they obtained an energy balance, stating the profitability of the treatment. The authors, based on available literature sources, demonstrated that in the extrusion process, a mixture consisting of rice straw silage (10% share), corn silage and triticale silage was obtained from 10.1 kWhel·Mg−1 cm pre-treatment energy. The energy gain after pre-treatment amounted to 40.2 kWhel·Mg−1 cm, while the energy balance of the process was at the level of 30.1 kWhel·Mg−1 cm. Increasing the share of rice straw to 30% resulted in an increase of 2.3 kWhel·Mg−1 cm of pre-treatment energy, while the energy gain after pre-treatment was only 13.4 kWhel·Mg−1 cm and the energy balance of 1.0 kWhel·Mg−1 cm. The authors found that the even higher content in the corn straw mixture resulted in a negative energy balance, resulting from higher energy expenditure on treatment.
7.3. Environmental Efficiency
The main tool used to assess environmental performance is the LCA, which makes it possible to assess the environmental hazards associated with the product system or performance. It allows for the identification and quantitative assessment of used materials and energy or waste introduced into the environment, as well as assessment of the impact of these materials, energy, and waste on the environment. Using the LCA also allows for the calculation of greenhouse gas emissions. Samson-Bręk and Smerkowska [27,93] performed calculations using the BIOGRACE calculator, which is a tool for estimating greenhouse gas emissions caused by the production and use of transport fuels, biofuels and bioliquids, as defined in Directive 2009/28/EC, Annex V, part C (Directive 2009). They compared the environmental impact of energy crops, which are raw materials for the production of second-generation bioethanol, with the cultivation of maize and rye as raw materials for producing first-generation bioethanol. Their studies have shown a much higher emissivity from the cultivation of corn and rye. This is due to the annual cultivation of the land, fertilization and harvesting, and thus, the increased number of field treatments performed with diesel-powered machines. For this reason, greenhouse gas emissions for annual crops are much higher than for perennial crops.
Budzinski, Cavalett, Nitzsche, and Strømman [80] conducted a study using a multi-purpose hybrid life cycle optimization model (hybrid life cycle assessment, LCA) to determine the optimal choice of new lignocellulosic biorefinery technologies in Germany. The model considered aspects, such as regionally diversified and sustainable availability of raw materials, identification of environmental impacts along global value chains, and identification of trade-offs between different sustainable development goals. They analyzed two different concepts, which show that ethylene production is more advantageous due to reducing the effects of climate change compared to ethanol. Furthermore, a biorefinery producing ethanol is more economical.
Currently, a biogas calculator is an increasingly common tool in biogas plants used to calculate the amount of biogas produced, electricity and heat, investment profitability, and environmental emission rates. Calculations allow one to approximately develop the initial characteristics of biogas installations, considering different raw material bases. Based on an online biogas calculator, researcher Smolarek analyzed technological and ecological indicators for 10,000 selected raw materials per 1 year (e.g., pig manure, cattle manure, animal poppy seed, flotation sludge from slaughterhouses, organic municipal waste, and others). Based on calculations, he obtained methane production at the level of over 7 thousand m3, biogas production of approx. 12.2 thousand m3, reduction of CO2 emissions 16.7 t per year, nitrogen oxides 27.4 t per year, sulfur oxides 42.6 t per year, and dust almost 2 t per year.
7.4. Economic Efficiency of Biorefineries
One of the most important elements of the value chain is a thorough and comprehensive economic analysis of the project. The preliminary analysis should consider operating costs and the investment costs estimation [42,94].
In Poland, the cost of building an agricultural biogas with an installed capacity of a 1 MW generator is currently PLN 14–15 million (approx. EUR 3.2 million), and for 0.5 MW about PLN 7 million (approx. EUR 1.5 million). The first biogas plant was constructed in 2005 with a capacity of 0.964 MW and cost PLN 2.5 million (approx. EUR 0.5 million), and in 2010 with a capacity of 0.625 MW, PLN 6.5 million (approx. EUR 1.4 million). In Germany, the investment costs per kW of installed capacity are 2000–3000 EUR/kW for larger systems and approx. 5000–7000 EUR/kW for smaller systems [95].
It is assumed that the operating costs associated with a biogas plant with a capacity of 0.5 MW may constitute 20–25% of the total expenditure [30,37,95]. Operating costs should include purchase of raw materials (price of raw materials, storage and transportation costs), maintenance and repair services, depreciation, taxes, loan repayment, insurance, salaries, other costs (e.g., security services, physico-chemical analyses) [96].
The share of individual operating costs depends on the investment’s technological options. Curkowski, Oniszk-Popławska, Mroczkowski, Zowsik, and Wiśniewski [96,97] gave an example of an operating cost structure (without depreciation) for a biogas plant with a capacity of 0.86 MWel, in which the substrate is corn silage and slurry. According to them, the largest share is the cost of purchasing and storing substrates (48%), while the cost of fertilizing digestate for fields/meadows is about 23%, and other costs (e.g., repairs, purchase of spare parts, taxes, insurance, employee remuneration)—29%.
In turn, revenues should include the sale of electricity and heat, digestate for fertilizer purposes, and origin certificates. The average annual electricity production of biogas with a capacity of 0.5 MW is about 4000 MWh. Annual revenue is almost PLN 2.9 million (approx. EUR 0.6 million), and in terms of 15 years in the guaranteed prices system it may amount to over PLN 43 million (approx. EUR 9.1 million) [37,95,96,97,98].
The largest turnover in the renewable energy sector was recorded in Germany—EUR 35 510 M, including the production of biofuels—EUR 1540 M and biogas—EUR 3640 M. Poland was ranked 11th. The total turnover was EUR 3800, 1480, and 130 M, respectively [68].
8. Conclusions
Bioenergy obtained from biomass is a very important part of renewable energy and fits into the concept of sustainable development, having an impact on the environment and the economy, including greater cost competitiveness. The sustainable use of biomass enhances the production of renewable energy and thus makes a significant contribution to the circular economy. Biorefineries play a special role in sustainable development, whose task is the multi-process conversion of biomass to produce energy, fuel, and valuable products.
Given the complexity of the systems included in the biorefinery, there is a need for a thorough analysis of all value chains, including biomass supply, biomass processing technologies, the obtained products and their sale.
According to the analysis of the value chain efficiency, it appears that:
The processing of biomass in agro-biorefineries achieves environmental, social, and economic objectives;
A rational supply chain makes it possible to exploit the potential of biomass and adapt transport to the type of biomass, cargo volume, cargo weight, distance, and travel costs. It also has a positive effect on reducing CO2 emissions during transport;
A favorable amount of energy produced from biomass can be obtained, as exemplified by the studies of Witaszek, Pilarska, and Pilarski [42] that included the pre-treatment analyses. By selecting the biomass share appropriately, a much higher profitability of the treatment used can be achieved;
Based on an environmental performance analysis, the optimal biorefinery technology can be selected, mainly being regionally diverse, taking into account the sustainable availability of raw materials, and the environmental impacts identification. The environmental impact of a biorefining investment can also be estimated, including the level of reductions in emissions of methane, carbon dioxide, nitrogen oxides, sulfur oxides, and dust;
Studies have shown that, for example, the annual revenue from biogas production in a biogas plant with a capacity of 0.5 MW and production of approx. 4000 MWh may amount to almost PLN 3 million (EUR 0.6 million).
All the determinants that make up the value chain, i.e., refining processes (biomass supply, conversion, and sales), waste valorization, the social and environmental aspect, and the profitability of investments are extremely important added values for sustainable development. In this way, they allow for implementing technology using renewable energy sources and the European strategy for the development of a low-carbon economy.
Conceptualization, A.B., G.K. and P.B.; methodology, A.B., G.K. and P.B.; software, A.B., G.K. and P.B.; validation, A.B., G.K. and P.B.; investigation, G.K., A.B. and P.B.; resources, G.K., A.B. and P.B.; data curation, G.K., A.B. and P.B.; writing—original draft preparation, A.B., G.K. and P.B.; writing—review and editing, G.K., A.B. and P.B.; visualization, G.K.; supervision, G.K.; All authors have read and agreed to the published version of the manuscript.
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Not applicable.
Not applicable.
The work was carried out as part of the statutory activity of the ITP-PIB, UEP, WSB University and Veolia.
The authors declare no conflict of interest.
| RM | Road map |
| FIT455 | Program EU “Fit for Fifthy Five” |
| GreenDeal | Program EU for Climate Saving |
| RES | Renewable Energy Sources |
| LCA | Life Cycle Assessment |
| ADP | Depletion of abiotic resources |
| GWP | Global warming potential |
| AP | Soil acidification |
| LCC | Lifecycle cost calculation |
| eLCC | Environmental lifecycle cost calculation |
| sLCC | Social lifecycle cost calculation |
| ODP | Stratospheric ozone resources |
| OTV | Resource perceptibility potential |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 3. A value chain in an agro-biorefinery with three key processes and selected factors influencing efficiency.
Descriptions and units of the measurements and pollutants.
| Index | Statistical Code/Field | Description |
|---|---|---|
| sAll | Averaging period | The basic data averaging period at a measurement site. The results of measurements are averaged in the form of annual series in accordance with that period. |
| All | Average | The average annual concentration. |
| SO2 | L 350 (S1) | The number of hours in a calendar year when the average 1 h concentration exceeded 350 µg/m3 (rounded to an integer). |
| SO2 | L 125 (S24) | The number of hours in a calendar year when the average 24-h concentration exceeded 125 µg/m3 (rounded to an integer). |
| NO2 | L 200 (S1) | The number of hours in a calendar year when the average 24-h concentration exceeded 200 µg/m3 (rounded to an integer). |
| NO2 | 19th max. (S1) | The 19th maximum value in an annual series of results—1 h averages, in [µg/m3]. |
| PM10 | L 50 (S24) | The number of hours in a calendar year when the average 24-h concentration exceeded 50 µg/m3 (rounded to an integer). |
| PM10 | Max. (S24) | The maximum average 24 h concentration in a year. |
Transportation costs and percentage increase in costs depending on exceeding threshold 2, cargo volume, cargo weight, and the adopted rate per kilometer.
| Distance above Threshold 2 | Cargo Volume 15 m3 |
Cargo Volume 15 m3 |
Cargo Volume 80 m3 |
Cargo Volume 80 m3 |
||||
|---|---|---|---|---|---|---|---|---|
| Rate over Threshold 2 (1.9 pln/km) | Increase % | Rate over Threshold 2 (0.68 pln/km) | Increase % | Rate over Threshold 2 (3.3 pln/km) | Increase % | Rate above Threshold 2 (1.13 pln/km) | Increase % | |
| 5 | 64.50 | 17 | 58.40 | 6 | 716.50 | 2 | 705.65 | 1 |
| 10 | 74.00 | 35 | 61.80 | 12 | 733.00 | 5 | 711.30 | 2 |
| 20 | 93.00 | 69 | 68.60 | 25 | 766.00 | 9 | 722.60 | 3 |
| 40 | 131.00 | 138 | 82.20 | 49 | 832.00 | 19 | 745.20 | 6 |
| 60 | 169.00 | 207 | 95.80 | 74 | 898.00 | 28 | 767.80 | 10 |
| 80 | 207.00 | 276 | 109.40 | 99 | 964.00 | 38 | 790.40 | 13 |
| 100 | 245.00 | 345 | 123.00 | 124 | 1030.00 | 47 | 813.00 | 16 |
| 120 | 283.00 | 415 | 136.60 | 148 | 1096.00 | 57 | 835.60 | 19 |
| 140 | 321.00 | 484 | 150.20 | 173 | 1162.00 | 66 | 858.20 | 23 |
| 160 | 359.00 | 553 | 163.80 | 198 | 1228.00 | 75 | 880.80 | 26 |
| 180 | 397.00 | 622 | 177.40 | 223 | 1294.00 | 85 | 903.40 | 29 |
| 200 | 435.00 | 691 | 191.00 | 247 | 1360.00 | 94 | 926.00 | 32 |
* Threshold 2–30 km. rate 55 PLN, ** Threshold 2–200 km. rate 700 PLN. Source: Own elaboration based on Duda-Kękuś [
References
1. Koszel, M.; Bartkowiak, P. Taksonomiczna miara zrównoważonego rozwoju obszarów metropolitalnych w Polsce. Zesz. Nauk. Uniw. Ekon. Krakowie; 2018; 3, pp. 83-100. [DOI: https://dx.doi.org/10.15678/ZNUEK.2018.0975.0306]
2. Bartkowiak, P.; Rutkowski, I.P.; Bartkowiak, A. A model approach to the maturity and the level of risk in the product innovation process. Stud. Pr. WNEiZ; 2019; 55, pp. 129-142. [DOI: https://dx.doi.org/10.18276/sip.2019.55-11]
3. Bartkowiak, A.; Bartkowiak, P. The Determinants of Sustainable Development of Agriculture Sector in Poland. Transform. Bus. Econ.; 2012; 11, pp. 298-314.
4. Kleinand, R.M.; Taylor, T.L.; Kingstone, A. Against a role for attentional disengagement in the gap effect: A friendly amendment to Tam and Stelmach (1993). Percept. Psychophys.; 1995; 57, pp. 573-577. [DOI: https://dx.doi.org/10.3758/BF03213082]
5. Kaszyński, P.; Komorowska, A.; Zamasz, K.; Kinelski, G.; Kamiński, J. Capacity Market and (the Lack of) New Investments: Evidence from Poland. Energies; 2021; 14, 7843. [DOI: https://dx.doi.org/10.3390/en14237843]
6. Jasiński, J.; Kozakiewicz, M.; Sołtysik, M. The Effectiveness of Energy Cooperatives Operating on the Capacity Market. Energies; 2021; 14, 3226. [DOI: https://dx.doi.org/10.3390/en14113226]
7. Bartkowiak, A.; Bartkowiak, P. Technical and Technological Progress in the Context of Sustainable Development of Agriculture in Poland. Procedia Eng.; 2017; 182, pp. 66-75. [DOI: https://dx.doi.org/10.1016/j.proeng.2017.03.118]
8. Wałowski, G. Development of Biogas and Biorafinery Systems in Polish Rural Communities. J. Water Land Dev.; 2021; 49, pp. 156-168.
9. Krzakiewicz, K.; Bartkowiak, P. Imitation as a Competitive Strategy. Proceedings of the International Scientific Conference Hradec Economic Days; Hradec Králové, Czech Republic, 25–26 March 2021; Volume 11.
10. Bartkowiak, A. Metody i instalacje do produkcji energii elektrycznej i ciepła w rafinerii biomasy. Produkcja Biogazu w Rafinerii Biomasy z Uwzględnieniem Aspektów Eksploatacji Biogazowi; Wydawnictwo ITP: Poznań, Poland, 2020.
11. Celiktas, M.S.; Alptekin, F.M. Biorefinery Concept: Current Status and Future Prospects. Int. Conf. Eng. Technol.; 2017; 7, 9.
12. Oleśkowicz-PoPiel, P.; Jankowska, E. Application of Fermentation Processes in Biorefineries. Przemysl Chem.; 2014; 93, pp. 351-354.
13. Bałdowski, M.; Będkowski-Kozioł, M.; Bruszewski, M.; Grzejdziak, Ł.; Hawranek, P.; Jankowski, Ł.; Karpiński, M.; Kinelski, G.; Kosiński, E.; Kowalczyk, J. Prawo Energetyczne. Ustawa o Odnawialnych Źródłach Energii. Ustawa o Rynku Mocy. Ustawa o Inwestycjach w Zakresie Elektrowni Wiatrowych: Komentarz; Wydawnictwo C.H.Beck Sp. z o.o.: Warsaw, Poland, 2020.
14. Soeters, J. Michael Porter. Management and Military Studies; Routledge: London, UK, 2020.
15. Weil, K.E. PORTER, Competitive advantage, creating and sustaining superior performance. Rev. Adm. Empres.; 1985; 25, pp. 82-84. [DOI: https://dx.doi.org/10.1590/S0034-75901985000200009]
16. Stonehouse, G.; Snowdon, B. Competitive Advantage Revisited: Michael Porter on Strategy and Competitiveness. J. Manag. Inq.; 2007; 16, pp. 256-273. [DOI: https://dx.doi.org/10.1177/1056492607306333]
17. Krzakiewicz, K.; Cyfert, S. Dynamic capabilities in strategic choice processes within organisations. Management; 2017; 21, pp. 7-19. [DOI: https://dx.doi.org/10.1515/manment-2015-0077]
18. Dyduch, W.; Chudziński, P.; Cyfert, S.; Zastempowski, M. Dynamic capabilities, value creation and value capture: Evidence from SMEs under COVID-19 lockdown in Poland. PLoS ONE; 2021; 16, e0252423. [DOI: https://dx.doi.org/10.1371/journal.pone.0252423]
19. Borowiecki, R.; Siuta-Tokarska, B. Challanges Facing Polish SMES in the Face of Globalization Processes. Folia Oeconomica Stetin.; 2011; 9, pp. 52-71. [DOI: https://dx.doi.org/10.2478/v10031-010-0004-8]
20. Rzepka, A.; Borowiecki, R.; Miskiewicz, R.; Olesinski, Z. Changes in Management During Transformation of Power Industry. Eur. Res. Stud. J.; 2021; XXIV, pp. 1149-1162. [DOI: https://dx.doi.org/10.35808/ersj/2179]
21. Gorynia, M. Competition and globalisation in economic sciences. Selected aspects. Econ. Bus. Rev.; 2019; 5, pp. 118-133. [DOI: https://dx.doi.org/10.18559/ebr.2019.3.7]
22. Mroczek-Dąbrowska, K.; Gorynia, M. Understanding transaction costs in the mesoeconomic perspective. Argum. Oeconomica; 2019; 1, pp. 337-360. [DOI: https://dx.doi.org/10.15611/aoe.2019.1.14]
23. McGee, J.; Sammut, T. Wiley Encyclopedia of Management: Strategic Management; Wiley: Hoboken, NJ, USA, 2015; Volume 12.
24. Parajuli, R.; Dalgaard, T.; Jørgensen, U.; Adamsen, A.P.S.; Knudsen, M.T.; Birkved, M.; Gylling, M.; Schjørring, J.K. Biorefining in the Prevailing Energy and Materials Crisis: A Review of Sustainable Pathways for Biorefinery Value Chains and Sustainability Assessment Methodologies. Renew. Sustain. Energy Rev.; 2015; 43, pp. 244-263. [DOI: https://dx.doi.org/10.1016/j.rser.2014.11.041]
25. Owczuk, M.; Rogulska, M.; Bogumil, D.; Biernat, K. Development Prospects of Biorefinery Technologies. Chemik; 2015; 69, 11.
26. Harasym, J. Biorafinerie—Rozwój Konceptu. Przegląd Zbożowo-Młynarski; 2015; 2, pp. 2-4.
27. Biernat, K.; Samson-Bręk, I.; Chłopek, Z.; Owczuk, M.; Matuszewska, A. Assessment of the Environmental Impact of Using Methane Fuels to Supply Internal Combustion Engines. Energies; 2021; 14, 3356. [DOI: https://dx.doi.org/10.3390/en14113356]
28. Dahmen, N.; Lewandowski, I.; Zibek, S.; Weidtmann, A. Integrated lignocellulosic value chains in a growing bioeconomy: Status quo and perspectives. GCB Bioenergy; 2018; 11, pp. 107-117. [DOI: https://dx.doi.org/10.1111/gcbb.12586]
29. Chandel, A.K.; Garlapati, V.K.; Singh, A.K.; Antunes, F.A.F.; Da Silva, S.S. The path forward for lignocellulose biorefineries: Bottlenecks, solutions, and perspective on commercialization. Bioresour. Technol.; 2018; 264, pp. 370-381. [DOI: https://dx.doi.org/10.1016/j.biortech.2018.06.004] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29960825]
30. Zarębski, P. Uwarunkowania przestrzenne lokalizacji biogazowni w Polsce. Roczniki; 2014; 16, [DOI: https://dx.doi.org/10.22004/ag.econ.204947]
31. Myczko, A. Budowa i Eksploatacja Biogazowni Rolniczych; ITP: Warsaw, Poland, 2011.
32. Mitterleitner, H.; Schilcher, A.; Demmel, M. Konzepte Zur Reduzierung Der Kosten Beim Transport von Nachwachsenden Rohstoffen Für Biogasanlagen; NawaRo-Transport LFL: Munchen, Germany, 2007.
33. Wyszomierski, R.; Bórawski, P.; Jankowski, K.; Zalewski, K. Przestrzenne zróżnicowanie produkcji biomasy w Polsce. Roczniki; 2017; 2017, [DOI: https://dx.doi.org/10.22004/ag.econ.293530]
34. Olkiewicz, M.; Olkiewicz, A.; Wolniak, R.; Wyszomirski, A. Effects of Pro-Ecological Investments on an Example of the Heating Industry—Case Study. Energies; 2021; 14, 5959. [DOI: https://dx.doi.org/10.3390/en14185959]
35. Duda-Kękuś, A. Transport biomasy w logistyce dostaw paliw dla elektrowni systemowych realizujących program zielonej energetyki. Logistyka; 2021; 2, pp. 107-118.
36. Kowalczyk-Juśko, A.; Maj, G.; Piekarski, W.; Ignaciuk, H. Gospodarka surowcowa wybranej biogazowni rolniczej. Logistyka; 2014; 6, pp. 156-161.
37. Kowalczyk, J.; Ochwat, R. Agroenergia—Biogazownie Rolnicze i Małe Elektrownie Wodne. Available online: https://ekodotacje.ios.edu.pl/agroenergia/ (accessed on 23 May 2022).
38. Sadurski, D. ENEA Zamowienia-Niepubliczne. Available online: https://www.enea.pl/bip/zamowienia/platforma-zakupowa (accessed on 23 May 2022).
39. Wilk, M.; Krzywonos, M. Distillery Wastewater Decolorization by Lactobacillus Plantarum MiLAB393. Arch. Environ. Prot.; 2020; 46, pp. 76-84. [DOI: https://dx.doi.org/10.24425/aep.2020.132528]
40. Wilk, M.; Krzywonos, M.; Seruga, P. Microbiological Colourants Removal from Sugar Beet Molasses Vinasse—The Effects of Process Parameters and Vinasse Dilution. Econ. Environ. Stud.; 2017; 17, pp. 335-345. [DOI: https://dx.doi.org/10.25167/ees.2017.42.11]
41. Seruga, P.; Krzywonos, M.; Wilk, M. Thermophilic Co-Digestion of the Organic Fraction of Municipal Solid Wastes—The Influence of Food Industry Wastes Addition on Biogas Production in Full-Scale Operation. Molecules; 2018; 23, 3146. [DOI: https://dx.doi.org/10.3390/molecules23123146] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30513604]
42. Witaszek, K.; Polarska, A.A.; Pilarski, K. Wybrane metody obróbki surowców roślinnych stosowanych do produkcji biogazu. Ekon. Środowisko Stud. Mater.; 2015; 2, pp. 130-144.
43. Wilk, M.; Krzywonos, M.; Borowiak, D.; Seruga, P. Decolourization of Sugar Beet Molasses Vinasse by Lactic Acid Bacteria—The Effect of Yeast Extract Dosage. Pol. J. Environ. Stud.; 2018; 28, pp. 385-392. [DOI: https://dx.doi.org/10.15244/pjoes/84861]
44. Seruga, P.; Krzywonos, M.; Wilk, M. Treatment of By-Products Generated from Anaerobic Digestion of Municipal Solid Waste. Waste Biomass-Valoriz.; 2019; 11, pp. 4933-4940. [DOI: https://dx.doi.org/10.1007/s12649-019-00831-6]
45. Ekman, A.; Wallbergb, O.; Joelsson, E.; Börjesson, P. Possibilities for sustainable biorefineries based on agricultural residues—A case study of potential straw-based ethanol production in Sweden. Appl. Energy; 2013; 102, pp. 299-308. [DOI: https://dx.doi.org/10.1016/j.apenergy.2012.07.016]
46. Ahlgren, S.; Björklund, A.; Ekman, A.; Karlsson, H.; Berlin, J.; Börjesson, P.; Ekvall, T.; Finnveden, G.; Janssen, M.; Strid, I. LCA of Biorefineries—Identification of Key Issues and Methodological Recommendations; The Swedish Knowledge Centre for Renewable Transportation Fuels: Göteborg, Sweden, 2013.
47. Mroziński, A. Inżynieria Rozdrabniania Biomasy. Wydawnictwo Współfinansowanie ze Środków Funduszy Norweskich Oraz Środków Krajowych; Grafpol: Bydgoszcz, Poland, 2016.
48. Gadsbøll, R.; Clausen, L.; Thomsen, T.P.; Ahrenfeldt, J.; Henriksen, U.B. Flexible TwoStage biomass gasifier designs for polygeneration operation. Energy; 2019; 166, pp. 939-950. [DOI: https://dx.doi.org/10.1016/j.energy.2018.10.144]
49. Hildreth, W.; Fierstein, J.; Calvert, A.T. McGee Till—oldest glacial deposit in the Sierra Nevada, California—And Quaternary evolution of the rangefront escarpment. Quat. Sci. Rev.; 2018; 198, pp. 242-265. [DOI: https://dx.doi.org/10.1016/j.quascirev.2018.08.008]
50. Archer, S.A.; Steinberger-Wilckens, R. Systematic analysis of biomass derived fuels for fuel cells. Int. J. Hydrog. Energy; 2018; 43, pp. 23178-23192. [DOI: https://dx.doi.org/10.1016/j.ijhydene.2018.10.161]
51. Li, S.; Song, X. Study on the preparation and production factors of a direct lignocellulose biomass fuel cell. J. Electroanal. Chem.; 2018; 810, pp. 55-61. [DOI: https://dx.doi.org/10.1016/j.jelechem.2017.12.085]
52. Firmansyah, H.; Tan, Y.; Yan, J. Power and methanol production from biomass combined with solar and wind energy: Analysis and comparison. Energy Procedia; 2018; 145, pp. 576-581. [DOI: https://dx.doi.org/10.1016/j.egypro.2018.04.084]
53. Pellegrini, L.A.; De Guido, G.; Langé, S. Biogas to liquefied biomethane via cryogenic upgrading technologies. Renew. Energy; 2018; 124, pp. 75-83. [DOI: https://dx.doi.org/10.1016/j.renene.2017.08.007]
54. Butlewski, K. Biofuel Production Level and the Development of Biofuel Technologies in the World. Proceedings of the 1st Sustainable Solutions for Growth (SSG) 2018 Conference; Wrocław, Poland, 17–18 September 2018.
55. Butlewski, K. Metody Uzdatniania biogazu z uwzględnieniem możliwości integracji termicznej z procesem fermentacji biomasy. Probl. Inżynierii Rolniczej; 2016; 92, pp. 67-83.
56. Butlewski, K. Current Status and Prospects for Biofuel Production in Poland. Proceedings of the European Biomass Conference and Exhibition; Copenhagen, Denmark, 14–18 May 2018; Volume 2018.
57. Scarlat, N.; Dallemand, J.-F.; Fahl, F. Biogas: Developments and perspectives in Europe. Renew. Energy; 2018; 129, pp. 457-472. [DOI: https://dx.doi.org/10.1016/j.renene.2018.03.006]
58. Bartkowiak, P.; Bartkowiak, A. Contextual nature of sustainable development in the activity of an enterprise, on the example of a municipal enterprise. J. Water Land Dev.; 2021; X–XII, pp. 279-284. [DOI: https://dx.doi.org/10.24425/jwld.2021.139936]
59. Mucha-Kuś, K.; Sołtysik, M.; Zamasz, K. Rola koopetycji w klastrach energii. Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; Gdańsk University of Technology: Gdańsk, Poland, 2017.
60. Mucha-Kuś, K.; Sołtysik, M.; Zamasz, K.; Szczepańska-Woszczyna, K. Coopetitive Nature of Energy Communities—The Energy Transition Context. Energies; 2021; 14, 931. [DOI: https://dx.doi.org/10.3390/en14040931]
61. Jasiński, J.; Kozakiewicz, M.; Sołtysik, M. Determinants of Energy Cooperatives’ Development in Rural Areas—Evidence from Poland. Energies; 2021; 14, 319. [DOI: https://dx.doi.org/10.3390/en14020319]
62. Knezevic, B.; Falat, M.; Mestrovic, I.S. Differences between X and Y Generation in Attitudes towards Online Book Purchasing. J. Logist. Inform. Serv. Sci.; 2020; 7, pp. 1-6. [DOI: https://dx.doi.org/10.33168/LISS.2020.0101]
63. Vlahovic, N.; Knezevic, B.; Batalic, P. Implementing Delivery Drones in Logistics Business Process: Case of Pharmaceutical Industry. Int. J. Econ. Manag. Eng.; 2016; 3, pp. 4026-4031.
64. Gontard, N.; Sonesson, U.; Birkved, M.; Majone, M.; Bolzonella, D.; Celli, A.; Angellier-Coussy, H.; Jang, G.-W.; Verniquet, A.; Broeze, J. et al. A research challenge vision regarding management of agricultural waste in a circular bio-based economy. Crit. Rev. Environ. Sci. Technol.; 2018; 48, pp. 614-654. [DOI: https://dx.doi.org/10.1080/10643389.2018.1471957]
65. Arancon, R.A.D.; Lin, C.S.K.; Chan, K.M.; Kwan, T.H.; Luque, R. Advances on waste valorization: New horizons for a more sustainable society. Energy Sci. Eng.; 2013; 1, pp. 53-71. [DOI: https://dx.doi.org/10.1002/ese3.9]
66. Krajowy Ośrodek Wsparcia Rolnictwa. Available online: https://www.kowr.gov.pl/ (accessed on 23 May 2022).
67. Rogulska, M.; Grzybek, A.; Szlachta, J.; Tys, J.; Krasuska, E.; Biernat, K.; Bajdor, K. Powiązanie rolnictwa i energetyki w kontekście realizacji celów gospodarki niskoemisyjnej w Polsce. Pol. J. Agron.; 2011; 7, pp. 92-101.
68. EurObserv’ER. Measures the Progress Made by Renewable Energies European Union; The state of renewable energies in Europe edition 2019 19th Report EurObserv’ER: Paris, France, 2019.
69. Szczepańska-Woszczyna, K. Strategy, Corporate Culture, Structure and Operational Processes as the Context for the Innovativeness of an Organization. Found. Manag.; 2018; 10, pp. 33-44. [DOI: https://dx.doi.org/10.2478/fman-2018-0004]
70. Szczepańska-Woszczyna, K. Innovation processes in the social space of the organization. Reg. Form. Dev. Stud.; 2021; 14, pp. 220-229. [DOI: https://dx.doi.org/10.15181/rfds.v14i3.878]
71. Hys, K.; Szczepanska-Woszczyna, K.; Czart, P. Analysis of Family Engagement in the Evaluation of Organisational Effectiveness in Family Businesses. Eur. Res. Stud. J.; 2020; XXIII, pp. 962-972. [DOI: https://dx.doi.org/10.35808/ersj/1909]
72. Zavadsky, J.; Zavadska, Z.; Szczepanska-Woszczyna, K. Quantification of the Process Improvement Exigency Related to Industry 4.0. Eur. Res. Stud. J.; 2021; XXIV, pp. 65-86. [DOI: https://dx.doi.org/10.35808/ersj/2583]
73. Szczepańska-Woszczyna, K.; Dacko-Pikiewicz, Z. Managerial Competencies and Innovations in the Company—The Case Of Enterprises in Poland. Business Manag. Educ.; 2014; 12, pp. 266-282. [DOI: https://dx.doi.org/10.3846/bme.2014.240]
74. Kurowska-Pysz, J.; Szczepańska-Woszczyna, K. The Analysis of the Determinants of Sustainable Cross-Border Cooperation and Recommendations on Its Harmonization. Sustainability; 2017; 9, 2226. [DOI: https://dx.doi.org/10.3390/su9122226]
75. Petkovic, G.; Knezevic, B.; Pindzo, R.; Goran, P.; Blaženka, K.; Renata, P. Social initiatives in trade and tourism: The cases of Serbia and Croatia. Èkon. Preduzeca; 2017; 65, pp. 229-243. [DOI: https://dx.doi.org/10.5937/ekopre1702229P]
76. Sosa Meštrović, I.; Knežević, B.; Falat, M. What Influences Decision Making in Online Purchasing of Books in Generation X and Y?. SSRN Electron. J.; 2019; 5, pp. 367-375. [DOI: https://dx.doi.org/10.2139/ssrn.3491744]
77. Lindorfer, J.; Lettner, M.; Hesser, F.; Fazeni, K.; Rosenfeld, D.; Annevelink, B.; Mandl, M. Technical, Economic and Environmental Assessment of Biorefinery Concepts; IEA Bioenergy: Paris, France, 2019.
78. Lesiuk, A.; Oleszczuk, P.; Kuśmierz, M. Zastosowanie techniki LCA w ekologicznej ocenie produktów, technologii i gospodarce odpadami. Ryczkowski, Adsorbenty i katalizatory, Wybrane technologie a środowisko; Ryczkowski, J. Uniwersytet Rzeszowski: Rzeszów, Poland, 2012; Volume 1, pp. 453-466.
79. Wrana, K.; Szulc, T.; Budziński, M.; Raczek, M. Non-spatial factors of development of Functional Urban Areas—Case study of selected FUAs of Silesian Voivodeship. Stud. Reg.; 2017; 47, pp. 51-69. [DOI: https://dx.doi.org/10.12657/studreg-47-04]
80. Budzinski, M.; Cavalett, O.; Nitzsche, R.; Strømman, A.H. Assessment of lignocellulosic biorefineries in Germany using a hybrid LCA multi-objective optimization model. J. Ind. Ecol.; 2019; 23, pp. 1172-1185. [DOI: https://dx.doi.org/10.1111/jiec.12857]
81. Wróblewski, L. Where there is a will, there is a way: Some remarks on institutional distance in the Polish-German borderland. Pogran. Pol. Borderl. Stud.; 2021; 9, pp. 39-62. [DOI: https://dx.doi.org/10.25167/brs3408]
82. Wróblewski, L. The Use of the Taxonomic Measure in Assessing the Intensity of Border Regions Interaction. Pogran. Pol. Borderl. Stud.; 2021; 9, pp. 91-104. [DOI: https://dx.doi.org/10.25167/brs3854]
83. Wróblewski, L.; Grzesiak, M. The Impact of Social Media on the Brand Capital of Famous People. Sustainability; 2020; 12, 6414. [DOI: https://dx.doi.org/10.3390/su12166414]
84. Lisiński, M.; Šaruckij, M. Principles of the Application of Strategic Planning Methods. J. Bus. Econ. Manag.; 2006; 7, pp. 37-43. [DOI: https://dx.doi.org/10.3846/16111699.2006.9636122]
85. Lisiński, M.; Sroka, W.; Brzeziński, P.; Jabłoński, A.; Stuglik, J. Application of Modern Management Concepts by Polish Companies—Analysis of Research Results. Organizacija; 2012; 45, pp. 41-49. [DOI: https://dx.doi.org/10.2478/v10051-012-0005-5]
86. Lis, M. Improving the Availability of University Offerings for the Business Sector Based on Blended Learning Tools. Cult. Manag. Sci. Educ.; 2021; 5, pp. 93-103. [DOI: https://dx.doi.org/10.30819/cmse.5-1.07]
87. Lis, M. Circle Patterns and Critical Ising Models. Commun. Math. Phys.; 2019; 370, pp. 507-530. [DOI: https://dx.doi.org/10.1007/s00220-019-03541-1]
88. Sulewski, P.; Wąs, A. Index-Based Insurance of Gross Margin in Agriculture—Key Challenges. Probl. Agric. Econ.; 2018; 355, pp. 3-27. [DOI: https://dx.doi.org/10.30858/zer/92059]
89. Sulewski, P.; Majewski, E.; Wąs, A. The Importance of Agriculture in the Renewable Energy Production in Poland and the EU. Probl. Agric. Econ.; 2017; 350, pp. 50-74. [DOI: https://dx.doi.org/10.30858/zer/82999]
90. Wąs, A.; Sulewski, P.; Majewski, E. Methodical and Practical Aspects of The Parity Income in the Polish Agriculture. Probl. Agric. Econ.; 2019; 2, pp. 3-27. [DOI: https://dx.doi.org/10.30858/zer/109926]
91. Sulewski, P.; Wąs, A.; Kobus, P.; Pogodzińska, K.; Szymańska, M.; Sosulski, T. Farmers’ Attitudes towards Risk—An Empirical Study from Poland. Agronomy; 2020; 10, 1555. [DOI: https://dx.doi.org/10.3390/agronomy10101555]
92. Kołodziej, B.; Matyka, M. Odnawialne Źródła Energii. Rolnicze Surowce Energetyczne; 1st ed. Kołodziej, B.; Matyka, M. PWRiL: Poznań, Poland, 2012.
93. Samson-Bręk, I.; Smerkowska, B.; Filip, A. Environmental Aspects in the Life Cycle of Liquid Biofuels with Biocomponents, Taking into Account the Storage Process. Storage Stability of Fuels; IntechOpen: London, UK, 2015.
94. Smolarek, T. Kalkulator biogazowy jako użyteczne narzędzie do obliczeń wskaźników pracy biogazowi. Eliksir; 2016; 1, pp. 52-55.
95. Koszty Biogazowni. 2021; Available online: https://www.odnawialne-firmy.pl/wiadomosci/pokaz/108,koszty-biogazowni (accessed on 23 May 2022).
96. Curkowski, A.; Mroczkowski, P.; Oniszk-Popławska, A.; Wiśniewski, G. Biogaz Rolniczy—Produkcja i Wykorzystanie; Mazowiecka Agencja Energetyczna Sp. z o.o.: Warszawa, Poland, 2009.
97. Curkowski, A.; Oniszk-Popławska, A.; Mroczkowski, P.; Zowsik, M.; Wiśniewski, G. Przewodnik Dla Inwestorów Zainteresowanych Budową Biogazowni Rolniczych; 1st ed. Instytut Energetyki Odnawialnej: Warszawa, Poland, 2011.
98. Mikos, P. Tygidnik Rolniczy. 2020; Available online: https://www.Tygodnik-Rolniczy.Pl/Articles/Pieniadze-i-Prawo/Jakie-Gospodarstwa-Moga-Postawic-Biogazownie-i-Ile-Kosztuje/ (accessed on 23 May 2022).
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1 Institute of Technology and Life Sciences-National Research Institute in Falentach, Hrabska Road 3, 05-090 Raszyn, Poland
2 Department of Investment and Real Estate, Institute of Management, Poznań University of Economics and Business, al. Niepodległości 10, 61-875 Poznań, Poland
3 Department of Management, University WSB, Cieplaka 1c, 41-300 Dąbrowa Górnicza, Poland; Veolia Energy Contracting Poland Sp z o.o., Puławska 2, 02-566 Warszawa, Poland