Reasons Behind Differences in the Use of the “Carbon Farming and Nutrient Management” Eco-Scheme Across the Polish Territory

Abstract

Today, there is an ongoing discourse on the notion of carbon farming on an international scale. The underlying factors contributing to this phenomenon are numerous. Firstly, the degradation of intensively farmed soils is increasing, and secondly, there is a clear need to restore their biodiversity. A multitude of pollutants stemming from agricultural production have incited the implementation of targeted measures, notably by the European Commission. Consequently, the adoption of the European Green Deal in Poland has prompted the agricultural sector to implement a series of modifications to its practices, with the objective of enhancing soil cultivation and animal husbandry methods. In response to these changes, the introduction of carbon farming practices is being proposed. These practices, which are to be implemented in Polish agriculture with the support of EU subsidies, are intended to mitigate the effects of climate change. This prompts further inquiry into the potential evolution of carbon farming practices and the extent of farmer interest in them. According to the available data, in Poland, 56% of the total agricultural area was covered by payments under the carbon farming eco-scheme. However, support was accessed by barely 31% of farms with an area of more than 1 ha. In turn, from a regional perspective, data analysis reveals significant regional differences in the use of support. Therefore, the purpose of this paper is to explore the structural, environmental, and production reasons behind differences in the use of the “Carbon farming and nutrient management“ eco-scheme across the Polish territory. The headline result is that participation is strongly associated with farm structure, moderately with production performance, and only weakly with environmental status.

1. Introduction

At present, the global food system is responsible for approximately 25% of annual anthropogenic greenhouse gas (GHG) emissions [1]. If this approach is not altered, the environmental consequences of excessive reliance on artificial fertilizers, synthetic pesticides, fossil fuels, and food waste may exceed the planet’s natural regenerative capacity [2]. Consequently, it poses a substantial challenge to produce sufficient food for a growing and increasingly affluent global population within the planet’s capacity while preserving the natural environment and maintaining biodiversity and animal welfare [1,3,4]. A growing emphasis on appropriate food security policies, including food production, is also evident. For instance, the Paris Climate Agreement [5] and the Common Agricultural Policy [6] underscore the role and importance of sustainable agriculture in the context of caring for the natural environment and soil. It is essential to identify suitable solutions [7,8]. Conversely, other researchers posit that a narrow emphasis on production is insufficient to optimize the global food system. Instead, they contend that a critical aspect of enhancing the system’s efficacy is a recalibration of consumption patterns [9,10]. Production- and consumption-oriented approaches must be balanced with the natural environment [1,11]. Consequently, there has recently been a discourse on the use of practices within carbon farming, which is regarded not as an approach involving rigid, specific agricultural rules and practices, but rather as a focus on the goals to be achieved [12]. The concept of regenerative (carbon) agriculture is characterized by its extensive scope, which permits the implementation of diverse practices. For instance, it does not preclude the utilization of mineral fertilizers, intensive farming methodologies, or pesticides [12]. Instead, the objective is to curtail their utilization through a rational and exacting application of these measures [13]. A substantial body of scientific research has demonstrated that carbon farming practices have a considerable impact on climate change mitigation and contribute to the promotion of biodiversity by restoring the carbon, water, and nutrient cycles [14,15,16,17,18,19,20,21]. The transition to such practices would reduce agricultural greenhouse gas emissions by nearly 20% globally by 2030 and by up to 40% in Europe by 2050, in line with the targets set out in the European Green Deal [22]. To date, empirical investigations addressing the underlying determinants of the spatial heterogeneity in the uptake of the “Carbon farming and nutrient management” eco-scheme have not yet been undertaken in Poland. This study is therefore positioned to partially bridge this research gap while simultaneously serving as a point of departure for more comprehensive examinations of eco-schemes currently being introduced both in Poland and within the broader framework of the European Union. Accordingly, the following research hypothesis has been proposed: the spatial differentiation in the utilization of funds is primarily determined by the agrarian structure of farms.

1.1. Regenerative Agriculture: Essence and Significance

A report by the European Academies Science Advisory Council (EASAC) published in 2022 demonstrates that contemporary agriculture exerts an influence on soil condition. The report clearly indicates that the transition to regenerative agriculture is an adequate and promising strategy for enhancing soil structure. Moreover, a review of the extant literature on the subject reveals a paucity of clearly defined scientific definitions of the term “regenerative agriculture” [19,20]. A variety of authors have proposed distinct definitions for this type of agriculture, each one highlighting a particular aspect of its nature and characteristics. Many researchers have emphasized the challenges associated with distinguishing between regenerative agriculture, organic agriculture, and other “alternative” agricultural systems (e.g., ref. [23]). Additionally, there are discernible disparities in agricultural concepts and practices associated with regenerative agriculture [12]. The concept of regenerative agriculture, also referred to as carbon farming, was initiated as early as the 1970s. However, since the 1980s, a range of definitions have been put forth, encompassing both broader and narrower interpretations. The term was initially defined in 1983 by Rodale, who delineated the concept of regenerative agriculture as “a practice that, through the augmentation of productivity, enhances the biological productivity of the land and soil. It exhibits a high degree of built-in economic and biological stability. It provides a productive contribution from an increasing number of people while transitioning to minimal dependence on non-renewable resources” [24]. Harwood [25] proposed an alternative definition, asserting that the philosophy of regenerative agriculture emphasizes several elements, namely “the interconnections between all components of the agricultural system, including the farmer and his family; the importance of biological balance in the system and the need to maximize desirable biological relationships in the system and to minimize the use of materials and practices that disrupt these relationships”. In turn, Giller et al. [15] have indicated that regenerative agriculture is characterized by a number of factors, including a practice which “should enhance rather than deteriorate soil productivity by increasing the depth, fertility, and physical properties of the topsoil”.

In turn, the definition of regenerative agriculture according to the global framework for regenerative agriculture of the SAI Platform “Regenerating Together” states that “regenerative agriculture is an outcome-based farming approach that protects and improves soil health, biodiversity, climate, and water resources while supporting farmer livelihoods” [26]. Newton et al. [14] emphasized in their review of definitions that “regenerative agriculture constitutes an alternative means of food production which—according to its proponents—may be characterized by lower, or even net positive, environmental and/or social impacts (…). Given the wide diversity of ways in which the term ‘regenerative agriculture’ has been defined and described, they suggest that users of the term should articulate a definition precisely, tailored to the specific purpose and context”.

Similarly, Lal [27] defines regenerative agriculture as “an outcome-based approach to farming that protects and improves soil health, biodiversity, climate, and water resources, while simultaneously supporting farmers’ livelihoods”. Stevenson et al. [28], however, highlight in their research that while interest in regenerative agriculture is growing, concrete actions in the field remain relatively limited. Although certain regenerative practices have been adopted in specific countries, broader implementation of regenerative agriculture on a large scale has not yet been effectively realized [29].

Towards the conclusion of 2021, the European Commission published a communication on the restoration of the sustainable carbon cycle within nature [30]. This initiative marks a pivotal step in the European Union’s pursuit of carbon farming, a strategy aimed at achieving climate neutrality by 2050. The European Commission has proposed the establishment of a novel business model that will incentivize land management methodologies that enhance carbon sequestration (retention) in the soil. The most common carbon farming practices include the following: proper crop rotation, plowing straw into the soil after harvest, extensive grazing of animals on permanent grasslands, no-till farming, the use of cover crops and catch crops, the application of organic fertilizers, and increasing the proportion of legumes in crop rotation [31]. Consequently, many farmers are reverting to traditional practices by reintroducing grazing on wasteland and fields after the season. This practice enables the soil to undergo a period of rest following the harvest, while concurrently serving as a natural source of animal fertilizers, including manure, compost, and slurry. Also, the disruption of monoculture systems and the integration of intercrops have been demonstrated to impede the process of soil weathering [32]. An additional element to be considered is no-till farming, which has been demonstrated to loosen the soil more effectively without altering its structural integrity. This approach serves to impede water erosion, evaporation, and excessive weed proliferation in agricultural fields. Furthermore, carbon farming has been demonstrated to be advantageous due to its capacity to enhance soil fertility and curtail CO₂ emissions [33].

In summary, regenerative agriculture can be defined as a holistic land management system that aims to restore and improve the condition of agricultural ecosystems. This approach to agricultural production is predicated on farming practices that regenerate the soil, improve its structure and fertility, increase its carbon storage capacity, and support biodiversity.

1.2. Regenerative Agriculture in Poland: Opportunities for Development

The notion of carbon farming remains underdeveloped in Poland, which can be attributed to a number of factors. As previously stated, a formal definition or standard for “regenerative agriculture” remains elusive. Secondly, there is a lack of awareness among farmers regarding the utilization of practices within eco-schemes. Thirdly, there is a paucity of knowledge transfer on this subject. It is important to acknowledge that the eco-scheme functions as a political instrument for the implementation of this system, rather than serving as the system itself. In light of the 2023–2027 financial perspective, during which the Strategic Plan for the CAP is being executed, the integration of carbon farming principles has the potential to offer numerous advantages to producers [31,34,35].

A study conducted in 2022 in Poland [36] sought to address this knowledge gap by surveying 595 farmers. It revealed that 38% of respondents were unaware of the concept of regenerative (carbon) agriculture, while nearly 35% correctly associated it with environmental protection, soil improvement, and greenhouse gas reduction. A subset of farmers engage in agri-technical practices and other treatments consistent with the principles of regenerative agriculture, often unbeknownst to them. This includes a reduction in the use of mineral fertilizers and a reversion to the natural symbiosis of plant and animal production.

Currently, it is of fundamental importance to have appropriate economic incentives that will stimulate and enable farmers to transition to carbon farming. This is in spite of the fact that the individual practices within the eco-scheme under this study are aimed at improving soil quality, which represents the farmer’s basic “toolkit”. Hence, farmers should be reasonably expected to rely on these practices without the need for additional financial incentives within the framework of the CAP. However, enhancing soil quality can yield economic benefits in the future, whereas economic operators prioritize immediate financial gain. Consequently, public support appears to be justified, at least for a certain period of time. The new CAP under the 2023–2027 Strategic Plan is predicated on the notion that there will be a strong focus on interventions aimed at building green agricultural architecture, which will serve as a catalyst for the transformation, and that the available tools, especially eco-schemes, will facilitate the achievement of the objectives of regenerative agriculture.

1.3. Opportunities for Supporting Carbon Farming in Poland Under the CAP Strategic Plan for 2023–2027

Since 2023, novel regulations have been implemented in Poland, effecting modifications to the categories and principles governing the provision of support under the Common Agricultural Policy (CAP). A notable new feature is the incorporation of eco-schemes, which represent an environmental component of direct payments. While the eco-schemes are mandatory for Member States, they remain voluntary for farmers [37,38]. Eco-schemes are defined as annual, paid practices, adapted to national conditions and needs, but assessed by the European Commission in terms of the environmental and climate objectives of the new CAP, i.e., the protection of soil, water, climate, animal welfare, and biodiversity in agricultural production. In Poland, eco-schemes have been designed to promote practices that generate agricultural income by enhancing soil fertility and ensuring optimal fertilization. As previously mentioned, the fundamental concept underlying eco-schemes is that they represent supplementary financial contributions to farmers, intended to incentivize the adoption of practices that promote environmental protection, climate mitigation, and animal welfare beyond the scope of basic requirements laid down in the mandatory compliance system (SMR, GAEC). In Poland, the Strategic Plan for the 2023–2027 Common Agricultural Policy has introduced a total of five area-based eco-schemes (Figure 1) and an animal welfare eco-scheme. The financial resources allocated to eco-schemes in Poland amount to a minimum of 25% of the aggregate sum of direct payments per year (averaging approximately EUR 884 million in 2023–2026) [39,40].

In Poland, “Carbon farming and nutrient management” is one of eight eco-schemes available to farmers. Financial incentives are allocated for the implementation of at least one of the following practices, which are designed to enhance carbon sequestration in the soil and improve nutrient management.

Table 1. Practices promoting environmental and climate protection covered by the implementation of the “Carbon farming and nutrient management” eco-scheme in Poland.

Practices Used	EU (EAGF) Funds [EUR Million]	EUR/ha Rate
Carbon farming and nutrient management (minimum rate 70%, maximum rate 130% of the base rate)
Extensive use of permanent grasslands with livestock grazing	274.90	112.35
Winter catch crops or undersown crops	170.30	112.35
Development and compliance with a fertilization plan 1. Basic variant 2. Variant with liming	217.92 585.74	22.47 67.41
Diverse crop structure	354.33	67.41
Incorporation of manure into arable land within 12 h of application	239.52	44.94
Application of natural liquid fertilizers using methods other than splashing	13.18	67.41
Simplified tillage systems	345.43	89.88
Incorporation of straw into the soil	575.94	44.94

Source: own compilation based on [31].

presents detailed information on the practices covered by the carbon farming eco-scheme in Poland.

2. Materials and Methods

This paper underscores the significance of the correlation between the utilization of financial resources under the “Carbon farming and nutrient management” eco-scheme and the prerequisites for agricultural advancement in relation to the agricultural framework, environmental circumstances, and Polish agricultural production. It is hypothesized that voluntary participation in this CAP instrument is attributable to specific characteristics of the farm, including its size and production potential, production line, and the state of the environment, both on the farm itself and in its immediate surroundings. Farmers’ decisions to apply may be influenced not only by the structural, environmental, and production conditions of agriculture, but also by additional factors such as the lack of awareness, knowledge transfer among farmers, access to advisory services, or individual motivation. Although these factors have not been examined in this paper, they could be further explored through the lens of behavioral economics. Certainly, the decisions are made on an individual basis and are the result of personal cost–benefit calculations. However, the adoption of a spatial perspective in this study stems from the fact that the saturation of specific characteristics relating to the agricultural structure, production performance, and the state of the environment varies across the country, which may translate into different intensities of use of the eco-scheme under study.

The following indicators were used to describe the level of use of direct payments under the “Carbon farming and nutrient management” eco-scheme:

• Share of agricultural land covered by this support system (%);
• Share of farms covered by this support system (%).

The analysis was conducted at the voivodeship level. The study relied on data concerning direct support schemes in the 2023 campaign. The study was based on data on direct support programs in the 2023 campaign and agricultural data from the 2020 agricultural census. This is currently the most up-to-date statistical data.

The conditions for agricultural development in Poland were characterized by a multifaceted analysis, encompassing the agrarian structure, environmental conditions, and the production capacity of agricultural holdings. In the context of the agricultural structure, the study incorporated a single variable, specifically the proportion of farms exceeding 10 hectares of agricultural land within the total farm area. This approach is substantiated by the findings of Sadowski et al. [41], who reported a high degree of intercorrelation among variables depicting agricultural structure. The indicator characterizing the agricultural structure, disaggregated by voivodeship in Poland, is presented in

Table 2. Indicators of the agricultural structure in Poland in 2020, broken down by voivodeship.

Voivodeship	Share of Farms Larger Than 10 ha in the Total Farm Area (%)
Dolnośląskie	80.7
Kujawsko–Pomorskie	83.5
Lubelskie	58.2
Lubuskie	86.5
Łódzkie	56.8
Małopolskie	29.4
Mazowieckie	62.9
Opolskie	83.0
Podkarpackie	38.5
Podlaskie	79.2
Pomorskie	83.4
Śląskie	59.5
Świętokrzyskie	42.6
Warmińsko–Mazurskie	90.0
Wielkopolskie	78.8
Zachodniopomorskie	90.9

Source: own compilation based on [40].

.

Conversely, the environmental condition and production performance are represented by more than one variable. Consequently, a decision was made to define two synthetic characteristics relating to these elements.

The TOPSIS method was employed to ascertain the synthetic characteristic for the two aforementioned aspects of agricultural development. The process was divided into the following stages [42]:

• Selection of the simple characteristics for the individual phenomena;
• Normalization of the values of simple characteristics;
• Determination of the values of synthetic characteristics.

The selection of simple characteristics was made based on the following statistical and relevant criteria [42]:

• Availability of statistical data at the voivodeship level;
• High significance;
• Low correlation with other characteristics within the same phenomenon (based on the analysis of diagonal elements of the inverse of the R correlation matrix).

The presentation of each of the examined elements (agrarian structure, environmental condition, production performance) was facilitated by the indicators delineated in

Table 3. Indicators of conditions for agricultural development in Poland.

Characteristics	Indicators	Source
Agrarian structure	Share of farms larger than 10 ha in the total farm area (%)	Local Data Bank of the Central Statistical Office
Environmental condition	Share of forests and forest land in the total area of the voivodeship (%)	Local Data Bank of the Central Statistical Office
	Share of permanent pasture in agricultural land (%)
	Share of organic farms in the total farm area (%)	General Inspectorate of Agri-Food Trade Quality
	Share of organic farms in the total population of farms (%)
	Quality index of agricultural production space (score)	Institute of Soil Science and Plant Cultivation of the National Research Institute
Production performance	Share of fallow land in the total agricultural area (%)	Local Data Bank of the Central Statistical Office
	Livestock units (LU) per ha of agricultural land
	NPK consumption per ha of agricultural land (kg)

Source: own compilation.

. The detailed data for environmental conditions and production performance, disaggregated by voivodeship in Poland, are presented in

Table 4. Indicators of environmental condition in Poland in 2020, broken down by voivodeship.

Voivodeship	Share of Forests and Forest Land in the Total Area of the Voivodeship (%)	Share of Permanent Pasture in Agricultural Land (%)	Share of Organic Farms in the Total Farm Area (%)	Share of Organic Farms in the Total Population of Farms (%)	Quality Index of Agricultural Production Space (Score)
Dolnośląskie	30.7	16.4	4.0	1.5	74.9
Lujawsko–Pomorskie	24.1	9.3	0.7	0.8	71.0
Lubelskie	23.7	14.7	2.1	1.3	74.1
Lubuskie	50.8	27.1	11.1	4.9	62.3
Łódzkie	21.8	14.3	1.0	0.5	61.9
Małopolskie	28.9	40.9	1.6	0.6	69.3
Mazowieckie	23.8	25.8	2.2	1.3	59.9
Opolskie	27.4	9.7	0.8	0.3	81.6
Podkarpackie	38.8	36.5	2.3	0.9	70.4
Podlaskie	31.4	36.8	4.8	3.8	55.0
Pomorskie	37.4	18.9	3.2	1.6	66.2
Śląskie	32.9	23.1	1.0	0.4	64.2
Świętokrzyskie	28.9	21.1	1.7	0.8	69.3
Warmińsko–Mazurskie	32.6	34.3	10.9	7.6	66.0
Wielkopolskie	26.4	13.8	1.9	0.8	64.8
Zachodniopomorskie	36.8	22.1	13.8	7.9	67.5

Source: own compilation based on [40].

and

Table 5. Indicators of production performance in Polish agriculture in 2020, broken down by voivodeship.

Voivodeship	Share of Fallow Land in the Total Agricultural Area (%)	Livestock Units (LU) Per ha of Agricultural Land	NPK Consumption Per ha of Agricultural Land (kg)
Dolnośląskie	0.9	0.3	148.6
Kujawsko–Pomorskie	0.4	0.8	170.4
Lubelskie	1.1	0.4	137.1
Lubuskie	2.1	0.5	82.0
Łódzkie	1.4	0.9	133.3
Małopolskie	1.4	0.4	83.4
Mazowieckie	1.5	1.0	118.2
Opolskie	0.4	0.6	181.8
Podkarpackie	3.0	0.3	84.2
Podlaskie	0.6	0.9	119.9
Pomorskie	1.0	0.7	129.3
Śląskie	3.3	0.7	123.2
Świętokrzyskie	2.5	0.5	104.5
Warmińsko–Mazurskie	1.4	0.7	98.9
Wielkopolskie	0.6	1.4	150.3
Zachodniopomorskie	1.6	0.4	108.7

Source: own compilation based on [40].

.

Next, the direction of preference for simple characteristics in relation to the general criterion under consideration was determined by dividing them into stimulants, disincentives, and nominants. The proportion of fallow land within the agricultural area was designated as having an inhibiting effect, while the remaining variables were classified as stimulants.

Normalization was achieved by making the values of individual characteristics comparable, by rescaling them and unifying their orders of magnitude. A valuable property of the normalized indicator values is that they fall within the range from 0 to 1. Vector normalization was applied in the study, as it is the standard approach in the TOPSIS method and allows for comparing criteria expressed in different units. For this purpose, the following formula was used [42,43]:

$$r_{ij}={\displaystyle \frac{s_{ij}}{\sqrt{\sum _{i=1}^n{s}_{ij}^2}}}$$

(1)

where

$s_{ij}$ is the value of the i-th variant according to the j-th criterion.

In the further stage of constructing the synthetic characteristics, simple features can be assigned weights. These may be determined based on statistical or substantive analysis, e.g., the Analytic Hierarchy Process (AHP) [44,45,46]. In the study, it was hypothesized that all sub-variables have equal weight due to the lack of clear empirical premises regarding the hierarchy of criteria importance. Moreover, the authors aimed to avoid subjectivity and maintain transparency.

The impact of adopting a different weighting system and alternative normalization was checked, and the results that were correct not only in terms of statistical but also substantive premises were selected.

The synthetic features for individual phenomena were determined using the standard method, which involves calculating the distance of an individual unit from the ideal solution. For this purpose, it is necessary to determine the positive ideal solution $x^{+}=(t_1^{+},t_2^{+},\dots ,t_k^{+})$ and the negative ideal solution $x^{-}=(t_1^{-},t_2^{-},\dots ,t_k^{-})$, based on the following formula:

• For factors with a stimulating effect (benefit criteria):

  $$t_j^{+}=\underset{i=1, \dots ,n}{\mathit{max}}{t}_{ij},$$

  (2)

  $$t_j^{-}=\underset{i=1, \dots ,n}{\mathit{min}}{t}_{ij}$$

  (3)
• For factors with an inhibiting effect (cost criteria):

  $$t_j^{+}=\underset{i=1, \dots ,n}{\mathit{min}}{t}_{ij},$$

  (4)

  $$t_j^{-}=\underset{i=1, \dots ,n}{\mathit{max}}{t}_{ij}$$

  (5)

The next stage of the study was to determine the Euclidean distance of each object from the positive ideal solution $x^{+}$ and negative ideal solution $x^{-}$ as per the formulas below:

$$D_i^{+}=\sqrt{{\sum }_{j=1}^k{(t_{ij}-t_j^{+})}^2}$$

(6)

$$D_i^{-}=\sqrt{{\sum }_{j=1}^k{(t_{ij}-t_j^{-})}^2}$$

(7)

The synthetic characteristics were calculated according to the following formula:

$$c_i^{+}={\displaystyle \frac{d_i^{-}}{D_i^{+}+D_i^{-}}}\in [\mathrm{0,1}].$$

(8)

The smaller the distance to the positive ideal solution $x^{+}$ and the larger the distance to the negative ideal solution $x^{-}$, the closer to 1 is the value of the synthetic measure.

The variants are sorted according to the principle that an elevated index value $c_i^{+}$ corresponds to a superior variant.

The results are shown in

Table 6. Characteristics used to determine the agricultural structure, environmental condition, and production performance.

Voivodeship	Agrarian Structure (Share of Farms Larger Than 10 ha in the Total Farm Area (%))	Environmental Condition (Synthetic Characteristic)	Production Performance (Synthetic Characteristic)
Dolnośląskie	80.74	0.23	0.49
Kujawsko–Pomorskie	83.46	0.08	0.72
Lubelskie	58.25	0.14	0.48
Lubuskie	86.50	0.68	0.31
Łódzkie	56.78	0.07	0.59
Małopolskie	29.39	0.31	0.42
Mazowieckie	62.87	0.21	0.59
Opolskie	83.03	0.12	0.65
Podkarpackie	38.51	0.31	0.07
Podlaskie	79.18	0.45	0.71
Pomorskie	83.44	0.24	0.57
Śląskie	59.50	0.18	0.25
Świętokrzyskie	42.57	0.17	0.23
Warmińsko–Mazurskie	90.04	0.78	0.50
Wielkopolskie	78.76	0.11	0.89
Zachodniopomorskie	90.89	0.78	0.37

Source: own compilation.

.

A subsequent analysis was conducted to ascertain the relationship between the utilization of direct payment support under the carbon farming eco-scheme in individual Polish voivodeships and the agrarian structure, environmental condition, and production performance. The analysis was conducted based on the results obtained using the TOPSIS method. To this end, an examination was conducted to ascertain the correlation between the indicators that characterize the use of payments and the characteristics of the conditions for agricultural development. Pearson’s correlation coefficient was used for that purpose, and the graphical similarity of the distribution of individual phenomena was assessed. To this end, quartile groups were determined, with each group comprising four voivodeships in one quartile.

3. Results and Discussion

3.1. Use of Support Under Direct Payments Within the “Carbon Farming and Nutrient Management” Eco-Scheme in Poland

It has been previously observed that eco-schemes are typically mandatory for the state, yet are voluntary for farmers. This prompts reflection on the factors that led individual producers to implement selected practices. The motivation to receive financial compensation has not yet been a determining factor in the adoption of a specific practice on a farm [47]. In most cases, individual practices had already been widely adopted. The introduction of direct payments within the carbon farming eco-scheme was intended to serve as a reward for efforts made to preserve or improve soil structure. According to the available data, during the 2023 campaign in Poland, 56% of the total agricultural area was covered by payments under the “Carbon farming and nutrient management” eco-scheme. However, support was accessed by barely 31% of farms with an area of more than 1 ha (

Table 7. Use of support under direct payments with the “Carbon farming and nutrient management” eco-scheme in Poland (2023 campaign).

Support Scheme	Share of Agricultural Land Covered by the Support Program (%)	Share of Farms with an Area of Over 1 ha Covered by the Support Program (%)
Direct payments under the “Carbon farming and nutrient management” eco-scheme	56.0	30.7

Source: own calculations based on [48].

).

The analysis of the data reveals significant regional differences in the use of support, both in terms of the area covered by payments and the number of farms that benefited from the aid (Figure 2 and Figure 3). When analyzing the share of agricultural land covered by payments under the carbon farming eco-scheme at the voivodeship level, a clear division of Poland into two parts can be observed: northern and western Poland, where the share is high, ranging from 60 to 95%, and southern and eastern Poland, with only 30 to 50% of agricultural land being covered by payments. A notable example of regions with a high proportion of agricultural land covered by support is the Opolskie voivodeship. Nearly 95% of its area, approximately 377,000 hectares, is under the purview of the eco-scheme. Given the characteristics of their production and the agrarian structure, farmers in this region predominantly engaged in one of the most prevalent practices, namely the “simplified cultivation systems” (Figure 4). An equally high proportion of agricultural land was found to be covered by support measures in the Dolnośląskie, Zachodniopomorskie, and Pomorskie voivodeships.

A similar trend is evident in the proportion of farms receiving direct payments under the carbon farming eco-scheme. However, it is imperative to acknowledge that the proportion of farmers who have derived benefit from this particular payment is considerably lower than the share of land covered by support. This could suggest that owners of larger farms may have received these payments more frequently.

According to the data from the Agency for Restructuring and Modernisation of Agriculture [49], among the three most popular practices used by farmers in Poland (based on the area declared for each practice) are “simplified tillage systems”, “incorporation of straw into the soil”, and “diverse crop structure”. It should be emphasized, however, that the analysis shows significant regional variation in this regard. In the western part of the country, where farms often have a more favorable agrarian structure and higher-than-average production potential, “simplified tillage systems” are more commonly applied. In contrast, in the southeastern part of the country, where agriculture is more fragmented, farmers primarily use “incorporation of straw into the soil” (Figure 4).

3.2. Use of Support vs. The Agrarian Structure

The ratio of farms larger than 10 ha to the total agricultural area was used to examine the relationship between agricultural structure and the use of support under the carbon farming eco-scheme. The agrarian structure at the voivodeship level is illustrated in Figure 5. A discernible dichotomy exists within the national territory, characterized by the presence of areas exhibiting a relatively concentrated structure, predominantly situated in western and northern Poland, and regions characterized by substantial fragmentation, predominantly located in southeastern Poland. This observation has been noted by numerous scholars, including [50,51,52,53,54]. Farms located in the northern and western regions are distinguished by their expansive acreage, enhanced marketability, and elevated adaptability to fluctuating environmental conditions. Conversely, a considerable proportion of farms in southern Poland have undergone a transformation in their nature, deviating from their traditional agricultural function and shifting towards tourism-oriented operations, or have been redefined as social or hobby farms [55]. The primary factors contributing to the spatial diversity of agriculture in Poland include historical conditions, particularly the distribution of various forms of ownership over agricultural land. The origins of this phenomenon can be traced back to the period of the partitions of Poland in the 19th century, when the contemporary territory of the nation was divided among the three partitioning powers—Germany, Russia, and Austria.

The diversity of the agrarian structure in Poland demonstrates a strong correlation with the utilization of support under direct payments from the carbon farming eco-scheme (

Table 8. Strength of correlation between the use of support under direct payments within the “Carbon farming and nutrient management” eco-scheme and the agrarian structure in Poland (Pearson’s correlation coefficient).

Specification	Share of Agricultural Land Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme	Share of Farms Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme
Indicator of agrarian structure	0.81	0.85
p-Value	0.00	0.00

Source: own compilation based on [40,48].

). In both instances, of the proportion of agricultural land and the proportion of farms receiving support, Pearson’s correlation coefficient exceeded 0.8 and is statistically significant. Similar results were obtained by calculating Spearman’s correlation coefficient. Consequently, the adoption of the carbon farming eco-scheme is predominantly observed among prominent agricultural enterprises with substantial production potential. It is noteworthy that these farms are better positioned to adhere to the principles of carbon farming, including the adoption of simplified cropping systems, winter intercrops/intercropping, and the development and implementation of a structured fertilization plan, for instance. In voivodeships affected by a more fragmented agricultural structure, farmers exhibit a reduced propensity to leverage such payments or adopt practices that are more readily implementable on a smaller scale, such as the incorporation of straw into soil.

3.3. Use of Support vs. The State of the Environment

Another salient aspect in the context of agricultural development is the state of the environment. This phenomenon is closely associated with natural conditions, which, according to Krasowicz [56], are 30–40% less favorable in Poland than in Western European countries with regard to agricultural production. Notwithstanding this fact, Polish agriculture maintains a substantial share in the agricultural production of the European Union. In this study, the state of the environment in Poland was described by several indicators, which served as the basis for structuring the relevant synthetic characteristic. As demonstrated in Figure 6, the most favorable environmental conditions are found in the northern part of the country, i.e., in the Warmińsko–Mazurskie, Zachodniopomorskie, Lubuskie, and Podlaskie voivodeships. Conversely, the synthetic characteristic exhibited its lowest values in the voivodeships situated in central Poland. The advantageous circumstances experienced by the northern voivodeships were predominantly attributable to the substantial presence of perennial grasslands in the northeast, the extensive forest cover, and the considerable proportion of ecologically significant areas in the northwest. The voivodeships with the lowest values of the synthetic characteristic relative to the state of the environment are located in the central part of the country and are extensively utilized for agricultural purposes. This has led to a reduction in the forest coverage and a decline in the area of permanent pasture.

When analyzing the strength of the relationship between the use of direct payment support under the “Carbon farming and nutrient management” eco-scheme and the state of the environment, no clear conclusions can be drawn (

Table 9. Strength of correlation between the use of support under direct payments within the carbon farming eco-scheme and the environmental condition in Poland (Pearson’s correlation coefficient).

Specification	Share of Agricultural Land Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme	Share of Farms Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme
Synthetic indicator of environmental condition	0.06	−0.05
p-Value	0.82	0.86

Source: own compilation based on [40,48].

). Pearson’s correlation coefficients were found to be nearly zero, which would suggest that the environmental state in Poland does not influence the utilization of support in any manner whatsoever. However, it cannot be unequivocally stated that such a correlation does not exist, as the p-value in both cases indicates that the result is statistically insignificant.

3.4. Use of Support vs. Production Performance

The final feature examined in the context of its impact on the utilization of direct payments within the “Carbon farming and nutrient management” eco-scheme pertains to production performance in Poland. The synthetic feature in question is represented in Figure 7. An analysis of the map reveals clear discrepancies in the structure and intensity of agricultural production across the Polish territory. The regions exhibiting the most favorable production conditions were the Wielkopolskie, Kujawsko–Pomorskie, Podlaskie, and Opolskie voivodeships. These regions had a relatively high percentage of cereals in the area of agricultural land, accompanied by a small area of fallow land. Furthermore, these regions were frequently distinguished by intensive animal and plant production, along with a consumption of NPK fertilizers per hectare of agricultural land that exceeded the national average level. The northeastern voivodeships demonstrated a predominant specialization in animal production, specifically milk and cattle. In contrast, the Wielkopolskie and Kujawsko–Pomorskie voivodeships exhibited a high degree of specialization in both plant and animal production, with a particular emphasis on swine [57]. Conversely, the southeastern regions of Poland exhibited notably diminished production outcomes, a phenomenon attributable to the prevalence of a relatively high agricultural fragmentation.

The production performance of Polish agriculture exerts a moderate influence on farmers’ utilization of support under the carbon farming eco-scheme. A higher correlation is observed between production performance and the share of farms covered by support than between the share of agricultural land for which payments were granted (

Table 10. Strength of correlation between the use of support under direct payments within the “Carbon farming and nutrient management” eco-scheme and the agricultural production performance in Poland (Pearson’s correlation coefficient).

Specification	Share of Agricultural Land Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme	Share of Farms Covered by the “Carbon Farming and Nutrient Management” Eco-Scheme
Synthetic indicator of production performance	0.40	0.69
p-Value	0.13	0.00

Source: own compilation based on [40,48].

). Analysis of Spearman’s correlation coefficient leads to similar results.

3.5. Characteristics of Agriculture in Poland with Respect to the Agrarian Structure, Environmental Condition, and Production Performance

As illustrated in

Table 11. Agricultural characteristics by percentage of farms covered by direct payments under the “Carbon farming and nutrient management” eco-scheme.

Voivodeships Ranked by the Percentage of Farms Covered by the Support Program Under Analysis	Number of Voivodeships in the Cluster	Indicators of
		Agrarian Structure	Environmental Condition	Production Performance
0.00–25.19	4	42.49	0.24	0.24
25.20–33.59	4	66.10	0.28	0.49
33.60–40.08	4	84.72	0.53	0.62
40.09–49.19	4	82.67	0.17	0.60

Source: own compilation based on [40,48].

, the study analyzes the characteristics of agriculture in Poland with respect to three features: the agrarian structure, environmental conditions, and production performance. The voivodeships were divided into four quartiles (each group comprising four voivodeships) according to the percentage of farms covered by direct payments under the “Carbon farming and nutrient management” eco-scheme. A subsequent analysis of the agrarian structure reveals a positive correlation between the degree of its favorability in a given region and the percentage of farms benefiting from the aid. A comparable scenario emerges in the context of production performance, as substantiated by prior calculations. However, this correlation was not as robust as that observed in the agrarian structure. Conversely, the indicator that reflects the environmental state exhibited an increase with the percentage of beneficiaries, albeit to a certain threshold. In the region with the highest percentage of farms receiving support (reaching 50%), the state of the environment is assessed as relatively the worst. It can be posited that these are regions characterized by intensive agricultural production, a practice that, while augmenting food productivity, comes at the expense of the environment.

Research on the implementation of eco-schemes, including the “Carbon farming and nutrient management” eco-scheme, is also being conducted in European countries. For example, in Germany, similarly to Poland, significant regional differences in the use of eco-schemes were observed. The participation rate was relatively high among farms classified as “other feed production” (farms keeping cattle and sheep, excluding dairy farms). In addition, the willingness to participate in a given eco-scheme was influenced by the necessity of incurring learning costs associated with implementing the practice. According to the German report titled “Beiträge zur Evaluierung der Öko-Regelungen nach GAP-Direktzahlungen-Gesetz (GAPDZG)” [58], the utilization of eco-schemes with high potential for environmental improvement (including carbon farming) was lower than initially expected. In the case of the Netherlands, according to the report “Netherlands—CAP Strategic Plan” [59], eco-schemes were assessed in terms of the number of participants and the area covered by the measures. The Netherlands is taking significant steps to increase participation in the carbon farming eco-scheme.

4. Conclusions

Payments under the “Carbon farming and nutrient management” eco-scheme generally meet the criteria for public payments for the provision of public goods. The environment, in its totality, is a subject of interest to society as a whole. Through the implementation of specific policies within the framework of taxation, society provides support to entities that prioritize the enhancement of environmental quality beyond the legal standards. However, the implementation of practices related to this eco-scheme also involves private goods. Indeed, the essence of this initiative is to enhance the quality of soil, which is recognized as the primary “toolkit” for farmers. It is reasonable to hypothesize that, with regard to the provision of public and private goods, the primary motivation of agricultural producers is purely economic. In the first case, the focus is on receiving compensation for the provision of a service to the society.

In the second case, the purpose is to ensure the quality of soil for the farmers themselves, which, in turn, contributes to the maintenance of long-term production capacity. In consideration of the aforementioned factors, the results (showing how the phenomenon under study varies across the country) become logical. The economic motivation for undertaking environmental measures is primarily witnessed in relatively large operators, which, on the one hand, can anticipate substantial financial returns in the form of payments and, on the other hand, are more inclined to prioritize the maintenance or enhancement of soil quality. This is why such a robust correlation exists between the intensity of utilization of support under the carbon farming eco-scheme and the agricultural structure and production performance, whereas the state of the environment exhibits a low (almost zero) correlation. It is important to acknowledge that, contrary to appearances, recognizing economic motivations may positively influence the environmental measures undertaken by farms that receive public funding (in this case, the budget allocated under the CAP). All economic operators, including farms, endeavor to optimize present and future economic outcomes. Consequently, both the provision of support itself and the implementation of measures aimed at enhancing soil quality can motivate farmers to act in a manner that benefits both the natural environment (i.e., society as a whole) and their own interests. The synergy between these two objectives is of paramount importance because it increases the likelihood that both public and private goods will be delivered. It cannot be excluded that short-term carbon sequestration measures may have adverse effects on the long-term soil quality or on the economic returns for farmers.

In the case of Poland, however, an additional factor merits consideration. A substantial body of research has demonstrated that considerable variations in the agrarian structure—more attributable to historical than natural factors—yield disparate levels of interest in environmentally oriented activities. Ensuring food security and protecting the environment (including agricultural soil) are contingent upon implementing measures to enhance the agricultural structure. This requires the establishment of large, economically efficient family farms that can supply the market with agricultural raw materials while concurrently possessing the technical capacity and social capital to implement measures that protect the soil and other elements of the agricultural environment.

However, it should be noted that these conclusions are based on research into the spatial differentiation of the phenomenon. On the one hand, this approach adds value to the understanding of the differentiated use of eco-schemes, but on the other hand, it also limits it. The study did not cover agricultural holdings, but it can be assumed that factors such as level of education, environmental awareness, and social capital in general may also determine participation in eco-schemes. However, this does not change the overall conclusion that, ultimately, it is the agrarian structure that is decisive. Research by Sadowski [60] shows that larger farms are characterized by higher levels of both social and material capital and, most importantly, demonstrate the highest level of social, economic, and environmental sustainability. Of course, the aforementioned postulate of the need to create large and economically strong family farms should not be understood in terms of an administrative command, but rather as the long-term and gradual creation of conditions for such a process to take place. An important role in this process should be played by both support for the farms themselves and by the creation of jobs in rural areas outside agriculture.