Evaluation of the Agricultural Green Competitiveness in the European Union

Evaluation of the Agricultural Green Competitiveness in the European Union | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of the Agricultural Green Competitiveness in the European Union Aina Muska, Irina Pilvere, Aleksejs Nipers This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6752700/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2025 Read the published version in Environmental Sciences Europe → Version 1 posted 9 You are reading this latest preprint version Abstract Background In the twenty-first century, there is a growing awareness of the role of sustainable agriculture in responding to environmental and socio-economic challenges, as well as the need to provide food for a growing population. Conventional intensive farming techniques often threaten the environment, biodiversity, and public health. Therefore, a possibility is sought to transform agriculture and ensure the green competitiveness thereof, based on the current environmental potential and the capability to manage it sustainably. The European Green Deal and the subordinate strategies set the targets to be achieved by the Member States of the European Union (EU). Therefore, the present research aims to assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators. Results For the present research, a synthetic index was developed – the Green Competitiveness Index of Agriculture –, which combines 15 environmental indicators in line with the targets set for the implementation of the European Green Deal to quantify the overall green competitiveness of the agricultural sector in the EU Member States. After calculating the index for 2018 and 2022, the research created a linear hierarchy and classification of Member States, ranking them accordingly. The overall level of green competitiveness of agriculture in the EU was found to be average. Of the 27 Member States, only 9 improved their position in the ranking, 14 experienced a decline, and 4 maintained their previous position in 2022. Most of the EU Member States face similar challenges in the area of green competitiveness of agriculture, both at the national level and at the EU level, to achieve the goals of the European Green Deal. Achieving the following targets of the European Green Deal might be problematic: area under organic farming, high diversity landscape features, air quality, sustainable energy, and energy efficiency. Conclusions The data analysed revealed significant changes in the level of green competitiveness of agriculture across EU Member States. Overall, the results showed that although the level of green competitiveness of agriculture in the EU remained medium and relatively steady in 2022 compared with 2018, the Member States' targets gradually converged as cross-country disparities decreased. The results indicated some convergence and changes in the ranking regarding the level of green competitiveness of agriculture, highlighting both the progress and the backwardness of individual Member States, which need to be considered by policymakers when developing future policies and sectoral development strategies. green competitiveness agriculture environmental indicators synthetic index EU Member States European Green Deal Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction In the twenty-first century, the need for sustainable agriculture arises from a confluence of environmental, economic, and social factors, which requires a paradigm shift in the management of agricultural systems and food production. Scientific projections show that conventional agricultural practices are unsustainable, leading to various harmful consequences, including groundwater pollution, greenhouse gas emissions, biodiversity loss and aquatic ecosystem eutrophication (77). As the global population continues to grow exponentially, the need for innovative and sustainable agricultural solutions tends to increase (70). The concept of sustainable agriculture, while it shares common features with green agriculture, is a broader area that covers not only environmental considerations but also economic viability and social equity (69; 75). Sustainable agriculture aims to meet the needs of the present without compromising the ability of future generations to meet their own needs by advocating practices that are environmentally friendly, economically feasible, and socially fair (12). Therefore, the implementation of environmentally and climate-friendly agricultural practices has contributed to the emergence of the term green agriculture. It is a paradigm for reducing the negative impacts of agriculture on the environment while ensuring the sustainability of this sector. Although the exact origins of green agriculture are difficult to identify, its philosophical foundations could be traced back to the early environmental movements of the 20 th century, which raised concerns about the harmful effects of conventional agriculture on ecosystems and human health (30). Green agriculture involves a holistic approach that integrates environmental principles into agricultural systems, thereby seeking to align agricultural production with environmental protection (50) and supply food for the planet's population by reducing the negative environmental impacts of agriculture, and is perceived as part of a broader global transition to a sustainable low-carbon economy (56). This approach is in stark contrast to the conventional agricultural pattern, with the farmers prioritising higher yields and productivity through the intensive use of both mineral fertilizers and plant protection products, which usually affect environmental quality, human health, and biodiversity (12). Green agriculture offers viable solutions by integrating environmental principles into agricultural practices, reducing dependence on synthetic resources, and contributing to ecosystem services. The introduction of green agricultural practices is an essential element to ensure food security for future generations, as the environmental impacts of conventional agriculture are significant, thus making it one of the main contributors to global environmental degradation, which disturbs the balance and poses a risk to human health (79). For example, excessive use of nitrogen fertilizers leads to the release of nitric oxide, whose global warming potential far exceeds the global warming potential of carbon dioxide (4). In addition, runoff of excess nutrients from fields contributes to the eutrophication of aquatic ecosystems, thereby resulting in algal blooms, a lack of oxygen and a decrease in aquatic biodiversity (76). The widespread use of conventional intensive agriculture has caused a global environmental crisis and leads to negative climate changes (44). The development of green agriculture urgently needs to be implemented as part of an integrated strategy for sustainable land use and food security to reduce the environmental impacts of agriculture and achieve the Sustainable Development Goals (67). Koohafkan et al. (2011) propose a set of 10 factors to define the green agricultural system and ensure enough access to food and ecosystem services, while reducing the negative impacts of climate change, the amount of fossil energy consumed for production and environmental degradation (42). Shen et al. (2020) propose the concept of green agriculture development as a model for transforming Chinese agriculture, thereby fostering the transformation of crop and livestock production and food production systems to achieve high environmental standards and food quality, high resource efficiency and low environmental impacts (70). The role of green technologies for the development of sustainable agriculture is important, as they can help to solve the agricultural, socio-economic, and environmental problems posed using chemicals in conventional agriculture. Several authors believe that various green technologies can help in developing green agriculture, e.g. Soares et al. (2023) refer to organic farming, integrated pest control systems, biogas, biofuel, wind energy, as well as the use of information and communication technologies (71). Zhnag et al. (2020) point out that soil biodiversity and crop diversification are essential for sustainable and environmentally friendly agriculture (83). Srisruthi et al. (2016) emphasize the need for environmentally friendly sensor technologies that contribute to sustainable agriculture by effectively monitoring and controlling processes and resources such as water, fertilizers, and energy (74). Lin & Li (2023) and Dong et al. (2025) argue that the development of green agriculture will be driven by its digitalization (46; 11). It could be concluded that scientists from various countries refer to different problems concerning the development of green agriculture, yet their common goal is to solve global food production problems and foster sustainable development around the world. That is why the European Green Deal also represents a paradigm shift in the common approach of the EU and its Member States to environmental sustainability. As a policy document, the European Green Deal has a decisive impact on the progress of agriculture towards climate neutrality and environmental sustainability (33). To implement the European Green Deal, the F2F was developed, which aims to create a fair, healthy, and environmentally friendly agri-food production system in the EU (2). The F2F strategy aims to revolutionize not only the way food is produced, processed, and supplied but also to change consumption habits by setting ambitious goals to reduce the environmental impacts of agriculture (78). The European Green Deal identifies the need to shift to green agriculture, assess conventional farming techniques already in place and move towards more environmentally friendly solutions (63). The sustainability of the agri-food system has become a central item on the agenda, thus contributing to the adoption of various documents by the EU institutions as well as Member State governments, which are aimed at implementing the European Green Deal and improving sustainability throughout the food supply chain, from production to consumption (64). Meeting the requirements set by the documents in the EU and its Member States is essential for the development of green agriculture (3). As a world leader in environmental policy and sustainable development, the EU recognises the critical role of agriculture in shaping the environmental, economic, and social wellbeing of its Member States, identifying the need for a transition to greener and environmentally friendly agricultural practices (64). This transition is not only an environmental imperative but also an economic opportunity to foster innovations, create new products and services and improve the resilience of the agricultural sector to climate change and other environmental challenges (78). Green agriculture involves a variety of areas, aiming to reduce the negative environmental impacts of agriculture while maintaining or even increasing productivity (59). Green agriculture also contributes to reducing greenhouse gas emissions, maintaining water resources, protecting biodiversity, and improving soil health, thereby ensuring the long-term sustainability of agricultural production (81). The development of green agriculture is also in line with EU commitments to achieve the United Nations Sustainable Development Goals, in particular food security, climate action and environmental protection (2). Therefore, assessing the green competitiveness of agriculture, which is a multifaceted concept and goes beyond the productivity and profitability of conventional agriculture, including environmental sustainability, social responsibility, and economic viability, has come to the attention of scientists. It indicates the ability of agricultural enterprises, including individual farms as well as the entire agriculture sector, to efficiently produce and supply agricultural products while reducing negative environmental impacts, maintaining natural resources, and contributing to public prosperity (1). At its core, the green competitiveness of agriculture is about achieving a balance between agricultural production and preserving the environment, thereby recognizing that the long-term sustainability of agriculture depends on the economic viability of the farm, the health and resilience of the natural environment (77). Environmental performance is critical with a focus on reducing greenhouse gas emissions, protecting biodiversity, improving soil health, and reducing water pollution through practices such as carbon sequestration, habitat restoration, and nutrient management planning (48). An analysis of various indicators should allow policymakers, farmers, businesses, and civil society to better understand the current circumstances, identify trends, set targets, monitor progress, and compare performance between regions and countries (62). Therefore, the present research aims to assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators. The research put forward three hypotheses (H) : H1: The competitiveness level of green agriculture in the EU is average. H2: The green competitiveness of agriculture in the EU tends to increase. H3: There are significant differences between EU Member States in the level of green competitiveness of agriculture. Novelties of the research : (1) a synthetic index was designed to assess the level of green competitiveness of agriculture regarding the goals of the European Green Deal; (2) unique indicators showing original characteristics resulting from the targets of the strategies underlying the European Green Deal were identified; (3) five indicators that have not been used to date in other competitiveness assessments were used by the research. The research included only indicators showing the environmental impacts of agriculture, as opposed to other research studies employing environmental indicators as only part of the set of indicators. Background: The concept of green competitiveness of agriculture Competitiveness is a multifaceted and dynamic concept that has attracted considerable attention in various scientific disciplines, including economics, management, political science, and sociology, mainly because it serves as a crucial indicator of success and sustainability for individuals, organizations, and countries in an increasingly interconnected and competitive world (51; 65). The concept of competitiveness has been the subject of scientific research in manufacturing and related industries since the early eighties and nineties of the 20 th century (61; 60; 8; 49). Competitiveness often refers to the ability to compete and develop effectively in a particular market or environment, facing a range of factors (28; 80). Debates on the national competitiveness of countries have also revealed various misunderstandings (43), e.g., that the success of a country occurs at the expense of others, ignoring the potential for mutually beneficial trade and cooperation (72). The competitiveness of a country is the ability to foster sustainable economic growth, increase the quality of life and attract and retain companies and talent in an increasingly interconnected and competitive global context. The ability of a country to compete effectively is not only a matter of economic prosperity but also an important characteristic of its long-term viability, social welfare, and overall state of development in the global arena (41). It is the nation's ability to create an environment where businesses can thrive, innovations can develop, and individuals can fully implement their potential (66). In the 21 st century, the problem of the competitiveness of a national environment has become topical. It can cover various levels, from individual companies to national economies, and requires a joint effort by stakeholders from various sectors to foster interactions between environmental regulations, corporate strategies and the economic and social development of a country or region (14). It recognises that environmental protection and economic competitiveness are not mutually exclusive but are strategically aligned to contribute to sustainable development (57). Green competitiveness is the ability of a country or organization to maintain or improve its economic position while reducing its environmental impacts and facilitating the transition to an economy producing low or zero greenhouse gas emissions (82). Bruneckienė et al. (2023) have similar opinions, emphasizing that green competitiveness is the ability of a country to maintain or improve economic performance while reducing the burden on the environment and fostering the transition to an economy producing low or zero greenhouse gas (GHG) emissions (5). The concept of green competitiveness of agriculture includes the ability of farms and food businesses to compete effectively in the market while reducing their environmental impacts (9). Porter was the first to begin advocating green competitiveness in 1991, pointing out that the contradiction between the environment and competitiveness will disappear after strict environmental standards encourage business innovation (45). Chygryn & Miskiewicz (2022), analysing scientific research papers from the Scopus database for the period 1991-2021, identified four main stages in the development of the theory of green competitiveness of enterprises: a) the first stage (2004-2012) was associated with the development of processes of greening economic activity; (b) the second stage (2012-2014) – with greening of economic activity and the development of the green economy; (c) the third stage (2014-2016) – with a competitiveness analysis of green marketing strategies; d) the fourth stage (since 2016) – with the direct formation of the concept of green competitiveness (7). The authors of the research believe that a similar development path is also associated with the evolution of the green competitiveness of agriculture in Europe. Until 2018, researchers focused more on the overall competitiveness of agriculture, yet with an increase in climate and environmental problems as well as because agricultural activity has an impact on the environment, there appeared research studies on the competitiveness of sustainable agriculture (55), green growth in agriculture (39; 38; 37), and only then there were available research studies on the green competitiveness of agriculture in the EU (53). Since there is not much research pertaining to the green competitiveness of agriculture, the definition of green competitiveness of agriculture by Nowak & Kasztelan (2022) is used for the purposes of this research, which means achieving the competitive advantages of the agricultural sector based on the current environmental potential and the ability to manage it sustainably (53). Nowak & Kasztelan (2022) point out that green competitiveness has not been clearly defined and researched; however, given the challenges faced by agriculture (growing competition for alternative uses for natural resources, the need to preserve biodiversity, tackle food safety and climate change problems) forces researchers to examine the competitiveness of the agricultural sector through the prism of the environment (53). Bruneckienė et al. (2023) have noted that despite the strong commitments that the EU has made through various statements and recommendations to achieve climate neutrality in the common European space, there are large differences between the results achieved by its Member States in various areas – economic, social, infrastructure, education, research, development and elsewhere –; however, overall, the EU Member States need to achieve a common goal of becoming competitive and climate neutral (5). This research, therefore, focuses on assessing the green competitiveness of agriculture in the EU Member States by using only environmental indicators. Governments can boost green competitiveness by putting in place policies that incentivise green innovation, encourage sustainable practices and set clear environmental standards. Achieving green competitiveness requires a concerted effort by governments, businesses, and individuals to prioritise environmental sustainability and adopt innovative solutions that contribute to economic growth while protecting the planet for future generations. Since the European Green Deal and its underlying strategies are the focus of the present research, these key EU documents are analysed as well. The European Green Deal, adopted in 2019, is a comprehensive document for achieving climate neutrality by 2050 (32). In the field of agriculture, it is subordinated to several strategies adopted in 2020: the F2F strategy (2), the EU Biodiversity Strategy for 2030, which is a comprehensive and ambitious long-term plan for the protection of biodiversity, the restoration of degraded ecosystems and the supply of essential ecosystem services (6). There should also be also highlighted the EU Energy System Integration Strategy (16), whose goal cannot be achieved without the contribution of agriculture to the production of renewable energy. Agriculture also has to contribute to the goal set by the EU Methane Emission Reduction Strategy, aimed at reducing methane emissions through the production of sustainable biogas (17). In 2021, the European Green Deal was enshrined in the European Climate Law, which requires the Member States to meet the targets set and face potential penalties for non-compliance (13). The EU Action Plan: 'Towards Zero Pollution for Air, Water and Soil' was also adopted in 2021, specifying an integrated vision for zero pollution for 2050 (21). It follows from the action plan that agriculture will have to contribute to limiting ammonia emissions by reducing nutrient losses, the use of pesticides and the associated risks, as well as the sale of antimicrobials for use in livestock and aquaculture by 50%. It follows from the Sustainable Carbon Cycles that agriculture should ensure the eradication of carbon-based farming practices (24). Methodology and Data The present research consists of seven consecutive stages : 1) definition of the research object and subject; 2) selection of indicators based on the goals of the European Green Deal; 3) standardization of indicators by applying the zero-unitization method; 4) calculation of the synthetic index GCIA (Green Competitiveness Index of Agriculture); 5) development of a linear hierarchy and classification of countries; 6) ranking of Member States; 7) discussion and development of conclusions. At the beginning, the research identified the research object and the research subjects to be analysed. Since the research aims to assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators, it was decided to design a synthetic index – GCIA –, which is a composite indicator that combines several individual indicators to quantify the overall green competitiveness of the agricultural sector. Kasztelan (2020) emphasizes that in case it is necessary to analyse several indicators, empirical research usually employs multidimensional comparative analysis methods, the main idea of which is to create a composite indicator called a synthetic index, which provides the grounds for setting a hierarchy of studied objects according to the level of a multi-feature phenomenon ( 36 ). The synthetic index is based on the TOPSIS method developed by Ching-Lai Hwang and Kwangsun Yoon (1981) ( 52 ). To be able to identify a change in the level of competitiveness over a period and assess whether it is improving or deteriorating, it was decided to calculate the synthetic index for 2018 (base year) and 2022, given the availability of the most up-to-date data for all EU Member States. The entities to be analysed were 27 EU Member States: Austria (AT), Belgium (BE), Bulgaria (BG), Croatia (HR), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (ES) and Sweden (SE). At the second stage, the research selected indicators showing the green competitiveness of agriculture to describe the phenomenon examined – the green competitiveness of agriculture regarding the goals of the European Green Deal. Given that the list of indicators depends on the context of the problem and that the competitiveness of EU Member States needs to be assessed in the context of the goals of the European Green Deal (European Commission, 2019), the authors of the research first identified environmental targets for agriculture resulting from the goals of the European Green Deal, as well as indicators set by its subordinate strategies when creating a set of indicators for a synthetic index (15; 16; 17; 18; 19; 21; 24), see Fig. 2. Figure 3 presents the logic of selecting the indicators. Based on a review of scientific literature (55; 47; 36; 37; 38; 53; 35; 54; 19) and the authors' research experience, the research selected 19 indicators that indicate agriculture's green competitiveness and are aligned with the goals of the European Green Deal. The availability of data was checked for all 27 Member States for all the selected indicators. Four indicators were excluded from the research: "Common farmland bird index", "Soil organic carbon in arable land", "Gross nitrogen balance in kilograms per hectare of UAA", and "Gross phosphorus balance in kilograms per hectare of UAA" due to a lack of data. Kasztelan (2020) has also pointed out that researchers at this stage might face two problems: correctly identifying indicators and a lack of available data ( 36 ). Magrini (2022) also found a similar problem, which led to the abandonment of several indicators that would show the environmental impacts of agriculture (phosphorus and potassium balances) due to a lack of available data ( 47 ). At the next stage, a correlation analysis was performed for the 15 indicators selected (Table 1 ) to identify relationships between the variables in the dataset. After the correlation analysis, a decision was made to use all 15 indicators in calculating the green competitiveness index of agriculture. The research used European Commission (EC) Agri-food Data Portal ( 22 ), Eurostat (European Commission database) ( 25 ), FAOSTAT (Food and Agriculture Organization database) ( 27 ), European Environment Agency (EEA) ( 23 ), European Medicines Agency ( 26 ), etc. (Table 1 ). The third stage involved standardizing the indicators by employing the zero unitarization method. For the research, all the indicators were divided into stimulants or destimulants. The set of explanatory indicators (i.e., all the indicators that were used to assess competitiveness) included both stimulating indicators (stimulants), which had a positive effect on competitiveness (the higher its value, the better), and destimulating indicators (destimulants), which negatively affected the phenomenon examined (the lower its value, the better) ( 36 ). For example, from the perspective of green competitiveness, larger areas of organic UAA are desirable, and this indicator is a typical stimulant. At the same time, high GHG emissions are undesirable for the competitiveness of agriculture, so this indicator is a destimulant. Of the 15 indicators, four were larger-the-better characteristics (stimulants) with a positive influence on the synthetic index (Table 1 ). Eleven indicators were regarded as smaller-the-better characteristics (destimulants), which reduced the green competitiveness index of agriculture. The values of the indicators ( Xj, j = 1, 2, .., m ) showing the subjects examined (EU Member States) ( Oi, i = 1, 2, .., n ) could be represented as a matrix of observations in the following form: X = \(\:\left[\begin{array}{ccc}{x}_{11}&\:\cdots\:&\:{x}_{1m}\\\:⋮&\:\ddots\:&\:⋮\\\:{x}_{n1}&\:\cdots\:&\:{x}_{nm}\end{array}\right]\) ( 1 ) To ensure comparability of the data and a uniform scale for further analyses, the indicators selected were standardized employing the zero unitarization method, which could be represented as follows (29; 73): z ij = \(\:\frac{{x}_{ij}-min{\left({x}_{{i}_{j}}\right)}_{i}}{\text{max}{\left({x}_{ij}\right)}_{i}\:-\:min\:{\left({x}_{{i}_{j}}\right)}_{i}}\) for stimulants ( 2 ) and z ij = \(\:\frac{\text{max}{\left({x}_{ij}\right)}_{i}\:-\:\:{x}_{ij}}{\text{max}{\left({x}_{ij}\right)}_{i}\:-\:min\:{\left({x}_{{i}_{j}}\right)}_{i}}\) for destimulants ( 3 ) Where: zij – normalised value of the j-th indicator in the i-th country, xij – initial value of the j-th indicator in the i-th country, min (xij) i – minimum value of xij , max (xij) i – maximum value of xij . This method was chosen because it was the only method that corresponded to all seven postulates stated for the procedure for standardizing the value of indicators ( 34 ). The z ij values of the indicators were in the range [0; 1], they had no physical units; therefore, they could be counted and compared (34; 40; 37). The normalised value of a variable was then used for calculating the median (formula 4) and standard deviation (formula 5) (31; 38). For the median odd number of observations (m = 15): Mei = \(\:{z}_{\left(\frac{m}{2}+1\right)i}\) ( 4 ) Standard deviation: $$\:Sei=\sqrt{\frac{1}{m}\sum\:_{j=1}^{m}{{({z}_{ij}\:-\:\stackrel{-}{z})}^{2}\:\:}_{\:}\:}$$ 5 Where: \(\:\stackrel{-}{z}\) – mean value for a z ij . At the fourth stage, a synthetic index – the Green Competitiveness Index of Agricultura ( GCIAi ) – was calculated for each EU Member State based on the median values and standard deviation of normalised variables (formula 6) for 2018 and 2022 ( 35 ): GCIA i = Me i \(\:\times\:\) (1-Se i ) ( 6 ) An index value closer to 1 means a relatively higher level of green competitiveness of agriculture, whereas a relatively lower level of green competitiveness is closer to 0. The synthetic indexes calculated made it possible to perform a comparative analysis of the EU Member States for the years selected and assess the changes that occurred in 2022 compared with the base year. At the fifth stage, the research made a linear hierarchy of Member States in descending order, and classified them based on the synthetic index calculated. The Member States were divided into four groups with similar levels of green agricultural competitiveness, using the following key ( 53 ) (Fig. 4). Based on the values of the synthetic index, the Member States were ranked (1st – the highest level of competitiveness, 27th – the lowest level), and the assigned rankings were compared between both years analysed. Results For the 15 indicators, the following statistical parameters were calculated: arithmetic mean, minimum value, maximum value, standard deviation, and coefficient of variation. The values are shown in Table 2 . The coefficients of variation ranged from 5.52% to almost 200%. The largest differences were observed for the following indicators: Share of GHG from agriculture in total net emission (X10); Production of renewable energy from agriculture (X13); Final energy consumption by the agriculture and forestry sector (X15); Share of groundwater monitoring stations with nitrate concentration greater than 50 mg/l (X5); Agricultural emissions of NH 3 , t per hectare of UAA (X11). In contrast, the smallest differences were found for the following indicators: Share of agriculture in total NH 3 emissions (X12); HRI 1 (X4); Pesticides use per value of agricultural production ( X3 ); Share of utilised agricultural area under organic farming ( X7 ). Based on the methodology described, the green competitiveness index of agriculture was calculated both for the EU as a whole and for each of the 27 Member States. The average value of GCIA for the EU in 2022 was 0.4749, while in the base year (2018) – 0.4786, which means that over a five-year period the index has remained almost unchanged, but with a downward trend (decrease of 0.0037). Given the possible range of the index [0–1], this means that the level of green competitiveness of agriculture in the EU was average. Consequently, hypothesis H1: The competitiveness level of green agriculture in the EU is average has been confirmed, whereas hypothesis H2: The green competitiveness of agriculture in the EU tends to increase was rejected because the index has remained almost unchanged over five years. The standard deviation of the GCIA mean value has decreased from 0.1113 (in 2018) to 0.1036 (in 2022), which means that the data dispersion around the mean has also decreased slightly, yet the differences are small. This might indicate the stable level of green competitiveness, as well as the fact that the differences between the EU-27 have decreased. Over the years analysed, the relative standard deviation (or coefficient of variation) has decreased from 23.2% in 2018 to 22% in 2022, which also indicates a moderate (medium) dispersion, which means that the data are not very dispersed, but also not very concentrated around the mean. If the GCIAi values for a Member State are compared with the highest level of green competitiveness of agriculture in 2018–0.6166 (SK) and in 2022–0.6058 (EL) and the lowest level of green competitiveness in 2018–0.1106 (CY) and in 2022–0.1402 (MT), it can be found that this difference in 2018 was almost 6 times, but in 2022–4.3 times. This also indicates that there are differences in the green competitiveness of agriculture between the EU Member States, yet the gap tends to decrease. Consequently, hypothesis H3: There are significant differences between EU Member States in the level of green competitiveness of agriculture – must be rejected. The results for the 27 EU Member States are presented in Table 3 and Fig. 5 , with the colours illustrating the division of the EU Member States into four groups with different levels of green competitiveness of agriculture. According to the results, three Member States (EL, SK, CZ) were classified into Group I, as they reached the highest level of green competitiveness of agriculture in 2022 (Table 3 , Fig. 5 ). In 2022, the highest level of green competitiveness of agriculture was in Greece (GCIAi = 0.6058), compared with the level reached in 2018 (GCIAi = 0.5980), which has slightly increased (by 1.3%). By contrast, Slovakia, which had the highest level of green competitiveness of agriculture (GCIAi = 0.6166) among the 27 EU Member States in 2018, and the Czech Republic showed a decrease by 3% and 1%, respectively, in 2022. In 2022, 15 Member States with a moderately high level of green competitiveness could be classified into Group II, while 7 with a moderately low level could be classified into Group III. As shown in Fig. 5 , the number of Member States with a moderately high (Group II) and moderately low level of green competitiveness (Group III) has increased during the period analysed. At the same time, the changes reduced the number of Member States with a low level of green competitiveness (Group IV). In 2022, the green competitiveness of both Dutch and Irish agriculture increased compared with the base year, by 15% and 35%, respectively, thus placing the Netherlands in Group III and Ireland in Group II in 2022. In 2022, only two EU Member States maintained a low level of green competitiveness (Group IV). Malta had the lowest level of green competitiveness (GCIA = 0.1402), which halved (50.6%) compared with 2018 levels (GCIA = 0.2837). There was also a low level of green competitiveness of agriculture in Cyprus, where the competitiveness index decreased by 77% over the period analysed. Over the period analysed, the level of green competitiveness of agriculture has increased in France, Italy, Portugal, and Slovenia from moderately low (2018 – Group III) to medium (2022 – Group II). By contrast, in four Member States (FI, HU, LU, EU), the level of green competitiveness of agriculture has decreased from medium high to medium low in 2022 compared with 2018. Table 4 shows the rankings assigned to EU Member States based on the synthetic index. In 2022, only 9 Member States have climbed up, 14 down, while four (CZ, DE, NL, RO) have maintained the status quo. The results also show that hypothesis H2: The green competitiveness of agriculture in the EU tends to increase must be rejected if viewed through the prism of the EU Member States. France (+ 16 places), Denmark (+ 11), Portugal and Lithuania (+ 9 each) and Ireland (+ 8) showed the greatest progress during the period analysed. In contrast, Finland, and Sweden (-10 places each), as well as Austria and Luxembourg (-7 each) experienced the largest decreases. An in-depth analysis of the indicators leads to a conclusion that for 10 indicators out of the 15 (or 67%), the average standardised mean values exceed 0.5000. But the other five indicators, with values below 0.5000, highlighted the most significant problems to be solved at the EU level. They were: A low share of UAA under organic farming (X 7 ), which was 0.3574 (2018) and 0.4191 (2022), tended upwards ("↑"); A low share of agricultural land occupied by high-diversity landscape features (X 8 ), 0.2504 (2018) and 0.1970 (2022), tended downwards ("↓"); A high share of agriculture in total NH 3 emissions (X 12 ), 0.4997 and 0.4084, respectively, showed a downward trend ("↓"); Production of renewable energy from agriculture (X 13 ), 0.0932 and 0.1000, respectively, an upward trend (“↑”); A low share of agriculture in the production of renewable energy (X 14 ), 0.2510 and 0.2765, respectively, an upward trend (“↑”). These results revealed that two indicators (X 8 , X 12 ) have decreased over a five-year period (those showing a trend of "↓") and three indicators (X 7 , X 13 , X 14 ) have slightly increased (those with a trend of "↑"). The indicators showed the average level of green competitiveness of agriculture in the EU during the two years analysed; therefore, these areas should be given special attention at both EU and Member State level. Table 5 summarises indicators for the EU Member States that show specific areas of green competitiveness of agriculture that require future corrective action at the national level. It is assumed that a specific area requires intervention if the standardized value of the indicator for the given country is below 0.4 (zij < 0.4000) ( 36 ). The data presented in Table 5 show that most of the EU Member States faced similar challenges in the green competitiveness of agriculture, both at the national and EU levels. If these areas are not given special attention at both the EU and national levels, this will have an impact on achieving the following goals of the European Green Deal and their subordinate targets: 1) area under organic farming (25% of the EU's agricultural land under organic farming by 2030); 2) high diversity landscape features (10% of agricultural area under high-diversity landscape features by 2030); 3) improvement in air quality (a 25% reduction in ecosystems where air pollution endangers biodiversity by 2030); ( 4 ) sustainable energy and energy efficiency (building a climate-neutral, sustainable, integrated energy system with renewable electricity, circularity, as well as renewable and low-carbon fuels at its core). Discussions For the discussion, the present research sought similar research studies who used other indicators for analysing agricultural sustainability (47; 55), green growth (37; 39; 38), agricultural competitiveness (35; 52; 54), as well as the green competitiveness of agriculture as opposed to the economic competitiveness of agriculture ( 53 ). From the results, it follows that they were dominated by 4 indicators: Share of UAA under organic farming (X 7 ); Share of agriculture in renewable energy production (X 14 ); Net emissions from agriculture, tonnes of CO 2 equivalent per hectare of UAA (X 9 ); Final energy consumption by agriculture and forestry (X 15 ). It could be concluded that the 5 indicators used by the research are unique: 1) use of pesticides per value of agricultural output, g/international Dollar (X 3 ); 2) HRI 1 (X 4 ); 3) share of groundwater monitoring stations where the nitrate concentration exceeds 50 mg/l (X 5 ); ( 4 ) active ingredient of veterinary antimicrobials applicable mainly for food-producing animal species (X 6 ); ( 5 ) share of high-diversity landscape features (X 8 ). The present research employed two indicators: agricultural emissions of NH 3 (tonnes per hectare of UAA) (X 11 ) and production of renewable energy from agriculture (tonnes of oil equivalent) (X 13 ) are not considered unique, as they have been used by other research studies in relative terms. According to Nowak and Kasztelan (2022), the highest level of green competitiveness of agriculture was found in Austria (Group I) ( 53 ). However, the research classified Austria into Group II for the two years analysed. According to the authors' conclusions, the strengths of Austria (Zij >0.9000) in 2018 were low X 6 , high X 7 and low X 10 and X 15 . However, in 2022 the strengths were only high X 7 and low X 10 . According to a research study by Nowak & Kasztelan (2022), low levels of green competitiveness of agriculture (Group IV) were found in the Netherlands, Belgium, Cyprus, Ireland, and Malta. In 2018, the research classified Malta, Cyprus, the Netherlands, and Ireland into Group IV, while Belgium was ranked at the end of Group III with a synthetic index of 0.3679, so the results were similar. Nowak & Kasztelan (2022) have concluded that the high level of green competitiveness of agriculture does not always correlate with the overall economic competitiveness of a country ( 53 ). Higher economic competitiveness is often associated with greater negative environmental impacts. The largest difference between economic and green competitiveness was found in the Netherlands, which ranked 2nd in terms of economic competitiveness and only 27th in terms of green competitiveness. Jarosz-Angowska et al. (2022) concluded that in 2018, the overall level of competitiveness of the agricultural sector in the EU Member States was very low, as well as significant differences between the Member States ( 35 ). Compared with 2004, the agricultural competitiveness of EU Member States had declined. In 2018, the highest levels of competitiveness were found in Romania, France, the Netherlands, and Denmark, while the lowest were in Poland, Cyprus, and Finland. The research study indicated that one of the main factors in the decrease in competitiveness was a decrease in the use of fertilizers. The present research identified the X 2 indicator as an area requiring increased attention and corrective action, as its value (Zij < 0.4000) was low in Belgium, Cyprus, Ireland, Italy, Malta, and the Netherlands in 2018 and remained low in Cyprus, Malta, and the Netherlands in 2022. Nowak and Kasztelan (2022) found that the highest levels of economic competitiveness of agriculture were in Spain, the Netherlands, France, and Germany ( 53 ). A similar opinion was expressed by Jarosz-Angowska et al. (2022), stressing that the high competitiveness of the Netherlands and France was stable and sustainable in the long term, as confirmed by several research studies, regardless of the research methods used ( 35 ). The research study additionally noted that Denmark, Germany, and Belgium were also the Member States with a high level of competitiveness. Belgium was particularly noteworthy, with a high intensity of use of technology in the agricultural sector, but at the same time it also had a significant negative impact on the environment ( 55 ). However, Jarosz-Angowska et al. (2022) concluded that the economic competitiveness of Ireland, Sweden, Finland, and Austria in agriculture was relatively low. The limited land resources of the Member States and the low share of agricultural workers were referred to as the main reasons for this situation ( 35 ). Magrini (2022) classified them into three groups when assessing the sustainability of agriculture in EU Member States between 2004 and 2018 ( 47 ). The first group (AT, FI, FR, HU, IT, LU, PT, SI, SP) included the Member States where partial economic and environmental sustainability, as well as full social sustainability, were achieved. The second group (BG, CY, DE, EL, IE, LV, NL, PL, SE) was characterised by significant progress in sustainability. Both groups shared a weak environmental sustainability objective of reducing greenhouse gas emissions. According to the results of the above research study, in 2018 (Table 5 ) X 9 and X 10 were problematic indicators for the Netherlands (X 9 ), as well as Sweden and Latvia (X 10 ). In 2022, X 9 and X 10 remained a challenge for the Netherlands and Malta (X 9 ), as well as Sweden (X 10 ). The third group (BE, CZ, DK, EE, LT, RO, SK) was characterised by full social and environmental sustainability, as well as partial economic sustainability. It should be noted that GHG emissions per hectare in this group were stable; therefore, reducing emissions was not a priority goal, which was also confirmed by the research results. Indicator X 9 was identified as a strength for the Czech Republic, Estonia, Lithuania, Romania, and Slovakia, while Denmark should pay attention to the development of this situation – the normalized value decreased from 0.4347 (2018) to 0.4146 (2022). If this trend continues and the value decreases below 0.4, X 9 becomes a weak area that requires special attention. Magrini (2022) emphasizes that the strong sustainable objectives common to all the three groups of Member States are an increase in renewable energy production and the development of organic farming, as the indicators have shown an upward trend during the period analysed ( 47 ). The present research found that X 7 and X 14 were problematic indicators for most EU Member States and for the EU as a whole: in 2018, X 7 was a weakness for 19 Member States and X 14 for 20 Member States, while in 2022 X 7 for 14 Member States and X 14 for 19 Member States (Table 5 ). The present research also found that, although positive progress has been made on the indicators, they were still not sufficient to achieve the goals set by the European Green Deal. Other researchers, e.g., Nowak et al. (2019), while examining the level of sustainability of agriculture in the EU, also concluded that the agricultural sustainability index varied significantly between the Member States, which was mainly determined by the diverse development levels of agriculture, the different production intensities, and the associated environmental impacts ( 55 ). Kasztelan (2021) pointed out that a decrease in the level of the green economy in EU Member States was mainly driven by low performance in energy efficiency, the social sphere, CO₂ productivity and resource productivity ( 37 ). The highest levels of green economy were found in Denmark, Austria, Sweden, France, and the Netherlands - i.e., the 'old' EU Member States. According to Kasztelan (2021), a low share of organic areas is a challenge for several EU Member States on the way to developing a green economy, highlighting several EU Member States: Belgium, Bulgaria, Croatia, Cyprus, Denmark, France, Germany, Greece, Hungary, Ireland, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden ( 37 ). The analysis performed by the present research also largely confirmed the conclusions, except for Sweden. Because, according to the calculations, the share of organic land in Sweden was an advantage of the green competitiveness of its agriculture in 2018, as evidenced by the normalized value of the indicator at 0.8399. Eurostat data show that in 2018, 20.29% of the total agricultural area in Sweden was organically managed (compared with the EU average of 8%); in 2022, this figure decreased slightly to 19.94%, while the EU average rose to 11% ( 25 ). The results of this research study for 2022 indicate the need for improvements, yet the still low share of organic farming was a significant challenge in Belgium, Bulgaria, Croatia, Cyprus, France, Germany, Hungary, Ireland, Lithuania, Luxembourg, Malta, the Netherlands, Poland, and Romania. Kasztelan et al. (2019), examining the green growth of agriculture in the EU, concluded that there was a very low general level of "greening" of agriculture in the Member States, and the situation varied significantly between the Member States ( 39 ). Although the research study focused specifically on agriculture (and one of the groups of indicators monitored the impacts of agriculture on natural resources and environmental quality), none of the analysed indicators had a direct overlap with the indicators used by the present research. According to Kasztelan et al. (2019), high levels of green growth in agriculture were characteristic of Poland, Denmark, Hungary, Bulgaria, and Slovakia, while low levels were characteristic of Malta, Slovenia, and Cyprus ( 39 ). Kasztelan & Nowak (2020) concluded that the level of green performance of agriculture in the 20 EU Member States analysed was generally very low, as evidenced by the average value of the synthetic index of 0.3069 ( 38 ). Their research study identified seven main problems, of which three should be particularly highlighted in the context of the present research: ( 1 ) the low share of renewable energy in agriculture (0.3059), ( 2 ) the small area under organic farming (0.3081) and ( 3 ) the high share of ammonia (NH₃) emissions from the agricultural sector. The indicators selected by the present research (X 7 , X 12 , X 13 , X 14 ) were highlighted as important problem areas at the EU level. Kasztelan & Nowak (2020) used the average value for the reference years 2008–2017 in their calculations ( 38 ), whereas the calculation results of the present research indicate the situation in 2018 and 2022 and demonstrate that the situation has worsened over a five-year period for the problematic indicator X 12 (share of agriculture in total NH 3 emissions), while there was a slight improvement in indicators X 7 , X 13 and X 14 . A decrease in the value of X 12 could indicate an increase in the intensity of livestock production, insufficiently efficient manure management or excessive use of mineral fertilizers, especially nitrogen-containing fertilizers as well as warmer climatic conditions in recent years. A research study by Kasztelan & Nowak (2020) found that the agricultural sector in the EU, on the one hand, was characterized by low investment in renewable energy production, which negatively affected the Agri-Environmental Index. On the other hand, many of the Member States analysed had low levels of final energy consumption, which improved the green performance of agriculture ( 38 ). The results of the present research also confirmed this observation, as indicator X 15 (final energy consumption) showed high normalised values for most of the EU Member States and was one of the most significant strengths for the green competitiveness of agriculture. However, particular attention should be paid to Malta, for which the normalised value of this indicator was very low in 2022 (0.0298) compared with 0.6609 in 2018, as well as to the Netherlands, with the value being 0 for both years. According to calculations by Kasztelan & Nowak (2020), Portugal stood out with the highest level of green performance of agriculture among the 20 EU Member States analysed, while in Belgium it was the lowest. Relatively high performance was also observed in Austria and Greece, but low in Hungary and Lithuania ( 38 ). The authors of the present research agree with Nowak & Kasztelan (2022) that one of the most important future challenges for EU Member States is to achieve a balance between economic and environmental objectives in agricultural production ( 53 ). To achieve this, targeted measures are needed at the EU level to contribute to an increase in the role of agriculture in the production of renewable energy, which is also in line with the findings of the present research. Conclusions Using 15 environmental indicators aligned with the targets set by the European Green Deal implementation documents, the research conducted on the green competitiveness of agriculture in the EU Member States revealed that there was a significant dispersion between the agricultural environment indicator values, with coefficients of variation ranging from 5.52% to almost 200%. The highest dispersion was found for emissions and energy consumption, while the lowest was found for indicators expressed in relative units and indexes (organic farming and pesticide use). The value of the competitiveness index (0.4749), which was just below the 0.5 threshold, indicated the average level of green competitiveness of agriculture in the EU in 2022, which slightly decreased compared with 2018, thereby confirming hypothesis H1 that the overall level of green competitiveness of agriculture in the EU was average. As the level of competitiveness has decreased slightly (-0.0037), hypothesis H2 – the green competitiveness of agriculture in the EU tended to increase was rejected. Although the value of the average green competitiveness index of agriculture has not changed significantly, the standard deviation of the index and the relative standard deviation have decreased slightly, indicating a stable level of green competitiveness and a more even level among the Member States. The difference between the highest and lowest index values in 2018 and 2022 has decreased, which also indicates a decrease in the gap between the Member States. Consequently, hypothesis H3 assuming significant differences between the Member States was rejected. In 2022, the highest level of green competitiveness of agriculture was achieved by Greece, Slovakia, and the Czech Republic (Group I). A moderately high level of competitiveness (Group II) was found in 15 EU Member States, while a moderately low level (Group III) was found in 7 Member States. The expansion of Groups II and III indicates that many Member States are moving away from the lowest competitive group (IV), where only two Member States were classified in 2022: Malta and Cyprus. Positive trends were observed in the Netherlands and Ireland, where the level of competitiveness has increased significantly, and similar trends have been observed in France, Italy, Portugal, and Slovenia, where the level of green competitiveness of agriculture has increased from medium low to medium high. By contrast, four Member States – Finland, Hungary, Luxembourg, and Spain – reported a decrease in the level of competitiveness, moving from medium high to medium low. The data analysed for 2022 revealed different trends in the performance of EU Member States in the green competitiveness of agriculture. Of the 27 Member States, only 9 improved their positions in the ranking, 14 experienced a decrease, and 4 retained their previous positions. The research results also show that hypothesis H2 must be rejected if viewed through the prism of the EU Member States. The most notable progress was found in France (+ 16 places), Denmark (+ 11), Portugal and Lithuania (+ 9), as well as Ireland (+ 8), while the most significant falls were recorded in Finland and Sweden (-10), as well as Austria and Luxembourg (-7). Of the total indicators included in the present research, 67% (10 out of 15) had average standardised values above the threshold of 0.5000, indicating relatively good performance in the EU in the respective areas. However, five indicators with low average standardised values (below 0.4000) revealed the most significant problems at the EU and national levels, which require action by the Member States to improve the situation in the future: a low share of UAA under organic farming, a low share of high-diversity landscape features on agricultural land, a high share of NH₃ emissions from agriculture, a negligible amount of renewable energy from agriculture and a low contribution of agriculture to the production of renewable energy. Abbreviations AT – Austria BE – Belgium BG – Bulgaria CO2 – Carbon dioxide EN – Cyprus CZ – Czech Republic D – Destimulants DE – Germany DK – Denmark EC – European Commission EE – Estonia EEA – European Environment Agency EL – Greece EU – Spain et al. – and others EU – European Union Eurostat – European Commission database F2F strategy – EU Farm to Fork Strategy FAOSTAT – Food and Agriculture Organization database FI – Finland FR – France G – Gram GCIA – Green Competitiveness Index of Agriculture H – Hypothesis HR – Croatia HRI 1 – Harmonised Risk Indicator 1 HE – Hungary IE – Ireland IT – Italy kg/ha – Kilograms per hectare LT – Lithuania LU – Luxembourg LV – Latvia Max – Maximum Me – Median mg/l – Milligrams per litre Who – Minimum MT – Malta NH 3 – Nitrogen trihydride NL – The Netherlands PL – Poland PT – Portugal RO – Romania S – Stimulant If – Standard deviation IF – Sweden SEG – Greenhouse Gases YES – Slovenia SK – Slovakia UAA – Utilised agricultural area % – Percent Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and material Muska A, Pilvere I, Nipers A (2025) Datasets for Evaluation of the Agricultural Green Competitiveness in the European Union. DataverseLV, V1. https://doi.org/10.71782/DATA/ONYMFM Competing interests The authors declare that they have no competing interests. Funding The research was promoted with the support of the Ministry of Agriculture of the Republic of Latvia and the Latvian Science Council national research programme "Research and Sustainable Use of Local Resources for the Development of Latvia" for 2023-2025, scientific project No. VPP-ZM-VRIIILA-2024/1-0002 Science-based Solutions for a Sustainable Food System to Achieve the Goals of the European Green Deal (GreenAgroRes). Authors' contributions Conceptualization, A.M.; methodology, A.M.; software, A.M.; validation, I.P. and A.N.; formal analysis, A.M.; investigation, A.M. and I.P.; resources, A.N.; data curation, A.M.; writing – original draft preparation, A.M. and I.P.; writing – review and editing, A.M.; I.P. and A.N.; visualization, A.M.; supervision, A.N.; project administration, A.N.; funding acquisition, A.N. All authors have read and agreed to the published version of the manuscript. Acknowledgements Not applicable. References Ahmed EM, Elfaki KE (2023) Green Technological Progress Implications on Long-Run Sustainable Economic Growth. Journal of the Knowledge Economy, 15(2), 6860. https://doi.org/10.1007/s13132-023-01268-y Arabska E (2021) From Farm to Fork: Human Health and Well-Being Through Sustainable Agri-Food Systems. 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Agriculture, 11(3), 204. https://doi.org/10.3390/agriculture11030204 Shah F, Wu W (2019) Soil and Crop Management Strategies to Ensure Higher Crop Productivity within Sustainable Environments. Sustainability, 11(5), 1485. https://doi.org/10.3390/su11051485 Shen J, Zhu Q, Jiao X, Ying H, Wang H, Wen X, Xu W, Li T, Cong W, Liu X, Hou Y, Cui Z, Oenema O, Davies WJ, Zhang F (2020) Agriculture Green Development: a model for China and the world. Front. Agr. Sci. Eng., 7(1): 5‒13 https://doi.org/10.15302/J-FASE-2019300 Soares PR, Galhano C, Gabriel R (2023) Alternative methods to synthetic chemical control of Cynodon dactylon (L.) Pers. A systematic review. Agronomy for Sustainable Development, 43(4). https://doi.org/10.1007/s13593-023-00904-w Sölvell Ö (2015) The Competitive Advantage of Nations 25 years – opening up new perspectives on competitiveness. Competitiveness Review An International Business Journal Incorporating Journal of Global Competitiveness, 25(5), 471. https://doi.org/10.1108/cr-07-2015-0068 Sompolska-Rzechuła A (2021) Selection of the optimal way of linear ordering of objects: case of sustainable development in EU countries. Statistika , 101 (1), 24 – 36. https://doi.org/10.15611/pn.2020.7.09 Srisruthi S, Swarna N, Ros GMS, Elizabeth E ( 2016) Sustainable agriculture using eco-friendly and energy efficient sensor technology," IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) , Bangalore, India, 2016, pp. 1442-1446. https://doi.org/10.1109/RTEICT.2016.7808070 Stanciu S, Zlati ML, Antohi VM, Bichescu CI (2019) The Development Analysis of the Romanian Traditional Product Market Based on the Performance Model for Sustainable Economic Development. Sustainability, 11(4), 1123. https://doi.org/10.3390/su11041123 Tilman D (1998) The greening of the green revolution. Nature, 396(6708), 211. https://doi.org/10.1038/24254 Trigo A, Marta‐Costa A, Fragoso R (2021) Principles of Sustainable Agriculture: Defining Standardized Reference Points. Sustainability, 13(8), 4086. https://doi.org/10.3390/su13084086 Tyczewska A, Twardowski T, Woźniak E (2023) Agricultural biotechnology for sustainable food security. Trends in Biotechnology, 41(3), 331. https://doi.org/10.1016/j.tibtech.2022.12.013 Udeigwe TK, Teboh JM, Eze PN, Stietiya MH, Kumar V, Hendrix JL, Mascagni H J, Teng Y, Kandakji T (2015) Implications of leading crop production practices on environmental quality and human health. Journal of Environmental Management, 151, 267. https://doi.org/10.1016/j.jenvman.2014.11.024 Vicente-Ramos W, Reymundo KGC, Pari LJE, Rudas NMN, Rodríguez PBV (2020) The effect of good corporate governance on banking profitability. Management Science Letters, 2045. https://doi.org/10.5267/j.msl.2020.2.007 Vieri S (2012) Common agricultural policy (CAP) and measures for environment protection and conservation: contrasts, balances and new methods of development for the future. International Journal of Environment and Health, 6(1), 48. https://doi.org/10.1504/ijenvh.2012.046856 Xu H, Mei Q, Shahzad F, Liu S, Long X, Zhang J (2020) Untangling the Impact of Green Finance on the Enterprise Green Performance: A Meta-Analytic Approach. Sustainability, 12(21), 9085. https://doi.org/10.3390/su12219085 Zhang J. van der Heijden MGA, Zhang F, Bender F (2020) Soil biodiversity and crop versification are vital components of healthy soils and agricultural sustainability. Front. Agr. Sci. Eng., 7(3): 236‒242 https://doi.org/10.15302/J-FASE-2020336 Tables Tables 1-5 are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6752700","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471252216,"identity":"876a6420-9e00-4bf6-9ae0-73018523b48a","order_by":0,"name":"Aina Muska","email":"","orcid":"","institution":"Latvia University of Life Sciences and Technologies","correspondingAuthor":false,"prefix":"","firstName":"Aina","middleName":"","lastName":"Muska","suffix":""},{"id":471252220,"identity":"08170f1c-9058-440c-a2fe-ea1f0d5bf169","order_by":1,"name":"Irina Pilvere","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACNgbGBhDNwwfmVlgkAEnGA0RpYQNzz0gk8AApvFqQ9IKMbyNCC5/04bYHPxjuyLBJJB/78HGeRJ69RALDYR58hvMlthv2MDzjYZNIS545c5tEMQ9BLTxAx/AA1bDxnDFm5t0mkdgD1HJwBgEtkn/AWs5/Zv47h0gt0mBb2HuYmRkbIFoOfCCkRcYA6Bf2NmPGnmNAv5x52IBXi3wP+zPJNxV37PmZmR8z/KixyWNvTz74IAGPFggwOIDMg0QuIXCAoIpRMApGwSgYwQAADddCGaUl74UAAAAASUVORK5CYII=","orcid":"","institution":"Latvia University of Life Sciences and Technologies","correspondingAuthor":true,"prefix":"","firstName":"Irina","middleName":"","lastName":"Pilvere","suffix":""},{"id":471252221,"identity":"958ef2a1-0d01-47ae-8c92-d88e320c23fb","order_by":2,"name":"Aleksejs Nipers","email":"","orcid":"","institution":"Latvia University of Life Sciences and Technologies","correspondingAuthor":false,"prefix":"","firstName":"Aleksejs","middleName":"","lastName":"Nipers","suffix":""}],"badges":[],"createdAt":"2025-05-26 16:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6752700/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6752700/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12302-025-01211-9","type":"published","date":"2025-12-01T15:58:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84765212,"identity":"5eec72f0-d836-49c1-bef1-bfabb0de7ed6","added_by":"auto","created_at":"2025-06-17 07:02:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138722,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig.2.\u003c/strong\u003e Main objectives and EU-level quantitative targets relevant to agriculture selected for the research. Source: authors’ construction based on the European Commission (17; 16; 18; 19; 21; 24).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/092b4906011c439eafd9d8ee.png"},{"id":84766269,"identity":"e7351b71-4dde-4f28-a5ba-0503a5499cd9","added_by":"auto","created_at":"2025-06-17 07:10:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12342,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig.3. \u003c/strong\u003eIndicator selection stages based on the goals of the European Green Deal. Source: authors’ construction.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/37e7dd282315fc8010c565d5.png"},{"id":84765211,"identity":"4e8bb451-0dd3-4e39-adb7-03dd38243094","added_by":"auto","created_at":"2025-06-17 07:02:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":15535,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig.4. \u003c/strong\u003eClassification of EU Member States based on the green competitiveness index of agriculture. Source: authors’ construction based on \u0026nbsp;(53).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/1edd86e236de6c5976ff1cec.png"},{"id":84766270,"identity":"1b0cb6c8-93cb-432c-8bba-6038ab3e8383","added_by":"auto","created_at":"2025-06-17 07:10:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48714,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig.5. \u003c/strong\u003eLinear hierarchy of the EU Member States in descending order based on the green competitiveness index of agriculture in 2018 and 2022. Source: authors' calculations.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/5aaeac31ece2fd3a389cdd2e.png"},{"id":84765218,"identity":"42f27113-06d2-421d-bf14-783bff1f15aa","added_by":"auto","created_at":"2025-06-17 07:02:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":15434,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig.6. \u003c/strong\u003eFrequency of the parameters used by the present research in other studies. Source: authors’ construction.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/eda9980fa92d4e2522c99d0a.png"},{"id":97724116,"identity":"8fc1ed3f-4fc1-4627-8f57-8ae12fd4438f","added_by":"auto","created_at":"2025-12-08 16:12:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":882963,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/6bc6c373-7390-4dfc-af61-1e3841d50cd3.pdf"},{"id":84765209,"identity":"f79eda13-48bf-47ee-9af0-23b93b69417b","added_by":"auto","created_at":"2025-06-17 07:02:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":43259,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6752700/v1/0aaf0e21a8297e508caf6e97.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of the Agricultural Green Competitiveness in the European Union","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the twenty-first century, the need for sustainable agriculture arises from a confluence of environmental, economic, and social factors, which requires a paradigm shift in the management of agricultural systems and food production. Scientific projections show that conventional agricultural practices are unsustainable, leading to various harmful consequences, including groundwater pollution, greenhouse gas emissions, biodiversity loss and aquatic ecosystem eutrophication (77). As the global population continues to grow exponentially, the need for innovative and sustainable agricultural solutions tends to increase (70). The concept of sustainable agriculture, while it shares common features with green agriculture, is a broader area that covers not only environmental considerations but also economic viability and social equity (69; 75). Sustainable agriculture aims to meet the needs of the present without compromising the ability of future generations to meet their own needs by advocating practices that are environmentally friendly, economically feasible, and socially fair (12). Therefore, the implementation of environmentally and climate-friendly agricultural practices has contributed to the emergence of the term green agriculture. It is a paradigm for reducing the negative impacts of agriculture on the environment while ensuring the sustainability of this sector. Although the exact origins of green agriculture are difficult to identify, its philosophical foundations could be traced back to the early environmental movements of the 20\u003csup\u003eth\u003c/sup\u003e century, which raised concerns about the harmful effects of conventional agriculture on ecosystems and human health (30). Green agriculture involves a holistic approach that integrates environmental principles into agricultural systems, thereby seeking to align agricultural production with environmental protection (50) and supply food for the planet\u0026apos;s population by reducing the negative environmental impacts of agriculture, and is perceived as part of a broader global transition to a sustainable low-carbon economy (56). This approach is in stark contrast to the conventional agricultural pattern, with the farmers prioritising higher yields and productivity through the intensive use of both mineral fertilizers and plant protection products, which usually affect environmental quality, human health, and biodiversity (12). Green agriculture offers viable solutions by integrating environmental principles into agricultural practices, reducing dependence on synthetic resources, and contributing to ecosystem services. The introduction of green agricultural practices is an essential element to ensure food security for future generations, as the environmental impacts of conventional agriculture are significant, thus making it one of the main contributors to global environmental degradation, which disturbs the balance and poses a risk to human health (79). For example, excessive use of nitrogen fertilizers leads to the release of nitric oxide, whose global warming potential far exceeds the global warming potential of carbon dioxide (4). In addition, runoff of excess nutrients from fields contributes to the eutrophication of aquatic ecosystems, thereby resulting in algal blooms, a lack of oxygen and a decrease in aquatic biodiversity (76). The widespread use of conventional intensive agriculture has caused a global environmental crisis and leads to negative climate changes (44). \u0026nbsp;The development of green agriculture urgently needs to be implemented as part of an integrated strategy for sustainable land use and food security to reduce the environmental impacts of agriculture and achieve the Sustainable Development Goals (67). Koohafkan et al. (2011) propose a set of 10 factors to define the green agricultural system and ensure enough access to food and ecosystem services, while reducing the negative impacts of climate change, the amount of fossil energy consumed for production and environmental degradation (42). Shen et al. (2020) propose the concept of green agriculture development as a model for transforming Chinese agriculture, thereby fostering the transformation of crop and livestock production and food production systems to achieve high environmental standards and food quality, high resource efficiency and low environmental impacts (70). The role of green technologies for the development of sustainable agriculture is important, as they can help to solve the agricultural, socio-economic, and environmental problems posed using chemicals in conventional agriculture. Several authors believe that various green technologies can help in developing green agriculture, e.g. Soares et al. (2023) refer to organic farming, integrated pest control systems, biogas, biofuel, wind energy, as well as the use of information and communication technologies (71). Zhnag et al. (2020) point out that soil biodiversity and crop diversification are essential for sustainable and environmentally friendly agriculture (83). Srisruthi et al. (2016) emphasize the need for environmentally friendly sensor technologies that contribute to sustainable agriculture by effectively monitoring and controlling processes and resources such as water, fertilizers, and energy (74). Lin \u0026amp; Li (2023) and Dong et al. (2025) argue that the development of green agriculture will be driven by its digitalization (46; 11). It could be concluded that scientists from various countries refer to different problems concerning the development of green agriculture, yet their common goal is to solve global food production problems and foster sustainable development around the world.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThat is why the European Green Deal also represents a paradigm shift in the common approach of the EU and its Member States to environmental sustainability. As a policy document, the European Green Deal has a decisive impact on the progress of agriculture towards climate neutrality and environmental sustainability (33). To implement the European Green Deal, the F2F was developed, which aims to create a fair, healthy, and environmentally friendly agri-food production system in the EU (2). The F2F strategy aims to revolutionize not only the way food is produced, processed, and supplied but also to change consumption habits by setting ambitious goals to reduce the environmental impacts of agriculture (78). The European Green Deal identifies the need to shift to green agriculture, assess conventional farming techniques already in place and move towards more environmentally friendly solutions (63). The sustainability of the agri-food system has become a central item on the agenda, thus contributing to the adoption of various documents by the EU institutions as well as Member State governments, which are aimed at implementing the European Green Deal and improving sustainability throughout the food supply chain, from production to consumption (64). Meeting the requirements set by the documents in the EU and its Member States is essential for the development of green agriculture (3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs a world leader in environmental policy and sustainable development, the EU recognises the critical role of agriculture in shaping the environmental, economic, and social wellbeing of its Member States, identifying the need for a transition to greener and environmentally friendly agricultural practices (64). This transition is not only an environmental imperative but also an economic opportunity to foster innovations, create new products and services and improve the resilience of the agricultural sector to climate change and other environmental challenges (78). Green agriculture involves a variety of areas, aiming to reduce the negative environmental impacts of agriculture while maintaining or even increasing productivity (59). Green agriculture also contributes to reducing greenhouse gas emissions, maintaining water resources, protecting biodiversity, and improving soil health, thereby ensuring the long-term sustainability of agricultural production (81). The development of green agriculture is also in line with EU commitments to achieve the United Nations Sustainable Development Goals, in particular food security, climate action and environmental protection (2). Therefore, assessing the green competitiveness of agriculture, which is a multifaceted concept and goes beyond the productivity and profitability of conventional agriculture, including environmental sustainability, social responsibility, and economic viability, has come to the attention of scientists. It indicates the ability of agricultural enterprises, including individual farms as well as the entire agriculture sector, to efficiently produce and supply agricultural products while reducing negative environmental impacts, maintaining natural resources, and contributing to public prosperity (1). At its core, the green competitiveness of agriculture is about achieving a balance between agricultural production and preserving the environment, thereby recognizing that the long-term sustainability of agriculture depends on the economic viability of the farm, the health and resilience of the natural environment (77). Environmental performance is critical with a focus on reducing greenhouse gas emissions, protecting biodiversity, improving soil health, and reducing water pollution through practices such as carbon sequestration, habitat restoration, and nutrient management planning (48). An analysis of various indicators should allow policymakers, farmers, businesses, and civil society to better understand the current circumstances, identify trends, set targets, monitor progress, and compare performance between regions and countries (62).\u003cstrong\u003e\u0026nbsp;Therefore,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe present research\u003c/strong\u003e \u003cstrong\u003e\u003cem\u003eaims\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eto assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators.\u003c/p\u003e\n\u003cp\u003eThe research put forward three hypotheses (H)\u003cstrong\u003e\u003cem\u003e:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH1: The competitiveness level of green agriculture in the EU is average.\u003c/p\u003e\n\u003cp\u003eH2: The green competitiveness of agriculture in the EU tends to increase.\u003c/p\u003e\n\u003cp\u003eH3: There are significant differences between EU Member States in the level of green competitiveness of agriculture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNovelties of the research\u003c/em\u003e\u003c/strong\u003e: (1) a synthetic index was designed to assess the level of green competitiveness of agriculture regarding the goals of the European Green Deal; (2) unique indicators showing original characteristics resulting from the targets of the strategies underlying the European Green Deal were identified; (3) five indicators that have not been used to date in other competitiveness assessments were used by the research. The research included only indicators showing the environmental impacts of agriculture, as opposed to other research studies employing environmental indicators as only part of the set of indicators.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBackground: The concept of green competitiveness of agriculture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompetitiveness is a multifaceted and dynamic concept that has attracted considerable attention in various scientific disciplines, including economics, management, political science, and sociology, mainly because it serves as a crucial indicator of success and sustainability for individuals, organizations, and countries in an increasingly interconnected and competitive world (51; 65). The concept of competitiveness has been the subject of scientific research in manufacturing and related industries since the early eighties and nineties of the 20\u003csup\u003eth\u003c/sup\u003e century (61; 60; 8;\u0026nbsp;49). Competitiveness\u0026nbsp;often refers to the ability to compete and develop effectively in a particular market or environment, facing a range of factors (28;\u0026nbsp;80). Debates on the national competitiveness of countries have also revealed various misunderstandings (43), e.g., that the success of a country occurs at the expense of others, ignoring the potential for mutually beneficial trade and cooperation (72). The competitiveness of a country is the ability to foster sustainable economic growth, increase the quality of life and attract and retain companies and talent in an increasingly interconnected and competitive global context. \u0026nbsp; The ability of a country to compete effectively is not only a matter of economic prosperity but also an important characteristic of its long-term viability, social welfare, and overall state of development in the global arena (41). It is the nation\u0026apos;s ability to create an environment where businesses can thrive, innovations can develop, and individuals can fully implement their potential (66). In the 21\u003csup\u003est\u003c/sup\u003e century, the problem of the competitiveness of a national environment has become topical. It can cover various levels, from individual companies to national economies, and requires a joint effort by stakeholders from various sectors to foster interactions between environmental regulations, corporate strategies and the economic and social development of a country or region (14). It recognises that environmental protection and economic competitiveness are not mutually exclusive but are strategically aligned to contribute to sustainable development (57). Green competitiveness is the ability of a country or organization to maintain or improve its economic position while reducing its environmental impacts and facilitating the transition to an economy producing low or zero greenhouse gas emissions (82). Bruneckienė et al. (2023) have similar opinions, emphasizing that green competitiveness is the ability of a country to maintain or improve economic performance while reducing the burden on the environment and fostering the transition to an economy producing low or zero greenhouse gas (GHG) emissions (5). The concept of green competitiveness of agriculture includes the ability of farms and food businesses to compete effectively in the market while reducing their environmental impacts (9). Porter was the first to begin advocating green competitiveness in 1991, pointing out that the contradiction between the environment and competitiveness will disappear after strict environmental standards encourage business innovation (45). Chygryn \u0026amp; Miskiewicz (2022), analysing scientific research papers from the Scopus database for the period 1991-2021, identified four main stages in the development of the theory of green competitiveness of enterprises: a) the first stage (2004-2012) was associated with the development of processes of greening economic activity; (b) the second stage (2012-2014) \u0026ndash; with greening of economic activity and the development of the green economy; (c) the third stage (2014-2016) \u0026ndash; with a competitiveness analysis of green marketing strategies; d) the fourth stage (since 2016) \u0026ndash; with the direct formation of the concept of green competitiveness (7). The authors of the research believe that a similar development path is also associated with the evolution of the green competitiveness of agriculture in Europe. Until 2018, researchers focused more on the overall competitiveness of agriculture, yet with an increase in climate and environmental problems as well as because agricultural activity has an impact on the environment, there appeared research studies on the competitiveness of sustainable agriculture (55), green growth in agriculture (39;\u0026nbsp;38;\u0026nbsp;37), and only then there were available research studies on the green competitiveness of agriculture in the EU (53).\u003c/p\u003e\n\u003cp\u003eSince there is not much research pertaining to the green competitiveness of agriculture, the definition of green competitiveness of agriculture by Nowak \u0026amp; Kasztelan (2022) is used for the purposes of this research, which means achieving\u003cem\u003e\u0026nbsp;the competitive advantages of the agricultural sector based on the current environmental potential and the ability to manage it sustainably\u0026nbsp;\u003c/em\u003e(53).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNowak \u0026amp; Kasztelan (2022) point out that green competitiveness has not been clearly defined and researched; however, given the challenges faced by agriculture (growing competition for alternative uses for natural resources, the need to preserve biodiversity, tackle food safety and climate change problems) forces researchers to examine the competitiveness of the agricultural sector through the prism of the environment (53). Bruneckienė et al. (2023) have noted that despite the strong commitments that the EU has made through various statements and recommendations to achieve climate neutrality in the common European space, there are large differences between the results achieved by its Member States in various areas \u0026ndash; economic, social, infrastructure, education, research, development and elsewhere \u0026ndash;; however, overall, the EU Member States need to achieve a common goal of becoming competitive and climate neutral (5). This research, therefore, focuses on assessing the green competitiveness of agriculture in the EU Member States by using only environmental indicators.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGovernments can boost green competitiveness by putting in place policies that incentivise green innovation, encourage sustainable practices and set clear environmental standards. Achieving green competitiveness requires a concerted effort by governments, businesses, and individuals to prioritise environmental sustainability and adopt innovative solutions that contribute to economic growth while protecting the planet for future generations. Since the European Green Deal and its underlying strategies are the focus of the present research, these key EU documents are analysed as well. \u0026nbsp;The European Green Deal, adopted in 2019, is a comprehensive document for achieving climate neutrality by 2050 (32). In the field of agriculture, it is subordinated to several strategies adopted in 2020: the F2F strategy (2), the EU Biodiversity Strategy for 2030, which is a comprehensive and ambitious long-term plan for the protection of biodiversity, the restoration of degraded ecosystems and the supply of essential ecosystem services (6). There should also be also highlighted the EU Energy System Integration Strategy (16), whose goal cannot be achieved without the contribution of agriculture to the production of renewable energy. Agriculture also has to contribute to the goal set by the EU Methane Emission Reduction Strategy, aimed at reducing methane emissions through the production of sustainable biogas (17). In 2021, the European Green Deal was enshrined in the European Climate Law, which requires the Member States to meet the targets set and face potential penalties for non-compliance (13). The EU Action Plan: \u0026apos;Towards Zero Pollution for Air, Water and Soil\u0026apos; was also adopted in 2021, specifying an integrated vision for zero pollution for 2050 (21). It follows from the action plan that agriculture will have to contribute to limiting ammonia emissions by reducing nutrient losses, the use of pesticides and the associated risks, as well as the sale of antimicrobials for use in livestock and aquaculture by 50%. It follows from the Sustainable Carbon Cycles that agriculture should ensure the eradication of carbon-based farming practices (24).\u003c/p\u003e"},{"header":"Methodology and Data","content":"\u003cp\u003eThe present research consists \u003cem\u003eof seven consecutive stages\u003c/em\u003e: 1) definition of the research object and subject; 2) selection of indicators based on the goals of the European Green Deal; 3) standardization of indicators by applying the zero-unitization method; 4) calculation of the synthetic index GCIA (Green Competitiveness Index of Agriculture); 5) development of a linear hierarchy and classification of countries; 6) ranking of Member States; 7) discussion and development of conclusions.\u003c/p\u003e \u003cp\u003eAt the beginning, the research identified \u003cem\u003ethe research object and the research subjects to be analysed.\u003c/em\u003e Since the research aims to assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators, it was decided to design a synthetic index \u0026ndash; GCIA \u0026ndash;, which is a composite indicator that combines several individual indicators to quantify the overall green competitiveness of the agricultural sector. Kasztelan (2020) emphasizes that in case it is necessary to analyse several indicators, empirical research usually employs multidimensional comparative analysis methods, the main idea of which is to create a composite indicator called a synthetic index, which provides the grounds for setting a hierarchy of studied objects according to the level of a multi-feature phenomenon (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The synthetic index is based on the TOPSIS method developed by Ching-Lai Hwang and Kwangsun Yoon (1981) (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). To be able to identify a change in the level of competitiveness over a period and assess whether it is improving or deteriorating, it was decided to calculate the synthetic index for 2018 (base year) and 2022, given the availability of the most up-to-date data for all EU Member States.\u003c/p\u003e \u003cp\u003eThe entities to be analysed were 27 EU Member States: Austria (AT), Belgium (BE), Bulgaria (BG), Croatia (HR), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (ES) and Sweden (SE).\u003c/p\u003e \u003cp\u003eAt the second stage, the research selected indicators \u003cem\u003eshowing the green competitiveness of agriculture\u003c/em\u003e to describe the phenomenon examined \u0026ndash; the green competitiveness of agriculture regarding the goals of the European Green Deal. Given that the list of indicators depends on the context of the problem and that the competitiveness of EU Member States needs to be assessed in the context of the goals of the European Green Deal (European Commission, 2019), the authors of the research first identified environmental targets for agriculture resulting from the goals of the European Green Deal, as well as indicators set by its subordinate strategies when creating a set of indicators for a synthetic index (15; 16; 17; 18; 19; 21; 24), see Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the logic of selecting the indicators. Based on a review of scientific literature (55; 47; 36; 37; 38; 53; 35; 54; 19) and the authors' research experience, the research selected 19 indicators that indicate agriculture's green competitiveness and are aligned with the goals of the European Green Deal.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe availability of data was checked for all 27 Member States for all the selected indicators. Four indicators were excluded from the research: \"Common farmland bird index\", \"Soil organic carbon in arable land\", \"Gross nitrogen balance in kilograms per hectare of UAA\", and \"Gross phosphorus balance in kilograms per hectare of UAA\" due to a lack of data. Kasztelan (2020) has also pointed out that researchers at this stage might face two problems: correctly identifying indicators and a lack of available data (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Magrini (2022) also found a similar problem, which led to the abandonment of several indicators that would show the environmental impacts of agriculture (phosphorus and potassium balances) due to a lack of available data (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). At the next stage, a correlation analysis was performed for the 15 indicators selected (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to identify relationships between the variables in the dataset. After the correlation analysis, a decision was made to use all 15 indicators in calculating the green competitiveness index of agriculture.\u003c/p\u003e \u003cp\u003eThe research used European Commission (EC) Agri-food Data Portal (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), Eurostat (European Commission database) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), FAOSTAT (Food and Agriculture Organization database) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), European Environment Agency (EEA) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), European Medicines Agency (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), etc. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe third stage involved standardizing the indicators by employing the zero unitarization method. For the research, all the indicators were divided into stimulants or destimulants. The set of explanatory indicators (i.e., all the indicators that were used to assess competitiveness) included both stimulating indicators (stimulants), which had a positive effect on competitiveness (the higher its value, the better), and destimulating indicators (destimulants), which negatively affected the phenomenon examined (the lower its value, the better) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). For example, from the perspective of green competitiveness, larger areas of organic UAA are desirable, and this indicator is a typical stimulant. At the same time, high GHG emissions are undesirable for the competitiveness of agriculture, so this indicator is a destimulant.\u003c/p\u003e \u003cp\u003eOf the 15 indicators, four were larger-the-better characteristics (stimulants) with a positive influence on the synthetic index (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Eleven indicators were regarded as smaller-the-better characteristics (destimulants), which reduced the green competitiveness index of agriculture.\u003c/p\u003e \u003cp\u003eThe values of the indicators (\u003cem\u003eXj, j\u0026thinsp;=\u0026thinsp;1, 2, .., m\u003c/em\u003e) showing the subjects examined (EU Member States) (\u003cem\u003eOi, i\u0026thinsp;=\u0026thinsp;1, 2, .., n\u003c/em\u003e) could be represented as a matrix of observations in the following form:\u003c/p\u003e \u003cp\u003e \u003cem\u003eX\u003c/em\u003e =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left[\\begin{array}{ccc}{x}_{11}\u0026amp;\\:\\cdots\\:\u0026amp;\\:{x}_{1m}\\\\\\:⋮\u0026amp;\\:\\ddots\\:\u0026amp;\\:⋮\\\\\\:{x}_{n1}\u0026amp;\\:\\cdots\\:\u0026amp;\\:{x}_{nm}\\end{array}\\right]\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eTo ensure comparability of the data and a uniform scale for further analyses, the indicators selected were standardized employing the zero unitarization method, which could be represented as follows (29; 73):\u003c/p\u003e \u003cp\u003e \u003cem\u003ez\u003c/em\u003e \u003csub\u003e \u003cem\u003eij\u003c/em\u003e \u003c/sub\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{x}_{ij}-min{\\left({x}_{{i}_{j}}\\right)}_{i}}{\\text{max}{\\left({x}_{ij}\\right)}_{i}\\:-\\:min\\:{\\left({x}_{{i}_{j}}\\right)}_{i}}\\)\u003c/span\u003e\u003c/span\u003e for stimulants (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eand\u003c/p\u003e \u003cp\u003e \u003cem\u003ez\u003c/em\u003e \u003csub\u003e \u003cem\u003eij\u003c/em\u003e \u003c/sub\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{max}{\\left({x}_{ij}\\right)}_{i}\\:-\\:\\:{x}_{ij}}{\\text{max}{\\left({x}_{ij}\\right)}_{i}\\:-\\:min\\:{\\left({x}_{{i}_{j}}\\right)}_{i}}\\)\u003c/span\u003e\u003c/span\u003e for destimulants (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003e \u003cem\u003ezij\u003c/em\u003e \u0026ndash; normalised value of the \u003cem\u003ej-th\u003c/em\u003e indicator in the i-th country,\u003c/p\u003e \u003cp\u003e \u003cem\u003exij\u003c/em\u003e \u0026ndash; initial value of the \u003cem\u003ej-th\u003c/em\u003e indicator in the i-th country,\u003c/p\u003e \u003cp\u003emin\u003cem\u003e(xij)\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e \u0026ndash; minimum value of \u003cem\u003exij\u003c/em\u003e,\u003c/p\u003e \u003cp\u003emax\u003cem\u003e(xij)\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e \u0026ndash; maximum value of \u003cem\u003exij\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThis method was chosen because it was the only method that corresponded to all seven postulates stated for the procedure for standardizing the value of indicators (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The \u003cem\u003ez\u003c/em\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e values of the indicators were in the range [0; 1], they had no physical units; therefore, they could be counted and compared (34; 40; 37).\u003c/p\u003e \u003cp\u003eThe normalised value of a variable was then used for calculating the median (formula 4) and standard deviation (formula 5) (31; 38). For the median odd number of observations (m\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;15):\u003c/p\u003e \u003cp\u003e \u003cem\u003eMei\u003c/em\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{z}_{\\left(\\frac{m}{2}+1\\right)i}\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eStandard deviation:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:Sei=\\sqrt{\\frac{1}{m}\\sum\\:_{j=1}^{m}{{({z}_{ij}\\:-\\:\\stackrel{-}{z})}^{2}\\:\\:}_{\\:}\\:}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{z}\\)\u003c/span\u003e \u003c/span\u003e \u0026ndash; mean value for a \u003cem\u003ez\u003c/em\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eAt the fourth stage, a synthetic index \u0026ndash; the Green Competitiveness Index of Agricultura (\u003cem\u003eGCIAi\u003c/em\u003e) \u0026ndash; was calculated for each EU Member State based on the median values and standard deviation of normalised variables (formula 6) for 2018 and 2022 (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e):\u003c/p\u003e \u003cp\u003e \u003cem\u003eGCIA\u003c/em\u003e \u003csub\u003e \u003cem\u003ei\u003c/em\u003e \u003c/sub\u003e \u003cem\u003e= Me\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003e(1-Se\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAn index value closer to 1 means a relatively higher level of green competitiveness of agriculture, whereas a relatively lower level of green competitiveness is closer to 0. The synthetic indexes calculated made it possible to perform a comparative analysis of the EU Member States for the years selected and assess the changes that occurred in 2022 compared with the base year.\u003c/p\u003e \u003cp\u003eAt the fifth stage, the research made a linear hierarchy of Member States in descending order, and classified them based on the synthetic index calculated. The Member States were divided into four groups with similar levels of green agricultural competitiveness, using the following key (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e) (Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eBased on the values of the synthetic index, the Member States were ranked (1st \u0026ndash; the highest level of competitiveness, 27th \u0026ndash; the lowest level), and the assigned rankings were compared between both years analysed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFor the 15 indicators, the following statistical parameters were calculated: arithmetic mean, minimum value, maximum value, standard deviation, and coefficient of variation. The values are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe coefficients of variation ranged from 5.52% to almost 200%. The largest differences were observed for the following indicators:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eShare of GHG from agriculture in total net emission (X10);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProduction of renewable energy from agriculture (X13);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFinal energy consumption by the agriculture and forestry sector (X15);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eShare of groundwater monitoring stations with nitrate concentration greater than 50 mg/l (X5);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAgricultural emissions of NH\u003csub\u003e3\u003c/sub\u003e, t per hectare of UAA (X11).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eIn contrast, the smallest differences were found for the following indicators:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eShare of agriculture in total NH\u003csub\u003e3\u003c/sub\u003e emissions (X12);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHRI 1 (X4);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePesticides use per value of agricultural production (\u003cem\u003eX3\u003c/em\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eShare of utilised agricultural area under organic farming (\u003cem\u003eX7\u003c/em\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eBased on the methodology described, the green competitiveness index of agriculture was calculated both for the EU as a whole and for each of the 27 Member States. The average value of GCIA for the EU in 2022 was 0.4749, while in the base year (2018) \u0026ndash; 0.4786, which means that over a five-year period the index has remained almost unchanged, but with a downward trend (decrease of 0.0037). Given the possible range of the index [0\u0026ndash;1], this means that the level of green competitiveness of agriculture in the EU was average. Consequently, hypothesis H1: \u003cem\u003eThe competitiveness level of green agriculture in the EU is average\u003c/em\u003e has been confirmed, whereas hypothesis H2: \u003cem\u003eThe green competitiveness of agriculture in the EU tends to increase\u003c/em\u003e was rejected because the index has remained almost unchanged over five years.\u003c/p\u003e \u003cp\u003eThe standard deviation of the GCIA mean value has decreased from 0.1113 (in 2018) to 0.1036 (in 2022), which means that the data dispersion around the mean has also decreased slightly, yet the differences are small. This might indicate the stable level of green competitiveness, as well as the fact that the differences between the EU-27 have decreased. Over the years analysed, the relative standard deviation (or coefficient of variation) has decreased from 23.2% in 2018 to 22% in 2022, which also indicates a moderate (medium) dispersion, which means that the data are not very dispersed, but also not very concentrated around the mean. If the GCIAi values for a Member State are compared with the highest level of green competitiveness of agriculture in 2018\u0026ndash;0.6166 (SK) and in 2022\u0026ndash;0.6058 (EL) and the lowest level of green competitiveness in 2018\u0026ndash;0.1106 (CY) and in 2022\u0026ndash;0.1402 (MT), it can be found that this difference in 2018 was almost 6 times, but in 2022\u0026ndash;4.3 times. This also indicates that there are differences in the green competitiveness of agriculture between the EU Member States, yet the gap tends to decrease. Consequently, hypothesis H3: \u003cem\u003eThere are significant differences between EU Member States in the level of green competitiveness of agriculture\u003c/em\u003e \u0026ndash; must be rejected.\u003c/p\u003e \u003cp\u003eThe results for the 27 EU Member States are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e, with the colours illustrating the division of the EU Member States into four groups with different levels of green competitiveness of agriculture.\u003c/p\u003e \u003cp\u003eAccording to the results, three Member States (EL, SK, CZ) were classified into Group I, as they reached the highest level of green competitiveness of agriculture in 2022 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In 2022, the highest level of green competitiveness of agriculture was in Greece (GCIAi\u0026thinsp;=\u0026thinsp;0.6058), compared with the level reached in 2018 (GCIAi\u0026thinsp;=\u0026thinsp;0.5980), which has slightly increased (by 1.3%). By contrast, Slovakia, which had the highest level of green competitiveness of agriculture (GCIAi\u0026thinsp;=\u0026thinsp;0.6166) among the 27 EU Member States in 2018, and the Czech Republic showed a decrease by 3% and 1%, respectively, in 2022.\u003c/p\u003e \u003cp\u003eIn 2022, 15 Member States with a moderately high level of green competitiveness could be classified into Group II, while 7 with a moderately low level could be classified into Group III. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the number of Member States with a moderately high (Group II) and moderately low level of green competitiveness (Group III) has increased during the period analysed. At the same time, the changes reduced the number of Member States with a low level of green competitiveness (Group IV). In 2022, the green competitiveness of both Dutch and Irish agriculture increased compared with the base year, by 15% and 35%, respectively, thus placing the Netherlands in Group III and Ireland in Group II in 2022. In 2022, only two EU Member States maintained a low level of green competitiveness (Group IV). Malta had the lowest level of green competitiveness (GCIA\u0026thinsp;=\u0026thinsp;0.1402), which halved (50.6%) compared with 2018 levels (GCIA\u0026thinsp;=\u0026thinsp;0.2837). There was also a low level of green competitiveness of agriculture in Cyprus, where the competitiveness index decreased by 77% over the period analysed.\u003c/p\u003e \u003cp\u003eOver the period analysed, the level of green competitiveness of agriculture has increased in France, Italy, Portugal, and Slovenia from moderately low (2018 \u0026ndash; Group III) to medium (2022 \u0026ndash; Group II). By contrast, in four Member States (FI, HU, LU, EU), the level of green competitiveness of agriculture has decreased from medium high to medium low in 2022 compared with 2018.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the rankings assigned to EU Member States based on the synthetic index. In 2022, only 9 Member States have climbed up, 14 down, while four (CZ, DE, NL, RO) have maintained the status quo. The results also show that hypothesis H2: \u003cem\u003eThe green competitiveness of agriculture in the EU tends to increase\u003c/em\u003e must be rejected if viewed through the prism of the EU Member States.\u003c/p\u003e \u003cp\u003eFrance (+\u0026thinsp;16 places), Denmark (+\u0026thinsp;11), Portugal and Lithuania (+\u0026thinsp;9 each) and Ireland (+\u0026thinsp;8) showed the greatest progress during the period analysed. In contrast, Finland, and Sweden (-10 places each), as well as Austria and Luxembourg (-7 each) experienced the largest decreases.\u003c/p\u003e \u003cp\u003eAn in-depth analysis of the indicators leads to a conclusion that for 10 indicators out of the 15 (or 67%), the average standardised mean values exceed 0.5000. But the other five indicators, with values below 0.5000, highlighted the most significant problems to be solved at the EU level. They were:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA low share of UAA under organic farming (X\u003csub\u003e7\u003c/sub\u003e), which was 0.3574 (2018) and 0.4191 (2022), tended upwards (\"\u0026uarr;\");\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA low share of agricultural land occupied by high-diversity landscape features (X\u003csub\u003e8\u003c/sub\u003e), 0.2504 (2018) and 0.1970 (2022), tended downwards (\"\u0026darr;\");\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA high share of agriculture in total NH\u003csub\u003e3\u003c/sub\u003e emissions (X\u003csub\u003e12\u003c/sub\u003e), 0.4997 and 0.4084, respectively, showed a downward trend (\"\u0026darr;\");\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eProduction of renewable energy from agriculture (X\u003csub\u003e13\u003c/sub\u003e), 0.0932 and 0.1000, respectively, an upward trend (\u0026ldquo;\u0026uarr;\u0026rdquo;);\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA low share of agriculture in the production of renewable energy (X\u003csub\u003e14\u003c/sub\u003e), 0.2510 and 0.2765, respectively, an upward trend (\u0026ldquo;\u0026uarr;\u0026rdquo;).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThese results revealed that two indicators (X\u003csub\u003e8\u003c/sub\u003e, X\u003csub\u003e12\u003c/sub\u003e) have decreased over a five-year period (those showing a trend of \"\u0026darr;\") and three indicators (X\u003csub\u003e7\u003c/sub\u003e, X\u003csub\u003e13\u003c/sub\u003e, X\u003csub\u003e14\u003c/sub\u003e) have slightly increased (those with a trend of \"\u0026uarr;\"). The indicators showed the average level of green competitiveness of agriculture in the EU during the two years analysed; therefore, these areas should be given special attention at both EU and Member State level.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarises indicators for the EU Member States that show specific areas of green competitiveness of agriculture that require future corrective action at the national level. It is assumed that a specific area requires intervention if the standardized value of the indicator for the given country is below 0.4 (zij\u0026thinsp;\u0026lt;\u0026thinsp;0.4000) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The data presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e show that most of the EU Member States faced similar challenges in the green competitiveness of agriculture, both at the national and EU levels.\u003c/p\u003e \u003cp\u003eIf these areas are not given special attention at both the EU and national levels, this will have an impact on achieving the following goals of the European Green Deal and their subordinate targets: 1) area under organic farming (25% of the EU's agricultural land under organic farming by 2030); 2) high diversity landscape features (10% of agricultural area under high-diversity landscape features by 2030); 3) improvement in air quality (a 25% reduction in ecosystems where air pollution endangers biodiversity by 2030); (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) sustainable energy and energy efficiency (building a climate-neutral, sustainable, integrated energy system with renewable electricity, circularity, as well as renewable and low-carbon fuels at its core).\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eFor the discussion, the present research sought similar research studies who used other indicators for analysing agricultural sustainability (47; 55), green growth (37; 39; 38), agricultural competitiveness (35; 52; 54), as well as the green competitiveness of agriculture as opposed to the economic competitiveness of agriculture (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). From the results, it follows that they were dominated by 4 indicators:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eShare of UAA under organic farming (X\u003csub\u003e7\u003c/sub\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eShare of agriculture in renewable energy production (X\u003csub\u003e14\u003c/sub\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNet emissions from agriculture, tonnes of CO\u003csub\u003e2\u003c/sub\u003e equivalent per hectare of UAA (X\u003csub\u003e9\u003c/sub\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFinal energy consumption by agriculture and forestry (X\u003csub\u003e15\u003c/sub\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\u003cp\u003eIt could be concluded that the 5 indicators used by the research are unique: 1) use of pesticides per value of agricultural output, g/international Dollar (X\u003csub\u003e3\u003c/sub\u003e); 2) HRI 1 (X\u003csub\u003e4\u003c/sub\u003e); 3) share of groundwater monitoring stations where the nitrate concentration exceeds 50 mg/l (X\u003csub\u003e5\u003c/sub\u003e); (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) active ingredient of veterinary antimicrobials applicable mainly for food-producing animal species (X\u003csub\u003e6\u003c/sub\u003e); (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) share of high-diversity landscape features (X\u003csub\u003e8\u003c/sub\u003e). The present research employed two indicators: agricultural emissions of NH\u003csub\u003e3\u003c/sub\u003e (tonnes per hectare of UAA) (X\u003csub\u003e11\u003c/sub\u003e) and production of renewable energy from agriculture (tonnes of oil equivalent) (X\u003csub\u003e13\u003c/sub\u003e) are not considered unique, as they have been used by other research studies in relative terms.\u003c/p\u003e \u003cp\u003eAccording to Nowak and Kasztelan (2022), the highest level of green competitiveness of agriculture was found in Austria (Group I) (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). However, the research classified Austria into Group II for the two years analysed. According to the authors' conclusions, the strengths of Austria (Zij \u0026gt;0.9000) in 2018 were low X\u003csub\u003e6\u003c/sub\u003e, high X\u003csub\u003e7\u003c/sub\u003e and low X\u003csub\u003e10\u003c/sub\u003e and X\u003csub\u003e15\u003c/sub\u003e. However, in 2022 the strengths were only high X\u003csub\u003e7\u003c/sub\u003e and low X\u003csub\u003e10\u003c/sub\u003e. According to a research study by Nowak \u0026amp; Kasztelan (2022), low levels of green competitiveness of agriculture (Group IV) were found in the Netherlands, Belgium, Cyprus, Ireland, and Malta. In 2018, the research classified Malta, Cyprus, the Netherlands, and Ireland into Group IV, while Belgium was ranked at the end of Group III with a synthetic index of 0.3679, so the results were similar. Nowak \u0026amp; Kasztelan (2022) have concluded that the high level of green competitiveness of agriculture does not always correlate with the overall economic competitiveness of a country (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Higher economic competitiveness is often associated with greater negative environmental impacts. The largest difference between economic and green competitiveness was found in the Netherlands, which ranked 2nd in terms of economic competitiveness and only 27th in terms of green competitiveness.\u003c/p\u003e \u003cp\u003eJarosz-Angowska et al. (2022) concluded that in 2018, the overall level of competitiveness of the agricultural sector in the EU Member States was very low, as well as significant differences between the Member States (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Compared with 2004, the agricultural competitiveness of EU Member States had declined. In 2018, the highest levels of competitiveness were found in Romania, France, the Netherlands, and Denmark, while the lowest were in Poland, Cyprus, and Finland. The research study indicated that one of the main factors in the decrease in competitiveness was a decrease in the use of fertilizers. The present research identified the X\u003csub\u003e2\u003c/sub\u003e indicator as an area requiring increased attention and corrective action, as its value (Zij\u0026thinsp;\u0026lt;\u0026thinsp;0.4000) was low in Belgium, Cyprus, Ireland, Italy, Malta, and the Netherlands in 2018 and remained low in Cyprus, Malta, and the Netherlands in 2022.\u003c/p\u003e \u003cp\u003eNowak and Kasztelan (2022) found that the highest levels of economic competitiveness of agriculture were in Spain, the Netherlands, France, and Germany (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). A similar opinion was expressed by Jarosz-Angowska et al. (2022), stressing that the high competitiveness of the Netherlands and France was stable and sustainable in the long term, as confirmed by several research studies, regardless of the research methods used (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The research study additionally noted that Denmark, Germany, and Belgium were also the Member States with a high level of competitiveness. Belgium was particularly noteworthy, with a high intensity of use of technology in the agricultural sector, but at the same time it also had a significant negative impact on the environment (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). However, Jarosz-Angowska et al. (2022) concluded that the economic competitiveness of Ireland, Sweden, Finland, and Austria in agriculture was relatively low. The limited land resources of the Member States and the low share of agricultural workers were referred to as the main reasons for this situation (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMagrini (2022) classified them into three groups when assessing the sustainability of agriculture in EU Member States between 2004 and 2018 (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). The first group (AT, FI, FR, HU, IT, LU, PT, SI, SP) included the Member States where partial economic and environmental sustainability, as well as full social sustainability, were achieved. The second group (BG, CY, DE, EL, IE, LV, NL, PL, SE) was characterised by significant progress in sustainability. Both groups shared a weak environmental sustainability objective of reducing greenhouse gas emissions. According to the results of the above research study, in 2018 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) X\u003csub\u003e9\u003c/sub\u003e and X\u003csub\u003e10\u003c/sub\u003e were problematic indicators for the Netherlands (X\u003csub\u003e9\u003c/sub\u003e), as well as Sweden and Latvia (X\u003csub\u003e10\u003c/sub\u003e). In 2022, X\u003csub\u003e9\u003c/sub\u003e and X\u003csub\u003e10\u003c/sub\u003e remained a challenge for the Netherlands and Malta (X\u003csub\u003e9\u003c/sub\u003e), as well as Sweden (X\u003csub\u003e10\u003c/sub\u003e). The third group (BE, CZ, DK, EE, LT, RO, SK) was characterised by full social and environmental sustainability, as well as partial economic sustainability. It should be noted that GHG emissions per hectare in this group were stable; therefore, reducing emissions was not a priority goal, which was also confirmed by the research results. Indicator X\u003csub\u003e9\u003c/sub\u003e was identified as a strength for the Czech Republic, Estonia, Lithuania, Romania, and Slovakia, while Denmark should pay attention to the development of this situation \u0026ndash; the normalized value decreased from 0.4347 (2018) to 0.4146 (2022). If this trend continues and the value decreases below 0.4, X\u003csub\u003e9\u003c/sub\u003e becomes a weak area that requires special attention. Magrini (2022) emphasizes that the strong sustainable objectives common to all the three groups of Member States are an increase in renewable energy production and the development of organic farming, as the indicators have shown an upward trend during the period analysed (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). The present research found that X\u003csub\u003e7\u003c/sub\u003e and X\u003csub\u003e14\u003c/sub\u003e were problematic indicators for most EU Member States and for the EU as a whole: in 2018, X\u003csub\u003e7\u003c/sub\u003e was a weakness for 19 Member States and X\u003csub\u003e14\u003c/sub\u003e for 20 Member States, while in 2022 X\u003csub\u003e7\u003c/sub\u003e for 14 Member States and X\u003csub\u003e14\u003c/sub\u003e for 19 Member States (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The present research also found that, although positive progress has been made on the indicators, they were still not sufficient to achieve the goals set by the European Green Deal.\u003c/p\u003e \u003cp\u003eOther researchers, e.g., Nowak et al. (2019), while examining the level of sustainability of agriculture in the EU, also concluded that the agricultural sustainability index varied significantly between the Member States, which was mainly determined by the diverse development levels of agriculture, the different production intensities, and the associated environmental impacts (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Kasztelan (2021) pointed out that a decrease in the level of the green economy in EU Member States was mainly driven by low performance in energy efficiency, the social sphere, CO₂ productivity and resource productivity (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The highest levels of green economy were found in Denmark, Austria, Sweden, France, and the Netherlands - i.e., the 'old' EU Member States.\u003c/p\u003e \u003cp\u003eAccording to Kasztelan (2021), a low share of organic areas is a challenge for several EU Member States on the way to developing a green economy, highlighting several EU Member States: Belgium, Bulgaria, Croatia, Cyprus, Denmark, France, Germany, Greece, Hungary, Ireland, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The analysis performed by the present research also largely confirmed the conclusions, except for Sweden. Because, according to the calculations, the share of organic land in Sweden was an advantage of the green competitiveness of its agriculture in 2018, as evidenced by the normalized value of the indicator at 0.8399. Eurostat data show that in 2018, 20.29% of the total agricultural area in Sweden was organically managed (compared with the EU average of 8%); in 2022, this figure decreased slightly to 19.94%, while the EU average rose to 11% (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The results of this research study for 2022 indicate the need for improvements, yet the still low share of organic farming was a significant challenge in Belgium, Bulgaria, Croatia, Cyprus, France, Germany, Hungary, Ireland, Lithuania, Luxembourg, Malta, the Netherlands, Poland, and Romania.\u003c/p\u003e \u003cp\u003eKasztelan et al. (2019), examining the green growth of agriculture in the EU, concluded that there was a very low general level of \"greening\" of agriculture in the Member States, and the situation varied significantly between the Member States (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Although the research study focused specifically on agriculture (and one of the groups of indicators monitored the impacts of agriculture on natural resources and environmental quality), none of the analysed indicators had a direct overlap with the indicators used by the present research. According to Kasztelan et al. (2019), high levels of green growth in agriculture were characteristic of Poland, Denmark, Hungary, Bulgaria, and Slovakia, while low levels were characteristic of Malta, Slovenia, and Cyprus (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKasztelan \u0026amp; Nowak (2020) concluded that the level of green performance of agriculture in the 20 EU Member States analysed was generally very low, as evidenced by the average value of the synthetic index of 0.3069 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Their research study identified seven main problems, of which three should be particularly highlighted in the context of the present research: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the low share of renewable energy in agriculture (0.3059), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the small area under organic farming (0.3081) and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) the high share of ammonia (NH₃) emissions from the agricultural sector. The indicators selected by the present research (X\u003csub\u003e7\u003c/sub\u003e, X\u003csub\u003e12\u003c/sub\u003e, X\u003csub\u003e13\u003c/sub\u003e, X\u003csub\u003e14\u003c/sub\u003e) were highlighted as important problem areas at the EU level. Kasztelan \u0026amp; Nowak (2020) used the average value for the reference years 2008\u0026ndash;2017 in their calculations (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), whereas the calculation results of the present research indicate the situation in 2018 and 2022 and demonstrate that the situation has worsened over a five-year period for the problematic indicator X\u003csub\u003e12\u003c/sub\u003e (share of agriculture in total NH\u003csub\u003e3\u003c/sub\u003e emissions), while there was a slight improvement in indicators X\u003csub\u003e7\u003c/sub\u003e, X\u003csub\u003e13\u003c/sub\u003e and X\u003csub\u003e14\u003c/sub\u003e. A decrease in the value of X\u003csub\u003e12\u003c/sub\u003e could indicate an increase in the intensity of livestock production, insufficiently efficient manure management or excessive use of mineral fertilizers, especially nitrogen-containing fertilizers as well as warmer climatic conditions in recent years.\u003c/p\u003e \u003cp\u003eA research study by Kasztelan \u0026amp; Nowak (2020) found that the agricultural sector in the EU, on the one hand, was characterized by low investment in renewable energy production, which negatively affected the Agri-Environmental Index. On the other hand, many of the Member States analysed had low levels of final energy consumption, which improved the green performance of agriculture (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The results of the present research also confirmed this observation, as indicator X\u003csub\u003e15\u003c/sub\u003e (final energy consumption) showed high normalised values for most of the EU Member States and was one of the most significant strengths for the green competitiveness of agriculture. However, particular attention should be paid to Malta, for which the normalised value of this indicator was very low in 2022 (0.0298) compared with 0.6609 in 2018, as well as to the Netherlands, with the value being 0 for both years.\u003c/p\u003e \u003cp\u003eAccording to calculations by Kasztelan \u0026amp; Nowak (2020), Portugal stood out with the highest level of green performance of agriculture among the 20 EU Member States analysed, while in Belgium it was the lowest. Relatively high performance was also observed in Austria and Greece, but low in Hungary and Lithuania (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The authors of the present research agree with Nowak \u0026amp; Kasztelan (2022) that one of the most important future challenges for EU Member States is to achieve a balance between economic and environmental objectives in agricultural production (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). To achieve this, targeted measures are needed at the EU level to contribute to an increase in the role of agriculture in the production of renewable energy, which is also in line with the findings of the present research.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eUsing 15 environmental indicators aligned with the targets set by the European Green Deal implementation documents, the research conducted on the green competitiveness of agriculture in the EU Member States revealed that there was a significant dispersion between the agricultural environment indicator values, with coefficients of variation ranging from 5.52% to almost 200%. The highest dispersion was found for emissions and energy consumption, while the lowest was found for indicators expressed in relative units and indexes (organic farming and pesticide use). The value of the competitiveness index (0.4749), which was just below the 0.5 threshold, indicated the average level of green competitiveness of agriculture in the EU in 2022, which slightly decreased compared with 2018, thereby confirming hypothesis H1 that the overall level of green competitiveness of agriculture in the EU was average. As the level of competitiveness has decreased slightly (-0.0037), hypothesis H2 \u0026ndash; the green competitiveness of agriculture in the EU tended to increase was rejected.\u003c/p\u003e \u003cp\u003eAlthough the value of the average green competitiveness index of agriculture has not changed significantly, the standard deviation of the index and the relative standard deviation have decreased slightly, indicating a stable level of green competitiveness and a more even level among the Member States. The difference between the highest and lowest index values in 2018 and 2022 has decreased, which also indicates a decrease in the gap between the Member States. Consequently, hypothesis H3 assuming significant differences between the Member States was rejected.\u003c/p\u003e \u003cp\u003eIn 2022, the highest level of green competitiveness of agriculture was achieved by Greece, Slovakia, and the Czech Republic (Group I). A moderately high level of competitiveness (Group II) was found in 15 EU Member States, while a moderately low level (Group III) was found in 7 Member States. The expansion of Groups II and III indicates that many Member States are moving away from the lowest competitive group (IV), where only two Member States were classified in 2022: Malta and Cyprus. Positive trends were observed in the Netherlands and Ireland, where the level of competitiveness has increased significantly, and similar trends have been observed in France, Italy, Portugal, and Slovenia, where the level of green competitiveness of agriculture has increased from medium low to medium high. By contrast, four Member States \u0026ndash; Finland, Hungary, Luxembourg, and Spain \u0026ndash; reported a decrease in the level of competitiveness, moving from medium high to medium low.\u003c/p\u003e \u003cp\u003eThe data analysed for 2022 revealed different trends in the performance of EU Member States in the green competitiveness of agriculture. Of the 27 Member States, only 9 improved their positions in the ranking, 14 experienced a decrease, and 4 retained their previous positions. The research results also show that hypothesis H2 must be rejected if viewed through the prism of the EU Member States. The most notable progress was found in France (+\u0026thinsp;16 places), Denmark (+\u0026thinsp;11), Portugal and Lithuania (+\u0026thinsp;9), as well as Ireland (+\u0026thinsp;8), while the most significant falls were recorded in Finland and Sweden (-10), as well as Austria and Luxembourg (-7).\u003c/p\u003e \u003cp\u003eOf the total indicators included in the present research, 67% (10 out of 15) had average standardised values above the threshold of 0.5000, indicating relatively good performance in the EU in the respective areas. However, five indicators with low average standardised values (below 0.4000) revealed the most significant problems at the EU and national levels, which require action by the Member States to improve the situation in the future: a low share of UAA under organic farming, a low share of high-diversity landscape features on agricultural land, a high share of NH₃ emissions from agriculture, a negligible amount of renewable energy from agriculture and a low contribution of agriculture to the production of renewable energy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eAT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eAustria \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eBE \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eBelgium\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eBG \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eBulgaria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eCO2\u0026nbsp;\u0026ndash;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eCarbon dioxide\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEN \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eCyprus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eCZ \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eCzech Republic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eD\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eDestimulants\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eDE \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eGermany\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eDK \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eDenmark\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEC \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEuropean Commission\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEE \u0026ndash;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEstonia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEEA \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEuropean Environment Agency\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEL \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eGreece\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEU \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eet al. \u0026ndash; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eand others\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEU \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEuropean Union\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eEurostat \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEuropean Commission database\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eF2F strategy \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eEU Farm to Fork Strategy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eFAOSTAT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eFood and Agriculture Organization database\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eFI \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eFinland\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eFR \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eFrance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eG\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eGram\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eGCIA \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eGreen Competitiveness Index of Agriculture \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eH\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eHypothesis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eHR \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eCroatia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eHRI 1\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eHarmonised Risk Indicator 1 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eHE \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eHungary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eIE \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eIreland\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eIT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eItaly\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003ekg/ha\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eKilograms per hectare\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eLT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eLithuania\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eLU \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eLuxembourg\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eLV \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eLatvia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eMax\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eMaximum\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eMe\u0026nbsp;\u0026ndash;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eMedian\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003emg/l\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eMilligrams per litre\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eWho\u0026nbsp;\u0026ndash;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eMinimum\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eMT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eMalta\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eNitrogen trihydride\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eNL \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eThe Netherlands\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003ePL \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003ePoland\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003ePT \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003ePortugal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eRO \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eRomania\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eS\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eStimulant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eIf\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eStandard deviation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eIF \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eSweden\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eSEG \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eGreenhouse Gases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eYES \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eSlovenia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eSK \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eSlovakia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003eUAA\u0026nbsp;\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003eUtilised agricultural area\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.8065%;\"\u003e\n \u003cp\u003e% \u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81.1935%;\"\u003e\n \u003cp\u003ePercent\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and material\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMuska A, Pilvere I, Nipers A (2025) Datasets for Evaluation of the Agricultural Green Competitiveness in the European Union. DataverseLV, V1. https://doi.org/10.71782/DATA/ONYMFM\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe research was promoted with the support of the Ministry of Agriculture of the Republic of Latvia and the Latvian Science Council national research programme \u0026quot;Research and Sustainable Use of Local Resources for the Development of Latvia\u0026quot; for 2023-2025, scientific project No. VPP-ZM-VRIIILA-2024/1-0002 Science-based Solutions for a Sustainable Food System to Achieve the Goals of the European Green Deal (GreenAgroRes).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, A.M.; methodology, A.M.; software, A.M.; validation, I.P. and A.N.; formal analysis, A.M.; investigation, A.M. and I.P.; resources, A.N.; data curation, A.M.; writing \u0026ndash; original draft preparation, A.M. and I.P.; writing \u0026ndash; review and editing, A.M.; I.P. and A.N.; visualization, A.M.; supervision, A.N.; project administration, A.N.; funding acquisition, A.N. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmed EM, Elfaki KE (2023) Green Technological Progress Implications on Long-Run Sustainable Economic Growth. Journal of the Knowledge Economy, 15(2), 6860. https://doi.org/10.1007/s13132-023-01268-y\u003c/li\u003e\n\u003cli\u003eArabska E (2021) From Farm to Fork: Human Health and Well-Being Through Sustainable Agri-Food Systems. Journal of Life Economics, 8(1), 11. https://doi.org/10.15637/jlecon.8.1.02\u003c/li\u003e\n\u003cli\u003eB\u0026aacute;nhegyi G (2015) Global Challenges and New Approaches in the Common Agricultural Policy 2014 - 2020. 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Sustainability, 12(21), 9085. https://doi.org/10.3390/su12219085\u003c/li\u003e\n\u003cli\u003eZhang J. van der Heijden MGA, Zhang F, Bender F (2020) Soil biodiversity and crop versification are vital components of healthy soils and agricultural sustainability. Front. Agr. Sci. Eng., 7(3): 236‒242 https://doi.org/10.15302/J-FASE-2020336\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1-5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"green competitiveness, agriculture, environmental indicators, synthetic index, EU Member States, European Green Deal","lastPublishedDoi":"10.21203/rs.3.rs-6752700/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6752700/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn the twenty-first century, there is a growing awareness of the role of sustainable agriculture in responding to environmental and socio-economic challenges, as well as the need to provide food for a growing population. Conventional intensive farming techniques often threaten the environment, biodiversity, and public health. Therefore, a possibility is sought to transform agriculture and ensure the green competitiveness thereof, based on the current environmental potential and the capability to manage it sustainably. The European Green Deal and the subordinate strategies set the targets to be achieved by the Member States of the European Union (EU). \u003cem\u003eTherefore, the present research aims\u003c/em\u003e to assess the green competitiveness of agriculture in EU Member States regarding the goals of the European Green Deal based on environmental indicators.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFor the present research, a synthetic index was developed \u0026ndash; the Green Competitiveness Index of Agriculture \u0026ndash;, which combines 15 environmental indicators in line with the targets set for the implementation of the European Green Deal to quantify the overall green competitiveness of the agricultural sector in the EU Member States. After calculating the index for 2018 and 2022, the research created a linear hierarchy and classification of Member States, ranking them accordingly. The overall level of green competitiveness of agriculture in the EU was found to be average. Of the 27 Member States, only 9 improved their position in the ranking, 14 experienced a decline, and 4 maintained their previous position in 2022. Most of the EU Member States face similar challenges in the area of green competitiveness of agriculture, both at the national level and at the EU level, to achieve the goals of the European Green Deal. Achieving the following targets of the European Green Deal might be problematic: area under organic farming, high diversity landscape features, air quality, sustainable energy, and energy efficiency.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe data analysed revealed significant changes in the level of green competitiveness of agriculture across EU Member States. Overall, the results showed that although the level of green competitiveness of agriculture in the EU remained medium and relatively steady in 2022 compared with 2018, the Member States' targets gradually converged as cross-country disparities decreased. The results indicated some convergence and changes in the ranking regarding the level of green competitiveness of agriculture, highlighting both the progress and the backwardness of individual Member States, which need to be considered by policymakers when developing future policies and sectoral development strategies.\u003c/p\u003e","manuscriptTitle":"Evaluation of the Agricultural Green Competitiveness in the European Union","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 07:02:29","doi":"10.21203/rs.3.rs-6752700/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-22T12:03:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-15T19:22:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125873793520653478112961507485872076179","date":"2025-07-14T12:20:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-19T05:09:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212988697725250514292897067669349987091","date":"2025-06-12T14:38:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-12T11:33:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-28T14:01:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-28T14:00:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Sciences Europe","date":"2025-05-26T16:31:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a62aa0cb-fe12-4088-81a3-e93c2b734576","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:07:18+00:00","versionOfRecord":{"articleIdentity":"rs-6752700","link":"https://doi.org/10.1186/s12302-025-01211-9","journal":{"identity":"environmental-sciences-europe","isVorOnly":false,"title":"Environmental Sciences Europe"},"publishedOn":"2025-12-01 15:58:18","publishedOnDateReadable":"December 1st, 2025"},"versionCreatedAt":"2025-06-17 07:02:29","video":"","vorDoi":"10.1186/s12302-025-01211-9","vorDoiUrl":"https://doi.org/10.1186/s12302-025-01211-9","workflowStages":[]},"version":"v1","identity":"rs-6752700","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-6752700","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}