Assessing the Environmental Sustainability of Organic Wine Grape Production with Qualified Designation of Origin in La Rioja, Spain

Academic Editors: Moritz von Cossel, Rocío A. Díaz-Chavez and Bastian Winkler Received: 28 January 2025 Revised: 26 February 2025 Accepted: 27 February 2025 Published: 28 February 2025 Citation: Agraso-Otero, A.; Cancela, J.J.; Vilanova, M.; Ugarte Andreva, J.; Rebolledo-Leiva, R.; González-García, S. Assessing the Environmental Sustainability of Organic Wine Grape Production with Qualified Designation of Origin in La Rioja, Spain. Agriculture 2025,15, 536. https://doi.org/ 10.3390/agriculture15050536 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Assessing the Environmental Sustainability of Organic Wine Grape Production with Qualified Designation of Origin in La Rioja, Spain Adrián Agraso-Otero 1, Javier J. Cancela 2,3 , Mar Vilanova 3,4 , Javier Ugarte Andreva 5, Ricardo Rebolledo-Leiva 6and Sara González-García 1,3,* 1 CRETUS, Department of Chemical Engineering, School of Engineering, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; [email protected] 2GI-1716, Proyectos y Planificación, Departamento Ingeniería Agroforestal, Escola Politécnica Superior de Enxeñaría, Universidade de Santiago de Compostela, Rúa Benigno Ledo s/n, 27002 Lugo, Spain; [email protected] 3CropQuality: Crop Stresses and Their Effects on Quality (USC), Associate Unit of Instituto de Ciencias de la Vid y del Vino (ICVV-CSIC), 27002 Lugo, Spain; mar[email protected] 4Instituto de Ciencias de la Vid y del Vino-ICVV (CSIC, UR, GR) Finca La Grajera, 26007 Logroño, Spain 5Servicio de Investigación Agraria y Sanidad Vegetal, Gobierno de La Rioja, 26071 Logroño, Spain; [email protected] 6 Department of Computing and Industries, Faculty of Engineering Sciences, Universidad Católica del Maule, Av. San Miguel 3605, Talca 3460000, Chile; [email protected] *Correspondence: [email protected] Abstract: Vineyards are significant demanders of fertilisers, pesticides, soil tillage and water. This study assessed the environmental profile of an organic grape production system with La Rioja qualified designation of origin using a cradle-to-gate life cycle assessment (LCA). The ReCiPe method was applied to assess the environmental impacts, while the Available WAter REmaining method was used to estimate the water scarcity. Additionally, the biodiversity loss, a global issue exacerbated by agricultural practices, was evaluated along with an ecosystem service indicator, pollination, to provide a more comprehensive analysis. This study employed two functional units: one kilogram of grapes and one hectare of land. The results revealed that the environmental impacts on global warming were more than ten times lower than those reported in most studies reviewed in the literature, primarily due to the effects of direct land use changes associated with pruning waste management. The total emissions in this category were 99.51 kg CO 2 eq per hectare or 15.31 g CO 2 eq per kilogram of grapes. Agrochemical-related emissions were identified as the environmental hotspot. The water scarcity was estimated at 48.4 litres per kilogram of grapes, mainly attributed to agrochemical dispersion. The biodiversity loss was largely driven by land transformation, with plants being the most impacted taxon. However, a high abundance of pollinators was observed in spring, contributing to improved grape quality and natural pest control. These findings could help highlight the environmental benefits of organic viticulture and the good practices implemented in this pilot. Keywords: biodiversity; non-irrigated; life cycle assessment; water scarcity; pollination; vineyard 1. Introduction Grapes are among the most widely cultivated crops on the planet, covering an estimated 7.2 million hectares globally in 2023. In terms of the global vineyard surface area, Agriculture 2025,15, 536 https://doi.org/10.3390/agriculture15050536 Agriculture 2025,15, 536 2 of 18 Spain covers 945,000 hectares, followed by France, China and Italy [ 1 ]. However, when it comes to wine production, the rankings shift: France tops the list with 48 million hL, followed by Italy with 38.3 million hL and Spain with 28.3 million hL [1]. Grapes are demanding crops in terms of fertilisers and phytosanitary products, as well as soil tillage [ 2 ]. In quantitative terms, grape cultivation for wine production accounts for about 2% of the global GHG emissions from the sector and about 0.3% of the annual worldwide emissions [ 3 ]. One alternative to this is organic agriculture, which focuses on the responsible use of energy, the maintenance of biodiversity and the enhancement of soil fertility using natural substances and processes [ 4 ]. Thus, organic viticulture aims to reduce the use of pesticides and synthetic fertilisers by implementing various practices that promote adequate biodiversity within the production system [5]. Water consumption is another crucial factor in agriculture, as the water demand represents roughly three-quarters of the total freshwater use, with more than half being lost during storage or transport [ 6 ]. The global average water footprint for the viticulture phase has been estimated at approximately 610 L per kilogram of grapes, which is clearly influenced by irrigation [ 7 ]. Practices that could help to minimise water use include drip irrigation, particularly subsurface drip irrigation, which facilitates direct water access to the roots, and fertigation, which supplies nutrients in a soluble form through irrigation [ 8 ]. In agriculture, the use of agrochemicals generates significant environmental impacts, being one of the main causes of contamination of drinking water and watersheds [ 9 ]. In addition, their application negatively impacts soil quality by decreasing the organic matter content, and it also pollutes the air, as some of their ingredients remain in the atmosphere for extended periods, where they decompose under the influence of sunlight, altering their chemical composition [10]. Life cycle assessment (LCA) is a widely recognised tool for assessing resource use and environmental impacts to support the transition towards a sustainable agriculture sector [ 11 – 13 ]. It measures the environmental burdens related to greenhouse gas emissions, acidification and fossil resource demand [ 13 ]. However, LCA still lacks a full understanding of the broader environmental costs and benefits of human activities [ 14 ]. Evaluating ecosystem services (ESs) is crucial for a more holistic view, covering aspects like carbon sequestration and pollination, new issues that have been under-represented in this type of research [ 15 ]. ESs are defined as the broad range of direct, indirect, and intermediate benefits that people derive from ecosystems, considered from a human well-being perspective [ 16 ]. Biodiversity decline is a major issue in agriculture, threatening 24,000 of 28,000 endangered species due to intensive farming practices and increased agrochemical and water use [ 17 ]. Additionally, agriculture drives around 90% of global deforestation [ 18 ]. Pollination is also vital, with 87% of major food crops and 35% of the crop production volume depending on animal pollinators [19]. Rioja wine is one of Spain’s most internationally renowned wines and holds Spain’s oldest designation of origin (DO), established in 1925. In 1991, it became the first qualified designation of origin (DOCa) in Spain, further cementing its prestige and quality [ 20 ]. The DO and DOCa are quality labels that ensure products are always elaborated, processed and prepared in the specific geographical region. However, DOCa is more restrictive in some aspects [ 21 ]. Spain has a total of 70 DOs, of which only two are DOCas: Rioja and Priorato [ 22 ]. La Rioja DOCa allows a maximum planting density of 10,000 vines per hectare of land and a maximum production of 6500 kg of red grapes per hectare and 9000 kg of white grapes per hectare, prioritising product recognition and quality over quantity [ 23 ]. Although grapes are a widely studied crop, both in the agricultural phase and in their subsequent transformation into wine [ 24 , 25 ], La Rioja DOCa stands out as one of the most prestigious wine-producing regions in the world. Therefore, it is crucial to analyse the Agriculture 2025,15, 536 3 of 18 agricultural practices in this region, not only from a productive and economic standpoint but also from an environmental perspective. Consequently, this research analyses not only the impact on typical environmental impact categories linked to agricultural systems, such as the global warming, acidification, or eutrophication, but also the water scarcity level, the biodiversity loss caused by the transformation of habitats for this purpose and the influence of pollination on this crop. Moreover, the fact that this is an organic farming system adds further relevance to this study, considering that only approximately 13% of vineyards in Spain are managed organically, highlighting the potential for expanding sustainable practices in the sector and the importance of understanding their environmental impacts [26]. In this context, the present manuscript aims to evaluate the environmental impacts of an organic red grape cultivation system without irrigation in La Rioja DOCa, as this sector requires a shift towards environmentally friendly practices. It is hoped that the findings of this research can help highlight these practices as benchmarking options to achieve an eco-friendly Spanish wine sector, since it is one of the most important in the world. To do so, a comprehensive environmental assessment has been carried out using the LCA methodology due to its capacity to provide an exhaustive analysis of environmental impacts by examining multiple indicators and considering all the inputs and outputs throughout the entire life cycle of the agricultural system being assessed. 2. Materials and Methods 2.1. Study Area and Evaluated Scenario This study was carried out in a vineyard located in La Rioja Alta subzone, northern Spain (42 ◦ 26 ′ 34.1 ′′ N, 2 ◦ 30 ′ 58.2 ′′ W) (Figure 1), one of the three subzones that are part of this DOCa. The region is characterised by a continental Mediterranean climate with annual rainfall of about 450 mm. The total cultivated area is about 2.6 ha, located in a single plot, and the field is completely flat. The production is about 6.5 t/ha of ‘Tempranillo’ grapes, from which about 4.5 t/ha of wine is produced. It is important to point out that the land is not irrigated, as rainwater is already sufficient for crop growth, using water only to disperse the agrochemicals. In addition, this farm holds an organic production certification, ensuring that the grapes produced meet the highest quality standards while respecting the environment and preserving the soil fertility. This is achieved through the optimal use of natural resources, fertilisation with organic matter, and the application of approved phytosanitary treatments, such as copper and sulphur [ 27 ]. In terms of the agricultural activities, the season begins in February with the pruning of the vines, followed by the shredding of the plant remains, which are left on the ground as organic matter. Subsequently, the soil is fertilised with 700 kg/ha of organic fertiliser and ploughed twice. As the plants develop, unwanted parts such as leaves or damaged bunches are selectively removed to ensure optimal growth. Between May and July, different phytosanitary treatments are applied to protect the crop, including the application of 4 kg/ha of copper and 28 kg/ha of sulphur, culminating in the grape harvest in September. Moreover, 8 t/ha of pruning waste is generated, which is shredded and incorporated into the soil. This primary information was collected through targeted interaction with farmers using specifically designed questionnaires. The practices discussed here are representative, as, despite the data being from the 2023 campaign, the field operations and inputs remain consistent across campaigns and throughout the entire vineyard area. On the other hand, it is important to note that the climatic and soil characteristics in La Rioja can vary across subzones. For this reason, these cultivation practices can be extended to other vineyards after conducting a prior study of such variability, as this study focuses only on the characteristics of this pilot. Agriculture 2025,15, 536 4 of 18 Agriculture 2025, 15, x FOR PEER REVIEW 4 of 19 the data being from the 2023 campaign, the field operations and inputs remain consistent across campaigns and throughout the entire vineyard area. On the other hand, it is important to note that the climatic and soil characteristics in La Rioja can vary across subzones. For this reason, these cultivation practices can be extended to other vineyards after conducting a prior study of such variability, as this study focuses only on the characteristics of this pilot. Figure 1. Map of Spain divided into autonomous communities and provinces, with La Rioja highlighted in red and the location of the grape cultivation system identified with a barrel. 2.2. Environmental Assessment The environmental impacts of the studied scenario were evaluated through the attributional approach of the LCA framework. The following sections provide an overview of the different methodological stages based on ISO 14040 and 14044 [28,29]. 2.2.1. Goal and Scope Definition The aim of the environmental analysis is to evaluate the impacts linked to this organic red grape cultivation system in one of the most renowned wine-producing regions globally, with the goal of promoting the adoption of more sustainable practices within the Spanish wine industry. To accomplish this, two functional units (FUs) were selected: (i) FU1: One hectare of land, to evaluate farming practices without considering the yield of the farm and then see which ones can be acted upon to achieve a better environmental profile [30]. (ii) FU2: One kilogram of produced grapes, to quantify the impacts per unit of product harvested. Thus, the winery stage could opt for a raw material with a lower environmental impact [31], as well as being the most useful when comparing the benefits of this organic farming system with others published in the literature. Figure 2 summarises the cradle-to-gate system boundaries, ranging from the extraction of resources (e.g., minerals, fuel) to the manufacture of inputs (e.g., fertilisers and fungicides), field machinery (e.g., tractor, tillage) and materials used for the infrastructure of the vineyard (e.g., high-density polyethylene (HDPE) for grape collection and steel for posts and wires). In this regard, the installation of 500 steel posts and the use of approximately 13,200 m of steel wire per ha have been applied to support the vines and ensure proper growth of the bunches, as well as the use of plastic boxes for the collection and transport of grapes. The useful life of these materials has been considered in their assignment to the operation time considered (1 year), with a lifespan of 36 years for steel and 10 years for plastic boxes [32,33]. Figure 1. Map of Spain divided into autonomous communities and provinces, with La Rioja highlighted in red and the location of the grape cultivation system identified with a barrel. 2.2. Environmental Assessment The environmental impacts of the studied scenario were evaluated through the attributional approach of the LCA framework. The following sections provide an overview of the different methodological stages based on ISO 14040 and 14044 [28,29]. 2.2.1. Goal and Scope Definition The aim of the environmental analysis is to evaluate the impacts linked to this organic red grape cultivation system in one of the most renowned wine-producing regions globally, with the goal of promoting the adoption of more sustainable practices within the Spanish wine industry. To accomplish this, two functional units (FUs) were selected: (i) FU1: One hectare of land, to evaluate farming practices without considering the yield of the farm and then see which ones can be acted upon to achieve a better environmental profile [30]. (ii) FU2: One kilogram of produced grapes, to quantify the impacts per unit of product harvested. Thus, the winery stage could opt for a raw material with a lower environmental impact [ 31 ], as well as being the most useful when comparing the benefits of this organic farming system with others published in the literature. Figure 2summarises the cradle-to-gate system boundaries, ranging from the extraction of resources (e.g., minerals, fuel) to the manufacture of inputs (e.g., fertilisers and fungicides), field machinery (e.g., tractor, tillage) and materials used for the infrastructure of the vineyard (e.g., high-density polyethylene (HDPE) for grape collection and steel for posts and wires). In this regard, the installation of 500 steel posts and the use of approximately 13,200 m of steel wire per ha have been applied to support the vines and ensure proper growth of the bunches, as well as the use of plastic boxes for the collection and transport of grapes. The useful life of these materials has been considered in their assignment to the operation time considered (1 year), with a lifespan of 36 years for steel and 10 years for plastic boxes [32,33]. In addition, the use of machinery, its maintenance and its end-of-life management were included within the system boundaries. No allocation was needed as only one product (i.e., grapes) is obtained from the system, because the pruning residues remain on the land as organic amendment. Agriculture 2025,15, 536 5 of 18 Agriculture 2025, 15, x FOR PEER REVIEW 5 of 19 In addition, the use of machinery, its maintenance and its end-of-life management were included within the system boundaries. No allocation was needed as only one product (i.e., grapes) is obtained from the system, because the pruning residues remain on the land as organic amendment. Figure 2. System boundaries of the vineyard with the main activities and processes considered. 2.2.2. Life Cycle Inventory The quality and representativeness of environmental analysis using the LCA methodology depend directly on the quality of the data used in its development. In this study, wherever possible, primary data provided directly by the farmer through questionnaires on farming practices, including the use of machinery and agrochemicals, have been used. To model the background processes, i.e., those that are not under the direct control of the farmer (such as agrochemical production, diesel production and the emissions associated with its combustion), secondary data obtained from the Ecoinvent ® database version 3.9.1 were used [34]. A summary of the data used and their sources is presented in Tables S1 and S2 in the Supplementary Materials (SMs). In addition, several empirical models were used to estimate the field emissions from agrochemical application. The Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories were used to quantify the direct and indirect N 2 O emissions, as well as those resulting from volatilisation/deposition and leaching [35]. The emissions of nitrogen dioxide (NO 2 ) and ammonia (NH 3 ), mainly caused using the organic fertiliser, were estimated according to the European Environment Agency (EEA) and the European Monitoring and Evaluation Programme (EMEP) [36]. The nitrate (NO 3− ) emissions discharged into water were calculated according to the model of Faist Emmenegger et al. [37], assuming inceptisol to be the dominant soil order, an annual rainfall of 450 mm/year and an average vineyard root depth of 1 m [38,39]. For the emissions of phosphates released into water, both by leaching and run-off, the SALCA-P method was followed [40]. Finally, the emissions from phytosanitary products were also estimated according to the European Commission’s Product Environmental Figure 2. System boundaries of the vineyard with the main activities and processes considered. 2.2.2. Life Cycle Inventory The quality and representativeness of environmental analysis using the LCA methodology depend directly on the quality of the data used in its development. In this study, wherever possible, primary data provided directly by the farmer through questionnaires on farming practices, including the use of machinery and agrochemicals, have been used. To model the background processes, i.e., those that are not under the direct control of the farmer (such as agrochemical production, diesel production and the emissions associated with its combustion), secondary data obtained from the Ecoinvent ® database version 3.9.1 were used [ 34 ]. A summary of the data used and their sources is presented in Tables S1 and S2 in the Supplementary Materials (SMs). In addition, several empirical models were used to estimate the field emissions from agrochemical application. The Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories were used to quantify the direct and indirect N 2 O emissions, as well as those resulting from volatilisation/deposition and leaching [ 35 ]. The emissions of nitrogen dioxide (NO 2 ) and ammonia (NH 3 ), mainly caused using the organic fertiliser, were estimated according to the European Environment Agency (EEA) and the European Monitoring and Evaluation Programme (EMEP) [ 36 ]. The nitrate (NO 3− ) emissions discharged into water were calculated according to the model of Faist Emmenegger et al. [ 37 ], assuming inceptisol to be the dominant soil order, an annual rainfall of 450 mm/year and an average vineyard root depth of 1 m [ 38 , 39 ]. For the emissions of phosphates released into water, both by leaching and run-off, the SALCA-P method was followed [ 40 ]. Finally, the emissions from phytosanitary products were also estimated according to the European Commission’s Product Environmental Footprint Category Rules [ 41 ], estimating their emissions into the air, water and soil (9%, 1% and 90%, respectively). Regarding the field emissions due to land use change, the indirect (iLUC) and direct land (dLUC) use change emissions were considered. iLUC are defined as those emissions due to the transformation of land use in a different area because of the occupation of the land for the cultivation of the assessed crop, as calculated following the method of Schmidt et al. [ 42 ] and taking into account the productivity capacity factor provided by Haberl Agriculture 2025,15, 536 6 of 18 et al. [ 43 ]. dLUC are emissions resulting from the management practices applied to the land under study, i.e., the management of pruning waste in the vineyard, which is crushed and left on the land [ 42 ]. Table 1displays a summary of the main inventory data collected from the farmers as well as the corresponding on-field emissions. Table 1. Main inventory data associated with the viticulture system expressed per hectare of land. Inputs Value Unit Tractor 3.96 kg Diesel 39.90 kg Tillage 13.49 kg Water 2.40 m3 N (organic fertiliser) 35.00 kg P2O5(organic fertiliser) 35.00 kg K2O (organic fertiliser) 70.00 kg Pesticides 32.00 kg Steel 51.39 kg High-density polyethylene 5.62 kg Outputs Value Unit Grapes 6.50 t Air emissions CO2(iLUC) 37.88 kg CO2(dLUC) −1246 kg N2O 1.43 kg NO21.40 kg NH38.50 kg Copper 17.67 mg Sulphur 1.81 kg Water emissions PO4−3(groundwater) 0.21 kg PO4−3(river) 0.58 kg NO3−14.80 kg Copper 1.89 g Sulphur 0.20 kg Soil emissions Sulphur 18.14 kg Moreover, to ensure the quality and reliability of the data provided, an uncertainty analysis following the Monte Carlo method [ 44 ] was performed on the system using SimaPro ® software. The results of this analysis are presented in Table S3 in the Supplementary Materials. 2.2.3. Life Cycle Impact Assessment The estimation of the environmental profile of the vineyard activities requires transformation of the inventory data (inputs and outputs) into environmental impacts. In this regard, some impact categories with high importance within the agricultural sector [ 45 , 46 ] have been considered in the analysis: global warming (GW), stratospheric ozone depletion (SOD), terrestrial acidification (TA), freshwater eutrophication (FE), marine eutrophication (ME), human non-carcinogenic toxicity (HNCT), land use (LU) and water scarcity (WS). To achieve this, the characterisation factors from the ReCiPe 2016 v1.06 Hierarchist Midpoint World (2010) method [ 47 ] were applied, except for water scarcity, which was assessed using the Available WAter REmaining (AWARE) method v1.2c [ 48 ], to consider both the Agriculture 2025,15, 536 7 of 18 water consumption and the availability at a regional scale (specifically for Spain), as the ReCiPe indicator only considers the former. From an endpoint perspective, the global potential species loss indicator (PDF) has been considered in the analysis to measure the impact of land use, both land occupation and land transformation stressors, on biodiversity. Finally, as increasing attention is being paid to the ecosystem services provided by insect pollinators [ 49 ], the valuation of the pollination service to crops has also been considered because pollinators affect the food supply on a global scale, with crops dependent on them contributing approximately 35% of the total crop production by volume [ 50 ]. A description of the procedure for estimating both biodiversity-related factors is detailed below. The product system was modelled using SimaPro®software version 9.4 [51]. Global Potential Species Loss To gain a broader understanding of the environmental performance of this wine system, the overall potential loss of species, calculated as the potentially disappearing fraction (PDF), was assessed. This model, developed by Chaudhary et al. [52] and further complemented by Chaudhary and Brooks [ 53 ], provides a framework for quantifying and projecting the biodiversity loss due to land use at a global scale, based on data collected from five different taxonomic groups: mammals, birds, amphibians, reptiles and plants. Biodiversity loss is applied in 804 different terrestrial ecoregions, with the case study being located in the ecoregion PA0406 (Cantabrian mixed forests) [ 54 ], and 175 countries. The local characterisation factors reported by Chaudhary et al. [ 52 ] for six different land use types (annual crops, permanent crops, pasture, urban, extensive forestry and intensive forestry) were used to calculate the probability of extinction for each species. Therefore, the model was used to analyse the damage generated at the ecosystem level, so it can be included as an endpoint category [ 55 ]. For all the necessary calculations, the software Microsoft Excel ® 365 MSO was used, based on land use/land transformation data obtained from SimaPro®software version 9.4 [51]. Pollination The pollination analysis was carried out using the free Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) crop pollination model [ 56 ]. Also, to perform the spatial and temporal variations, the QGIS software version 3.34.12 was used [ 57 ]. The InVEST crop pollination model focuses on wild bees as a key pollinator and on two main aspects: pollinator supply and pollinator visits to crops [ 56 ]. For the pollinator supply, the model focuses on estimating their relative abundance per pixel based on the availability of nesting sites, the abundance of floral resources for feeding and the average distances pollinators can travel to flowers from their nests. For the crop visits, they are based on the supply of pollinators from nearby areas, the quality of flowers in the soil type and the behaviour of the bees. Among the benefits of this ecosystem service are that it increases the yield, quality and stability of fruit and seeds crops as diverse as almond and coffee. Indeed, Klein et al. [ 58 ] found that 87 of 115 globally important crops benefit from animal pollination, a service that was valuated in terms of billions per year worldwide. Other animals, such as butterflies or birds, can act as pollinators too, but bees are the most important group. The model translates the land cover into an index of suitability (0–1) for bees to create a pollinator source map, with higher scores indicating greater relative bee abundance. To simulate this, the model requires the following data: a land use land cover (LULC) map, a biophysical table paired with the LULC map that has the nesting suitability and floral resources for each season and a guild table with the properties of the active seasons, nesting preferences, mean flight distance and relative abundance. The LULC map was downloaded from CORINE Land Cover for 2018 using the Copernicus Land Monitoring Service [ 59 ]. Agriculture 2025,15, 536 8 of 18 The bee species abundance in Spain were taken from the paper of Bartomeus et al. [ 60 ] about the Iberian bees database and the other parameters for the guild and pollinator table were taken from the varied literature [61–63]. 3. Results 3.1. Environmental Impact Profile The environmental profile results provide a comprehensive overview of the impacts associated with the grape growing system under study. These results are essential for understanding the contribution of different processes to the overall environmental burden and serve as a basis for future research in the field. Table 2presents the total impacts for each analysed category and functional unit, serving as a basis for a detailed discussion and contextual comparison with the findings from previous research. Table 2. Total impacts by impact category for each of the analysed functional units. GW: global warming, SOD: stratospheric ozone depletion, TA: terrestrial acidification, FE: freshwater eutrophication, ME: marine eutrophication, HNCT: human non-carcinogenic toxicity, LU: land use, WS: water scarcity. Impact Category FU1: 1 ha of Land FU2: 1 kg Grapes Value Unit Value Unit GW 99.51 kg CO2eq 15.31 g CO2eq SOD 0.02 kg CFC11 eq 2.62 mg CFC11 eq TA 8.83 kg SO2eq 1.36 g SO2eq FE 0.74 kg P eq 0.11 g P eq ME 4.51 kg N eq 0.69 g N eq HNCT 1.00 t 1,4-DCB 0.15 kg 1,4-DCB LU 24.26 m2a crop eq 37.32 cm2a crop eq WS 315 m348.4 L To identify the main contributors and potential areas for improvement, Figure 3 illustrates the distribution of the impacts across the analysed categories, providing insight into the contribution of each activity carried out. The activity that is responsible for the greatest number of impacts at a general level is field emissions, a category grouping together emissions into the air, soil and water derived from the use of agrochemicals. The next stage with the greatest contribution to the environmental profile is the production of chemicals used for pest control or fertilisation, followed by the impacts derived from the infrastructure related to the vineyard itself, such as steel wire or water pipes. Finally, the one that generates the least number of total impacts is field operations, i.e., those derived from the consumption of machinery for each of the operations carried out in the field and the combustion of the fuel consumed. Monte Carlo analysis was performed with a 95% confidence interval and 2000 iterations to assess the variability of the obtained parameters. The analysis reveals that the mean values given are quite similar to the obtained results, with standard deviations close to zero in almost all the categories (Table S3 in Supplementary Materials). This indicates that the input data have very little associated uncertainty, except for GW and LU, which suggests that these are the most sensitive impact categories in the model, with a relative standard deviation of 39% and 22%, respectively. The variability observed in these categories highlights their dependence on uncertain input parameters, making them more sensitive to fluctuations. GW is one of the impact categories in which the environmental burdens are more evenly distributed, with the stages that have the greatest weight being the production of agrochemicals and the field emissions derived from their use, with 27% and 32%, respectively. Agriculture 2025,15, 536 9 of 18 It is worth noting that in this category, the total impact is considerably reduced due to the high weight of the dLUC, which offsets 1246 kg CO 2 eq per hectare because of the carbon fixed in the soil by the pruning remains that are crushed and left on the ground, that is, they account for 92% of the total emissions in this category. Moreover, these good practices have a long-term effect, helping to mitigate soil degradation, increase fertility, and enhance microbial activity, all of which positively impact the vineyard’s productivity and health [ 64 ]. It is important to note that emissions in this category come mainly from CO 2 , CH 4 , N 2 O and SF 6 generated in the production of pesticides and steel, the combustion of diesel fuel in the tractor and the application of nitrogen fertilisers in the field. Agriculture 2025, 15, x FOR PEER REVIEW 9 of 19 Monte Carlo analysis was performed with a 95% confidence interval and 2000 iterations to assess the variability of the obtained parameters. The analysis reveals that the mean values given are quite similar to the obtained results, with standard deviations close to zero in almost all the categories (Table S3 in Supplementary Materials). This indicates that the input data have very little associated uncertainty, except for GW and LU, which suggests that these are the most sensitive impact categories in the model, with a relative standard deviation of 39% and 22%, respectively. The variability observed in these categories highlights their dependence on uncertain input parameters, making them more sensitive to fluctuations. Figure 3. Contribution of factors to the environmental profile. GW: global warming; SOD: stratospheric ozone depletion; TA: terrestrial acidification; FE: freshwater eutrophication; ME: marine eutrophication; HNCT: human non-carcinogenic toxicity; LU: land use; WS: water scarcity. GW is one of the impact categories in which the environmental burdens are more evenly distributed, with the stages that have the greatest weight being the production of agrochemicals and the field emissions derived from their use, with 27% and 32%, respectively. It is worth noting that in this category, the total impact is considerably reduced due to the high weight of the dLUC, which offsets 1246 kg CO 2 eq per hectare because of the carbon fixed in the soil by the pruning remains that are crushed and left on the ground, that is, they account for 92% of the total emissions in this category. Moreover, these good practices have a long-term effect, helping to mitigate soil degradation, increase fertility, and enhance microbial activity, all of which positively impact the vineyard’s productivity and health [64]. It is important to note that emissions in this category come mainly from CO 2 , CH 4 , N 2 O and SF 6 generated in the production of pesticides and steel, the combustion of diesel fuel in the tractor and the application of nitrogen fertilisers in the field. The categories with the highest weight of on-field emissions are SOD and ME, with more than 90% of the total impacts, followed by TA, with almost half of the category contribution (45%). This is due to emissions from N 2 O and CH 4 released into the atmosphere in the case of SOD and to NH 4 and NO 3− in ME, both due to the transformation of nitrogen from fertilisers in its different forms. This is in line with the findings of Müller [65], who stated that the application of nitrogen fertilisers in agriculture has increased N 2 O emissions, posing a significant risk to the stratospheric ozone layer. On the other hand, ammonia derived from the application of nitrogen fertiliser and SO 2 derived from the industrial Figure 3. Contribution of factors to the environmental profile. GW: global warming; SOD: stratospheric ozone depletion; TA: terrestrial acidification; FE: freshwater eutrophication; ME: marine eutrophication; HNCT: human non-carcinogenic toxicity; LU: land use; WS: water scarcity. The categories with the highest weight of on-field emissions are SOD and ME, with more than 90% of the total impacts, followed by TA, with almost half of the category contribution (45%). This is due to emissions from N 2 O and CH 4 released into the atmosphere in the case of SOD and to NH 4 and NO 3− in ME, both due to the transformation of nitrogen from fertilisers in its different forms. This is in line with the findings of Müller [ 65 ], who stated that the application of nitrogen fertilisers in agriculture has increased N 2 O emissions, posing a significant risk to the stratospheric ozone layer. On the other hand, ammonia derived from the application of nitrogen fertiliser and SO 2 derived from the industrial production of pesticides are the main emissions that contribute to TA. Moving on to FE, the emissions are more equally distributed, with the largest contributor being field emissions, with 36% of the total, followed by the manufacture of chemicals used for soil fertilisation and pest control, with 32% and 16%, respectively. In the FE category, the emissions are caused by BOD 5 and COD, from steel and pesticide production, and especially phosphates, which come from the transformation of the phosphorus contained in the fertiliser used in the field. In terms of LU, the impacts primarily stem from the occupation and transformation of forests, associated mainly with the production of steel for infrastructure and the production of necessary pesticides. Both are the main contributors to this category. For HNCT, the profile is quite similar to that obtained for LU, with infrastructure and pesticide production responsible for around 40% of the impacts. Finally, in the WS category, the main hotspot (with 60%) is the water needed for fertiliser and pesticide dispersion, followed by the water requirements associated with infrastructure production. 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