Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks
Abstract
:1. Introduction
2. Background on the Circular Economy and Farm to Fork Strategy
2.1. The Circular Economy Framework in Agri-Food Life Cycle
2.2. The EU “Farm to Fork Strategy”: Main Goals/Areas of Intervention
- Ensuring sustainable food production;
- Ensuring food security;
- Stimulating sustainable food processing, wholesale, retail, hospitality, and food services practices;
- Promoting sustainable food consumption and facilitating the shift to healthy, sustainable diets;
- Reducing food losses and waste;
- Fighting food fraud along the whole food supply chain.
3. Material and Methods
3.1. Data Quality and Categories
- Policy documents and other materials available from the websites of the European Union, including the data about performance indicators comprised in the monitoring and evaluation framework of the CAP [20];
- Scientific literature available in the international database (such as Web of Science, Scopus, and Google Scholar), covering the topics investigated in this study.
3.2. Methods for Data Collection
- (1)
- Identification of the keywords for searching the articles;
- (2)
- Searching and retrieval of the articles;
- (3)
- Verification of the relevance of the articles compared to the investigated topics mentioned above;
- (4)
- Critical review of articles and synthesis of their results.
3.3. Short Overview of the Accounting Methods Referred to in This Study
- Life cycle assessment (LCA) is an internationally standardized methodology (ISO 14040/2006/Amd 1:2020) [49] that quantifies the environmental impacts associated with the life cycle of products, processes, or activities and the opportunities for the improvement of such impacts [50]. LCA midpoint indicators are summarized in Table 2.
- Material flow accounting (MFA) assesses the flows of materials entering in a system (e.g., industrial) and the patterns in which such flows are used, reused, and lost in the form of waste in a given time [51]. The MFA takes into account physical and socioeconomic flows of an investigated system and the biotic or renewable resources, abiotic or nonrenewable raw materials, water, air, earth consumption, solid waste, emissions, and stocks [52].
- Emergy accounting (EA) is a methodology that uses the thermodynamic basis of all forms of energy, materials and human services and converts them into equivalents of one form of available energy (exergy). Emergy is, by definition, the amount of available energy of one form (usually solar) needed to provide a given flow or storage of energy or matter [53]. Several performance indicators are calculated by means of the EA [54]:
- Total emergy used in a process;
- Emergy yield ratio (EYR), i.e., the emergy used per unit of emergy invested;
- Environmental loading ratio (ELR), i.e., the total nonrenewable and imported emergy released per unit of local renewable resources;
- Emergy sustainable index (ESI), i.e., the emergy yield per unit of environmental loading,
- Renewability (%REN), i.e., the percentage of renewable emergy used compared to the total emergy.
- Crop accounting method (CAM) is a tool very suitable for agricultural enterprises that takes into account all the revenues and costs of growing crops until the time they are harvested. The nature of the costs considered by this method depend on the farming practice and varies e.g., from conventional to organic farming. In addition to the revenues and costs, the method calculates the gross income indicator as the difference between the revenues and costs [55].
4. Environmental and Energy Indicators in the Life Cycle of Food Systems: A Critical Description of Achieved Results
4.1. Ensuring Sustainable Food Production: Environmental and Energy Indicators at Production Stage
4.1.1. Indicators of the Common Agricultural Policy
4.1.2. Environmental Indicators Evaluating the Effects of the EU Food System Outside the EU Area
4.1.3. Brief Overview of Organic Farming
Environmental and Energy Indicators of Organic Farming
Indicators for Organic Olive Production
Indicators of Organic Durum Wheat Production
Miscellaneous Indicators of National, Regional, and Urban Organic Productions
4.1.4. The Circular Biobased Economy at Agricultural Stage: Environmental and Energy Indicators
4.2. Stimulating EU Sustainable Food Processing, Wholesale, Retail, Hospitality, and Food Distribution Practices
4.2.1. Environmental and Energy Indicators of Food Supply Chain
Indicators of Short and Long Food Supply Chains
Indicators of Specific Products: The Egg Supply Chain
Supply Chain Indicator Frameworks for Decision Making
4.2.2. Promoting Sustainable Food Consumption and the Shift to Healthy and More Sustainable Diets
4.2.3. Energy, Water, and Carbon Footprints of Mediterranean Diet
4.3. Reducing Food Losses and Waste
Environmental and Energy Indicators of Food Waste Prevention and Valorization
Authors | Indicators | Method | Geographical Scale |
---|---|---|---|
Banasik et al. [40] | Exergy indicators (MJ) | Exergy analysis, mathematical modeling, and case study | The Netherlands |
Bernstad et al. [41] | GHG emissions (kg CO2 eq.) | Review on 28 LCA case studies and 2 review papers. | Worldwide |
Corrado et al. [42] | Avoidable food loss Unavoidable food loss Total food loss (equal to avoidable food loss + unavoidable food loss) | Literature review on LCA studies. | Worldwide |
De Menna et al. [43] | Net present value Internal rate of return Cost-to-benefit ratio Private cost/benefit to external cost/benefit | Literature review on LCA and LCC studies about food waste | Worldwide |
Caldeira et al. [93] | Redistribution of food for human consumption Food valorization Transformation of waste Consumer behavior change Improvement of the supply chain efficiency Food waste prevention governance | Survey of members of the EU Platform on FLW and literature review | EU |
Santagata et al. [115] | 18 midpoint LCA indicators (ReCiPe 2016) and emergy accounting indicators (total emergy with/without L&S) | Literature review LCA and emergy accounting studies | Worldwide |
Amicarelli et al. [118] | Domestic material input (Mt), domestic material output (Mt), and material use efficiency indicator (Mt and % of total DMI) | Material flow analysis | Italy |
Lins et al. [122] | Water footprint (L/kg) Cleaning materials Food production waste (kg) Amount of rest intake (kg) Amount of distributed leftover (kg) | Mathematical formula: EIy pilot test based on eco-efficiency with focus on food waste | Brazil |
Subramanian et al. [125] | Food waste, energy, water consumption, and emissions | LCA and survey | Hong Kong |
Cudjoe et al. [126] | Amount of food waste (kg), hydrogen yield potential (TWh), return on investment (ROI), payback period (PBP), and global warming reduction potential (kt CO2 eq.). | Energy analysis, cost–benefit analysis, and environmental analysis | China |
Wu et al. [127] | GWP, AP, and primary energy demand | LCA and economic analysis | China |
5. Discussion: Application of the Proposed Framework to Italy
5.1. Application of the Identified Indicators at the National Italian Scale
5.2. Application of the Identified Indicators at the Product Scale
6. Concluding Remarks
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Areas of Intervention (Food Life Cycle Stage and Goals) | Suggested Actions/Practices/Goals in the Farm to Fork Strategy |
---|---|
1. Ensuring sustainable food production systems |
|
2. Ensuring food security |
|
3. Stimulating sustainable food processing, wholesale, retail, hospitality, and food services practices |
|
4. Promoting sustainable food consumption and facilitating the shift to healthy, sustainable diets |
|
5. Reducing food loss and waste |
|
6. Combating food fraud along the food supply chain |
|
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Keywords |
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Impact Category | Unit | Abbreviation |
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Climate change potential | kg CO2 eq | CCP |
Stratospheric ozone depletion potential | kg CFC11 eq | SODP |
Ionizing radiation potential | kBq Co-60 eq | IRP |
Ozone formation, human health potential | kg NOx eq | OFHP |
Fine particulate matter formation potential | kg PM2.5 eq | PMFP |
Ozone formation, terrestrial ecosystems potential | kg NOx eq | OFEP |
Terrestrial acidification potential | kg SO2 eq | TAP |
Freshwater eutrophication potential | kg P eq | FEP |
Marine eutrophication potential | kg N eq | MEP |
Terrestrial ecotoxicity potential | kg 1,4-DCB | TETP |
Freshwater ecotoxicity potential | kg 1,4-DCB | FETP |
Marine ecotoxicity potential | kg 1,4-DCB | METP |
Human carcinogenic toxicity potential | kg 1,4-DCB | HCTP |
Human noncarcinogenic toxicity potential | kg 1,4-DCB | HNCTP |
Land use potential | m2a crop eq | LUP |
Mineral resource scarcity potential | kg Cu eq | MRSP |
Fossil resource scarcity potential | kg oil eq | FRSP |
Water consumption potential | m3 | WCP |
Indicators | Description | Unit |
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Land cover | Distribution of land devoted to forests, water, desert, grassland, and other physical features of the land, including land created by human activities. The source of the data for the EU is Corinne land cover. | % of total area |
Areas facing natural and other specific constraints | Measure of the share of agricultural area in different categories of areas facing natural or other specific constraints (ANCs) (ex-LFAs as they were defined in the period 2007–2013). | % of utilized agricultural area |
Farming intensity | Defined as the level of inputs used by the farm per unit of production factor (in general land). Intensification is the increase in farm intensity, while extensification is the opposite, evidencing a reduction in farm intensity | ha and % of total utilized agricultural area |
Natura 2000 areas | Information on the areas protected under Natura 2000 used for agriculture and/or forestry. Natura 2000 is a network of areas conserving natural habitats and species of wildlife which are rare, endangered, or vulnerable in the European Union. This indicator includes three sub-indicators: share of territory under Natura 2000 by categories; share of UAA (utilized agricultural area is the total area including arable land, permanent grassland, permanent crops, and kitchen gardens) under Natura 2000; share of forest area under Natura 2000. | % of area under Natura 2000 |
Farmland birds index | Composite index measuring the rate of change in the relative abundance of common bird species at selected sites. Birds are considered indicators in the evaluation of the state of biodiversity of European agricultural landscape. | Index (base year 2000 = 100) |
Conservation status of agricultural habitats (grassland) | Conservation status of agricultural habitats (grassland) | % of total assessments of grassland (favorable, unfavorable/inadequate and unfavorable/bad conservation status) |
High-nature-value farming | High-nature-value farmland areas are considered valuable assets of European agricultural landscapes, providing highly varied living conditions for a wide range of species contributing to biodiversity preservation. | |
Protected Forests | Percentage of forests and other wooded land (FOWL) protected to conserve biodiversity, landscapes, and specific natural elements. This indicator has four sub-indicators based on different classes (1.1, 1.2, 1.3, and 2) of intervention and management. | % of FOWL area protected under each classes: 1.1, 1.2, 1.3, 2. |
Water withdrawal in agriculture | Volume of water used for soils irrigation purposes. Data refer to water withdrawn from total surface and ground water. | m3 |
Irrigated land | The indicator consists of two sub-indicators: (1) total irrigated area, i.e., the area which has actually been irrigated at least once during the 12 months prior to the reference day of the survey; (2) share of irrigated area in total UAA. | (ha) (%) |
Water quality | Potential impact of agriculture activities on water quality due to pollution by nitrates and phosphates. | (Nitrates): kg N/ha/year (Phosphates): kg P/ha/year |
Soil organic matter in arable land | Estimation of the content of soil organic matter in arable lands. The indicator contains two sub-indicators: (1) total estimate of organic carbon content in arable soils; (2) the mean organic carbon content. |
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Soil erosion by water | Assessment of the soil loss due to water erosion including information of the areas affected by a certain rate of soil erosion (moderate to severe, i.e., >11 t/ha/year in the OECD definition). The indicator has two sub-indicators: (1) estimated rate of soil loss by water erosion; (2) estimated agricultural area affected by a certain rate of soil erosion by water (expressed as share of the total agricultural area). |
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Production of renewable energy from agriculture and forestry | Provides two sub-indicators: production of renewable energy from agriculture (biodiesel from biomass, ethanol from starch/sugar crops, energy from biogas with energy crops, and manure as the main feedstocks) and from forestry. | kt |
Energy use in agriculture, forestry and food industry | Provides three sub-indicators measuring the direct energy use in the three sectors: (1) direct use of energy in agriculture and forestry; (2) direct use of energy in agriculture and forestry; (3) direct use of energy in food processing. |
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Emissions from agriculture (GHG per LSU and GHG per ha) | The indicator contains different sub-indicators of the greenhouse gas emissions and ammonia emissions released from agriculture. |
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Sales use of antimicrobials in food producing animals | Information on the actions aimed to improve the response of EU agriculture to the problems of antimicrobial resistance (AMR) and the need for promoting safe, nutritious and sustainable food, and a better animal welfare. | Sales of antimicrobial substances, (product package level), corrected by a population correction unit (PCU) |
Sustainable and reduced use of pesticides: risk, use, and impact of pesticides | The indicator contains three specific sub-indicators: (1) sales of pesticides (sales as a proxy of the use of pesticides in agriculture); (2) the harmonized risk indicator 1 (related to risk of pesticides); (3) sales of the most hazardous pesticides (so-called “candidates for substitution” referring to active substances defined in Regulation (EC) No 1107/2009). |
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Share of a member state organic farming area compared to total UAA | Area under organic farming compared to the total UAA excludes kitchen gardens and refers to organic crop area by agricultural production methods and crops. | (% of total UAA) |
Organic area and organic producers | Indicators refer to the organically cropped area and the number of farmers involved. | ha Total amount |
Share of organic area receiving CAP support | This indicator refers to the share in total organic area. | (%) |
Authors | Olives Production Systems | Environmental–Ecological Dimensions—Indicators | ||
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Environmental Impacts and Support | Soil | Biological | ||
Lehmann et al. [72] | Olives in Italy cultivated under:
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Guarino et al. [12] | Olives in Italy cultivated under:
| CCP, SODP, IRP, OFHP, PMFP, TAP, FEP, TETP, FETP, METP, HCTP, HNCTP, LUP, MRSP, FRSP, WCP, primary energy | ||
Durán Zuazo et al. [73] | Rainfed olives in Spain cultivated under:
| Soil physio-chemical parameters:
| Microbial activities:
| |
Solomou and Sfougaris [74] | Olives in Greece cultivated under:
| Organic matter
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Type of Benefits | Description |
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Environmental benefits | Lower use of natural resources (land, water, and resource use for production) and lower release of GHG emissions, compared to a diet mostly based on the consumption of meat and animal fats |
Higher seasonality as it encourages the consumption of season food. This translates into a reduction in greenhouse crops and related environmental impacts, as well as lower supply and transport costs from distant countries (food miles) | |
Higher biodiversity, due to higher respect of each territory and its specific biodiversity, through different sowing in each area and crop rotation, in order to also guarantee food security | |
Higher frugality as it considers moderate portions and consumption of whole and fresh, lightly processed foods. Both the quantities consumed and the minor transformations undergone by food contribute to reducing the environmental impacts of MD-based eating behaviors | |
Social benefits | Physical health: The MD, together with physical activity, helps prevent cardiovascular disease, diabetes, and some types of cancer (colorectal, breast, prostate, pancreas, and endometrial). In addition, the intake of fresh and whole foods allows greater availability and use of micronutrients and antioxidants |
Food awareness: The MD promotes greater food awareness and link with the territory and knowledge of seasonality, biodiversity, and naturalness of food | |
Conviviality: The MD promotes social interaction; common meals are the cornerstone of the holidays and of social traditions | |
Identity: The MD is an expression of the entire historical and cultural system of the Mediterranean area. It is a millenary food tradition that has been handed down from generation to generation, promoting not only the quality of foods and their territorial characterization, but also the dialogue between peoples | |
Economic benefits | Health expenditure: A greater adherence of eating habits to the MD would improve the general state of health of the population, which would translate into a decrease in national health expenditure |
Household spending: Adherence to the MD, favoring seasonal foods, mainly cereals and vegetables, would allow a decrease in household food spending | |
Business enhancement: The spread of the MD would result in an increase in the commercial demand for natural products (fruit, vegetables, cereals, legumes, etc.) and their derivatives (oil, wine, pasta, bread, etc.), creating income and employment for companies in the Mediterranean regions | |
Enhancement of territories: The spread of the MD would enhance the agro-eno-gastronomic offer of Mediterranean territories, contributing to the seasonal adjustment of the tourist offer |
Midpoint Impact Categories | Unit | Upstream | Core | Downstream | Total | |
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Global Warming Potential | Fossil | kg CO2 eq. | 1.22 × 10−1 | 2.24 × 10−1 | 5.38 × 10−2 | 4.00 × 10−1 |
Biogenic | kg CO2 eq. | 9.75 × 10−5 | 4.07 × 10−4 | 1.64 × 10−5 | 5.21 × 10−4 | |
Land use | kg CO2 eq. | 3.92 × 10−3 | 1.72 × 10−4 | 1.96 × 10−5 | 4.11 × 10−3 | |
Total | kg CO2 eq. | 1.26 × 10−1 | 2.24 × 10−1 | 5.39 × 10−2 | 4.04 × 10−1 | |
Acidification potential | kg SO2 eq. | 1.20 × 10−3 | 2.50 × 10−3 | 2.46 × 10−4 | 3.95 × 10−3 | |
Eutrophication potential | kg PO43-eq. | 6.92 × 10−4 | 2.06 × 10−3 | 4.90 × 10−5 | 2.80 × 10−3 | |
Photochemical oxidant formation potential | kg NMVOC eq. | 4.57 × 10−4 | 1.72 × 10−3 | 2.96 × 10−4 | 2.47 × 10−3 | |
Abiotic Depletion potential (Elements) | kg Sb eq. | 6.92 × 10−6 | 9.37 × 10−6 | 1.48 × 10−6 | 1.78 × 10−5 | |
Abiotic Depletion potential (Fossil resources) | MJ, net calorific value | 8.81 × 10−1 | 2.57 | 8.10 × 10−1 | 4.26 | |
Water scarcity potential | m3 eq. | 7.85 × 10−1 | 2.08 × 10−2 | 2.34 × 10−3 | 8.08 × 10−1 |
Midpoint Impact Categories | Unit | Upstream | Core | Downstream | Total | |
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Global Warming Potential | Fossil | kg CO2 eq. | 9.35 × 10−2 | 2.73 × 10−1 | 5.11 × 10−2 | 4.17 × 10−1 |
Biogenic | kg CO2 eq. | 7.12 × 10−5 | 4.31 × 10−4 | 1.56 × 10−5 | 5.18 × 10−4 | |
Land use | kg CO2 eq. | 6.19× 10−5 | 2.04 × 10−4 | 1.85 × 10−5 | 2.85 × 10−4 | |
Total | kg CO2 eq. | 9.37 × 10−2 | 2.73 × 10−1 | 5.11 × 10−2 | 4.18 × 10−1 | |
Acidification potential | kg SO2 eq. | 1.93 × 10−3 | 2.14 × 10−3 | 2.33 × 10−4 | 4.31 × 10−3 | |
Eutrophication potential | kg PO43-eq. | 1.42 × 10−3 | 1.43 × 10−3 | 4.64 × 10−5 | 2.89 × 10−3 | |
Photochemical oxidant formation potential | kg NMVOC eq. | 3.84 × 10−4 | 2.03 × 10−3 | 2.81 × 10−4 | 2.70 × 10−3 | |
Abiotic Depletion potential (Elements) | kg Sb eq. | 4.17 × 10−6 | 1.21 × 10−5 | 1.41 × 10−6 | 1.77 × 10−5 | |
Abiotic Depletion potential (Fossil resources) | MJ, net calorific value | 6.36 × 10−1 | 3.38 | 7.68 × 10−1 | 4.79 | |
Water scarcity potential | m3 eq. | 1.97 × 10−1 | 2.24 × 10−2 | 2.21 × 10−3 | 2.21 × 10−1 |
Midpoint Impact Categories | Unit | Upstream | Core | Downstream | Total | |
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Global Warming Potential | Fossil | kg CO2 eq. | 1.97 × 100 | 4.21 × 10−1 | 2.06 × 10−1 | 2.60 × 100 |
Biogenic | kg CO2 eq. | 7.12 × 10−3 | 9.54 × 10−4 | 2.30 × 10−5 | 8.09 × 10−3 | |
Land use | kg CO2 eq. | 9.72 × 10−4 | 5.20 × 10−4 | 2.07 × 10−5 | 1.51 × 10−3 | |
Total | kg CO2 eq. | 1.98 × 100 | 4.22 × 10−1 | 2.06 × 10−1 | 2.61 × 100 | |
Acidification potential | kg SO2 eq. | 6.70 × 10−2 | 1.84 × 10−3 | 1.19 × 10−3 | 7.00 × 10−2 | |
Eutrophication potential | kg PO43-eq. | 4.06 × 10−2 | 6.99 × 10−4 | 2.09 × 10−4 | 4.15 × 10−2 | |
Photochemical oxidant formation potential | kg NMVOC eq. | 8.98 × 10−3 | 1.62 × 10−3 | 2.04 × 10−3 | 1.26 × 10−2 | |
Abiotic Depletion potential (Elements) | kg Sb eq. | 5.15 × 10−5 | 1.00 × 10−5 | 1.28 × 10−6 | 6.28 × 10−5 | |
Abiotic Depletion potential (Fossil resources) | MJ, net calorific value | 1.57 × 10 | 7.24 × 100 | 2.85 × 100 | 2.58 × 10 | |
Water scarcity potential | m3 eq. | 2.14 × 100 | 5.48 × 10−1 | 2.69 × 10−3 | 2.69 × 100 |
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Ghisellini, P.; Ncube, A.; Rotolo, G.; Vassillo, C.; Kaiser, S.; Passaro, R.; Ulgiati, S. Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks. Energies 2023, 16, 1671. https://doi.org/10.3390/en16041671
Ghisellini P, Ncube A, Rotolo G, Vassillo C, Kaiser S, Passaro R, Ulgiati S. Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks. Energies. 2023; 16(4):1671. https://doi.org/10.3390/en16041671
Chicago/Turabian StyleGhisellini, Patrizia, Amos Ncube, Gloria Rotolo, Chiara Vassillo, Serena Kaiser, Renato Passaro, and Sergio Ulgiati. 2023. "Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks" Energies 16, no. 4: 1671. https://doi.org/10.3390/en16041671
APA StyleGhisellini, P., Ncube, A., Rotolo, G., Vassillo, C., Kaiser, S., Passaro, R., & Ulgiati, S. (2023). Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks. Energies, 16(4), 1671. https://doi.org/10.3390/en16041671