# Life cycle inventory and life cycle impact assessment datasets of PDO Feta production in Stymfalia region, Greece

Samuel Le Féon, Andreas Papadakis, Gwenola Yannou-Le Bris, Julie

Auberger, Dimitrios Chatzitheodorou, Joël Aubin, Caroline Pénicaud

► To cite this version:

Samuel Le Féon, Andreas Papadakis, Gwenola Yannou-Le Bris, Julie Auberger, Dimitrios Chatzitheodorou, et al.. Life cycle inventory and life cycle impact assessment datasets of PDO Feta production in Stymfalia region, Greece. Data in Brief, 2023, 48, pp.109207. 10.1016/j.dib.2023.109207. hal-04092943

HAL Id: hal-04092943

https://hal.inrae.fr/hal-04092943

Submitted on 10 May 2023

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Data Article

Life cycle inventory and life cycle impact
assessment datasets of PDO Feta production in
Stymfalia region, Greece

Samuel Le Féon<sup>a</sup>, Andreas Papadakis<sup>b</sup>, Gwenola Yannou-Le Bris<sup>a</sup>, Julie Auberger<sup>c</sup>, Dimitrios Chatzitheodorou<sup>d</sup>, Joël Aubin<sup>c</sup>, Caroline Pénicaud<sup>a,\*</sup>

ARTICLE INFO

Article history:
Received 31 March 2023
Revised 17 April 2023
Accepted 2 May 2023
Available online xxx

Dataset link: (FAIRCHAIN)CS-Gre_datapaper
(Original data)

Keywords:
Environmental assessment
LCA
Cheese production
Data inventory

A B S T R A C T

Considering and reducing the environmental impacts has be-
come one of the main concerns of agri-food systems. More
specifically, the agri-food sector is increasingly confronted to
the necessity of quantifying environmental impacts, e.g., to
eco-design their products or to inform the consumers. Liter-
ature shows a high variability in environmental impacts be-
tween existing systems, as for example between cheeses and
the necessity of more case studies to validate statements. In
this context, this data paper provides some data related to
Feta production in Greece, based on 8 farms of a coopera-
tive (7 sheep livestock and one goat livestock). Feta cheese
is PDO (Protected Designation of Origin), composed solely of
goat's milk and sheep's milk under specific percentages (at
least 70% sheep). More specifically, the data paper displays
all the data used to obtain environmental impacts (calculated
by using life cycle assessment (LCA)) of the production of
Feta, from cradle to consumer. It includes the – sheep and
goat – milk productions, the transformation into cheese, the
packaging and the transport to wholesalers, then stores and

<footnote><sup>a</sup> Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, 91120, Palaiseau, France</footnote>

<footnote><sup>b</sup> Synelixis SA, 10 Farmakidou, 34100, Chalkida, Greece</footnote>

<footnote><sup>c</sup> UMR SAS, INRAE, Institut Agro, 65 rue de Saint Brieuc, 35042, Rennes, France</footnote>

<footnote><sup>d</sup> Stymfalia SA, Kalliani Korinthia, Adresscode 200 16, Greece</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: caroline.penicaud@inrae.fr (C. Pénicaud).</footnote>

<footnote>Social media: 👤 @cpenicaud (C. Pénicaud)</footnote>
then consumers. The raw data have mostly been obtained through interviews and surveys with the cheese and milk producers and complemented by literature. Data were used to build a life cycle inventory (LCI). For the milk production, the LCI was modeled using MEANS InOut software. For the whole LCI, Agribalyse 3.0 and Ecoinvent 3.8 were used as background databases, with modifications to reflect Greek context. The dataset also compiles the life cycle impact assessment (LCIA). The characterization method used is method EF3.0. This dataset participates in filling two gaps: (1) providing data to represent the variability between Feta cheese production systems and (2) providing data linking impacts of farm, transformation, retail and transport in a value chain perspective. This is done by (1) enlarging the perimeter when most studies found in literature focus on one stage (e.g. the production of milk) and (2) applying LCA to data specific to a regional production (Stymfalia in Greece).

© 2023 Published by Elsevier Inc.

This is an open access article under the CC BY license

(http://creativecommons.org/licenses/by/4.0/)

# 1 Specifications table

<table><tr><td>Subject</td><td>Environmental engineering</td></tr><tr><td>Specific subject area</td><td>Environmental assessment of agri-food value chains</td></tr><tr><td>Type of data</td><td>Table<br>CSV</td></tr><tr><td>How the data were acquired</td><td>The raw data have mostly been obtained through interviews and surveys with the cheese and milk producers. The collection was realized by a representative of the local dairy based on a template provided by the LCA team. They were supplemented by scientific and technical literature as well as model calculations (MEANS-InOut software).<br>Background data are issued from AGRIBALYSE 3.0 and Ecoinvent 3.8 databases.<br>Life-cycle impact assessment was done using Simapro 8.4 and the "EF 3.0 Method".<br>Raw</td></tr><tr><td>Data format</td><td>Analyzed</td></tr><tr><td>Description of data collection</td><td>The raw data have mostly been obtained through interviews and surveys with the cheese and milk producers. The collection was realized by a representative of the local dairy based on a template provided by the LCA team. The dataset was complemented by literature. Ecoinvent 3.8 and Agribalyse 3.0 were used for background data.<br>LCIA data were calculated using the software Simapro and the characterization method "EF 3.0 method (adapted)"</td></tr><tr><td>Data source location</td><td>Background data collected at farm and dairy<br><ul><li>Institution: Stymfalia SA</li><li>City/Town/Region: Kaliani</li><li>Country: Greece</li></ul>Agribalyse 3.0<br><ul><li>Institution: ADEME</li><li>City/Town/Region: Nantes</li><li>Country: France</li><li>https://agribalyse.ademe.fr/</li></ul></td></tr></table>
Ecoinvent 3.8

• Institution: Ecoinvent

• City/Town/Region: Zurich

• Country: Switzerland

• https://ecoinvent.org/

MEANS-InOut

• Institution: INRAE and CIRAD

• City/Town/Region: Rennes

• Country: France

• https://www6.inrae.fr/means

Data accessibility

Repository name: Recherche Data Gouv - INRAE Dataverse

Data identification number: https://doi.org/10.57745/1 × 4QYO

Direct URL to data: https://doi.org/10.57745/1 × 4QYO

3 Value of the data

4

5 • The article presents a unique set of LCI and LCIA data for on the production of Feta in Stymfalia region, Greece.

7 • Data from different farms are used and variability between farms is presented.

8 • The LCI for sheep and goat milks were calculated using MEANS InOut software.

9 • The article can be used to identify hotspots for Feta production as well as for sheep and goat milk productions on a regional scale.

11 1. Objective

12 Literature shows a high variability in environmental impacts between existing systems, as for
13 example between cheeses [1] and the necessity of more case studies to validate statements [2].

14 In this context, this data paper provides some data related to Feta production in Greece, based
15 on 8 farms of a cooperative (7 sheep livestock and one goat livestock). This work was conducted
16 in the framework of EU FAIRCHAIN project Feta cheese is PDO (Protected Designation of Origin),
17 composed solely of goat's milk and sheep's milk under specific percentages (at least 70% sheep).

18 More specifically, the data paper displays all the data used to obtain environmental impacts (cal-
19 culated by using life cycle assessment (LCA)) of the production of Feta, from cradle to consumer.

20 This dataset has the objective to participate in filling two gaps: (1) providing data to represent
21 the variability between Feta cheese production systems and (2) providing data linking impacts
22 of farm, transformation, retail and transport in a value chain perspective.

23 2. Data description

24 The dataset associated with this article contains eight files with information on raw data,
25 inventory data and the LCIA:

26 1. (FAIRCHAIN)CS-Gre_raw_data_milk_production: it describes the raw data collected with the
27 dairy to build the inventories and completed by literature for the milk productions. Type of
28 data (collected, literature, calculated) is specified as well as hypothesis.

29 2. (FAIRCHAIN)CS-GRE_raw_data_other_stages: it describes the raw data collected with the
30 dairy to build the inventories and completed by literature for other stages (processing, pack-
31 aging, distribution). Type of data (collected, literature, calculated) is specified as well as hy-
32 pothesis.
33

3. (FAIRCHAIN)CS-Gre_LCI_milk_production: it describes the life cycle inventories calculated with MEANS InOut and adapted with Simapro. The values of input/output flows are specified as well as the database and processes used to model them.

34

35

36

4. (FAIRCHAIN)CS-Gre_LCI_one_year_production: it describes the life cycle inventory for one-year of production of the cheese factory. The values of input/output flows are specified as well as the database and processes used to model them.

37

38

39

5. (FAIRCHAIN)CS-Gre_LCI_packaging: it gives details on the simplified inventories used to model the packaging solutions.

40

41

6. (FAIRCHAIN)CS-Gre_LCIA_milk_production_contributions: it presents LCIA at farm for the production of all milks involved as well as for the weighted average for sheep milk.

42

43

7. (FAIRCHAIN)CS-Gre_LCIA_one_year_value_chain: it presents LCIA for the whole value chain for one-year production.

44

45

8. Bibliography: it details the additional bibliographical sources cited in the different data files.

46

## 3. Experimental design, materials and methods

47

### 3.1. LCA methodology

48

Our work followed ISO 14040 [3].

49

#### 3.1.1. Goal and scope

50

51

52

53

54

55

In the framework of FAIRCHAIN, the LCA is a first step analysis towards the implementation of innovations. The objectives are to collect data to build a LCI that is representative of the current situation. The calculation of the environmental impacts (LCIA) is carried out with the main objective to constitute the frame of reference that will allow to evaluate the environmental impacts of the innovation in the future. The innovation should only have a marginal effect on markets. Following these objectives, an attributional approach is chosen.

56

#### 3.1.2. System boundaries

57

The system boundaries include (Fig. 1):

58

- The sheep and goat milk production from 8 farms;

59

- The cold storage of milk at farms before collection;

60

- The collection and transport of the milk to the cheese factory;

61

- The production of Feta cheese. Greek yogurt and myzithra are also produced in the factory but they are not considered in the scope of the assessment;

62

63

- The cleaning of the cheese factory;

64

- The wastewater treatment of water used at the cheese factory;

65

- The management of the whey: the totality of the whey is considered sent to wastewater treatment;

66

67

- The packaging of the Feta, including four different packaging types with end-of-life treatments;

68

69

- The transports to wholesalers then to stores;

70

- The consumption.

71

The processes are described in [4].

72

#### 3.1.3. Functional unit

73

74

75

The functional units are defined as "the annual production of Feta at the cheese factory". However, LCIA is also calculated and provided at farms level with functional units defined as "1 kg of milk produced in farm [X]".
<figure><img src="image_3.png" /><figcaption>Fig. 1. Simplified flow diagram of the studied system from cradle to grave</figcaption></figure>

### 3.1.4. Life cycle inventory

76 3.1.4.1. At farm. The Greek CS concerns sheep and goat milk cheeses produced in Stymfalia region, in Peloponnese. Specific data were provided by the dairy cooperative for 7 sheep farms 78 and 1 goat farm. These data were used to model and calculate LCI for each farm using MEANS-InOut software (https://www6.inrae.fr/means). The Agribalyse 2022 model set was selected to 80 calculate the emissions. The models associated are named in dataset_models_MEANS. The LCI 81 generated were exported in Simapro software then adapted to the context. Firstly, the electricity mix was modified from French (data set by default in MEANS-InOut) to Greek. Secondly, the 82 electricity consumption related to the cold storage of milk is separated from the rest of electricity consumption (as the information was available and should be valuable for the data users). 83 The related dataset is (FAIRCHAIN)CS-Gre_raw_data_milk_production.tab. 84 85

86 3.1.4.2.0. Transformation. The dataset at the cheese factory represents one-year production, 87 involving more milk than produced by the 8 farms for which specific data were available 88 ((FAIRCHAIN)CS-Gre_LCI_one_year_production). Following, the judgement of the dairy representative about the representativity of the sample, the goat's milk is taken as proxy for goat's milk 89 and an average sheep milk has been considered as input for the cheese factory, based on a 90 weighted average of the 7 sheep's milks. 91 92

$$ \text{Inventory}_{1 \text{ kg average sheep milk}} = \sum_{i} \text{Inventory}_{1 \text{ kg of sheep milk from farm i}} * \frac{Q_i}{Q_T} $$

93 Where $Q_i$ is the quantity of milk produced at farm i and $Q_T$ is the total quantity of sheep 94 milk produced in the 7 studied farms. The collection and transportation of the milk from farms 95 to the cheese factory is modelled in the same way, based on the weighted average distance from 96 farms to the cheese factory. 97

97 Other data at the cheese factory are based on specific data and include:

98 - The storage at factory, including tanks and energy;
99

- The processing, including ingredients (salt, rennet and lactic bacteria), energy (electricity and heat) and water;

100

- The cleaning, including water, energy and detergents (nitric acid and sodium hydroxide);

101

- The wastewater treatment of water and whey.

102

**3.1.4.3.0. Packaging, distribution and consumption.** As this part of the inventory was not part of the perimeter under FAIRCHAIN project, it should be only considered as a first approach aiming at representing being included in the whole value chain. However, it provides valuable inputs from the cheese factory and has been judged relevant to be included in the dataset.

103

104

105

106

107

108

109

110

111

112

Four types of packaging and their respective shares in the whole cheese packaging were modelled based on specific data provided by the cheese factory: two tin containers, one wood barrel and one plastic container((FAIRCHAIN)CS-Gre_LCI_packaging.tab). The repartition between those packaging is given in (FAIRCHAIN)CS-Gre_LCI_one_year_production. In the absence of specific data, the packages were considered managed following generic mixes available in Ecoinvent database (FAIRCHAIN)CS-Gre_LCI_packaging.tab).

113

114

115

116

117

The transport to wholesalers was extrapolated based on the three biggest wholesalers (that represent 25% of the total volume). In the same way, the transport to stores was modelled based on the three biggest volumes delivered by the biggest wholesaler (100% of the total volume of the wholesaler). This method has been validated by the cheese factory as representative of its market.

118

119

120

Finally, the transport to consumer and the storage at home were modelled to consider the whole value chain. As no specific data were available, this is based on generic literature data and subject to high uncertainty.

121

**3.1.4.4. Databases.** Agribalyse 3.0 and Ecoinvent 3.8 databases are used for background data.

122

**3.1.5. Life cycle impact assessment**

123

124

The LCIA is realized using Simapro 8.3 and EF 3.0 as characterization method. It is compiled into two separated files:

125

126

127

128

129

130

131

132

133

- (FAIRCHAIN)CS-Gre_LCIA_milk_production_contributions: it presents LCIA at farm for the production of all milks involved as well as for the weighted average for sheep milk. For each farm, for each indicator, the contributions are given for direct emissions, feedstock (wheat straw, grass, barley and water), the building, the electricity consumption, the water used for cleaning and the litter (wheat straw).

- (FAIRCHAIN)CS-Gre_LCIA_one_year_value_chain: it presents LCIA for the whole value chain for one-year production. For each indicator, contributions are details by subprocesses. They are given in absolute value, related to the unit of the indicator (top table) and relatively to the total impact (bottom table).

134

## Ethics statements

135

136

This work did not involve human subjects or laboratory animal, therefore did not meet any ethical issues.

137

## Declaration of Competing Interest

138

139

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

140

## Data availability

141

(FAIRCHAIN)CS-Gre_datapaper (Original data) (entrepot.recherche.data.gouv.f)
142 **CRediT Author Statement**

143 **Samuel Le Féon:** Conceptualization, Methodology, Investigation, Software, Writing – original draft; **Andreas Papadakis:** Conceptualization, Writing – review & editing, Data curation;

144 **Gwenola Yannou-Le Bris:** Conceptualization, Writing – review & editing; **Julie Auberger:** Software, Conceptualization, Writing – review & editing; **Dimitrios Chatzitheodorou:** Data curation,

145 Writing – review & editing; **Joël Aubin:** Conceptualization, Writing – review & editing; **Caroline Pénicaud:** Conceptualization, Writing – review & editing, Supervision.

146 **Caroline Pénicaud:** Conceptualization, Writing – review & editing, Supervision.

147 Writing – review & editing; **Joël Aubin:** Conceptualization, Writing – review & editing; **Caroline Pénicaud:** Conceptualization, Writing – review & editing, Supervision.

148 **Caroline Pénicaud:** Conceptualization, Writing – review & editing, Supervision.

149 **Acknowledgments**

150 This project has received funding from the European Union's Horizon 2020 research and in-

151 novation programme under grant agreement No 101000723. This document reflects only the au-

152 thors' view. The European Commission is not responsible for any use that may be made of the

153 information it contains.

154 The authors thank the members and colleagues of FAIRCHAIN for great discussions. The au-

155 thors also thank the members of AgorACV, the French regional Western network on LCA.

156 The authors are most grateful to MEANS-INRAE-CIRAD platform for its contribution in achiev-

157 ing the here-presented work.

158 This research was funded, in whole or in part, by European Union's Horizon 2020 research

159 and innovation programme under grant agreement no. 101000723. A CC-BY public copyright

160 license has been applied by the authors to the present document and will be applied to all

161 subsequent versions up to the Author Accepted Manuscript arising from this submission, in ac-

162 cordance with the grant's open access conditions.

<figure><img src="image_4.png" /></figure>

163

164 **References**

165 [1] A. Cortesi, L. Dijoux, G. Yannou-Le Bris, C. Pénicaud, Explaining the Differences between the Environmental Impacts of 44 French Artisanal Cheeses, Sustainability 14 (2022) 9484, doi:10.3390/su14159484.

166 [2] W. Finnegan, M. Yan, N.M. Holden, J. Goggins, A review of environmental life cycle assessment studies examining cheese production, Int. J. Life Cycle Assess. 23 (2018) 1773–1787, doi:10.1007/s11367-017-1407-7.

167 [3] ISOISO-14040:2006 Environmental management–life cycle assessment–principles and framework, International Organization for Standardization, 2006.

168 [4] G. Gésan-Guiziou, B. Husing, K. Ostergren, A. Papadakis, T. Zahariadis, Challenges and working practices for the application of Blockchain in Intermediate Dairy Value Chains, in: 2022. https://hal.inrae.fr/hal-03695998 (accessed January 27, 2023).

174