Supplemental Material 2:Description of the methodological approach for the evaluation of environmental impact indicators
1.Assessment of impacts of raw products at farm level
1)Description of the French diagnostic tool used to assess environmental impacts and perimeter
Environmental data were derived from the French diagnostic tool DIALECTE(1). DIALECTE is a comprehensive tool developed by Solagrowhich aims to describe farming systems and to carry out an agro-environmental diagnosis of farms using a global approach at farm scale. To date, DIALECTE database includes information from 2,086 farms with various agricultural production systems, in particular organic farming,throughout France. A total of 46% of farms included in the DIALECTE database followed certified organic practices.
Information collected by DIALECTE allowed estimating the environmental impacts at farm level of 60 raw agricultural products using the Life Cycle Assessment method (LCA). Here, the perimeter of LCA was limited tothe agricultural production step. Hence, the upstream processes were included in the assessment such as the production of inputs or energy provision.Conditioning, transport, processing, storage and recycling were excluded from the analysis. This limitation should be considered as relative since most environmental impacts generally occur duringthe agricultural phase(2–4).Some exceptions should be noted such asalcoholic beverages which require a high level of processingand bottlingorfruit and vegetables when transported by plane.
The choice of DIALECTE pertained to its great diversity of data as basedon real French farms with various types of farming systems. To our knowledge, apart data from the Agribalyse project(5)in which organic data are scarceDIALECTE is to date the only French database that coverssuch a large panel of data for both organic and conventional agricultural products, making it possible the calculation of LCA-based indicators for thewhole individual diet (representing our objective).
2)Description of the indicators used for impact assessment of raw agricultural products
Primary energy consumption
The primary energy consumption is defined by the cumulative energy demand (CED) method(6),commonly used in LCA studies. Primary energy consumptionisdirectly computed within DIALECTE in accordance with calculation module of Dia’terre®(7).
Most energy consumptionwas evaluated at farm level.Allocations of energy consumption at farm scale between crops and livestock buildings were made using generic coefficientsof energy consumption. Table 1 shows the different sources of energy consumption and the nature of data used to allocate the primary energy consumption of farm between agricultural productions.
Table 1: Sources of energy consumption and corresponding allocations between agricultural productions
Sources of energy consumption / Survey data / AllocationsDirect energy (without irrigation)
Fuel
(Fuel, lubricants, diesel and petrol) / Data at farm level / Allocation of energy consumption between crops and livestock buildings in proportion to their theoretical consumption
Gas (propane, butane, natural gas)
Electricity
Direct energy for irrigation
Fuel / Data at farm level / Allocation of energy consumption between irrigated cropsin proportionto their theoretical water consumption
Electricity
Indirect energy
Livestock and veterinary products / Data at farm level / Not included
Mechanization / Allocation of energy consumption between crops in proportion of land occupation
Buildings (<30 years)
Plastic sheetings
Silage preservatives
Fertilizers / Data at crop level / No allocation needed
Pesticides
Feed (forage and feed concentrate) / Data at farm level / Allocation of energy consumption between animals in proportion of their consumption
Greenhouse gas emissions (GHGEs)
We calculated the Global Warming Potential for a 100-year time horizon (GWP100)of the three main greenhouse gasesin agricultural production (carbon dioxideCO2, methane CH4 and nitrous oxideN2O). The GWPs are expressed in kg CO2eq. Their calculation was based on the methodologydeveloped in the tool Dia’terre®(7), in compliance with the IPCC (Intergovernmental Panel on climate change) methodology. The GWP100 (Global Warming Potentialfor a 100-year time horizon)of CH4is equal to 23 kg CO2eq/kgand the GWP of N2O is equal to 296 kg CO2eq/kg.
The GHG emissions of land use change and carbon storage were not included.
Table 2 shows the different sources of GHG emissions taken into account in the LCA andtheoretical GHGEs factors to assign the emissions between crops and livestock buildings.
Table 2: Sources of GHG emissions and corresponding allocations between agricultural productions
Sourcesof GHG emissions / Survey data / AllocationsDirect energy
Direct energy without irrigation
(fuel, gas, electricity) / Data at farm level / Allocation of GHGEsbetweencrops and livestock buildings in proportionto their theoretical GHGEs
Direct energy for irrigation
(fuel, electricity) / Data at farm level / Allocation of GHGEs between irrigated crops in proportionto their theoretical water consumption
Indirect energy
Mechanization, plastic, building (< 30 years), silagepreservatives and veterinary products / Data at farm level / Allocation of GHGEs between crops in proportion of land occupation
Fertilizers and pesticides / Data at crop level / No allocation needed
Feed (forage and feed concentrate) / Data at farm level / Allocation of GHGEsbetween animals in proportion of their consumptionof forage and feed concentrates.
Diffuse emissions
Enteric fermentation / Data by domestic animal category / No allocation needed
Direct emission of N2O (Application of nitrogen fertilisers and manure, nitrogen excreted during grazing, mineralization of crop residues) / Data at crop level
Indirect emission of N2O (atmospheric deposition, runoff and leaching of reactive nitrogen)
Land occupation
Land occupation corresponds to the area required to produce raw agricultural products, withoutconsidering the duration of the land use. Itis expressed as the inverse of yield, in m2.kg-1. This indicator differs from the LCA indicator land use, expressed in m2.kg-1.year, which reflects the surface of land occupied over a period of time.Both indicators are similar when the production period is 1 year, which corresponds to most agricultural production cycles.
In the case of the 29 types of vegetables, the impacts were calculated using the average yield between 2010 and 2015 from the agricultural annual French statistics.As the French statistics provided data for conventional farming only, we used a rebate coefficient for organic farming as described by de Ponti et al (8), namely 14% for salads, 41% for strawberries and 23% for all other vegetable crops.Regarding vegetable crops, we distinguished between vegetables produced in heated greenhouse (conventional tomatoes and cucumber), cold greenhouse (organic tomatoes and cucumber, eggplant, sweet pepper, lamb’s lettuce, strawberry) or in open-field (all other vegetables), for both organic and conventional methods of production, as greenhouse has a considerable impact on energy and GHG values.
For animal production, the land occupationwas calculated as the sum of the areas needed for pasture and feed production, including purchased feed.Areas related to livestock farm facilities were excluded, as they are negligible compared to areas required for feed production and grazing.
3)Categorization of specific raw agricultural products present in DIALECTE
Some agricultural products available in DIALECTEwith a higher level of detail than in the BioNutriNet database were aggregated into one single BioNutrinetproduct (see Table 3) using weighting coefficientsfromthe Annual Agricultural Survey from the French Ministry of Agriculture(9).
Table 3: Weighting coefficientsused for the categorizationof some specific raw agricultural products
BioNutriNet agricultural product / Dialecte agricultural product / ProportionOlive / Black olive / 0.5
Green olive / 0.5
Chicken / Standard chicken / 0.88
Labelled chicken / 0.12
Bovine meat / From cattle rearing and fattening farms / 0.66
From dairy cattle / 0.34
Sheep meat / Sheep fattening / 0.9
Dairy Sheep / 0.1
Moreover, the «cherry tomatoes» and «fresh tomatoes» in the BioNutrinet list were considered coming from heated greenhouses, whereas «cooked tomatoes» and «tomato pulp» were considered coming from open fields.
4)Distribution of indicators and completion of missing data
Using the methodology described above, we obtained the environmental impacts of 62 raw agricultural products from 2,086 farms surveyed in DIALECTE were assessed using the three before-mentioned indicators (greenhouse gas emissions, primary energy consumption and land occupation).Regarding organic farming, the number of dataavailable ranged from 2 (duck) to 355 (beef meat) (IQR: 34; 348)whereasregarding conventional farming,the number rangedfrom 1 (nuts) to 408(soft wheat) (IQR: 40; 348).
Medians were used since outliers are relatively common in this type of survey.No distinction was made between French regions as it would have required substantial additional calculations and assumptions while being out of the scope of this study.However, we assessed the representativeness of DIALECTE sample for each raw agricultural product and conducted additional field surveys whennecessary.
Whenever possible, the impactsof agricultural raw products were assessed using data from DIALECTE.We completedthe database usingpublished literature and Agribalyse data in particular for some raw products,such as seafood (N=6), honey (N=1), tropical or imported products (N=12) and for products with too few datain DIALECTE(N=13).
Appendix 1details the origin andvalues of the three environmental indicators obtained for the 92 raw conventional and organicagricultural products used in the present study(60 from DIALECTE and 32 from literature searches).
2. Methodology for obtaining the impacts of food items as consumed from those of raw products
To compute the environmental impacts of food itemsfrom those of raw agricultural products,we conducted a set of conversions.
1.Description oftheorg-FFQ itemincluded in the food frequency questionnaire and translation in simple ingredients
Two-step decomposition was applied to obtain ingredient consumption (corresponding to simple constituent) from FFQ consumption.
Org-FFQ (Organic Food Frequency Questionnaire)comprises 264 generic items to estimate food consumption. Most of the itemswere composed of different sub-items. For example, the item “pasta”encompasses: vermicelli, pasta, Chinese noodles, egg pasta, fresh pasta, and egg and fresh pasta spinach flavour.
To determine the weight of each sub-item within an item, we used the frequency of consumption of thesesub-items by gender, based on the 24-h dietary records tool of the NutriNet-Santé study. The 24-h dietary records database contains a very large number of food items(N=3,276) but does not distinguish organic products from conventional ones(10). Finally, we assess asex-specific list of sub-items and their contribution toeach item.
In a second step, each sub-item, in case of composed food, were translated into ingredients according to recipes validated by a group of nutritionists and dieticians. Finally, the 264 Org-FFQ food items were decomposed into 766 ingredients (i.e. simple constituents corresponding to single raw agricultural products).
For feasibility reasons, the environmental impacts of the ingredients which accounted for at least 5% of the item composition were computed, corresponding to 442 ingredients.
On the basis of environmental impacts determined for raw agricultural products, we then determined the environmental impacts of ingredients and finally the environmental impacts of Org-FFQ items.
2.Conversion from raw agricultural products to ingredients
Some ingredients come from the treatment of raw agricultural products. In some cases, the transformation of one raw product leads to several co-products. In that case,to disentangle the impacts between the various co-products, economic allocation was taken into account.
Economic allocations were estimated for each ingredient accounting for the quantities of each co-product obtained during the same processing and their price.
We also applied cooking and edibility coefficients(11,12)to obtain impacts for the ingredient as consumed, using data from NutriNet-santé composition database.
Data of a total of 59 ingredients accounting for more than 5% in at least one item composition were not available. Missing information coveredsome foodsimported from tropical areas, some alcoholic beverages, grains or yeast. For these 59 ingredients, the environmental impacts were considered as null. Although probably rather marginal, we acknowledge this issue as a limitation.
3.Conversion from ingredients to food items
The environmental impact of each item (100g) was finally obtained by summing up, for all constituting ingredients,the product of its environmental impact (for 100g) byits contribution(<1) to the itemand then multiplied by 100.
About 75% of the food items had more than 98.8% of their composition covered by the 442 ingredients. When an ingredient was missing (because it accounted for less than 5% in at least one item composition)for a given item, environmental impacts were ”standardized” for 100g of the item.
The items especially concerned by the standardization were fish products, jam, cheeses and dressings.
Finally, theenvironmental impactswere determined for most of the Org-FFQ items inboth their organic and conventional forms.However, no data were available for 22 items for primary energy consumption, 21 items forGHGEs and 25 items forland occupation. Missing data included the following food items: water, certain alcoholic beverages, or tropical fruit or vegetables, grains and oils.
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Appendix1:Environmental impacts of raw agricultural products in organic and conventional form
Raw agricultural products / Data source / Typeof production (organic or conventional) / Primary energy consumption (MJ/kg) / Greenhouse gas emissions (kgCO2eq/kg) / Land occupation (m2/kg) / Number of cases / ReferencesVegetables produced in heated greenhouse
Tomato / AGRIBALYSE® / CA / 33.760 / 2.080 / 0.030 / - / (13)
Cucumber / AGRIBALYSE® adaptation1 / CA / 137.236 / 8.455 / 0.122
Vegetables produced in cold greenhouse
Tomato / AGRIBALYSE® / OA / 3.500 / 0.200 / 0.100 / - / (13)
cucumber / AGRIBALYSE® adaptation 1 / OA / 5.543 / 0.317 / 0.158
Aubergine / CA / 14.167 / 0.833 / 0.294
OA / 13.369 / 0.764 / 0.382
Strawberry / OA / 26.738 / 1.528 / 0.764
CA / 28.333 / 1.667 / 0.588
Peppers / OA / 14.205 / 0.812 / 0.406
CA / 15.052 / 0.885 / 0.313
Lamb’s lettuce / CA / 96.333 / 5.667 / 2.000
OA / 90.909 / 5.195 / 2.597
Vegetables produced in open-field
Carrot / AGRIBALYSE® / CA / 0.750 / 0.070 / 0.150 / - / (13)
OA / 0.890 / 0.060 / 0.240
Garlic / DIALECTE / CA / 2.708 / 0.270 / 1.429 / 348 / (13–15)
OA / 4.465 / 0.336 / 1.855
Artichoke / CA / 3.792 / 0.378 / 2.000
OA / 6.251 / 0.470 / 2.597
Red beetroot / CA / 0.412 / 0.041 / 0.217
OA / 0.679 / 0.051 / 0.282
Chard / CA / 0.558 / 0.056 / 0.294
OA / 0.919 / 0.069 / 0.382
Celery stalk / CA / 0.558 / 0.056 / 0.294
OA / 0.919 / 0.069 / 0.382
Celeriac / CA / 0.512 / 0.051 / 0.270
OA / 0.845 / 0.064 / 0.351
Broccoli / CA / 2.106 / 0.210 / 1.111
OA / 3.473 / 0.261 / 1.443
Brussels sprouts / CA / 1.053 / 0.105 / 0.556
OA / 1.736 / 0.131 / 0.722
Cauliflower / DIALECTE adaptation1 / CA / 1.053 / 0.105 / 0.556 / 348 / (3,13,14)
OA / 1.736 / 0.131 / 0.722
Cabbage / CA / 0.903 / 0.090 / 0.476
OA / 1.488 / 0.112 / 0.618
Cabbage for sauerkraut / CA / 0.903 / 0.090 / 0.476
OA / 1.488 / 0.112 / 0.618
Zucchini / CA / 0.451 / 0.045 / 0.238
OA / 0.744 / 0.056 / 0.309
Shallot / CA / 0.862 / 0.086 / 0.455
OA / 1.421 / 0.107 / 0.590
Endive chicon / CA / 0.824 / 0.082 / 0.435
OA / 1.359 / 0.102 / 0.565
Spinach / CA / 0.948 / 0.094 / 0.500
OA / 1.563 / 0.117 / 0.649
Fennel / CA / 0.948 / 0.094 / 0.500
OA / 1.563 / 0.117 / 0.649
Green bean / CA / 1.580 / 0.157 / 0.833
OA / 2.604 / 0.196 / 1.082
Melon / DIALECTE adaptation 1 / CA / 0.998 / 0.099 / 0.526 / 348 / (13–15)
OA / 1.645 / 0.124 / 0.684
Turnip / CA / 0.790 / 0.079 / 0.417
OA / 1.302 / 0.098 / 0.541
Onion / CA / 0.451 / 0.045 / 0.238
OA / 0.744 / 0.056 / 0.309
Green pea / CA / 2.370 / 0.236 / 1.250
OA / 3.907 / 0.294 / 1.623
Leek / CA / 0.612 / 0.061 / 0.323
OA / 1.008 / 0.076 / 0.419
Pumpkin / CA / 0.702 / 0.070 / 0.370
OA / 1.158 / 0.087 / 0.481
Radish / CA / 1.185 / 0.118 / 0.625
OA / 1.953 / 0.147 / 0.812
Lettuce / CA / 0.729 / 0.073 / 0.385
OA / 1.076 / 0.081 / 0.447
Salsify / CA / 0.632 / 0.063 / 0.333
OA / 1.042 / 0.078 / 0.433
Open-field tomato / DIALECTE adaptation 1 / CA / 0.237 / 0.024 / 0.125 / 348 / (13–15)
OA / 0.391 / 0.029 / 0.162
Broad beans / CA / 3.160 / 0.315 / 1.667
OA / 5.209 / 0.392 / 2.165
Apricot / DIALECTE / CA / 3.332 / 0.304 / 0.924 / 8 / (14,16)
OA / 2.977 / 0.225 / 3.333 / 8
Cherry / CA / 6.905 / 0.695 / 3.030 / 23 / (14)
OA / 10.257 / 0.409 / 2.500 / 9
Fig / CA / 3.550 / 0.303 / 2.000 / 4
OA / 4.759 / 0.326 / 1.250 / 3
Olive / CA / 6.485 / 0.722 / 5.441 / 40 / (14,17,18)
OA / 5.529 / 0.420 / 5.115 / 48
Black olive / CA / 6.684 / 0.758 / 5.000 / 21
OA / 4.573 / 0.410 / 4.348 / 23
Pear / CA / 1.686 / 0.083 / 0.400 / 9 / (13,14,16)
OA / 2.393 / 0.145 / 0.667 / 10
Apple / CA / 0.677 / 0.056 / 0.253 / 57 / (13,14)
OA / 1.273 / 0.099 / 0.667 / 37
Plums / DIALECTE / CA / 2.320 / 0.114 / 0.520 / 22 / (13,14)
OA / 3.609 / 0.221 / 1.623 / 12
Peach and nectarine / AGRIBALYSE® / CA / 1.400 / 0.170 / 0.440 / - / (13)
OA / 1.460 / 0.190 / 0.780
Wine grape / CA / 3.09 / 0.29 / 1 / (13)
OA / 2.7 / 0.26 / 1.08
Orange and clementine / Other works / CA / 2.870 / 0.130 / 0.370 / - / (15,19)
OA / 2.380 / 0.040 / 0.430
Lemon and grapefruit / CA / 2.850 / 0.120 / 0.350
OA / 2.100 / 0.040 / 0.390
Apple cider / Other works / CA / 0.20 / 0.02 / 0.42 / - / (IDRAC, 2017)
OA / 0.13 / 0.01 / 0.27
Kiwi* / CA / 0.51 / 0.59 / (FAO; Kiwi France;and SCEES, 2012)
Avocado* / CA / 1.02 / Average yield of Mexico
Banana* / CA / 2.16 / 0.22 / 0.23 / (AgriclimateChange project, 2010-2013 (Canary Islands, Spain))
Oat / DIALECTE / CA / 2.856 / 0.340 / 2.500 / 40 / (13–15)
OA / 2.728 / 0.294 / 3.333 / 70
Dural wheat / CA / 3.631 / 0.505 / 2.198 / 202
OA / 3.647 / 0.371 / 4.395 / 53
Soft wheat / CA / 2.740 / 0.380 / 1.538 / 408
OA / 2.453 / 0.266 / 3.125 / 301
Rape / CA / 5.660 / 0.831 / 3.333 / 217
OA / 5.544 / 0.615 / 6.667 / 30
Grain maize / DIALECTE / CA / 2.281 / 0.283 / 1.000 / 229 / (13–15)
OA / 1.823 / 0.144 / 1.505 / 98
Sunflower / CA / 4.425 / 0.491 / 4.167 / 211
OA / 3.980 / 0.333 / 5.000 / 133
Buckwheat / CA / 4.340 / 0.377 / 5.000 / 7 / (20)
OA / 5.853 / 0.737 / 10.000 / 32
Soya / CA / 2.672 / 0.219 / 3.333 / 62 / (14,15,21,22)
OA / 3.263 / 0.269 / 4.000 / 67
Sugarbeet / CA / 0.201 / 0.030 / 0.126 / 52 / (14,15,21,22)
OA / 0.144 / 0.019 / 0.167 / 3
Potato 3 / CA / 0.750 / 0.080 / 0.325 / 116 / (13–15,21,22)
OA / 0.924 / 0.067 / 0.227 / 48
Lens3 / CA / 5.330 / 0.399 / 6.557 / 10
OA / 5.201 / 0.410 / 7.452 / 66
Oilseedflax 3 / CA / 6.558 / 1.132 / 5.003 / 15
OA / 6.666 / 0.642 / 7.697 / 12
Rye / DIALECTE / CA / 2.357 / 0.500 / 2.051 / 15 / (3,8,13,14,21)
OA / 1.891 / 0.211 / 2.699 / 65
Rice / Otherworks / CA / 8.910 / 2.480 / 1.630 / - / (23)
OA / 8.550 / 2.800 / 2.270
Robusta coffee 2 / AGRIBALYSE® / CA / 9.7 / 1.42 / 4.55 / - / (13)
Cacao 2 / CA / 26.94 / 3.61 / 19.61
Tea / Other works / CA / 0.4 / 0.02 / 7.3 / (24)
OA / 0.34 / 0.01
Sugar cane2 / CA / 0.54 / 0.08 / 0.12 / (25)
Honey4 / OA / 1.50 / 1.40 / (Les agriculteurs Bio de PACA, 2017)
Cow’s milk / DIALECTE / CA / 2.971 / 1.023 / 2.155 / 179 / (13,15,26)
OA / 2.553 / 0.937 / 2.905 / 189
Sheep milk2 / AGRIBALYSE® / CA / 2.22 / 1.44 / 3.41 / - / (13)
OA / 2.22 / 1.44 / 3.41
Goat’s milk 2 / AGRIBALYSE® / CA / 6.45 / 0.93 / 2.16 / (13)
OA / 6.45 / 0.93 / 2.16
Beef meat / DIALECTE / CA / 23.72 / 10.74 / 28.73 / 374 / (13,27)
OA / 22.65 / 11.68 / 36.63 / 355
Sheepmeat / CA / 22.93 / 19.07 / 59.00 / 171 / (15,28,29)
OA / 32.75 / 18.73 / 65.18 / 109
Pork 5 / DIALECTE and AGRIBALYSE® / CA / 15.90 / 2.78 / 3.35 / 20 / (13,15)
OA / 16.57 / 3.46 / 10.64 / 16
Chicken / DIALECTE / CA / 15.25 / 1.98 / 4.35 / 51
OA / 16.44 / 2.57 / 8.43 / 34
Turkey / CA / 18.27 / 4.01 / 3.67 / 13
OA / 12.26 / 2.41 / 5.57 / 5
Duck / CA / 16.46 / 2.01 / 3.08 / 9 / (15)
OA / 16.34 / 0.45 / 0.08 / 2
Eggs / AGRIBALYSE® / CA / 11.29 / 1.77 / 3.09 / (13)
DIALECTE / OA / 19.01 / 1.91 / 5.13 / 35
Rabbit 2 / AGRIBALYSE® / CA / 18.02 / 2.66 / 4.45
Trout and farmed fishs / Other works / CA / 24.34 / 2 / (13)
Salmon / CA / 26.9 / 2.07 / (30,31)
Sport fish / CA / 23.21 / 1.18 / (32–34)
Shellfish / CA / 38.00 / 2.92 / (33,35)
Shell / CA / 0.51 / 0.04 / (33)
CA: conventional agriculture and OA: Organic agriculture