SLU - Swedish University of Agricultural Sciences (SLU), Department of Energy and Technology

Farm-gate carbon footprints in kg CO2e per kg for raw food commodities in 79 producing countries, split by process, from SAFAD, the food and diet assessment tool of the Swedish University of Agricultural Sciences (SLU).

Research

Food

SpecialistRestricted licence

Publisher's page Browse 13,523 factors

Factors

13,523

Values

13,523

One per year and method

Countries

80 regions, sub-national included

Edition

1.4.3

published 3 Sept 2026 · all versions

Last loaded

6 Oct 2026

Report a newer version

Overview

SAFAD (Sustainability Assessment of Foods and Diets) is published by the Department of Energy and Technology of the Swedish University of Agricultural Sciences (SLU). The tool lets researchers and planners compute the environmental and social footprint of foods and diets; its default data sits in the open SLU-foodsystems/safad repository. The method is described in Röös et al. 2025, Journal of Cleaner Production 519, 146002, and introduced by the Stockholm Resilience Centre; an open-access copy is in SLU's repository.

We load the footprint file of release 1.4.3 (tag v1.4.3, September 2026). Each row is a raw primary commodity, coded with EFSA's FoodEx2 food classification and mapped to an FAO Supply Utilization Account item, in one producing country. SLU has announced a version 2.0 with updated environmental data; it was not released when we loaded 1.4.3.

At a glance

Publisher: Swedish University of Agricultural Sciences (SLU), Department of Energy and Technology
Kind: Research
Scope: Specialist
Home region: Sweden
Edition: 1.4.3
Licence: Restricted licence (slu-safad-repo-mit-data-unstated)

Open data

How this works

What open-climate.ai standardised

over the publisher's own fileHow we standardise

One category axis

13,523 of 13,523 factor values mapped to one category

13,523 keep the publisher's own classification too

Learn more 6 checks behind this

Coded regions

80 regions as ISO or registry codes

Learn more 3 checks behind this

Canonical units

1 canonical unit in 1 unit families, raw unit kept

Learn more 4 checks behind this

Warming potentials

0 factor values recalculated on AR6

13,523 factor values already on AR6

0 factor values left on the publisher's GWP

Learn more 7 checks behind this

6 more things standardised

Declared boundaries

6 boundary codes

2,490 factor values state in, out or varies for each scope term

Learn more 7 checks behind this

Parts and parents

10,968 factor values grouped under 2,555 parents

Use a part on its own, or the parent when you want the whole.

Learn more 3 checks behind this

Data quality

13,523 of 13,523 factor values rated on one quality tier

Learn more 7 checks behind this

Languages

English: 100.0% of factor values

German: 7.6% of factor values

French: 8.0% of factor values

Learn more 11 checks behind this

Traceable to the source

2,855 source rows archived

299 rows skipped, each with a reason

Learn more 4 checks behind this

Stable addresses

Slugs never break

Learn more

Audit checks

73 passed3 enforced when loadedlast run 5 Oct 2026

Checks we run on every load to keep the data above trustworthy. Counts are for this library; the grey figure is the same check across all libraries. Point at the i to see why a check matters.

What the statuses mean How checks are counted Why we check How checks are grouped

One category axis

Learn more

Every source category maps to our vocabulary
Enforced when loaded
Why it matters A factor with no category drops out of every category filter and comparison. The load stops rather than serve one.
The publisher's classification is kept
Not recorded
Why it matters You can still find a factor the way the publisher filed it, and check our mapping against theirs.
Every classification level has a valid parent
Not recorded
Why it matters A broken tree hides factors from browse and puts them in the wrong category totals.
Every product code comes with the codes above it
Not recorded
Why it matters In product codes like HS or CPC, a search for a chapter should reach every code inside it. A missing level hides the factor from that search.
A publisher's own classification is used only by that publisher
Not recorded
Why it matters A publisher's own tree only makes sense inside its library. Filed under another publisher's codes, a factor would show up in categories that do not describe it.
A standard classification code has one label in every library
Passed
Why it matters Codes like NACE or NAICS are meant to link libraries. If one code carries two labels, you cannot tell whether both libraries mean the same activity.

Coded regions

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Every region is a known code
Enforced when loaded
Why it matters Free text like “France continentale” cannot be filtered or joined to your own data. A code can.
No named region is filed under a broader one
Not recorded
Why it matters A French factor filed as World would be applied to the wrong country, or lose to a global value in a search for France.
Every region sits in the world hierarchy
Passed
Why it matters A search for Europe has to reach France. A region outside the hierarchy is invisible to broader searches.

Canonical units

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Every unit is a known code
Enforced when loaded
Why it matters Activity data only multiplies correctly when the unit is exact. An unknown unit stops the load.
One source unit maps to one unit
Not recorded
Why it matters If one of the publisher's units were read as two different units, factors that share it would give inconsistent footprints.
A unit label means the same in every library
Passed
Why it matters Comparing two libraries is only safe when a label like t.km means tonne-kilometre in both.
A unit label that names no basis folds one way
Passed · 1 in all libraries
Why it matters A label like GJ says nothing about the heating value behind it. If the same bare label folds to two different units, two factors that look alike are not comparable.

Declared boundaries

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Every boundary states what it includes
Not recorded
Why it matters Cradle-to-gate and full life-cycle values can differ several times over. Without a stated boundary you cannot tell which you are adding up.
Boundary scope terms are known codes
Not recorded
Why it matters Consistent terms let you keep exactly the life-cycle stages your inventory needs.
No two factors for the same activity partly overlap in scope
Not recorded
Why it matters Two totals that share some stages but not all cannot safely be added or swapped: adding them counts the shared stages twice.
Separate stages of one activity are linked as parts
Not recorded
Why it matters Stages served as unrelated factors give no total, so you may use one stage and miss the others.
Every part of a factor states its boundary
Not recorded
Why it matters A part with an unknown boundary cannot be told apart from the other parts, so you cannot pick out, say, the combustion share of a total.
Every biofuel counted with its biogenic CO2 says how much
Passed
Why it matters Some publishers count the CO2 a burnt biofuel releases and others leave it out. Search tells the counting ones apart by their biogenic CO2 figure, so a factor without it would be offered to someone who asked to leave that CO2 out.
No recycling credit is hidden inside a life-cycle total
Passed
Why it matters A negative total may be a credit for avoided emissions. Filed as a life-cycle burden, it would quietly subtract emissions from your footprint.

Warming potentials

Learn more

Methane and nitrous oxide figures match the stated GWP
Not recorded
Why it matters If a gas's CO2e is not its mass times the stated GWP, the GWP label is wrong, and converting the value to another GWP version would give a wrong result.
Every convertible value has its AR6 version
Not recorded
Why it matters Reporting now asks for AR6. Mixing AR5 and AR6 shifts methane-heavy totals by several percent.
CO2e totals leave out what their basis excludes
Passed
Why it matters A value's basis names the carbon pools its total leaves out. When the gas breakdown shows the total counting one of them anyway (biogenic CO2, land-use change, or biogenic methane on a fossil-only value), the label or the total is wrong.
Values that exclude a carbon pool list the gases behind the total
Passed · 50,262 in all libraries
Why it matters With no breakdown by gas, nothing can confirm that a fossil-only or biogenic-CO2-excluded total really leaves those pools out. The value rests on the publisher's word alone.
Standardised figures keep every gas the publisher lists
Not recorded
Why it matters The comparable figure we serve must carry each gas the publisher reported. A lost gas makes the breakdown disagree with the total and hides that gas from you.
Every value states what its CO2e total includes
Not recorded
Why it matters For a biofuel, a total with or without biogenic CO2 can differ widely. Without that convention you cannot tell which one you are comparing.
A library with no AR6 version at all has a recorded reason
Passed · 2 in all libraries
Why it matters Values that cannot be converted to AR6 cannot be compared with AR6 figures. That has to be a documented decision, not something missed at load.

Parts and parents

Learn more

Every part links to a valid parent
Not recorded
Why it matters A part that points nowhere gets summed twice or dropped when you use the parent total.
No factor is an unlinked part of another factor
Not recorded
Why it matters If one stage of a total is also served on its own, beside that total, adding both counts the same emissions twice.
Every factor points to its top parent
Passed · 1 in all libraries
Why it matters Search groups parts under their top factor. A stale link shows a part as a stand-alone result.

Data quality

Learn more

Quality ratings fall inside their scale
Not recorded
Why it matters An out-of-scale rating cannot be compared, so the value would be ranked arbitrarily.
Every zero value is explained
Not recorded
Why it matters A zero can be real (contracted renewable power) or a gap in the data. A gap read as real erases emissions from your total.
No default value is withheld for poor quality
Not recorded
Why it matters A default rated too poor to serve is hidden from search and exports, so that factor is missing for you even when it is the right one.
No implausibly high per-kilogram value is rated reliable
Not recorded
Why it matters Above 1,000 kgCO2e per kg is often a unit slip, such as grams read as kilograms. Rated reliable, such a value could inflate a footprint a thousandfold.
Every quality level gives a recognised reason
Not recorded
Why it matters The reason explains why a value got its quality level. An unrecognised one cannot be filtered on or explained to you.
A zero that is only a gap in the source is withheld
Not recorded
Why it matters A zero with no quality signal, or an implausible regulatory default of zero, is more likely missing data than a real zero. Served, it would erase emissions from your total.
The library is not rated entirely on one fallback quality level
Not recorded
Why it matters When every value gets the same level because the publisher gives no quality signal, the level tells you nothing and cannot rank one value above another.

Languages

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Every factor has an English name
Passed
Why it matters Every factor can be searched and cited in one shared language, whatever the publisher's.
Translations match the current source text
Passed · 310 in all libraries
Why it matters When the publisher rewords a label, an old translation can describe a different activity than the one priced.
Translations follow a corrected source text
Passed · 4 in all libraries
Why it matters When we correct an English label, a French or German label translated from the old wording can still describe what the old wording said.
Recorded translations survive a reload
Passed · 5 in all libraries
Why it matters A reload rewrites a library's labels; a translation we recorded and did not put back leaves that factor without a label in that language.
Every served factor has a name
Not recorded
Why it matters A factor with no name in any language shows as a blank row: you cannot search for it or tell what it measures.
Factors are searched on their English name where one exists
Passed · 20 in all libraries
Why it matters Search matches your query against one name per factor. A name kept in the publisher's language, when an English one exists, is harder to find in English.
Every language with a main name also has a full name
Passed
Why it matters Without the full name, the detail that tells similar factors apart is missing in that language, so two different factors can look identical.
Full names are built from their parts in the same language
Passed
Why it matters A full name must read as the main name followed by its detail. Translated separately, it can drift and describe a slightly different activity.
Every text is labelled with its real language
Passed
Why it matters A French name labelled English would be shown to English readers and matched against English searches.
Every description is available for display and translation
Not recorded
Why it matters A description missing from the per-language text store is not shown in your language, and never gets translated.
Every usage note is available for display and translation
Not recorded
Why it matters Names and notes are served from one text store per language. A note missing from that store is not shown, and never gets translated.

Traceable to the source

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Values traced to one source row agree with each other
Passed
Why it matters Each value traces back to one source row. When values that disagree share a row, it can back only one of them, which weakens that audit trail.
No duplicate factors are served
Passed · 174 in all libraries
Why it matters Identical duplicates split search results and invite counting the same factor twice.
No factor value claims two things that cannot both be true
Passed · 3,243 in all libraries
Why it matters For example, a purchaser price that leaves out retail or delivery, or packaging on an energy unit. One of the two claims is wrong, and you cannot tell which.
No factor value the publisher has withdrawn is still served
Passed · 10,480 in all libraries
Why it matters The publisher's end date for the value has passed. The figure may be out of date, so look for a newer one before you use it.

Other checks

One activity keeps one family across its units
Passed · 9 in all libraries
Why it matters When a publisher prints the same activity per kg and per kWh, the two factors belong to one activity family, with the unit as a choice. Filed as separate activities, they look unrelated, and nothing says they measure the same thing.
An activity's grouping key names only the activity
Passed · 5 in all libraries
Why it matters If the key also carried the unit, country or scope, one activity would split into several, and search would not show you its other versions side by side.
A Creative Commons credit names its licence
Passed
Why it matters CC BY asks you to say which licence applies. A credit that leaves it out makes your attribution incomplete when you copy it.
No note of ours appears in the credit or licence notice
Passed
Why it matters Our own notes on how we handle the data would end up in the credit you reproduce, as if the publisher had written them.
The credit line carries no terms of use
Passed
Why it matters You copy the credit line as it stands. Terms of use belong in the licence notice, which you read rather than reproduce.
Every impact assessment method is a recognised code
Passed
Why it matters Free text in place of a code splits one method into several spellings, so filtering by method misses some of its values.
Summed totals keep their parts' classification
Passed
Why it matters A total takes a classification only when all its parts share it. Otherwise it lands in a category its parts do not support, or misses one they all share.
Green-electricity zeros are not rated below market-based peers
Passed
Why it matters A green-contract zero is the contract's own figure. Marked down for being zero, it would lose to less relevant values when you look up contracted supply.
An avoided credit is linked to the burden it belongs to
Passed
Why it matters Served on its own, a credit reads as a factor in its own right. Linked beside its burden, it applies only where it belongs and is never subtracted twice.
Every value is typed as specific, generic or average
Passed
Why it matters The type says how closely a figure fits the product you bought. Any other word would be invisible to a filter on it.
No battery-electric vehicle carries tailpipe emissions
Passed
Why it matters An electric vehicle has no tailpipe. A non-zero combustion figure means its electricity emissions sit in the wrong place, or are counted twice.
The text of each estimated electricity total matches its current figures
Passed
Why it matters The description of an estimated electricity total states its year, mix, quality and the parts it adds up. If those moved, the text would explain a different number than the one served.
Every estimated factor carries its description in each language
Passed · 16 in all libraries
Why it matters An estimated factor is one we computed, not one a publisher printed. Its description says so and names the data behind it. Without it, you could not tell the estimate from a published figure.
The text of each estimated factor matches its current figures
Passed
Why it matters An estimated factor's description states the year, shares and quality behind it. If those moved, the text would explain a different number than the one served.
A total built on an estimated part is marked as estimated
Passed
Why it matters If the total lost the mark, you would read a figure we partly computed as one the publisher printed.
Every estimate is built only from data we may redistribute
Passed
Why it matters An estimate derived from restricted data would pass that data on under our open licence, which its owner never allowed.
No estimated factor is rated above the data it was built from
Passed
Why it matters An estimate cannot be more reliable than its inputs. Rating it higher would lead you to trust it more than a published figure.
No estimate sits beside a total of unclear scope
Passed
Why it matters When the publisher does not say whether its total includes a stage, our estimate of that stage may count it twice. These cases are listed for review.
No estimate repeats a stage the publisher's total already includes
Passed · 2 in all libraries
Why it matters If the publisher's figure already covers, say, grid losses, adding our estimate of those losses would count them twice and overstate your emissions.
Every factor we complete has all of its estimated parts
Passed · 7 in all libraries
Why it matters If one part, such as grid losses, is missing where the others were estimated, a total built from them silently leaves that part out.
No estimate is served where the publisher printed the figure
Passed · 25 in all libraries
Why it matters When the publisher states the number itself, theirs is the one to use. An estimate beside it would give you two answers to the same question.
We only estimate for publishers whose rule allows it
Passed
Why it matters Some publishers print every part themselves, or are deliberately left as they are. An estimate added to them would mix our numbers into theirs, against the rule set for that library.
Every estimated factor still matches the inputs it was computed from
Passed
Why it matters When an input is revised or withdrawn, the estimate built on it is out of date until it is recomputed.
No estimated total competes with a published one
Passed · 24 in all libraries
Why it matters Where the publisher prints a total for the same activity, region and year, an estimated total beside it would give you two answers to the same question.
The text of each fuel supply-chain estimate matches its current figures
Passed
Why it matters Its description states the year, the figures, the ratio and the quality behind the estimate. If those moved, the text would explain a different number than the one served.
No fuel supply-chain estimate is rated above what its method allows
Passed
Why it matters Each way of estimating a fuel's supply chain has a highest rating it can earn, and an estimate never outranks the combustion figure it builds on. A better rating would lead you to trust it more than it deserves.
Every fuel estimate is built only from data we may redistribute
Passed
Why it matters An estimate derived from restricted data would pass that data on under our open licence, which its owner never allowed.
Every fuel eligible for a supply-chain estimate is classified
Passed
Why it matters The supply-chain estimate depends on which fuel is burned. A fuel nobody has classified gets no estimate, so you would miss that part of its emissions without knowing why.
No fuel estimate is served where the publisher printed the supply-chain figure
Passed
Why it matters When the publisher states the figure itself, theirs is the one to use. An estimate beside it would give you two answers to the same question.
No supply-chain estimate is served for a fuel we deliberately left out
Passed
Why it matters Some fuels are left out on purpose, for instance when no published supply-chain figure fits them. An estimate on one of them would be a number we decided not to stand behind.
Every fuel supply-chain estimate still matches the figures it was computed from
Passed
Why it matters The estimate scales the publisher's combustion figure by a supply-chain ratio taken from other published data. When either is revised or withdrawn, the estimate is out of date until it is recomputed.
Every tagged gas has a known GWP
Passed
Why it matters A kilogram of one named gas is restated in AR6 with that gas's own GWP. A tag the GWP table does not carry would leave the value unconverted, or convert it with the wrong number.
Every fixed group of regions lists what it covers
Passed
Why it matters A group like “Europe outside the EU” with no member list cannot be placed, so its factor values never match a search for any country in it.
Where both exist, the residual mix is shown before the green-tariff zero
Passed
Why it matters Green electricity counts as zero only for buyers who hold the matching certificates. Showing zero by default would understate everyone else's emissions.
Every green-electricity zero is a market-based value
Passed
Why it matters A zero from a green contract only holds for the buyer of that contract. Filed as location-based, it would put a zero on the physical grid.
Every publisher has a rule on whether we estimate its missing parts
Passed
Why it matters For electricity and fuels we can estimate parts a publisher leaves out, such as grid losses or the fuel supply chain. Without a rule, a missing part could be a gap or a deliberate choice, so nothing is estimated until one is set.
Factor descriptions describe the factor, not the whole library
Passed
Why it matters When the same long text is repeated on every factor, it tells you nothing about the one you are looking at and hides what is specific to it.
Every library's licence has its rights recorded
Passed
Why it matters Without them, the library page cannot tell you what you may do with the data: share it, change it or use it commercially.
No fossil electricity mix has a zero fuel supply chain
Passed
Why it matters Electricity with fossil emissions always has a supply chain behind it: extracting and transporting the fuel. A zero there means the chain was priced from the wrong mix. Green power is the exception: its chain covers only biomass, and is a real zero on a grid that burns none.
Every green-electricity zero is exactly zero and says why
Passed
Why it matters A green-tariff factor is zero by rule. Any other number, or a zero with no stated reason, would mean the rule was applied wrongly.
Green-electricity zeros cover power generation only
Passed
Why it matters Certificates cover the power plant's emissions, not grid losses or the upstream fuel chain. A zero on those stages would understate your Scope 2 and Scope 3 figures.
No factor description is too long to display in full
Passed · 28 in all libraries
Why it matters Text beyond the limit is cut short on the factor page, so part of what the publisher wrote shows only in the download.
The library-wide answers on what a factor covers are up to date
Passed
Why it matters Some questions, such as whether a figure includes transport, are answered once for a whole library. If the stored answers fall behind, a factor's details can tell you something we no longer state.
Every library-wide answer applies to at least one factor
Passed · 3 in all libraries
Why it matters An answer about a category or stage the library no longer covers changes nothing you see. It is listed so it can be removed.
Every residual mix has its green-tariff counterpart
Passed
Why it matters Market-based Scope 2 reporting needs both: the residual mix for ordinary contracts and a zero for certified green power. With one missing, you have to find it elsewhere.
Every publisher's quality rating system is read
Passed
Why it matters If we do not read a publisher's rating system, its values are treated as unrated and marked down, although the publisher rated them.
Every factor is filed under the most specific category its source allows
Passed · 1,852 in all libraries
Why it matters Some factors sit in a broad category because their source covers several narrower ones. They are listed so a finer mapping can place them more precisely where the source allows it.
Every factor has a category
Passed
Why it matters A factor with no category drops out of every category filter and comparison. Without this check, a library with no category mapping would load unlabelled, and nothing would say so.
Every categorised factor has a GHG Protocol scope
Passed · 30 in all libraries
Why it matters Without a scope, you cannot tell whether the factor belongs in Scope 1, 2 or 3 of your inventory, and you have to place it yourself.
Single-gas values have their AR6 version
Passed · 5 in all libraries
Why it matters A kilogram of one refrigerant is worth its GWP, so it can be restated in AR6 exactly. Blends and untagged gases stay on their published vintage, which can move a leak's footprint by several percent or more.
No factor answers a question that does not arise for it
Passed · 5 in all libraries
Why it matters Some questions only make sense for some kinds of factor. An answer where the question should not arise is either misplaced, or a sign the kind is too coarse for that factor, so each case is reviewed.

How the audit works

What can I do with this data?

Restricted licence · credit the publisher

safad

Restricted licence · slu-safad-repo-mit-data-unstated

Use it to calculate my own footprint: Yes
Publish my footprint results: Yes, if
you credit the publisher
Share the file with my customers: Unclear: ask Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU)
Put the factors in a product I sell: Unclear: ask Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU)
Modify it or combine it with my own data: Unclear: ask Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU)

Publisher's published terms, checked on 1 Oct 2026

The repository LICENSE is MIT and names "this software and associated documentation files"; the method paper scopes it: "All model code is provided under the MIT license" (Röös et al. 2025, section 2.1), and its data-availability line says only "The tool and data is available at https://safad.se/". No sentence grants rights on the data files in src/default-input-files/. Withheld from open distribution until SLU confirms in writing (IMP-0037).

Credit line

SAFAD v1.4.3, Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU); Röös et al. 2025, J. Cleaner Production 519, 146002. Normalised by open-climate.ai, https://open-climate.ai/factors/libraries/slu/ (CC BY 4.0)

Not legal advice: the publisher's terms prevail.

Full terms

How to read these answers

Coverage

Browse factors

top 0 matches

Saved	Unfold	Factor	Region	Boundary	Unit

Versions

How this works

Version	Published	Loaded	Status	Source
1.4.3safad	3 Sept 2026	6 Oct 2026	Served	Source

Methodology

How this works

A footprint is per kg of raw primary commodity at the farm gate of the producing country, before waste and before conversion into edible products. Meat, fish and seafood are per kg of bone-free edible weight.
The emissions counted are nitrous oxide from soils, mineral fertiliser production, capital goods, energy used in cropping, post-harvest handling, greenhouses, feed processing and transport, land-use change, and, for livestock, enteric fermentation and manure management. Soil carbon change is not counted, and neither is biogenic CO2.
The global warming potentials are those of the IPCC Sixth Assessment Report over 100 years: 27.0 for biogenic methane, 29.8 for fossil methane and 273 for nitrous oxide. The publisher prints each gas, so the values are not restated.
Crop yields are FAOSTAT averages over 2017 to 2021, and land-use change is deforestation emissions for 2018. We give every value the year 2021, the end of the yield window. Fish, seafood and novel foods come from published studies whose years are not stated.
Footprints are computed for FAO commodity items and then served to every FoodEx2 commodity mapped to the same item. Allocation between co-products is economic.
The fertiliser, energy and capital-goods emissions draw in part on licensed life-cycle inventory data; only SLU's own aggregated results are loaded, never that data itself.

Data year: 2021 on every value, the end of the 2017-2021 FAOSTAT yield window the footprints are built on.

What we import

13,524 factors from release 1.4.3: 2,556 farm-gate totals and 10,968 process slices beneath them. The slices are mineral fertiliser production, capital goods, energy, land-use change, and soil emissions, enteric fermentation and manure management, which together make up agriculture. On 2,490 totals the slices add up to the total; the other 66 print one figure only.
Every factor is per kg. They cover 79 countries and a rest-of-world group, which we file under global: the 59 rest-of-world totals are mostly fish and seafood taken from the literature, with no country of origin.
The rest-of-world factors are marked generic; every other factor is an average for its country.
Eleven nitrous oxide totals for novel foods (microbial milk, ovalbumin, fat, mycoprotein and Solein) are printed against the wrong row in the file. We recomputed them from SLU's own process figures and mark them as corrected.
One factor, cultivated mushrooms for the rest of the world, prints a total with no gas or process breakdown; it is kept but withheld.
Each factor carries its FoodEx2 code, its FAO commodity item, a matching CPC code and an open-climate.ai category. The English names come from SAFAD; descriptions and usage notes are written by open-climate.ai, and some names have French and German translations.
Not imported: 169 rows repeated under the same commodity and country, where the later row wins as it does in the SAFAD tool itself; 129 rows with a zero footprint (wild foods and miscellaneous ingredients); and one blank row.
Kept with each value but not served as separate fields: the nine other indicators SAFAD prints (land use, nitrogen, phosphorus, water, pesticides, biodiversity, ammonia, animal welfare and antibiotics).
Not imported: the three auxiliary files for energy, packaging and transport, which are parameters of the tool rather than food footprints.

Licence

How this works

Restricted. The repository carries an MIT licence, which covers "this software", and the paper states that "All model code is provided under the MIT license"; no licence names the data files. Holding the values for your own footprint and publishing results with attribution are allowed; sharing the values with customers, embedding them in a product and modifying them need SLU's written agreement, which we are requesting. Until then the values are not shown on the public site. Attribution: "SAFAD v1.4.3, Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU); Röös et al. 2025, J. Cleaner Production 519, 146002". Last verified 2026-10-06.

What can I do with this data?

Credit line: SAFAD v1.4.3, Department of Energy and Technology, Swedish University of Agricultural Sciences (SLU); Röös et al. 2025, J. Cleaner Production 519, 146002

slu-safad-repo-mit-data-unstated

All model code is provided under the MIT license (https://github.com/SLU-foodsystems/safad).

Limitations

These are farm-gate figures for raw commodities. They exclude processing, packaging, retail and household waste, so they are not comparable with retail or as-eaten footprints without accounting for the difference in boundary.
One FAO commodity footprint is served to every FoodEx2 commodity mapped to it, so many commodities share the same value in a country, and a minor crop can carry the footprint of a quite different one (in Poland, physalis and persimmon carry the greenhouse tomato value). Prefer a factor computed for the commodity itself where one exists.
SAFAD prints no uncertainty. Most factors are rated medium quality; the rest-of-world literature values are rated low. How quality tiers are set.
Some commodity names change with the producing country, because SAFAD prints the FAO item name per row.
One edition is loaded, and SLU has announced a version 2.0 with updated environmental data.

Changelog

2026-10-06: release 1.4.3 loaded, 13,524 factors: 2,556 farm-gate totals and their process slices.

Know a newer edition?

If SLU has published an edition we do not serve yet, tell us where to find it.