USEEIO - U.S. EPA Supply Chain GHG Emission Factors (USEEIO)

The US Environmental Protection Agency's supply chain emission factors for US commodities, per dollar spent, built from the USEEIO input-output model for 392 commodities.

Government

Spend

GeneralistOpen licence

Publisher's page Browse 1,176 factors

Factors

1,176

Values

1,176

One per year and method

Countries

1 region, sub-national included

Edition

1.4.0

published 14 Oct 2025 · all versions

Last loaded

24 Sept 2026

Report a newer version

Overview

The Supply Chain Greenhouse Gas Emission Factors for US Commodities give the emissions caused by buying a US commodity, per US dollar of purchases. EPA derives them from USEEIO, its environmentally extended input-output model of the US economy, which couples the Bureau of Economic Analysis (BEA) 2017 benchmark input-output tables with EPA emissions data.

They are built for spend-based accounting, mainly Scope 3 purchased goods and services, where only the amount paid is known. The release is published by the Cornerstone Sustainability Data Initiative on Zenodo, with a new version roughly every 15 to 18 months.

At a glance

Publisher: U.S. EPA Supply Chain GHG Emission Factors (USEEIO)
Kind: Government
Scope: Generalist4 categories each hold at least 5% of its factors; the largest, Manufactured goods, holds 30.1%. A generalist needs 4.
Home region: United States
Edition: 1.4.0
Licence: Open licence (cc-by-4.0)

Open data

How this works

Standardised file

U.S. EPA Supply Chain GHG Emission Factors (USEEIO), standardised by open-climate.ai

The publisher's file, re-cut into the schema every library on open-climate.ai shares: one category axis, coded regions, canonical units, AR6 warming potentials, the source row kept beside each value. What is in the file

Edition 1.4.0xlsxen392 rows · built 2026-09-01 · 70e5a36b7593free account required
Edition 1.4.0csven392 rows · built 2026-09-01 · 6ea3aadd329dfree account required

What open-climate.ai standardised

over the publisher's own fileHow we standardise

One category axis

1,176 of 1,176 factor values mapped to one category

1,176 keep the publisher's own classification too

Learn more 6 checks behind this

Coded regions

1 region as an ISO or registry code

1,176 take the publisher's default region, stated rather than assumed

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

1,176 factor values already on AR6

0 factor values left on the publisher's GWP

Learn more 7 checks behind this

7 more things standardised

Declared boundaries

3 boundary codes

1,176 factor values state in, out or varies for each scope term

Learn more 7 checks behind this

Parts and parents

784 factor values grouped under 392 parents

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

Learn more 3 checks behind this

Spend factors

1,176 spend factors

priced in 1 year

Learn more 1 check behind this

Data quality

1,176 of 1,176 factor values rated on one quality tier

Learn more 7 checks behind this

Languages

English: 100.0% of factor values

German: 100.0% of factor values

French: 100.0% of factor values

Learn more 9 checks behind this · 1 known limitation

Traceable to the source

1,176 source rows archived

Learn more 4 checks behind this

Stable addresses

Slugs never break

392 old addresses redirect

Learn more

Audit checks

91 passed1 known limitation3 enforced when loadedlast run 25 Sept 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

Needs attention

Translations match the current source text
Known limitation · 2,352 in this library · 286,941 in all libraries
Why it matters When the publisher rewords a label, an old translation can describe a different activity than the one priced.

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
Passed
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
Passed
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
Passed
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
Passed
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

Learn more

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
Passed
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

Learn more

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
Passed
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

Learn more

Every boundary states what it includes
Passed
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
Passed
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
Passed
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
Passed
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
Passed
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.
Each biofuel follows one convention for biogenic CO2
Passed · 12 in all libraries
Why it matters Burning a biofuel releases CO2 that some publishers count and others leave out, so the same fuel can differ many times over between libraries.
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
Passed
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
Passed
Why it matters Reporting now asks for AR6. Mixing AR5 and AR6 shifts methane-heavy totals by several percent.
CO2e totals agree with their gases
Passed · 3,229 in all libraries
Why it matters A value labelled fossil-only should carry no gas other than CO2 and not exceed its own CO2. When it does, the label or the total is wrong.
Fossil-only values list the gases that back the label
Passed · 19,942 in all libraries
Why it matters With no breakdown by gas, nothing can confirm the fossil-only label. The value rests on the publisher's word alone.
Standardised figures keep every gas the publisher lists
Passed
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
Passed
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
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
Passed
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
Passed
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
Why it matters Search groups parts under their top factor. A stale link shows a part as a stand-alone result.

Spend factors

Learn more

Spend factors state their price year and basis
Passed
Why it matters A 2019 euro is not a 2024 euro, and a purchaser price includes margins a basic price does not. Without both, spend footprints drift.

Data quality

Learn more

Quality ratings fall inside their scale
Passed
Why it matters An out-of-scale rating cannot be compared, so the value would be ranked arbitrarily.
Every zero value is explained
Passed
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
Passed
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
Passed
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
Passed
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
Passed
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
Passed
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

Learn more

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
Known limitation · 2,352 in this library · 286,941 in all libraries
Why it matters When the publisher rewords a label, an old translation can describe a different activity than the one priced.
Every served factor has a name
Passed
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 · 7 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
Passed
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
Passed
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

Learn more

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 · 302 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 · 5,836 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 · 556 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

An activity's grouping key names only the activity
Passed · 6 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.
Every summed total has a classification when its parts do
Passed
Why it matters A total with no classification drops out of every category filter, even though its parts are filed there.
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.
The market-based value is the default
Passed
Why it matters The default then matches the figure most Scope 2 reports lead with, and a green-tariff zero is never the default when another figure exists.
Summed totals equal their parts on every gas
Passed
Why it matters Where a total is the sum of its parts, the two must agree on every gas. Otherwise your footprint changes depending on whether you use the total or the parts.
Validity dates are the publisher's own, never guessed
Passed
Why it matters A start date we invented looks just like one the publisher printed, and would hide correct factor values from a search for what applied on a given date.
Quality breakdowns use their scheme's axes
Passed
Why it matters A score on an axis the scheme does not define, or off its scale, cannot be read, so the breakdown behind a rating would mislead.
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 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 is served where the publisher printed the figure
Passed
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.
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.
Every factor with a current value has a default
Passed
Why it matters A factor with values but no default is left out of the served catalogue, so you would never find it in search or exports.
Every factor has a value, in a library that publishes values
Passed
Why it matters A factor listed with no number looks like a match in search but gives you nothing to calculate with.
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 electricity factor states its mix
Passed
Why it matters Without its mix you cannot tell a location-based figure from a market-based one, and Scope 2 reporting needs both side by side.
The newest edition of each value is the one marked current
Passed
Why it matters If an older edition stayed marked as current, you would get superseded numbers, or two answers for the same factor.
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.
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.
Only a total we computed may mix GWP vintages
Passed
Why it matters A published row states one GWP vintage. A mix of AR5 and AR6 can only come from a total assembled out of several rows, and saying so tells you the number was computed, not published.
One default value per factor and year
Passed
Why it matters Two defaults for one year give two answers to the same lookup.
Every value has a number, a GWP version and a reference year
Passed
Why it matters Without the number there is nothing to multiply. Without the GWP version or the year, you cannot tell whether two values are comparable.
No factor description is too long to display in full
Passed · 4 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.
Every excused arithmetic disagreement is stated
Passed
Why it matters Where a publisher's own total does not equal its parts and we serve it anyway, the exception is listed on every audit run rather than left in code where nobody sees it.
Every reference year falls between 1960 and next year
Passed
Why it matters A year outside that range points to a typo or a misread column, and would put the value in the wrong period when you filter by year.
The parts of a total are never listed twice under one label
Passed
Why it matters A group that repeats a part label is a list of terms, not a split of the total, so adding its rows up would count some emissions twice.
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.
A supplier named in the source is linked to the factor
Passed
Why it matters If the supplier is named but not linked, you cannot filter by supplier or tell a company's own figure from a generic one.
A part covering the same scope as its total is linked to it
Passed
Why it matters When a part and the total beside it cover exactly the same scope, nothing in the numbers tells them apart. Linking them stops you adding a part to the total that already contains it.
A year in a factor's name matches its reference year
Passed
Why it matters A name like “Grid 2019” on a 2023 value usually means a yearly series was flattened, so you could apply one year's figure to another.

How the audit works

What can I do with this data?

Open licence · credit the publisher

Your rights

Open licence · cc-by-4.0

Use it to calculate my own footprint: Yes
Publish my footprint results: Yes, if
you credit the publisher
you say what you changed
Share the file with my customers: Yes, if
you credit the publisher
you say what you changed
Put the factors in a product I sell: Yes, if
you credit the publisher
you say what you changed
Modify it or combine it with my own data: Yes, if
you credit the publisher
you say what you changed

Named licence, checked on 2 Aug 2026

CC BY 4.0 §2(a)(1) grants the right to reproduce and Share the Licensed Material and to produce and Share Adapted Material, for any purpose, commercial included; §3(a) requires attribution and an indication of changes.

Credit line

Data: U.S. EPA Supply Chain GHG Emission Factors for U.S. Commodities v1.4.0 (USEEIO), CC BY 4.0. Underlying data is public-domain U.S. EPA. Normalised by open-climate.ai, https://open-climate.ai/factors/libraries/useeio (CC BY 4.0)

Not legal advice: the publisher's terms prevail.

Full terms Where this answer comes from

How to read these answers

Coverage

What the library covers, by category and by boundary. Click a slice to drill in, then a sub-category or a boundary to filter the factors below.

By category

392factors

Click a slice to see what is under it. Click a name to hide it from the ring.

By boundary

392factors

Click a slice to see what is under it. Click a name to hide it from the ring.

Browse factors

Currency

top 0 matches

Saved	Unfold	Activity		Sub-category	Region	Boundary			Unit	GWP

Versions

How this works

Checked for updates 18 Sept 2026: the publisher still shows the edition we serve (1 signal watched)

Version	Published	Loaded	Status	Source
1.4.0	14 Oct 2025	24 Sept 2026	Served	Source

Methodology

How this works

Factors are kg CO2e per US dollar, with IPCC AR6 100-year GWPs. Each covers the whole supply chain of the commodity.
EPA publishes three columns per commodity: without margins (cradle to factory gate), the margins (factory gate to shelf) and with margins (cradle to shelf). With margins is the sum of the other two.
The unit is per dollar of purchases, in 2024 US dollars. We serve it adjusted for inflation to each activity year from 2015 to 2025, on the US deflator.
The data year is 2023.
Overheads and services are inside the supply chain; capital goods are not, because the model treats investment as final demand.
EPA also publishes the split by gas (17 gases). We serve the CO2e total and keep that split in our archive.

Data year: the year of the USEEIO emissions data.

What we import

Version 1.4.0, the CO2e sheet of the workbook.
One factor per BEA commodity: 392 factors. The 1,016 NAICS 2017 rows of the workbook collapse onto these, since several NAICS codes share one factor; each factor carries all its NAICS codes.
Two values per factor: with margins, the default, and without margins.
Commodities are tagged with their BEA 2017 code, except the six whose reference names several commodities at once.
All factors are placed in the United States.
French names are machine translated.

Licence

How this works

Open. The data is a work of the US federal government and in the public domain; the Cornerstone release adds CC BY 4.0, which allows commercial use and redistribution with attribution: "U.S. EPA Supply Chain GHG Emission Factors for U.S. Commodities v1.4.0 (USEEIO), CC BY 4.0." No ShareAlike applies.

What can I do with this data?

Credit line: U.S. EPA Supply Chain GHG Emission Factors for U.S. Commodities v1.4.0 (USEEIO), CC BY 4.0. Underlying data is public-domain U.S. EPA.

cc-by-4.0

Limitations

A spend-based factor averages a whole commodity. A physical or supplier-specific factor is more accurate when available.
Both values are labelled cradle to gate for now, although the with margins value runs to the shelf. Pick with margins for a purchase price and without margins for a factory gate price.
The factors describe the US economy and US supply chains.
Versions are not comparable as published: the dollar year and the GWP basis change with each version.
No uncertainty or data quality rating is published with the factors.
Only version 1.4.0 is loaded so far.

Changelog

2026-09-15: capital goods marked as outside the boundary, overheads and services inside.
2026-09-10: factors adjusted for inflation per activity year.
2026-08-18: commodities tagged with their BEA 2017 codes.
2026-07-24: version 1.4.0 loaded.

Know a newer edition?

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