ECCC - Environment and Climate Change Canada

Grid electricity intensity for Canada and each of its 13 provinces and territories, from 1990 to 2024, taken from Environment and Climate Change Canada's National Inventory Report.

GovernmentSpecialistOpen licence

Publisher's page Browse 56 factors

Factors

Values

550

One per year and method

Countries

14 regions, sub-national included

Edition

NIR-1990-2024

published 14 Apr 2026 · all versions

Last loaded

24 Sept 2026

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Overview

Environment and Climate Change Canada (ECCC) submits Canada's official greenhouse gas inventory to the UNFCCC every April. Annex 7 of the National Inventory Report, Electricity in Canada: Summary and Intensity Tables, prints one table for Canada and one for each province and territory. It is published as a workbook on the ECCC data portal.

The value of the library is its provincial grain. In 2024 the generation intensity of Quebec was 2.097 g CO2e per kWh and that of Nunavut 740.0, a 352.9x spread that a national average hides.

At a glance

Publisher: Environment and Climate Change Canada
Kind: Government
Scope: SpecialistOne category holds at least 5% of its factors: Electricity, with 100.0%. A generalist needs 4.
Home region: Canada
Edition: NIR-1990-2024
Licence: Open licence (ogl-canada-2.0)

Open data

How this works

Standardised file

Environment and Climate Change Canada, 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 NIR-1990-2024xlsxen28 rows · built 2026-09-01 · 31ae4a10f2e1free account required
Edition NIR-1990-2024csven28 rows · built 2026-09-01 · 80016c0d1b7afree account required

What open-climate.ai standardised

over the publisher's own fileHow we standardise

One category axis

56 of 56 factor values mapped to one category

56 keep the publisher's own classification too

Learn more 6 checks behind this

Coded regions

14 regions as ISO or registry codes

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Canonical units

1 canonical unit in 1 unit families, raw unit kept

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Warming potentials

14 factor values recalculated on AR6

0 factor values already on AR6

42 factor values left on the publisher's GWP

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7 more things standardised

Declared boundaries

4 boundary codes

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

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Summed totals

28 totals summed from their printed parts

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Electricity mix

56 electricity factors state their instrument; one default, market first

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Data quality

56 of 56 factor values rated on one quality tier

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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

Traceable to the source

980 source rows archived

704 rows skipped, each with a reason

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Stable addresses

Slugs never break

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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

An activity's grouping key names only the activity
Known limitation · 1 in this library · 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.

One category axis

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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
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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
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Coded regions

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Every region is a known code
Enforced when loaded
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No named region is filed under a broader one
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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
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
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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
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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
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
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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
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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
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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

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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.

Summed totals

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Summed totals equal their parts on every gas
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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.
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.
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.

Electricity mix

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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 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.
One default value per factor and year
Passed
Why it matters Two defaults for one year give two answers to the same lookup.
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.
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.

Data quality

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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

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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 · 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

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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 · 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
Known limitation · 1 in this library · 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
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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
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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 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.
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.
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.
Validity dates are the publisher's own, never guessed
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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
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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.
The newest edition of each value is the one marked current
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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
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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
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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.
Spend factors state their price year and basis
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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.
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 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.
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.
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.
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 · ogl-canada-2.0

Use it to calculate my own footprint: Yes
Publish my footprint results: Yes, if
you credit the publisher
you imply no endorsement by the publisher
Share the file with my customers: Yes, if
you credit the publisher
you imply no endorsement by the publisher
Put the factors in a product I sell: Yes, if
you credit the publisher
you imply no endorsement by the publisher
Modify it or combine it with my own data: Yes, if
you credit the publisher
you imply no endorsement by the publisher

Named licence, checked on 16 Aug 2026

Open Government Licence - Canada 2.0: copy, modify, publish, adapt and distribute the Information for any lawful purpose, commercial included; attribution is the only condition, with no suggestion of official endorsement.

Credit line

Data: Contains information licensed under the Open Government Licence – Canada. Normalised by open-climate.ai, https://open-climate.ai/factors/libraries/eccc_canada (CC BY 4.0)

Not legal advice: the publisher's terms prevail.

Full terms

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

56factors

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

By boundary

56factors

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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 has released something newer, which we are reviewing (1 signal watched)

Version	Published	Loaded	Status	Source
NIR-1990-2024	14 Apr 2026	24 Sept 2026	Served	Source

Methodology

How this works

Each table covers the power sector, NAICS 22111 Electric Power Generation, and publishes two series per year: generation intensity and consumption intensity. Values are printed in g CO2e per kWh; we serve them in kg per kWh.
Only main activity producers are counted: companies whose main business is generating electricity, public or private, reported under NAICS 22111. Autoproducers, which generate for their own operations, are reported under the industry they belong to and are outside these tables.
The emissions counted are those from burning coal, natural gas, refined petroleum products such as light and heavy fuel oil and diesel, petroleum coke, still gas and other fuels the source does not categorise. On-site combustion at a plant that is not directly for generation is in as well. CO2 that is captured and stored is taken back out of the total.
ECCC derives the values from Statistics Canada: the Report on Energy Supply and Demand in Canada for fuel consumption, and the Electric Power Generation, Transmission and Distribution publication together with data tables 25-10-0019-01, 25-10-0020-01, 25-10-0021-01 and 25-10-0084-01 for generation. Generation data come from the data tables for 2005 onwards and from the publication for 1990 to 2004. Some jurisdictions come from their regional electricity system operator instead.
The printed report rounds these values. We import the unrounded ones from the workbook.
Generation intensity is the sector's emissions divided by the electricity it generates. It carries a breakdown into CO2, CH4 and N2O. Biogenic CO2 is left out, while CH4 and N2O from burning biomass are in. SF6 from electrical equipment is reported separately and is not included.
Consumption intensity is the intensity of electricity as delivered: a supply mix adjusted for trade between provinces and grossed up for transmission and distribution losses. It has no gas breakdown. We label it Well-to-use.
For consumption intensity, electric energy losses in transmission and distribution are subtracted from total generation, and the power sector's share of SF6 emissions from switchgear and other electrical equipment is added to total emissions. Those losses are the sector's share of what the annex calls unallocated energy, so the consumption values move with it.
The two series are different quantities of electricity, not parts of one total. In 2024 Prince Edward Island's consumption intensity is 82.93 times its generation intensity, because the island imports most of its power. Never add one to the other.
The workbook states no GWP basis. The gas breakdown reproduces IPCC AR5 (100-year) and no other report, so values are marked AR5, as inferred. We also compute an AR6 value for the generation series from its gas breakdown; the consumption series has none.
The reference year is the inventory year. The 2024 values are marked preliminary by ECCC.
Canada's generation intensity is the generation-weighted average of the 13 provinces and territories, so the national factor overlaps them.

Data year: the inventory year of the National Inventory Report.

What we import

The National Inventory Report 1990-2024 edition, released 2026-04-14: the 14 intensity tables of Annex 7, two series each, for the years 1990, 2005, 2010, 2015 and 2019 to 2024. That gives 28 factors and 276 values.
The table notes. The ones that set a series apart, on what the delivered mix adds, become that factor's included processes; the ones on how to read the numbers become its applicability. The notes printed identically in all 14 tables are on this page instead of on 28 factors.
Not imported: Annex 6 and the rest of the report; the breakdown of emissions and generation by fuel inside each Annex 7 table; the unallocated energy and SF6 rows, which are not per-kWh values and are kept only as context; and cells printed as x, ** or unk, which are never read as zero. Those rows and cells are kept in our archive with their reason.
Nunavut: 1990 is published only combined with the Northwest Territories, so the Northwest Territories 1990 values cover both. Nunavut's 2005 and 2010 generation values are withheld by ECCC for statistical reasons; its consumption values for those years are served.
Names are generated in English. French names are machine translated.

ECCC prints generation and a consumption intensity that already holds the grid losses, but no fuel chain. Beside each generation intensity, open-climate.ai adds two legs ECCC never printed, each as its own factor marked as an estimate: the fuel chain (extracting, refining and transporting the fuel the plants burn) and the fuel chain of the losses. They are computed by a stated rule from ECCC's own tables: the loss share is the gap between the consumption and generation series, and the fuel weights are the fuel shares of each Annex 7 table, with Ember's mix for Canada as a whole. They are rated low quality. No loss leg and no new total are added, since the consumption intensity is ECCC's own delivered total. How the legs are estimated.

Licence

How this works

Open, under the Open Government Licence – Canada, version 2.0. Commercial use and redistribution are allowed; attribution is the only condition. The attribution statement is: "Contains information licensed under the Open Government Licence – Canada."

What can I do with this data?

Credit line: Contains information licensed under the Open Government Licence – Canada.

ogl-canada-2.0

Limitations

Emissions from flooding land for hydro reservoirs are excluded. This matters most for Quebec, Manitoba and British Columbia, whose grids are mostly hydro.
ECCC does not say whether the electricity generated is counted gross or net. The Statistics Canada tables it cites are gross, so we read it as gross; that is our inference, not a publisher statement.
ECCC's values hold no upstream fuel chain. The fuel-chain legs we add estimate it, at low quality.
Where a province imports much of its power, the gap between the consumption and generation series is mostly trade, not loss, and the fuel chain of the losses reads it as loss. That leg is overstated on Prince Edward Island in every year and in Quebec in 2015, 2020 and 2021: on Prince Edward Island in 2024 it is 0.0577 kg per kWh, 18 times the generation intensity it is computed from. Do not use it there.
The Northwest Territories and Nunavut are printed to two significant figures, far coarser than the provinces.
Every submission restates the whole series back to 1990. Cite the edition along with the year.

Changelog

2026-09-25: estimated fuel-chain legs added beside the generation intensities.
2026-09-24: the annex narrative and the shared table notes moved here from the factors, which all carried them.
2026-09-15: consumption intensities relabelled Well-to-use.
2026-08-17: National Inventory Report 1990-2024 edition loaded, 28 factors for Canada and its 13 provinces and territories.

Know a newer edition?

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