From b7fc795742a40522e6a80f57071918b1cd8194f0 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 11:05:24 -0400 Subject: [PATCH 01/26] Draft GHG extension overview and GHG data by country tier Write the GHG extension overview (gases, GWPs, scope, accounting basis, shared steps, data years) and replace the data-sources placeholder with a country-tiers page covering Tier 0 (U.S. v0.6) through Tier 3 and the rest of world. Add glossary terms for CEDS, EDGAR, GHGRP, and residence and territorial bases. Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 157 ++++++++++++++++++++++++++++++++++++++++++ ee/data-sources.md | 45 ------------ ee/index.md | 98 +++++++++++++++++++++++--- myst.yml | 2 +- reference/glossary.md | 15 ++++ 5 files changed, 260 insertions(+), 57 deletions(-) create mode 100644 ee/country-tiers.md delete mode 100644 ee/data-sources.md diff --git a/ee/country-tiers.md b/ee/country-tiers.md new file mode 100644 index 00000000..ef6899d4 --- /dev/null +++ b/ee/country-tiers.md @@ -0,0 +1,157 @@ +--- +title: "GHG data by country tier" +--- + +:::{tip} Summary +The emissions data for each country follow its {term}`tier `: a detailed facility- and inventory-based model for the U.S., national sources for the four Tier 1 countries, the FIGARO or ICIO emissions data for Tier 2, and a scaled template for Tier 3. Within Tier 2, the detail available differs by source. +::: + +:::{note} Draft +:class: dropdown +**Key visuals to add:** world map colored by GHG data source; timeline of emissions data years. +::: + +## What each tier starts from + +| {term}`Country tier` | Countries | Emissions source | Data year | Gas detail | +|---|---|---|---|---| +| Tier 0 | United States | National GHG inventory, placed on industries with facility, energy, and economic data | 2024 | All 7 gases | +| Tier 1 | China, Japan, South Korea, United Kingdom | National sources for each country | 2018–2023 | All 7 gases, with gaps filled for South Korea | +| Tier 2, FIGARO | 40 countries | FIGARO emissions data from Eurostat | 2023 | 6 gas groups | +| Tier 2, ICIO | 20 countries | OECD emissions data matched to the ICIO tables | 2020 | Total CO₂e only | +| Tier 3 | 83 countries | A template scaled to each country's emissions per unit of GDP | Varies | Template | +| Rest of world | | Pooled from four Tier 2 countries | 2020–2023 | As for those countries | + +## Tier 0: The U.S. GHG model + +The U.S. has the most detailed emissions data, and its model is built on all 405 common sectors. + +**National totals.** The U.S. greenhouse gas inventory sets the national totals for 2024, by emitting activity and gas. These come from the University of Maryland's GHG inventory analysis, which follows the tables of EPA's *Inventory of U.S. Greenhouse Gas Emissions and Sinks*, with detail from EPA's inventory for 2023 where it is needed (for example, agricultural soils and fluorinated gases). The inventory is on a {term}`territorial basis `. + +**Placing the totals on industries.** The inventory names an industry for some emissions and not others, so each emitting activity is placed on industries by one of these routes: + +- **Directly.** Where the inventory names the industry, as for most process and fugitive emissions (petroleum and natural gas systems, cement, and other industrial processes), the emissions go to that industry. +- **Facility reports.** Most fuel burned at industrial plants is placed using what the plants themselves report: emissions reported to EPA's {term}`GHGRP`, and to the National Emissions Inventory, matched to one record per site. Power plants come from EPA's eGRID for 2024. For manufacturing natural gas, coal, and petroleum fuels, each industry's share comes from facility reports where they cover at least 80% of the industry's combustion, and from the Manufacturing Energy Consumption Survey (2022) where they don't. +- **Physical fuel use.** Fuel burned in vehicles and equipment is placed on the industries that use it, based on fuel volumes. Highway fuel is split by vehicle owner using Federal Highway Administration data for 2024, with federal fleets from GSA's Federal Fleet Report and private trucks by business type from the Census Bureau's Vehicle Inventory and Use Survey (2021). Industrial diesel is split across agriculture, construction, mining, and manufacturing from fuel sales and survey data. +- **Purchases.** The remaining emissions are spread across the industries that buy the relevant fuel or product, in proportion to their purchases in the U.S. Use table. + +**Checks inside the build.** After placing the emissions, every industry's emissions are held at or above what its own facilities report to the GHGRP, and industries whose facilities cover nearly all their combustion are held at or below it. National totals for each activity and gas are unchanged. + +**Households.** Emissions the inventory places in homes and personal vehicles go to households and are not in `B` (see [](index.md)). + +:::{note} Changed in U.S. model v0.6 +Fuel burned in trucks, buses, and cars is now placed by who owns and uses the vehicles, and industrial diesel by physical fuel volumes. Previously both were spread by purchases of refined petroleum products, which placed about 350 Mt CO₂ on state and local government. That fuel now goes mainly to transportation, construction, other private industries, and households. See the [release notes](../releases/index.md). +::: + +## Tier 1: National sources + +Each Tier 1 country's emissions come from its own national data. + +| Country | Source | Data year | Sectors | +|---|---|---|---| +| China | Built from several sources (see below) | 2023 | 211, matching the IO table | +| Japan | Environmental data published with the Input-Output Tables for Japan | 2020 | Matching the IO table | +| South Korea | GHG data published with the Bank of Korea input-output tables | 2018 | Matching the IO table | +| United Kingdom | ONS atmospheric emissions accounts | 2023 | By industry | + +China's data are on a territorial basis, and the UK's on a residence basis. + +**China** has no published emissions table matching its IO table, so we build one: + +- CO₂ from fossil fuels and cement sets the totals, from Our World in Data, and is placed on sectors by each sector's physical fuel use from China's national energy statistics. +- Power-sector CO₂ is set to match China's official 2023 grid emission factor. +- CH₄ and N₂O come from the Community Emissions Data System ({term}`CEDS`), and farm CH₄ and N₂O from China's first Biennial Transparency Report. +- Fluorinated gases come from China's first Biennial Transparency Report, brought forward to 2023 with {term}`EDGAR` trends. + +Household fuel use is not separated in China's national totals, so its CO₂ is spread over the industries rather than left out. + +**South Korea's** source covers six gases. The missing gas (NF₃) is estimated from the sector's CO₂ using the U.S. ratio. + +Each country's emissions are then mapped to the common sectors with {term}`structural reflection `, the same as its IO table. Each national total is kept. + +## Tier 2: FIGARO and ICIO emissions data + +Tier 2 countries take their emissions from the same source as their IO table, so emissions and output line up sector by sector. The two sources differ a lot in detail. + +| | FIGARO | ICIO | +|---|---|---| +| Publisher | Eurostat | OECD | +| Version | 2026 | 2025 | +| Data year | 2023 | 2020 | +| Sectors | 64 industries (NACE Rev. 2) | 50 industries (ISIC Rev. 4) | +| Gases | CO₂, CH₄, N₂O, HFCs, PFCs, and SF₆ with NF₃ | Total CO₂e only | +| GWPs in source | AR5 | AR5 | +| Basis | Residence | Residence | + +### FIGARO countries + +FIGARO emissions come from two kinds of underlying data: + +- **Air emissions accounts (30 countries).** The 27 EU member states report emissions by industry in their air emissions accounts. For Norway, Switzerland, and Türkiye, Eurostat fills in the industry split. +- **EDGAR estimates (10 countries).** For Argentina, Australia, Brazil, Canada, India, Indonesia, Mexico, Russia, Saudi Arabia, and South Africa, Eurostat estimates emissions by industry from {term}`EDGAR`. EDGAR groups some activities together, so we correct the split. Within mining, refining, and the power and gas utilities, CO₂, CH₄, and N₂O are re-split using {term}`CEDS` shares, holding the combined total fixed. Shares for steel, chemicals, and non-metallic minerals are also reset to CEDS, and process CO₂ is kept off trade and service industries. + +For both groups, FIGARO's industries are first converted to products using FIGARO's supply table, to match the product-by-product IO table. The same broad sectors split in the IO table are split here too: + +- Electricity, gas, and heat are separated using Eurostat energy balances and CEDS gas distribution methane. +- Agriculture is split into farm sectors using FAOSTAT CH₄ and N₂O and Eurostat agricultural accounts. +- Mining, non-metallic minerals, and basic metals are split as in the IO table. + +The products are then mapped to the common sectors with {term}`ABSR`. The last gas group, SF₆ with NF₃, is split using the U.S. share of SF₆ in each sector. + +### ICIO countries + +The OECD data give one CO₂e total for each of the 50 industries, with no split by gas. Farming is split out first, using FAOSTAT CH₄ and N₂O, before the totals are mapped to the common sectors with ABSR. The split by gas comes entirely from the U.S. mix for each sector. Electricity is mapped as one sector, with no separate split for gas and heat. + +## Tier 3: Template emissions + +Tier 3 countries have no emissions data by sector. Their direct emission intensities start from the same template as their input recipe, a blend of Mexico (30%), Malaysia (30%), and Tunisia (40%), based on CO₂ intensities from an earlier ICIO edition. Other gases are added using the U.S. ratio of total CO₂e to CO₂ in each sector. + +Each country then adjusts the template two ways: + +- **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. +- **Electricity.** The electricity sector uses the country's own electricity emissions per dollar of electricity output. + +## Rest of world + +The rest-of-world region's direct emission intensities are the output-weighted average of four Tier 2 countries: Colombia and Chile (from ICIO) and Mexico and Türkiye (from FIGARO). See [](../io/index.md) for how the region is used. + +:::{important} Key assumptions +:class: dropdown +**ICIO countries take the U.S. gas mix** + +- **Assumption:** For ICIO countries, the split of each sector's CO₂e total into gases follows the U.S. mix for that sector. +- **Why we make it:** The OECD data give only total CO₂e by industry. +- **How it affects results:** Total CO₂e for each sector is unchanged, but results by gas are less reliable. Where a country's methane or fluorinated-gas share differs from the U.S., for example in rice farming, gas-level results could be off. + +**EDGAR-based FIGARO countries are re-split with CEDS** + +- **Assumption:** For the 10 FIGARO countries whose emissions Eurostat estimates from EDGAR, CEDS gives a better split between mining, refining, and power and gas utilities. +- **Why we make it:** EDGAR merges some activities that CEDS keeps separate, such as public power plants and on-site generation, and refining and extraction. +- **How it affects results:** The split between these industries changes, but the country's total for the group is unchanged. + +**Tier 3 countries share one template** + +- **Assumption:** Tier 3 countries share one pattern of direct emission intensities. They differ only in their overall level, set by fossil CO₂ per unit of GDP, and in their electricity intensity. +- **Why we make it:** These countries have no emissions data by sector. +- **How it affects results:** Differences between Tier 3 countries in which sectors emit the most are not captured, and non-CO₂ gases are scaled with fossil CO₂. Factors for these countries carry more uncertainty than those for Tiers 0 to 2. +::: + +:::{seealso} Checks we run +- Each country's total emissions are kept through splitting and mapping. +- For the U.S., each industry is checked against what its own facilities report. + +See [Validation](#validation-hub). +::: + +## Learn more + +- **From the field:** *to be added* +- **Cornerstone papers:** *to be added* +- **Code:** *to be added* + ++++ + +:::{div} +:class: page-status +Applies to: RC · Last reviewed: RC +::: diff --git a/ee/data-sources.md b/ee/data-sources.md deleted file mode 100644 index edbd646b..00000000 --- a/ee/data-sources.md +++ /dev/null @@ -1,45 +0,0 @@ ---- -title: "Data sources by tier" ---- - -:::{tip} Summary -*To be written.* -::: - -:::{note} Draft placeholder -:class: dropdown -Plan §3.3.2 · target: **RC (Oct 27)** - - -**Planned content** - -- One table per tier with source, coverage, gases, and vintage - -**Key visuals** - -- 🖼 World map colored by GHG data source -- 🖼 Timeline of data vintages -::: - -:::{important} Key assumptions -:class: dropdown -*Assumptions specific to this step, using the assumption card: Assumption · Why we make it · -How it affects results · Alternatives or sensitivity tested.* -::: - -:::{seealso} Checks we run -*The validation behind this part of the model. See [Validation](#validation-hub).* -::: - -## Learn more - -- **From the field:** *to be added* -- **Cornerstone papers:** *to be added* -- **Code:** *to be added* - -+++ - -:::{div} -:class: page-status -Applies to: RC · Last reviewed: RC -::: diff --git a/ee/index.md b/ee/index.md index 2369b026..779f952d 100644 --- a/ee/index.md +++ b/ee/index.md @@ -3,31 +3,107 @@ title: "The GHG extension: overview" --- :::{tip} Summary -*To be written.* +The GHG extension attaches each sector's own greenhouse gas emissions to the IO model, as emissions of each gas per dollar of output (`B`). Every country follows the same steps, but the emissions data behind them, and how much detail they carry, depend on the country's tier. ::: -:::{note} Draft placeholder +:::{note} Draft :class: dropdown -Plan §3.3.1 · target: **RC (Oct 27)** +**Key visual to add:** pipeline from source emissions → split and map to the common sectors → convert to AR6 → divide by output → `B`. +::: +## What the extension adds -**Planned content** +The IO model traces the dollars that flow through supply chains. The GHG extension adds what each sector emits while making its output. For each country and sector it records: -- Gases (CO₂, CH₄ fossil and non-fossil, N₂O, F-gases), AR6 GWPs (100-year), units +- **Emissions** (`E`): kilograms of each gas emitted by the sector in a year. +- **Direct emission intensities** (`B`): those emissions divided by the sector's output (`q`), so kilograms of each gas per dollar of output. -**Key visuals** +`B` holds direct emissions only: what the sector emits from its own fuel use, processes, and other activities. Emissions from the sector's suppliers come in through the supply chain (`L`), not through `B`. For example, the emissions from generating electricity stay with the power sector, and other sectors' purchased electricity reaches them through `L`. -- 🖼 Pipeline: emissions data → sector assignment → `B` -::: +Characterization factors (`C`) then weight each gas by its global warming potential, which gives the direct emission factors `D = C × B` and the total emission factors `N = C × B × L` (see [](../reference/notation.md)). + +## Gases and global warming potentials + +`B` has a row for each of seven gases or gas groups: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF₆), and nitrogen trifluoride (NF₃). + +They are combined into CO₂-equivalent with 100-year {term}`GWPs ` from the IPCC's Sixth Assessment Report (AR6). Methane is valued two ways: fossil methane, from fuel production and use, at 29.8, and non-fossil methane, from farming and waste, at 27.0. Fossil methane is valued higher because, once it breaks down, it leaves CO₂ that was not already in the atmosphere. + +Several sources report emissions as CO₂-equivalent using older GWPs from the Fifth Assessment Report (AR5). These are converted to AR6, gas by gas. + +## What is and isn't counted + +`B` covers emissions from producing goods and services. Some emissions in national inventories do not come from a producing sector, and they are left out: + +- **Household direct emissions.** Fuel burned in homes and in personal vehicles is emitted by households, not by an industry, so it is not in `B`. +- **Land use, land-use change, and forestry (LULUCF).** Emissions and removals from land are not included. + +## Accounting basis + +Emissions data are compiled on one of two bases, and the model uses each source as published: + +- **{term}`Territorial basis`:** emissions that occur within the country's borders. National GHG inventories use this basis, and so do the U.S. and China data. +- **{term}`Residence basis`:** emissions by the country's resident businesses, wherever they occur. Air emissions accounts use this basis, as do the {term}`FIGARO` and {term}`ICIO` emissions data. Emissions from a country's airlines and shipping companies abroad are counted for that country. + +The residence basis matches how IO tables define a country's economy, so it suits an IO model. The two bases differ most for countries with large international transport fleets or many visitors. See [](country-tiers.md) for the basis of each source. + +## From source emissions to `B` + +Every country's emissions go through the same steps: + +1. **Start from source emissions by source sector.** Each source reports emissions on its own sector list, which can be anything from hundreds of activities (the U.S. inventory) to 50 industries (ICIO). +2. **Split broad sectors where better data exist.** Some sources lump together sectors with very different emissions, such as electricity, gas, and heat, or all of farming. Where other data can separate them, the broad sector is split first, keeping its total. +3. **Spread onto the common sectors.** Each source sector's emissions are spread over the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. +4. **Fill in missing gas detail.** Where a source does not separate every gas, the missing split is taken from the U.S. mix for the same sector. +5. **Convert to AR6** where the source used other GWPs. +6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. + +The U.S. model is built directly on the 405 common sectors, so steps 3 and 4 do not apply. [](country-tiers.md) gives the sources and the variations for each tier. + +## Data years + +Emissions data are published on different schedules, and the model uses the most recent of each. + +| Emissions data year | Countries | +|---|---| +| 2024 | United States | +| 2023 | China, United Kingdom, FIGARO countries (Tier 2) | +| 2020 | Japan, ICIO countries (Tier 2) | +| 2018 | South Korea | + +Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. :::{important} Key assumptions :class: dropdown -*Assumptions specific to this step, using the assumption card: Assumption · Why we make it · -How it affects results · Alternatives or sensitivity tested.* +**U.S. intensities shape detail within each source sector** + +- **Assumption:** Within each source sector, a country's emissions are spread over the common sectors in proportion to U.S. emission intensities. +- **Why we make it:** Outside the U.S., emissions data come on far fewer sectors than the 405 common sectors, and the U.S. data are the most detailed available. +- **How it affects results:** Each country's total for each source sector is correct, but its split between detailed sectors follows the U.S. pattern. Where a country's mix of processes differs from the U.S. (for example, a different steelmaking route), detailed sectors within the same source sector could be too high or too low. + +**Data-year emissions per 2024 dollar** + +- **Assumption:** Each country's emissions from its data year still describe 2024 production. +- **Why we make it:** Emissions data for 2024 are not yet published for most countries. +- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea (2018) and for Japan and ICIO countries (2020). + +**Household emissions are excluded** + +- **Assumption:** Direct emissions from homes and personal vehicles are not assigned to any sector. +- **Why we make it:** They are not emitted in producing goods or services, so they do not belong in emission factors for purchases. +- **How it affects results:** Totals in `B` are lower than national inventory totals. Emissions from fuel *production* for household use, such as refining, are still counted, in the producing sectors. + +**Mixed accounting basis** + +- **Assumption:** Each source is used on its published basis, territorial or residence. +- **Why we make it:** Converting between bases needs data on emissions by residents abroad and non-residents at home, which are not consistently available. +- **How it affects results:** Transport emissions in particular may be counted differently for territorial-basis countries (the U.S. and China) than for the others. ::: :::{seealso} Checks we run -*The validation behind this part of the model. See [Validation](#validation-hub).* +- Splitting and mapping keep each country's source totals, so its total emissions in the model match its source data. +- U.S. totals by gas match the national inventory. + +See [Validation](#validation-hub). ::: ## Learn more diff --git a/myst.yml b/myst.yml index 1b9a0469..8e9f796e 100644 --- a/myst.yml +++ b/myst.yml @@ -35,7 +35,7 @@ project: - title: The GHG extension children: - file: ee/index.md - - file: ee/data-sources.md + - file: ee/country-tiers.md - title: Emission factors children: - file: factors/whats-in-a-release.md diff --git a/reference/glossary.md b/reference/glossary.md index b15ccca3..30bd2ec1 100644 --- a/reference/glossary.md +++ b/reference/glossary.md @@ -17,15 +17,24 @@ Basic price BACI : The CEPII database of bilateral international trade by product, used to split each country's imports by country of origin. +CEDS +: Community Emissions Data System. A global inventory of emissions by country and detailed activity, used to refine the split of emissions between energy industries and for China's CH₄ and N₂O. + Country tier : A group of countries modeled with the same level of detail and the same kinds of data sources: Tier 0, detailed annual IO tables (the United States); Tier 1, detailed periodic national IO tables; Tier 2, coarse multi-regional tables from FIGARO or ICIO; and Tier 3, no IO tables (a template built from other countries). +EDGAR +: Emissions Database for Global Atmospheric Research, from the European Commission's Joint Research Centre. Global emissions by country and activity; the basis of FIGARO emissions for its non-European countries. + EEIO : Environmentally-extended input-output model. An input-output model of an economy with environmental data (here, greenhouse gas emissions) attached to each sector. FIGARO : Full International and Global Accounts for Research in input-Output analysis. Multi-regional IO tables from Eurostat and the European Commission's Joint Research Centre, used for many Tier 2 countries. +GHGRP +: EPA's Greenhouse Gas Reporting Program, under which large U.S. facilities report their emissions each year. + GWP : Global warming potential. The warming effect of 1 kg of a gas relative to 1 kg of CO₂ over a time horizon. The model uses AR6 values with a 100-year horizon. @@ -53,8 +62,14 @@ RAS Redefinitions : Adjustments that move secondary products (and their inputs) to the industry where they are the primary product. +Residence basis +: Emissions accounting that counts emissions by a country's resident businesses and households wherever they occur, matching the boundary of national accounts and IO tables. + Structural reflection : Using a detailed table's structure (here, the U.S. tables) as weights to split a coarser table into finer sectors. + +Territorial basis +: Emissions accounting that counts emissions occurring within a country's borders, as national GHG inventories do. ::: +++ From f8da59f957eb111068f1b7cceb33238ac1c737ed Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 11:50:45 -0400 Subject: [PATCH 02/26] Remove v0.6 change callout from GHG country tiers Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index ef6899d4..67af896e 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -39,10 +39,6 @@ The U.S. has the most detailed emissions data, and its model is built on all 405 **Households.** Emissions the inventory places in homes and personal vehicles go to households and are not in `B` (see [](index.md)). -:::{note} Changed in U.S. model v0.6 -Fuel burned in trucks, buses, and cars is now placed by who owns and uses the vehicles, and industrial diesel by physical fuel volumes. Previously both were spread by purchases of refined petroleum products, which placed about 350 Mt CO₂ on state and local government. That fuel now goes mainly to transportation, construction, other private industries, and households. See the [release notes](../releases/index.md). -::: - ## Tier 1: National sources Each Tier 1 country's emissions come from its own national data. From 768c99f6bbde5f30b06f6cb16ee3c6aad5f18b60 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 13:29:11 -0400 Subject: [PATCH 03/26] Link L in GHG overview to the IO total requirements section Co-Authored-By: Claude Opus 5.5 --- ee/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ee/index.md b/ee/index.md index 779f952d..f2f1165f 100644 --- a/ee/index.md +++ b/ee/index.md @@ -18,7 +18,7 @@ The IO model traces the dollars that flow through supply chains. The GHG extensi - **Emissions** (`E`): kilograms of each gas emitted by the sector in a year. - **Direct emission intensities** (`B`): those emissions divided by the sector's output (`q`), so kilograms of each gas per dollar of output. -`B` holds direct emissions only: what the sector emits from its own fuel use, processes, and other activities. Emissions from the sector's suppliers come in through the supply chain (`L`), not through `B`. For example, the emissions from generating electricity stay with the power sector, and other sectors' purchased electricity reaches them through `L`. +`B` holds direct emissions only: what the sector emits from its own fuel use, processes, and other activities. Emissions from the sector's suppliers come in through the supply chain ([`L`](../io/index.md#total-requirements)), not through `B`. For example, the emissions from generating electricity stay with the power sector, and other sectors' purchased electricity reaches them through `L`. Characterization factors (`C`) then weight each gas by its global warming potential, which gives the direct emission factors `D = C × B` and the total emission factors `N = C × B × L` (see [](../reference/notation.md)). From 902c6711e43d1373963bdb62f52c068d571e117d Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 13:38:34 -0400 Subject: [PATCH 04/26] Clarify which land and farming emissions the GHG extension counts Co-Authored-By: Claude Opus 5.5 --- ee/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ee/index.md b/ee/index.md index f2f1165f..b96c3742 100644 --- a/ee/index.md +++ b/ee/index.md @@ -35,7 +35,7 @@ Several sources report emissions as CO₂-equivalent using older GWPs from the F `B` covers emissions from producing goods and services. Some emissions in national inventories do not come from a producing sector, and they are left out: - **Household direct emissions.** Fuel burned in homes and in personal vehicles is emitted by households, not by an industry, so it is not in `B`. -- **Land use, land-use change, and forestry (LULUCF).** Emissions and removals from land are not included. +- **Land use, land-use change, and forestry (LULUCF).** National inventories, following IPCC guidelines, report farming and LULUCF as separate sectors. Farming emissions are counted, in the farm sectors: methane from livestock and rice, N₂O from agricultural soils, CO₂ from liming and urea, and methane and N₂O from burning crop residues in the field. The LULUCF sector is not counted. This leaves out changes in the carbon stored in forests, soils, and other land, including CO₂ removed from the atmosphere, along with emissions from flooded lands and from forest and grassland fires. ## Accounting basis From 1dc4c1af42019862a3c3d428274ebbab6379c0a3 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 13:44:41 -0400 Subject: [PATCH 05/26] change language of spread over to allocate to --- ee/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ee/index.md b/ee/index.md index b96c3742..0e1e45e7 100644 --- a/ee/index.md +++ b/ee/index.md @@ -52,7 +52,7 @@ Every country's emissions go through the same steps: 1. **Start from source emissions by source sector.** Each source reports emissions on its own sector list, which can be anything from hundreds of activities (the U.S. inventory) to 50 industries (ICIO). 2. **Split broad sectors where better data exist.** Some sources lump together sectors with very different emissions, such as electricity, gas, and heat, or all of farming. Where other data can separate them, the broad sector is split first, keeping its total. -3. **Spread onto the common sectors.** Each source sector's emissions are spread over the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. +3. **Allocate to the common sectors.** For non-Tier 0 countries, each source sector's emissions are allocated to the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. 4. **Fill in missing gas detail.** Where a source does not separate every gas, the missing split is taken from the U.S. mix for the same sector. 5. **Convert to AR6** where the source used other GWPs. 6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. From d7ba1a0bd608d2f4ab2f874e32605379505607dd Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 13:56:12 -0400 Subject: [PATCH 06/26] Give Tier 3 emissions sources and 2018 data year Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 10 ++++++---- ee/index.md | 6 +++--- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 67af896e..0d78eed8 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -19,7 +19,7 @@ The emissions data for each country follow its {term}`tier `: a de | Tier 1 | China, Japan, South Korea, United Kingdom | National sources for each country | 2018–2023 | All 7 gases, with gaps filled for South Korea | | Tier 2, FIGARO | 40 countries | FIGARO emissions data from Eurostat | 2023 | 6 gas groups | | Tier 2, ICIO | 20 countries | OECD emissions data matched to the ICIO tables | 2020 | Total CO₂e only | -| Tier 3 | 83 countries | A template scaled to each country's emissions per unit of GDP | Varies | Template | +| Tier 3 | 83 countries | A template scaled to each country's fossil CO₂ per unit of GDP from {term}`EDGAR` | 2018 | CO₂, with other gases from U.S. ratios | | Rest of world | | Pooled from four Tier 2 countries | 2020–2023 | As for those countries | ## Tier 0: The U.S. GHG model @@ -100,12 +100,14 @@ The OECD data give one CO₂e total for each of the 50 industries, with no split ## Tier 3: Template emissions -Tier 3 countries have no emissions data by sector. Their direct emission intensities start from the same template as their input recipe, a blend of Mexico (30%), Malaysia (30%), and Tunisia (40%), based on CO₂ intensities from an earlier ICIO edition. Other gases are added using the U.S. ratio of total CO₂e to CO₂ in each sector. +Tier 3 countries have no emissions data matched to an IO table. Their direct emission intensities start from the same template as their input recipe, a blend of Mexico (30%), Malaysia (30%), and Tunisia (40%). The template uses those countries' CO₂ emissions by industry for 2018, from the OECD's 2021 edition of CO₂ emissions embodied in international trade. Other gases are added using the U.S. ratio of total CO₂e to CO₂ in each sector. Each country then adjusts the template two ways: -- **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. -- **Electricity.** The electricity sector uses the country's own electricity emissions per dollar of electricity output. +- **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. Fossil CO₂ is from EDGAR (version 6.0) for 2018, and GDP from the IMF World Economic Outlook (October 2021). +- **Electricity.** The electricity sector uses the country's own power-sector CO₂ from EDGAR for 2018, divided by the value of its electricity output: 2018 generation from the U.S. Energy Information Administration times an average electricity price from the World Bank. + +Unlike other countries' intensities, Tier 3 intensities are not re-priced: they are 2018 emissions per 2018 dollar. ## Rest of world diff --git a/ee/index.md b/ee/index.md index 0e1e45e7..da029376 100644 --- a/ee/index.md +++ b/ee/index.md @@ -68,9 +68,9 @@ Emissions data are published on different schedules, and the model uses the most | 2024 | United States | | 2023 | China, United Kingdom, FIGARO countries (Tier 2) | | 2020 | Japan, ICIO countries (Tier 2) | -| 2018 | South Korea | +| 2018 | South Korea, Tier 3 countries | -Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. +Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. Tier 3 countries are the exception: their intensities are 2018 emissions per 2018 dollar. :::{important} Key assumptions :class: dropdown @@ -84,7 +84,7 @@ Emissions stay at their data year. Output, the denominator of `B`, is re-priced - **Assumption:** Each country's emissions from its data year still describe 2024 production. - **Why we make it:** Emissions data for 2024 are not yet published for most countries. -- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea (2018) and for Japan and ICIO countries (2020). +- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). **Household emissions are excluded** From ad19e922e0b9b4a2137c80b9f4dd7e02ae99859b Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 15:22:02 -0400 Subject: [PATCH 07/26] Move GHG data years table to the country tiers page Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 24 ++++++++++++++++++++++++ ee/index.md | 21 +-------------------- 2 files changed, 25 insertions(+), 20 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 0d78eed8..3e3e496b 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -113,8 +113,32 @@ Unlike other countries' intensities, Tier 3 intensities are not re-priced: they The rest-of-world region's direct emission intensities are the output-weighted average of four Tier 2 countries: Colombia and Chile (from ICIO) and Mexico and Türkiye (from FIGARO). See [](../io/index.md) for how the region is used. +(ghg-data-years)= +## Data years + +Emissions data are published on different schedules, and the model uses the most recent for each country. + +| Tier | Countries | Emissions data year | Intensities per | +|---|---|---|---| +| Tier 0 | United States | 2024 | 2024 dollar | +| Tier 1 | China, United Kingdom | 2023 | 2024 dollar | +| Tier 1 | Japan | 2020 | 2024 dollar | +| Tier 1 | South Korea | 2018 | 2024 dollar | +| Tier 2 | FIGARO countries | 2023 | 2024 dollar | +| Tier 2 | ICIO countries | 2020 | 2024 dollar | +| Tier 3 | 83 countries | 2018 | 2018 dollar | +| Rest of world | | 2020–2023, from its four countries | 2024 dollar | + +Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. Tier 3 countries are the exception: their intensities are not re-priced. + :::{important} Key assumptions :class: dropdown +**Data-year emissions per 2024 dollar** + +- **Assumption:** Each country's emissions from its data year still describe 2024 production. +- **Why we make it:** Emissions data by sector, matched to each source's IO sectors, are published with a lag of two to six years. +- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). Tier 3 intensities are also per 2018 dollar, so price changes since 2018 are not reflected. + **ICIO countries take the U.S. gas mix** - **Assumption:** For ICIO countries, the split of each sector's CO₂e total into gases follows the U.S. mix for that sector. diff --git a/ee/index.md b/ee/index.md index da029376..43c927c2 100644 --- a/ee/index.md +++ b/ee/index.md @@ -55,23 +55,10 @@ Every country's emissions go through the same steps: 3. **Allocate to the common sectors.** For non-Tier 0 countries, each source sector's emissions are allocated to the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. 4. **Fill in missing gas detail.** Where a source does not separate every gas, the missing split is taken from the U.S. mix for the same sector. 5. **Convert to AR6** where the source used other GWPs. -6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. +6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. Emissions data years differ by country; see [](country-tiers.md#ghg-data-years). The U.S. model is built directly on the 405 common sectors, so steps 3 and 4 do not apply. [](country-tiers.md) gives the sources and the variations for each tier. -## Data years - -Emissions data are published on different schedules, and the model uses the most recent of each. - -| Emissions data year | Countries | -|---|---| -| 2024 | United States | -| 2023 | China, United Kingdom, FIGARO countries (Tier 2) | -| 2020 | Japan, ICIO countries (Tier 2) | -| 2018 | South Korea, Tier 3 countries | - -Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. Tier 3 countries are the exception: their intensities are 2018 emissions per 2018 dollar. - :::{important} Key assumptions :class: dropdown **U.S. intensities shape detail within each source sector** @@ -80,12 +67,6 @@ Emissions stay at their data year. Output, the denominator of `B`, is re-priced - **Why we make it:** Outside the U.S., emissions data come on far fewer sectors than the 405 common sectors, and the U.S. data are the most detailed available. - **How it affects results:** Each country's total for each source sector is correct, but its split between detailed sectors follows the U.S. pattern. Where a country's mix of processes differs from the U.S. (for example, a different steelmaking route), detailed sectors within the same source sector could be too high or too low. -**Data-year emissions per 2024 dollar** - -- **Assumption:** Each country's emissions from its data year still describe 2024 production. -- **Why we make it:** Emissions data for 2024 are not yet published for most countries. -- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). - **Household emissions are excluded** - **Assumption:** Direct emissions from homes and personal vehicles are not assigned to any sector. From b25b3519d222fc90a759d1439626ce3f8bc52fe0 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 15:22:27 -0400 Subject: [PATCH 08/26] Fix data lag wording in data years assumption Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 3e3e496b..54eeb922 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -136,7 +136,7 @@ Emissions stay at their data year. Output, the denominator of `B`, is re-priced **Data-year emissions per 2024 dollar** - **Assumption:** Each country's emissions from its data year still describe 2024 production. -- **Why we make it:** Emissions data by sector, matched to each source's IO sectors, are published with a lag of two to six years. +- **Why we make it:** Emissions data by sector, matched to each source's IO sectors, are published with a lag, in some cases of several years. - **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). Tier 3 intensities are also per 2018 dollar, so price changes since 2018 are not reflected. **ICIO countries take the U.S. gas mix** From d120fe1c5fc0730c424c13635fafb739dedfff60 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 15:50:38 -0400 Subject: [PATCH 09/26] Add methods-by-country table with IO and GHG sources and years Extend data/country_tiers.csv with country names, IO source and year, and GHG source and year, and generate the table on the Methods by country page from it with figures/scripts/methods_by_country.py. Co-Authored-By: Claude Opus 5.5 --- data/country_tiers.csv | 298 +++++++++++++------------- figures/scripts/methods_by_country.py | 49 +++++ reference/methods-by-country.md | 171 ++++++++++++++- 3 files changed, 360 insertions(+), 158 deletions(-) create mode 100644 figures/scripts/methods_by_country.py diff --git a/data/country_tiers.csv b/data/country_tiers.csv index ad10ae92..9753c5f1 100644 --- a/data/country_tiers.csv +++ b/data/country_tiers.csv @@ -1,149 +1,149 @@ -iso3,tier,io_source -AUS,2,FIGARO -AUT,2,FIGARO -BEL,2,FIGARO -CAN,2,FIGARO -CHL,2,ICIO -COL,2,ICIO -CRI,2,ICIO -CZE,2,FIGARO -DNK,2,FIGARO -EST,2,FIGARO -FIN,2,FIGARO -FRA,2,FIGARO -DEU,2,FIGARO -GRC,2,FIGARO -HUN,2,FIGARO -ISL,2,ICIO -IRL,2,FIGARO -ISR,2,ICIO -ITA,2,FIGARO -JPN,1,National statistical agency -KOR,1,National statistical agency -LVA,2,FIGARO -LTU,2,FIGARO -LUX,2,FIGARO -MEX,2,FIGARO -NLD,2,FIGARO -NZL,2,ICIO -NOR,2,FIGARO -POL,2,FIGARO -PRT,2,FIGARO -SVK,2,FIGARO -SVN,2,FIGARO -ESP,2,FIGARO -SWE,2,FIGARO -CHE,2,FIGARO -TUR,2,FIGARO -GBR,1,National statistical agency -USA,0,Cornerstone nowcast -ARG,2,FIGARO -BRA,2,FIGARO -BGR,2,FIGARO -KHM,2,ICIO -CHN,1,National statistical agency -HRV,2,FIGARO -CYP,2,FIGARO -IND,2,FIGARO -IDN,2,FIGARO -HKG,2,ICIO -KAZ,2,ICIO -LAO,2,ICIO -MYS,2,ICIO -MLT,2,FIGARO -MAR,2,ICIO -MMR,2,ICIO -PER,2,ICIO -PHL,2,ICIO -ROU,2,FIGARO -RUS,2,FIGARO -SAU,2,FIGARO -SGP,2,ICIO -ZAF,2,FIGARO -TWN,2,ICIO -THA,2,ICIO -TUN,2,ICIO -VNM,2,ICIO -AFG,3,Template -AGO,3,Template -ALB,3,Template -ARE,3,Template -ATG,3,Template -BDI,3,Template -BEN,3,Template -BFA,3,Template -BGD,3,Template -BHR,3,Template -BHS,3,Template -BLZ,3,Template -BOL,3,Template -BRB,3,Template -BTN,3,Template -CAF,3,Template -CIV,3,Template -CMR,3,Template -COG,3,Template -DMA,3,Template -DOM,3,Template -DZA,3,Template -ECU,3,Template -EGY,3,Template -ETH,3,Template -FJI,3,Template -GAB,3,Template -GIN,3,Template -GMB,3,Template -GNB,3,Template -GNQ,3,Template -GRD,3,Template -GTM,3,Template -HND,3,Template -HTI,3,Template -IRN,3,Template -IRQ,3,Template -JAM,3,Template -JOR,3,Template -KEN,3,Template -KIR,3,Template -KNA,3,Template -KWT,3,Template -LBN,3,Template -LCA,3,Template -LKA,3,Template -LSO,3,Template -MDA,3,Template -MDV,3,Template -MKD,3,Template -MLI,3,Template -MNG,3,Template -MUS,3,Template -MWI,3,Template -NAM,3,Template -NER,3,Template -NGA,3,Template -NIC,3,Template -NPL,3,Template -NRU,3,Template -OMN,3,Template -PAK,3,Template -PNG,3,Template -PRY,3,Template -QAT,3,Template -RWA,3,Template -SEN,3,Template -SLB,3,Template -SLE,3,Template -SLV,3,Template -SWZ,3,Template -SYC,3,Template -TCD,3,Template -TGO,3,Template -TLS,3,Template -TTO,3,Template -TZA,3,Template -UGA,3,Template -UKR,3,Template -URY,3,Template -VCT,3,Template -VUT,3,Template -WSM,3,Template +iso3,country,tier,io_source,io_year,ghg_source,ghg_year +AFG,Afghanistan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ALB,Albania,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +DZA,Algeria,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +AGO,Angola,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ATG,Antigua and Barbuda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ARG,Argentina,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +AUS,Australia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +AUT,Austria,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +BHS,Bahamas,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BHR,Bahrain,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BGD,Bangladesh,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BRB,Barbados,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BEL,Belgium,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +BLZ,Belize,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BEN,Benin,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BTN,Bhutan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BOL,Bolivia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BRA,Brazil,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +BGR,Bulgaria,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +BFA,Burkina Faso,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BDI,Burundi,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KHM,Cambodia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +CMR,Cameroon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CAN,Canada,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +CAF,Central African Republic,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TCD,Chad,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CHL,Chile,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +CHN,China,1,China National Bureau of Statistics IO table,2023,"Built from OWID, CEDS, national energy statistics, and China's BTR1",2023 +COL,Colombia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +COG,Congo,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CRI,Costa Rica,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +CIV,Côte d'Ivoire,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +HRV,Croatia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +CYP,Cyprus,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +CZE,Czechia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +DNK,Denmark,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +DMA,Dominica,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +DOM,Dominican Republic,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ECU,Ecuador,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +EGY,Egypt,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SLV,El Salvador,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GNQ,Equatorial Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +EST,Estonia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +SWZ,Eswatini,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ETH,Ethiopia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +FJI,Fiji,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +FIN,Finland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +FRA,France,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +GAB,Gabon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GMB,Gambia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +DEU,Germany,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +GRC,Greece,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +GRD,Grenada,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GTM,Guatemala,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GIN,Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GNB,Guinea-Bissau,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +HTI,Haiti,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +HND,Honduras,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +HKG,Hong Kong,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +HUN,Hungary,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +ISL,Iceland,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +IND,India,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +IDN,Indonesia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +IRN,Iran,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +IRQ,Iraq,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +IRL,Ireland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +ISR,Israel,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +ITA,Italy,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +JAM,Jamaica,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +JPN,Japan,1,Input-Output Tables for Japan,2020,Environmental data published with the Japan IO tables,2020 +JOR,Jordan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KAZ,Kazakhstan,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +KEN,Kenya,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KIR,Kiribati,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KWT,Kuwait,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LAO,Laos,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +LVA,Latvia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +LBN,Lebanon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LSO,Lesotho,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LTU,Lithuania,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +LUX,Luxembourg,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +MWI,Malawi,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MYS,Malaysia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +MDV,Maldives,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MLI,Mali,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MLT,Malta,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +MUS,Mauritius,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MEX,Mexico,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +MDA,Moldova,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MNG,Mongolia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MAR,Morocco,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +MMR,Myanmar,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +NAM,Namibia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NRU,Nauru,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NPL,Nepal,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NLD,Netherlands,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +NZL,New Zealand,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +NIC,Nicaragua,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NER,Niger,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NGA,Nigeria,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MKD,North Macedonia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NOR,Norway,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +OMN,Oman,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +PAK,Pakistan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +PNG,Papua New Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +PRY,Paraguay,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +PER,Peru,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +PHL,Philippines,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +POL,Poland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +PRT,Portugal,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +QAT,Qatar,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ROU,Romania,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +RUS,Russia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +RWA,Rwanda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KNA,Saint Kitts and Nevis,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LCA,Saint Lucia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +VCT,Saint Vincent and the Grenadines,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +WSM,Samoa,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SAU,Saudi Arabia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +SEN,Senegal,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SYC,Seychelles,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SLE,Sierra Leone,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SGP,Singapore,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +SVK,Slovakia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +SVN,Slovenia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +SLB,Solomon Islands,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ZAF,South Africa,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 +KOR,South Korea,1,Bank of Korea IO tables,2018,GHG data published with the Bank of Korea IO tables,2018 +ESP,Spain,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +LKA,Sri Lanka,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SWE,Sweden,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +CHE,Switzerland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +TWN,Taiwan,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +TZA,Tanzania,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +THA,Thailand,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +TLS,Timor-Leste,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TGO,Togo,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TTO,Trinidad and Tobago,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TUN,Tunisia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 +TUR,Türkiye,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 +UGA,Uganda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +UKR,Ukraine,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +ARE,United Arab Emirates,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GBR,United Kingdom,1,ONS IO Analytical Tables,2023,ONS atmospheric emissions accounts,2023 +USA,United States,0,Cornerstone nowcast Make and Use tables,2024,U.S. GHG inventory with facility data,2024 +URY,Uruguay,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +VUT,Vanuatu,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +VNM,Viet Nam,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 diff --git a/figures/scripts/methods_by_country.py b/figures/scripts/methods_by_country.py new file mode 100644 index 00000000..4c23b1d5 --- /dev/null +++ b/figures/scripts/methods_by_country.py @@ -0,0 +1,49 @@ +"""Write the country table in reference/methods-by-country.md from data/country_tiers.csv. + +Usage: + python figures/scripts/methods_by_country.py + +The table is written between the BEGIN and END markers in the page; everything +else on the page is left as it is. Rows keep the CSV's order (by country name). +""" + +from __future__ import annotations + +import csv +import os + +ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) +TIERS_CSV = os.path.join(ROOT, "data", "country_tiers.csv") +PAGE = os.path.join(ROOT, "reference", "methods-by-country.md") +BEGIN = "" +END = "" + +HEADER = ( + "| Country | ISO3 | Tier | IO table | IO data year | GHG data | GHG data year |\n" + "|---|---|---|---|---|---|---|\n" +) + + +def build_table() -> str: + with open(TIERS_CSV, encoding="utf-8", newline="") as f: + rows = list(csv.DictReader(f)) + lines = [ + f"| {r['country']} | {r['iso3']} | {r['tier']} | {r['io_source']} " + f"| {r['io_year']} | {r['ghg_source']} | {r['ghg_year']} |" + for r in rows + ] + return HEADER + "\n".join(lines) + "\n" + + +def main() -> None: + with open(PAGE, encoding="utf-8") as f: + page = f.read() + start = page.index(BEGIN) + len(BEGIN) + stop = page.index(END) + page = page[:start] + "\n\n" + build_table() + "\n" + page[stop:] + with open(PAGE, "w", encoding="utf-8", newline="\n") as f: + f.write(page) + + +if __name__ == "__main__": + main() diff --git a/reference/methods-by-country.md b/reference/methods-by-country.md index 41e37350..b9d31a36 100644 --- a/reference/methods-by-country.md +++ b/reference/methods-by-country.md @@ -3,21 +3,174 @@ title: "Methods by country" --- :::{tip} Summary -*To be written.* +The IO table and greenhouse gas data behind each of the 148 countries in the model, with the year of each. ::: -:::{note} Draft placeholder +:::{note} Draft :class: dropdown -Plan §3.8 · target: **RC (Oct 27)** +Planned for v1.0: a filterable table with a clickable map, and per-country details on trade reconciliation, accounting basis, currency and price index, and benchmarked sectors. +::: +Each country's {term}`tier ` sets which kind of IO table and emissions data it starts from. See [](../io/country-tiers.md) for the IO tables and [](../ee/country-tiers.md) for the emissions data. -**Planned content** +All IO tables are converted to 2024 U.S. dollars. Emissions stay at their data year, so a country's direct emission intensities are its data-year emissions per 2024 dollar of output. Tier 3 countries are the exception: their intensities are 2018 emissions per 2018 dollar (see [](../ee/country-tiers.md#ghg-data-years)). -- RC: a simple table of all countries generated from the version record -- v1.0: filterable table with a clickable map, plus one page per country at `/countries//` -- Per country: tier, IO source/edition/year, trade reconciliation, GHG source/year, accounting basis, currency and price index, benchmarked sectors, "Changed in" notes -- Per country: data years for the IO table, trade shares, and gap-fill shares, and any country-specific assumptions (e.g., where data years differ) -::: +The rest-of-world region is not in the table. Its input recipe and emission intensities are pooled from Colombia, Mexico, Türkiye, and Chile. + + + +| Country | ISO3 | Tier | IO table | IO data year | GHG data | GHG data year | +|---|---|---|---|---|---|---| +| Afghanistan | AFG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Albania | ALB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Algeria | DZA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Angola | AGO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Antigua and Barbuda | ATG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Argentina | ARG | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Australia | AUS | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Austria | AUT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Bahamas | BHS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Bahrain | BHR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Bangladesh | BGD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Barbados | BRB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Belgium | BEL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Belize | BLZ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Benin | BEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Bhutan | BTN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Bolivia | BOL | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Brazil | BRA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Bulgaria | BGR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Burkina Faso | BFA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Burundi | BDI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Cambodia | KHM | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Cameroon | CMR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Canada | CAN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Central African Republic | CAF | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Chad | TCD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Chile | CHL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| China | CHN | 1 | China National Bureau of Statistics IO table | 2023 | Built from OWID, CEDS, national energy statistics, and China's BTR1 | 2023 | +| Colombia | COL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Congo | COG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Costa Rica | CRI | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Côte d'Ivoire | CIV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Croatia | HRV | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Cyprus | CYP | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Czechia | CZE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Denmark | DNK | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Dominica | DMA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Dominican Republic | DOM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Ecuador | ECU | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Egypt | EGY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| El Salvador | SLV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Equatorial Guinea | GNQ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Estonia | EST | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Eswatini | SWZ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Ethiopia | ETH | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Fiji | FJI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Finland | FIN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| France | FRA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Gabon | GAB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Gambia | GMB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Germany | DEU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Greece | GRC | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Grenada | GRD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Guatemala | GTM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Guinea | GIN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Guinea-Bissau | GNB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Haiti | HTI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Honduras | HND | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Hong Kong | HKG | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Hungary | HUN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Iceland | ISL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| India | IND | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Indonesia | IDN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Iran | IRN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Iraq | IRQ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Ireland | IRL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Israel | ISR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Italy | ITA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Jamaica | JAM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Japan | JPN | 1 | Input-Output Tables for Japan | 2020 | Environmental data published with the Japan IO tables | 2020 | +| Jordan | JOR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Kazakhstan | KAZ | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Kenya | KEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Kiribati | KIR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Kuwait | KWT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Laos | LAO | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Latvia | LVA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Lebanon | LBN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Lesotho | LSO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Lithuania | LTU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Luxembourg | LUX | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Malawi | MWI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Malaysia | MYS | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Maldives | MDV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Mali | MLI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Malta | MLT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Mauritius | MUS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Mexico | MEX | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Moldova | MDA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Mongolia | MNG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Morocco | MAR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Myanmar | MMR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Namibia | NAM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Nauru | NRU | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Nepal | NPL | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Netherlands | NLD | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| New Zealand | NZL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Nicaragua | NIC | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Niger | NER | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Nigeria | NGA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| North Macedonia | MKD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Norway | NOR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Oman | OMN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Pakistan | PAK | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Papua New Guinea | PNG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Paraguay | PRY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Peru | PER | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Philippines | PHL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Poland | POL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Portugal | PRT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Qatar | QAT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Romania | ROU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Russia | RUS | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Rwanda | RWA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Saint Kitts and Nevis | KNA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Saint Lucia | LCA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Saint Vincent and the Grenadines | VCT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Samoa | WSM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Saudi Arabia | SAU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| Senegal | SEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Seychelles | SYC | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Sierra Leone | SLE | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Singapore | SGP | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Slovakia | SVK | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Slovenia | SVN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Solomon Islands | SLB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| South Africa | ZAF | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | +| South Korea | KOR | 1 | Bank of Korea IO tables | 2018 | GHG data published with the Bank of Korea IO tables | 2018 | +| Spain | ESP | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Sri Lanka | LKA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Sweden | SWE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Switzerland | CHE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Taiwan | TWN | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Tanzania | TZA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Thailand | THA | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Timor-Leste | TLS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Togo | TGO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Trinidad and Tobago | TTO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Tunisia | TUN | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | +| Türkiye | TUR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | +| Uganda | UGA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Ukraine | UKR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| United Arab Emirates | ARE | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| United Kingdom | GBR | 1 | ONS IO Analytical Tables | 2023 | ONS atmospheric emissions accounts | 2023 | +| United States | USA | 0 | Cornerstone nowcast Make and Use tables | 2024 | U.S. GHG inventory with facility data | 2024 | +| Uruguay | URY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Vanuatu | VUT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Viet Nam | VNM | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | + + +++ From 0d2f4126d77249b766cc9090735f730ece06c427 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 16:01:15 -0400 Subject: [PATCH 10/26] Shorten Tier 3 labels and give one IO year in methods-by-country Co-Authored-By: Claude Opus 5.5 --- data/country_tiers.csv | 166 +++++++++++++++---------------- reference/methods-by-country.md | 168 ++++++++++++++++---------------- 2 files changed, 168 insertions(+), 166 deletions(-) diff --git a/data/country_tiers.csv b/data/country_tiers.csv index 9753c5f1..b5d61b41 100644 --- a/data/country_tiers.csv +++ b/data/country_tiers.csv @@ -1,149 +1,149 @@ iso3,country,tier,io_source,io_year,ghg_source,ghg_year -AFG,Afghanistan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -ALB,Albania,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -DZA,Algeria,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -AGO,Angola,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -ATG,Antigua and Barbuda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +AFG,Afghanistan,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +ALB,Albania,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +DZA,Algeria,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +AGO,Angola,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +ATG,Antigua and Barbuda,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 ARG,Argentina,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 AUS,Australia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 AUT,Austria,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -BHS,Bahamas,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BHR,Bahrain,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BGD,Bangladesh,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BRB,Barbados,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BHS,Bahamas,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BHR,Bahrain,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BGD,Bangladesh,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BRB,Barbados,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 BEL,Belgium,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -BLZ,Belize,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BEN,Benin,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BTN,Bhutan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BOL,Bolivia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BLZ,Belize,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BEN,Benin,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BTN,Bhutan,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BOL,Bolivia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 BRA,Brazil,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 BGR,Bulgaria,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -BFA,Burkina Faso,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -BDI,Burundi,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +BFA,Burkina Faso,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +BDI,Burundi,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 KHM,Cambodia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -CMR,Cameroon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CMR,Cameroon,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 CAN,Canada,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 -CAF,Central African Republic,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -TCD,Chad,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CAF,Central African Republic,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +TCD,Chad,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 CHL,Chile,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 CHN,China,1,China National Bureau of Statistics IO table,2023,"Built from OWID, CEDS, national energy statistics, and China's BTR1",2023 COL,Colombia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -COG,Congo,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +COG,Congo,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 CRI,Costa Rica,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -CIV,Côte d'Ivoire,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +CIV,Côte d'Ivoire,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 HRV,Croatia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 CYP,Cyprus,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 CZE,Czechia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 DNK,Denmark,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -DMA,Dominica,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -DOM,Dominican Republic,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -ECU,Ecuador,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -EGY,Egypt,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -SLV,El Salvador,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -GNQ,Equatorial Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +DMA,Dominica,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +DOM,Dominican Republic,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +ECU,Ecuador,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +EGY,Egypt,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +SLV,El Salvador,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +GNQ,Equatorial Guinea,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 EST,Estonia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -SWZ,Eswatini,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -ETH,Ethiopia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -FJI,Fiji,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SWZ,Eswatini,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +ETH,Ethiopia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +FJI,Fiji,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 FIN,Finland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 FRA,France,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -GAB,Gabon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -GMB,Gambia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GAB,Gabon,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +GMB,Gambia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 DEU,Germany,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 GRC,Greece,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -GRD,Grenada,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -GTM,Guatemala,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -GIN,Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -GNB,Guinea-Bissau,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -HTI,Haiti,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -HND,Honduras,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +GRD,Grenada,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +GTM,Guatemala,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +GIN,Guinea,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +GNB,Guinea-Bissau,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +HTI,Haiti,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +HND,Honduras,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 HKG,Hong Kong,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 HUN,Hungary,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 ISL,Iceland,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 IND,India,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 IDN,Indonesia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 -IRN,Iran,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -IRQ,Iraq,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +IRN,Iran,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +IRQ,Iraq,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 IRL,Ireland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 ISR,Israel,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 ITA,Italy,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -JAM,Jamaica,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +JAM,Jamaica,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 JPN,Japan,1,Input-Output Tables for Japan,2020,Environmental data published with the Japan IO tables,2020 -JOR,Jordan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +JOR,Jordan,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 KAZ,Kazakhstan,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -KEN,Kenya,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -KIR,Kiribati,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -KWT,Kuwait,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +KEN,Kenya,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +KIR,Kiribati,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +KWT,Kuwait,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 LAO,Laos,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 LVA,Latvia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -LBN,Lebanon,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -LSO,Lesotho,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LBN,Lebanon,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +LSO,Lesotho,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 LTU,Lithuania,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 LUX,Luxembourg,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -MWI,Malawi,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MWI,Malawi,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 MYS,Malaysia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -MDV,Maldives,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -MLI,Mali,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MDV,Maldives,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +MLI,Mali,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 MLT,Malta,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -MUS,Mauritius,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MUS,Mauritius,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 MEX,Mexico,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 -MDA,Moldova,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -MNG,Mongolia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +MDA,Moldova,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +MNG,Mongolia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 MAR,Morocco,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 MMR,Myanmar,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -NAM,Namibia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -NRU,Nauru,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -NPL,Nepal,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NAM,Namibia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +NRU,Nauru,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +NPL,Nepal,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 NLD,Netherlands,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 NZL,New Zealand,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -NIC,Nicaragua,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -NER,Niger,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -NGA,Nigeria,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -MKD,North Macedonia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +NIC,Nicaragua,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +NER,Niger,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +NGA,Nigeria,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +MKD,North Macedonia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 NOR,Norway,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -OMN,Oman,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -PAK,Pakistan,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -PNG,Papua New Guinea,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -PRY,Paraguay,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +OMN,Oman,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +PAK,Pakistan,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +PNG,Papua New Guinea,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +PRY,Paraguay,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 PER,Peru,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 PHL,Philippines,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 POL,Poland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 PRT,Portugal,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -QAT,Qatar,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +QAT,Qatar,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 ROU,Romania,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 RUS,Russia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 -RWA,Rwanda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -KNA,Saint Kitts and Nevis,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -LCA,Saint Lucia,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -VCT,Saint Vincent and the Grenadines,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -WSM,Samoa,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +RWA,Rwanda,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +KNA,Saint Kitts and Nevis,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +LCA,Saint Lucia,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +VCT,Saint Vincent and the Grenadines,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +WSM,Samoa,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 SAU,Saudi Arabia,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 -SEN,Senegal,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -SYC,Seychelles,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -SLE,Sierra Leone,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SEN,Senegal,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +SYC,Seychelles,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +SLE,Sierra Leone,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 SGP,Singapore,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 SVK,Slovakia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 SVN,Slovenia,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -SLB,Solomon Islands,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +SLB,Solomon Islands,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 ZAF,South Africa,2,"FIGARO, 2026 edition",2023,"FIGARO, from EDGAR with CEDS corrections",2023 KOR,South Korea,1,Bank of Korea IO tables,2018,GHG data published with the Bank of Korea IO tables,2018 ESP,Spain,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -LKA,Sri Lanka,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +LKA,Sri Lanka,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 SWE,Sweden,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 CHE,Switzerland,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 TWN,Taiwan,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -TZA,Tanzania,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TZA,Tanzania,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 THA,Thailand,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 -TLS,Timor-Leste,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -TGO,Togo,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -TTO,Trinidad and Tobago,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +TLS,Timor-Leste,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +TGO,Togo,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +TTO,Trinidad and Tobago,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 TUN,Tunisia,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 TUR,Türkiye,2,"FIGARO, 2026 edition",2023,"FIGARO, from air emissions accounts",2023 -UGA,Uganda,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -UKR,Ukraine,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -ARE,United Arab Emirates,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +UGA,Uganda,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +UKR,Ukraine,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +ARE,United Arab Emirates,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 GBR,United Kingdom,1,ONS IO Analytical Tables,2023,ONS atmospheric emissions accounts,2023 USA,United States,0,Cornerstone nowcast Make and Use tables,2024,U.S. GHG inventory with facility data,2024 -URY,Uruguay,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 -VUT,Vanuatu,3,"Template from Mexico, Malaysia, and Tunisia",2020–2023,Template scaled with EDGAR v6.0 fossil CO₂,2018 +URY,Uruguay,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 +VUT,Vanuatu,3,Tier 3 IO template,2020,"Tier 3 GHG template, scaled to national CO₂ total",2018 VNM,Viet Nam,2,"ICIO, 2025 edition",2020,"OECD GHG emissions for ICIO, 2025 edition",2020 diff --git a/reference/methods-by-country.md b/reference/methods-by-country.md index b9d31a36..a2d53515 100644 --- a/reference/methods-by-country.md +++ b/reference/methods-by-country.md @@ -15,159 +15,161 @@ Each country's {term}`tier ` sets which kind of IO table and emiss All IO tables are converted to 2024 U.S. dollars. Emissions stay at their data year, so a country's direct emission intensities are its data-year emissions per 2024 dollar of output. Tier 3 countries are the exception: their intensities are 2018 emissions per 2018 dollar (see [](../ee/country-tiers.md#ghg-data-years)). +Tier 3 countries share one IO template, a blend of Malaysia (30%) and Tunisia (40%) from the ICIO for 2020 and Mexico (30%) from FIGARO for 2023; the table gives 2020, the year of most of the blend. They also share one GHG template, scaled to each country's fossil CO₂ total from {term}`EDGAR` (see [](../ee/country-tiers.md#tier-3-template-emissions)). + The rest-of-world region is not in the table. Its input recipe and emission intensities are pooled from Colombia, Mexico, Türkiye, and Chile. | Country | ISO3 | Tier | IO table | IO data year | GHG data | GHG data year | |---|---|---|---|---|---|---| -| Afghanistan | AFG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Albania | ALB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Algeria | DZA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Angola | AGO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Antigua and Barbuda | ATG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Afghanistan | AFG | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Albania | ALB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Algeria | DZA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Angola | AGO | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Antigua and Barbuda | ATG | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Argentina | ARG | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | | Australia | AUS | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | | Austria | AUT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Bahamas | BHS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Bahrain | BHR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Bangladesh | BGD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Barbados | BRB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Bahamas | BHS | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Bahrain | BHR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Bangladesh | BGD | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Barbados | BRB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Belgium | BEL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Belize | BLZ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Benin | BEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Bhutan | BTN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Bolivia | BOL | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Belize | BLZ | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Benin | BEN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Bhutan | BTN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Bolivia | BOL | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Brazil | BRA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | | Bulgaria | BGR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Burkina Faso | BFA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Burundi | BDI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Burkina Faso | BFA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Burundi | BDI | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Cambodia | KHM | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Cameroon | CMR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Cameroon | CMR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Canada | CAN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | -| Central African Republic | CAF | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Chad | TCD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Central African Republic | CAF | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Chad | TCD | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Chile | CHL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | China | CHN | 1 | China National Bureau of Statistics IO table | 2023 | Built from OWID, CEDS, national energy statistics, and China's BTR1 | 2023 | | Colombia | COL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Congo | COG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Congo | COG | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Costa Rica | CRI | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Côte d'Ivoire | CIV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Côte d'Ivoire | CIV | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Croatia | HRV | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Cyprus | CYP | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Czechia | CZE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Denmark | DNK | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Dominica | DMA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Dominican Republic | DOM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Ecuador | ECU | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Egypt | EGY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| El Salvador | SLV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Equatorial Guinea | GNQ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Dominica | DMA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Dominican Republic | DOM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Ecuador | ECU | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Egypt | EGY | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| El Salvador | SLV | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Equatorial Guinea | GNQ | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Estonia | EST | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Eswatini | SWZ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Ethiopia | ETH | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Fiji | FJI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Eswatini | SWZ | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Ethiopia | ETH | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Fiji | FJI | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Finland | FIN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | France | FRA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Gabon | GAB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Gambia | GMB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Gabon | GAB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Gambia | GMB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Germany | DEU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Greece | GRC | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Grenada | GRD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Guatemala | GTM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Guinea | GIN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Guinea-Bissau | GNB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Haiti | HTI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Honduras | HND | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Grenada | GRD | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Guatemala | GTM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Guinea | GIN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Guinea-Bissau | GNB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Haiti | HTI | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Honduras | HND | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Hong Kong | HKG | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Hungary | HUN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Iceland | ISL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | India | IND | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | | Indonesia | IDN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | -| Iran | IRN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Iraq | IRQ | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Iran | IRN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Iraq | IRQ | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Ireland | IRL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Israel | ISR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Italy | ITA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Jamaica | JAM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Jamaica | JAM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Japan | JPN | 1 | Input-Output Tables for Japan | 2020 | Environmental data published with the Japan IO tables | 2020 | -| Jordan | JOR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Jordan | JOR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Kazakhstan | KAZ | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Kenya | KEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Kiribati | KIR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Kuwait | KWT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Kenya | KEN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Kiribati | KIR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Kuwait | KWT | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Laos | LAO | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Latvia | LVA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Lebanon | LBN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Lesotho | LSO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Lebanon | LBN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Lesotho | LSO | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Lithuania | LTU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Luxembourg | LUX | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Malawi | MWI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Malawi | MWI | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Malaysia | MYS | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Maldives | MDV | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Mali | MLI | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Maldives | MDV | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Mali | MLI | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Malta | MLT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Mauritius | MUS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Mauritius | MUS | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Mexico | MEX | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | -| Moldova | MDA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Mongolia | MNG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Moldova | MDA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Mongolia | MNG | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Morocco | MAR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Myanmar | MMR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Namibia | NAM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Nauru | NRU | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Nepal | NPL | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Namibia | NAM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Nauru | NRU | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Nepal | NPL | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Netherlands | NLD | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | New Zealand | NZL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Nicaragua | NIC | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Niger | NER | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Nigeria | NGA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| North Macedonia | MKD | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Nicaragua | NIC | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Niger | NER | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Nigeria | NGA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| North Macedonia | MKD | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Norway | NOR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Oman | OMN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Pakistan | PAK | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Papua New Guinea | PNG | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Paraguay | PRY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Oman | OMN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Pakistan | PAK | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Papua New Guinea | PNG | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Paraguay | PRY | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Peru | PER | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Philippines | PHL | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Poland | POL | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Portugal | PRT | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Qatar | QAT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Qatar | QAT | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Romania | ROU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Russia | RUS | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | -| Rwanda | RWA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Saint Kitts and Nevis | KNA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Saint Lucia | LCA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Saint Vincent and the Grenadines | VCT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Samoa | WSM | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Rwanda | RWA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Saint Kitts and Nevis | KNA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Saint Lucia | LCA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Saint Vincent and the Grenadines | VCT | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Samoa | WSM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Saudi Arabia | SAU | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | -| Senegal | SEN | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Seychelles | SYC | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Sierra Leone | SLE | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Senegal | SEN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Seychelles | SYC | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Sierra Leone | SLE | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Singapore | SGP | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Slovakia | SVK | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Slovenia | SVN | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Solomon Islands | SLB | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Solomon Islands | SLB | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | South Africa | ZAF | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from EDGAR with CEDS corrections | 2023 | | South Korea | KOR | 1 | Bank of Korea IO tables | 2018 | GHG data published with the Bank of Korea IO tables | 2018 | | Spain | ESP | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Sri Lanka | LKA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Sri Lanka | LKA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Sweden | SWE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Switzerland | CHE | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Taiwan | TWN | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Tanzania | TZA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Tanzania | TZA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Thailand | THA | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | -| Timor-Leste | TLS | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Togo | TGO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Trinidad and Tobago | TTO | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Timor-Leste | TLS | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Togo | TGO | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Trinidad and Tobago | TTO | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Tunisia | TUN | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Türkiye | TUR | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | -| Uganda | UGA | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Ukraine | UKR | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| United Arab Emirates | ARE | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Uganda | UGA | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Ukraine | UKR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| United Arab Emirates | ARE | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | United Kingdom | GBR | 1 | ONS IO Analytical Tables | 2023 | ONS atmospheric emissions accounts | 2023 | | United States | USA | 0 | Cornerstone nowcast Make and Use tables | 2024 | U.S. GHG inventory with facility data | 2024 | -| Uruguay | URY | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | -| Vanuatu | VUT | 3 | Template from Mexico, Malaysia, and Tunisia | 2020–2023 | Template scaled with EDGAR v6.0 fossil CO₂ | 2018 | +| Uruguay | URY | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | +| Vanuatu | VUT | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Viet Nam | VNM | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | From 0bac91fdfd9d57cf6096c21facc62c5326500129 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 16:33:17 -0400 Subject: [PATCH 11/26] Drop dollar-year detail from GHG and methods pages; scope country table to 2024-2026 factors Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 28 +++++++++++++--------------- factors/year-and-currency.md | 1 + reference/methods-by-country.md | 8 ++++++-- 3 files changed, 20 insertions(+), 17 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 54eeb922..84177b6d 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -107,8 +107,6 @@ Each country then adjusts the template two ways: - **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. Fossil CO₂ is from EDGAR (version 6.0) for 2018, and GDP from the IMF World Economic Outlook (October 2021). - **Electricity.** The electricity sector uses the country's own power-sector CO₂ from EDGAR for 2018, divided by the value of its electricity output: 2018 generation from the U.S. Energy Information Administration times an average electricity price from the World Bank. -Unlike other countries' intensities, Tier 3 intensities are not re-priced: they are 2018 emissions per 2018 dollar. - ## Rest of world The rest-of-world region's direct emission intensities are the output-weighted average of four Tier 2 countries: Colombia and Chile (from ICIO) and Mexico and Türkiye (from FIGARO). See [](../io/index.md) for how the region is used. @@ -118,26 +116,26 @@ The rest-of-world region's direct emission intensities are the output-weighted a Emissions data are published on different schedules, and the model uses the most recent for each country. -| Tier | Countries | Emissions data year | Intensities per | -|---|---|---|---| -| Tier 0 | United States | 2024 | 2024 dollar | -| Tier 1 | China, United Kingdom | 2023 | 2024 dollar | -| Tier 1 | Japan | 2020 | 2024 dollar | -| Tier 1 | South Korea | 2018 | 2024 dollar | -| Tier 2 | FIGARO countries | 2023 | 2024 dollar | -| Tier 2 | ICIO countries | 2020 | 2024 dollar | -| Tier 3 | 83 countries | 2018 | 2018 dollar | -| Rest of world | | 2020–2023, from its four countries | 2024 dollar | +| Tier | Countries | Emissions data year | +|---|---|---| +| Tier 0 | United States | 2024 | +| Tier 1 | China, United Kingdom | 2023 | +| Tier 1 | Japan | 2020 | +| Tier 1 | South Korea | 2018 | +| Tier 2 | FIGARO countries | 2023 | +| Tier 2 | ICIO countries | 2020 | +| Tier 3 | 83 countries | 2018 | +| Rest of world | | 2020–2023, from its four countries | -Emissions stay at their data year. Output, the denominator of `B`, is re-priced to 2024 dollars, so each country's `B` is its data-year emissions per 2024 dollar. Tier 3 countries are the exception: their intensities are not re-priced. +Emissions stay at their data year. For the data year of each country's IO table, see [](../reference/methods-by-country.md). :::{important} Key assumptions :class: dropdown -**Data-year emissions per 2024 dollar** +**Data-year emissions describe current production** - **Assumption:** Each country's emissions from its data year still describe 2024 production. - **Why we make it:** Emissions data by sector, matched to each source's IO sectors, are published with a lag, in some cases of several years. -- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). Tier 3 intensities are also per 2018 dollar, so price changes since 2018 are not reflected. +- **How it affects results:** Where emissions per unit of output have fallen since the data year, for example as electricity grids get cleaner, factors may be too high. The gap is largest for South Korea and Tier 3 countries (2018) and for Japan and ICIO countries (2020). **ICIO countries take the U.S. gas mix** diff --git a/factors/year-and-currency.md b/factors/year-and-currency.md index 0ee194d6..3b845315 100644 --- a/factors/year-and-currency.md +++ b/factors/year-and-currency.md @@ -14,6 +14,7 @@ Plan §3.4.4 · target: **RC (Oct 27)** **Planned content** - Pick the file for your spend year (RC dollar years to confirm) +- How the 2024, 2025, and 2026 factors are made from the same data: price indices used, and the exception for Tier 3 countries, whose direct intensities are not re-priced from 2018 dollars - Spend in another year: sector-specific price indices vs. general CPI - Spend in another currency: market exchange rate for the year of spend, then the factor for that year - Reporting across years and recalculating when a new release comes out diff --git a/reference/methods-by-country.md b/reference/methods-by-country.md index a2d53515..05cd0688 100644 --- a/reference/methods-by-country.md +++ b/reference/methods-by-country.md @@ -3,7 +3,7 @@ title: "Methods by country" --- :::{tip} Summary -The IO table and greenhouse gas data behind each of the 148 countries in the model, with the year of each. +The IO table and greenhouse gas data behind each of the 148 countries in the model, with the data year of each. ::: :::{note} Draft @@ -13,12 +13,16 @@ Planned for v1.0: a filterable table with a clickable map, and per-country detai Each country's {term}`tier ` sets which kind of IO table and emissions data it starts from. See [](../io/country-tiers.md) for the IO tables and [](../ee/country-tiers.md) for the emissions data. -All IO tables are converted to 2024 U.S. dollars. Emissions stay at their data year, so a country's direct emission intensities are its data-year emissions per 2024 dollar of output. Tier 3 countries are the exception: their intensities are 2018 emissions per 2018 dollar (see [](../ee/country-tiers.md#ghg-data-years)). +The data sources and years used can differ between the dollar years that factors are published for, so the table is given for each set of dollar years that share the same data. Tier 3 countries share one IO template, a blend of Malaysia (30%) and Tunisia (40%) from the ICIO for 2020 and Mexico (30%) from FIGARO for 2023; the table gives 2020, the year of most of the blend. They also share one GHG template, scaled to each country's fossil CO₂ total from {term}`EDGAR` (see [](../ee/country-tiers.md#tier-3-template-emissions)). The rest-of-world region is not in the table. Its input recipe and emission intensities are pooled from Colombia, Mexico, Türkiye, and Chile. +## 2024, 2025, and 2026 emission factors + +The release candidate's 2024, 2025, and 2026 factors are all built from the same data, below. Each is expressed in its own year's dollars; see [](../factors/year-and-currency.md). + | Country | ISO3 | Tier | IO table | IO data year | GHG data | GHG data year | From daeaffba85b4ea2f44af44d04991255ee1b07e8f Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 16:37:52 -0400 Subject: [PATCH 12/26] Rename IO country tiers page to IO sources by country tier Co-Authored-By: Claude Opus 5.5 --- io/country-tiers.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/io/country-tiers.md b/io/country-tiers.md index a17bae2e..17e0a529 100644 --- a/io/country-tiers.md +++ b/io/country-tiers.md @@ -1,5 +1,5 @@ --- -title: "Country tiers" +title: "IO sources by country tier" --- :::{tip} Summary From 7835b27a8a0257e7b5ae98549a6a62492ce72cab Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 16:41:22 -0400 Subject: [PATCH 13/26] Add GHG pipeline diagram and stop overview at D = C x B Co-Authored-By: Claude Opus 5.5 --- ee/index.md | 11 ++-- figures/diagrams/ghg-pipeline.svg | 100 ++++++++++++++++++++++++++++++ figures/figures.csv | 1 + 3 files changed, 107 insertions(+), 5 deletions(-) create mode 100644 figures/diagrams/ghg-pipeline.svg diff --git a/ee/index.md b/ee/index.md index 43c927c2..0fcc1204 100644 --- a/ee/index.md +++ b/ee/index.md @@ -6,9 +6,10 @@ title: "The GHG extension: overview" The GHG extension attaches each sector's own greenhouse gas emissions to the IO model, as emissions of each gas per dollar of output (`B`). Every country follows the same steps, but the emissions data behind them, and how much detail they carry, depend on the country's tier. ::: -:::{note} Draft -:class: dropdown -**Key visual to add:** pipeline from source emissions → split and map to the common sectors → convert to AR6 → divide by output → `B`. +:::{figure} ../figures/diagrams/ghg-pipeline.svg +:label: fig-ghg-pipeline +:alt: Seven boxes in a row joined by arrows. 1, source emissions by source sector, from a national inventory, national accounts, FIGARO, or ICIO. 2, split broad sectors, such as electricity, gas, and heat, or farming. 3, spread onto the 405 common sectors with ABSR, weighted by U.S. intensities. 4, fill in gas detail from the U.S. mix for the sector. 5, convert sources reported as AR5 CO2e to AR6, gas by gas. 6, divide by the same sector's output q in the IO model. The result is B, kilograms of each gas per dollar, for 7 gases and 405 sectors in each country. A dashed line shows the U.S. skipping steps 2 to 4, because it is already on the 405 common sectors with all 7 gases. A bracket under steps 2 to 4 notes that each country's source totals are kept through them. +From source emissions to direct emission intensities (`B`). Every country follows the same steps; the U.S. starts on the common sectors and skips steps 2 to 4. ::: ## What the extension adds @@ -20,7 +21,7 @@ The IO model traces the dollars that flow through supply chains. The GHG extensi `B` holds direct emissions only: what the sector emits from its own fuel use, processes, and other activities. Emissions from the sector's suppliers come in through the supply chain ([`L`](../io/index.md#total-requirements)), not through `B`. For example, the emissions from generating electricity stay with the power sector, and other sectors' purchased electricity reaches them through `L`. -Characterization factors (`C`) then weight each gas by its global warming potential, which gives the direct emission factors `D = C × B` and the total emission factors `N = C × B × L` (see [](../reference/notation.md)). +Characterization factors (`C`) then weight each gas by its global warming potential, which gives the direct emission factors `D = C × B` (see [](../reference/notation.md)). ## Gases and global warming potentials @@ -57,7 +58,7 @@ Every country's emissions go through the same steps: 5. **Convert to AR6** where the source used other GWPs. 6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. Emissions data years differ by country; see [](country-tiers.md#ghg-data-years). -The U.S. model is built directly on the 405 common sectors, so steps 3 and 4 do not apply. [](country-tiers.md) gives the sources and the variations for each tier. +The U.S. model is built directly on the 405 common sectors with all seven gases, so steps 2 to 4 do not apply ([](#fig-ghg-pipeline)). [](country-tiers.md) gives the sources and the variations for each tier. :::{important} Key assumptions :class: dropdown diff --git a/figures/diagrams/ghg-pipeline.svg b/figures/diagrams/ghg-pipeline.svg new file mode 100644 index 00000000..5a7b9181 --- /dev/null +++ b/figures/diagrams/ghg-pipeline.svg @@ -0,0 +1,100 @@ + + + + + + + + + + + + + + U.S.: already on the 405 common sectors, with all 7 gases + + + + 1 + Source + emissions + by source sector + + + + 2 + Split broad + sectors + + + + 3 + Spread onto + 405 sectors + + + + 4 + Fill in + gas detail + + + + 5 + Convert + to AR6 + + + + 6 + Divide by + output q + + + + B + kg gas per $ + + + + + + + + + + + + National inventory, + national accounts, + FIGARO, or ICIO + + For example, + electricity, gas, + and heat; farming + + With ABSR, + weighted by U.S. + intensities + + Missing gases + from the U.S. mix + for the sector + + Sources reported + as AR5 CO₂e, + gas by gas + + The same sector's + output in the + IO model + + 7 gases × + 405 sectors, + for each country + + + + + Each country's source totals are kept through steps 2 to 4 + diff --git a/figures/figures.csv b/figures/figures.csv index dd8bf7f0..500ca58c 100644 --- a/figures/figures.csv +++ b/figures/figures.csv @@ -4,3 +4,4 @@ io-domestic-imported,io/index.md,diagram (SVG),hand-made,,,draft io-tables-to-a,io/index.md,diagram (SVG),hand-made,,,draft io-mrio-blocks,io/index.md,diagram (SVG),hand-made (after CEDA team slide 19),,,draft country-tiers-map,io/country-tiers.md,map (SVG),data/country_tiers.csv + Natural Earth 1:50m admin-0,figures/scripts/tier_map.py,,draft +ghg-pipeline,ee/index.md,diagram (SVG),hand-made,,,draft From 7a76c69b187a4d023d2998c8291749af14c5123f Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 16:57:41 -0400 Subject: [PATCH 14/26] Revise GHG pipeline: allocate wording, step 4 only where needed, x then q Drop the U.S. bypass and per-step captions; mark gas fill as dashed and not needed for the U.S., China, Japan, or the UK; describe division by industry output then conversion to commodities with market shares. Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 2 +- ee/index.md | 16 ++-- figures/diagrams/ghg-pipeline.svg | 126 +++++++++++------------------- 3 files changed, 56 insertions(+), 88 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 84177b6d..d54565f4 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -33,7 +33,7 @@ The U.S. has the most detailed emissions data, and its model is built on all 405 - **Directly.** Where the inventory names the industry, as for most process and fugitive emissions (petroleum and natural gas systems, cement, and other industrial processes), the emissions go to that industry. - **Facility reports.** Most fuel burned at industrial plants is placed using what the plants themselves report: emissions reported to EPA's {term}`GHGRP`, and to the National Emissions Inventory, matched to one record per site. Power plants come from EPA's eGRID for 2024. For manufacturing natural gas, coal, and petroleum fuels, each industry's share comes from facility reports where they cover at least 80% of the industry's combustion, and from the Manufacturing Energy Consumption Survey (2022) where they don't. - **Physical fuel use.** Fuel burned in vehicles and equipment is placed on the industries that use it, based on fuel volumes. Highway fuel is split by vehicle owner using Federal Highway Administration data for 2024, with federal fleets from GSA's Federal Fleet Report and private trucks by business type from the Census Bureau's Vehicle Inventory and Use Survey (2021). Industrial diesel is split across agriculture, construction, mining, and manufacturing from fuel sales and survey data. -- **Purchases.** The remaining emissions are spread across the industries that buy the relevant fuel or product, in proportion to their purchases in the U.S. Use table. +- **Purchases.** The remaining emissions are allocated to the industries that buy the relevant fuel or product, in proportion to their purchases in the U.S. Use table. **Checks inside the build.** After placing the emissions, every industry's emissions are held at or above what its own facilities report to the GHGRP, and industries whose facilities cover nearly all their combustion are held at or below it. National totals for each activity and gas are unchanged. diff --git a/ee/index.md b/ee/index.md index 0fcc1204..e43b3a90 100644 --- a/ee/index.md +++ b/ee/index.md @@ -8,8 +8,8 @@ The GHG extension attaches each sector's own greenhouse gas emissions to the IO :::{figure} ../figures/diagrams/ghg-pipeline.svg :label: fig-ghg-pipeline -:alt: Seven boxes in a row joined by arrows. 1, source emissions by source sector, from a national inventory, national accounts, FIGARO, or ICIO. 2, split broad sectors, such as electricity, gas, and heat, or farming. 3, spread onto the 405 common sectors with ABSR, weighted by U.S. intensities. 4, fill in gas detail from the U.S. mix for the sector. 5, convert sources reported as AR5 CO2e to AR6, gas by gas. 6, divide by the same sector's output q in the IO model. The result is B, kilograms of each gas per dollar, for 7 gases and 405 sectors in each country. A dashed line shows the U.S. skipping steps 2 to 4, because it is already on the 405 common sectors with all 7 gases. A bracket under steps 2 to 4 notes that each country's source totals are kept through them. -From source emissions to direct emission intensities (`B`). Every country follows the same steps; the U.S. starts on the common sectors and skips steps 2 to 4. +:alt: Seven boxes in a row joined by arrows: 1, source emissions by source sector; 2, split broad sectors; 3, allocate to the 405 common sectors; 4, fill in gas detail where needed, drawn dashed, with a note that it is not needed for the U.S., China, Japan, or the UK; 5, convert to AR6; 6, divide by output, first industry output x and then per commodity output q. The result is B, kilograms of each gas per dollar. A bracket under steps 2 to 4 notes that each country's source totals are kept through them. +From source emissions to direct emission intensities (`B`). Every country follows the same steps; step 4 is needed only where a source does not separate every gas. ::: ## What the extension adds @@ -17,7 +17,7 @@ From source emissions to direct emission intensities (`B`). Every country follow The IO model traces the dollars that flow through supply chains. The GHG extension adds what each sector emits while making its output. For each country and sector it records: - **Emissions** (`E`): kilograms of each gas emitted by the sector in a year. -- **Direct emission intensities** (`B`): those emissions divided by the sector's output (`q`), so kilograms of each gas per dollar of output. +- **Direct emission intensities** (`B`): those emissions divided by output, so kilograms of each gas per dollar of output. `B` holds direct emissions only: what the sector emits from its own fuel use, processes, and other activities. Emissions from the sector's suppliers come in through the supply chain ([`L`](../io/index.md#total-requirements)), not through `B`. For example, the emissions from generating electricity stay with the power sector, and other sectors' purchased electricity reaches them through `L`. @@ -53,18 +53,18 @@ Every country's emissions go through the same steps: 1. **Start from source emissions by source sector.** Each source reports emissions on its own sector list, which can be anything from hundreds of activities (the U.S. inventory) to 50 industries (ICIO). 2. **Split broad sectors where better data exist.** Some sources lump together sectors with very different emissions, such as electricity, gas, and heat, or all of farming. Where other data can separate them, the broad sector is split first, keeping its total. -3. **Allocate to the common sectors.** For non-Tier 0 countries, each source sector's emissions are allocated to the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. -4. **Fill in missing gas detail.** Where a source does not separate every gas, the missing split is taken from the U.S. mix for the same sector. +3. **Allocate to the common sectors.** For the U.S., each inventory activity is allocated to the industries that emit it. For other countries, each source sector's emissions are allocated to the matching common sectors with {term}`ABSR`, weighted by U.S. emission intensities. The country's total for each source sector is kept. +4. **Fill in missing gas detail.** Where a source does not separate every gas, the missing split is taken from the U.S. mix for the same sector. This is not needed for the U.S., China, Japan, or the UK, whose sources cover all seven gases. 5. **Convert to AR6** where the source used other GWPs. -6. **Divide by output.** Emissions for each sector are divided by the same sector's output in the IO model, giving `B`. Emissions data years differ by country; see [](country-tiers.md#ghg-data-years). +6. **Divide by output.** Each industry's emissions are divided by its output (`x`), then converted to commodities using market shares (who makes each commodity), giving `B` per dollar of commodity output (`q`). Emissions data years differ by country; see [](country-tiers.md#ghg-data-years). -The U.S. model is built directly on the 405 common sectors with all seven gases, so steps 2 to 4 do not apply ([](#fig-ghg-pipeline)). [](country-tiers.md) gives the sources and the variations for each tier. +[](country-tiers.md) gives the sources and how each step is done for each tier. :::{important} Key assumptions :class: dropdown **U.S. intensities shape detail within each source sector** -- **Assumption:** Within each source sector, a country's emissions are spread over the common sectors in proportion to U.S. emission intensities. +- **Assumption:** Within each source sector, a country's emissions are allocated to the common sectors in proportion to U.S. emission intensities. - **Why we make it:** Outside the U.S., emissions data come on far fewer sectors than the 405 common sectors, and the U.S. data are the most detailed available. - **How it affects results:** Each country's total for each source sector is correct, but its split between detailed sectors follows the U.S. pattern. Where a country's mix of processes differs from the U.S. (for example, a different steelmaking route), detailed sectors within the same source sector could be too high or too low. diff --git a/figures/diagrams/ghg-pipeline.svg b/figures/diagrams/ghg-pipeline.svg index 5a7b9181..154036f1 100644 --- a/figures/diagrams/ghg-pipeline.svg +++ b/figures/diagrams/ghg-pipeline.svg @@ -1,100 +1,68 @@ - + - - - - - - - - U.S.: already on the 405 common sectors, with all 7 gases + - - 1 - Source - emissions - by source sector + + 1 + Source + emissions + by source sector - - 2 - Split broad - sectors - - - - 3 - Spread onto - 405 sectors - - - - 4 - Fill in - gas detail + + 2 + Split broad + sectors + + + + 3 + Allocate to + 405 sectors + + + + 4 + Fill in + gas detail + where needed - - 5 - Convert - to AR6 + + 5 + Convert + to AR6 - - 6 - Divide by - output q + + 6 + Divide by + output + x, then per q - - B - kg gas per $ + + B + kg gas per $ - - - - - - - - - - National inventory, - national accounts, - FIGARO, or ICIO - - For example, - electricity, gas, - and heat; farming - - With ABSR, - weighted by U.S. - intensities - - Missing gases - from the U.S. mix - for the sector - - Sources reported - as AR5 CO₂e, - gas by gas - - The same sector's - output in the - IO model + + + + + + - 7 gases × - 405 sectors, - for each country - + + Not needed for the U.S., + China, Japan, or the UK - - Each country's source totals are kept through steps 2 to 4 + + Each country's source totals are kept through steps 2 to 4 From 6f0925ee9efe0db6b448aa4facd0d37382e03e93 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 17:37:25 -0400 Subject: [PATCH 15/26] Move U.S. facility floor and ceiling into the Checks we run box Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index d54565f4..90f54aaf 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -35,8 +35,6 @@ The U.S. has the most detailed emissions data, and its model is built on all 405 - **Physical fuel use.** Fuel burned in vehicles and equipment is placed on the industries that use it, based on fuel volumes. Highway fuel is split by vehicle owner using Federal Highway Administration data for 2024, with federal fleets from GSA's Federal Fleet Report and private trucks by business type from the Census Bureau's Vehicle Inventory and Use Survey (2021). Industrial diesel is split across agriculture, construction, mining, and manufacturing from fuel sales and survey data. - **Purchases.** The remaining emissions are allocated to the industries that buy the relevant fuel or product, in proportion to their purchases in the U.S. Use table. -**Checks inside the build.** After placing the emissions, every industry's emissions are held at or above what its own facilities report to the GHGRP, and industries whose facilities cover nearly all their combustion are held at or below it. National totals for each activity and gas are unchanged. - **Households.** Emissions the inventory places in homes and personal vehicles go to households and are not in `B` (see [](index.md)). ## Tier 1: National sources @@ -157,8 +155,8 @@ Emissions stay at their data year. For the data year of each country's IO table, ::: :::{seealso} Checks we run -- Each country's total emissions are kept through splitting and mapping. -- For the U.S., each industry is checked against what its own facilities report. +- Each country's total emissions are kept through splitting and allocation. +- **U.S. facility floor and ceiling.** After the U.S. emissions are allocated, every industry's emissions are held at or above what its own facilities report to the {term}`GHGRP`, and industries whose facilities cover nearly all their combustion are held at or below it. U.S. national totals for each activity and gas are unchanged. See [Validation](#validation-hub). ::: From 2bb793984e9edeea9d2b80bd37ab83c094b8988c Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 17:45:58 -0400 Subject: [PATCH 16/26] Drop Learn more sections from GHG extension pages for now Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 6 ------ ee/index.md | 6 ------ 2 files changed, 12 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 90f54aaf..7c2f4371 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -161,12 +161,6 @@ Emissions stay at their data year. For the data year of each country's IO table, See [Validation](#validation-hub). ::: -## Learn more - -- **From the field:** *to be added* -- **Cornerstone papers:** *to be added* -- **Code:** *to be added* - +++ :::{div} diff --git a/ee/index.md b/ee/index.md index e43b3a90..b9c38432 100644 --- a/ee/index.md +++ b/ee/index.md @@ -88,12 +88,6 @@ Every country's emissions go through the same steps: See [Validation](#validation-hub). ::: -## Learn more - -- **From the field:** *to be added* -- **Cornerstone papers:** *to be added* -- **Code:** *to be added* - +++ :::{div} From 7440ec0a9e929105ae535e4a11c1733198f2097d Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 17:46:36 -0400 Subject: [PATCH 17/26] Use allocation wording in GHG overview checks Co-Authored-By: Claude Opus 5.5 --- ee/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ee/index.md b/ee/index.md index b9c38432..ad1f5609 100644 --- a/ee/index.md +++ b/ee/index.md @@ -82,7 +82,7 @@ Every country's emissions go through the same steps: ::: :::{seealso} Checks we run -- Splitting and mapping keep each country's source totals, so its total emissions in the model match its source data. +- Splitting and allocation keep each country's source totals, so its total emissions in the model match its source data. - U.S. totals by gas match the national inventory. See [Validation](#validation-hub). From c86791766a6a71641f6c05bfd33137e5ab62cdae Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 17:52:27 -0400 Subject: [PATCH 18/26] Add source citations to GHG extension pages Add 38 verified references (U.S. inventory, facility, energy and vehicle data; EDGAR, CEDS, OWID, FAOSTAT, Eurostat, OECD, ONS, Bank of Korea, IPCC GWPs and guidelines) and cite them inline on the GHG overview and GHG data by country tier pages. Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 36 ++-- ee/index.md | 6 +- references.bib | 427 +++++++++++++++++++++++++++++++++++++++++++- 3 files changed, 447 insertions(+), 22 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 7c2f4371..30648473 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -26,13 +26,13 @@ The emissions data for each country follow its {term}`tier `: a de The U.S. has the most detailed emissions data, and its model is built on all 405 common sectors. -**National totals.** The U.S. greenhouse gas inventory sets the national totals for 2024, by emitting activity and gas. These come from the University of Maryland's GHG inventory analysis, which follows the tables of EPA's *Inventory of U.S. Greenhouse Gas Emissions and Sinks*, with detail from EPA's inventory for 2023 where it is needed (for example, agricultural soils and fluorinated gases). The inventory is on a {term}`territorial basis `. +**National totals.** The U.S. greenhouse gas inventory sets the national totals for 2024, by emitting activity and gas. These come from the University of Maryland's GHG inventory analysis [@desaiGreenhouseGasInventory2026], which follows the tables of EPA's *Inventory of U.S. Greenhouse Gas Emissions and Sinks*, with detail from EPA's inventory for 2023 where it is needed (for example, agricultural soils and fluorinated gases) [@epaInventoryUSGreenhouse2025]. The inventory is on a {term}`territorial basis `. **Placing the totals on industries.** The inventory names an industry for some emissions and not others, so each emitting activity is placed on industries by one of these routes: - **Directly.** Where the inventory names the industry, as for most process and fugitive emissions (petroleum and natural gas systems, cement, and other industrial processes), the emissions go to that industry. -- **Facility reports.** Most fuel burned at industrial plants is placed using what the plants themselves report: emissions reported to EPA's {term}`GHGRP`, and to the National Emissions Inventory, matched to one record per site. Power plants come from EPA's eGRID for 2024. For manufacturing natural gas, coal, and petroleum fuels, each industry's share comes from facility reports where they cover at least 80% of the industry's combustion, and from the Manufacturing Energy Consumption Survey (2022) where they don't. -- **Physical fuel use.** Fuel burned in vehicles and equipment is placed on the industries that use it, based on fuel volumes. Highway fuel is split by vehicle owner using Federal Highway Administration data for 2024, with federal fleets from GSA's Federal Fleet Report and private trucks by business type from the Census Bureau's Vehicle Inventory and Use Survey (2021). Industrial diesel is split across agriculture, construction, mining, and manufacturing from fuel sales and survey data. +- **Facility reports.** Most fuel burned at industrial plants is placed using what the plants themselves report: emissions reported to EPA's {term}`GHGRP` [@epaGreenhouseGasReporting2026], and to the National Emissions Inventory [@epaNationalEmissionsInventory2025], matched to one record per site. Power plants come from eGRID for 2024 [@cornerstoneEGRID20242026]. For manufacturing natural gas, coal, and petroleum fuels, each industry's share comes from facility reports where they cover at least 80% of the industry's combustion, and from the Manufacturing Energy Consumption Survey (2022) where they don't [@eiaManufacturingEnergyConsumption2025]. +- **Physical fuel use.** Fuel burned in vehicles and equipment is placed on the industries that use it, based on fuel volumes. Highway fuel is split by vehicle owner using Federal Highway Administration data for 2024 [@fhwaHighwayStatistics2025], with federal fleets from GSA's Federal Fleet Report [@gsaFederalFleetReport2025] and private trucks by business type from the Census Bureau's Vehicle Inventory and Use Survey (2021) [@censusVehicleInventoryUse2023]. Industrial diesel is split across agriculture, construction, mining, and manufacturing from fuel sales and survey data [@eiaFuelOilKerosene2022; @eiaManufacturingEnergyConsumption2025]. - **Purchases.** The remaining emissions are allocated to the industries that buy the relevant fuel or product, in proportion to their purchases in the U.S. Use table. **Households.** Emissions the inventory places in homes and personal vehicles go to households and are not in `B` (see [](index.md)). @@ -45,17 +45,17 @@ Each Tier 1 country's emissions come from its own national data. |---|---|---|---| | China | Built from several sources (see below) | 2023 | 211, matching the IO table | | Japan | Environmental data published with the Input-Output Tables for Japan | 2020 | Matching the IO table | -| South Korea | GHG data published with the Bank of Korea input-output tables | 2018 | Matching the IO table | -| United Kingdom | ONS atmospheric emissions accounts | 2023 | By industry | +| South Korea | GHG data published with the Bank of Korea input-output tables [@bokUpdatedInputOutput2020] | 2018 | Matching the IO table | +| United Kingdom | ONS atmospheric emissions accounts [@onsAtmosphericEmissionsGreenhouse2024] | 2023 | By industry | China's data are on a territorial basis, and the UK's on a residence basis. **China** has no published emissions table matching its IO table, so we build one: -- CO₂ from fossil fuels and cement sets the totals, from Our World in Data, and is placed on sectors by each sector's physical fuel use from China's national energy statistics. -- Power-sector CO₂ is set to match China's official 2023 grid emission factor. -- CH₄ and N₂O come from the Community Emissions Data System ({term}`CEDS`), and farm CH₄ and N₂O from China's first Biennial Transparency Report. -- Fluorinated gases come from China's first Biennial Transparency Report, brought forward to 2023 with {term}`EDGAR` trends. +- CO₂ from fossil fuels and cement sets the totals, from Our World in Data [@ritchieCO2GreenhouseGas2023], and is placed on sectors by each sector's physical fuel use from China's national energy statistics. +- Power-sector CO₂ is set to match China's official 2023 grid emission factor [@meeAnnouncementRelease2025]. +- CH₄ and N₂O come from the Community Emissions Data System ({term}`CEDS`) [@hoeslyCEDSAggregate2025; @hoeslyHistorical17502014Anthropogenic2018], and farm CH₄ and N₂O from China's first Biennial Transparency Report [@chinaFirstBiennialTransparency2024]. +- Fluorinated gases come from China's first Biennial Transparency Report, brought forward to 2023 with {term}`EDGAR` trends [@crippaGHGEmissionsAll2025]. Household fuel use is not separated in China's national totals, so its CO₂ is spread over the industries rather than left out. @@ -69,7 +69,7 @@ Tier 2 countries take their emissions from the same source as their IO table, so | | FIGARO | ICIO | |---|---|---| -| Publisher | Eurostat | OECD | +| Publisher | Eurostat [@eurostatGreenhouseGasEmission2026] | OECD [@oecdGreenhouseGasFootprints2025; @yamanoCO2EmissionsEmbodied2020] | | Version | 2026 | 2025 | | Data year | 2023 | 2020 | | Sectors | 64 industries (NACE Rev. 2) | 50 industries (ISIC Rev. 4) | @@ -81,29 +81,29 @@ Tier 2 countries take their emissions from the same source as their IO table, so FIGARO emissions come from two kinds of underlying data: -- **Air emissions accounts (30 countries).** The 27 EU member states report emissions by industry in their air emissions accounts. For Norway, Switzerland, and Türkiye, Eurostat fills in the industry split. -- **EDGAR estimates (10 countries).** For Argentina, Australia, Brazil, Canada, India, Indonesia, Mexico, Russia, Saudi Arabia, and South Africa, Eurostat estimates emissions by industry from {term}`EDGAR`. EDGAR groups some activities together, so we correct the split. Within mining, refining, and the power and gas utilities, CO₂, CH₄, and N₂O are re-split using {term}`CEDS` shares, holding the combined total fixed. Shares for steel, chemicals, and non-metallic minerals are also reset to CEDS, and process CO₂ is kept off trade and service industries. +- **Air emissions accounts (30 countries).** The 27 EU member states report emissions by industry in their air emissions accounts [@eurostatAirEmissionsAccounts2026]. For Norway, Switzerland, and Türkiye, Eurostat fills in the industry split. +- **EDGAR estimates (10 countries).** For Argentina, Australia, Brazil, Canada, India, Indonesia, Mexico, Russia, Saudi Arabia, and South Africa, Eurostat estimates emissions by industry from {term}`EDGAR` [@crippaGHGEmissionsAll2025; @schaafEmissionsDatabaseGlobal2025]. EDGAR groups some activities together, so we correct the split. Within mining, refining, and the power and gas utilities, CO₂, CH₄, and N₂O are re-split using {term}`CEDS` shares [@hoeslyCEDSAggregate2025], holding the combined total fixed. Shares for steel, chemicals, and non-metallic minerals are also reset to CEDS, and process CO₂ is kept off trade and service industries. For both groups, FIGARO's industries are first converted to products using FIGARO's supply table, to match the product-by-product IO table. The same broad sectors split in the IO table are split here too: -- Electricity, gas, and heat are separated using Eurostat energy balances and CEDS gas distribution methane. -- Agriculture is split into farm sectors using FAOSTAT CH₄ and N₂O and Eurostat agricultural accounts. +- Electricity, gas, and heat are separated using Eurostat energy balances [@eurostatCompleteEnergyBalances2026] and CEDS gas distribution methane. +- Agriculture is split into farm sectors using FAOSTAT CH₄ and N₂O [@faoFAOSTATEmissionsTotals2025] and Eurostat agricultural accounts [@eurostatEconomicAccountsAgriculture2026]. - Mining, non-metallic minerals, and basic metals are split as in the IO table. The products are then mapped to the common sectors with {term}`ABSR`. The last gas group, SF₆ with NF₃, is split using the U.S. share of SF₆ in each sector. ### ICIO countries -The OECD data give one CO₂e total for each of the 50 industries, with no split by gas. Farming is split out first, using FAOSTAT CH₄ and N₂O, before the totals are mapped to the common sectors with ABSR. The split by gas comes entirely from the U.S. mix for each sector. Electricity is mapped as one sector, with no separate split for gas and heat. +The OECD data give one CO₂e total for each of the 50 industries, with no split by gas. Farming is split out first, using FAOSTAT CH₄ and N₂O [@faoFAOSTATEmissionsTotals2025], before the totals are mapped to the common sectors with ABSR. The split by gas comes entirely from the U.S. mix for each sector. Electricity is mapped as one sector, with no separate split for gas and heat. ## Tier 3: Template emissions -Tier 3 countries have no emissions data matched to an IO table. Their direct emission intensities start from the same template as their input recipe, a blend of Mexico (30%), Malaysia (30%), and Tunisia (40%). The template uses those countries' CO₂ emissions by industry for 2018, from the OECD's 2021 edition of CO₂ emissions embodied in international trade. Other gases are added using the U.S. ratio of total CO₂e to CO₂ in each sector. +Tier 3 countries have no emissions data matched to an IO table. Their direct emission intensities start from the same template as their input recipe, a blend of Mexico (30%), Malaysia (30%), and Tunisia (40%). The template uses those countries' CO₂ emissions by industry for 2018, from the OECD's 2021 edition of CO₂ emissions embodied in international trade [@oecdCarbonDioxideEmissions2021]. Other gases are added using the U.S. ratio of total CO₂e to CO₂ in each sector. Each country then adjusts the template two ways: -- **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. Fossil CO₂ is from EDGAR (version 6.0) for 2018, and GDP from the IMF World Economic Outlook (October 2021). -- **Electricity.** The electricity sector uses the country's own power-sector CO₂ from EDGAR for 2018, divided by the value of its electricity output: 2018 generation from the U.S. Energy Information Administration times an average electricity price from the World Bank. +- **Overall level.** All intensities are scaled by the country's fossil CO₂ per unit of GDP relative to the template's. Fossil CO₂ is from EDGAR (version 6.0) for 2018 [@crippaGHGEmissionsAll2021; @monfortiferrarioEDGARV60Greenhouse2021], and GDP from the IMF World Economic Outlook (October 2021) [@imfWorldEconomicOutlook2021]. +- **Electricity.** The electricity sector uses the country's own power-sector CO₂ from EDGAR for 2018, divided by the value of its electricity output: 2018 generation from the U.S. Energy Information Administration [@eiaInternationalEnergyStatistics2026] times an average electricity price from the World Bank. ## Rest of world diff --git a/ee/index.md b/ee/index.md index ad1f5609..318c2e1e 100644 --- a/ee/index.md +++ b/ee/index.md @@ -27,16 +27,16 @@ Characterization factors (`C`) then weight each gas by its global warming potent `B` has a row for each of seven gases or gas groups: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF₆), and nitrogen trifluoride (NF₃). -They are combined into CO₂-equivalent with 100-year {term}`GWPs ` from the IPCC's Sixth Assessment Report (AR6). Methane is valued two ways: fossil methane, from fuel production and use, at 29.8, and non-fossil methane, from farming and waste, at 27.0. Fossil methane is valued higher because, once it breaks down, it leaves CO₂ that was not already in the atmosphere. +They are combined into CO₂-equivalent with 100-year {term}`GWPs ` from the IPCC's Sixth Assessment Report (AR6) [@forsterEarthsEnergyBudget2021]. Methane is valued two ways: fossil methane, from fuel production and use, at 29.8, and non-fossil methane, from farming and waste, at 27.0. Fossil methane is valued higher because, once it breaks down, it leaves CO₂ that was not already in the atmosphere. -Several sources report emissions as CO₂-equivalent using older GWPs from the Fifth Assessment Report (AR5). These are converted to AR6, gas by gas. +Several sources report emissions as CO₂-equivalent using older GWPs from the Fifth Assessment Report (AR5) [@myhreAnthropogenicNaturalRadiative2013]. These are converted to AR6, gas by gas. ## What is and isn't counted `B` covers emissions from producing goods and services. Some emissions in national inventories do not come from a producing sector, and they are left out: - **Household direct emissions.** Fuel burned in homes and in personal vehicles is emitted by households, not by an industry, so it is not in `B`. -- **Land use, land-use change, and forestry (LULUCF).** National inventories, following IPCC guidelines, report farming and LULUCF as separate sectors. Farming emissions are counted, in the farm sectors: methane from livestock and rice, N₂O from agricultural soils, CO₂ from liming and urea, and methane and N₂O from burning crop residues in the field. The LULUCF sector is not counted. This leaves out changes in the carbon stored in forests, soils, and other land, including CO₂ removed from the atmosphere, along with emissions from flooded lands and from forest and grassland fires. +- **Land use, land-use change, and forestry (LULUCF).** National inventories, following IPCC guidelines [@egglestonIPCCGuidelinesNational2006], report farming and LULUCF as separate sectors. Farming emissions are counted, in the farm sectors: methane from livestock and rice, N₂O from agricultural soils, CO₂ from liming and urea, and methane and N₂O from burning crop residues in the field. The LULUCF sector is not counted. This leaves out changes in the carbon stored in forests, soils, and other land, including CO₂ removed from the atmosphere, along with emissions from flooded lands and from forest and grassland fires. ## Accounting basis diff --git a/references.bib b/references.bib index f11e9417..cce06d35 100644 --- a/references.bib +++ b/references.bib @@ -37,4 +37,429 @@ @report{beaConceptsMethodsUS2009 url = {https://www.bea.gov/resources/methodologies/concepts-methods-io-accounts}, urldate = {2019-10-29}, } - \ No newline at end of file + +@report{desaiGreenhouseGasInventory2026, + title = {Greenhouse {{Gas Inventory}} and {{Analysis}} for the {{United States}}: 1990--2024}, + author = {Desai, Mausami and Camobreco, Vincent and Hedger, Toby and Irving, William and Rewcastle, Kenna and Steller, John and Barbieri, Lindsay and Weitz, Melissa and Murumkar, Tanvi and Fawcett, Allen and Lou, Jiehong and Cui, Ryna and Hultman, Nate}, + date = {2026}, + institution = {Center for Global Sustainability, University of Maryland}, + location = {College Park, MD}, + doi = {10.13016/g1xw-qftw}, + url = {https://ghgi.cgs.umd.edu/Web%20Content/Chapters/GHGIA_FullReport_2026.pdf}, + urldate = {2026-10-21}, +} + +@report{epaInventoryUSGreenhouse2025, + title = {Inventory of {{U}}.{{S}}. {{Greenhouse Gas Emissions}} and {{Sinks}}: 1990--2023}, + author = {{U.S. Environmental Protection Agency}}, + date = {2025}, + institution = {U.S. Environmental Protection Agency (EPA)}, + location = {Washington, DC}, + number = {EPA 430-R-25-003}, + note = {Not published by EPA; released via Freedom of Information Act request to the Environmental Defense Fund, posted May 8, 2025}, + url = {https://www.edf.org/freedom-information-act-documents-epas-greenhouse-gas-inventory}, + urldate = {2026-10-21}, +} + +@dataset{epaGreenhouseGasReporting2026, + title = {Greenhouse {{Gas Reporting Program}} ({{GHGRP}}): {{Reporting Year}} 2024 {{Data}}}, + author = {{U.S. Environmental Protection Agency}}, + date = {2026-03-12}, + publisher = {Environmental Integrity Project}, + location = {Washington, DC}, + note = {Facility-level data reported to EPA under 40 CFR Part 98 for calendar year 2024; not published by EPA, obtained via Freedom of Information Act request and released by the Environmental Integrity Project}, + url = {https://environmentalintegrity.org/2024-greenhouse-gas-reporting-program-data/}, + urldate = {2026-10-21}, +} + +@dataset{epaNationalEmissionsInventory2025, + title = {2022 {{National Emissions Inventory}} ({{NEI}})}, + author = {{U.S. Environmental Protection Agency}}, + date = {2025}, + publisher = {U.S. Environmental Protection Agency (EPA)}, + location = {Research Triangle Park, NC}, + note = {2022 inventory-year data, including facility summaries by pollutant and the 2022 emissions modeling platform}, + url = {https://www.epa.gov/air-emissions-inventories/get-air-emissions-data-0}, + urldate = {2026-10-21}, +} + +@dataset{cornerstoneEGRID20242026, + title = {{{eGRID2024}}}, + author = {{Cornerstone Sustainability Data Initiative}}, + date = {2026-03-17}, + publisher = {Cornerstone Sustainability Data Initiative}, + version = {1.0.0}, + doi = {10.5281/zenodo.18968658}, + note = {Generated by running U.S. EPA's public eGRID source code on 2024 input data; not an official EPA release}, + url = {https://zenodo.org/records/18968658}, + urldate = {2026-10-21}, +} + +@dataset{eiaManufacturingEnergyConsumption2025, + title = {2022 {{Manufacturing Energy Consumption Survey}} ({{MECS}})}, + author = {{U.S. Energy Information Administration}}, + date = {2025}, + publisher = {U.S. Energy Information Administration (EIA)}, + location = {Washington, DC}, + note = {Tables released August 6, 2025 through March 18, 2026}, + url = {https://www.eia.gov/consumption/manufacturing/data/2022/}, + urldate = {2026-10-21}, +} + +@dataset{fhwaHighwayStatistics2025, + title = {Highway {{Statistics}} 2024}, + author = {{Federal Highway Administration}}, + date = {2025-12/2026-01}, + publisher = {U.S. Department of Transportation, Federal Highway Administration, Office of Highway Policy Information}, + location = {Washington, DC}, + note = {Tables MF-21 (Motor-Fuel Use), MV-7 (Publicly Owned Vehicles), and MV-10 (Bus Registrations)}, + url = {https://www.fhwa.dot.gov/policyinformation/statistics/2024/}, + urldate = {2026-10-21}, +} + +@dataset{gsaFederalFleetReport2025, + title = {Federal {{Fleet Report}}: {{Fiscal Year}} 2024}, + author = {{U.S. General Services Administration}}, + date = {2025}, + publisher = {U.S. General Services Administration (GSA), Office of Government-wide Policy}, + location = {Washington, DC}, + note = {Agency fleet inventory, cost, fuel, and use data reported through the Federal Automotive Statistical Tool (FAST)}, + url = {https://www.gsa.gov/policy-regulations/policy/motor-vehicle-management-policy/federal-fleet-report-ffr}, + urldate = {2026-10-21}, +} + +@dataset{censusVehicleInventoryUse2023, + title = {2021 {{Vehicle Inventory}} and {{Use Survey}} ({{VIUS}}): {{National Estimates}}}, + author = {{U.S. Census Bureau} and {Bureau of Transportation Statistics}}, + date = {2023}, + publisher = {U.S. Census Bureau and U.S. Department of Transportation, Bureau of Transportation Statistics}, + location = {Washington, DC}, + note = {Data tables released September 28, 2023; public use file released December 28, 2023}, + url = {https://www.census.gov/programs-surveys/vius.html}, + urldate = {2026-10-21}, +} + +@dataset{eiaFuelOilKerosene2022, + title = {Fuel {{Oil}} and {{Kerosene Sales}} 2020}, + author = {{U.S. Energy Information Administration}}, + date = {2022-02-14}, + publisher = {U.S. Energy Information Administration (EIA)}, + location = {Washington, DC}, + note = {2020 data; final release, series suspended}, + url = {https://www.eia.gov/petroleum/fueloilkerosene/}, + urldate = {2026-10-21}, +} + +@incollection{forsterEarthsEnergyBudget2021, + title = {The {{Earth}}'s {{Energy Budget}}, {{Climate Feedbacks}}, and {{Climate Sensitivity}}}, + booktitle = {Climate {{Change}} 2021: {{The Physical Science Basis}}. {{Contribution}} of {{Working Group I}} to the {{Sixth Assessment Report}} of the {{Intergovernmental Panel}} on {{Climate Change}}}, + author = {Forster, Piers and Storelvmo, Trude and Armour, Kyle and Collins, William and Dufresne, Jean-Louis and Frame, David and Lunt, Daniel J. and Mauritsen, Thorsten and Palmer, Matthew D. and Watanabe, Masahiro and Wild, Martin and Zhang, Hua}, + editor = {Masson-Delmotte, Valérie and Zhai, Panmao and Pirani, Anna and Connors, Sarah L. and Péan, Clotilde and Berger, Sophie and Caud, Nada and Chen, Yang and Goldfarb, Leah and Gomis, Melissa I. and Huang, Mengtian and Leitzell, Katherine and Lonnoy, Elisabeth and Matthews, J. B. Robin and Maycock, Thomas K. and Waterfield, Tim and Yelekçi, Özge and Yu, Rong and Zhou, Baiquan}, + date = {2021}, + pages = {923--1054}, + publisher = {Cambridge University Press}, + location = {Cambridge, UK and New York, NY, USA}, + doi = {10.1017/9781009157896.009}, +} + +@collection{egglestonIPCCGuidelinesNational2006, + title = {2006 {{IPCC Guidelines}} for {{National Greenhouse Gas Inventories}}}, + editor = {Eggleston, H. S. and Buendia, L. and Miwa, K. and Ngara, T. and Tanabe, K.}, + date = {2006}, + publisher = {Institute for Global Environmental Strategies (IGES)}, + location = {Hayama, Japan}, + note = {Prepared by the National Greenhouse Gas Inventories Programme of the Intergovernmental Panel on Climate Change}, + url = {https://www.ipcc-nggip.iges.or.jp/public/2006gl/}, + urldate = {2026-10-21}, +} + +@incollection{myhreAnthropogenicNaturalRadiative2013, + title = {Anthropogenic and {{Natural Radiative Forcing}}}, + booktitle = {Climate {{Change}} 2013: {{The Physical Science Basis}}. {{Contribution}} of {{Working Group I}} to the {{Fifth Assessment Report}} of the {{Intergovernmental Panel}} on {{Climate Change}}}, + author = {Myhre, Gunnar and Shindell, Drew and Bréon, François-Marie and Collins, William and Fuglestvedt, Jan and Huang, Jianping and Koch, Dorothy and Lamarque, Jean-François and Lee, David and Mendoza, Blanca and Nakajima, Teruyuki and Robock, Alan and Stephens, Graeme and Takemura, Toshihiko and Zhang, Hua}, + editor = {Stocker, T. F. and Qin, D. and Plattner, G.-K. and Tignor, M. and Allen, S. K. and Boschung, J. and Nauels, A. and Xia, Y. and Bex, V. and Midgley, P. M.}, + date = {2013}, + pages = {659--740}, + publisher = {Cambridge University Press}, + location = {Cambridge, UK and New York, NY, USA}, + doi = {10.1017/CBO9781107415324.018}, +} + +@dataset{monfortiferrarioEDGARV60Greenhouse2021, + title = {{{EDGAR}} v6.0 {{Greenhouse Gas Emissions}}}, + author = {Monforti-Ferrario, Fabio and Crippa, Monica and Guizzardi, Diego and Muntean, Marilena and Schaaf, Edwin and Lo Vullo, Eleonora and Solazzo, Efisio and Olivier, Jos and Vignati, Elisabetta}, + date = {2021}, + publisher = {{European Commission, Joint Research Centre (JRC)}}, + version = {6.0}, + doi = {10.2905/JRC.787T5VR}, + url = {https://edgar.jrc.ec.europa.eu/dataset_ghg60}, + urldate = {2026-10-21}, +} + +@report{crippaGHGEmissionsAll2021, + title = {{{GHG}} Emissions of All World Countries -- 2021 Report}, + author = {Crippa, Monica and Guizzardi, Diego and Solazzo, Efisio and Muntean, Marilena and Schaaf, Edwin and Monforti-Ferrario, Fabio and Banja, Manjola and Olivier, Jos and Grassi, Giacomo and Rossi, Simone and Vignati, Elisabetta}, + date = {2021}, + number = {EUR 30831 EN; JRC126363}, + institution = {{Publications Office of the European Union}}, + location = {Luxembourg}, + isbn = {978-92-76-41546-6}, + doi = {10.2760/173513}, + url = {https://publications.jrc.ec.europa.eu/repository/handle/JRC126363}, +} + +@dataset{schaafEmissionsDatabaseGlobal2025, + title = {Emissions {{Database}} for {{Global Atmospheric Research}}, Version 2025 ({{EDGAR}}\_2025\_{{GHG}})}, + author = {Schaaf, Edwin and Crippa, Monica and Guizzardi, Diego and Pisoni, Enrico and Rossi, Simone and Banja, Manjola and Muntean, Marilena and Grassi, Giacomo and Pagani, Federico and Jacome Felix Oom, Duarte and Branco, Alfredo and San-Miguel, Jesus and Brandao De Melo, Joana and Pekar, Ferenc and Manca, Giovanni and Köykkä, Juha and Suarez-Moreno, Maria}, + date = {2025}, + publisher = {{European Commission, Joint Research Centre (JRC)}}, + version = {EDGAR\_2025\_GHG}, + doi = {10.2905/JRC.SYNW48G}, + url = {https://edgar.jrc.ec.europa.eu/dataset_ghg2025}, + urldate = {2026-10-21}, + note = {Includes IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O and EDGAR F-gases, 1970--2024}, +} + +@report{crippaGHGEmissionsAll2025, + title = {{{GHG}} Emissions of All World Countries -- 2025 Report}, + author = {Crippa, Monica and Guizzardi, Diego and Pagani, Federico and Banja, Manjola and Muntean, Marilena and Schaaf, Edwin and Quadrelli, Roberta and Risquez Martin, A. and Taghavi-Moharamli, Pouya and Köykkä, Juha and Grassi, Giacomo and Rossi, Simone and Melo, Joana and Jacome Felix Oom, Duarte and Branco, Alfredo and Suárez-Moreno, M. and Sedano, Fernando and San-Miguel, Jesus and Manca, Giovanni and Pisoni, Enrico and Pekar, Ferenc}, + date = {2025}, + number = {EUR 40443; JRC143227}, + institution = {{Publications Office of the European Union}}, + location = {Luxembourg}, + isbn = {978-92-68-31401-2}, + doi = {10.2760/9816914}, + url = {https://publications.jrc.ec.europa.eu/repository/handle/JRC143227}, +} + +@dataset{hoeslyCEDSAggregate2025, + title = {{{CEDS}} v\_2025\_03\_18 {{Aggregate Data}}}, + author = {Hoesly, Rachel and Smith, Steven J. and Ahsan, Hamza and Prime, Noah and O'Rourke, Patrick and Crippa, Monica and Klimont, Zbigniew and Guizzardi, Diego and Feng, Leyang and Harkins, Colin and McDonald, Brian and Wang, Shuxiao}, + date = {2025-03-18}, + publisher = {Zenodo}, + version = {v\_2025\_03\_18}, + doi = {10.5281/zenodo.15059443}, + url = {https://zenodo.org/records/15059443}, + urldate = {2026-10-21}, +} + +@article{hoeslyHistorical17502014Anthropogenic2018, + title = {Historical (1750--2014) Anthropogenic Emissions of Reactive Gases and Aerosols from the {{Community Emissions Data System}} ({{CEDS}})}, + author = {Hoesly, Rachel M. and Smith, Steven J. and Feng, Leyang and Klimont, Zbigniew and Janssens-Maenhout, Greet and Pitkanen, Tyler and Seibert, Jonathan J. and Vu, Linh and Andres, Robert J. and Bolt, Ryan M. and Bond, Tami C. and Dawidowski, Laura and Kholod, Nazar and Kurokawa, June-ichi and Li, Meng and Liu, Liang and Lu, Zifeng and Moura, Maria Cecilia P. and O'Rourke, Patrick R. and Zhang, Qiang}, + date = {2018}, + journaltitle = {Geoscientific Model Development}, + volume = {11}, + number = {1}, + pages = {369--408}, + doi = {10.5194/gmd-11-369-2018}, +} + +@online{ritchieCO2GreenhouseGas2023, + title = {{{CO2}} and {{Greenhouse Gas Emissions}}}, + author = {Ritchie, Hannah and Rosado, Pablo and Roser, Max}, + date = {2023}, + organization = {{Our World in Data}}, + url = {https://ourworldindata.org/co2-and-greenhouse-gas-emissions}, + urldate = {2026-10-21}, +} + +@report{chinaFirstBiennialTransparency2024, + title = {The {{People's Republic}} of {{China First Biennial Transparency Report}} on {{Climate Change}}}, + author = {{People's Republic of China}}, + date = {2024-12}, + institution = {{United Nations Framework Convention on Climate Change}}, + type = {Biennial Transparency Report}, + url = {https://unfccc.int/sites/default/files/resource/The%20People%E2%80%99s%20Republic%20of%20China%20First%20Biennial%20Transparency%20Report%20on%20Climate%20Change.pdf}, + urldate = {2026-10-21}, + note = {Unofficial English translation}, +} + +@online{meeAnnouncementRelease2025, + title = {Announcement on the Release of the 2023 Electricity Carbon Dioxide Emission Factors}, + author = {{Ministry of Ecology and Environment of the People's Republic of China} and {National Bureau of Statistics of China}}, + date = {2025-12-31}, + number = {Announcement No. 47 of 2025}, + url = {https://www.mee.gov.cn/xxgk2018/xxgk/xxgk01/202512/t20251231_1139517.html}, + urldate = {2026-10-21}, + langid = {chinese}, + note = {关于发布2023年电力二氧化碳排放因子的公告 (公告 2025年 第47号). National average electricity CO2 emission factor 0.5306 kg CO2/kWh}, +} + +@dataset{faoFAOSTATEmissionsTotals2025, + title = {{{FAOSTAT}}: {{Emissions Totals}}}, + author = {{FAO}}, + date = {2025}, + publisher = {{Food and Agriculture Organization of the United Nations}}, + location = {Rome}, + url = {https://www.fao.org/faostat/en/#data/GT}, + urldate = {2026-10-21}, + note = {Climate Change: Agrifood systems emissions domain (GT)}, +} + +@dataset{eurostatFIGAROEUInterCountry2026, + title = {{{FIGARO}} -- {{EU Inter-Country Supply}}, {{Use}} and {{Input-Output Tables}}, 2026 Edition}, + author = {{Eurostat}}, + date = {2026}, + publisher = {Eurostat}, + location = {Luxembourg}, + version = {2026 edition}, + url = {https://ec.europa.eu/eurostat/web/esa-supply-use-input-tables/database}, + urldate = {2026-10-21}, + note = {Covers 2010--2024; 64 industries (NACE Rev. 2) by 64 products (CPA 2.1)}, +} + +@report{remondtiedrezEUInterCountrySupply2019, + title = {{{EU}} Inter-Country Supply, Use and Input-Output Tables -- {{Full}} International and Global Accounts for Research in Input-Output Analysis ({{FIGARO}})}, + editor = {Remond-Tiedrez, Isabelle and Rueda-Cantuche, José M.}, + date = {2019}, + institution = {{Publications Office of the European Union}}, + location = {Luxembourg}, + type = {Statistical Working Papers}, + number = {KS-TC-19-002}, + isbn = {978-92-76-00805-7}, + doi = {10.2785/008780}, + url = {https://ec.europa.eu/eurostat/web/products-statistical-working-papers/-/ks-tc-19-002}, +} + +@dataset{eurostatGreenhouseGasEmission2026, + title = {Greenhouse Gas Emission Footprints (in {{CO2}} Equivalent, {{FIGARO}} Application)}, + author = {{Eurostat}}, + date = {2026}, + publisher = {Eurostat}, + number = {env\_ac\_ghgfp}, + doi = {10.2908/ENV_AC_GHGFP}, + url = {https://ec.europa.eu/eurostat/databrowser/view/env_ac_ghgfp/default/table}, + urldate = {2026-10-21}, +} + +@dataset{eurostatAirEmissionsAccounts2026, + title = {Air Emissions Accounts by {{NACE Rev}}. 2 Activity}, + author = {{Eurostat}}, + date = {2026}, + publisher = {Eurostat}, + number = {env\_ac\_ainah\_r2}, + doi = {10.2908/ENV_AC_AINAH_R2}, + url = {https://ec.europa.eu/eurostat/databrowser/view/env_ac_ainah_r2/default/table}, + urldate = {2026-10-21}, +} + +@dataset{eurostatCompleteEnergyBalances2026, + title = {Complete Energy Balances}, + author = {{Eurostat}}, + date = {2026}, + publisher = {Eurostat}, + number = {nrg\_bal\_c}, + doi = {10.2908/NRG_BAL_C}, + url = {https://ec.europa.eu/eurostat/databrowser/view/nrg_bal_c/default/table}, + urldate = {2026-10-21}, +} + +@dataset{eurostatEconomicAccountsAgriculture2026, + title = {Economic Accounts for Agriculture -- Values at Current Prices}, + author = {{Eurostat}}, + date = {2026}, + publisher = {Eurostat}, + number = {aact\_eaa01}, + doi = {10.2908/AACT_EAA01}, + url = {https://ec.europa.eu/eurostat/databrowser/view/aact_eaa01/default/table}, + urldate = {2026-10-21}, +} + +@dataset{oecdGreenhouseGasFootprints2025, + title = {Greenhouse {{Gas Footprints}} ({{GHGFP}}) 2025 Edition}, + author = {{OECD}}, + date = {2025}, + publisher = {{OECD Publishing}}, + location = {Paris}, + version = {2025 edition}, + url = {https://www.oecd.org/en/data/datasets/greenhouse-gas-footprint-indicators.html}, + urldate = {2026-10-21}, + note = {OECD Data Explorer dataflows OECD.STI.PIE:DSD\_ICIO\_GHG\_MAIN\_2025@DF\_ICIO\_GHG\_MAIN\_2025 (principal indicators), DF\_ICIO\_GHG\_SCOPE\_2025, DF\_ICIO\_GHG\_TRADE\_2025, DF\_ICIO\_GHG\_ORGN\_2025, DF\_ICIO\_GHG\_EXPD\_2025}, +} + +@report{yamanoCO2EmissionsEmbodied2020, + title = {{{CO2}} Emissions Embodied in International Trade and Domestic Final Demand: {{Methodology}} and Results Using the {{OECD Inter-Country Input-Output Database}}}, + author = {Yamano, Norihiko and Guilhoto, Joaquim}, + date = {2020}, + institution = {{OECD Publishing}}, + location = {Paris}, + type = {{{OECD Science}}, {{Technology}} and {{Industry Working Papers}}}, + number = {2020/11}, + doi = {10.1787/8f2963b8-en}, +} + +@dataset{oecdCarbonDioxideEmissions2021, + title = {Carbon Dioxide Emissions Embodied in International Trade ({{TECO2}}), 2021 Edition}, + author = {{OECD}}, + date = {2021-11}, + publisher = {{OECD Publishing}}, + location = {Paris}, + version = {2021 edition}, + url = {https://www.oecd.org/en/data/datasets/carbon-dioxide-emissions-embodied-in-international-trade.html}, + urldate = {2026-10-21}, + note = {Based on the 2021 editions of the OECD ICIO tables and IEA CO2 emissions from fuel combustion; production and final demand estimates 1995--2018}, +} + +@dataset{oecdInterCountryInputOutput2025, + title = {Inter-{{Country Input-Output}} ({{ICIO}}) {{Tables}}, 2025 Edition}, + author = {{OECD}}, + date = {2025}, + publisher = {{OECD Publishing}}, + location = {Paris}, + version = {2025 edition}, + url = {https://www.oecd.org/en/data/datasets/inter-country-input-output-tables.html}, + urldate = {2026-10-21}, + note = {Covers 1995--2022}, +} + +@dataset{onsAtmosphericEmissionsGreenhouse2024, + title = {Atmospheric Emissions: Greenhouse Gases by Industry and Gas}, + author = {{Office for National Statistics}}, + date = {2024-10-17}, + publisher = {{Office for National Statistics}}, + location = {Newport}, + url = {https://www.ons.gov.uk/economy/environmentalaccounts/datasets/ukenvironmentalaccountsatmosphericemissionsgreenhousegasemissionsbyeconomicsectorandgasunitedkingdom}, + urldate = {2026-10-21}, + note = {UK Environmental Accounts; SIC 2007 groups (around 130 industries)}, +} + +@dataset{micInputOutputTables2024, + title = {2020 {{Input-Output Tables}} for {{Japan}}}, + author = {{Ministry of Internal Affairs and Communications}}, + date = {2024-06-25}, + publisher = {{Ministry of Internal Affairs and Communications, Director-General for Policy Planning (Statistical Policy)}}, + location = {Tokyo}, + url = {https://www.soumu.go.jp/english/dgpp_ss/data/io/io20_00001.html}, + urldate = {2026-10-21}, + note = {Compiled jointly by ten ministries and agencies; also on e-Stat, statistics code 00200603 (https://www.e-stat.go.jp/en/statistics/00200603)}, +} + +@dataset{bokUpdatedInputOutput2020, + title = {2018 {{Updated Input-Output Tables}}}, + author = {{Bank of Korea}}, + date = {2020-06-24}, + publisher = {{Bank of Korea, Economic Statistics Department}}, + location = {Seoul}, + url = {https://www.bok.or.kr/eng/bbs/E0000634/view.do?nttId=10058883&menuNo=400069}, + urldate = {2026-10-21}, +} + +@dataset{imfWorldEconomicOutlook2021, + title = {World {{Economic Outlook Database}}, {{October}} 2021}, + author = {{International Monetary Fund}}, + date = {2021-10}, + publisher = {{International Monetary Fund}}, + location = {Washington, DC}, + url = {https://www.imf.org/en/publications/weo/weo-database/2021/october}, + urldate = {2026-10-21}, +} + +@online{eiaInternationalEnergyStatistics2026, + title = {International {{Energy Statistics}}: {{Electricity Generation}}}, + author = {{U.S. Energy Information Administration}}, + date = {2026}, + organization = {{U.S. Energy Information Administration}}, + location = {Washington, DC}, + url = {https://www.eia.gov/international/data/world}, + urldate = {2026-10-21}, +} From f2b4b6b762c9c9471f14db1fa3e52433043f9b47 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Wed, 21 Oct 2026 21:22:30 -0400 Subject: [PATCH 19/26] Update GHG source citations per review Cite NIES 3EID for Japan GHG data, describe FIGARO emissions as built on the 2025 FIGARO tables, and point the ONS citation at the June 2026 release. Co-Authored-By: Claude Opus 5.5 --- ee/country-tiers.md | 10 ++++++---- reference/methods-by-country.md | 2 +- references.bib | 19 ++++++++++++++++--- 3 files changed, 23 insertions(+), 8 deletions(-) diff --git a/ee/country-tiers.md b/ee/country-tiers.md index 30648473..f815ecf1 100644 --- a/ee/country-tiers.md +++ b/ee/country-tiers.md @@ -44,11 +44,11 @@ Each Tier 1 country's emissions come from its own national data. | Country | Source | Data year | Sectors | |---|---|---|---| | China | Built from several sources (see below) | 2023 | 211, matching the IO table | -| Japan | Environmental data published with the Input-Output Tables for Japan | 2020 | Matching the IO table | +| Japan | NIES 3EID dataset [@nansai3EID2020IOT2025] | 2020 | Matching the IO table | | South Korea | GHG data published with the Bank of Korea input-output tables [@bokUpdatedInputOutput2020] | 2018 | Matching the IO table | -| United Kingdom | ONS atmospheric emissions accounts [@onsAtmosphericEmissionsGreenhouse2024] | 2023 | By industry | +| United Kingdom | ONS atmospheric emissions accounts [@onsAtmosphericEmissionsGreenhouse2026] | 2023 | By industry | -China's data are on a territorial basis, and the UK's on a residence basis. +China's data are on a territorial basis, and the UK's on a residence basis. Japan's 3EID data are built on the same 2020 IO table and reconciled to Japan's national GHG inventory. **China** has no published emissions table matching its IO table, so we build one: @@ -70,7 +70,7 @@ Tier 2 countries take their emissions from the same source as their IO table, so | | FIGARO | ICIO | |---|---|---| | Publisher | Eurostat [@eurostatGreenhouseGasEmission2026] | OECD [@oecdGreenhouseGasFootprints2025; @yamanoCO2EmissionsEmbodied2020] | -| Version | 2026 | 2025 | +| Version | 2025 FIGARO tables | 2025 | | Data year | 2023 | 2020 | | Sectors | 64 industries (NACE Rev. 2) | 50 industries (ISIC Rev. 4) | | Gases | CO₂, CH₄, N₂O, HFCs, PFCs, and SF₆ with NF₃ | Total CO₂e only | @@ -90,6 +90,8 @@ For both groups, FIGARO's industries are first converted to products using FIGAR - Agriculture is split into farm sectors using FAOSTAT CH₄ and N₂O [@faoFAOSTATEmissionsTotals2025] and Eurostat agricultural accounts [@eurostatEconomicAccountsAgriculture2026]. - Mining, non-metallic minerals, and basic metals are split as in the IO table. +The emissions are built on the 2025 FIGARO tables, while the FIGARO IO tables are the 2026 edition. Only each country's direct emissions by industry are used, so the difference matters mainly for non-EU countries, where Eurostat estimates the emissions. + The products are then mapped to the common sectors with {term}`ABSR`. The last gas group, SF₆ with NF₃, is split using the U.S. share of SF₆ in each sector. ### ICIO countries diff --git a/reference/methods-by-country.md b/reference/methods-by-country.md index 05cd0688..69d2c86f 100644 --- a/reference/methods-by-country.md +++ b/reference/methods-by-country.md @@ -96,7 +96,7 @@ The release candidate's 2024, 2025, and 2026 factors are all built from the same | Israel | ISR | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Italy | ITA | 2 | FIGARO, 2026 edition | 2023 | FIGARO, from air emissions accounts | 2023 | | Jamaica | JAM | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | -| Japan | JPN | 1 | Input-Output Tables for Japan | 2020 | Environmental data published with the Japan IO tables | 2020 | +| Japan | JPN | 1 | Input-Output Tables for Japan | 2020 | NIES 3EID dataset | 2020 | | Jordan | JOR | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | | Kazakhstan | KAZ | 2 | ICIO, 2025 edition | 2020 | OECD GHG emissions for ICIO, 2025 edition | 2020 | | Kenya | KEN | 3 | Tier 3 IO template | 2020 | Tier 3 GHG template, scaled to national CO₂ total | 2018 | diff --git a/references.bib b/references.bib index cce06d35..91a8d448 100644 --- a/references.bib +++ b/references.bib @@ -330,6 +330,7 @@ @dataset{eurostatGreenhouseGasEmission2026 doi = {10.2908/ENV_AC_GHGFP}, url = {https://ec.europa.eu/eurostat/databrowser/view/env_ac_ghgfp/default/table}, urldate = {2026-10-21}, + note = {Last updated 22 January 2026; built on the 2025 FIGARO tables; covers 2010--2023}, } @dataset{eurostatAirEmissionsAccounts2026, @@ -412,15 +413,27 @@ @dataset{oecdInterCountryInputOutput2025 note = {Covers 1995--2022}, } -@dataset{onsAtmosphericEmissionsGreenhouse2024, +@dataset{onsAtmosphericEmissionsGreenhouse2026, title = {Atmospheric Emissions: Greenhouse Gases by Industry and Gas}, author = {{Office for National Statistics}}, - date = {2024-10-17}, + date = {2026-06-05}, publisher = {{Office for National Statistics}}, location = {Newport}, url = {https://www.ons.gov.uk/economy/environmentalaccounts/datasets/ukenvironmentalaccountsatmosphericemissionsgreenhousegasemissionsbyeconomicsectorandgasunitedkingdom}, urldate = {2026-10-21}, - note = {UK Environmental Accounts; SIC 2007 groups (around 130 industries)}, + note = {UK Environmental Accounts, June 2026 release; covers 1990--2024; SIC 2007 groups (around 130 industries)}, +} + +@dataset{nansai3EID2020IOT2025, + title = {Embodied Energy and Emission Intensity Data for {{Japan}} Using Input-Output Tables ({{3EID}}) for the 2020 {{Input-Output Tables}}}, + author = {Nansai, Keisuke}, + date = {2025-06-03}, + publisher = {{National Institute for Environmental Studies}}, + location = {Tsukuba, Japan}, + version = {2025-06-03}, + url = {https://3eid.nies.go.jp/database/index.html}, + urldate = {2026-10-21}, + note = {Built on the 2020 Input-Output Tables for Japan (390 sectors); reconciled to Japan's GHG inventory submitted to the UNFCCC in April 2025}, } @dataset{micInputOutputTables2024, From 3ac47a8cda38ecd177349673b1aa85d263987a95 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 09:29:47 -0400 Subject: [PATCH 20/26] addrefs for eeio-intro --- references.bib | 126 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 126 insertions(+) diff --git a/references.bib b/references.bib index 91a8d448..058b7f28 100644 --- a/references.bib +++ b/references.bib @@ -476,3 +476,129 @@ @online{eiaInternationalEnergyStatistics2026 url = {https://www.eia.gov/international/data/world}, urldate = {2026-10-21}, } + +@article{davisImportanceMultiregionalAccounting2025, + title = {The Importance of Multiregional Accounting for Corporate Carbon Emissions}, + author = {Davis, Steven J. and Dumit, Andrew and Li, Mo and Maldonado, Yohanna and Steffen, Michael and Stevenson, Martha and Boldyreva, Tatiana and Suh, Sangwon}, + date = {2025-12-20}, + journaltitle = {Nat Commun}, + issn = {2041-1723}, + doi = {10.1038/s41467-025-67759-5}, + url = {https://www.nature.com/articles/s41467-025-67759-5}, + urldate = {2026-01-07}, + abstract = {Abstract Corporations routinely use environmentally-extended input-output models to estimate and report greenhouse gas emissions upstream in their supply chains. However, the most widely used models assume that supply chains and emissions intensities of industries match those of a single region—usually the U.S. or the U.K. Here, we use a high-resolution multiregional input-output model to demonstrate the scale and pattern of emissions that may be missed by single-region models. We find that the upstream emissions of the companies reporting to CDP are together greater by 2.0 gigatons of CO 2 -equivalent emissions (\textasciitilde 10\%) when estimated by a multiregional model instead of a U.S.-based single-region model, with the largest differences in manufacturing sectors of moderate emissions intensity. Widespread adoption of multiregional models could thus improve the accuracy of corporate emissions inventories and help prioritize primary data collection and emissions reduction efforts, often by shifting focus to energy- and emissions-intensive sectors of industrializing nations.}, + langid = {english}, +} + +@book{hendricksonEnvironmentalLifeCycle2006a, + title = {Environmental {{Life Cycle Assessment}} of {{Goods}} and {{Services}}: {{An Input}}-Output {{Approach}}}, + shorttitle = {Environmental {{Life Cycle Assessment}} of {{Goods}} and {{Services}}}, + author = {Hendrickson, Chris T. and Lave, Dr Lester B. and Matthews, H. Scott}, + date = {2006}, + publisher = {Resources for the Future}, + location = {Washington DC}, + abstract = {Environmental life cycle assessment is often thought of as cradle to grave and therefore as the most complete accounting of the environmental costs and benefits of a product or service. However, as anyone who has done an environmental life cycle assessment knows, existing tools have many problems: data is difficult to assemble and life cycle studies take months of effort. A truly comprehensive analysis is prohibitive, so analysts are often forced to simply ignore many facets of life cycle impacts. But the focus on one aspect of a product or service can result in misleading indications if that aspect is benign while other aspects pollute or are otherwise unsustainable. This book summarizes the EIO-LCA method, explains its use in relation to other life cycle assessment models, and provides sample applications and extensions of the model into novel areas. A final chapter explains the free, easy-to-use software tool available on a companion website. (www.eiolca.net) The software tool provides a wealth of data, summarizing the current U.S. economy in 500 sectors with information on energy and materials use, pollution and greenhouse gas discharges, and other attributes like associated occupational deaths and injuries. The joint project of twelve faculty members and over 20 students working together over the past ten years at the Green Design Institute of Carnegie Mellon University, the EIO-LCA has been applied to a wide range of products and services. It will prove useful for research, industry, and in economics, engineering, or interdisciplinary classes in green design.}, + isbn = {978-1-933115-23-8}, + langid = {english}, + pagetotal = {271}, + keywords = {Nature / Ecology,Nature / Environmental Conservation & Protection,Nature / Natural Resources} +} + +@article{ingwersenConsideringInputoutputDerived2026, + title = {Considering Input-Output Derived Data as Background Life Cycle Inventory Data}, + author = {Ingwersen, Wesley}, + date = {2026-09}, + journaltitle = {Int J Life Cycle Assess}, + volume = {31}, + number = {9}, + pages = {164}, + issn = {0948-3349, 1614-7502}, + doi = {10.1007/s11367-026-02735-9}, + url = {https://link.springer.com/10.1007/s11367-026-02735-9}, + urldate = {2026-08-27}, + langid = {english} +} + +@article{ingwersenUSEEIOV20US2022a, + title = {{{USEEIO}} v2.0, {{The US Environmentally-Extended Input-Output Model}} v2.0}, + author = {Ingwersen, Wesley W. and Li, Mo and Young, Ben and Vendries, Jorge and Birney, Catherine}, + date = {2022-05-03}, + journaltitle = {Sci Data}, + volume = {9}, + number = {1}, + pages = {194}, + publisher = {Nature Publishing Group}, + issn = {2052-4463}, + doi = {10.1038/s41597-022-01293-7}, + url = {https://www.nature.com/articles/s41597-022-01293-7}, + urldate = {2022-08-08}, + abstract = {USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.}, + eid = {1}, + langid = {english}, + keywords = {Environmental impact,Industry}, +} + +@article{leontiefEnvironmentalRepercussionsEconomic1970, + title = {Environmental Repercussions and the Economic Structure: {{An}} Input-Output Approach}, + author = {Leontief, Wassily}, + date = {1970-08}, + journaltitle = {The Review of Economics and Statistics}, + volume = {52}, + number = {3}, + eprint = {1926294}, + eprinttype = {jstor}, + pages = {262--271}, + publisher = {The MIT Press}, + doi = {10.2307/1926294}, + url = {https://www.jstor.org/stable/1926294}, + langid = {english} +} + +@article{minxInputOutputAnalysisCarbon2009, + ids = {minx_inputoutput_2009}, + title = {Input-{{Output Analysis}} and {{Carbon Footprinting}}: {{An Overview}} of {{Applications}}}, + shorttitle = {Input-{{Output Analysis}} and {{Carbon Footprinting}}}, + author = {Minx, J.c. and Wiedmann, T. and Wood, R. and Peters, G.p. and Lenzen, M. and Owen, A. and Scott, K. and Barrett, J. and Hubacek, K. and Baiocchi, G. and Paul, A. and Dawkins, E. and Briggs, J. and Guan, D. and Suh, S. and Ackerman, F.}, + date = {2009-09}, + journaltitle = {Economic Systems Research}, + volume = {21}, + number = {3}, + pages = {187--216}, + issn = {09535314}, + doi = {10.1080/09535310903541298}, + url = {http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,uid&db=buh&AN=49234930&site=bsi-live}, + urldate = {2019-10-29}, + abstract = {This article provides an overview of how generalised multi-regional input-output models can be used for carbon footprint applications. We focus on the relevance and suitability of such evidence to inform decision making. Such an overview is currently missing. Drawing on UK results, we cover carbon footprint applications in seven areas: national emissions inventories and trade, emission drivers, economic sectors, supply chains, organisations, household consumption and lifestyles as well as sub-national emission inventories. The article highlights the multiple uses of generalised multi-regional input-output models for carbon footprinting and concludes by highlighting important avenues for future research.}, + keywords = {Carbon footprint,CONSUMPTION (Economics),Consumption-based accounting,DECISION making,ECOLOGICAL impact,Emission inventory,INPUT-output analysis,Multi-regional input-output model,Multi-regional input–output model,SUPPLY chains,Trade}, +} + +@article{suhDevelopingSectoralEnvironmental2005, + title = {Developing a Sectoral Environmental Database for Input–Output Analysis: The Comprehensive Environmental Data Archive of the {{US}}}, + shorttitle = {Developing a Sectoral Environmental Database for Input–Output Analysis: The Comprehensive Environmental Data Archive of the {{US}}}, + author = {Suh, S}, + date = {2005}, + journaltitle = {Economic Systems Research}, + volume = {17}, + number = {4}, + pages = {449--469} +} + +@article{yangUSEEIONewTransparent2017, + ids = {yang_useeio_2017}, + title = {{{USEEIO}}: A {{New}} and {{Transparent United States Environmentally-Extended Input-Output Model}}}, + shorttitle = {{{USEEIO}}}, + author = {Yang, Yi and Ingwersen, Wesley W. and Hawkins, Troy R. and Srocka, Michael and Meyer, David E.}, + date = {2017-08}, + journaltitle = {J CLEAN PROD}, + volume = {158}, + eprint = {30344374}, + eprinttype = {pubmed}, + pages = {308--318}, + issn = {0959-6526}, + doi = {10.1016/j.jclepro.2017.04.150}, + url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=USEEIO}, + abstract = {National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.}, + langid = {english}, + pmcid = {PMC6192422}, + keywords = {Data quality assessment,Environmentally-extended input-output (EEIO),Life cycle assessment,Product hotspot analysis,Streamlined life cycle assessment,Sustainable materials management}, +} From 09cbecaa8f32229ff32903612bd11d7e6172fb6e Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 09:42:38 -0400 Subject: [PATCH 21/26] Add one-page EEIO intro with overview diagram Write the "What is an EEIO model?" page: origins in IO analysis, the model's matrices, the link to LCA, and multi-regional models, with an overview diagram of IO tables and the GHG extension combining into emission factors. Drop the other intro placeholder pages from the TOC for now. Co-Authored-By: Claude Opus 5.5 --- figures/diagrams/eeio-overview.svg | 54 ++++++++++++++++++++++++++++++ figures/figures.csv | 1 + intro/what-is-eeio.md | 36 +++++++++++++------- myst.yml | 9 +---- 4 files changed, 79 insertions(+), 21 deletions(-) create mode 100644 figures/diagrams/eeio-overview.svg diff --git a/figures/diagrams/eeio-overview.svg b/figures/diagrams/eeio-overview.svg new file mode 100644 index 00000000..d890a244 --- /dev/null +++ b/figures/diagrams/eeio-overview.svg @@ -0,0 +1,54 @@ + + + + + + + + + + + + + + + + + Input-output tables + Dollars flowing between + sectors and to final users + V, U → A, L + + + + + + + + + + CO₂, CH₄, … + Environmental extension + Greenhouse gases emitted + by each sector + E → B, C + + + + + + + + EEIO model + Emissions traced through + every round of suppliers + + + + + + Emission factors + D, N + kg CO₂e per $ of purchases, + by sector and country + diff --git a/figures/figures.csv b/figures/figures.csv index 500ca58c..095dd2ce 100644 --- a/figures/figures.csv +++ b/figures/figures.csv @@ -5,3 +5,4 @@ io-tables-to-a,io/index.md,diagram (SVG),hand-made,,,draft io-mrio-blocks,io/index.md,diagram (SVG),hand-made (after CEDA team slide 19),,,draft country-tiers-map,io/country-tiers.md,map (SVG),data/country_tiers.csv + Natural Earth 1:50m admin-0,figures/scripts/tier_map.py,,draft ghg-pipeline,ee/index.md,diagram (SVG),hand-made,,,draft +eeio-overview,intro/what-is-eeio.md,diagram (SVG),hand-made,,,draft diff --git a/intro/what-is-eeio.md b/intro/what-is-eeio.md index 81b23f39..68191ecc 100644 --- a/intro/what-is-eeio.md +++ b/intro/what-is-eeio.md @@ -3,28 +3,38 @@ title: "What is an EEIO model?" --- :::{tip} Summary -*To be written.* +An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on what each sector emits. Together they produce emission factors: the greenhouse gas emissions across a whole supply chain per dollar spent on a sector's products. ::: -:::{note} Draft placeholder -:class: dropdown -Plan §3.1.1 · target: **RC (Oct 27)** +:::{figure} ../figures/diagrams/eeio-overview.svg +:label: fig-eeio-overview +:alt: Two grey boxes on the left feed arrows into a central box labeled EEIO model. The upper box, input-output tables, shows a small grid of cells and is described as dollars flowing between sectors and to final users, with the letters V, U, A, and L. The lower box, environmental extension, shows a row of shaded cells labeled CO₂, CH₄, and so on, and is described as greenhouse gases emitted by each sector, with the letters E, B, and C. The EEIO model traces emissions through every round of suppliers. An arrow from it leads to a highlighted box, emission factors D and N, in kilograms of CO₂e per dollar of purchases, by sector and country. +An EEIO model combines input-output tables with an environmental extension to produce emission factors. +::: +## Where EEIO comes from -**Planned content** +EEIO grew out of economic input-output analysis when Leontief added the pollution generated by each sector to his model of the economy [@leontiefEnvironmentalRepercussionsEconomic1970], and it has been a basis for carbon footprinting of nations, organizations, and products over the last few decades [@minxInputOutputAnalysisCarbon2009]. -- Why spend-based supply chain emission factors exist and what they answer: the cradle-to-gate emissions per dollar of purchases from sector X in country Y +## The parts of the model -**Key visuals** +Each data component is put into a matrix, named by a letter that is common in input-output analysis and used throughout these docs (see [](../reference/notation.md)). Input-output analysis then combines the matrices with matrix algebra. -- 🖼 Story graphic: a $1 furniture purchase → the furniture maker buys wood, metal, electricity, transport → each of those buys from others, some abroad -::: +- **Input-output tables.** The supply (`V`) and use (`U`) tables record which sectors produce which products, and which products each sector and final user buys. From them come the direct requirements (`A`), the inputs a sector buys per dollar of its output, and the total requirements (`L`, the Leontief inverse), which add up the purchases through every round of suppliers. See [](../io/index.md). +- **Environmental extension.** Emissions of each gas by each sector (`E`), divided by the sector's output, give the direct emission intensities (`B`). Characterization factors (`C`) convert each gas to CO₂-equivalent. See [](../ee/index.md). +- **Emission factors.** Combining the two gives the direct emission factors, `D = C × B`, for what a sector emits itself, and the total emission factors, `N = C × B × L`, for what is emitted across its whole supply chain. + +## EEIO and life cycle assessment + +An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA). In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. + +## Multi-regional models + +A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions of the country that made it. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). -## Learn more +## Further reading -- **From the field:** USEEIO supply chain factors [@ingwersen_supply_2022] -- **Cornerstone papers:** *to be added* -- **Code:** *to be added* +For a book-length introduction to EEIO and its use in LCA, see {cite:t}`hendricksonEnvironmentalLifeCycle2006a`. +++ diff --git a/myst.yml b/myst.yml index 8e9f796e..b86fc29f 100644 --- a/myst.yml +++ b/myst.yml @@ -20,14 +20,7 @@ project: output: exports/cornerstone-eeio-guide.pdf toc: - file: index.md - - title: Introduction to EEIO models - children: - - file: intro/what-is-eeio.md - - file: intro/io-part.md - - file: intro/multi-regional.md - - file: intro/ee-part.md - - file: intro/emission-factors.md - - file: intro/uses-and-limits.md + - file: intro/what-is-eeio.md - title: The IO model children: - file: io/index.md From 45da930e97c908fabf1783d9c9dedafae4a388ba Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 10:18:14 -0400 Subject: [PATCH 22/26] Add Suh ref, fix summary statement --- intro/what-is-eeio.md | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/intro/what-is-eeio.md b/intro/what-is-eeio.md index 68191ecc..3d46a1fa 100644 --- a/intro/what-is-eeio.md +++ b/intro/what-is-eeio.md @@ -3,7 +3,7 @@ title: "What is an EEIO model?" --- :::{tip} Summary -An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on what each sector emits. Together they produce emission factors: the greenhouse gas emissions across a whole supply chain per dollar spent on a sector's products. +An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on environmental attributes of each sector. When the EEIO model included GHG emissions, it can produce emission factors that represent the GHG emissions across a whole supply chain per dollar spent on a sector's products. ::: :::{figure} ../figures/diagrams/eeio-overview.svg @@ -26,11 +26,11 @@ Each data component is put into a matrix, named by a letter that is common in in ## EEIO and life cycle assessment -An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA). In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. +An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA) [@suhDevelopingSectoralEnvironmental2005]. In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. ## Multi-regional models -A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions of the country that made it. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). +A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions as it was produced in the origin country. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). ## Further reading @@ -38,7 +38,3 @@ For a book-length introduction to EEIO and its use in LCA, see {cite:t}`hendrick +++ -:::{div} -:class: page-status -Applies to: RC · Last reviewed: RC -::: From d1677ae23261618df03ce4b982ad5bda3b9d5ae5 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 09:29:47 -0400 Subject: [PATCH 23/26] addrefs for eeio-intro --- references.bib | 126 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 126 insertions(+) diff --git a/references.bib b/references.bib index 91a8d448..058b7f28 100644 --- a/references.bib +++ b/references.bib @@ -476,3 +476,129 @@ @online{eiaInternationalEnergyStatistics2026 url = {https://www.eia.gov/international/data/world}, urldate = {2026-10-21}, } + +@article{davisImportanceMultiregionalAccounting2025, + title = {The Importance of Multiregional Accounting for Corporate Carbon Emissions}, + author = {Davis, Steven J. and Dumit, Andrew and Li, Mo and Maldonado, Yohanna and Steffen, Michael and Stevenson, Martha and Boldyreva, Tatiana and Suh, Sangwon}, + date = {2025-12-20}, + journaltitle = {Nat Commun}, + issn = {2041-1723}, + doi = {10.1038/s41467-025-67759-5}, + url = {https://www.nature.com/articles/s41467-025-67759-5}, + urldate = {2026-01-07}, + abstract = {Abstract Corporations routinely use environmentally-extended input-output models to estimate and report greenhouse gas emissions upstream in their supply chains. However, the most widely used models assume that supply chains and emissions intensities of industries match those of a single region—usually the U.S. or the U.K. Here, we use a high-resolution multiregional input-output model to demonstrate the scale and pattern of emissions that may be missed by single-region models. We find that the upstream emissions of the companies reporting to CDP are together greater by 2.0 gigatons of CO 2 -equivalent emissions (\textasciitilde 10\%) when estimated by a multiregional model instead of a U.S.-based single-region model, with the largest differences in manufacturing sectors of moderate emissions intensity. Widespread adoption of multiregional models could thus improve the accuracy of corporate emissions inventories and help prioritize primary data collection and emissions reduction efforts, often by shifting focus to energy- and emissions-intensive sectors of industrializing nations.}, + langid = {english}, +} + +@book{hendricksonEnvironmentalLifeCycle2006a, + title = {Environmental {{Life Cycle Assessment}} of {{Goods}} and {{Services}}: {{An Input}}-Output {{Approach}}}, + shorttitle = {Environmental {{Life Cycle Assessment}} of {{Goods}} and {{Services}}}, + author = {Hendrickson, Chris T. and Lave, Dr Lester B. and Matthews, H. Scott}, + date = {2006}, + publisher = {Resources for the Future}, + location = {Washington DC}, + abstract = {Environmental life cycle assessment is often thought of as cradle to grave and therefore as the most complete accounting of the environmental costs and benefits of a product or service. However, as anyone who has done an environmental life cycle assessment knows, existing tools have many problems: data is difficult to assemble and life cycle studies take months of effort. A truly comprehensive analysis is prohibitive, so analysts are often forced to simply ignore many facets of life cycle impacts. But the focus on one aspect of a product or service can result in misleading indications if that aspect is benign while other aspects pollute or are otherwise unsustainable. This book summarizes the EIO-LCA method, explains its use in relation to other life cycle assessment models, and provides sample applications and extensions of the model into novel areas. A final chapter explains the free, easy-to-use software tool available on a companion website. (www.eiolca.net) The software tool provides a wealth of data, summarizing the current U.S. economy in 500 sectors with information on energy and materials use, pollution and greenhouse gas discharges, and other attributes like associated occupational deaths and injuries. The joint project of twelve faculty members and over 20 students working together over the past ten years at the Green Design Institute of Carnegie Mellon University, the EIO-LCA has been applied to a wide range of products and services. It will prove useful for research, industry, and in economics, engineering, or interdisciplinary classes in green design.}, + isbn = {978-1-933115-23-8}, + langid = {english}, + pagetotal = {271}, + keywords = {Nature / Ecology,Nature / Environmental Conservation & Protection,Nature / Natural Resources} +} + +@article{ingwersenConsideringInputoutputDerived2026, + title = {Considering Input-Output Derived Data as Background Life Cycle Inventory Data}, + author = {Ingwersen, Wesley}, + date = {2026-09}, + journaltitle = {Int J Life Cycle Assess}, + volume = {31}, + number = {9}, + pages = {164}, + issn = {0948-3349, 1614-7502}, + doi = {10.1007/s11367-026-02735-9}, + url = {https://link.springer.com/10.1007/s11367-026-02735-9}, + urldate = {2026-08-27}, + langid = {english} +} + +@article{ingwersenUSEEIOV20US2022a, + title = {{{USEEIO}} v2.0, {{The US Environmentally-Extended Input-Output Model}} v2.0}, + author = {Ingwersen, Wesley W. and Li, Mo and Young, Ben and Vendries, Jorge and Birney, Catherine}, + date = {2022-05-03}, + journaltitle = {Sci Data}, + volume = {9}, + number = {1}, + pages = {194}, + publisher = {Nature Publishing Group}, + issn = {2052-4463}, + doi = {10.1038/s41597-022-01293-7}, + url = {https://www.nature.com/articles/s41597-022-01293-7}, + urldate = {2022-08-08}, + abstract = {USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.}, + eid = {1}, + langid = {english}, + keywords = {Environmental impact,Industry}, +} + +@article{leontiefEnvironmentalRepercussionsEconomic1970, + title = {Environmental Repercussions and the Economic Structure: {{An}} Input-Output Approach}, + author = {Leontief, Wassily}, + date = {1970-08}, + journaltitle = {The Review of Economics and Statistics}, + volume = {52}, + number = {3}, + eprint = {1926294}, + eprinttype = {jstor}, + pages = {262--271}, + publisher = {The MIT Press}, + doi = {10.2307/1926294}, + url = {https://www.jstor.org/stable/1926294}, + langid = {english} +} + +@article{minxInputOutputAnalysisCarbon2009, + ids = {minx_inputoutput_2009}, + title = {Input-{{Output Analysis}} and {{Carbon Footprinting}}: {{An Overview}} of {{Applications}}}, + shorttitle = {Input-{{Output Analysis}} and {{Carbon Footprinting}}}, + author = {Minx, J.c. and Wiedmann, T. and Wood, R. and Peters, G.p. and Lenzen, M. and Owen, A. and Scott, K. and Barrett, J. and Hubacek, K. and Baiocchi, G. and Paul, A. and Dawkins, E. and Briggs, J. and Guan, D. and Suh, S. and Ackerman, F.}, + date = {2009-09}, + journaltitle = {Economic Systems Research}, + volume = {21}, + number = {3}, + pages = {187--216}, + issn = {09535314}, + doi = {10.1080/09535310903541298}, + url = {http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,uid&db=buh&AN=49234930&site=bsi-live}, + urldate = {2019-10-29}, + abstract = {This article provides an overview of how generalised multi-regional input-output models can be used for carbon footprint applications. We focus on the relevance and suitability of such evidence to inform decision making. Such an overview is currently missing. Drawing on UK results, we cover carbon footprint applications in seven areas: national emissions inventories and trade, emission drivers, economic sectors, supply chains, organisations, household consumption and lifestyles as well as sub-national emission inventories. The article highlights the multiple uses of generalised multi-regional input-output models for carbon footprinting and concludes by highlighting important avenues for future research.}, + keywords = {Carbon footprint,CONSUMPTION (Economics),Consumption-based accounting,DECISION making,ECOLOGICAL impact,Emission inventory,INPUT-output analysis,Multi-regional input-output model,Multi-regional input–output model,SUPPLY chains,Trade}, +} + +@article{suhDevelopingSectoralEnvironmental2005, + title = {Developing a Sectoral Environmental Database for Input–Output Analysis: The Comprehensive Environmental Data Archive of the {{US}}}, + shorttitle = {Developing a Sectoral Environmental Database for Input–Output Analysis: The Comprehensive Environmental Data Archive of the {{US}}}, + author = {Suh, S}, + date = {2005}, + journaltitle = {Economic Systems Research}, + volume = {17}, + number = {4}, + pages = {449--469} +} + +@article{yangUSEEIONewTransparent2017, + ids = {yang_useeio_2017}, + title = {{{USEEIO}}: A {{New}} and {{Transparent United States Environmentally-Extended Input-Output Model}}}, + shorttitle = {{{USEEIO}}}, + author = {Yang, Yi and Ingwersen, Wesley W. and Hawkins, Troy R. and Srocka, Michael and Meyer, David E.}, + date = {2017-08}, + journaltitle = {J CLEAN PROD}, + volume = {158}, + eprint = {30344374}, + eprinttype = {pubmed}, + pages = {308--318}, + issn = {0959-6526}, + doi = {10.1016/j.jclepro.2017.04.150}, + url = {https://www.ncbi.nlm.nih.gov/pubmed/?term=USEEIO}, + abstract = {National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.}, + langid = {english}, + pmcid = {PMC6192422}, + keywords = {Data quality assessment,Environmentally-extended input-output (EEIO),Life cycle assessment,Product hotspot analysis,Streamlined life cycle assessment,Sustainable materials management}, +} From 5c95d8c7d0c68bb89744343c6cdc7b9b08b90063 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 09:42:38 -0400 Subject: [PATCH 24/26] Add one-page EEIO intro with overview diagram Write the "What is an EEIO model?" page: origins in IO analysis, the model's matrices, the link to LCA, and multi-regional models, with an overview diagram of IO tables and the GHG extension combining into emission factors. Drop the other intro placeholder pages from the TOC for now. Co-Authored-By: Claude Opus 5.5 --- figures/diagrams/eeio-overview.svg | 54 ++++++++++++++++++++++++++++++ figures/figures.csv | 1 + intro/what-is-eeio.md | 36 +++++++++++++------- myst.yml | 9 +---- 4 files changed, 79 insertions(+), 21 deletions(-) create mode 100644 figures/diagrams/eeio-overview.svg diff --git a/figures/diagrams/eeio-overview.svg b/figures/diagrams/eeio-overview.svg new file mode 100644 index 00000000..d890a244 --- /dev/null +++ b/figures/diagrams/eeio-overview.svg @@ -0,0 +1,54 @@ + + + + + + + + + + + + + + + + + Input-output tables + Dollars flowing between + sectors and to final users + V, U → A, L + + + + + + + + + + CO₂, CH₄, … + Environmental extension + Greenhouse gases emitted + by each sector + E → B, C + + + + + + + + EEIO model + Emissions traced through + every round of suppliers + + + + + + Emission factors + D, N + kg CO₂e per $ of purchases, + by sector and country + diff --git a/figures/figures.csv b/figures/figures.csv index 500ca58c..095dd2ce 100644 --- a/figures/figures.csv +++ b/figures/figures.csv @@ -5,3 +5,4 @@ io-tables-to-a,io/index.md,diagram (SVG),hand-made,,,draft io-mrio-blocks,io/index.md,diagram (SVG),hand-made (after CEDA team slide 19),,,draft country-tiers-map,io/country-tiers.md,map (SVG),data/country_tiers.csv + Natural Earth 1:50m admin-0,figures/scripts/tier_map.py,,draft ghg-pipeline,ee/index.md,diagram (SVG),hand-made,,,draft +eeio-overview,intro/what-is-eeio.md,diagram (SVG),hand-made,,,draft diff --git a/intro/what-is-eeio.md b/intro/what-is-eeio.md index 81b23f39..68191ecc 100644 --- a/intro/what-is-eeio.md +++ b/intro/what-is-eeio.md @@ -3,28 +3,38 @@ title: "What is an EEIO model?" --- :::{tip} Summary -*To be written.* +An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on what each sector emits. Together they produce emission factors: the greenhouse gas emissions across a whole supply chain per dollar spent on a sector's products. ::: -:::{note} Draft placeholder -:class: dropdown -Plan §3.1.1 · target: **RC (Oct 27)** +:::{figure} ../figures/diagrams/eeio-overview.svg +:label: fig-eeio-overview +:alt: Two grey boxes on the left feed arrows into a central box labeled EEIO model. The upper box, input-output tables, shows a small grid of cells and is described as dollars flowing between sectors and to final users, with the letters V, U, A, and L. The lower box, environmental extension, shows a row of shaded cells labeled CO₂, CH₄, and so on, and is described as greenhouse gases emitted by each sector, with the letters E, B, and C. The EEIO model traces emissions through every round of suppliers. An arrow from it leads to a highlighted box, emission factors D and N, in kilograms of CO₂e per dollar of purchases, by sector and country. +An EEIO model combines input-output tables with an environmental extension to produce emission factors. +::: +## Where EEIO comes from -**Planned content** +EEIO grew out of economic input-output analysis when Leontief added the pollution generated by each sector to his model of the economy [@leontiefEnvironmentalRepercussionsEconomic1970], and it has been a basis for carbon footprinting of nations, organizations, and products over the last few decades [@minxInputOutputAnalysisCarbon2009]. -- Why spend-based supply chain emission factors exist and what they answer: the cradle-to-gate emissions per dollar of purchases from sector X in country Y +## The parts of the model -**Key visuals** +Each data component is put into a matrix, named by a letter that is common in input-output analysis and used throughout these docs (see [](../reference/notation.md)). Input-output analysis then combines the matrices with matrix algebra. -- 🖼 Story graphic: a $1 furniture purchase → the furniture maker buys wood, metal, electricity, transport → each of those buys from others, some abroad -::: +- **Input-output tables.** The supply (`V`) and use (`U`) tables record which sectors produce which products, and which products each sector and final user buys. From them come the direct requirements (`A`), the inputs a sector buys per dollar of its output, and the total requirements (`L`, the Leontief inverse), which add up the purchases through every round of suppliers. See [](../io/index.md). +- **Environmental extension.** Emissions of each gas by each sector (`E`), divided by the sector's output, give the direct emission intensities (`B`). Characterization factors (`C`) convert each gas to CO₂-equivalent. See [](../ee/index.md). +- **Emission factors.** Combining the two gives the direct emission factors, `D = C × B`, for what a sector emits itself, and the total emission factors, `N = C × B × L`, for what is emitted across its whole supply chain. + +## EEIO and life cycle assessment + +An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA). In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. + +## Multi-regional models + +A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions of the country that made it. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). -## Learn more +## Further reading -- **From the field:** USEEIO supply chain factors [@ingwersen_supply_2022] -- **Cornerstone papers:** *to be added* -- **Code:** *to be added* +For a book-length introduction to EEIO and its use in LCA, see {cite:t}`hendricksonEnvironmentalLifeCycle2006a`. +++ diff --git a/myst.yml b/myst.yml index 8e9f796e..b86fc29f 100644 --- a/myst.yml +++ b/myst.yml @@ -20,14 +20,7 @@ project: output: exports/cornerstone-eeio-guide.pdf toc: - file: index.md - - title: Introduction to EEIO models - children: - - file: intro/what-is-eeio.md - - file: intro/io-part.md - - file: intro/multi-regional.md - - file: intro/ee-part.md - - file: intro/emission-factors.md - - file: intro/uses-and-limits.md + - file: intro/what-is-eeio.md - title: The IO model children: - file: io/index.md From f62c3141e57f491d0e88d094996b15189f4e4771 Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Thu, 22 Oct 2026 10:18:14 -0400 Subject: [PATCH 25/26] Add Suh ref, fix summary statement --- intro/what-is-eeio.md | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/intro/what-is-eeio.md b/intro/what-is-eeio.md index 68191ecc..3d46a1fa 100644 --- a/intro/what-is-eeio.md +++ b/intro/what-is-eeio.md @@ -3,7 +3,7 @@ title: "What is an EEIO model?" --- :::{tip} Summary -An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on what each sector emits. Together they produce emission factors: the greenhouse gas emissions across a whole supply chain per dollar spent on a sector's products. +An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on environmental attributes of each sector. When the EEIO model included GHG emissions, it can produce emission factors that represent the GHG emissions across a whole supply chain per dollar spent on a sector's products. ::: :::{figure} ../figures/diagrams/eeio-overview.svg @@ -26,11 +26,11 @@ Each data component is put into a matrix, named by a letter that is common in in ## EEIO and life cycle assessment -An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA). In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. +An EEIO model has the same matrix structure as the models used for life cycle assessment (LCA) [@suhDevelopingSectoralEnvironmental2005]. In both, a matrix of the inputs each activity needs is inverted to trace every upstream supplier, and a matrix of emissions per unit of each activity is multiplied through it. The difference is that EEIO describes sectors in dollars, where LCA usually describes individual processes in physical units. Because of this shared structure, EEIO data can serve as background data in LCA, as discussed in {cite:t}`ingwersenConsideringInputoutputDerived2026`. ## Multi-regional models -A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions of the country that made it. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). +A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions as it was produced in the origin country. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). ## Further reading @@ -38,7 +38,3 @@ For a book-length introduction to EEIO and its use in LCA, see {cite:t}`hendrick +++ -:::{div} -:class: page-status -Applies to: RC · Last reviewed: RC -::: From 20f3e70ff0199e032566489690bfa1069c5aea7f Mon Sep 17 00:00:00 2001 From: WesIngwersen Date: Fri, 23 Oct 2026 16:53:29 -0400 Subject: [PATCH 26/26] edits from jvendries --- intro/what-is-eeio.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/intro/what-is-eeio.md b/intro/what-is-eeio.md index 3d46a1fa..4f6eaee2 100644 --- a/intro/what-is-eeio.md +++ b/intro/what-is-eeio.md @@ -3,7 +3,7 @@ title: "What is an EEIO model?" --- :::{tip} Summary -An environmentally-extended input-output ({term}`EEIO`) model joins tables of how an economy's sectors buy from one another with data on environmental attributes of each sector. When the EEIO model included GHG emissions, it can produce emission factors that represent the GHG emissions across a whole supply chain per dollar spent on a sector's products. +An environmentally-extended input-output ({term}EEIO) model combines data of how outputs produced by sectors in an economy serve as inputs for other sectors along with environmental attributes of each sector. When the economic data is extended with environmental data this way, such as with GHG emissions, the resulting model can produce emission factors that represent the GHG emissions across a whole supply chain per dollar spent on a sector's products. ::: :::{figure} ../figures/diagrams/eeio-overview.svg @@ -14,7 +14,7 @@ An EEIO model combines input-output tables with an environmental extension to pr ## Where EEIO comes from -EEIO grew out of economic input-output analysis when Leontief added the pollution generated by each sector to his model of the economy [@leontiefEnvironmentalRepercussionsEconomic1970], and it has been a basis for carbon footprinting of nations, organizations, and products over the last few decades [@minxInputOutputAnalysisCarbon2009]. +EEIO grew out of economic input-output analysis when economist Wassily Leontief added the pollution generated by each sector to his model of the economy [@leontiefEnvironmentalRepercussionsEconomic1970], and it has been a basis for carbon footprinting of nations, organizations, and products over the last few decades [@minxInputOutputAnalysisCarbon2009]. ## The parts of the model @@ -30,7 +30,7 @@ An EEIO model has the same matrix structure as the models used for life cycle as ## Multi-regional models -A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions as it was produced in the origin country. For the companies reporting to CDP, using an MRIO model instead of a U.S. single-region model raises their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). +A single-country model assumes imported products are made the same way, and with the same emissions, as products made at home. A multi-regional input-output ({term}`MRIO`) model instead links countries' input-output tables through international trade, so each import carries the supply chain and emissions as it was produced in the origin country. For the companies reporting to the Carbon Disclosure Project (CDP), in one study using an MRIO model instead of a U.S. single-region model raised their estimated upstream emissions by about 10% [@davisImportanceMultiregionalAccounting2025]. The Cornerstone model is an MRIO model; see [](../io/index.md#from-single-country-tables-to-the-multi-region-model). ## Further reading