Grid emission factors across ASEAN: an orientation

The short version

This guide surveys the region. For the full explanation of one country's number, see the Singapore grid emission factor guide.

A grid emission factor answers one question — how much CO₂-equivalent was emitted, on average, for each kilowatt-hour that came off a national grid — and the honest answer is that this number is different in every ASEAN country, because every country burns a different mix of fuel to make its electricity. Singapore's fuel mix and its low, well-documented factor make it the easiest country in the region to explain properly; this guide uses it as the anchor and works outward to the rest of Southeast Asia, where official figures are patchier and harder to cite with confidence.

Why the numbers differ: fuel mix, not geography

A kilowatt-hour is a kilowatt-hour everywhere — the physics is identical. What differs is what got burned to generate it. Coal produces roughly twice the CO₂ per kWh of natural gas; hydro, solar, and wind are close to zero at the point of generation. A national grid's factor is essentially a weighted average of whatever mix of plants fed it that year, so:

• A grid running mostly coal sits near the top of the range.
• A grid running mostly gas sits in the middle.
• A grid with heavy hydro or nuclear sits near the bottom.

That single mechanism explains almost the entire spread you will see across ASEAN, without needing any country-specific story beyond "what does this grid burn."

Singapore: the anchor case

Singapore's factor is the clearest one to cite in the region because it is published directly by a national regulator on an open licence, with a transparent methodology:

| Data year | Factor (kgCO₂e/kWh) | Published in | Licence | | --- | --- | --- | --- | | 2023 | 0.4085 | SES 2024 | Singapore Open Data Licence | | 2024 | 0.4020 | SES 2025 | Singapore Open Data Licence |

Both come from the Energy Market Authority's Singapore Energy Statistics, calculated as an Operating Margin average across the whole grid. Around 95% of Singapore's generation is natural gas, which is why its factor sits below several coal-heavier neighbours despite Singapore having no hydro, and no significant renewables share, of its own. The full mechanics — why the number moves the way it does, which data year to use for which reporting period, location-based vs market-based — are covered in the dedicated Singapore guide; it is worth reading in full if Singapore is your primary jurisdiction, since this guide only summarises it here as a reference point for the rest of the region.

The rest of ASEAN: what's seeded here, and what isn't

Our factor registry — the same one behind every calculator on this site — carries approximate electricity intensities for five other ASEAN countries, sourced from Ember's Yearly Electricity Data (CC-BY licence, 2024 dataset):

| Country | Approximate factor (kgCO₂e/kWh) | Source | | --- | --- | --- | | Malaysia | ~0.61 | Ember, CC-BY | | Indonesia | ~0.68 | Ember, CC-BY | | Thailand | ~0.55 | Ember, CC-BY | | Vietnam | ~0.47 | Ember, CC-BY | | Philippines | ~0.62 | Ember, CC-BY |

Two things are important about this table. First, these are generation-intensity approximations, not official national grid-average factors — Ember calculates them from national generation and emissions data (CO₂ per kWh generated), which can drift from what a country's own regulator would publish once imports, transmission losses, and reporting-boundary choices are accounted for. Second, unlike Singapore, none of these five countries currently has an easily citable, regulator-published figure seeded in our registry the way EMA's number is for Singapore. Both facts point to the same practice: fine for screening and comparison, worth checking against an official source before it goes into a customer-facing or regulator-facing disclosure.

Finding and citing an official factor for MY, ID, TH, VN or PH

When an Ember approximation is not precise enough — a formal disclosure, a customer questionnaire that asks for a national factor, or a report where the country in question is your primary reporting jurisdiction — go to the source that actually governs that grid:

• Malaysia — the Energy Commission (Suruhanjaya Tenaga) is the regulator that periodically publishes grid-factor figures for the Peninsular Malaysia grid; Sabah and Sarawak run separate grids with their own mixes, so check which one applies to your site.
• Indonesia — PLN (the state electricity utility) and the Ministry of Energy and Mineral Resources publish generation and emissions data that feed national grid-factor figures; Indonesia's grid is not fully unified, so regional variation can matter for multi-site operations.
• Thailand — the Energy Policy and Planning Office and EGAT (the Electricity Generating Authority of Thailand) are the bodies that publish generation-mix and emissions data behind Thailand's factor.
• Vietnam — Vietnam Electricity (EVN) and the Ministry of Industry and Trade publish the data underlying Vietnam's grid factor, alongside periodic reporting tied to Vietnam's own emissions-reduction commitments.
• Philippines — the Department of Energy and the National Grid Corporation of the Philippines are the relevant sources; the Philippine grid is split across Luzon, Visayas, and Mindanao, which do not all run the same mix.

Where none of these publishes a figure you can cite with confidence for your reporting year, the recognised fallback across development-finance and carbon-project methodologies is the UNFCCC's list of harmonised IFI default grid factors — a set of country-level figures maintained jointly by international financial institutions specifically so project developers have one citable number when no better national figure is publicly available. Note that an IFI harmonised factor is not automatically the same as a country's own official figure: check whether the country publishes its own number first, and treat the IFI list as the fallback, not the first stop.

Whichever source you end up citing, state it the same way every time: value, publishing body, data year, licence — exactly the discipline covered in the evidence and audit-trail guide.

The region-cascade concept

Every calculator on tc02e.com resolves an electricity factor through the same lookup order, and it is worth understanding because it explains why a result always appears even for a country with a thin data trail:

1. Try the country-specific factor first — an exact match for the region you selected, for the activity type in question.
2. Fall back to GLOBAL if no country-specific factor is seeded for that activity — currently an Ember-derived world average of approximately 0.48 kgCO₂e/kWh.

This cascade means a calculation never silently fails, but it also means two different kinds of number can come out the other end looking similar: a genuine national factor (Singapore's EMA figure, for instance) and a GLOBAL fallback standing in for a country with no seeded row at all. The source and licence shown next to every result is how you tell which one you got — always check it before treating a number as country-specific.

A worked example: same consumption, three countries

An organization with sites using an identical 20,000 kWh in a month, compared across three ASEAN grids using the figures above:

Singapore: 20,000 × 0.4020 = 8,040 kgCO₂e

Malaysia: 20,000 × ~0.61 ≈ 12,200 kgCO₂e

Indonesia: 20,000 × ~0.68 ≈ 13,600 kgCO₂e

Identical consumption, and the Indonesian site's estimated emissions run nearly 70% higher than the Singapore site's — entirely a function of what each grid burns, not anything the site itself did differently. This is why per-country factors are not optional for a regional operation: summing consumption across sites and applying one factor to the total (rather than each site's own country factor) will misstate the total, sometimes substantially, in either direction depending on which country's factor got applied where.

Common mistakes worth naming

• Stale factors. A grid factor is a snapshot of one data year's fuel mix. Using a factor from several years ago without checking for a refresh — especially in a market adding renewables or shutting old coal plants — understates or overstates the true figure depending on the direction of change.
• Mixing data years across a comparison. Comparing this year's Singapore figure against last year's Malaysia figure produces a misleading gap that has nothing to do with the actual grids — always match vintages when comparing countries.
• Confusing IFI harmonised factors with national official factors. They can differ meaningfully in methodology and boundary; state which one you used.
• Applying one country's factor to another country's bill. The spreadsheet-copy mistake described above — easy to make, easy to check for by naming the country directly next to the factor cell.
• Treating an approximation as a citation-grade figure. An Ember generation-intensity number is a good screening estimate; label it as such rather than presenting it with the same confidence as a regulator-published factor.

What this guide deliberately doesn't cover

• Sub-national grid variation. Indonesia and the Philippines in particular run grids that are not fully unified nationally; this guide gives one national approximation per country, which will not capture island-to-island or region-to-region differences.
• Market-based Scope 2 (RECs, PPAs). Everything above is location-based. If you hold renewable energy certificates or a power purchase agreement in any of these markets, your market-based figure needs its own contractual evidence and calculation, separate from the grid average.
• Non-electricity factors. Fuel combustion, freight, and other Scope 1 and Scope 3 activities use a different (mostly global, DEFRA-sourced) factor set — see Scope 1, 2 and 3, explained in 10 minutes for how those map to documents.

Self-check: which regions have seeded factors here, and which don't

To be precise about what this guide can and cannot back with a number from our own registry: Singapore (official, EMA), Malaysia, Indonesia, Thailand, Vietnam, and the Philippines all have a seeded electricity factor in the factor registry — Singapore's is an official regulator figure, the other five are Ember generation-intensity approximations, all stated above with their values. No other ASEAN country (Brunei, Cambodia, Laos, Myanmar, Timor-Leste) has a seeded factor in this registry, which is why this guide does not quote a number for any of them — for those markets, go directly to the national utility or ministry, or the UNFCCC's harmonised IFI list, and cite whatever you find with its own year and source.

Where this fits in your reporting

Whichever ASEAN country your electricity bill comes from, the arithmetic is the same one line: kWh × grid factor. The business electricity calculator applies the right country factor automatically across all six ASEAN markets covered here, prints the source and licence on every result, and sits underneath the same organization footprint calculator if you are consolidating electricity alongside fuel, travel, and waste. For Singapore-specific reporting deadlines that pull regional suppliers into the same disclosure chain, see the SGX climate reporting deadlines guide.

Sources

• EMA — Singapore Energy Statistics (Singapore Open Data Licence): ema.gov.sg
• Ember — Yearly Electricity Data (CC-BY): ember-energy.org
• UNFCCC — harmonised IFI default grid emission factors: unfccc.int
• Malaysia Energy Commission (Suruhanjaya Tenaga): st.gov.my
• GHG Protocol — Scope 2 Guidance (location- vs market-based methods): ghgprotocol.org