Japan vs Saudi Arabia: Maritime transport CO2 emissions (experimental)

Japan
3.08 million Tonnes
in 2025
Saudi Arabia
2.05 million Tonnes
in 2025
Japan rank
11th
Saudi Arabia rank
14th

Maritime transport CO2 emissions (experimental) over time

  • Japan
  • Saudi Arabia
2.0M3.0M4.0M5.0M201920222025

How they compare

Japan currently reports 3.08 million Tonnes against 2.05 million Tonnes in Saudi Arabia, a difference of 1.03 million Tonnes.

That makes Japan's figure about 1.5 times Saudi Arabia's.

Across all 7 years both countries report, Japan has been ahead every year.

Japan ranks 11th and Saudi Arabia ranks 14th of 138 countries.

Japan has averaged higher in every one of the 2 decades both report.

Head to head by decade

Decade Japan Saudi Arabia Difference Ahead
2010s 4.68 million Tonnes 1.75 million Tonnes 2.93 million Tonnes Japan
2020s 3.78 million Tonnes 1.90 million Tonnes 1.89 million Tonnes Japan

Averages of every year both report within each decade.

Frequently asked questions

Which has higher maritime transport co2 emissions, Japan or Saudi Arabia?
Japan, at 3.08 million Tonnes against 2.05 million Tonnes in Saudi Arabia as of 2025.
What is the difference in maritime transport co2 emissions between Japan and Saudi Arabia?
1.03 million Tonnes, with Japan ahead.
How many years of comparable data are there for Japan and Saudi Arabia?
7 years are reported by both, from 2019 to 2025.
How do Japan and Saudi Arabia rank globally for maritime transport co2 emissions?
Japan ranks 11th and Saudi Arabia ranks 14th of 138 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Maritime transport CO2 emissions (experimental). Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Japan vs Saudi Arabia: Maritime transport CO2 emissions. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 07 October 2026, from https://climate.statizoid.com/compare/maritime-transport-co2-emissions-experimental/japan/saudi-arabia/

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About this data

Indicator
Maritime transport CO2 emissions (experimental)
Unit
Tonnes
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
160 places, 1,105 data points, 2019–2025
Last refreshed

This experimental dataset includes annual, quarterly, and monthly information on carbon dioxide (CO2) emissions from maritime transport based on ship-tracking information collected via Automatic Identification System (AIS) transponders, covering all large vessels (above 300 gross tonnage) around the world, accessed via the United Nations Global Platform, from 2019 onwards. The CO2 emissions are estimated by the OECD, based on a consistent methodology across countries and include emissions from both domestic and international voyages. The CO2 emissions are classified using the ship-type classification used by the International Maritime Organisation (IMO) distinguishing between 19 vessel categories such as bulk carriers, tankers, and cruise ships. The database provides a measure of CO2 emissions on a territory basis for domestic navigation, which is used for reporting in the UN Framework Convention on Climate Change (UNFCCC) inventories; and also on a residence basis, which is used to estimate the emissions of maritime transport (H50 in the International Standard Industrial Classification of All Economic Activities, or ISIC) in the SEEA Air Emission Accounts (AEAs). Seven components of these CO2 emissions measures can be selected from the ‘Vessel emissions ’ filter. In the tables, these are also shown with the letters A, B, C, D, E, F and G. The aggregate measures of CO2 emissions are calculated as: Domestic navigation = A + C International navigation (memo item) = D + G Air emissions accounts: maritime transport (ISIC H50) = A + B + D + E + F For residence based measures, the allocation of emissions to countries is based on the residence of the companies that operate the ships. More information can be found on the dataset webpage