Maritime transport CO2 emissions in Mauritania
Mauritania: Maritime transport CO2 emissions was 116,150 Tonnes in 2025. ▲ Rising
Maritime transport CO2 emissions in Mauritania, 2019–2025
Source: Organisation for Economic Co-operation and Development. Measured in Tonnes.
Analysis
In 2025, maritime transport co2 emissions in Mauritania stood at 116,150 Tonnes.
Compared with earlier readings it is up 3.0% on the previous year and up 101.3% over ten years.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 57,694 Tonnes | 57,694 Tonnes | 57,694 Tonnes | 1 |
| 2020s | 132,302 Tonnes | 112,798 Tonnes | 157,793 Tonnes | 6 |
Countries ranked near Mauritania
- 1 OECD 54.81 million Tonnes compare
- 2 China (People’s Republic of) 24.22 million Tonnes compare
- 3 United States 9.33 million Tonnes compare
- 4 Brazil 6.01 million Tonnes compare
- 5 Spain 4.45 million Tonnes compare
More climate change data for Mauritania
- Africa's Development Dynamics (AfDD) Table 25 - GHG Emissions by 0 Kilotonnes of CO2-equivalent (2020)
- Africa's Development Dynamics (AfDD) Table 25 - GHG Emissions by 1,004 Kilotonnes of CO2-equivalent (2020)
Frequently asked questions
- What is maritime transport co2 emissions in Mauritania?
- Maritime transport co2 emissions in Mauritania was 116,150 Tonnes in 2025, according to Organisation for Economic Co-operation and Development.
- What is the highest maritime transport co2 emissions recorded in Mauritania?
- The highest recorded value was 157,793 Tonnes in 2022.
- What is the lowest maritime transport co2 emissions recorded in Mauritania?
- The lowest recorded value was 57,694 Tonnes in 2019.
- How does Mauritania rank for maritime transport co2 emissions?
- Mauritania ranks 2nd out of 10 groups with data for 2025.
- Is maritime transport co2 emissions rising or falling in Mauritania?
- Over the last ten years it is up 101.3%. The long-run trend across the full record is rising.
- Where does this Mauritania data come from?
- The figures come from Organisation for Economic Co-operation and Development, published as part of Maritime transport CO2 emissions (experimental). Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 7 observations, free to reuse under OECD Terms and Conditions (attribution required).
About this data
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