EU MRV emissions · IMO 9604744
LADY MARY
What this ship reported burning and emitting on voyages touching the European Economic Area, one line per reporting year, as verified under the EU MRV regulation and published by EMSA. Bulk carrier. The figures are the source figures. We add nothing to them.
| Year | CO2 | Fuel | Time at sea | Verifier |
|---|---|---|---|---|
| 2025 | 1,498 t | 470 t | 1,226 h | ICS Verification Services Single Member P.C. |
| 2024 | 2,973 t | 954 t | 1,649 h | ICS Verification Services Single Member P.C. |
| 2023 | 3,035 t | 968 t | 1,448 h | NORMEC VERIFAVIA SAS |
| 2019 | 7,008 t | 2,232 t | 3,329 h | Nippon Kaiji Kyokai |
| 2018 | 6,055 t | 1,934 t | 2,815 h | Nippon Kaiji Kyokai |
Reading these numbers
- 2025, filed by Alma Shipmanagement & Trading
- Technical efficiency as filed: EEXI (5.8 gCO₂/t·nm). Every tonne of fuel in this filing carries 3.19 tonnes of CO2. Source: EMSA THETIS MRV, 2025 file version 84. Other ships this company filed for.
- 2024, filed by Alma Shipmanagement & Trading
- Technical efficiency as filed: EEXI (5.8 gCO₂/t·nm). Every tonne of fuel in this filing carries 3.12 tonnes of CO2. Source: EMSA THETIS MRV, 2024 file version 254. Other ships this company filed for.
- 2023
- Technical efficiency as filed: EEXI (5.8 gCO₂/t·nm). Every tonne of fuel in this filing carries 3.14 tonnes of CO2. Source: EMSA THETIS MRV, 2023 file version 92.
- 2019
- Technical efficiency as filed: EIV (7.49 gCO₂/t·nm). Every tonne of fuel in this filing carries 3.14 tonnes of CO2. Source: EMSA THETIS MRV, 2019 file version 228.
- 2018
- Technical efficiency as filed: EIV (7.49 gCO₂/t·nm). Every tonne of fuel in this filing carries 3.13 tonnes of CO2. Source: EMSA THETIS MRV, 2018 file version 275.
Source: the EU MRV publication of information, European Maritime Safety Agency. The exact file these rows came from. Read on 2026-11-07.
Scope is EU MRV scope: voyages to, from and between ports in the European Economic Area, plus time at berth there. It is not the ship’s whole year. How the whole dataset is put together.