Bottom-up estimation of CO2 emissions from container ships: a proof of concept using real operational data on the Brazil–Asia route
Abstract
Granular quantification of greenhouse gas (GHG) emissions from maritime transport matters both for the assessment of decarbonisation strategies and for the attribution of the carbon footprint to logistics flows. This study proposes a bottom up approach that integrates operational reconstruction of the voyage, physical–energy modelling, Tank-to-Wake (TTW) and Well-to-Wake (WTW) assessment, and allocation of emissions to the flows carried. The approach was applied to the M/V EVER FAME along a sequential rotation between the east coast of South America and Asia, comprising 11 port calls, 10 legs and 13,913.3 nautical miles. Under the assumptions adopted, the model estimated a fuel consumption of 3,407.9 t and emissions of 10,612 tCO2 TTW and 12,741 tCO2eq WTW, corresponding to intensities of 768 kgCO2/TEU, counting laden and empty containers together, and 37.0 gCO2/TEU·km. Among the decarbonisation scenarios, the largest WTW reductions were obtained with e-ammonia (91.9%) and e-methanol (72.0%), whereas LNG performance varied with engine technology and methane slip. The approach further allocated emissions in full across 3,251 shipment records, preserving the voyage balance with a conservation deviation of 0.0000%. The results demonstrate the feasibility of integrating vessel operating conditions, energy consumption, life-cycle emissions and logistics flows within a traceable structure, thereby supporting the assessment of decarbonisation alternatives and the measurement of the carbon footprint of maritime transport.
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BibTeX
@misc{junior2026bottomup,
title = {{Bottom-up estimation of CO2 emissions from container ships: a proof of concept using real operational data on the Brazil–Asia route}},
author = {Walter Teixeira Lima Junior and Rudinei André Welter and Thiago Nobre Mascarenhas and Marcos Paulo Silva and Andrew Maccrimmon Lorimer},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x56v4d},
url = {https://eartharxiv.org/repository/view/15371/},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Bottom-up estimation of CO2 emissions from container ships: a proof of concept using real operational data on the Brazil–Asia route
AU - Walter Teixeira Lima Junior
AU - Rudinei André Welter
AU - Thiago Nobre Mascarenhas
AU - Marcos Paulo Silva
AU - Andrew Maccrimmon Lorimer
PY - 2026
DA - 2026/10/06
PB - EarthArXiv
DO - 10.31223/x56v4d
UR - https://eartharxiv.org/repository/view/15371/
AB - Granular quantification of greenhouse gas (GHG) emissions from maritime transport matters both for the assessment of decarbonisation strategies and for the attribution of the carbon footprint to logistics flows. This study proposes a bottom up approach that integrates operational reconstruction of the voyage, physical–energy modelling, Tank-to-Wake (TTW) and Well-to-Wake (WTW) assessment, and allocation of emissions to the flows carried. The approach was applied to the M/V EVER FAME along a sequential rotation between the east coast of South America and Asia, comprising 11 port calls, 10 legs and 13,913.3 nautical miles. Under the assumptions adopted, the model estimated a fuel consumption of 3,407.9 t and emissions of 10,612 tCO2 TTW and 12,741 tCO2eq WTW, corresponding to intensities of 768 kgCO2/TEU, counting laden and empty containers together, and 37.0 gCO2/TEU·km. Among the decarbonisation scenarios, the largest WTW reductions were obtained with e-ammonia (91.9%) and e-methanol (72.0%), whereas LNG performance varied with engine technology and methane slip. The approach further allocated emissions in full across 3,251 shipment records, preserving the voyage balance with a conservation deviation of 0.0000%. The results demonstrate the feasibility of integrating vessel operating conditions, energy consumption, life-cycle emissions and logistics flows within a traceable structure, thereby supporting the assessment of decarbonisation alternatives and the measurement of the carbon footprint of maritime transport.
ER -