Time series modeling of greenhouse gas emissions: A case study for a chemical tanker ship
DOI:
https://doi.org/10.33175/mtr.2026.278949Keywords:
Maritime; Shipping; Greenhouse gases; ModelingAbstract
Maritime transportation is, relatively, responsible for a small fraction of the total emissions; however, it is significant in the context of global carbon dioxide (CO2) emissions. The International Maritime Organization (IMO) has charted out an extensive program in its strategy on the reduction of greenhouse gas (GHG) emissions from ships. This research employs Box-Jenkins time series modeling for analysis and forecasting of CO2 and total sulfur dioxide (SO2) emissions by GHG index, as well as ton-mile-based emissions, utilizing actual data from the engine of a chemical tanker ship. Time series analysis can develop effective regulatory and operational strategies, as underlined by this research that investigates how operations, regulations, and technology influence profiles of emissions. By carrying out the Box-Jenkins methodology, incorporating autocorrelation moving average integrated autoregressive integrated variables, this study presents a modeling study that corrects importance in future policies emission reductions. Results obtained from strict model choice, validation, and assessment give useful input into emission patterns, and can be used as a foundation for more study and policy making aimed at improving the environmental sustainability of shipping operations. Decision-makers in the shipping sector can leverage the findings of this study to implement similar evidence-based approaches.
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Cite this article:
Bolat, F. (2026). Time series modeling of greenhouse gas emissions: A case study for a chemical tanker ship. Maritime Technology and Research, 8(1), 278949. https://doi.org/10.33175/mtr.2026.278949
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Highlights
- Although maritime transport accounts for a relatively small share of total emissions, it constitutes a significant contributor to global carbon dioxide (CO₂) outputs.
- This study utilises Box-Jenkins time series modelling to analyse and forecast CO₂ and sulphur dioxide (SO₂) emissions, based on real-world engine data from a chemical tanker vessel.
- Time series analysis is employed to assess how operational practices, regulatory frameworks, and technological interventions shape emission profiles.
- Through rigorous model selection, validation, and evaluation, the research offers robust insights that may underpin future policy development in maritime emissions reduction.
- The findings provide a valuable evidence base that can inform sustainable decision-making practices within the shipping industry.
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