Integrated LCA–AHP Assessment of Alternative Marine Fuels with ARIMA-Based Emission Forecasting

Geographical Scope and Rationale for SOₓ and NOₓ Data The dataset specifically focuses on the European region for SOₓ and NOₓ emission records. This targeted geographical scope is driven by three rigorous scientific and regulatory factors: Data Reliability and MRV Framework: The European Environment Agency (EEA) provides the most comprehensive, standardized, and verified (MRV) maritime emission inventory globally. Including other regions with fragmented or unverified reporting systems would compromise the statistical robustness of the dataset. Stringent Policy Environment (ECAs): European waters encompass the world's most mature and strictly enforced Emission Control Areas (ECAs) under MARPOL Annex VI. This provides an ideal, highly regulated baseline for evaluating the actual impact of stringent environmental policies on non-CO₂ pollutants. Demonstrated Regulatory Effectiveness: As demonstrated in our comparative analysis between European and Asian fleets, European operations exhibit statistically significant emission reduction trends driven by binding frameworks (e.g., EU ETS, CII requirements). Therefore, European data offers the highest reliability for assessing the integrated LCA-AHP performance of alternative fuels under advanced decarbonization trajectories. Data Variables and Unit Specifications To ensure accurate interpretation of the raw datasets accompanying this study, the operational variables and units are defined as follows: Fuel Consumption and CO₂ Emissions: All values regarding annual fuel consumption and corresponding total CO₂ emissions are expressed in absolute metric tonnes (t). These columns contain whole numbers without thousands separators (e.g., a value of 17314027 represents exactly 17,314,027 metric tonnes). Reference Speed (Vref): The design reference speed of the vessel categories is expressed in knots. SOₓ and NOₓ Emissions: The regional annual SOₓ and NOₓ emission records are expressed in kilotonnes (kt) (i.e., thousands of metric tonnes). For clarity, a dataset value of 19.483 directly translates to 19,483 metric tonnes. Numerical Formatting: The entire dataset conforms to international numerical standards, utilizing a period (.) as the decimal separator. No thousands separators are used in any file to ensure direct compatibility with statistical software.