A model for estimating the carbon footprint of maritime transportation of Liquefied Natural Gas under uncertainty

The demand for Liquefied Natural Gas (LNG) in the global markets has changed significantly. As a result, industries have been forced to consider investing significantly in supply chains to achieve an efficient distribution of LNG for cost efficiency and carbon footprint reduction. To minimize the contribution of LNG maritime transportation to global climate change, there is a need to quantify the carbon footprints systematically. In this research, we developed a novel and practical model for estimating the carbon footprint for LNG maritime transport. Using the MATLAB program, an uncertainty-based carbon footprint accounting framework is created. The Monte Carlo simulation model is built to conduct a carbon footprint analysis while the main input parameters were changed within a reliable range. Later, a multivariate sensitivity analysis is performed using the Risk Solver software to estimate the most significant parameters on the net carbon footprints. The sensitivity analysis results showed that that steam process day and steaming fuel consumption are found to be the most sensitive parameters for the overall carbon footprint for both Laden and Ballast trips. Furthermore, it was found that the Q-Max vessel produces more carbon emissions when compared to the Q-Flex, although both are traveling the same distance and are using the same fuel type. The type of fuel is also significantly affecting the emission values due to the relevant carbon content in the fuel. Like the case of the two conventional vessels, the one that is running with the only LNG is found to have fewer emissions when compared to the one run with dual-mode.Scopu