Development of green port index : a tool for assessing ports based on implementation of GHG emission reduction measures
Date of Award
11-1-2025
Document Type
Dissertation
Degree Name
Master of Science in Maritime Affairs
Specialization
Maritime Energy Management
Campus
Malmö, Sweden
Country
Gambia
First Advisor
Aykut Ölcer
Abstract
As the global attention shift towards climate change due its devastating impact on our environment, all sectors including ports should implement mitigation and adaptation strategies to combat it. This is why green port development and operation has become increasingly important to reduce the environmental impact of port operations. Despite the growing number of research in green ports, quantitative assessment of ports based on implementation of measures to mitigate their environmental impacts is rarely addressed. Therefore, this study seeks to develop a green port index (GPI) which is a comprehensive mechanism for evaluating ports based on implementation of key measures to reduce GHG emissions. This assessment tool produces a 0 – 100% composite score taking into account 12 key performance indicators (KPIs) identified through literature review. These KPIs include energy efficiency, electrification, green fuel utilization, port greenery, renewable energy usage, smart/microgrid coverage, onshore power supply (OPS) usage, just in time arrival, alternative fuel bunkering, green hinterland transportation of cargo, employee commuting and truck congestion reduction. The KPIs are classified based on the greenhouse gas (GHG) emission scope impacted. Additionally, this research proposes a methodology to quantify each of the 12 KPIs. Fuzzy Analytical Hierarchy Process (FAHP) and Adaptive Neuro-Fuzzy Inference System (ANFIS) hybrid methodology was used to develop the GPI. Questionnaires were sent to heterogeneous group of experts to determine relative importance of the KPIs. FAHP technique was used to determine the weights of the KPIs. The scores and weights of the KPIs are used to develop a mathematical model which provide training data for the ANFIS model. ANFIS is then used to develop GPI which undergoes rigorous testing to determine its sensitivity to changes in KPI scores. The study revealed that renewable energy (RE) usage is the most important measure to reduce port GHG emission and green employee commuting is the least important. Additionally, the findings reveal that electrification, RE and OPS usage are the most important KPIs for scope 1, scope 2 and scope 3 port GHG emission reduction respectively. This study also demonstrated how policy makers and other relevant stakeholders can use the propose methodology to evaluate their GPI score.