Carbon emission allowance allocation based on a bi-level multi-objective model in maritime shipping

Abstract

To mitigate carbon emissions from maritime shipping, this study investigates the strategies and performance of allocating carbon emission allowances (CEAs) with the cap-and-trade mechanism among shipping companies. Using a bi-level model solved by the multi-objective particle swarm optimization algorithm based on Pareto solution set, the interactions between decisions of the government and shipping companies are well characterized. The results of the benchmark scenario indicate that all shipping companies’ optimal carbon emissions decrease annually during the planning period, and a larger company usually exhibits a better emission reduction performance. However, economic benefits of shipping companies and the society display an annually declining trend due to additional carbon emission reduction costs. The sensitivity analysis demonstrates that the decreasing carbon prices lead to more emissions, while the optimal total carbon emissions decrease as carbon reduction costs increase. These findings create implications for multiple stakeholders to formulate their own carbon emissions mitigation strategies under the cap-and-trade mechanism.