Carbon emission estimation and carbon reduction strategies analysis: a case study of Shanghai Port

Against the backdrop of advancing the United Nations sustainable development goals SDG 7 (affordable and clean energy) and 13 (climate action), measuring and reducing carbon emissions has been critical for ports’ decarbonization and sustainable development. This paper integrates data from multiple sources to establish a comprehensive carbon emission evaluation framework for ports, employing system dynamic simulation models to analyze the impact of various emission reduction strategies. And a dual modeling approach integrates bottom-up and top-down methodologies to respectively estimate emissions from in-port ships and port facilities, predicting forward emissions for multiple scenarios using artificial neural networks. A case study of the world’s busiest container port—Shanghai Port is presented to demonstrate the proposed evaluation framework. The result shows that strategies, such as adopting alternative fuels, implementing government subsidies, and promoting carbon trading schemes, are effective methods for reducing carbon emissions. This study develops a data-driven framework to identify the most effective emission-reduction strategies providing a foundation for port managers and operators to assess and improve the sustainability performance of their operations. The results also offer insights for policymakers to reduce port carbon emissions and enhance sustainable port development.