AIS data-driven assessment of shore side electricity's emission reduction potential in China

Abstract

Emissions from ships at ports significantly affect air quality and public health. Shore side electricity (SSE) is a promising solution for mitigating these emissions. Based on Automatic Identification System (AIS) data and national grid emission factors, this study developed a bottom-up model to evaluate SSE's emission reduction potential. We compiled an emission inventory of container ships at 37 coastal ports in mainland China in 2022 and evaluated the effectiveness of SSE. Results show that the emissions of air pollutants (SO₂, NO_X, PM_2.5, CO, and NMVOC) from these ships totaled 5.58 × 10⁴ tons, while greenhouse gases (CO₂, CH₄, and N₂O) totaled 2.90 × 10⁶ tons. SSE implementation results in significant emission reductions, decreasing overall port emissions by approximately 58 % and berth emissions by nearly 90 %. However, due to substantial differences in port characteristics and regional grid energy structures, the emission reduction potential exhibits considerable heterogeneity across ports. Based on our analysis of emission reduction data across various ports, we propose three targeted strategies: First, at the regional level, in areas with cleaner grid structures and high port activity, SSE facilities should be prioritized. In contrast, in regions that rely on fossil fuels, a combination of clean-energy vessels and route optimization measures should be promoted. Second, at the policy level, it is recommended to stimulate enterprise investment by implementing tiered subsidies, preferential electricity tariffs, and enhanced regulatory oversight. Third, at the implementation level, a collaborative mechanism between ports and shipping companies should be established to jointly optimize the planning and operation of SSE facilities.