This article examines the impact of automatic identification system (AIS) data thinning on ship emissions inventory results. AIS data thinning is theoretically proven to lead to a smaller result for a ship’s air pollutant emissions inventory. The AIS dynamic data of six sampled ships for 1 day and for 1 year were thinned at 1 min, 3 min, 10 min, 30 min, and 1 h time intervals, and then CO₂, NO_X, CH, PM, SO₂, and other air pollutant emissions were estimated both with and without AIS data thinning in the different time intervals. The results show that AIS data thinning affects the air pollutant emissions inventory results of the ships, and the impact is greater as the thinning interval increases. When the thinning interval is less than 10 min, the impact is less than 10%, but the impact increases to about 10–15% at a 30 min interval and about 15–20% at a 60 min interval. The impacts of thinning on the emissions of ships with acutely fluctuating speeds are more significant because the constantly changing speed is the main reason why data thinning affects the ship emissions inventory. Therefore, these data suggest that the AIS data can be thinned at intervals of 5 or 10 min when establishing a coastal or national ship air pollutant emissions inventory, the AIS data should be thinned at intervals of less than 3 min when establishing the air pollutant emissions inventory of inland river ships, and data thinning is not recommended when establishing a port or smaller-scale ship air pollutant emissions inventory.

With the rapid development of Quanzhou, the risk of offshore oil spill accidents has increased. Once a spill accident takes place, the spilled oil causes decades or even hundreds of years of continuous pollution to the marine environment. The direct economic loss may be as high as hundreds of millions of yuan, while the natural resources that are almost impossible to fully recover after such pollution may generate inestimable indirect economic losses in the long term. Therefore, predicting the accident probability, analyzing the causes of risk and putting forward suggestions for improvement have important practical guiding significance for reducing the risk and improving the emergency prevention and ability to control offshore oil spill accidents. Based on the statistical data of cargo throughput, the number of ships entering and leaving the port, and maritime pollution accidents in Quanzhou from 2011 to 2020, the frequency of oil spills during the 14th Five-Year Plan could be predicted by using the direct calculation method and fault tree analysis (FAT). The results show that the frequency of operational and average oil spills from ships are once in 4.92 years and once in 2.41 years, respectively, while the frequency of oil spills from storage tanks is once in 7.28 years. The main causes are anthropic factors, which are manifested as irregular operation, misoperation, unfamiliar equipment, disorganization of the emergency response and failure of the emergency facilities. Therefore, the suggestions put forward for reducing accidents in the future include enhancing the inspection of crew member qualifications as well as the offshore supervision of engineering operation vessels and fishing vessels, increasing the proportion of terminal emergency equipment and personnel and participation in emergency actions, clarifying the division of responsibilities between the terminal and cleanup company, and revising the relevant standards for the evaluation of the terminal's ability to cope with the emergency of offshore oil spill accidents.