Air pollution from ship exhaust gas can be reduced by the establishment of emission control areas (ECAs). Efficient supervision of ship emissions is currently a major concern of maritime authorities. In this study, a measurement system for exhaust gas from ships based on an unmanned aerial vehicle (UAV) was designed and developed. Sensors were mounted on the UAV to measure the concentrations of SO2 and CO2 in order to calculate the fuel sulfur content (FSC) of ships. The Waigaoqiao port in the Yangtze River Delta, an ECA in China, was selected for monitoring compliance with FSC regulations. Unlike in situ or airborne measurements, the proposed measurement system could be used to determine the smoke plume at about 5 m from the funnel mouth of ships, thus providing a means for estimating the FSC of ships. In order to verify the accuracy of these measurements, fuel samples were collected at the same time and sent to the laboratory for chemical examination, and these two types of measurements were compared. After 23 comparative experiments, the results showed that, in general, the deviation of the estimated value for FSC was less than 0.03 % (m/m) at an FSC level ranging from 0.035 % (m/m) to 0.24 % (m/m). Hence, UAV measurements can be used for monitoring of ECAs for compliance with FSC regulations.

Due to technical and cost limitations, the monitoring of emissions from ships sailing in open water within ship emission control areas (ECAs) is relatively rare. The present study adopts a monitoring method involving an unmanned aerial vehicle (UAV) that takes off from a patrol boat to measure the concentrations of SO₂ and CO₂ within the plumes of sailing ships. Our method aims to provide a low-cost, remote approach for estimating the fuel sulfur content (FSC) of sailing ships in open water, which overcomes the limitations of ground-based and small-aircraft-based methods. The selected monitoring area was the Yangtze River estuary, a domestic ECA with an FSC limit of 0.5 % (m∕m) implemented by the Chinese government. A total of 27 sailing ships were monitored, 12 of which were found to have an FSC of >0.5 % (m∕m). Moreover, the FSCs of the sailing ships were found to be higher than those of berthing ships in the study area. Based upon the online monitoring results, four of the monitored ships were intercepted by maritime law enforcement, and fuel samples were collected and analyzed in a laboratory; the results confirmed that all four FSCs were >0.5 % (m∕m). Among them, one offending ship was tracked down on 15 July 2019; this was the first time that a sailing ship had been caught for having failed the FSC regulations in China. Overall, the present study provides scientific support for evaluating the effectiveness of ECA policies and recommends that emissions from sailing ships be monitored more often in open water in the future.

A key research problem in the field of ship emissions is how to perform efficient, accurate, and timely measurements of pollutant gases in a ship’s plume. To address this, we have designed and implemented an unmanned aerial system (UAS) that consists of a rotary unmanned aerial vehicle (UAV), a lightweight pod for exhaust monitoring, and a mobile control terminal. The UAV carries the pod and a camera and can fly into a plume at close range. The pod is equipped with a gas acquisition module, SO₂ and NO₂ sensors, and communication modules to measure the gases in real time. The mobile control terminal is convenient for operators and receives real-time video and measured gas concentrations. We measured SO₂ and NO₂ in six ship plumes in 2018 to verify the effectiveness and accuracy of the UAS. The SO₂/NO₂ ratios in high-sulfur fuel were significantly higher than of those in low-sulfur fuel and can thus be used for distinguishing the sulfur content of ship fuel. In comparison to land-based and airborne-based measurements, we conclude that the UAS provides an active, close-range, low-cost, and accurate measurement approach for monitoring ship emissions in real time.

Effective technical methods for verifying the authenticity and accuracy of Automatic Identification System (AIS) data, which are important for safe navigation and traffic regulation, are still lacking. In this study, we propose a new method to verify AIS data by using video images taken by an Unmanned Aerial Vehicle (UAV). An improved ViBe algorithm is used to extract the ship target image from the video images and the ship's spatial position is calculated using a monocular target-positioning algorithm. The positioning results are compared with the position, speed and course data of the same ship in AIS, and the authenticity and accuracy of the AIS data are verified. The results of the experiment conducted in the inland waterways of Huangpu River in Shanghai, China, show that AIS signals can be automatically checked and verified by a UAV in real time and can thus improve the supervision efficiency of maritime departments.