| Author: | Lu, Keru |
| Title: | Development of a UV-based remote sensing technology for sulphur dioxide monitoring from ship emissions |
| Advisors: | Wong, Man Sing Charles (LSGI) Li, Zhilin (LSGI) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Ships -- Fuel Combustion gases -- Environmental aspects Air -- Pollution -- Measurement Sulphur dioxide Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Land Surveying and Geo-Informatics |
| Pages: | xiv, 95 pages : color illustrations |
| Language: | English |
| Abstract: | Sulphur Dioxide (SO₂) is one of the major pollutants in the atmosphere and can be regarded as one of the main indicators of air quality. In Hong Kong, about 49% of SO₂ comes from ship emissions according to the annual statistics released by the Environmental Protection Department (EPD 2018). To reduce such pollution, the HKSAR Government has recently adopted regulations for fuel switching, improving fuel efficiency, and optimizing operation practices. Such regulations require ships, to comply with switching to low sulphur marine fuel with a sulphur content of less than 0.5%, when approaching to and at the harbours, with effect from January 2019. In 2020, Hong Kong water has 87,831 vessel arrivals. Therefore, the EPD is not capable of checking the fuels used in each ship through on-board sampling. Besides, a relatively limited portion of the ships can be checked manually due to the resource implications. As the manual checking is time-consuming and labour-intensive, it essentially demonstrates an urgent need to develop an effective and efficient method for detection and monitoring the level of SO₂ from ship emissions. This study aims at development of a UV-based remote sensing technology for SO₂ monitoring from ship emissions. Through this technology, the ship could be quickly screened for non-compliance with the regulations of emissions, so as to increase the effectiveness and efficiency of the monitoring process for monitoring the ship emissions. In this study, a set of comprehensive mathematical models is built, demonstrating the relationship between the intensity of UV image points (pixels) and the SO₂ concentrations, in different atmospheric environments. This model is the first of all obtained through systematic experiments in the laboratory using tailor-designed devices in controlled environments, then it is calibrated with extensive field experiments on the effect of factors in the coastal environments; and finally, it is validated with Sulphur content in the fuel from the Bunker Delivery Note (BDN) of ships. The monitoring results of SO₂ concentrations from fumes can also be converted into sulphur content of fuel as required. From the observational experiment, this UV-based remote sensing technology was used to monitor 200 ships. About 50 ships of them had the BDN values for validation. A 4-category standard for reclassification of the monitoring results has been designed. According to this standard, this technology has achieved a high accuracy of about 95.918%. The mean absolute error of the monitoring results is 0.060. The RMSE of the monitoring results is 0.096. For the sake of convenience and reliability, this technology is enhanced by integrating all the monitoring devices into an expandable support device that can be mounted onto the car, on the aircraft, onto law enforcement boats, and standing on the ground while extending the monitoring range. This monitoring system has the ubiquitous features of free from contact (remote sensing) with a long detection range of distance, high sensitivity and reliable results. It allows monitoring in normal weather conditions. No disturbance is generated to affect the normal navigation of the ships and/or ships in normal operations parking at the harbours during the monitoring process. In addition, this system can assist to monitor all ships in a certain range at the same time. However, this technology also has a limitation as a passive light source remote sensing technology. That means, it could not work well at the periods with very weak UV light intensity such as the night-time and on heavy hazy days. With the development of UV hardware and models, it is expected that the monitoring accuracy and monitoring range can be improved in the future. |
| Rights: | All rights reserved |
| Access: | open access |
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