Articles | Volume 13, issue 9
https://doi.org/10.5194/amt-13-4899-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-4899-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Sep 2020
Research article |
| 17 Sep 2020
| 17 Sep 2020
Monitoring the compliance of sailing ships with fuel sulfur content regulations using unmanned aerial vehicle (UAV) measurements of ship emissions in open water
College of Information Engineering, Shanghai Maritime University,
Shanghai 201306, China
Shanghai Engineering Research Center of Ship Exhaust Intelligent
Monitoring, Shanghai 201306, China
Liwei Hou
College of Ocean Science and Engineering, Shanghai Maritime
University, Shanghai 201306, China
Rui Zhong
College of Information Engineering, Shanghai Maritime University,
Shanghai 201306, China
Shanghai Engineering Research Center of Ship Exhaust Intelligent
Monitoring, Shanghai 201306, China
Wei Chen
Pudong Maritime Safety Administration of the People's Republic of
China, Shanghai 200137, China
Xunpeng Ni
Pudong Maritime Safety Administration of the People's Republic of
China, Shanghai 200137, China
Shengda Pan
College of Information Engineering, Shanghai Maritime University,
Shanghai 201306, China
Shanghai Engineering Research Center of Ship Exhaust Intelligent
Monitoring, Shanghai 201306, China
Ming Zhao
College of Information Engineering, Shanghai Maritime University,
Shanghai 201306, China
Shanghai Engineering Research Center of Ship Exhaust Intelligent
Monitoring, Shanghai 201306, China
Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences, Shanghai 200083, China
Bowen An
College of Information Engineering, Shanghai Maritime University,
Shanghai 201306, China
Shanghai Engineering Research Center of Ship Exhaust Intelligent
Monitoring, Shanghai 201306, China
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- Tracking and measuring plumes from sailing ships using an unmanned aerial vehicle F. Zhou et al. 10.1049/itr2.12256
- Remote Detection of Different Marine Fuels in Exhaust Plumes by Onboard Measurements in the Baltic Sea Using Single-Particle Mass Spectrometry E. Rosewig et al. 10.3390/atmos14050849
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- Applications, Evolutions, and Challenges of Drones in Maritime Transport J. Wang et al. 10.3390/jmse11112056
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- Unmanned aerial vehicles and low-cost sensors for air quality monitoring: A comprehensive review of applications across diverse emission sources . Vishal et al. 10.1016/j.scs.2025.106409
- A comprehensive review of machine learning and Internet of Things integrations for emission monitoring and resilient sustainable energy management of ships in port areas M. Elsisi et al. 10.1016/j.rser.2025.115843
- Air Pollutant Emission Factors of Inland River Ships under Compliance F. Zhou et al. 10.3390/jmse12101732
- Evaluating methods for marine fuel sulfur content using microsensor sniffing systems on ocean-going vessels S. Yang et al. 10.1016/j.scitotenv.2024.173765
- Characteristics of real-world ship energy consumption and emissions based on onboard testing A. Fan et al. 10.1016/j.marpolbul.2023.115411
- Ship Emission Measurements Using Multirotor Unmanned Aerial Vehicles: Review L. Šaparnis et al. 10.3390/jmse12071197
- Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports L. Shen et al. 10.1016/j.trd.2022.103415
- Rapid detection of trace sulfur content in ship fuel oil based on tin oxide quantum dot fluorescent sensors assisted by multi-column convolutional neural network C. Fu et al. 10.1016/j.microc.2024.111396
- A bibliometric analysis of scientific research trends in monitoring systems for measuring ship emissions L. Egan et al. 10.1007/s11356-023-26723-w
- A Ship Emission Monitoring Option for Fuel Sulphur Content Measurement in Complex Environments F. Zhou et al. 10.3390/jmse13040775
- Intelligent detection and emission characteristics analysis of black smoke and blackness from navigating ships: A case study of Shanghai waters M. Deng et al. 10.1016/j.ocecoaman.2025.107692
- A Study on Monitoring and Supervision of Ship Nitrogen-Oxide Emissions and Fuel-Sulfur-Content Compliance Z. Wang et al. 10.3390/atmos14010175
- Evaluating the reliability of UAV-based carbon dioxide measurements in the lower troposphere C. Fernando & M. Adams 10.1016/j.geomat.2024.100032
- The Positive Effects of Linked Control Policy for Vessels Passing Through Locks on Air Quality—A Case Study of Yichang, China L. Hou & B. Zhang 10.3390/atmos16040368
- Ship emission monitoring with a joint mode of motherships and unmanned aerial vehicles D. Zhuge et al. 10.1016/j.cor.2025.107012
- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. 10.1016/j.atmosenv.2022.119384
- A Diffused Mini-Sniffing Sensor for Monitoring SO2 Emissions Compliance of Navigating Ships M. Deng et al. 10.3390/s22145198
- Detection and analysis of ship emissions using single-particle mass spectrometry: A land-based field study in the port of rostock, Germany E. Rosewig et al. 10.1016/j.aeaoa.2024.100302
28 citations as recorded by crossref.
- Detection of ship plumes from residual fuel operation in emission control areas using single-particle mass spectrometry J. Passig et al. 10.5194/amt-14-4171-2021
- Ship emission monitoring sensor web for research and application F. Zhou et al. 10.1016/j.oceaneng.2022.110980
- A Real-Time Measurement-Modeling System for Ship Air Pollution Emission Factors F. Zhou et al. 10.3390/jmse10060760
- Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. 10.5194/amt-16-1767-2023
- Particle Measurements from In-use Maritime Traffic Using an Unmanned Aerial Vehicle in Rafina, Greece M. Haugen et al. 10.1016/j.trpro.2023.11.693
- Tracking and measuring plumes from sailing ships using an unmanned aerial vehicle F. Zhou et al. 10.1049/itr2.12256
- Remote Detection of Different Marine Fuels in Exhaust Plumes by Onboard Measurements in the Baltic Sea Using Single-Particle Mass Spectrometry E. Rosewig et al. 10.3390/atmos14050849
- Three-dimensional spatiotemporal variability of CO2 in suburban and urban areas of Shaoxing City in the Yangtze River Delta, China Z. Wu et al. 10.1016/j.scitotenv.2023.163501
- Applications, Evolutions, and Challenges of Drones in Maritime Transport J. Wang et al. 10.3390/jmse11112056
- SO2 compliance monitoring and emission characteristics analysis of navigating ships: A case study of Shanghai waters in emission control areas, China M. Deng et al. 10.1016/j.apr.2022.101560
- Unmanned aerial vehicles and low-cost sensors for air quality monitoring: A comprehensive review of applications across diverse emission sources . Vishal et al. 10.1016/j.scs.2025.106409
- A comprehensive review of machine learning and Internet of Things integrations for emission monitoring and resilient sustainable energy management of ships in port areas M. Elsisi et al. 10.1016/j.rser.2025.115843
- Air Pollutant Emission Factors of Inland River Ships under Compliance F. Zhou et al. 10.3390/jmse12101732
- Evaluating methods for marine fuel sulfur content using microsensor sniffing systems on ocean-going vessels S. Yang et al. 10.1016/j.scitotenv.2024.173765
- Characteristics of real-world ship energy consumption and emissions based on onboard testing A. Fan et al. 10.1016/j.marpolbul.2023.115411
- Ship Emission Measurements Using Multirotor Unmanned Aerial Vehicles: Review L. Šaparnis et al. 10.3390/jmse12071197
- Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports L. Shen et al. 10.1016/j.trd.2022.103415
- Rapid detection of trace sulfur content in ship fuel oil based on tin oxide quantum dot fluorescent sensors assisted by multi-column convolutional neural network C. Fu et al. 10.1016/j.microc.2024.111396
- A bibliometric analysis of scientific research trends in monitoring systems for measuring ship emissions L. Egan et al. 10.1007/s11356-023-26723-w
- A Ship Emission Monitoring Option for Fuel Sulphur Content Measurement in Complex Environments F. Zhou et al. 10.3390/jmse13040775
- Intelligent detection and emission characteristics analysis of black smoke and blackness from navigating ships: A case study of Shanghai waters M. Deng et al. 10.1016/j.ocecoaman.2025.107692
- A Study on Monitoring and Supervision of Ship Nitrogen-Oxide Emissions and Fuel-Sulfur-Content Compliance Z. Wang et al. 10.3390/atmos14010175
- Evaluating the reliability of UAV-based carbon dioxide measurements in the lower troposphere C. Fernando & M. Adams 10.1016/j.geomat.2024.100032
- The Positive Effects of Linked Control Policy for Vessels Passing Through Locks on Air Quality—A Case Study of Yichang, China L. Hou & B. Zhang 10.3390/atmos16040368
- Ship emission monitoring with a joint mode of motherships and unmanned aerial vehicles D. Zhuge et al. 10.1016/j.cor.2025.107012
- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. 10.1016/j.atmosenv.2022.119384
- A Diffused Mini-Sniffing Sensor for Monitoring SO2 Emissions Compliance of Navigating Ships M. Deng et al. 10.3390/s22145198
- Detection and analysis of ship emissions using single-particle mass spectrometry: A land-based field study in the port of rostock, Germany E. Rosewig et al. 10.1016/j.aeaoa.2024.100302
Latest update: 30 May 2025
Short summary
On 15 July 2019, using an unmanned aerial vehicle (UAV), maritime authorities ferreted out a sailing ship whose fuel sulfur content (FSC) failed to meet Chinese regulations. This was the first time that a sailing ship had been caught for having failed the FSC regulations in China. The UAV system, method, and monitoring result utilized are discussed in this paper. We recommend that emissions from sailing ships be monitored more often in the open water in the future.
On 15 July 2019, using an unmanned aerial vehicle (UAV), maritime authorities ferreted out a...
