Articles | Volume 19, issue 21
https://doi.org/10.5194/acp-19-13611-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-19-13611-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surveillance of SO2 and NO2 from ship emissions by MAX-DOAS measurements and the implications regarding fuel sulfur content compliance
Yuli Cheng
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanshan Wang
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanghai Institute of Eco-Chongming (SIEC), No.3663 Northern
Zhongshan Road, Shanghai, 200062, China
Jian Zhu
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Yanlin Guo
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Ruifeng Zhang
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Yiming Liu
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Yan Zhang
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanghai Institute of Eco-Chongming (SIEC), No.3663 Northern
Zhongshan Road, Shanghai, 200062, China
Institute of Atmospheric Sciences, Fudan University, Shanghai,
200433, China
Qi Yu
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanghai Institute of Eco-Chongming (SIEC), No.3663 Northern
Zhongshan Road, Shanghai, 200062, China
Weichun Ma
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanghai Institute of Eco-Chongming (SIEC), No.3663 Northern
Zhongshan Road, Shanghai, 200062, China
Bin Zhou
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention (LAP), Department of Environmental Science and Engineering,
Fudan University, Shanghai, 200433, China
Shanghai Institute of Eco-Chongming (SIEC), No.3663 Northern
Zhongshan Road, Shanghai, 200062, China
Institute of Atmospheric Sciences, Fudan University, Shanghai,
200433, China
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37 citations as recorded by crossref.
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- Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. 10.1016/j.envpol.2021.116501
- Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. 10.5194/amt-16-1767-2023
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- Identification of NO2 and SO2 over China: Characterization of polluted and hotspots Provinces M. Ali et al. 10.1007/s11869-024-01565-8
- Monitoring of compliance with fuel sulfur content regulations through unmanned aerial vehicle (UAV) measurements of ship emissions F. Zhou et al. 10.5194/amt-12-6113-2019
34 citations as recorded by crossref.
- Long-term variations of ground-level NO2 concentrations along coastal areas in China N. Zhan et al. 10.1016/j.atmosenv.2022.119158
- Robust Co(II)-Based Metal–Organic Framework for the Efficient Uptake and Selective Detection of SO2 V. López-Cervantes et al. 10.1021/acs.chemmater.3c02715
- Significant contribution of inland ships to the total NOx emissions along the Yangtze River X. Zhang et al. 10.5194/acp-23-5587-2023
- Investigation of emission characteristics of a marine cargo ship in real-world conditions Y. Zhang et al. 10.1016/j.scitotenv.2024.174991
- Impacts of Omicron associated restrictions on vertical distributions of air pollution at a suburb site in Shanghai S. Zhang et al. 10.1016/j.atmosenv.2022.119461
- Detection of Sulfur Dioxide by Broadband Cavity-Enhanced Absorption Spectroscopy (BBCEAS) R. Thalman et al. 10.3390/s22072626
- Monitoring the compliance of sailing ships with fuel sulfur content regulations using unmanned aerial vehicle (UAV) measurements of ship emissions in open water F. Zhou et al. 10.5194/amt-13-4899-2020
- Ground-Based MAX-DOAS Observations of Tropospheric NO2 and HCHO During COVID-19 Lockdown and Spring Festival Over Shanghai, China A. Tanvir et al. 10.3390/rs13030488
- MAX-DOAS observation in the midlatitude marine boundary layer: Influences of typhoon forced air mass R. Zhang et al. 10.1016/j.jes.2021.12.010
- MAX-DOAS observations of ship emissions in the North Sea A. Mahajan et al. 10.1016/j.marpolbul.2024.116761
- Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. 10.1016/j.envpol.2021.116501
- Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. 10.5194/amt-16-1767-2023
- Development of a spectrum-based ship fuel sulfur content real-time evaluation method H. Wu et al. 10.1016/j.marpolbul.2022.114484
- Trace Gases over Land and Ocean Surfaces of China: Hotspots, Trends, and Source Contributions M. Ali et al. 10.1007/s41748-023-00354-0
- Validation of Water Vapor Vertical Distributions Retrieved from MAX-DOAS over Beijing, China H. Lin et al. 10.3390/rs12193193
- Observations by Ground-Based MAX-DOAS of the Vertical Characters of Winter Pollution and the Influencing Factors of HONO Generation in Shanghai, China S. Xu et al. 10.3390/rs13173518
- Vertical distributions of atmospheric HONO and the corresponding OH radical production by photolysis at the suburb area of Shanghai, China S. He et al. 10.1016/j.scitotenv.2022.159703
- Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations M. Ghahremanloo et al. 10.1016/j.envint.2024.108818
- A Diffused Mini-Sniffing Sensor for Monitoring SO2 Emissions Compliance of Navigating Ships M. Deng et al. 10.3390/s22145198
- Impact Assessment of COVID‐19 Lockdown on Vertical Distributions of NO2 and HCHO From MAX‐DOAS Observations and Machine Learning Models S. Zhang et al. 10.1029/2021JD036377
- Gaseous Emissions from a Seagoing Ship under Different Operating Conditions in the Coastal Region of China C. Bai et al. 10.3390/atmos11030305
- The investigation of retrieval method for aerosol and water vapor profiles based on MAX-DOAS technology C. Zhou et al. 10.1016/j.apr.2024.102183
- Vertical distributions and potential sources of wintertime atmospheric pollutants and the corresponding ozone production on the coast of Bohai Sea C. Xing et al. 10.1016/j.jenvman.2022.115721
- Implementation of particulate measuring and SO2 gas based on Android S. Syahrorini et al. 10.1088/1757-899X/1098/4/042062
- Protocol development for real-time ship fuel sulfur content determination using drone based plume sniffing microsensor system A. Anand et al. 10.1016/j.scitotenv.2020.140885
- Monitoring Sulfur Content in Marine Fuel Oil Using Ultraviolet Imaging Technology Z. Zhang et al. 10.3390/atmos12091182
- Simultaneous measurement of SO2 and CO2 for sulfur content detection in marine diesel fuel using QCL absorption spectroscopy J. Li et al. 10.1016/j.measurement.2024.115861
- Investigating the Sources of Formaldehyde and Corresponding Photochemical Indications at a Suburb Site in Shanghai From MAX‐DOAS Measurements S. Zhang et al. 10.1029/2020JD033351
- MAX-DOAS and in-situ measurements of aerosols and trace gases over Dongying, China: Insight into ozone formation sensitivity based on secondary HCHO X. Zheng et al. 10.1016/j.jes.2022.09.014
- Surveillance of ship emissions and fuel sulfur content based on imaging detection and multi-task deep learning K. Cao et al. 10.1016/j.envpol.2021.117698
- Ship emission monitoring sensor web for research and application F. Zhou et al. 10.1016/j.oceaneng.2022.110980
- An improved method for optimizing detection bands of marine exhaust SO2 concentration in ultraviolet dual-band measurements based on signal-to-noise ratio Z. Zhang et al. 10.1016/j.apr.2022.101479
- Estimation of ship emission rates at a major shipping lane by long-path DOAS measurements K. Krause et al. 10.5194/amt-14-5791-2021
- Investigation of formaldehyde sources and its relative emission intensity in shipping channel environment J. Liu et al. 10.1016/j.jes.2023.06.020
3 citations as recorded by crossref.
- Trace Gases over Land and Ocean Surfaces of China: Hotspots, Trends, and Source Contributions M. Ali et al. 10.1007/s41748-023-00354-0
- Identification of NO2 and SO2 over China: Characterization of polluted and hotspots Provinces M. Ali et al. 10.1007/s11869-024-01565-8
- Monitoring of compliance with fuel sulfur content regulations through unmanned aerial vehicle (UAV) measurements of ship emissions F. Zhou et al. 10.5194/amt-12-6113-2019
Latest update: 14 Dec 2024
Short summary
Owing to the gradual implementation of emission control zone (ECA) regulations, feasible technology for the surveillance of compliance with respect to fuel sulfur content is in high demand. We presented shore-based MAX-DOAS measurements of ship-emitted SO2 and NO2 under different traffic conditions. The results of this study indicate that this technique has high potential as a fast and accurate way to surveil ship emissions and fuel sulfur content.
Owing to the gradual implementation of emission control zone (ECA) regulations, feasible...
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