Articles | Volume 7, issue 5
https://doi.org/10.5194/amt-7-1213-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/amt-7-1213-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 May 2014
Research article |
| 12 May 2014
Measuring SO2 ship emissions with an ultraviolet imaging camera
A. J. Prata
Nicarnica Aviation AS 2007, Kjeller, Norway
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Cited
29 citations as recorded by crossref.
- Ship emission monitoring sensor web for research and application F. Zhou et al. 10.1016/j.oceaneng.2022.110980
- 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
- Spectral Calibration for SO2 Cameras with Light Dilution Effect Correction K. Wu et al. 10.3390/rs15143652
- First estimates of fumarolic SO 2 fluxes from Putana volcano, Chile, using an ultraviolet imaging camera K. Stebel et al. 10.1016/j.jvolgeores.2014.12.021
- Monitoring Sulfur Content in Marine Fuel Oil Using Ultraviolet Imaging Technology Z. Zhang et al. 10.3390/atmos12091182
- 基于背景图像重构的船舶尾气遥感监测方法 何. He Weiwei et al. 10.3788/AOS231889
- Real-world emission characteristics of an ocean-going vessel through long sailing measurement L. Yang et al. 10.1016/j.scitotenv.2021.152276
- Using Multispectral Imaging to Reveal the Relationship between UV Absorbance and Sulphur Dioxide Concentration K. Lu et al. 10.3390/su15010138
- 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
- Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. 10.1016/j.envpol.2021.116501
- Monitoring shipping emissions in the German Bight using MAX-DOAS measurements A. Seyler et al. 10.5194/acp-17-10997-2017
- 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
- Real-time correction of light dilution effect for ship emission monitoring of SO2 H. Zhang et al. 10.1364/OE.543864
- Quantitative determination of SO2 flux from industrial chimney through machine vision with plume model verification W. He et al. 10.1016/j.measurement.2024.115255
- Observation of turbulent dispersion of artificially released SO2 puffs with UV cameras A. Dinger et al. 10.5194/amt-11-6169-2018
- Real-time continuous calibration method for an ultraviolet camera K. Wu et al. 10.1364/OL.410635
- The Role of Belgian Airborne Sniffer Measurements in the MARPOL Annex VI Enforcement Chain W. Van Roy et al. 10.3390/atmos14040623
- Surveillance of SO2 and NO2 from ship emissions by MAX-DOAS measurements and the implications regarding fuel sulfur content compliance Y. Cheng et al. 10.5194/acp-19-13611-2019
- Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days M. Osorio et al. 10.3390/rs9060517
- Simulation Analysis on the Optimal Imaging Detection Wavelength of SO2 Concentration in Ship Exhaust Z. Zhang et al. 10.3390/atmos11101119
- Effect of UV Scattering on Detection Limit of SO2 Cameras K. Wu et al. 10.3390/rs15030705
- Quantification of ash sedimentation dynamics through depolarisation imaging with AshCam B. Esse et al. 10.1038/s41598-018-34110-6
- Research on Monitoring Method of Fuel Sulfur Content of Ships in Tianjin Port Q. Songbo et al. 10.1088/1742-6596/2009/1/012073
- Development of a self-calibration method for real-time monitoring of SO2 ship emissions with UV cameras K. Wu et al. 10.1364/OE.415156
- Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. 10.5194/amt-16-1767-2023
- Influence of ship direct emission on HONO sources in channel environment Y. Guo et al. 10.1016/j.atmosenv.2020.117819
- Computer vision for improved estimates of SO2emission rates and plume dynamics H. Thomas & A. Prata 10.1080/01431161.2017.1401250
- Characteristics of real-world ship energy consumption and emissions based on onboard testing A. Fan et al. 10.1016/j.marpolbul.2023.115411
- Field test of available methods to measure remotely SOx and NOx emissions from ships J. Balzani Lööv et al. 10.5194/amt-7-2597-2014
29 citations as recorded by crossref.
- Ship emission monitoring sensor web for research and application F. Zhou et al. 10.1016/j.oceaneng.2022.110980
- 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
- Spectral Calibration for SO2 Cameras with Light Dilution Effect Correction K. Wu et al. 10.3390/rs15143652
- First estimates of fumarolic SO 2 fluxes from Putana volcano, Chile, using an ultraviolet imaging camera K. Stebel et al. 10.1016/j.jvolgeores.2014.12.021
- Monitoring Sulfur Content in Marine Fuel Oil Using Ultraviolet Imaging Technology Z. Zhang et al. 10.3390/atmos12091182
- 基于背景图像重构的船舶尾气遥感监测方法 何. He Weiwei et al. 10.3788/AOS231889
- Real-world emission characteristics of an ocean-going vessel through long sailing measurement L. Yang et al. 10.1016/j.scitotenv.2021.152276
- Using Multispectral Imaging to Reveal the Relationship between UV Absorbance and Sulphur Dioxide Concentration K. Lu et al. 10.3390/su15010138
- 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
- Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. 10.1016/j.envpol.2021.116501
- Monitoring shipping emissions in the German Bight using MAX-DOAS measurements A. Seyler et al. 10.5194/acp-17-10997-2017
- 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
- Real-time correction of light dilution effect for ship emission monitoring of SO2 H. Zhang et al. 10.1364/OE.543864
- Quantitative determination of SO2 flux from industrial chimney through machine vision with plume model verification W. He et al. 10.1016/j.measurement.2024.115255
- Observation of turbulent dispersion of artificially released SO2 puffs with UV cameras A. Dinger et al. 10.5194/amt-11-6169-2018
- Real-time continuous calibration method for an ultraviolet camera K. Wu et al. 10.1364/OL.410635
- The Role of Belgian Airborne Sniffer Measurements in the MARPOL Annex VI Enforcement Chain W. Van Roy et al. 10.3390/atmos14040623
- Surveillance of SO2 and NO2 from ship emissions by MAX-DOAS measurements and the implications regarding fuel sulfur content compliance Y. Cheng et al. 10.5194/acp-19-13611-2019
- Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days M. Osorio et al. 10.3390/rs9060517
- Simulation Analysis on the Optimal Imaging Detection Wavelength of SO2 Concentration in Ship Exhaust Z. Zhang et al. 10.3390/atmos11101119
- Effect of UV Scattering on Detection Limit of SO2 Cameras K. Wu et al. 10.3390/rs15030705
- Quantification of ash sedimentation dynamics through depolarisation imaging with AshCam B. Esse et al. 10.1038/s41598-018-34110-6
- Research on Monitoring Method of Fuel Sulfur Content of Ships in Tianjin Port Q. Songbo et al. 10.1088/1742-6596/2009/1/012073
- Development of a self-calibration method for real-time monitoring of SO2 ship emissions with UV cameras K. Wu et al. 10.1364/OE.415156
- Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. 10.5194/amt-16-1767-2023
- Influence of ship direct emission on HONO sources in channel environment Y. Guo et al. 10.1016/j.atmosenv.2020.117819
- Computer vision for improved estimates of SO2emission rates and plume dynamics H. Thomas & A. Prata 10.1080/01431161.2017.1401250
- Characteristics of real-world ship energy consumption and emissions based on onboard testing A. Fan et al. 10.1016/j.marpolbul.2023.115411
- Field test of available methods to measure remotely SOx and NOx emissions from ships J. Balzani Lööv et al. 10.5194/amt-7-2597-2014
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