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.
Measuring SO2 ship emissions with an ultraviolet imaging camera
A. J. Prata
Nicarnica Aviation AS 2007, Kjeller, Norway
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Cited
28 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
- 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 SO<sub>2</sub> 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 SO<sub>2</sub> and NO<sub>2</sub> 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 SO<sub>x</sub> and NO<sub>x</sub> emissions from ships J. Balzani Lööv et al. 10.5194/amt-7-2597-2014
28 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
- 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 SO<sub>2</sub> 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 SO<sub>2</sub> and NO<sub>2</sub> 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 SO<sub>x</sub> and NO<sub>x</sub> emissions from ships J. Balzani Lööv et al. 10.5194/amt-7-2597-2014
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