87 citations as recorded by crossref.

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11. Monitoring Sulfur Content in Marine Fuel Oil Using Ultraviolet Imaging Technology Z. Zhang et al. https://doi.org/10.3390/atmos12091182
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19. Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes S. Ausmeel et al. https://doi.org/10.5194/amt-12-4479-2019
20. Monitoring shipping emissions in the German Bight using MAX-DOAS measurements A. Seyler et al. https://doi.org/10.5194/acp-17-10997-2017
21. Detection of NO2 pollution plumes from individual ships with the TROPOMI/S5P satellite sensor A. Georgoulias et al. https://doi.org/10.1088/1748-9326/abc445
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24. Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. https://doi.org/10.1016/j.envpol.2021.116501
25. 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. https://doi.org/10.3390/atmos14050849
26. 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. https://doi.org/10.5194/amt-13-4899-2020
27. Sensitivity analysis for the detection of NO2 plumes from seagoing ships using TROPOMI data S. Kurchaba et al. https://doi.org/10.1016/j.rse.2024.114041
28. Using Multispectral Imaging to Reveal the Relationship between UV Absorbance and Sulphur Dioxide Concentration K. Lu et al. https://doi.org/10.3390/su15010138
29. Estimation of ship emission rates at a major shipping lane by long-path DOAS measurements K. Krause et al. https://doi.org/10.5194/amt-14-5791-2021
30. Remote detection sulfur content in fuel oil used by ships in emission control areas: A case study of the Yantian model in Shenzhen X. Peng et al. https://doi.org/10.1016/j.oceaneng.2021.109652
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33. An intercomparison of aircraft sulfur dioxide measurements in clean and polluted marine environments L. Temple et al. https://doi.org/10.5194/amt-19-1165-2026
34. Surveillance of ship emissions and fuel sulfur content based on imaging detection and multi-task deep learning K. Cao et al. https://doi.org/10.1016/j.envpol.2021.117698
35. Current progress in developing a MARPOL Annex VI enforcement strategy in the Bonn Agreement through remote measurements W. Van Roy et al. https://doi.org/10.1016/j.marpol.2023.105882
36. Simultaneous measurement of SO2 and CO2 for sulfur content detection in marine diesel fuel using QCL absorption spectroscopy J. Li et al. https://doi.org/10.1016/j.measurement.2024.115861
37. UAV Inspection of Compliance of Fuel Sulfur Content of Sailing Ships in the Pearl River Delta, China J. Hu et al. https://doi.org/10.3390/atmos13111894
38. Characteristics of real-world ship energy consumption and emissions based on onboard testing A. Fan et al. https://doi.org/10.1016/j.marpolbul.2023.115411
39. Policy recommendations for international regulations addressing air pollution from ships W. Van Roy et al. https://doi.org/10.1016/j.marpol.2023.105913
40. A wide field-of-view imaging DOAS instrument for two-dimensional trace gas mapping from aircraft A. Schönhardt et al. https://doi.org/10.5194/amt-8-5113-2015
41. Emission measurements of alkenes, alkanes, SO2, and NO2from stationary sources in Southeast Texas over a 5 year period using SOF and mobile DOAS J. Johansson et al. https://doi.org/10.1002/2013JD020485
42. Field test of available methods to measure remotely SOx and NOx emissions from ships J. Balzani Lööv et al. https://doi.org/10.5194/amt-7-2597-2014
43. Experimental Flight Patterns Evaluation for a UAV-Based Air Pollutant Sensor J. Araujo et al. https://doi.org/10.3390/mi11080768
44. Research on Machine Vision Detection Method of Ship Sulfur Emission Based on Convolutional Neural Network Y. Han et al. https://doi.org/10.1088/1742-6596/2171/1/012071
45. A Real-Time Measurement-Modeling System for Ship Air Pollution Emission Factors F. Zhou et al. https://doi.org/10.3390/jmse10060760
46. Surveillance practice and automatic data algorithm of sniffing telemetry for SO2 emissions from ship exhaust in Tianjin Port Z. Qi et al. https://doi.org/10.1016/j.jclepro.2023.137225
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48. Research progress of monitoring technology of ship-source air pollutants in china emission control area M. Tianyu et al. https://doi.org/10.1051/e3sconf/202020602006
49. Aerosol sources in the western Mediterranean during summertime: a model-based approach M. Chrit et al. https://doi.org/10.5194/acp-18-9631-2018
50. High Time-resolution Characterization of PM2.5 Sulfate Measured in a Japanese Urban Site C. Ma et al. https://doi.org/10.5572/ajae.2015.9.4.280
51. Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker Amundsen from the Polar 6 aircraft platform A. Aliabadi et al. https://doi.org/10.5194/acp-16-7899-2016
52. A Study on Monitoring and Supervision of Ship Nitrogen-Oxide Emissions and Fuel-Sulfur-Content Compliance Z. Wang et al. https://doi.org/10.3390/atmos14010175
53. Evaluating methods for marine fuel sulfur content using microsensor sniffing systems on ocean-going vessels S. Yang et al. https://doi.org/10.1016/j.scitotenv.2024.173765
54. Prospect Theory based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation C. Lu et al. https://doi.org/10.32604/cmc.2020.012556
55. Real-Time Monitoring of SO2 Emissions Using a UV Camera with Built-in NO2 and Aerosol Corrections Y. Xiong et al. https://doi.org/10.3390/s22103900
56. Fast-hyperspectral imaging remote sensing: Emission quantification of NO2 and SO2 from marine vessels C. Xing et al. https://doi.org/10.1038/s41377-025-01922-x
57. High-resolution mapping of SO2 using airborne observations from the GeoTASO instrument during the KORUS-AQ field study: PCA-based vertical column retrievals H. Chong et al. https://doi.org/10.1016/j.rse.2020.111725
58. Sulfur dioxide vertical column DOAS retrievals from the Ozone Monitoring Instrument: Global observations and comparison to ground‐based and satellite data N. Theys et al. https://doi.org/10.1002/2014JD022657
59. The quantification of NOx and SO2 point source emission flux errors of mobile differential optical absorption spectroscopy on the basis of the Gaussian dispersion model: a simulation study Y. Huang et al. https://doi.org/10.5194/amt-13-6025-2020
60. Faster, Better, Cheaper: Solutions to the Atmospheric Shipping Emission Compliance and Attribution Conundrum T. Smyth et al. https://doi.org/10.3390/atmos14030500
61. High-resolution airborne imaging DOAS measurements of NO2 above Bucharest during AROMAT A. Meier et al. https://doi.org/10.5194/amt-10-1831-2017
62. Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution L. Johansson et al. https://doi.org/10.1016/j.atmosenv.2017.08.042
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64. Surveillance of SO2 and NO2 from ship emissions by MAX-DOAS measurements and the implications regarding fuel sulfur content compliance Y. Cheng et al. https://doi.org/10.5194/acp-19-13611-2019
65. Comparative analysis of ship exhaust gas monitoring methods Y. CHENG et al. https://doi.org/10.65658/j.hndk.2026010901
66. A comprehensive inventory of ship traffic exhaust emissions in the European sea areas in 2011 J. Jalkanen et al. https://doi.org/10.5194/acp-16-71-2016
67. Selection of onshore sites based on monitoring possibility evaluation of exhausts from individual ships for Yantian Port, China L. He et al. https://doi.org/10.1016/j.atmosenv.2021.118187
68. Remote sensing monitoring system for ship exhaust using infrared multispectral imaging W. Zhou et al. https://doi.org/10.1016/j.measurement.2025.116964
69. A Systematic Approach to Identify Shipping Emissions Using Spatio-Temporally Resolved TROPOMI Data J. Kim et al. https://doi.org/10.3390/rs15133453
70. Characteristics and temporal evolution of particulate emissions from a ship diesel engine L. Mueller et al. https://doi.org/10.1016/j.apenergy.2015.05.115
71. The Role of Belgian Airborne Sniffer Measurements in the MARPOL Annex VI Enforcement Chain W. Van Roy et al. https://doi.org/10.3390/atmos14040623
72. Scanning and mobile multi-axis DOAS measurements of SO2 and NO2 emissions from an electric power plant in Montevideo, Uruguay E. Frins et al. https://doi.org/10.1016/j.atmosenv.2014.03.069
73. A Comprehensive Inventory of the Ship Traffic Exhaust Emissions in the Baltic Sea from 2006 to 2009 J. Jalkanen et al. https://doi.org/10.1007/s13280-013-0389-3
74. Characterization of the particle emission from a ship operating at sea using an unmanned aerial vehicle T. Villa et al. https://doi.org/10.5194/amt-12-691-2019
75. The Study of Ship Exhaust Emission Monitoring System Based on UAV 晓. 于 https://doi.org/10.12677/DSC.2023.121001
76. Tropospheric NO2 measurements using a three-wavelength optical parametric oscillator differential absorption lidar J. Su et al. https://doi.org/10.5194/amt-14-4069-2021
77. Development of a spectrum-based ship fuel sulfur content real-time evaluation method H. Wu et al. https://doi.org/10.1016/j.marpolbul.2022.114484
78. Determination of NOx emission rates of inland ships from onshore measurements K. Krause et al. https://doi.org/10.5194/amt-16-1767-2023
79. Air Pollutant Emission Factors of Inland River Ships under Compliance F. Zhou et al. https://doi.org/10.3390/jmse12101732
80. Oil tanker emissions: Measurement, factors, and future scenarios S. Kose https://doi.org/10.1080/15568318.2024.2443819
81. Airborne emission measurements of SO2 , NOx and particles from individual ships using a sniffer technique J. Beecken et al. https://doi.org/10.5194/amt-7-1957-2014
82. On-board measurements of particle and gaseous emissions from a large cargo vessel at different operating conditions T. Chu-Van et al. https://doi.org/10.1016/j.envpol.2017.11.008
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87. Emission factors for gaseous and particulate pollutants from offshore diesel engine vessels in China F. Zhang et al. https://doi.org/10.5194/acp-16-6319-2016