Mengtao Deng , Shitao Peng , Jianbo Hu , Zhongru Wang , Xin Xie , Lin Jiang , Zhaoyu Qi
{"title":"航行船舶黑烟、黑烟智能检测及排放特征分析——以上海海域为例","authors":"Mengtao Deng , Shitao Peng , Jianbo Hu , Zhongru Wang , Xin Xie , Lin Jiang , Zhaoyu Qi","doi":"10.1016/j.ocecoaman.2025.107692","DOIUrl":null,"url":null,"abstract":"<div><div>Ship black smoke is a serious air pollution phenomenon, an important regulatory object for preventing and controlling ship air pollution. The traditional black smoke detection method is the Ringelmann smoke chart, which is highly subjective, has low detection accuracy, and is easily affected by environmental background and illumination variation. To solve the problems of the traditional Ringelmann smoke chart method, an intelligent ship black smoke intelligent tracking and detection algorithm is proposed, and an intelligent ship black smoke detection APP is developed. Secondly, 5224 cruising ships are monitored during the experiment, and 155 ships with black smoke are found. Then, the black smoke video of 155 ships was detected using the Ringelmann smoke chart method and the proposed method, respectively, and the experimental results demonstrate that the proposed method not only can reduce the influence of illumination variation and the differences in visual habits, but also has high detection accuracy. Moreover, the developed novel approach is a much more versatile method to be followed in general to efficiently and accurately check ship emissions for smoke blackness. Finally, a comprehensive analysis of the black smoke emission characteristics of ships in the waters of the Yangtze estuary was carried out. It was found that 0.15 % exceeded the Ringelmann blackness level of 2, providing a reference basis for the formulation of legal and regulatory documents.</div></div>","PeriodicalId":54698,"journal":{"name":"Ocean & Coastal Management","volume":"266 ","pages":"Article 107692"},"PeriodicalIF":4.8000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent detection and emission characteristics analysis of black smoke and blackness from navigating ships: A case study of Shanghai waters\",\"authors\":\"Mengtao Deng , Shitao Peng , Jianbo Hu , Zhongru Wang , Xin Xie , Lin Jiang , Zhaoyu Qi\",\"doi\":\"10.1016/j.ocecoaman.2025.107692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Ship black smoke is a serious air pollution phenomenon, an important regulatory object for preventing and controlling ship air pollution. The traditional black smoke detection method is the Ringelmann smoke chart, which is highly subjective, has low detection accuracy, and is easily affected by environmental background and illumination variation. To solve the problems of the traditional Ringelmann smoke chart method, an intelligent ship black smoke intelligent tracking and detection algorithm is proposed, and an intelligent ship black smoke detection APP is developed. Secondly, 5224 cruising ships are monitored during the experiment, and 155 ships with black smoke are found. Then, the black smoke video of 155 ships was detected using the Ringelmann smoke chart method and the proposed method, respectively, and the experimental results demonstrate that the proposed method not only can reduce the influence of illumination variation and the differences in visual habits, but also has high detection accuracy. Moreover, the developed novel approach is a much more versatile method to be followed in general to efficiently and accurately check ship emissions for smoke blackness. Finally, a comprehensive analysis of the black smoke emission characteristics of ships in the waters of the Yangtze estuary was carried out. It was found that 0.15 % exceeded the Ringelmann blackness level of 2, providing a reference basis for the formulation of legal and regulatory documents.</div></div>\",\"PeriodicalId\":54698,\"journal\":{\"name\":\"Ocean & Coastal Management\",\"volume\":\"266 \",\"pages\":\"Article 107692\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ocean & Coastal Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0964569125001541\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OCEANOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean & Coastal Management","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0964569125001541","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
Intelligent detection and emission characteristics analysis of black smoke and blackness from navigating ships: A case study of Shanghai waters
Ship black smoke is a serious air pollution phenomenon, an important regulatory object for preventing and controlling ship air pollution. The traditional black smoke detection method is the Ringelmann smoke chart, which is highly subjective, has low detection accuracy, and is easily affected by environmental background and illumination variation. To solve the problems of the traditional Ringelmann smoke chart method, an intelligent ship black smoke intelligent tracking and detection algorithm is proposed, and an intelligent ship black smoke detection APP is developed. Secondly, 5224 cruising ships are monitored during the experiment, and 155 ships with black smoke are found. Then, the black smoke video of 155 ships was detected using the Ringelmann smoke chart method and the proposed method, respectively, and the experimental results demonstrate that the proposed method not only can reduce the influence of illumination variation and the differences in visual habits, but also has high detection accuracy. Moreover, the developed novel approach is a much more versatile method to be followed in general to efficiently and accurately check ship emissions for smoke blackness. Finally, a comprehensive analysis of the black smoke emission characteristics of ships in the waters of the Yangtze estuary was carried out. It was found that 0.15 % exceeded the Ringelmann blackness level of 2, providing a reference basis for the formulation of legal and regulatory documents.
期刊介绍:
Ocean & Coastal Management is the leading international journal dedicated to the study of all aspects of ocean and coastal management from the global to local levels.
We publish rigorously peer-reviewed manuscripts from all disciplines, and inter-/trans-disciplinary and co-designed research, but all submissions must make clear the relevance to management and/or governance issues relevant to the sustainable development and conservation of oceans and coasts.
Comparative studies (from sub-national to trans-national cases, and other management / policy arenas) are encouraged, as are studies that critically assess current management practices and governance approaches. Submissions involving robust analysis, development of theory, and improvement of management practice are especially welcome.