Intelligent detection and emission characteristics analysis of black smoke and blackness from navigating ships: A case study of Shanghai waters

Abstract

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.