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Analysis of the uncertainty of the AIS-based bottom-up approach for estimating ship emissions.
Chen, Xiaoyan; Yang, Jiaxuan.
Afiliación
  • Chen X; Navigation College, Dalian Maritime University, Dalian 116026, China; The Key Laboratory of Navigation Safety Guarantee, Liaoning Province, Dalian 116026, China.
  • Yang J; Navigation College, Dalian Maritime University, Dalian 116026, China; The Key Laboratory of Navigation Safety Guarantee, Liaoning Province, Dalian 116026, China. Electronic address: yangjiaxuan@dlmu.edu.cn.
Mar Pollut Bull ; 199: 115968, 2024 Feb.
Article en En | MEDLINE | ID: mdl-38181472
ABSTRACT
Although the AIS-based bottom-up approach has become the dominant method for estimating ship emissions, there are still inherent uncertainties due to the numerous complex factors involved. This paper aims to investigate the development process of the AIS-based bottom-up approach and identify the primary sources of uncertainty by conducting a systematic review of 29 articles published since 2015. The result shows three sources of uncertainty for estimating ship emissions, i.e., the acquisition and processing of AIS data, ship characteristic information and engine load calculation, and the determination of emission factors. This paper suggests that the accuracy of ship emission inventories can be improved by enhancing the reliability of datasets, uniformly defining engine load calculation formulas, and making more extensive measurements of local emissions to provide substantial support for ship emissions management and facilitate the development of more effective emission reduction strategies.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Mar Pollut Bull Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Mar Pollut Bull Año: 2024 Tipo del documento: Article País de afiliación: China