Atmospheric ship emissions in ports: A review. Correlation with data of ship traffic
Ports represent a source of atmospheric pollutants that can contribute significantly to jeopardise air quality of port cities. NOx, SOx, PM and VOCs (Volatile Organic Compounds) are emitted by ships during manoeuvring in ports at arrival or departure and during hotelling when moored at wharves. Seve...
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Published in: | Atmospheric Environment: X Vol. 4; p. 100050 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-10-2019
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | Ports represent a source of atmospheric pollutants that can contribute significantly to jeopardise air quality of port cities. NOx, SOx, PM and VOCs (Volatile Organic Compounds) are emitted by ships during manoeuvring in ports at arrival or departure and during hotelling when moored at wharves. Several methods exist to estimate emissions in function of ships’ activity and engine parameters. However, there is still a significant uncertainty in these calculations. This is a severe limitation to develop effective plans of mitigation of air pollution in port cities. In this paper data of NOx and PM10 emitted in port and traffic of passenger and commercial ships have been reviewed and critically analysed. All vessels are lumped into three categories: cruise, passenger ships other than cruise and commercial ships. Emissions have been correlated with traffic data per year: passengers, hours at hotelling and manoeuvring, calls and tons of goods transported. The result is a summary of regression equations that can be used for the estimation of ship emissions in ports based on traffic data. The analysis does not consider emissions of all the ancillary activities that take place at land inside a port like: upload and download of goods, vehicular traffic, manipulation of containers and others.
•PM10 and NOx ship emissions in ports are correlated with transport data.•Uncertainty of correlations are generally in the range 25%–50%.•The cruise ships' category shows the best correlation with transport data.•Lowest correlation is observed for “other than cruise ships” category.•A satisfactory correlation is observed for commercial ships. |
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ISSN: | 2590-1621 2590-1621 |
DOI: | 10.1016/j.aeaoa.2019.100050 |