Open Access Repository

Quantifying and controlling ship exhaust emissions and their impacts in the Australian region

Downloads

Downloads per month over past year

Goldsworthy, BL ORCID: 0000-0003-3984-334X 2019 , 'Quantifying and controlling ship exhaust emissions and their impacts in the Australian region', PhD thesis, University of Tasmania.

[img] PDF (Whole thesis)
Goldsworthy_who...pdf | Document not available for request/download
Full text restricted until 1 October 2021.

Abstract

Ship exhaust emissions contribute to air pollution that has adverse health impacts such as premature mortality, climate impacts and other environmental impacts such as acidification and eutrophication of waterways. Long-term exposure to fine particulate matter (PM2.5) is associated with premature mortality from cardiopulmonary disease and lung cancer. Short-term exposure is also associated with mortality and hospitalisation with cardiovascular and respiratory disease. Most of the fuel used by ocean going vessels in the Australian region is based on crude oil refining residue. This fuel has a high sulfur content, which increases PM2.5 emissions and contributes to secondary particle formation and growth. The combustion conditions in marine diesel engines result in high emissions of oxides of nitrogen, which are precursors for tropospheric ozone and photochemical smog that primarily affect air quality in summer. A high proportion of ship exhaust emissions occur in coastal areas, and ports are often located in coastal cities. A high proportion of the Australian population lives in close proximity to the coast.
Shipping provides a relatively low greenhouse gas option for transport of goods and is a major part of the Australian economy. However, ship exhaust emissions in the Australian region have not been comprehensively studied. There is limited knowledge about the exhaust emissions from ship engines and boilers in coastal regions and ports in Australia and the effects of these emissions on air quality in nearby urban regions. This issue is of growing significance because of the increased regulation of land-based emissions, the limited regulation of ship emissions and planned increases in shipping activity. Coastal and in-port ship emissions, when advected over land may cause deterioration in air quality. Further, the coastal emissions that can be subsequently advected over land are not generally considered in Australian studies, in spite of them being much larger than in-port emissions. This thesis uses a detailed modelling approach to make a comprehensive study of ship exhaust emissions in the Australian region. The modelled emissions are also used to assess ship-related health impacts and the potential benefits of control measures.
A model is developed to calculate ship exhaust emissions using activity data from the Automatic Identification System (AIS). The AIS data are combined with ship specific technical data to calculate exhaust emissions and fuel consumption for individual ships. The methodology allows ship exhaust emissions to be calculated at both large scales and fine resolutions. The model is applied to the Australian coast and Australian ports. Emissions and fuel consumption are calculated for 34 ports representing 99% of total cargo throughput, regions within 300 km of major population centres, the Great Barrier Reef Marine Park, the region nominally within 200 km of the coast, and the entire study region, which extends between 5°S to 45°S and 105°E to 160°E. Emissions are categorised by ship type, ship size, operating mode and machinery type. The model is evaluated using a detail approach that includes comparisons with independent data sources. Ship exhaust emissions are compared with emissions from other sources.
The ship emissions model is used to assess the mortality impact of ship-related PM2.5 in the greater Sydney region, and the benefits of two control scenarios that involve using 0.1% low-sulfur fuel. The two control scenarios involve using low-sulfur fuel at berth in the four major ports in the region, and using low-sulfur fuel within 300 km of Sydney. A comprehensive approach is used for impact assessment, involving detailed emission inventories and meteorological data, chemical transport modelling to calculate ship-related PM2.5 exposures, and health impact assessment based on the modelled population exposures. The analysis uses spatially gridded hourly ship exhaust emissions down to approximately 1 km × 1 km resolution. The results indicate that using 0.1% low-sulfur fuel within 300 km of Sydney would reduce the population weighted-mean concentration of ship-related PM2.5 by 56%, compared to a 25% reduction using low-sulfur fuel at berth only, and would provide more than twice the mortality benefit.
The ship emissions model is developed further to improve the treatment of regional gaps and short-term gaps in the AIS data. There are regional gaps in the coverage afforded by the network of ground stations that are used to collect the terrestrial AIS data. Calculating emissions for the gap regions involves generating interpolated ship tracks that span the gaps. A simple shortest path or straight-line interpolation works well where the coast has a concave shape through the gap region. This method does not work well where the coast has a convex shape, most notably between Brisbane and Newcastle on the east coast. The spatial distribution of the emissions in this gap region is considerably improved through steering interpolated ship tracks around land using a combination of visibility graphs and Dijkstra’s algorithm. The constructed paths are not constrained to pre-defined route networks. A geographical cluster analysis is first used to identify the boundary regions of the data gaps. It is also shown that emissions in this gap region contribute substantially to the total ship emissions within 300 km of Brisbane.
Further refinements to the model for calculating ship exhaust emissions are made to improve the scheme for estimating auxiliary power requirements. While physical models exist for estimating propulsive power requirements, similar models are not available for estimating auxiliary power requirements. Earlier approaches assumed that installed auxiliary engine power increased in proportion to installed main engine power. Auxiliary-to-main engine power ratios were specified by ship type, and load factors were specified by ship type and operating mode. Auxiliary boiler power was generally not differentiated by ship size. More recent approaches are based on extensive ship survey data, and give tables of auxiliary engine and auxiliary boiler power binned against ship type, ship size and operating mode. These surveys show that auxiliary power does not necessarily increase with ship size or main engine power. A revised approach based on the recent data sources is adopted and applied to a case study for the four major ports in Victoria. The revised approach is informed by results from a small local survey. Comparisons are made of the impact of the different approaches on the magnitude and spatial distribution of the emissions.
Hourly ship exhaust emissions are required because chemical transport processes are affected by diurnally varying meteorological conditions. The environment in which the emissions occur can also be affected by time varying emissions from other sources. Hourly emissions down to 1 km resolution are examined in greater detail for the region within 300 km of Sydney. These emissions are aggregated regionally and by vessel type to examine variability at different temporal resolutions. An analysis is made of the accuracy with which the hourly emissions are estimated using longer term emissions. These estimates use a spatial structure provided by the longer-term emissions, together with assumed temporal profiles. Spatial cell activity hours are analysed to explain large differences in the average spatial extent of the emissions at different temporal resolutions, the accuracy with which the hourly emission rates are estimated using longer term emissions, and the suitability of generalised temporal profiles to describe the emissions data. Regression analysis is used to model the spatial extent of the hourly and daily emissions.

Item Type: Thesis - PhD
Authors/Creators:Goldsworthy, BL
Keywords: Ship exhaust emissions, AIS activity data, Health impact assessment, Emission control measures, Ship routeing, Auxiliary power schemes, Gridded hourly emissions
Copyright Information:

Copyright 2019 the author

Additional Information:

Chapter 2 appears to be the equivalent of a post-print version of an article published as: Goldsworthy, L., Goldsworthy, B., 2015. Modelling of ship engine exhaust emissions in ports and extensive coastal waters based on terrestrial AIS data – an Australian case study. 2015. Environmental modelling & software. 63, 45-60

Chapter 3 appears to be the equivalent of a post-print version of an article published as: Broome, R. A., Cope, M. E., Goldsworthy, B., Goldsworthy, L., Emmerson, K., Jegasothy, E., Morgan, G. G., 2016. The mortality effect of ship-related fine particulate matter in the Sydney greater metropolitan region of NSW, Australia, Environment international 87, 85-93

Chapter 4 appears to be the equivalent of a post-print version of an article published as: Goldsworthy, B., 2017. Spatial and temporal allocation of ship exhaust emissions in Australian coastal waters using AIS data: analysis and treatment of data gaps, Atmospheric environment 163, 77-86

Chapter 5 appears to be the equivalent of a post-print version of an article published as: Goldsworthy, B., Goldsworthy, L., 2019. Assigning machinery power values for estimating ship exhaust emissions: comparison of auxiliary power schemes, Science of the total environment 657, 963-977

Chapter 6 appears to be the equivalent of a post-print version of an article published as: Goldsworthy, B., Enshaei, H., Jayasinghe, S., 2019. Comparison of large-scale ship exhaust emissions across multiple
resolutions: From annual to hourly data, Atmospheric environment, 214, 1-14

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP