Responsible for CO2 emissions of the order of 1 Gt, about 2-3 % of the global total, the shipping sector is part of the challenge to reduce emissions, in order to avoid dangerous climate change. Aiming to inform the sector's response to the challenge, this research addresses two knowledge gaps.Current methods of estimating carbon emissions from shipping are subject to large uncertainties and lacking with respect to a set of greenhouse gas accounting criteria. Based on Automatic Identification System (AIS) data, a new methodology is developed to monitor fuel consumption and ensuing carbon emissions around the globe. Results from applying the method to a sample fleet of 13 vessels and validating it against fuel consumption records covering a time interval of one year demonstrate that, for the first time, estimating shipping emissions from individual ship AIS movement data has become possible at the global scale.Lacking information on the performance of carbon abatement technologies is the second knowledge gap. Due to its geographical and temporal variability, wind power technology is particularly dependent on a transparent assessment to exploit its carbon saving potential as a freely available and renewable energy source. Numerical performance models of two wind power technologies - a Flettner rotor and a towing kite - are combined with wind velocity data from a weather model to calculate their propulsive power contribution. Average results along five analysed sample routes range between 0.3 MW and 1.0 MW for a single Flettner rotor andbetween 0.1 MW and 0.9 MW for the modelled towing kite.Both methodologies are ready for further use. Applying the AIS-based method to data covering the world fleet may provide a concise, up-to-date view of greenhouse gas emissions from shipping when and where they take place. The wind power technology model can be applied to any shipping route around the world. Next steps towards fully exploring and optimising the potential of wind power technology are outlined. A better understanding of greenhouse gas emissions from shipping and of mitigation options gained from applying the models may, in turn, contribute to the sector's successful response to the climate change challenge.
|Date of Award||1 Aug 2014|
- The University of Manchester
|Supervisor||Alice Larkin (Supervisor) & Ruth Wood (Supervisor)|