Optimization models for reducing air emissions from ships

Abstract

This research deals with the reduction of air emissions from ships. Ships are large contributors to air pollution with implications for climate change and human health. Regulations have entered into force or will in the near future, which will force shipowners to reduce the air emissions from their vessels. Multiple technologies or operational measures reducing these main pollutants are available and the term air emission control has here been defined as any effort made by ship-owners, operators or designers to reduce the amount of emission to air from a vessel. Knowing which air emission control to install and when to do so to comply with regulations is a challenging decision problem.

This thesis develops optimization models for selecting air emission controls enabling a ship to comply with air emission regulations. This work consists of four papers. The first one establishes the air emission reduction problem in shipping and presents a deterministic optimization problem solving it. The three following papers are extensions of this model adding different aspects to the problem, respectively: Design phase, uncertainty and non-financial decision criteria.

The thesis aims to answer the four following research questions:

RQ1: Can the real-life problem of selecting air emission controls be efficiently captured in an optimization model?

RQ2: Which specific problem aspects that are not currently being taken into account, such as interaction effects, should be part of this model?

RQ3: Can uncertainty about the future be efficiently handled, and does it have a significant impact on the solution?

RQ4: What is the role of non-monetary aspects in the problem and how could they be integrated into the model?