Result | LCPA-Tool

Objective

The objective of the LCPA-Tool is to support a comprehensive decision making process for design alternatives in the early design stage using a sustainability approach. This includes the following categories:

  1. The economic viability of design alternatives will be assessed using the net present value (NPV) concept as key performance indictor.
  2. The environmental impact from construction, operating and recycling of different ship designs will be evaluated using the global warming potential (GWP). The acidification potential (AP), the eutrophication potential (EP) and the release of particulate matter (PM 10) act as key performance indicators during ship operation.
  3. The use of resources will be attributed using the cumulative energy demand (CED) as key performance indicator. This applies for the well to tank approach for fuels, the use of relevant materials for production and energy consumption on the shipyard for building and operating of the ship. This approach ensures that all energy consumption (including their related GHG-emissions) related for production of the fuels, relevant materials and on shipyard is considered.

    To increase the transparency of the cumulated energy demand, a split of fossil energy resources and renewable energy resource is preferred but could not be implemented in the current version of the LCPA-Tool. In case of renewable bio-mass as feedstock for production of energy carriers, the land use as a resource is of significant influence but could also not be implemented due the same reason.

  4. The societal impact of emissions from burning of fossil fuels is well documented and commonly known as external costs (ExterneE, NEEDS, UBA). In order to be able to internalize the effect of these external costs in the LCPA-Tool, corresponding assumptions have been made for these external costs and can optionally be linked to the Net Present Value.

The LCPA-Tool will finally be used to assess the 2025 and 2050 designs as developed by the application cases against the baseline designs. From the progress made so far it can be stated that the quantitative prediction of values for KPIs as introduced is very much depending on ship type, operational profile, use of future alternative fuels, technology used and fuel price projections. In particular, trade-offs between the individual KPIs are expected and can be presented in a transparent way. Thus, the objective of the LCPA-Tool will support the decision making process for design alternatives as requested for the JOULES project on an increased rational basis using important sustainability aspects.

Scientific Approach

A complete Life Cycle Assessment according to ISO 14040 is very time-consuming and many data are not available in the early design phase. In order to overcome this issue, a screening LCA can be used, which is less accurate than a full LCA and uses a limited set of data and indicators. It is typically used for quick decision making for comparing of design alternatives and will thus be adapted in the early design process.

Using this approach, the Cumulated Energy Demand (CED) and Global Warming Potential (GWP) can be calculated in early design stage covering the life cycle from cradle to grave.

The elements contributing to these leading KPIs during the production phase have been identified to be energy use from production of the ship at the shipyard. This use of energy can be related to GHG-emissions as soon as the sources of energy are known and how the energy is produced. The other elements are production emissions, energy consumption for relevant materials used in ship components and the impact of the use of new materials in components can then be addressed in the GWP.

During the operating phase, GHG-emission from burning of fuels as well as the impact of fuel production from well to tank will be considered and corresponding information is stored in the LCA database.

The CED and GWP from scrapping / recycling is very hard to be achieved and was not further considered at this stage of the tool development with the exemption that typical recycling rates in the LCA information for materials are considered (provided, recycling rates are known).

Data Handling in LCPA Tool

The overall architecture of the data handling as needed for the LCPA-Tool is shown in the figure below. It will be possible to assess and compare the economic and environmental impact of any design variation to support the decision process for the best possible solution in a holistic way. It thus combines Life Cycle Assessment (LCA) aspects and Life Cycle Costing (LCC) in one single tool.

The main elements are:

  • Simulation component Database as developed in the JOULES project
  • Simulation of baseline vessel and 2025 / 2050 design in yards simulation environment
  • Transfer of simulation results to LCPA-Tool via SIFF-File (Simulation Interface Format File)
  • LCA Database containing all data necessary for environmental assessment from cradle to grave
  • Global Values with cost information of fuels, consumables, external costs
  • The LCPA-Tool
  • The presentation of KPIs in order to be able to assess the 2025 / 2050 design against the baseline design

The LCPA-Tool can also be used as a stand-alone tool without using the SIFF-File as input from simulation results.

Example

Comparison of three different designs, qualitative representation as spider graph:

The 2025 design has some improvements (e.g. drop-in BTL-fuel) with respect to Global Warming Potential (GWP), Acidification Potential (AP), Eutrophication Potential (EP) and Particulate Matter (PM) at slightly worse Net Present Value (NPV). The overall cumulated energy demand (incl. well to tank fraction for fuel production) is approx. the same as for the baseline vessel.

The 2050 design offers a large potential in reduction of all kind of emissions (incl. GWP in particular) at the expense of much higher cumulated energy demand and worse Net Present Value. A full electric ship using fuel cells with supply of energy from renewable sources is behind this ecological design concept and perfectly shows the trade-off between emission reduction and resource efficiency resp. costs.