Annex 4 analytical methods

model description

general description

acronym: DIONE

name: Road Transport Fleet Impact Model

main purpose: DIONE can support road transport related policies by assessing the implications of future road vehicle fleet composition and drive patterns on energy consumption, emissions and total costs of ownership.

homepage: —

Developer and its nature

ownership: Co-ownership (EU & third parties)

ownership additional info: Code based on 3rd party

is the model code open-source?: NO

Model structure and approach with any key assumptions, limitations and simplifications

details on model structure and approach

The DIONE model uses a modular structure which allows to add new functionalities as more data becomes available and as policy needs arise. Model development originally started with the DIONE fleet impact model, which is used to calculate road transport fuel and energy consumption and emissions for future fleet development scenarios. The model presently consists of the following modules, which can be used either standalone or in combinations, and cover a broad range of road vehicles (cars, vans, trucks):

DIONE Fleet Impact Model
DIONE COPERT module (under development)
DIONE Cost Curve Module
DIONE Cross-Optimization Module
DIONE Fuel and Energy Cost Module
DIONE TCO and Payback Module

model inputs

Parametrisation: The DIONE fleet impact model contains a calibrated stock baseline which is consistent with the country-specific stock and activity data collected in the project TRACCS, and is taken forward following the trends of PRIMES 2012 baseline scenario with adopted measures.

Fuel consumption and emission calculation for combustion engine vehicles is based on COPERT 4 v.11 road transport emission inventory software. For alternative fuel vehicles, an energy and emission calculation methodology has been developed which takes account of vehicle characteristics, trip lengths and speed distributions.

Inputs:

Main variables that can be defined by the user include:

vehicle stock,
new registrations,
survival rates,
activity,
efficiency improvement,
fuel use of flex-fuel vehicles,
fuel pathways for well-to-wheel energy consumption and emissions,
biofuel admixture shares for conventional fuels,
driving patterns.

Users can define custom scenarios either by adapting baseline values in the DIONE input tables or graphical user interface graphs, or by uploading input files. The user can decide to create a scenario for any predefined entity, i.e., any single EU member state (plus some extra neighbour countries), pre-defined groupings such as EU28, EU15 and EU12, but can also decide to define a custom scenario for any region, city, country or other entity of interest.

The DIONE Cost Curve Module uses data on vehicle efficiency improvement technologies (their efficiencies, costs and compatibilities) as additional inputs, whereas the DIONE Fuel and Energy Cost Module needs to be fed with energy price estimates. For Cross-Optimization and TCO/Payback Calculations, Fleet Composition scenarios can be aligned with DIONE fleet impact model runs or provided from other sources.

model outputs

The output of the DIONE fleet impact model contains fleet development and activity, energy demand, CO2 emissions, other GHGs and all air pollutants included in the COPERT methodology.

For both energy consumption and greenhouse gas (GHG) emissions, DIONE can provide real world tank-to-wheel (TtW) figures up to the year 2050 as well as well-to-wheel (WtW) results up to 2030. For CO2 emissions, NEDC type approval values can be calculated, as well. DIONE also includes a cost module which determines additional costs for achieving given efficiency targets for conventional passenger cars.

DIONE can be used for policy-relevant scenario analysis, including analysis of the following options:

Fuel efficiency targets
Technology replacement, Stock composition or new registration technology share targets
Biofuel Admixture
Fuel GHG intensities
Scrappage Schemes
Vehicle Activity

The further modules provide additional outputs such as

Cost-optimal segment and powertrain-specific CO2 reductions and related costs
Fuel and energy costs of vehicle types and fleets
Total costs of ownership for vehicles within a given scenario,
Payback times for efficiency technology

Intended field of application

policy role

The model is employed to provide policy support in the context of decarbonisation and electrification of road transport, as well as for assessing possible transitions towards alternative fuels for road transport in general.

It has been used in support of the Impact Assessment for post-2020 emissions standards for cars and vans (2017) supporting DG CLIMA, for the Assessment of National Framework Plans under the Alternative Fuels Infrastructure Directive (2017) supporting DG MOVE, and for the support of the Impact Assessment on fuel efficiency standards for heavy-duty vehicles (2018) supporting DG CLIMA. Previously, it has been employed to prepare scenarios as an input for the EC Communication on decarbonising the transport sector. Furthermore, it was recently used to calculate road transport energy consumptions for a 2050 scenario study within the ERTRAC CO2 working group. Further work is under way to soft-link DIONE emission calculation and cost curves with JRC's POTEnCIA model and employ it for scenario analysis on behalf of DG MOVE.

It can also be used to assess scenarios on the electrification of transport in line with the Energy Union strategy, to analyse possible transport sector measures for implementing a new effort sharing decision, as well as for reaching the Transport White Paper carbon emission reduction and conventional vehicle phase-out goals.

policy areas

Climate action
Energy
Environment
Transport

Model transparency and quality assurance

Are uncertainties accounted for in your simulations?: NO - Most of the DIONE modules are deterministic, such that uncertainties relate mainly to the quality of input data, which is hard to quantify and quality checks of which remain with data providers. The DIONE Cost Curve Model uses random and probabilistic elements in the exploration process for determining optimal technology packages, which according to internal test have very little impact on the final cost curves.

Has the model undergone sensitivity analysis?: YES - Sensitivities of model results have been explored before making use of the model, and by verifying the response of model outcomes to the variation of input parameters during intensive scenario calculation.

Has the model been published in peer review articles?: YES

Has the model formally undergone scientific review by a panel of international experts?: NO

Has model validation been done? Have model predictions been confronted with observed data (ex-post)?: NO - Model projections regard future years and cannot yet be confronted with observed data.

To what extent do input data come from publicly available sources?: Based on both publicly available and restricted-access sources

Is the full model database as such available to external users?: NO - Most modules rely extensively on publicly available data. Input data used for the Cost Curves and total costs of ownership calculations is referenced in the respective JRC reports.

Have model results been presented in publicly available reports?: YES

Have output datasets been made publicly available?: NO - Some fleet model outputs are summarized in papers; all final JRC cost curves as well as exemplary total cost of ownership (TCO) results are specified in the respective JRC reports; central TCO results have been included in the impact assessments for CO2 standards for LDV and HDV.

Is there any user friendly interface presenting model results that is accessible to the public?: NO

Has the model been documented in a publicly available dedicated report or a manual?: YES - The cost curve model, cross-optimization module and TCO module documentation have been published in two JRC reports (for LDV and HDV respectively). For the fleet impact model, an updated model version is under development, publication of the model documentation outstanding.

Intellectual property rights

Licence type: Non-Free Software licence

application to the impact assessment

Please note that in the annex 4 of the impact assessment report, the general description of the model (available in MIDAS) has to be complemented with the specific information on how the model has been applied in the impact assessment.

See Better Regulation Toolbox, tool #11 Format of the impact assessment report).