DIONE
Source: Commission modelling inventory and knowledge management system (MIDAS)
Date of Report Generation: Wed Mar 19 2025
Dissemination: Public
© European Union, 2025
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Overview
Acronym
DIONE
Full title
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.
Summary
The DIONE Fleet Impact Model is used to assess the impacts of changes in the European and MS road transport fleet characteristics up to the year 2050. It is a flexible tool which can be employed to analyse scenarios on road vehicle stock development and composition, vehicle activity and driving patterns, and vehicle technology and fuel use trends. The model contains a calibrated 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 a PRIMES baseline scenario. Fuel consumption and emission calculation for combustion engine vehicles is based on COPERT methodology. For alternative fuel vehicles, an energy and emission calculation methodology has been developed which takes account of vehicle characteristics, trip lengths and speed distributions. For both energy consumption and greenhouse gas (GHG) emissions, DIONE can provide real world Tank-to-Wheel (TtW) up to the year 2050 as well as Well-to-Wheel (WtW) results up to 2030.
The DIONE cost curve model is employed for developing cost curves which describe the costs associated with reaching a given CO2 standard, for a given vehicle segment and powertrain. Cost curves are constructed by identifying cost-optimal bundles of technologies for CO2 reduction and then fitting a continuous cost curve.
The DIONE Cross-optimization module identifies cost-optimal strategies to reach given emission targets, building on the cost curves. Cross-optimization outcomes can be used to assess the impact of different policy options on manufacturing costs for different manufacturers and the market as a whole.
The DIONE Total Cost of Ownership Module computes total costs of ownership for different vehicle types and powertrains, summarizing the results from the previous steps and adding fuel/energy costs and maintenance costs. This allows assessing the societal costs associated with a policy option, as well as costs for consumers (new vehicle buyers and second-hand vehicle buyers).
DIONE can be used for ex-ante policy support. All DIONE modules are 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.
Model categories
Transport
Model keywords
transport modelroad transportscenario analysiselectromobilityCO2 emissionsalternative fuelsenergy consumptionair pollutant emissionsCost CurveTotal Costs of Ownership
Model homepage
Ownership and Licence
Ownership
Co-ownership (EU & third parties)
Ownership details
Licence type
Non-Free Software licence
The license has one or more of the following restrictions: it prohibits creation of derivative works; it prohibits commercial use; it obliges to share the licensed or derivative works on the same conditions.
Details
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
Input and parametrization
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.
Main output
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
Spatial & Temporal extent
The output has the following spatial-temporal resolution and extent:
| Parameter | Description |
|---|---|
| Spatial extent / country coverage | EU Member states 27 |
| Spatial resolution | World-regions (supranational)National |
| Temporal extent | Medium-term (5 to 15 years)Long-term (more than 15 years) |
| 2010-2050 | |
| Temporal resolution | Years |
Quality & Transparency
Quality
Model uncertainties
Models are by definition affected by uncertainties (in input data, input parameters, scenario definitions, etc.). Have the model uncertainties been quantified? Are uncertainties accounted for in your simulations?
- response
- no
- details
- 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.
- url
Sensitivity analysis
Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?
- response
- yes
- details
- 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.
- url
Have model results been published in peer-reviewed articles?
- response
- yes
- details
- url
Has the model formally undergone scientific review by a panel of international experts?
Please note that this does not refer to the cases when model results were validated by stakeholders.
- response
- no
- details
- url
Model validation
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
- response
- no
- details
- Model projections regard future years and cannot yet be confronted with observed data.
- url
Transparency
To what extent do input data come from publicly available sources?
This may include sources accessible upon subscription and/or payment
- response
- Based on both publicly available and restricted-access sources
Is the full model database as such available to external users?
Whether or not it implies a specific procedure or a fee
- response
- no
- details
- 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.
- url
Have model results been presented in publicly available reports?
Note this excludes IA reports.
- response
- yes
- details
- documents
For details please refer to the 'peer review for model validation' documents in the bibliographic references
Have output datasets been made publicly available?
Note this could also imply a specific procedure or a fee.
- response
- no
- details
- 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.
- url
Is there any user friendly interface presenting model results that is accessible to the public?
For instance: Dashboard, interactive interfaces...
- response
- no
- details
- url
Has the model been documented in a publicly available dedicated report or a manual?
Note this excludes IA reports.
- response
- yes
- details
- 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.
Is there a dedicated public website where information about the model is provided?
- response
- no
- details
- url
Is the model code open-source?
- response
- no
- details
Can the code be accessed upon request?
- response
- no
- details
The model’s policy relevance and intended role in the policy cycle
The model is designed to contribute to the following policy areas
- Climate action
- Energy
- Environment
- Transport
The model is designed to contribute to the following phases of the policy cycle
- Anticipation – such as foresight and horizon scanning
- Formulation – such as ex-ante Impact Assessments
The model’s potential
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.
Previous use of the model in ex-ante impact assessments of the European Commission
Use of the model in ex-ante impact assessments since July 2017.
2023SWD/2023/88 final
Impact Assessment Part 1 Accompanying the document Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL amending Regulation (EU) 2019/1242 as regards strengthening the CO₂ emission performance standards for new heavy-duty vehicles and integrating reporting obligations, and repealing Regulation (EU) 2018/956
- Lead by
- CLIMA
- Run by
- European Commission
- Contribution role
- baseline and assessment of policy options
- Contribution details
The model helped to assess the following impacts:
- Emission of greenhouse gases
- Vehicle emissions
- Additional costs on businesses
2021SWD/2021/613 final
Impact assessment accompanying the document Proposal for a Regulation of the European Parliament and of the Council: amending Regulation (EU) 2019/631 as regards strengthening the CO2 emission performance standards for new passenger cars and new light commercial vehicles in line with the Union's increased climate ambition
- Lead by
- CLIMA
- Run by
- European Commission
- Contribution role
- baseline and assessment of policy options
- Contribution details
DIONE is used to assess economic impacts of different CO2 emission standards for vehicles levels.
2018SWD/2018/185 final
Impact assessment accompanying the document Proposal for a Regulation of the European Parliament and of the Council: setting CO2 emission performance standards for new heavy duty vehicles
- Lead by
- CLIMA
- Run by
- European Commission
- Contribution role
- baseline and assessment of policy options (indirect)
- Contribution details
- Documented in study :
Refer to Study: Heavy duty vehicle CO2 emission reduction cost curves and cost assessment – enhancement of the DIONE model
2017SWD/2017/0650 final
Impact assessment accompanying the document Proposal for a Regulation of the European Parliament and of the Council: setting emission performance standards for new passenger cars and for new light commercial vehicles as part of the Union's integrated approach to reduce CO2 emissions from light-duty vehicles and amending Regulation (EC) No 715/2007 (recast)
- Lead by
- CLIMA
- Run by
- European Commission
- Contribution role
- baseline and assessment of policy options (indirect)
- Contribution details
- Documented in study :
Refer to Study: Light duty vehicle CO2 emission reduction cost curves and cost assessment