Energy and fleet modelling within the TRIMODE integrated transport model framework for Europe

Siskos, Pelopidas; Capros, Pantélis; Zazias, Georgios; Fiorello, Davide; Nökel, Klaus

doi:10.1016/j.trpro.2018.12.205

Cited by 7 publications

(8 citation statements)

References 3 publications

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“…In multi-country analyses of future fleet compositions it is essential to model country-specific survival rates and cross-border flows of im-/exported cars. The two most prominent models to assess the impact of potential CO 2 reduction policies for the European transport sector are PRIMES-TREMOVE [ 25 – 27 ] and TRIMODE [ 28 , 29 ], which are used by the European Commission. However, even PRIMES-TREMOVE does not apply country-specific survival rates, but is “based on data provided for Germany, due to the lack of suitable information for the rest of the countries” [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Lifespans of passenger cars in Europe: empirical modelling of fleet turnover dynamics

Held

Rosat

Georges

et al. 2021

Eur. Transp. Res. Rev.

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Cars have a high share of global transport-related CO2 emissions. To model the market diffusion of new energy carriers and powertrains like electric vehicles, fleet turnover models are commonly used. A decisive influence factor for the substitution dynamics of such transformations is the survival rate of the national car fleet of a country. It represents the likelihood of a car reaching a certain lifespan. Due to a lack of data, current methods to estimate such survival probabilities neglect the imports and exports of used cars. Existing studies are limited to countries with a predominant market of new cars, compared to low numbers of imported and exported used cars. In this study, we resolve this marked simplification and propose a new method to estimate survival probabilities for countries with a high number of imported and exported used cars. Empirical data on the car stock, on inflows of new and used cars, and on outflows of exported and scrapped cars are gathered from 71 national statistics offices. Survival rates of the car fleets of 31 European countries are derived, for which we find a pronounced regional variability. Average lifespans of cars vary from 8.0 to 35.1 years, with a mean of 18.1 years in Western and 28.4 years in Eastern European countries, revealing the high impact of cross-border flows of cars. The study also shows that survival rate estimates can be improved significantly even in the absence of reliable data if a combination of a Weibull and a Gaussian distribution is used. It is likely that the predictive power of existing models (regarding the future environmental impact of car fleets) could be improved significantly if these findings were considered accordingly. The findings of this study can directly be included in fleet turnover and policy assessment models. They also enable the analysis of economic and environmental spillover effects from the imports and exports of used cars between countries.

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Section: Introductionmentioning

confidence: 99%

Lifespans of passenger cars in Europe: empirical modelling of fleet turnover dynamics

Held

Rosat

Georges

et al. 2021

Eur. Transp. Res. Rev.

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“…Within the Renewability modeling framework, this is achieved by means of exogenous assumptions [52]. Siskos et al take into account different speed bands, as depicted in Figure 7 [53]. The overall fuel consumption is determined by activity shares for these defined speed bands, and the corresponding specific fuel consumption values.…”

Section: Fuel Shiftmentioning

confidence: 99%

“…These categories can be defined based on various socio-economic parameters. Brooker et al [60] and Siskos et al [53] use income as a classification criterion. Meanwhile, Manley et al classify according to buyers' housing types [61].…”

Section: Belmonte Et Al Weight Different Artemis Drive Cycles Dependi...mentioning

confidence: 99%

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Mobility Trends in Transport Sector Modeling

Kraus

Grube

Stolten

2022

Future Transportation

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Transport sector models help provide strategic information for the future development of the transportation sector. Such long-term scenarios are typically challenged by uncertainties. Moreover, certain trends, such as the transition to zero-emission transportation systems and modal shifts, as well as connected, shared and autonomous vehicles, are already apparent today. Therefore, this paper investigates the impact of these trends on greenhouse gas emissions, as well as their implementation in transport sector modeling thus far. The investigations are structured into the four main parts of transport sector greenhouse gas emission calculation: activity, modal share, energy intensity and fuel carbon intensity. Our analysis of the related effects reveals their importance to the transportation sector of the future. Current models and scenarios widely consider trends such as the modal shift and electrification. However, other trends such as the sharing economy and automated driving are not commonly regarded in the context of transport sector modeling. The coupling of the different types of models and collaboration among researchers from the different fields is recommended for filling this gap.

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“…The regional granularity of the results enables the analysis and assessment of policy action at a regional level, rather than on a generalized national level and, hence, allows for the reassessment of policies to better account for the differences between regions. Several previous studies have simulated the market uptake of alternative fuel vehicles; however, demographic regional features are often not accounted for [7]. One study calculated the Beijing market penetration rate using a nested multinomial logit model for the choice between vehicle segments and technologies.…”

Section: Introductionmentioning

confidence: 99%

Electromobility Prospects in Greece by 2030: A Regional Perspective on Strategic Policy Analysis

Shaban,

Siskos,

Tjortjis

2023

Energies

Self Cite

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Electromobility represents a strong option for reducing carbon emissions in the road transport sector. This study presents a methodology and a simulation tool that project the evolution of the market share of electric vehicles (EVs) in the new car market. The analysis adopts a stylized regional resolution, which accounts for attributes on the NUTS-2 level, such as the population density, GDP/capita, education levels, and current EV charger distribution, to simulate the uptake of BEVs in different regions. The methodology applies discrete choice modelling techniques, considering tangible and intangible factors, including purchasing and operation costs, an estimated cost for range anxiety and public charging, and a market maturity index. The analysis is based on four different scenarios, referring to the updated Greek National Energy Climate Plan. The results reveal that regions with a higher average income, GDP/capita, and population density show a higher uptake of EVs. Overall, the tool implements a method of simulating the market evolution of EVs up to 2030 in reference to regional parameters and, hence, highlights the regions that require the most attention in order to achieve national targets. The results can inform policymakers in developing tailored strategies and financial support to accelerate the adoption of BEVs, particularly in regions where their uptake prospects are lower.

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Energy and fleet modelling within the TRIMODE integrated transport model framework for Europe

Cited by 7 publications

References 3 publications

Lifespans of passenger cars in Europe: empirical modelling of fleet turnover dynamics

Lifespans of passenger cars in Europe: empirical modelling of fleet turnover dynamics

Mobility Trends in Transport Sector Modeling

Electromobility Prospects in Greece by 2030: A Regional Perspective on Strategic Policy Analysis

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