Rijkswaterstaat gebruikt het goederenvervoermodel BasGoed om lange termijn prognoses te maken van het goederenvervoer. Economische verwachtingen spelen hierbij een belangrijke rol. Het model BasGoed begint dan ook met een module waarin de economische groei bepaald wordt en vervolgens vertaald wordt naar de hoeveelheid vervoerde goederen. De vorige versie van de economie module was verouderd. Deze paper beschrijft de nieuw ontwikkelde module op basis van multiregionale input-output analyses, aansluitend bij de manier waarop het Planbureau voor de leefomgeving economische analyses maakt. De werking van de module wordt toegelicht, en de eerste resultaten worden vergeleken met de uitkomsten van de oude module.@en

In 2020 hebben Rijkswaterstaat en ProRail in opdracht van het Nederlandse Ministerie van Infrastructuur en Waterstaat de ReferentiePrognose Goederenvervoer 2021 (kort: RPGV2021) laten uitvoeren. In deze paper geven we een korte toelichting over het model BasGoed in het algemeen en het project RPGV2021 specifiek. Het vernieuwing van het model BasGoed bevat onder ander een meer gedetailleerde kostenfunctie waarmee de transportkosten wordt berekend, de implementatie van een nieuwe containerketenmodule en de inclusie van een nieuw energiescenario. Om de werking van deze vernieuwing te analyseren, wordt in deze paper de plausibiliteit van de modelelasticiteiten getoetst. Verder vergelijken we de modeluitkomsten voor een prognose voor het jaar 2018 met realisatiecijfers. Deze vergelijking laat zien dat het weggoederenvervoer inclusief bestelauto op hetzelfde niveau uitkomt als de realisatie, maar dat op een gedetailleerder niveau de verdeling over de voertuigtypen afwijkt. In het algemeen geven de analyseresultaten vertrouwen in de resultaten uit de RPGV2021, welke in hoofdlijn in dit paper worden omschreven en visualiseert.@en

In 2017, the newly installed Dutch government announced in its coalition agreement to introduce a distancebased heavy goods vehicle charge, similar to the charges levied in other European countries. To study the possible transport impacts, we applied available models and methods in preparation for the introduction of this truck charge in the Netherlands in 2023, in order to present decision information to the government on different aspects of the charge. In this paper we present the analysis of different implementation scenarios for a distancebased truck charge. Different behavioural responses can be expected in terms of freight transport demand, mode choice, logistic efficiency, and route choice. Many studies however lack sufficient detail to properly describe the
impact of road charges for HGV on OD flows and freight traffic. In our contribution we explore the bandwidth of impacts of different pricing schemes, using strategic transport models for freight demand and traffic assignment,
with detailed modal split and route choice models, ensuring a proper representation of generalsed transport costs. We explain how we use available transport models in an overarching analytical framework to make a
comprehensive impact assessment of the different responses, and to decompose the impacts on the different responses. Final impacts are quantified in terms of freight demand (spatial pattern of transport flows), modal split and traffic flows (route choice, and congestion).
Depending on the pricing scenario the tonne kilometres decrease by 0.4%–4.8% on average. The modal shift impacts are stronger on longer transport distances: this is explained both by the larger impact of a distance-based charge on these routes, and by higher substitution possibilities to barge or rail. The results indicate that the overall impacts of the introduction of the different charging alternatives are moderate. However, the network impacts at local level can be substantial due to the impact of re-routing of truck trips to avoid charge.@en

A transition from the use of conventional energy carriers to more sustainable alternatives is an important policy objective to mitigate the impact of our energy consumption on earth’s climate. This transition involves changes in the use of commodities in freight transport. This paper addresses how we improved the strategic freight transport model BasGoed for the Netherlands to better forecast the impact of energy transition scenarios on freight transport demand. BasGoed is developed as a tool for supporting policy decisions and produces forecasts for road, rail, barge and sea shipping. These forecasts are inputs for sectoral models of road, rail and barge transport. Energy carriers such as coal, lignite, crude oil and fossil fuels make up for a substantial part of all freight transport in the Netherlands. The increase or decline in transport demand for these commodities is closely correlated to the speed of the energy transition. The uncertainty in future growth levels of energy carriers is one of the larger uncertainties in forecasting future freight demands, especially for rail and barge transport because of high market-shares for energy carriers. In De Bok et al. (2018a) a broad range of sensitivity runs for BasGoed is presented. The results showed that the assumptions in the energy transition scenario have the biggest impact on forecasted freight transport demand. The strategic transport model BasGoed has been improved to better capture the outcomes of the energy transition to be able to assess policy measures related to reducing CO2 emissions. The global mix of energy carriers in energy production are our starting point in the input scenario. These global targets are translated into changes in economic structure (production and consumption of commodities by economic sector) using the outcomes of Energy System Simulation model (ENSYSI). This model is developed by the Dutch Environmental assessment agency (PBL) and provides quantitative information regarding developments in energy demand and production between 2010 and 2050. In section 2 of this paper an overview of literature is given. Section 3 describes the policy context. Section 4 describes the modelling framework BasGoed. The different parts of energy transition scenario are given in section 5. Section 6 presents the BasGoed results from the energy transition scenario. This paper ends with a conclusion and discussion section. @en

Strategic freight transport models can be used for a quantitative analysis of long term forecasts. This paper discusses an analysis of the bandwidth of freight transport forecasts for The Netherlands with the strategic freight transport model ‘BasGoed’. This model was developed over the past years as a basic model, satisfying the needs of policy making, based on proven knowledge and available transport data. Starting point for the analysis are the long-term scenarios for The Netherlands developed recently by CPB Netherlands Bureau for Economic Policy Analysis and PBL Netherlands Environmental Assessment Agency (WLO scenarios: Future outlook on welfare, prosperity and the human environment). The scenarios describe two base cases: The High and Low scenario. Both scenarios include a consistent set of assumptions on economic development (domestic growth by industry sector and international trade), infrastructure development, fuel prices, and logistic efficiency. The bandwidth of freight forecasts is further explored in five distinctive sensitivity analyses: different development in fuel prices, energy markets, CO2-pricing, dematerialization and modal shift in the port of Rotterdam. The sensitivity analysis provides more insight in the level of importance of each scenario assumption and it can be useful in estimating a bandwidth for freight transport demand. This is valuable in providing insight in the robustness of the freight transport forecasts for policy studies.@en