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1. Overview and motivation The emergence of e-commerce in the past decade and the surging growth during the pandemic, partially at the cost of in-store shopping, have reinforced the need for a better representation of this type of consumer demand and its effects in urban transportation studies (Reiffer et al, 2021). Since this is a recent development, conventional passenger transport models only model the personal mobility for in-store shopping. Standard modelling tools for large-scale demand forecasts for online and in-store shopping are limited. A proper representation of this demand segment first of all requires an estimate of e-commerce demand, and second the simulation of the delivery of the orders. Jaller and Pahwa (2020) developed both an econometric MNL model for in-store and online shopping and applied it to a synthetic population to estimate externalities of the alternatives. The econometric model explains the preferences for type of shopping but not the total level of product consumption, and the delivery of online orders is estimated on aggregate statistics. Other disaggregate simulation studies only focus on e-commerce demand, without considering the trade-off between online versus in-store shopping, such as Cheng et al (2021). In effect, online ordering may reduce physical movements of people to stores, while increasing the delivery of orders to people’s home addresses. This shift is taking place for many consumer products and groceries as well. Weltevreden and Rotem-Minaldi (2007) show early evidence that e-commerce ordering in the Netherlands increases freight transport, while personal travel decreases marginally. On the side of e-commerce deliveries, the simulation of urban freight transport is a well-studied topic in recent literature (Mommens et al, 2021; Hörl and Puchinger, 2021; Reiffer et al, 2021). However, modelling the demand side of e-commerce is often still minimal. 2. Methodology, results and main contributions, Transport and Planning

1. Overview and motivation E-commerce is a rapidly developing segment within urban goods transportation. While currently making up only 5.5% of all kilometers driven by vans in the Netherlands (CBS, 2018), this segment is experiencing rapid growth. For example, in the Netherlands, the volume of parcel deliveries grew by 20% in 2018 (ACM, 2018). This growth is further accelerated by the current coronavirus pandemic. The increasing importance of this segment is not reflected yet in strategic models used in practice for transportation demand forecasting. Parcel deliveries are not modelled explicitly, which does not only prevent the model users from calculating effects of scenarios and policies related to e-commerce, but it also disregards the unique nature of this segment (e.g. specific depot locations, strong growth rates) and, therefore, leads to flawed reference forecasts of van traffic. In the scientific literature there are some first examples of simulation models for parcel deliveries (Sakai et al, 2020; Hörl & Puchinger, 2021; Llorca & Moeckel, 2021; Mommens et al., 2021; Reiffer et al., 2021). However, each of these examples lacks an empirical disaggregate demand model, focusses on one (part of a) city rather than a whole region, or focusses on one product/service segment rather than all parcel deliveries in a region. Moreover, little experience is gathered in applying such urban freight simulators for traffic forecasting. 2. Methodology, results and main contributions To combat these shortcomings of the state-of-practice freight models, we developed a module for last-mile parcel deliveries and used it to explore the impacts of different scenario assumptions regarding parcel demand and scheduling. The module consists of two sub-modules: the parcel demand sub-module and the parcel scheduling sub-module. The parcel demand sub-module calculates parcel demand based on the households and businesses in each zone. For parcels to hou, Transport and Planning

As part of a broader vision for emission-free city logistics, the city of Rotterdam plans to introduce a zero-emission zone in combination with urban consolidation centers (UCCs) on the outskirts of the city to generate a shift to zero-emission vehicles. For the design of this zero-emission zone, several research questions arise that require a systematic analysis of the impacts of the transition scenarios on freight demand patterns, the use and market shares of new (zero-emission) vehicles, and the impacts of truck flow and emissions. As a case study, we implemented heterogenous transition scenarios for each logistic segment into the Tactical Freight Simulator from the HARMONY project and analyzed the systemwide impacts. This model is multiagent, empirical, and shipment based and simulates long-term tactical choices (distribution channel choice, shipment size and vehicle type choice, sourcing) and short-term tactical choices (tour formation, delivery times). Results showed that the impact of UCCs is not trivial: we observed a small increase in vehicle kilometers traveled overall of +0.25%, which can be attributed to the rerouting of shipments through the UCCs. Calculations confirmed that emissions reduced dramatically, by 90%, inside the zero-emission zone. At the city scale this corresponds to a reduction of almost 10%, as most freightrelated traffic is generated by the port and involves long-haul heavy goods vehicle transport that does not enter the city center. At a regional level, impact reduction was very small. More measures are needed if more ambitious reductions in emissions are to be achieved., Transport and Planning, Transport and Logistics

As part of a broader vision for emission-free city logistics, the city of Rotterdam plans to introduce a zero-emission zone in combination with urban consolidation centers (UCCs) on the outskirts of the city to generate a shift to zero-emission vehicles. For the design of this zero-emission zone, several research questions arise that require a systematic analysis of the impacts of the transition scenarios on freight demand patterns, the use and market shares of new (zero-emission) vehicles, and the impacts of truck flow and emissions. As a case study, we implemented heterogenous transition scenarios for each logistic segment into the Tactical Freight Simulator from the HARMONY project and analyzed the systemwide impacts. This model is multiagent, empirical, and shipment based and simulates long-term tactical choices (distribution channel choice, shipment size and vehicle type choice, sourcing) and short-term tactical choices (tour formation, delivery times). Results showed that the impact of UCCs is not trivial: we observed a small increase in vehicle kilometers traveled overall of +0.25%, which can be attributed to the rerouting of shipments through the UCCs. Calculations confirmed that emissions reduced dramatically, by 90%, inside the zero-emission zone. At the city scale this corresponds to a reduction of almost 10%, as most freightrelated traffic is generated by the port and involves long-haul heavy goods vehicle transport that does not enter the city center. At a regional level, impact reduction was very small. More measures are needed if more ambitious reductions in emissions are to be achieved., Transport and Planning, Transport and Logistics