The treatment of traffic in the Dutch environmental outlooks: the role of science in policy making and policy evaluation

The Dutch National Institute of Public Health and Environmental Protection publishes Environmental Outlooks in which 25‐year projections are made. These Outlooks quantifying the environmental problems, form the scientific basis for Dutch environmental policy. Traffic and transport is one of the main sectors causing environmental problems. The emissions and energy use of all relevant categories (road traffic, non‐road traffic) are based on model simulations with models. This paper describes the main models used.

If present policy is implemented only a minority of the environmental targets will be met.

If a sustainable transport system for the Netherlands means a large reducton in CO₂ emissions and energy use after 2010 a stronger emphasis on both technical and non‐technical measures (such as land‐use planning combined with public transport improvements) for the period until 2010 is needed than proposed in the Second Transport Structure Plan, unless a sustainable energy source becomes available.     

Road transport and climate change: Stepping off the greenhouse gas

Transport is Australia’s third largest and second fastest growing source of greenhouse gas (GHG) emissions. The road transport sector makes up 88% of total transport emissions and the projected emissions increase from 1990 to 2020 is 64%. Achieving prospective emission reduction targets will pose major challenges for the road transport sector. This paper investigates two targets for reducing Australian road transport greenhouse gas emissions, and what they might mean for the sector: emissions in 2020 being 20% below 2000 levels; and emissions in 2050 being 80% below 2000 levels. Six ways in which emissions might be reduced to achieve these targets are considered. The analysis suggests that major behavioural and technological changes will be required to deliver significant emission reductions, with very substantial reductions in vehicle emission intensity being absolutely vital to making major inroads in road transport GHG emissions.     

Quantifying the climate impact of emissions from land-based transport in Germany

Although climate change is a global problem, specific mitigation measures are frequently applied on regional or national scales only. This is the case in particular for measures to reduce the emissions of land-based transport, which is largely characterized by regional or national systems with independent infrastructure, organization, and regulation. The climate perturbations caused by regional transport emissions are small compared to those resulting from global emissions. Consequently, they can be smaller than the detection limits in global three-dimensional chemistry-climate model simulations, hampering the evaluation of the climate benefit of mitigation strategies. Hence, we developed a new approach to solve this problem. The approach is based on a combination of a detailed three-dimensional global chemistry-climate model system, aerosol-climate response functions, and a zero-dimensional climate response model. For demonstration purposes, the approach was applied to results from a transport and emission modeling suite, which was designed to quantify the present-day and possible future transport activities in Germany and the resulting emissions. The results show that, in a baseline scenario, German transport emissions result in an increase in global mean surface temperature of the order of 0.01 K during the 21st century. This effect is dominated by the CO₂ emissions, in contrast to the impact of global transport emissions, where non-CO₂ species make a larger relative contribution to transport-induced climate change than in the case of German emissions. Our new approach is ready for operational use to evaluate the climate benefit of mitigation strategies to reduce the impact of transport emissions.     

Modal-split effects of climate change: The effect of low water levels on the competitive position of inland waterway transport in the river Rhine area

Future climate change is expected to affect inland waterway transport in most main natural waterways in Europe. For the river Rhine it is expected that, in summer, more and longer periods with low water levels will occur. In periods of low water levels inland waterway vessels have to reduce their load factors and, as a result, transport prices per tonne will increase. One possible consequence of these higher transport prices is a deterioration of the competitive position of inland waterway transport compared with rail and road transport, and thus a change in modal split. We study this issue using a GIS-based software model called NODUS which provides a tool for the detailed analysis of freight transportation over extensive multimodal networks. We assess the effect of low water levels on the costs of transport operations for inland waterway transport in North West Europe under several climate scenarios. It turns out, that the effect on the modal split is limited. Under the most extreme climate scenario, inland waterway transport would lose about 5.4% of the quantity that is currently being transported annually in the part of the European inland waterway transport market considered. The very dry year of 2003 can be seen as an analogue for this scenario.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies

Forecasting the impacts of a proposed policy is an important component of the transportation planning and decision making process. Although scientific tools are often used in transportation forecasts, biases and, more specifically, overestimations of the expected impact are often observed. This study explores the correlations between forecast-maker’s characteristics and forecast bias creation and reduction. The study examines two transport-related policies aiming at the reduction of car use: telecommuting and carsharing. Both are Travel Demand Management (TDM) policies, which attract much attention from transport experts. We tested the extent to which the forecast-maker’s beliefs about the policy at stake affected the forecast bias. We found that attitudes and beliefs associates not only with overestimation bias but also with its reduction over time. We also tested the extent to which the forecast-maker’s affiliation, the performing institute and the publication type were correlated with the biases of the forecast and with the forecaster attitudes and beliefs. These characteristics are intuitively used by the forecast user as tools to assess the ‘objectivity’ of the forecast, but our analysis found no association between these characteristics and the forecast bias.     

Centralized versus distributed feeder ship service: The case of the Maasvlakte harbour area of Rotterdam

Coastal and inland feeder shipping is a critical factor for intercontinental container transport. The question is whether each intercontinental terminal should be equipped with its own service stations for feeder shipping, or whether pooling of the facilities would be more effective. For this paper, the service station examined for the service of feeder ships is equipped with two quay cranes operating in parallel supported by a small active quay stack. The centre for this feeder service consists of several of these stations. Simulation shows that a crane productivity of 96% is feasible with an average vehicle waiting time of 1 min, that a central service requires fewer service stations than a distributed service and that the quay transport for central and distributed transport requires the same number of terminal vehicles. The analysis shows that a centralized service is preferable, attracting 70% of the market potential.