A valuation of the environmental performance of vehicles: an analysis and comparison of two methodologies

The European Clean Vehicle Directive was introduced in 2009 to create an obligation on public authorities to take into account the impact of energy consumption, carbon dioxide (CO₂) emissions and pollutant emissions into their purchasing decisions for road transport vehicles. This should stimulate the market for clean and energy-efficient vehicles and improve transport's impact on environment, climate change and energy use. Therefore the so-called ‘Operational Lifetime Cost’ of a vehicle is calculated, divided into the cost for energy consumption, CO₂ and pollutant (nitrous oxide, particulate matter, non-methane hydrocarbons) emissions. In Belgium, a different methodology has been developed to calculate the environmental impact of a vehicle, called ‘Ecoscore’, based on a well-to-wheel approach. More pollutants are included compared to the Clean Vehicle methodology, but also indirect emissions are taken into account. In this paper, both methodologies are compared and used to analyze the environmental performance of passenger cars with different fuel types and from different vehicle segments. Similar rankings between both methodologies are obtained; however, the large impact of energy use (and CO₂ emissions) in the Clean Vehicle methodology disadvantages compressed natural gas cars, as well as diesel cars equipped with particulate filters, compared to the Ecoscore methodology.     

Impact of ICT access on personal activity space and greenhouse gas production: evidence from Quebec City, Canada

This paper presents an approach to investigating the impact of information and communication technologies (ICTs) on travel behaviour and its environmental effects. The paper focuses on the spatial dispersion of out-of-home activities and travel (activity space) and greenhouse gas emissions (GHGs) at the level of the individual. An original method, combining spatial analysis in a geographic information system with advanced regression techniques, is proposed to explore these potentially complex relationships in the case of access to mobile phones and the internet, while taking into account the influence of socio-economics and built environment factors. The proposed methodology is tested using a 7-day activity-based survey in Quebec City in 2003?C2004, a juncture of particular interest because these ICTs had recently crossed the threshold of 40?% (mobile phone) and 60?% (home-based internet) penetration at the time. The study period also largely pre-dates the era of mobile internet access. Among other results, socio-demographic factors were found to significantly affect both ICT access and travel out-comes. The built environment, represented by neighbourhood typologies, also played an important role. However, it was found that after controlling for the self-selection effect, built environment and socio-demographics, those who had a mobile phone available produced 30?% more GHGs during the observed week than those who did not. This higher level of GHG pro-duction was accompanied by a 12?% higher measure of activity dispersion. On the other hand, having internet access at home was associated with lower GHGs (?19?%) and lesser activity dispersion (?25?%). Possibly, mobile phones enable individuals to cover more space and produce more emissions, while the internet provides opportunities to stay at home or avoid motorized travel thus reducing emissions. The estimated effects of having a mobile phone were not only negative but also larger in magnitude from the environmental point of view than those of fixed internet access. However, the results of this study also suggest that access to mobile phones and internet may have substantial and compensatory effects at the individual level that are undetected when using model structures that do not take into account that unobserved factors may influence both ICT choices and travel outcomes.     

Estimating the value of risk reductions for car drivers when pedestrians are involved: a case study in Spain

We estimated the benefits associated with reducing fatal and severe injuries from traffic accidents using a stated choice experiment where choice situations were generated through a statistically efficient design. Specifically, the risk variables were defined as the expected annual number of vehicle car-users that suffered their death or were severely injured in a traffic accident. In addition, and differing from previous research, the number of pedestrians that died or were severely injured in traffic accidents per year was also included as a risk attribute in the choice experiment, to attempt at measuring drivers’ willingness to pay to reduce the risk of hitting pedestrians in a crash. The empirical setting was a choice of route for a particular trip that a sample of car drivers periodically undertakes in Tenerife, Spain. Models were estimated accounting for random taste heterogeneity and pseudo-panel data correlation. The median of the distribution of simulated parameters was used to obtain a representative measure for the monetary valuation of risk reductions. We found that the ratio between the values of reducing the risk of suffering a serious injury and that of reducing a fatality was approximately 18 %. Further, and quite novel, we also found that the value of reducing a pedestrian fatality was 39 % of the value of reducing a car occupant fatality.     

How household transportation expenditures have evolved in Canada: a long term perspective

In recent years, increasing recognition of the challenges associated with global climate change and inequity in developed countries have revived researcher’s interest towards analyzing transportation related expenditure of households. The current research contributes to travel behaviour literature by developing an econometric model of household budgetary allocations with a particular focus on transportation expenditure. Towards this end, we employ the public-use micro-data extracted from the Survey of Household Spending (SHS) for the years 1997–2009. The proposed econometric modeling approach is built on the multiple discrete continuous extreme value model (MDCEV) framework. Specifically, in our analysis, the scaled version of the MDCEV model outperformed its other counterparts. Broadly, the model results indicated that a host of household socio-economic and demographic attributes along with the residential location characteristics affect the apportioning of income to various expenditure categories and savings. We also observed a relatively stable transportation spending behaviour over time. Additionally, a policy analysis exercise is conducted where we observed that with increase in health expenses and reduction in savings results in adjustments in all expenditure categories.     

Users’ perceptions and willingness to pay in interurban toll roads: identifying differences across regions from a nationwide survey in Spain

Users’ acceptability is considered one of the key drivers for the successful implementation of transport policy measures. This is especially crucial in the case of toll roads since they are financed through drivers’ contributions. Previous literature in this field has mainly focused on measuring users’ attitudes towards urban congestion pricing strategies. However limited research has been developed concerning interurban toll roads. Previous research shows that socioeconomic variables are not conclusive to explain users’ perceptions towards tolls. By contrast, other drivers such as regional differences seem to play a more important role, especially when charging conditions within the same nation greatly vary across regions. This paper analyzes regional differences in users’ attitudes within an asymmetrical distribution of the toll road network across regions. Based on a nationwide survey conducted to road users in interurban toll roads in Spain, we develop both a binomial logit and a censored regression (tobit) model to explore drivers’ perceptions and willingness to pay. The research concludes that users from regions with a more extensive tolled network generally show a more negative attitude towards charges, but not necessarily a lower willingness to pay. The paper also points out that an asymmetrical distribution of toll roads across regions may result in negative perceptions among those users perceiving to be unfairly treated when compared to citizens in other regions.     

Flexible long range planning using low cost information

Contemporary transport planning requires a flexible modelling approach which can be used to monitor the implementation of a long term plan checking regularly its short term performance with easily available data; the original model is periodically updated using low cost information and this allows the evaluation of the changes to the plan which may be required. Such an approach requires models suited to regular updating and to the use of data from different sources. Models to update trip matrices from traffic counts have been available for some time; however, the estimation and/or updating of other model stages with low cost data has escaped analytical treatment. The paper discusses this idea and formulates the updating problem for an example involving a joint destination/mode choice model under various assumptions about the nature of the available data. Analytical solutions are proposed as well as some general conclusions.requests for offprints     

Seasonality of picophytoplankton chlorophyll a and biomass in the central Cantabrian Sea, southern Bay of Biscay

Seasonal changes in the abundance and biomass of cyanobacteria (Synechococcus and Prochlorococcus) and picoeukaryotes were studied by flow cytometry in the upper layers of the central Cantabrian Sea continental shelf, from April 2002 to April 2006. The study area displayed the typical hydrographic conditions of temperate coastal zones. A marked seasonality of the relative contribution of prokaryotes and eukaryotes was found. While cyanobacteria were generally more abundant for most of the year (up to 2.4 10⁵ cells mL^− 1), picoeukaryotes dominated the community (up to 10⁴ cells mL^− 1) from February to May. The disappearance of Prochlorococcus from spring through summer is likely related to shifts in the prevailing current regime. The maximum total abundance of picophytoplankton was consistently found in late summer–early autumn. Mean photic-layer picoplanktonic chlorophyll a ranged from 0.06 to 0.53 µg L^− 1 with a relatively high mean contribution to total values (33 ± 2% SE), showing maxima around autumn and minima in spring. Biomass (range 0.58–40.16 mg C m^− 3) was generally dominated by picoeukaryotes (mean ± SE, 4.28 ± 0.27 mg C m^− 3) with an average contribution of cyanobacteria of 30 ± 2%. Different seasonality of pigment and biomass values resulted in a clear temporal pattern of picophytoplanktonic carbon to chlorophyll a ratio, which ranged from 10 (winter) to 140 (summer). This study highlights the important contribution of picoplanktonic chlorophyll a and carbon biomass in this coastal ecosystem.     

Statistical comparison of trace metal concentrations in wild mussels (Mytilus galloprovincialis) in selected sites of Galicia and Gulf of Biscay (Spain)

Concentrations of five trace metals (Cd, Hg, Pb, Cu and Zn) in wild mussels (Mytilus galloprovincialis) from the Galician and Gulf of Biscay areas in Spain were monitored from 2000 to 2004. A pool of mussel soft tissue was prepared using 50 or more individuals representing the available size range (35–60 mm) present at the sampling points (A Coruña, Pontevedra and Vigo–Galicia, NW of Spain—and Avilés, Bilbao and Santander–Gulf of Biscay). Metals were analysed by atomic absorption spectrometry, AAS, (flame–AAS: Cu and Zn; graphite furnace–AAS: Cd and Pb; flow injection-cold vapour–AAS: total Hg). Quality of the chemical analyses was assessed by participation in periodic QUASIMEME intercalibration exercises carried out from 2000 to 2004, while the present study was developed . Univariate statistical studies, Anova (Analysis of the Variance) and Principal Component Analysis (autoscaled data, Varimax rotation) were carried out. Differences between the two areas as well as certain temporal trends were found and, in general, the Gulf of Biscay samples showed higher metallic contents, mainly close to Avilés, where iron and steel factories thrown residues for years into a nearby coastal area.     

A week in the life of baby boomers: how do they see the spatial–temporal organization of their activities and travel?

In this paper, we take an initial look at the spatial and temporal flexibility in the activity patterns of the so-called “baby-boomer” cohort (born 1947–1966) in comparison with younger and older adults. Using a unique longitudinal survey carried in Quebec City from 2002 to 2005, we explore activity patterns and trip rates over a seven-day observation period during the first wave, and take a first look at some aspects of their evolution over two subsequent waves at about one-year intervals. We model the propensity to undertake activities within selected conventional non-work classifications such as “shopping” and “leisure”, and also according to respondents’ own perceptions of the spatial and temporal flexibility of each out-of-home activity that they had executed. While we cannot strictly separate cohort effects from age-related effects, after controlling for gender and household structure, we infer that age and related lifestyle effects dominate in explaining these propensities. However, the boomers were the only age stratum to increase their total out-of-home activity participation over the course of the panel, an intriguing starting point for the future study of this cohort.

Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review

Abstract

Household vehicle ownership, and the associated dimensions including fleet size, vehicle type and usage, has been one of the most researched transport topics. This paper endeavors to provide a critical overview of the wide-ranging methodological approaches employed in vehicle ownership modeling depending on the ownership representation over the past two decades. The studies in the existing literature based on the vehicle ownership representation are classified as: exogenous static, exogenous dynamic, endogenous static and endogenous dynamic models. The methodological approaches applied range from simple linear regressions to complex econometrics formulations taking into account a rich set of covariates. In spite of the steady advancement and impressive evolution in terms of methodological approaches to examine the decision process, we identify complex issues that pose a formidable challenge to address the evolution of vehicle ownership in the coming years. Specifically, we discuss challenges with data availability and methodological framework selection. In light of these discussions, we provide a decision matrix for aiding researchers/practitioners in determining appropriate model frameworks for conducting vehicle ownership analysis.