A welfare cost assessment of various policy measures to reduce pollutant emissions from passenger road vehicles

Policy options to reduce passenger transport emissions in Europe are simulated with the EUCARS model. The EUCARS welfare analysis includes changes in consumer surplus, congestion and tax revenues. Simulations also address consumer myopia, i.e., the underestimation of fuel costs by car buyers. The best policy mix to reduce CO₂ consists of fuel taxes that are combined with differentiated purchase taxes to correct for the assumed myopia. This combination could reduce CO₂ emissions of over 25% without reducing contemporaneous well-being. For the reduction of conventional emissions, an equivalent best mix includes an emissions-based kilometre tax combined with a purchase feebate. This mix allows a 60% reduction in toxic emissions without any noticeable welfare reduction. The overall superiority of these two mixes compared to alternative choices is higher when the evaluation includes a broad group of externalities, a premium on public funds, and positive feedbacks across emissions categories. Local traffic management measures are important zero-cost complements for an overall emissions strategy.     

Is DOC the main source of organic matter remineralization in the ocean water column?

Recent interpretations of carbon flux data and deep-sea processes have led to a reconsideration of the role of dissolved organic carbon (DOC) in supporting water column remineralization and other mid-water biogeochemical transformations (Suzuki et al., 1985; Cho and Azam, 1988; Karl et al., 1988; Christensen et al., 1989; Naqvi and Shailaja, 1993). To date, there have been no direct comparisons of particulate carbon flux data with water column metabolic rates. Here, for the first time, particulate carbon flux and respiratory electron transport activity (from which metabolic CO₂ production is derived), have been monitored simultaneously for one year in the same area of the northwestern Mediterranean Sea. In the aphotic layer (200–1000 m), particulate organic carbon (POC) can support only 20% of the overall organic matter remineralization. Remineralization rates are consistent with recent calculations of DOC exported from the euphotic layer in this area, confirming the vital importance of DOC in maintaining deep-water metabolism. This finding would apply to other regions of mesotrophic and oligotrophic production and thus affect our understanding of carbon recycling in the water column, new production and O₂ utilization.     

Wave climate evolution in the Bay of Biscay over two decades

As a background, a review of long term evolution of wave climate in the North Atlantic is discussed. Most studies show that interannual evolutions in wave heights may be related to climatic factors, such as the North Atlantic Oscillation Index for example.Data of a waverider, consisting of a time series of 20 years in the Bay of Biscay (off Biscarosse, France), are analysed. Based on these data obtained from 1980, wave heights tend to decrease over the period. Also, interannual evolutions exist, particularly in the wave period. The fact that the annual wave periods at Biscarosse are found to vary more significantly than the annual wave heights led us to assume that it is an indirect effect of the evolution in the location of generating storms relative to the buoy. The relationships between wave parameters and climatic factors such as the North Atlantic Oscillation Index and the Garonne discharge have been derived: they show that the NAO index is negatively correlated with the river discharge and positively correlated with the wave period. This result is in agreement with the general climate scheme associated with NAO cycle proposed by Kushnir et al. [Kushnir, Y., Cardone, V.J., Cane, M., 1995. Link between Atlantic climate variability of surface wave height and sea level pressure. Proc. Fourth Int. Workshop on Wave Incasting and forecasting, Banff, AB, Canada, 59–64.]: NAO+ shifts storm tracks northward and dry weather are encountered in the southern part of Europe (conversely NAO− brings storm tracks and rainfall closer). Concerning wave heights, the lack of dependence on NAO index may be associated with compensation effects between wind intensity and storm tracks: wave energy is partly dissipated while reaching the Bay of Biscay in case of severe but distant storms (NAO+), which is not the case for storms generated nearer to the buoy and associated with moderate westerly winds (NOA−). However, the reason of the decrease in wave heights is not clear.     

Evaluation of marine radar as an ocean-wave-field detector through full numerical simulation

The importance of ocean waves parameters (propagation direction, mean period, significant wave height, etc.) is related to several aspects of a ships safety, efficiency in operation, routing, design, and maintenance. However, some available methods for obtaining those parameters have data limitations and inconvenient aspects. In severe weather conditions, an ocean-wave-field detector is necessary. This can provide two-dimensional ocean-wave-field information directly. Among other conventional methods, ship-borne wave radar has the ability to function as such a detector, and some researchers have tried to develop practical systems. A numerical approach using plan position indicator (PPI) images from conventional marine radars is proposed to retrieve valuable information from the ocean waves. A three-dimensional Fourier transform is applied to a set of consecutive radar PPI images to perform spectrum analysis. The removal of undesired elements in the spectrum is achieved by applying a hi-pass filter to remove static components, and by comparing the data with the expected dispersion shell to correct for nonocean-wave power. Numerical experiments under controlled conditions using simulated PPI images were performed through numerical simulations based on theoretical ocean-wave equations. The results include a comparison between the original wave parameters used in the simulation and the values retrieved from the spectrum analysis.     

Understanding individual travel decisions: results from a commuters survey in Geneva

In this paper, we present the results of an extended traveler behavior survey conducted in Geneva (Switzerland) in March 1994. In this survey, commuters were asked about the impact of various factors, related to individual or household characteristics and situational, contextual and environmental constraints on their basic travel decisions. In particular, the issues of mode, route and departure time choice were investigated, together with the diversion from normal patterns in response to adverse weather conditions. Some cross cultural comparisons are discussed with respect to the results of a similar survey conducted in Brussels (Belgium) in 1992 (Khattak & de Palma 1995, 1997).     

A disaggregated tool for evaluation of road safety policies

This paper presents a methodological disaggregated approach to analyze the impact of interventions on road safety. The model aims to describe the accident rates of an individual using mileage as a measure of risk exposure. The model is formulated as a system of equations that takes into account interactions between the mileage of a given individual and the other drivers. Once estimated, the model acts as a simulator allowing us to measure the performance of policy interventions to increase road safety.     

Covariance, identification, and finite-sample performance of the MSL and Bayes estimators of a logit model with latent attributes

In this paper we discuss the specification, covariance structure, estimation, identification, and point-estimate analysis of a logit model with endogenous latent attributes that avoids problems of inconsistency. We show first that the total error term induced by the stochastic latent attributes is heteroskedastic and nonindependent. In addition, we show that the exact identification conditions support the two-stage analysis found in much current work. Second, we set up a Monte Carlo experiment where we compare the finite-sample performance of the point estimates of two alternative methods of estimation, namely frequentist full information maximum simulated likelihood and Bayesian Metropolis Hastings-within-Gibbs sampling. The Monte Carlo study represents a virtual case of travel mode choice. Even though the two estimation methods we analyze are based on different philosophies, both the frequentist and Bayesian methods provide estimators that are asymptotically equivalent. Our results show that both estimators are feasible and offer comparable results with a large enough sample size. However, the Bayesian point estimates outperform maximum likelihood in terms of accuracy, statistical significance, and efficiency when the sample size is low.     

Random covariance heterogeneity in discrete choice models

In this paper, we extend the standard discrete choice modelling framework by allowing for random variations in the substitution patterns between alternatives across respondents, leading to increased model flexibility. The paper shows how such a Mixed Covariance model can be specified either with purely random variation or with a mixture of random and deterministic variation. Additionally, the model can be based on an underlying GEV or ECL structure. Finally, the model can be specified as a continuous mixture or as a discrete mixture. An application on Stated Preference data for the choice of departure time and travel mode shows that important gains in model performance can be obtained by allowing for random covariance heterogeneity. Furthermore, the approach leads to significant differences in the implied willingness to pay measures, and the substitution patterns between alternatives.