Recherche

Abstract: Numerous Low Emission Zones (LEZs) have been implemented across Europe to improve air quality and reduce car use. However, to date, the impact of LEZs has been widely perceived as regressive, since vehicles that meet the low emission requirements are more expensive than others. The literature assessing the impact of LEZs on vulnerable and poor households prior to their implementation is sparse, particularly if we take into account the diversity of households’ capacities to adapt according to their characteristics and mobility habits, beyond the sole solution of purchasing a LEZ-compatible vehicle. However, such assessments would make it possible to define accompanying policies to improve the social justice of the LEZs. In this article, we develop a methodology to evaluate the ex-ante impacts of a LEZ on vulnerable or poor households. First, we identify households affected by the LEZ. Second, the VulMob multidimensional indicator is used to identify, among affected households, households with low transport-affordability and highly vulnerable households according to their vulnerability profiles. Third, we assess the adaptive capacity in terms of modal shift options and considering the possibility to modify the destination. We apply this methodology to the Grenoble area (France), using the Local Household Travel Survey. The results show that not only are highly vulnerable households more affected by the LEZ than other households, but also that more of them are left with no alternative but to buy a LEZ-compliant car. Nevertheless, modal shift seems an adaptation solution with great potential for all households. This could improve the environmental and health performance of LEZs. This work can guide decision-makers in the definition of preventive and compensatory policies, considering the profiles of transport vulnerability and the specificities of the territory. 

Share of Highly Vulnerable households: 

Abstract

Mobility enables to find jobs, go to school or meet people. However, long distances, high costs, car dependency and poor accessibility are sources of mobility vulnerabilities. The current rise in fuel prices may have a strong impact on mobility, especially for households that rely heavily on their cars. Moreover, the need to reduce air pollution and greenhouse gases emissions requires the implementation of ambitious environmental policies. It is therefore necessary to identify transport poor households, affected by financial issues, as well as vulnerable households whose mobility would be strongly impacted by changes in individual mobility conditions and would have difficulties to adapt to this situation. To this end, we construct VulMob, a multidimensional indicator made up of thirteen individual factors organized in four dimensions: financial resources and transport affordability, work constraints, heavy car use and accessibility and structural constraints. We apply this indicator to the Grenoble area, in France. Our results show that 9.6% are highly vulnerable, meaning that they face at least six vulnerability issues and 5.5% of the households face transport affordability issues. A typology of five profiles of highly vulnerable households shows that some are financially constrained; others are heavy car users, work at night or face public transport accessibility problems. 

Share of Highly Vulnerable households: 

Abstract

Context

Policies aiming at decreasing air pollutants (e.g., fine particulate matter, PM2.5) are often designed without targeting an explicit health benefit nor carrying out cost-benefit analyses.

Methods

We developed a transdisciplinary backward and forward approach at the conurbation level: from health objectives set by local decision-makers, we estimated which reductions in PM2.5 exposures and emissions would allow to reach them, and identified urban policies leading to these reductions (backward approach). We finally conducted health impact and cost-benefit analyses of these policies (forward approach). The policies were related to the most emitting sectors in the considered area (Grenoble, France), wood heating and transport sectors. The forward approach also considered the health impact and co-benefits of these policies related to changes in physical activity and CO2 emissions.

Findings

Decision-makers set three health targets, corresponding to decreases by 33% to 67% in PM2.5-attributable mortality in 2030, compared to 2016. A decrease by 42% in PM2.5 exposure (from 13.9 µg/m3) was required to reach the decrease by 67% in PM2.5-attributable mortality. For each Euro invested, the total benefit was about 30€ for policies focusing on wood heating, and 1 to 68€ for traffic policies. Acting on a single sector was not enough to attain a 67% decrease in PM2.5-attributable mortality. This target could be achieved by replacing all inefficient wood heating equipment by low-emission pellet stoves and reducing by 36% the traffic of private motorized vehicles. This would require to increase the share of active modes (walking, biking…), inducing increases in physical activity and additional health benefits beyond the initial target. Annual net benefits were between €484 and €629 per capita for policies with report on active modes, compared to between €162 and €270 without.

Conclusions

Urban policies strongly reducing air pollution-attributable mortality can be identified by our approach. Such policies can be cost-efficient.

Using a stated preferences survey, the objective of this paper is to investigate the intra- and inter-individual heterogeneity of mode choice, when travel time is subject to variability. By‘inter-individual heterogeneity’ is meant that people are different in terms of attitude to risk and have different utility functions. By ‘intra-individual heterogeneity’ is meant that the behaviour may be different even when performed by the same individual when faced with a different mode of transport. Based on Rank-Dependent Utility Theory, the paper shows that the occurrence of delays associated with train trips is overestimated whereas they are underestimated for car trips. A latent-class logit model offers a somewhat different perspective: if, overall, car users are more likely to perceive possible delays for train trips than for car trips, train users tend to consider the objective occurrence of delays as they are presented in the survey and adopt a risk neutral choice behaviour. 

Based on choice experiments conducted in the Rhône-Alpes Region (France), we estimate an Integrated Choice and Latent Variable model that addresses heterogeneity in values of interurban travel time. We evaluate how sensitivity to travel time by public transport is distributed according to the level of comfort. Comfort is modeled as a function of objective attributes and individual perceptions about it: whether a seat is guaranteed, quality of trip experience (feelings experienced), (perceived) use of travel time during the trip, and overall ease of using public transport (perceived behavioral control). The results show that the last two play a significant role in the choice of a public transport mode and that the value of time function is downward sloping with higher levels of objective and perceived comfort. We discuss public policy implications and show that the most effective measure, in terms of economic benefits, would be to optimize and target investments in seat capacity supply. 

Background

Fine particulate matter (PM2.5) exposure entails large health effects in many urban areas. Public measures aiming at decreasing air pollution are often designed without targeting an explicit health benefit. Our objective was to investigate the health and economic benefits and the social inequalities in exposure resulting from several scenarios of reduction of PM2.5 exposure, in order to support decisions about urban policies.

Material and methods

In the French conurbations of Grenoble and Lyon (0.4 and 1.4 million inhabitants, respectively), PM2.5 yearly average exposure was estimated on a 10-m grid by coupling a PM2.5 dispersion model to population density. Changes in death cases, life expectancy, lung cancer and term low birth weight incident cases as well as associated health economic costs were estimated for ten PM2.5 reduction scenarios differing in terms of amplitude of reduction and spatial extent. Changes in social differences in PM2.5 exposure were also assessed.

Results

During the 2015–2017 period, PM2.5 average exposure was 13.9 μg/m3 in Grenoble and 15.3 μg/m3 in Lyon conurbations. Exposure to PM2.5 led to an estimated 145 (95% Confidence Interval, CI, 90–199) and 531 (95% CI, 330–729) premature deaths, 16 (95% CI, 8–24) and 65 (95% CI, 30–96) incident lung cancers, and 49 (95% CI, 19–76) and 193 (95% CI, 76–295) term low birth weight cases each year in Grenoble and Lyon conurbations, respectively, compared to a situation without PM2.5 anthropogenic sources, i.e. a PM2.5 concentration of 4.9 μg/m3. The associated costs amounted to 495 (Grenoble) and 1767 (Lyon) M€/year for the intangible costs related to all-cause non-accidental mortality and 27 and 105 M€ for the tangible and intangible costs induced by lung cancer. A PM2.5 exposure reduction down to the WHO air quality guideline (10 μg/m3) would reduce anthropogenic PM2.5-attributable mortality by half while decreases by 2.9 μg/m3 (Grenoble) and 3.3 μg/m3 (Lyon) were required to reduce it by a third. Scenarios focusing only on the most exposed areas had little overall impact. Scenarios seeking to reach a homogeneous exposure in the whole study area were the most efficient in alleviating social inequalities in exposure.

Conclusions

Reduction scenarios targeting only air pollution hotspots had little expected impact on population health. We provided estimates of the PM2.5 change required to reduce PM2.5-attributable mortality by one third or more. Our approach can help targeting air pollution reduction scenarios expected to entail significant benefits, and it could easily be transposed to other urban areas.