Modeling Exposure to Mobility-Related Pollution: Review and Key Challenges - Archive ouverte HAL
Article Dans Une Revue Transportation Research Record Année : 2023

Modeling Exposure to Mobility-Related Pollution: Review and Key Challenges

Résumé

The health and equity issues related to urban pollution, coupled with the need to assess the consequences of implementing transport policies or new mobility solutions, make it imperative to provide decision-makers with a relevant modeling framework. The coupling of activity-based travel models with environmental models presents a promising approach to thoroughly investigate the interconnected issues related to the impact of road traffic on individual exposure to noise and air pollution. Integrated modeling chains provide a robust framework to comprehensively assess traffic scenarios on a city scale and address issues related to environmental inequalities. This article reviews the recent work in this field to identify both the main contributions and key challenges still to be addressed. It illustrates how the use of a dynamic approach, which considers the intraday dynamics of individual mobilities and pollution concentrations, can contribute to more accurate estimates of the exposure of individuals to pollutants. This modeling approach also has the potential to investigate how the level of exposure depends on the characteristics of the individuals (socioeconomic factors, commuting patterns, location of residence, and main activities). Nonetheless, there are still important challenges to overcome to further enhance the accuracy and applicability of these models: taking into account all types of traffic and transport modes; refining the modeling of exposure to pollution during travel; taking better consideration of microenvironments; and so forth.
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Dates et versions

hal-04312243 , version 1 (28-11-2023)

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Citer

Pascal Gastineau, Arnaud Can, Boyam Yaméogo, Leonardo Luquezi, Pierre Hankach, et al.. Modeling Exposure to Mobility-Related Pollution: Review and Key Challenges. Transportation Research Record, 2023, ⟨10.1177/03611981231208907⟩. ⟨hal-04312243⟩
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