Active Transport Modes Research Articles

Adaptación metodológica en el diseño y desarrollo urbano de bajo impacto para el manejo de aguas pluviales en Colima, México

Contexto: Hoy en día, las ciudades requieren la implementación de nuevas experiencias de transformación urbana, debido a que la urbanización es responsable del 70 % de emisiones globales de CO2. El reto que confronta en materia urbana es hacer frente al CCG a nivel ciudad, mediante infraestructura multifuncional.
 Método: El presente estudio se llevó a cabo bajo la perspectiva del diseño y desarrollo urbano de bajo impacto (LIUDD, por su sigla en inglés) contextualizando el marco francés de planeación urbana, en el cual, el manejo de agua es prioritario. La ciudad de Colima presenta un crecimiento horizontal desordenado y, en consecuencia, la extensión de áreas impermeables ha provocado escorrentías, inundaciones y congestionamiento vial.
 Resultados: La zona norte-poniente presenta un área de oportunidad para tratar dichas problemáticas, como se analizó en esta investigación. La zona de estudio presenta un alto nivel de ocupación del suelo (COS=0,76-1,00) obteniendo un coeficiente de escorrentía CE=0,96. Además, presenta una baja densidad poblacional (51-100 hab/ha), con un 92 % de motorización. La vialidad ocupa el 91 % de la superficie de espacio público, por lo que representa un área de oportunidad para la infraestructura multifuncional. Se propone que mediante técnicas de drenaje urbano sostenible implementadas en vialidades principales, se reduzca el CE a 0,90, y el volumen de inundaciones en un 203 %, priorizando los modos activos de transporte.
 Conclusiones: Desarrollar e implementar una gestión integral del agua, sustentada en un cuadro reglamentario que priorice el LIUDD, puede paliar el estrés hídrico en esta y otras ciudades con problemáticas comunes, mediante la creación de una coordinación integrada por representantes de diversos sectores. Lo anterior, con el objetivo de poder gestionar el espacio público, y de impulsar proyectos multifuncionales para manejo de aguas pluviales, movilidad y desarrollo urbano que puedan ser útiles en la aplicación de nuevas maneras de planificar nuestras ciudades y mitigar los riesgos climáticos.

Using the abstraction hierarchy to identify how the purpose and structure of road transport systems contributes to road trauma

Research is beginning to demonstrate the merits of considering the broader road transport system when attempting to understand and prevent road trauma. This study involved the use of Work Domain Analysis, a systems analysis method, to develop a model of a road transport system based on Queensland, Australia. The model was subsequently used to identify the system wide contributory factors that play a role in road crashes, and to identify aspects of road transport systems that could be exploited when developing road safety interventions. The findings show that there are a set of crash contributory factors relating to the raison d'etre, values, and functions of road transport systems. This suggests that further significant reductions in road trauma will only be achieved through fundamental changes to the road transport system itself. Examples discussed include reducing the emphasis on the use of road transport for economic growth, reducing motor vehicle use and increasing active transport modes, and overhauling road safety strategies.

Identification of Enablers and Barriers for Public Bike Share System Adoption using Social Media and Statistical Models

Public bike share (PBS) systems are meant to be a sustainable urban mobility solution in areas where different travel options and the practice of active transport modes can diminish the need on the vehicle and decrease greenhouse gas emission. Although PBS systems have been included in transportation plans in the last decades experiencing an important development and growth, it is crucial to know the main enablers and barriers that PBS systems are facing to reach their goals. In this paper, first, sentiment analysis techniques are applied to user generated content (UGC) in social media comments (Facebook, Twitter and TripAdvisor) to identify these enablers and barriers. This analysis provides a set of explanatory variables that are combined with data from official statistics and the PBS observatory in Spain. As a result, a statistical model that assesses the connection between PBS use and certain characteristics of the PBS systems, utilizing sociodemographic, climate, and positive and negative opinion data extracted from social media is developed. The outcomes of the research work show that the identification of the main enablers and barriers of PBS systems can be effectively achieved following the research method and tools presented in the paper. The findings of the research can contribute to transportation planners to uncover the main factors related to the adoption and use of PBS systems, by taking advantage of publicly available data sources.

Residential relocation trajectories and neighborhood density, mixed land use and access networks as predictors of walking and bicycling in the Northern Finland Birth Cohort 1966

BackgroundGiven the high global prevalence of physical inactivity, there is a need to design cities that support active modes of transportation. High density diverse neighborhoods with good access networks have been associated with enhanced walking and cycling, but there is a lack of large-scale longitudinal studies utilizing a life course perspective to model residential relocation trajectories. The objectives of the present longitudinal study were to model and visualize residential relocation trajectories between 31 and 46 years of age based on neighborhood density, mixed land use and access networks (DMA), and to assess neighborhood DMA as a predictor of self-reported regular walking and cycling and objectively measured physical activity.MethodsBased on data from the Northern Finland Birth Cohort 1966 (N = 5947), we used self-reported regular walking and cycling and objectively measured physical activity as outcome variables and objectively assessed neighborhood DMA as the main explanatory variable. We conducted sequence analysis to model residential relocation trajectories, and generalized linear mixed models and Fisher’s exact test were used to explore longitudinal associations between neighborhood DMA and physical activity.ResultsOver 80% of the participants lived in a neighborhood with the same level of neighborhood DMA during the follow-up. Relocation occurred more often from higher to lower DMA neighborhoods than reverse. Increased neighborhood DMA was associated with increased regular walking (OR 1.03; 95% CI: 1.00, 1.05; p = 0.023) and cycling (OR 1.17; 95% CI: 1.12, 1.23; p < 0.001). Residential relocation trajectory from lower to highest neighborhood DMA increased the odds of starting regular walking (OR 3.15; 95% CI: 1.50, 7.14; p = 0.001) and cycling (OR 2.63; 95% CI: 1.23, 5.79; p = 0.009) as compared to higher to lower neighborhood DMA trajectory.ConclusionsThe results strongly support the hypothesis that increasing urban DMA can enhance regular walking and cycling at population level and so improve public health. The findings have implications for zoning and transportation policies, favoring the creation of dense and diverse neighborhoods with good access networks to support regular walking and cycling.

Effects of violent crime and vehicular crashes on active mode choice decisions in New York City

Substantial research has explored the effects of different variables on mode choice with the intent of understanding this behavior so that active modes can be encouraged. This study furthers that effort by investigating the impact of perceived danger from crime on the probability of choosing an active mode of transportation among travellers in New York City from 2009 to 2011. This study uses trip data from the New York Metropolitan Transportation Council Regional Household Travel Survey along with historical crime and vehicle collision data to estimate a random utility model. Traveller demographic information, travel cost and incidence of crime and vehicle collisions involving pedestrians or cyclists are used as explanatory variables in a mixed logit model. The finding implies that travellers could be encouraged to cycle by reducing crime levels, or by being provided an alternative route with less crime. Based on the model results it can be determined that travellers are willing to pay $0.66 for a 1000-point reduction in crime severity. An increase in crime of 1% has a much greater impact on bike ridership (2.11% reduction) than on walking (0.06% reduction). Removing crime completely would improve a traveler’s trip satisfaction by as much as $0.26 per trip. Compared to crime, collision rate has a much stronger impact on bike ridership, with an elasticity of −7.56 (3.6 times higher elasticity than crime).

Promoting active mobility: Evidence-based decision-making using statistical models

Shifting traffic to active transport modes (eg. walking/cycling) poses one of the most promising ways of tackling the persisting challenges that arise from motorized traffic. However, planning and policy making in walking and cycling domains is frequently impeded by a small-scaled and heterogeneous political landscape that rarely acts based on evidence thus limiting cost-effectiveness and target achievement. This paper proposes a largely data-driven planning approach that builds upon aggregated statistical models explaining walking and cycling modal shares. In addition to investigating a comprehensive set of influencing factors in relevant fields such as environment, climate, infrastructure or demographics, we bring attention to the role of political and administrative commitment in aggregated modal share modeling. Results suggest that our holistic approach is feasible both methodologically and in terms of its applicability in planning practice. As a first step towards evidence-based decision making the incremental effects of individual planning measures can be simulated and thus be used to rank options according to their effectiveness. Another outcome lies in the data-driven identification of spatial target areas for specific agenda setting in terms of awareness, mobility behavior, infrastructure, settlement structure and other planning-relevant domains.

The comparison of Holux and Qstarz GPS receivers in free living conditions: Dynamic accuracy in different active transport modes

Background: Physical activity (PA) is one of the major factors influencing human health. An important group of determinants are elements forming the built environment. For a proper understanding of relationships between the built environment and PA, we need to measure PA in space. Objective: This study aims to verify the accuracy of the Holux RCV-3000 GPS logger, which has not yet been validated in relation with PA. Methods: Two GPS receivers (Holux RCV-3000 and already validated Qstarz BT-Q1000XT) were tested during walking, running and cycling. A total of 1,908 GPS points were recorded by each device. For each trip, we calculated the percentage of points that fell within 1, 2.5, 5, and 10 m buffers, as well as the mean and median error. Results: Our results showed that 53.1% of all Holux and 45.1% of Qstarz GPS points fell within 2.5 m of the expected location, 90% (Holux) and 80% (Qstarz) fell within 10 m and the median error was 2.33 m and 3.15 m, respectively. Conclusions: The dynamic spatial accuracy of the tested Holux RCV-3000 was better than more expensive Qstarz device and can be considered as a valid instrument for assessing the spatial location of PA in future work.

Is motorcycle use associated with unhealthy lifestyles? Findings from Taiwan

IntroductionIn addition to driving, using a motorcycle is a common mode of sedentary transportation in Asian countries, but its associations with lifestyle behaviors remain unknown. The present study aimed to examine the associations of motorcycle use time with lifestyle behaviors in a sample of Taiwanese urban adults. MethodsA cross-sectional survey was administered to Taiwanese urban adults aged 20–64 years. Data on time spent in motorcycle use (none: 0, low: 1–209, high: 210 + min/week), lifestyle behaviors, and sociodemographic characteristics were acquired from 1069 adults in three urban cities. Unadjusted and adjusted logistic regression analysis were used. ResultsAfter adjusting for potential covariates, adults who spent at least 30 min a day on motorcycles were less likely to have sufficient levels of active transportation (odds ratio [OR] = 0.44; 95% confidence intervals [CI]: 0.31–0.62) and less likely to drink alcohol (OR = 0.53; 95% CI: 0.31–0.90) than those who did not. No significant associations of motorcycle use with leisure-time physical activity, sitting time, sleep, current smoking status, and dietary behavior were observed. ConclusionsMotorcycle use is a potential behavioral risk factor for active mode of transportation. Future lifestyle interventions and transportation-related policies may consider reducing motorcycle use time as a possible strategy for health promotion.

Reducing Cyclist Crashes by Assessing the Road Environment: An Application of Google Imagery and Machine Learning

Background: Cycling is an active and sustainable transportation mode, and is associated with health, environmental and societal benefits. Therefore, increasing the use of bicycles is being supported as a transport policy in many countries. However, despite these benefits, cyclists are vulnerable road users and are over-represented in traffic crash casualties compared to other modes of transport. The injury concern can discourage people from adopting cycling as a main transportation mode. Urban infrastructure that caters to cyclists' safety can potentially reduce crashes and therefore, injury morbidity and mortality. Methods: This research uses cyclist crashes recorded by the state road authority from 2010 to 2013 in Greater Melbourne. Exposure data used anonymised bicycle trips recorded by volunteer users of RiderLog smartphone application from 2010 to 2013. Crash locations and control sites were sampled from areas with high cycling exposure. Google Street View maps and satellite images at crash locations and control sites were downloaded to capture information of the road environments where cyclists crash and never crash. Deep learning methods using generative adversarial networks were applied to explore features of road environments associated with cyclist crashes. Results: A number of unique observations were identified namely, that locations that have low crash risk had more green space (trees or grass), and median strips (that separate traffic from opposing lanes on divided roadways) also decreased a cyclist’s crash risk. Road environments with high-rise buildings casting shadows on the roadside are mostly seen in the environment in which crashes occurred. The experiments also identified factors that have been reported previously in the literature and statistical analysis, providing confidence in the presented methods. Such factors include tram tracks, intersections, on-road parking and off-road bicycle paths. Statistical analysis showed 52.6% of crash locations were within 5 metres of a tram line, while this percentage for control sites was 5.6%. Conclusions: This research presents a method that takes advantage of the increasing availability of big datasets, computing power and the advances of deep learning techniques, to analyse the road environments of locations where cyclists crash from a new perspective. The findings give urban planners insights on how streetscapes might be reconstructed to improve safety situations for cyclists. The results also provide transportation engineers and cyclists with visual indications about what kind of streetscapes are safer.

The Impacts of Socio-Cultural Dimensions on Active Transportation Mode Choice across Several Countries Case Study of Kalamazoo (USA), Seoul (South Korea), Jeddah (Saudi Arabia), and Samarra (Iraq)

The Impacts of Socio-Cultural Dimensions on Active Transportation Mode Choice across Several Countries Case Study of Kalamazoo (USA), Seoul (South Korea), Jeddah (Saudi Arabia), and Samarra (Iraq)

Right tree, right place, right time: A visual-functional design approach to select and place trees for optimal shade benefit to commuting pedestrians

Australia tops the world’s charts in occurrence of skin cancer and intensity of heat waves, while concurrently achieving high childhood obesity levels, due in part to low rates of physical activity. These issues converge in the challenge of protecting school children from heat and ultra-violet light exposure whilst simultaneously encouraging them to select active modes of transport for school journeys.This paper describes a new performance-based tree-scape design approach for quantifying shaded walking routes using the pedestrian accessibility modelling tool “PedestrianCatch”, combined with visual-functional tree-scape modelling for both solar impact analysis and qualitative aesthetic outcomes of different street tree-scape designs. We test this design approach on a precinct surrounding a school as a case study.The study results demonstrate the potential for targeted strategic street tree selection and planting in proximity to schools, providing the co-benefits of improved thermal comfort and reduced solar and ultra-violet exposure of children walking home from school. This performance-based design approach offers local government, public health and education departments with a way to mediate multiple and divergent concerns for climate amelioration, transport choices and population health by planting the right tree, positioned to provide shade in the right place at the right time.

Process and determinants of mobility decisions – A holistic and dynamic travel behaviour framework

Countries/cities worldwide are constantly advocating efforts to improve living standards of the country/city, with many aiming to implement/enhance sustainable mobility by promoting usage of mass public transport services, and active modes of transport such as walking and cycling. Active modes of transport have the capability of reducing negative effects of motorisation while providing benefits for individuals and the society. Transport planning is related to travel demand, which is enmeshed within travel behaviour. As users shift from their conventional modes to public or active modes, it is important to understand factors that drive travel behaviour changes. Thus, it is timely to review and possibly expand established travel behaviour theories. In this paper, 29 theories/frameworks are reviewed and a holistic and dynamic “Process and Determinants of Mobility Decisions (PDMD)” framework is introduced. Most existent theories/frameworks lack dynamism thereby making it hard to adapt them to specific travel contexts. To illustrate the dynamic element, examples from two contrasting contexts are presented, mainly Singapore and Asunción, in highlighting usage and application of the PDMD (e.g. developing survey instruments, analysis of polices, and demand analysis). This paper is deemed of aid for researchers and planners to gain a deeper understanding regarding travel behaviour, while such knowledge can be applied to measure travel demand and assessment of factors pertinent to the development of transport policies and programmes.

Adolescents and their aspirations for private car-based transport

The need to transition away from the current car-dominated transport system is well documented in sustainability, health and transportation literatures. Despite growing interest in active and public transport modes, the car still dominates travel preferences for most age groups. There is, however, some evidence of declining preferences for car-based travel for younger generations. In this paper, we use empirical material gathered through a mixed methods study of high school students in Dunedin, New Zealand, to explore the aspirations of adolescents for private car-based transport. We present and interpret findings from a quantitative survey of high school students (n = 1240) and qualitative focus groups (n = 10 focus groups, 54 participants). Contrary to somewhat optimistic reports of reduced aspiration for driving and cars, we find evidence of ongoing preference for car-based transport, and intentions to learn to drive amongst the cohort of young urban millennials. The findings signal the importance of socialisation processes and everyday travel decisions (e.g. mode choice) for long term aspirations to replicate practices of automobility. Such findings have important implications for interventions to increase non-motorised mobilities, and reduce dependence on private vehicles across the transport system.

Exposure to ultrafine particulate air pollution in the school commute: Examining low-dose route optimization with terrain-enforced dosage modelling

Exposure to ultrafine particulate air pollution (UFP) contributes to adverse health effects in sensitive population groups such as children. There is a need to explore UFP exposure in terms of respiratory dosage, which leverages the effect of activity-specific ventilation rates. Commute-related dosage, which describes the dosage that occurs during travel between fixed locations on a routine schedule (i.e. morning school commute), is often underrepresented in air pollution studies. School commutes commonly utilize active transportation modes, and modelling dosage during such commutes requires the development of an approach that captures the influence of travel mode and terrain-enforced ventilation rates. The concept of low-dosage routing is discussed as a solution to UFP dose mitigation; however, it requires an in-depth understanding of the factors that control how dosage is accumulated at different points in the commute. This paper presents a modelling workflow for examining UFP dosage while walking to school. We apply a GIS-based approach that simulates school commute routes for 296,862 homes in Toronto. We use a physical exertion–dependent dosage model that reflects broad-scale variability in physiology, travel velocity, travel gradient, and ambient UFP concentration to evaluate route-specific commute dosage. Our results reveal the patterns of within-route variation in dosage and demonstrate the effects high regional UFP concentration and accelerated physical exertion (i.e. where ventilation rate increases during uphill travel) on creating sections of greater UFP dosage within a route. We use the model to examine UFP dosage under shortest-distance and lowest-dosage routing solutions and find that 13.4% of homes had low-dosage alternative routes, while 86.6% had shortest-distances route that were already the lowest-dosage. Our findings were consistent with studies in the literature that implement a dosage modelling approach. This study highlights the importance of dosage models that account for the dynamic nature of walking speed, ventilation rate, terrain, and pollution concentration along a school commute.

The short-term association between exposure to noise and heart rate variability in daily locations and mobility contexts.

Personal exposure to noise has been shown to be associated with concomitant increases and lagged decreases of short-term heart rate variability (HRV). It is however unknown whether this association differs between contexts defined by visited places or mobility as both exposure sources and expectations may be different between these contexts. Between July 2014 and June 2015, the RECORD MultiSensor Study collected sound level and heart rate data for 75 participants, aged 34-74 years, in their living environments for 7 days using a personal dosimeter and electrocardiography sensor on the chest. Their whereabouts were collected using a GPS receiver and a mobility survey. Short-term concomitant and lagged associations between sound level and HRV parameters were assessed within types of visited places and transport modes using mixed effects models with a random intercept for participants. Increases in sound level were associated with a concomitant increase in all HR/HRV parameters, and delayed decreases in the overall HRV. Interactions between the sound level and the visited place/mobility context were documented. Compared with home, the concomitant association of sound level with HR and rMSSD was doubled within active and private-motorized transport modes, respectively. The association of sound level with HR/HRV varies between visited places/mobility contexts. Future studies investigating these context-dependent associations in ambulatory settings will need to assess additional acoustical factors relating to the visited environments as well as non-acoustical factors impacting the perception of noise.

Health impacts of active commuters’ exposure to traffic-related air pollution in Stockholm, Sweden

IntroductionAddressing walking and cycling commuters, this study aimed to measure personal exposure to traffic-related air pollution and analyze the associated health risks. MethodDiffusive NO2-samplers were worn by 19 participants as they commuted to work in rush-hour traffic in May 2018 in Stockholm, Sweden (in total 336 trips, 197 h). The average NO2-concentration per route was measured, and the health impacts were calculated based on previous epidemiological studies of the association between annual NO2-exposure and premature death. ResultThe measured average concentration per route ranged from 48 to 105 μgNO2/m3, and the average 67 μgNO2/m3 was more than five times higher than the urban background. This corresponded to an annual mean exposure of 16.4 μgNO2/m3, 40% higher than the average exposure at other times. Thus, the increased risk for premature death was 3.3%, with a range of 1.9%–4.8%, as related to assumptions regarding breathing rates and risk relationships between NO2-exposure and premature death. For active commuters in Stockholm in general, this indicated that one-fourth (23%) of the annual inhaled dose of NO2 could be attributed to commuting, and that the risk for premature death increased by 2.5% (1.4%–3.7%) due to air pollution. Note that these results were indicative rather than precise. These relationships may be applicable to active commuters in other cities. ConclusionThe results indicated that active commuting in Stockholm is associated with significant exposure to traffic-related air pollution and that this increases the risk of premature death. It is recommended that future studies consider longer time periods to assess active commuters’ personal exposure with higher precision. Policy implications include greater separation between active commuters and motor traffic, and promotion of behavioral changes in favor of emissions free vehicles and active modes of transport.

Evidence of gendered modal split from Warsaw, Poland

In order to design strategies focused on reducing car use and favoring alternative modes of transportation, it is first necessary to analyze and understand the current use of transport. While current discussions on modal share is present in Polish media and political debate in the context of class conflict, the gender aspect that we propose in this article, provides a completely new perspective. The present study analyzes the diverse relationship that men and women establish with different modes in a post-socialist capital city, such as Warsaw, Poland. The study explores how gender disparities are mitigated or exacerbated when interacted with other variables, such as age, access to private transport, and the presence of children in the household and seeks to understand its impact in terms of sustainability. The results show that Warsaw women have a greater willingness to use transit or active modes of transport, despite having cars available. In contrast, middle-aged women, with preschoolers in the household, are characterized by a high automobile dependency, in comparison to other women. Therefore, they should be especially targeted in future policy making.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BackgroundGPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals’ daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.MethodsWith the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals’ daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.ResultsThe proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult’s daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.ConclusionThis research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals’ daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

Weather and daily mobility in international perspective: A cross-comparison of Dutch, Norwegian and Swedish city regions

With climate change, weather has emerged as an important theme in transport research and planning. Although recent studies demonstrate profound weather effects on mobility in single case study areas, international cross-comparisons are required to reveal how effects differ between cities with different transport and climate regimes. This paper provides an international cross-comparison of the simultaneous effects of weather on destination choices, distances, trip chaining, and transport modes in the urban regions of Utrecht (Netherlands), Oslo and Stavanger (Norway), and Stockholm (Sweden). Hereto, regional subsamples of national travel survey data were linked to meteorological records for the three respective countries and analysed in generalised Structural Equation Models. Our findings generally indicate that light, calm, dry and warm atmospheric conditions may positively affect cycling and the selection of outdoor leisure destinations, while cold and to a lesser extent wet and windy weather conditions reduce cycling and enhance car use and travel optimising strategies like trip chaining, to reduce weather exposures. A positive effect of air temperature on cycling flattens out above 20–25 °C in most of our study areas, but hot weather does not seem to reduce cycling strongly. However, our findings also show considerable regional differences in the effects of weather on mobility. Both general effects and differences are interpreted in relation to geographical context, transport and land use, climate conditions, cultures, habits and adaptations and are discussed to formulate policies to mitigate active transport mode users’ exposures to adverse weather and make walking and cycling (even more) year-round modes.

Exposure to traffic air pollutants in taxicabs and acute adverse respiratory effects: A systematic review.

Taxi drivers could be at risk regarding their respiratory health due to their constant exposure to traffic related air pollutants (TRAP) inside their vehicles. Therefore, we aimed to review pollutants exposure inside taxi vehicles and its determinants as well as its acute adverse respiratory effects. The literature search was done in Pubmed and in Embase. For additional resources we searched manually articles from the reference lists of the selected papers and from Google Scholar. We included only studies in French or in English language meeting the following eligibility criteria: design: observational and quasi-experimental; study population: taxi drivers or taxi commuters, outcome: pollutants levels in taxicabs and/or acute adverse respiratory effects. Data was extracted using tabulation according to the type of the study (exposure or epidemiological). Out of 1753 articles, 21 studies were included. Exposure studies underlined that TRAP concentrations inside taxicabs were higher than their urban background levels and even exceeded those recorded in buses, in trains and when commuting by active transport modes. Overall, their concentrations varied widely between studies depending on the characteristics of the urban environment and the vehicle fleet of each location. Meteorological parameters and ventilation settings appeared to influence pollutants concentrations inside each vehicle. Otherwise, deficiency in epidemiological studies and inconsistencies in their findings restrain our ability to determine the association between acute respiratory effects and exposure to TRAP inside taxicabs. Although studies are heterogeneous, results have shown a high but variable occupational exposure of taxi drivers to TRAP inside their vehicles. However, future researches are required to study short respiratory impact of taxi drivers' exposure to TRAP inside their vehicles.