Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities

Okokon, Enembe O.; Yli‐Tuomi, Tarja; Turunen, Anu W.; Taimisto, Pekka; Pennanen, Arto; Vouitsis, Ilias; Samaras, Zissis; Voogt, M.H.; Keuken, Menno; Lanki, Timo

doi:10.1016/j.envres.2016.12.012

Cited by 102 publications

(60 citation statements)

References 34 publications

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“…This contrasts with the findings of Okokon et al [9], who observed a higher exposure to PM 2.5 for the CC with open windows than for public bus and bicycle and with Ham et al [23] who reported similar exposure for private cars and public buses. This could be due to differences in the traffic flow but mostly to vehicular fleet technology; while in Europe around 50% of total light duty vehicles are diesel-powered [26]; in the MCMA around 80% of the light duty vehicle fleet is petrol-powered [27].…”

Section: Personal Exposure To Pm 25 In the Mcmacontrasting

confidence: 57%

“…The median exposure levels reported here for public buses and CC are lower than those reported in the MCMA by Vallejo et al [12] of 101.7 and 62.4 µg m −3 , respectively. However, the average exposure levels reported here are within the range of those reported by Okokon et al [9] (14 ± 5 to 85 ± 39 µg m −3 ) in three European cities for bicycle, public bus and car with open and closed windows. However, comparisons between on-field measurements and ground-based monitoring were not made.…”

Section: Personal Exposure To Pm 25 In the Mcmasupporting

confidence: 42%

“…For instance, Okokon et al [9] addressed exposure to PM 2.5 when commuting in cars with open and closed windows, and by bicycle and bus in three European cities, observing mostly higher exposure for passive transport modes. Similarly, higher exposure to PM 2.5 in Central London for passive as compared to active commute was reported by Adams et al [1].…”

Section: Introductionmentioning

confidence: 99%

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Personal Exposure to PM2.5 in the Megacity of Mexico: A Multi-Mode Transport Study

et al. 2018

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Recurrent personal exposure to ambient PM 2.5 is associated with adverse human health effects, in particular on the respiratory and cardiovascular systems. Here, we present an assessment of personal exposure and inhalation of PM 2.5 for five modes of transport (walking, cycling, public bus (trolleybus and diesel bus), conventional car (CC) and hybrid-electric car (HEC)) and two routes of similar distance, along a major road in the Mexico City metropolitan area (MCMA). Arithmetic average exposure concentrations ranged from 16.5 ± 6.5 µg m −3 for walking to 81.7 ± 9.1 µg m −3 for cycling (henceforth shown as average ±1 SD), with no significant differences with geometric averages. The maximum exposure concentration of 110.9 µg m −3 was observed for the conventional car. The highest exposure concentrations depended on route and the mode of transport, being observed for cycling and walking. The PM 2.5 measurements showed large spatial heterogeneity in the exposure levels for walking and cycling, while public buses and private transport showed less spatial heterogeneity. The greatest peaks in PM 2.5 coincided with 4-way intersections for all modes of transport, being positively influenced by traffic density. The mass of PM 2.5 inhaled depended mostly on the mode of transport, and ranged between 1.0 ± 0.3 and 30.1 ± 14.2 µg km −1 for the HEC and bicycle, respectively. Local area PM 2.5 increments identified as 'residuals' after subtraction of data recorded at the closest fixed monitoring site from exposure concentrations along the studied road suggested that inhalation for bicycle and diesel buses is strongly influenced by vehicular emissions. Residuals estimated for the trolleybus, CC and HEC confirmed a lower inhalation than for the other modes of transport evaluated due to protection by the cabin.

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Section: Personal Exposure To Pm 25 In the Mcmacontrasting

confidence: 57%

Section: Personal Exposure To Pm 25 In the Mcmasupporting

confidence: 42%

Section: Introductionmentioning

confidence: 99%

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Personal Exposure to PM2.5 in the Megacity of Mexico: A Multi-Mode Transport Study

et al. 2018

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“…However, recent findings suggest that in urban areas, a lack of time-activity patterns during pregnancy little influenced exposure estimates [75], although several existing studies reported that personal exposure levels varied in different commuting patterns (e.g. biking, taking a bus, and driving a car) [76,77]. Third, birth weight also increases a lot in last few weeks before delivery, but exposures after the 37th gestational week were not included in DLNMs because of the reasons listed above.…”

Section: Discussionmentioning

confidence: 99%

Associations between maternal weekly air pollutant exposures and low birth weight: a distributed lag non-linear model

Jiang

Zhu

et al. 2018

Environ. Res. Lett.

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When discussing the association between birth weight and air pollution, previous studies mainly focus on the maternal trimester-specific exposures during pregnancy, whereas the possible associations between birth weight and weekly-specific exposures have been largely neglected. We conducted a nested 1:4 matched case-control study in Jinan, China to examine the weekly-specific associations during pregnancy between maternal fine particulate matter (aerodynamic diameter < 2.5 m, PM 2.5 ), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) exposure and birth weight, which is under a representative scenario of very high pollution levels. Ambient air monitoring data from thirteen monitoring stations and daily mean temperature data for Jinan during 2013-2016 were continuously collected. Birth data were obtained from the largest maternity and child care hospital of this city during 2014-2016. Individual exposures to PM 2.5 , NO 2 , and SO 2 during pregnancy were estimated using an inverse distance weighting method. Birth weight for gender-, gestational age-, and parity-specific standard score (BWGAP z-score) was calculated as the outcome of interest. Distributed lag non-linear models (DLNMs) were applied to estimate weekly-specific relationship between maternal air pollutant exposures and birth weight. For an increase of per inter-quartile range in maternal PM 2.5 exposure concentration during pregnancy, the BWGAP z-score decreased significantly during the 27th-33th gestational weeks with the strongest association in the 30th gestational weeks (standard deviation units decrease in BWGAP z-score: −0.049, 95% CI: −0.080 −0.017, in three-pollutant model). No significant association between maternal weekly NO 2 or SO 2 BWGAP z-score was observed. In conclusion, this study provides evidence that maternal PM 2.5 exposure during the 27th-33th gestational weeks may reduce the birth weight in the context of very high pollution level of PM 2.5 .

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“…An important reason for this is the strong spatial variability of BC compared to PM 10 [4]. Most of the experiments focus on quantifying the differences between different commuting modes [5][6][7][8][9][10][11]. General statistics by road type are provided by Dons and colleagues, showing relevant differences by road class, period of the day and period of the week [12].…”

Section: Introductionmentioning

confidence: 99%

A High Resolution Spatiotemporal Model for In-Vehicle Black Carbon Exposure: Quantifying the In-Vehicle Exposure Reduction Due to the Euro 5 Particulate Matter Standard Legislation

Dekoninck

Panis

2017

Atmosphere

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Abstract:Several studies have shown that a significant amount of daily air pollution exposure is inhaled during trips. In this study, car drivers assessed their own black carbon exposure under real-life conditions (223 h of data from 2013). The spatiotemporal exposure of the car drivers is modeled using a data science approach, referred to as "microscopic land-use regression" (µLUR). In-vehicle exposure is highly dynamical and is strongly related to the local traffic dynamics. An extensive set of potential covariates was used to model the in-vehicle black carbon exposure in a temporal resolution of 10 s. Traffic was retrieved directly from traffic databases and indirectly by attributing the trips through a noise map as an alternative traffic source. Modeling by generalized additive models (GAM) shows non-linear effects for meteorology and diurnal traffic patterns. A fitted diurnal pattern explains indirectly the complex diurnal variability of the exposure due to the non-linear interaction between traffic density and distance to the preceding vehicles. Comparing the strength of direct traffic attribution and indirect noise map-based traffic attribution reveals the potential of noise maps as a proxy for traffic-related air pollution exposure. An external validation, based on a dataset gathered in 2010-2011, quantifies the exposure reduction inside the vehicles at 33% (mean) and 50% (median). The EU PM Euro 5 PM emission standard (in force since 2009) explains the largest part of the discrepancy between the measurement campaign in 2013 and the validation dataset. The µLUR methodology provides a high resolution, route-sensitive, seasonal and meteorology-sensitive personal exposure estimate for epidemiologists and policy makers.

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Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities

Cited by 102 publications

References 34 publications

Personal Exposure to PM2.5 in the Megacity of Mexico: A Multi-Mode Transport Study

Personal Exposure to PM2.5 in the Megacity of Mexico: A Multi-Mode Transport Study

Associations between maternal weekly air pollutant exposures and low birth weight: a distributed lag non-linear model

A High Resolution Spatiotemporal Model for In-Vehicle Black Carbon Exposure: Quantifying the In-Vehicle Exposure Reduction Due to the Euro 5 Particulate Matter Standard Legislation

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