It is known that air pollution affects human health and commuting environments are significant contributors to the total daily personal exposure to air pollution. With this study we aim at assessing and comparing personal exposure to traffic-related air pollution and related estimated inhaled dose of different typical commuter profiles in real-world scenarios focusing on multimodal commuting and different transport microenvironments. A car driver and two multimodal commuters (cyclist/public transport and pedestrian/public transport commuters), which reached the same destination in the city center, leaving from the same starting point in the metropolitan area of the city, were investigated in the metropolitan area of Milan, Italy. Real-time monitors for the measurement of size-fractionated particulate matter (PM - Aerocet 831-Met One Instrument Inc., Grant Pass, Oregon, USA), equivalent Black Carbon (eBC - Aethlabs, San Francisco, CA, USA), and NO2 (CairClip NO2, Cairpol; La Roche Blanche, France) and time-integrated samplers for the measurement of NO2 and benzene were used. Inhaled dose was estimated as well by applying estimated pulmonary ventilation rates to 1-min exposure measures. The Bootstrapping method was used to resample data and perform more robust comparisons among commuters and microenvironments (MEs). Results of the study could be summarized as follows: (i) travel times of the cyclist were the shortest; (ii) the highest concentrations and estimated inhaled doses were found during morning rush hour; (iii) the cyclist and the car commuter were exposed to the highest overall median values of fractionated PM and benzene, respectively; (iv) cycling MEs presented the highest median concentrations of PM, while the overall median concentration of eBC was higher commuting by car than walking and cycling; (v) the cyclist was the commuter with the highest overall median estimated inhaled dose for fractionated PM, while benzene was the highest for the car driver, and NO2 for the pedestrian; (vi) exposure differences both among microenvironments and commuters diverged comparing morning and evening commuting. Our results suggest that a multi-pollutant approach is necessary to better represent the complexity of personal exposure to traffic-related air pollution in multimodal mobility studies. Moreover, shifting from car driving to multimodal mobility is already a valuable choice for the metropolitan area of Milan considering both exposure and commuting time. However, to further reduce personal exposure and especially estimated inhaled dose of multimodal and active commuters, exposure mitigation interventions in selected MEs, traffic calming, and innovative mobility policies are still needed.

Commuting by car, public transport, and bike : Exposure assessment and estimation of the inhaled dose of multiple airborne pollutants / L. Boniardi, F. Borghi, S. Straccini, G. Fanti, D. Campagnolo, L. Campo, L. Olgiati, S. Lioi, A. Cattaneo, A. Spinazze, D.M. Cavallo, S. Fustinoni. - In: ATMOSPHERIC ENVIRONMENT. - ISSN 1352-2310. - 262:(2021 Oct), pp. 118613.1-118613.12. [10.1016/j.atmosenv.2021.118613]

Commuting by car, public transport, and bike : Exposure assessment and estimation of the inhaled dose of multiple airborne pollutants

L. Boniardi
Primo
;
D. Campagnolo;L. Campo;S. Fustinoni
2021

Abstract

It is known that air pollution affects human health and commuting environments are significant contributors to the total daily personal exposure to air pollution. With this study we aim at assessing and comparing personal exposure to traffic-related air pollution and related estimated inhaled dose of different typical commuter profiles in real-world scenarios focusing on multimodal commuting and different transport microenvironments. A car driver and two multimodal commuters (cyclist/public transport and pedestrian/public transport commuters), which reached the same destination in the city center, leaving from the same starting point in the metropolitan area of the city, were investigated in the metropolitan area of Milan, Italy. Real-time monitors for the measurement of size-fractionated particulate matter (PM - Aerocet 831-Met One Instrument Inc., Grant Pass, Oregon, USA), equivalent Black Carbon (eBC - Aethlabs, San Francisco, CA, USA), and NO2 (CairClip NO2, Cairpol; La Roche Blanche, France) and time-integrated samplers for the measurement of NO2 and benzene were used. Inhaled dose was estimated as well by applying estimated pulmonary ventilation rates to 1-min exposure measures. The Bootstrapping method was used to resample data and perform more robust comparisons among commuters and microenvironments (MEs). Results of the study could be summarized as follows: (i) travel times of the cyclist were the shortest; (ii) the highest concentrations and estimated inhaled doses were found during morning rush hour; (iii) the cyclist and the car commuter were exposed to the highest overall median values of fractionated PM and benzene, respectively; (iv) cycling MEs presented the highest median concentrations of PM, while the overall median concentration of eBC was higher commuting by car than walking and cycling; (v) the cyclist was the commuter with the highest overall median estimated inhaled dose for fractionated PM, while benzene was the highest for the car driver, and NO2 for the pedestrian; (vi) exposure differences both among microenvironments and commuters diverged comparing morning and evening commuting. Our results suggest that a multi-pollutant approach is necessary to better represent the complexity of personal exposure to traffic-related air pollution in multimodal mobility studies. Moreover, shifting from car driving to multimodal mobility is already a valuable choice for the metropolitan area of Milan considering both exposure and commuting time. However, to further reduce personal exposure and especially estimated inhaled dose of multimodal and active commuters, exposure mitigation interventions in selected MEs, traffic calming, and innovative mobility policies are still needed.
Inhalation dose; Microenvironment; Personal exposure; Time-activity pattern; Traffic related air pollution (TRAP); Travel mode
Settore MED/44 - Medicina del Lavoro
ott-2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/874441
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