Studying human exposure to vehicular emissions using computational fluid dynamics and an urban mobility simulator: The effect of sidewalk residence time, vehicular technologies and a traffic-calming device

A computational system consisting of an urban mobility simulator, validated fluid dynamics and an integral exposure model, is proposed to obtain cyclist and pedestrian exposure to PMx and NOx. Pedestrian activities in the urban anthroposphere include walking and running. The computational experiments take place in a computergenerated urban canyon, subject to emissions fromdiesel and gasoline Euro 5 and Euro 6 vehicular technologies, in continuous and stop-and-go traffic scenarios, and three wind directions at two speeds. The exposure time in the computational domain of slow and fast pedestrians were obtained. Slow pedestrians had exposure times around 17% more than fast pedestrians due to their higher sidewalk residence time. Runners and cyclists decreased their exposures by 57% and 73% respectively compared with walkers. Two traffic scenarios are implemented: one due the presence of a hump and another without a hump. The presence of the hump, increased exposure and fuel consumption by 60% per heavy duty vehicle, about 44-48% per light duty vehicle and about 54-71% per passenger car. Vehicular technology had a large influence on exposure: Heavy duty-Euro 6 vehicle decreased 86% the exposure to PM2.5 and 66% to NOX with respect to Euro 5. The proposed computational system provides information on how wind velocity influenced the inhomogeneous pollutant distribution in the street-canyon, causing exposure to be dependent on pedestrian route location. Microscale sidewalk areas in the order of meters containing higher concentrations were thus located. The cleanest routes in the urban canyon were identified. When the wind intensity doubled from 2 to 4 m s(-1), exposure concentration decreased around 45%. The proposed system provides a computational platform to study urban atmospheric fluids, scenarios such as pedestrian routes, vehicular technologies, traffic velocities, meteorological conditions and urban morphology affecting pollution exposure. (C) 2019 Published by Elsevier B.V.