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

Abstract

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.

Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

“…This evolution is a driving force in the research field on cyclists' exposure to air and noise pollution. Thus, new tools have been made accessible to researchers to address new research goals like estimating the difference in exposure for similar trips according to the transport mode [9,26], measuring the short term health impact of cyclists' exposure to air pollution [27], or modelling and predicting cyclists' exposure in urban environments [18][19][20]28,29].…”

Replacing Diesel Buses with Electric Buses for Sustainable Public Transportation and Reduction of CO₂ Emissions

“…In their study, Hernandez-Paniagua et al [34] used boxplot analysis to highlight the statistical values of pollutant emissions, comparing emissions from urban areas with diesel bus transportation with emissions from areas with trolleybus transportation (electric propulsion system).…”

Fine particulate matter exposure in four transport modes of Greater Cairo

“…The event was considered as an anomaly that would have skewed the averaged concentrations. However, it indicates a higher susceptibility of cyclists to such extreme pollution on-road events that can commonly occur on congested routes in urban areas (Hernández-Paniagua et al 2018). Other studies have also reported that cyclists are in the most vulnerable position in terms of traffic pollution exposure (Chaney et al 2017) where it was estimated that an hour of cycling in Delhi during MP caused 40% higher PM2.5 inhaled dose than an entire-day's dose in cities like Tokyo, London and New…”

“…(2020) reported that PM2.5 exposure concentrations for walking and cycling were quite similar and were notably higher than for bus and car. Several studies concluded that the largest exposure to PM2.5 was observed during cycling; however, the route choice can reduce exposures by 15-75% (Ham et al, 2017;Hernández-Paniagua et al, 2018). It was clear from these studies that fixed-site monitoring did not properly reflect personal exposure, especially during heavy traffic times, where PM2.5 levels are significantly influenced by the mode of travel (Frey et al, 2020;Huang et al, 2012;Kaur and Nieuwenhuijsen, 2009;Qiu et al, 2017).…”