Exploring the effects of ventilation practices in mitigating in-vehicle exposure to traffic-related air pollutants in China.

ABSTRACT

In most major cities of China, commuters inevitably spend a considerable amount of time in vehicle cabins due to the escalation of traffic congestion and a rapidly increasing vehicle population. The in-vehicle microenvironment that is in close proximity to traffic emission sources is at particular risk of increased exposure to traffic-related air pollutants (TRAPs). In this study, a mobile measurement campaign was carried out to investigate in-vehicle exposure to TRAPs in China where the elevated level of TRAPs has drawn worldwide attention in recent years. Our analysis demonstrates that vehicle ventilation mode (i.e., mechanical ventilation, natural ventilation, hybrid ventilation, and infiltration) played a critical role in determining the level of in-vehicle exposure. Although the outside air (OA) mode of mechanical ventilation provided adequate air exchange to passengers, the average in-vehicle PM2.5 and UFP concentrations (119 µg/m3 and 97,227 cm-3 on freeway, and 93 µg/m3 and 42,829 cm-3 on local roadway) during a 20-min sampling period were observed at the level that are markedly greater than those from studies conducted in the U.S., posing a serious health threat to vehicle occupants. We elaborated how our results collected in China with a significantly more polluted on-road environment differ from existing studies in terms of ventilation and driving conditions. In addition, we made the first effort to examine in-vehicle exposure under hybrid ventilation that is a common ventilation practice in everyday commute to potentially reduce symptoms similar to sick building syndrome (SBS). Our data indicate that vehicle occupants under hybrid ventilation are at much greater risk of TRAPs exposure if operating in a polluted on-road environment, and we call for future research on automated ventilation system with advanced window control especially for vans and buses with a large cabin volume.