Fine airborne particulate matter (PM) is a major public health concern, with road traffic thought to play a particularly critical role in this problem. Minute-by-minute data of PM exposure and travel speed were recorded for an urban car trip in Sydney using a combination of Global Positioning Systems (GPS) and real-time particle monitors which allows researcher to observe how personal exposure to fine particulate inside the car varies over a trip. Timeseries Box-Jenkins transfer function modelling is used as a tool to assess the relative importance of travel speed (which is known as a proxy for traffic conditions) and meteorological conditions on PM exposure level. Time-series Box-Tiao intervention modelling is also employed to examine the experimental effects on PM exposure level due to in-vehicle environments (ventilation open/closed, air-conditioning on/off), built environments (residential, commercial, industrial) along the study route and time-of-day (AM/PM). During the analysis, unusual peak-exposure levels that occur due to specific events (e.g., following a smoky vehicle or smells entering the vehicle) are statistically detected and controlled for. The results of the transfer function modelling show that travel speed has a statistically negative relationship with PM exposure level. The intervention analysis reveals that the in-vehicle environment, built environment and time-of-day all have significant effects on the PM exposure level. (a) For the covering entry of this conference, please see IRRD abstract no. E216410.
Abstract