Emissions from motor vehicles are a major source of air pollution and studies have shown that exposure to the particulate matter in fresh diesel exhaust is a significant risk to health. Short-term peak exposures are thought to have the greatest impact. Despite the development of several vehicle power-based models to estimate the second-by-second mass emission rates of gaseous pollutant species such as carbon monoxide, carbon dioxide, hydrocarbons and nitrogen oxides, none of these models predicts particulate matter emissions. This paper presents a new technique for modelling the second-by-second particulate matter mass emission rate of a light-duty diesel vehicle. Here, particulate matter emission rates are modelled as a function of both vehicle kinematic parameters (i.e., speed or acceleration) and the mass emission rates of the gaseous co-pollutants. The importance of time alignment in the calibration data is evaluated and a technique for deriving an appropriate lag structure is devised. Various regression models are estimated that provide a good model fit, comparable to existing models of gaseous pollutants. (A) "Reprinted with permission from Elsevier".
Abstract