VOC speciation of vehicle emissions: what is the impact on air quality modelling?

A numerical model named AZUR has been developed by IFP-EDF-LISA to simulate regional episodes of photochemical pollution. This model requires data on pollutant emissions defined at space and time scales corresponding to one s quare kilometre and one hour. In addition to the amount of emitted pollutan ts, the knowledge of their chemical composition is of prime interest for co rrectly representing air chemistry through detailed modules such as MOCA. I t is therefore important to know the emitter type in order to assign an app ropriate chemical composition to various pollutant flows. IFP has developed a set of methods whose aim is to determine an inventory of traffic-related pollutants (CO, SO2, particles, VOCs and NOx). They are based on the knowl edge of the vehicle density and average traffic flow at the site of each me asurement point. Density and speed data were converted into pollutant flows using emission factors (in grams of pollution per km travelled) as functio ns of speed. The emission factors are specific to each vehicle category. Se parate counts for each category enabled us to assign, as previously mention ed, a specific chemical composition (in particular for VOCs) to emissions i n each category. But very few data are available regarding the VOC emission speciation as a function of different vehicle types. Moreover, these data are very often associated with a specific driving cycle, which does not nec essarily correspond to cycles used for determining emission factors. The pu rpose of this paper is to evaluate the impact of these uncertainties in VOC speciation. Air quality in the Paris area will be simulated using the AZUR model with various VOC distributions. These distributions, taken from the literature, are either measurements carried out using specific driving cycl es or overall values. Ozone profiles will be analysed and compared in both urban and rural areas to assess the sensitivity of results to the VOC distr ibution related to road traffic.