Influence of traffic emissions estimation variability on urban air quality modelling

Abstract

The main objective of this work is to analyse how uncertainties in emission data of nitrogen oxides (NOx) and volatile organic compounds (VOC), originated from road traffic, influence the model prediction of ozone (O3) concentration fields. Different methods to estimate emissions were applied and results were compared in order to obtain their variability. Based on these data, different emission scenarios were compiled for each pollutant considering the minimum and the maximum values of the estimated emission range. These scenarios were used as input to the MARIV mesoscale modelling system. Simulations have been performed for a summer day in the Northern Region of Portugal. The different approaches to estimate NOx and VOC traffic emissions show a significant variability of absolute values and of their spatial distribution. Comparison of modelling results obtained from the two scenarios presents a dissimilarity of 37% for ozone concentration fields as a response of the system to a variation in the input emission data of 63% for NOx and 59% for VOC. Far beyond all difficulties and approximations, the developed methodology to build up an emission data base shows to be consistent and an useful tool in order to turn applicable an air quality model. Nevertheless, the sensitivity of the model to input data should be considered when it is used as a decision support tool.