Spatial inhomogeneity in pollutant concentrations, and their implications for air quality model evaluation

Abstract The Southern California Air Quality Study database provides a valuable resource with which to test urban-scale photochemical models and to achieve a better understanding of the atmospheric dynamics of pollutant formation. The CIT model was evaluated using the SCAQS database according to traditional model performance guidelines. A first application, reported previously, focused on model enhancement and application of the model to the 27–29 August 1987 episode. This study evaluates the CIT model using the 24–25 June SCAQS episode, providing further evaluation of the model. Results show that the CIT airshed model can follow the diurnal variations of reactive species and the transport for relatively unreactive species. The normalized gross error for ozone was 31 % in June compared to 38% in August. However, to fully judge model performance in proper perspective, a question arises: “How well do the measurements reflect the air quality surrounding the monitoring station, not just in that location?” This is an important but seldom quantitatively considered factor, not only in model evaluation but in the study of health effects as well. Analyses indicate that individual concentration measurements only approximately represent the true volume-averaged concentrations within a computational grid cell and that significant spatial variations exist. Thus any evaluation of models using these data sets should take these local variations into consideration. A series of tests found that the local inhomogeneities had a normalized gross error in the range of 25–45% depending on the pollutant. In this context, the performance of the CIT model is consistent with known modeling limitations such as emissions inventories and sub-grid scale variation of observations.