SPATIAL INHOMOGENEITY IN POLLUTANT CONCENTRATIONS, AND THEIR IMPLICATIONS FOR AIR-QUALITY MODEL EVALUATION

The Southern California Air Quality Study database provides a valuable resource with which to test urban-scale photochemical models and to a chieve a better understanding of the atmospheric dynamics of pollutant formation. The CIT model was evaluated using the SCAQS database accor ding 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 C IT model using the 24-25 June SCAQS episode, providing further evaluat ion of,the model. Results show that the CIT airshed model can follow t he diurnal variations of reactive species and the transport for relati vely unreactive species. The normalized gross error for ozone was 31% in June compared to 38% in August. However, to fully judge model perfo rmance in proper perspective, a question arises: ''How well do the mea surements reflect the air quality surrounding the monitoring station, not just in that location?'' This is an important bur seldom quantitat ively considered factor, not only in model evaluation but in the study of health effects as well. Analyses indicate that individual concentr ation measurements only approximately represent the true volume-averag ed concentrations within a computational grid cell and that significan t spatial variations exist. Thus any evaluation of models using these data sets should take these local variations into consideration. A ser ies of tests found that the local inhomogeneities had a normalized gro ss error in the range of 25-45% depending on the pollutant. In this co ntext, the performance of the CIT model is consistent with known model ing limitations such as emissions inventories and sub-grid scale varia tion of observations. Copyright (C) 1996 Elsevier Science Ltd