1.1 ,This guide provides techniques that are useful for the comparison of modeled air concentrations with observed field data. Such comparisons provide a means for assessing a model's performance, for example, bias and precision or uncertainty, relative to other candidate models. Methodologies for such comparisons are yet evolving, hence, modifications will occur in the statistical tests and procedures and data analysis as work progresses in this area. Until the interested parties agree upon standard testing protocols, differences in approach will occur. This guide describes a framework, or philosophical context, within which one determines whether a model's performance is significantly different from other candidate models. It is suggested that the first step should be to determine which model's estimates are closest on average to the observations, and the second step would then test whether the differences seen in the performance of the other models are significantly different from the model chosen in the first step. An example procedure is provided in Appendix X1 to illustrate an existing approach for a particular evaluation goal. This example is not intended to inhibit alternative approaches or techniques that will produce equivalent or superior results. As discussed in Section 6, statistical evaluation of model performance is viewed as part of a larger process that collectively is referred to as model evaluation.