An intercomparison study has been performed with six empirical ozone interpolation procedures to predict hourly concentrations in ambient air between monitoring stations. The objective of the study is to use monitoring network data to empirically identify an improved procedure to estimate ozone concentrations at subject exposure points. Four of the procedures in the study are currently used in human exposure models (nearest monitors daily mean and maximum, regression estimate used in the U.S. Environmental Protection Agency's (EPA) pNEM, and inverse distance weighting), and two are being evaluated for this purpose (kriging in space and kriging in space and time). The study focused on spatial estimation during June 1-June 5, 1996, with relatively high observed ozone levels over Houston, Texas. The study evaluated these procedures at three types of locations with monitors of varying proximity. Results from the empirical evaluation indicate that kriging in space and time provides excellent estimates of ozone concentrations within a monitoring network, while the more often used techniques failed to capture observed pollutant concentrations. Improved estimation of pollutant concentrations within the region, and thus at subject locations, should result in improved exposure modeling.