Abstract
A novel sampling design is proposed that optimizes the spatial configuration of sampling sites and captures maximum intraurban variability in ambient air pollution with a minimum sample size. Unlike the classical sampling design, a deterministic approach is adopted and the redundancy in the site selection is minimized by controlling for spatial autocorrelation. The proposed design was tested and implemented in a medium-sized midwestern city. The analysis suggested that 32 sites were adequate to capture more than 95% of the total variance in airborne particulate 10 µm or less in aerodynamic diameter (PM
10
). A list of 20 households was prepared around each of the 32 sites. Households were approached in order of their distance from these sites until one was recruited for intensive indoor and outdoor air pollution monitoring from spring through fall of 2008. Finally, 30 households located around the optimal sites participated in the study. One set of four photometric and gravimetric samplers was deployed for each indoor and outdoor environment. The average ambient PM
10
concentration (monitored from April to September 2008) at the selected locations was lower but statistically insignificant as compared with the PM
10
(computed using the data from mobile sampling in 2006) at the optimal sites.
