Assessing the exposure of an individual or population is a challenging statistical task. Borrowing from the concept of the genome in genetics, recently the concept of an exposome has emerged to help explain the complexities of exposure assessment and guide research in this area. According to the Centers for Disease Control and Prevention, “The exposome can be defined as the measure of all the exposures of an individual in a lifetime and how those exposures relate to health.” The simplest algorithm to estimate concentration at an unmonitored locations is to use the measured value for the nearest monitoring location. The estimated nearest-neighbor concentration surface is then piecewice constant over Voronoi polygons around the monitors. This is a special case of K-nearest neighbor (KNN) interpolation. Inverse distance weighting (also known as kernel smoothing) is an extension to KNN that weights locations according to their distance from the prediction location.