Wednesday, 12 January 2000
Interpolation of ozone data from a limited monitoring network is often used for the analysis and display of ozone concentration patterns, the preparation of gridded initial conditions for air quality modeling, and the estimation of health and ecosystem effects. Interpolation/extrapolation of data from an existing monitoring network, however, may not provide realistic concentration estimates, especially over long distances, over variable terrain, or for areas with differing emissions and transport characteristics.
To avoid the unrealistic interpolation of observed ozone data to unmonitored areas for a variety of health effects and air quality related analyses, we have developed a "homology mapping" technique. Homologues sites are assigned to unmonitored areas based on similarities in geographical, land-use, and meteorological characteristics. Observed data from the homologue sites are then used to represent concentrations, within the unmonitored areas. Development, testing, and application of this technique for a variety of analyses is discussed in this paper.
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