Spatial design for air pollution measurement network optimization
Abstrakt
We consider a spatial design problem related to optimal expansions of existing air pollution networks on arbitrary domain that is discretized via a fine equidistant grid. We work with a natural min-max optimality criterion that seeks placement of a new design (measurement) point in such a way that it minimizes the worst-case spatial prediction error. Hence it gives the best placement with respect to the worst map quality based on interpolation from a formal statistical model that we specify and that acknowledges vastly different statistical behavior of the concentration field over the background locations and in the urbanized areas. While the maximum is always evaluated over the whole grid, the actual measurement placement can be restricted to an arbitrary subset. This work was supported by the TACR project ARAMIS No. SS02030031.