In this paper, we present a criticality index that is simple to
implement and quantifies the importance of each monitor in the
network. Currently, the approaches to evaluating monitors within
an existing network are limited to the repurposing of techniques for
locating entire networks, which are complex and challenging to
implement (Ainslie et al., 2009). Our index defines the criticality of
the monitoring units with historical data, spatial interpolation and
simulations of reduced monitor configurations to determine the
effect on spatial air pollution estimates. The index emphasizes the
correct estimation of conditions above an air quality guideline,
which are often set by the government of a region or through the
adoption of global standards.