variable of concentration, gives a complete picture of spatial variations
of the polluting factor under investigation, covering a whole
model domain, thus not depending on any monitoring site. For this
reason the method is sound and appropriate for a preliminary
evaluation of spatial representativeness, and it is well suited to
appropriately design new air quality monitoring networks.
Moreover, this study shows that it is really important to make
some step ahead in integrating atmospheric dispersion models into
GIS, and coupling different technologies/approaches, i.e. by
implementing new advanced interfaces as already done in Piersanti
et al. (2012) for the model validation, in order to develop more
flexible techniques of air pollution understanding.
Acknowledgements
This work is part of the Cooperation Agreement for the starting
up the Italian National Network of Special Purpose Monitoring
Station, funded by the Italian Ministry for Environment and Territory
and Sea (CUP F57G1VVVVV50001), which the authors wish to
thank also for providing MINNI project results.