All activities aimed to study primary causes and effects of air pollution cannot disregard the fact that is necessary to have an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks. In the framework of a cooperation between ARPA Sicilia organisation and Department of Engineering, University of Palermo, researches were performed to develop an innovative methodology useful to define environmental similarity maps, aimed at supporting the design of air quality monitoring networks at regional scale. This approach is based on new index, called fuzzy environmental analogy index (FEAI), based on fuzzy theory. FEAI is deduced by combining two indexes: meteorological pressure indicator (MPI) and anthropic pressure indicator (API). MPI allows to investigate, for the examined territory, analogies relevant to meteorological conditions, API emphasizes the importance of impacts related to anthropogenic or natural sources at regional scale. Finally, FEAI applications for a case study, related to Sicily region, Italy, are also described. The obtained results allow to confirm the capability of FEAI index to investigate similarities between neighboring areas, in terms of environmental pressures due to anthropic and natural sources, and so to identify gaps of the monitoring network used to define existing air quality conditions.