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Several studies have suggested that specific respiratory benefits may be obtained by experimenting with forests and other natural resources. Despite this, forests have never been considered according to this potential. This study aims to compare municipalities considering the absence / presence of tree species that generate potential "above the threshold" respiratory benefits. Methods: The Autonomous Region of Friuli Venezia Giulia in Italy was assumed as a research area. The vision based on natural resources (NRBV) has been adopted, which postulates the strategic role played by natural resources in achieving both above-average (therefore "precious") and "concentrated" (therefore "rare" among competitors) performances. The literature reviews dealing with the potential respiratory benefits of organic biogenic compounds (BVOCs) emitted from trees, published as part of the "forest therapy" research, were adopted. Three analysis models were outlined that evaluate tree species on the basis of their potential respiratory benefits in terms of "holistic-general" (P1), "particular" (P2) and "dynamic" (P3). The resulting overall potentials of tree species were assessed using the well-established Hollerith distance (HD) model. Tree species were rated "1" when meeting one or more of the 58 potential respiratory benefits. The municipalities have been classified considering the area covered by forest types whose dominant tree species obtain above-average potential respiratory benefits. The QGIS software was adopted to refer geographically to the results obtained. Results: (P1) Valuable municipalities include those covered by coniferous and deciduous forests; (P2–3) The municipalities that obtain the maximum potential respiratory benefits, both in particular and dynamic terms, have been mapped. Discussion: The ongoing forestry initiatives in the pre-selected municipalities can be further improved and diversified in a targeted way. Conclusions: Despite some limitations mostly incorporated in the concept of "model", this study allows scholars to reduce uncertainties in the location of municipalities in which to conduct experiments on a local scale.

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