Measurement and Modeling of Ground-Level Ozone Concentration in Catania, Italy using Biophysical Remote Sensing and GIS

dc.contributor.authorFamoso, Fabio
dc.contributor.authorWilson, Jeffrey S.
dc.contributor.authorMonforte, Pietro
dc.contributor.authorLanzafame, Rosario
dc.contributor.authorBrusca, Sebastian
dc.contributor.authorLulla, Vijay
dc.date.accessioned2019-03-05T19:48:08Z
dc.date.available2019-03-05T19:48:08Z
dc.date.issued2017
dc.description.abstractThis experimental study examined spatial variation of ground level ozone (O3) in the city of Catania, Italy using thirty passive samplers deployed in a 500-m grid pattern. Significant spatial variation in ground level O3 concentrations (ranging from 12.8 to 41.7 g/m3) was detected across Catania’s urban core and periphery. Biophysical measures derived from satellite imagery and built environment characteristics from GIS were evaluated as correlates of O3 concentrations. A land use regression model based on four variables (land surface temperature, building area, residential street length, and distance to the coast) explained 74% of the variance (adjusted R2) in measured O3. The results of the study suggest that biophysical remote sensing variables are worth further investigation as predictors of ground level O3 (and potentially other air pollutants) because they provide objective measurements that can be tested across multiple locations and over time.en_US
dc.identifier.citationFamoso, F., Wilson, J., Monforte, P., Lanzafame, R., Brusca, S., & Lulla, V. (2017). Measurement and Modeling of Ground-Level Ozone Concentration in Catania, Italy using Biophysical Remote Sensing and GIS, 12(21), 12.en_US
dc.identifier.issn0973-4562
dc.identifier.urihttps://hdl.handle.net/1805/18533
dc.language.isoen_USen_US
dc.publisherResearch India Publicationsen_US
dc.subjectGISen_US
dc.subjectOzone Concentrationen_US
dc.subjectRemote Sensingen_US
dc.subjectCataniaen_US
dc.titleMeasurement and Modeling of Ground-Level Ozone Concentration in Catania, Italy using Biophysical Remote Sensing and GISen_US
dc.typeArticleen_US
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