Litcius/Paper detail

Spatial-temporal prediction of ambient nitrogen dioxide and ozone levels over Italy using a Random Forest model for population exposure assessment

Camillo Silibello, Giuseppe Carlino, Massimo Stafoggia, Claudio Gariazzo, Sandro Finardi, Nicola Pepe, Paola Radice, Francesco Forastiere, Giovanni Viegi

2021Air Quality Atmosphere & Health40 citationsDOI

Topics & Concepts

Random forestEnvironmental scienceAir quality indexNitrogen dioxidePollutantPopulationImage resolutionTemporal resolutionCMAQMeteorologyComputer scienceGeographyMachine learningEnvironmental healthPhysicsArtificial intelligenceChemistryQuantum mechanicsOrganic chemistryMedicineAir Quality and Health ImpactsAir Quality Monitoring and ForecastingAtmospheric chemistry and aerosols
Spatial-temporal prediction of ambient nitrogen dioxide and ozone levels over Italy using a Random Forest model for population exposure assessment | Litcius