# Odor Impact Assessment via Dispersion Model: Comparison of Different Input Meteorological Datasets
## 2 Materials and Methods
### Calmet
#### 2.2.1 Meteorological Data  
The collection and preprocessing of meteorological data are of fundamental importance for environmental impact assessment studies [39]. The detail and quality of the input data requirements depend on the complexity of the model. Sophisticated, non-steady-state models--such as Lagrangian puff models like the CALPUFF/CALMET modeling system--can process a 3D dataset of meteorological data. In principle, meteorological data could be obtained from meteorological stations (surface + upper air) or from prognostic models. The implementation of prognostic data appears to be necessary in certain locations where nearby meteorological stations are not available. In this study, WRF prognostic data (CALPUFF \"NO-OBS\") as well as observational data, i.e., one surface station and one upper air station (CALPUFF \"OBS\"), are both implemented as input meteorological data to run the simulations. Additionally, CALPUFF \"HYBRID\" combines surface observational data and upper air prognostic data. The meteorological prognostic data adopted for CALPUFF \"NO-OBS\" and CALPUFF \"HYBRID\" are 3D hourly data processed by the WRF (Weather Research and Forecasting) model with a spatial resolution of 1 km and 3 km, respectively, for the Italian and Cuban domains for the reference year 2016. For the Italian domain, the WRF data are collected by \"Lakes Environmental\", while the Cuban ones are processed by the \"Centre for Atmospheric Physics\" (Meteorology Institute of Cuba). The WRF configuration adopted in this study is based exclusively on analysis data from the Global Forecast System (GFS) model, meaning that no meteorological observation data were incorporated using any data assimilation method into the model. Consistently, for the observed data, surface and upper air measurements from meteorological stations were considered for the same reference year for both the Cuban and Italian domains. The reference year (i.e., 2016) was chosen as the most recent year with a complete meteorological dataset available for both domains. In both domains, the simulation period covers the entire year of 2016. For the Cuban site, hourly surface meteorological observations for wind speed (Ws), wind direction (Wd), atmospheric pressure (Patm), air temperature (T), relative humidity (RH), and cloud cover (CC) were measured by the surface station Aguada de Pasajeros AGP, Cienfuegos (22.37\({}^{\circ}\) N, 80.83\({}^{\circ}\) W), located in the eastern part of the domain. The height of the meteorological station is 10 m above ground level. To fulfill the standard quality criteria set by the CALMET meteorological pre-processor [38], upper air data were obtained from the upper station located in Key West KW, Florida, positioned about 240 km away from the domain (24.55\({}^{\circ}\) N, 81.75\({}^{\circ}\) W) due to the limited raw-insonde data available in this region. Despite this station being located more than 200 km away, numerous authors have used these data to represent the upper air in Cuba [40; 41] based on the reports of [PERSON] [42] and [PERSON] [43], who assert that upper air observations separated by distances of up to 2000 km and 1000 km, respectively, can be assumed without any notable error. For the Italian site, hourly surface meteorological observations of Wd, Ws, T, Patm, and RH were acquired by the Regional Agency for Environmental Protection (ARPA Lombardia, Milan, Italy) for the station of Landriano Cascina Marianna LDR (45.32\({}^{\circ}\) N, 9.27\({}^{\circ}\) E), located inside the domain, in the same position as the Cuban surface station with respect to the corresponding SW corner. The height of the meteorological station is 10 m, as is the case for the monitoring station in Cuba. The measuring network of ARPA Lombardia does not provide CC data. Instead, the CC was obtained from the METAR meteorological database of Iowa State University for the station of Milano Linate International Airport LIML (45.43\({}^{\circ}\) N, 9.28\({}^{\circ}\) E), 13 km away from the domain.