Abstract
This study estimates air pollution at urban background level for Quito, Ecuador, using the Urban Background Model (UBM) developed at Aarhus University, Denmark. Hourly concentrations of CO, NO2, NOx, O3, PM2.5 and SO2 were calculated for the year 2009. UBM performance is evaluated at six monitoring locations. The air pollution emission inventory was scaled, using calibration factors, until modeled concentrations were in line with observations. Predicted values were graphically and statistically evaluated by comparison to measurements. The statistical assessment is conducted for: Fraction of predictions within a factor of two of the observations (FAC2), Fractional mean bias (FB), Normalized mean-square error (NMSE) and Normalized absolute difference (NAD). Results show that the UBM model successfully predicts concentrations of CO, NO2, NOx, O3 and PM2.5 while the predicted SO2 concentrations are unsatisfactory. PM2.5 modeling meets the criteria of acceptance, but their results depend largely on the regional levels, so the quality of this information is extremely relevant. The UBM model was applied for the years 2008 and 2010 using meteorological data retrieved from the modeling sites with emissions and calibration factors derived for the year 2009, showing a performance similar to that of 2009. The findings confirm the applicability of UBM to predict air pollution at the urban background level in Quito. Satisfactory results are obtained by applying meteorological data derived from any of the available monitoring stations. The unsatisfactory results for SO2 suggest that emission data should be reviewed and that this cannot be obtained simply by scaling.