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AERMOD results were compared with the reported CALPUFF results to estimate the concentrations and temporal distributions of SO2 and NO2 from Tema Oil Refinery with particlar attention to heavy rainy season (HRS), minor rainy season (MRS), and dry season (DS). Statistical indices, including the fractional bias (FB), geometric mean variance (VG), normalized mean square error (NMSE), index of agreement (IOA), and geometric mean bias (MG), were used to assess the reliability of the models. Overall, AERMOD better predicted ambient SO2 and NO2 levels than the reported CALPUFF model. For SO2, AERMOD showed a good agreement with FB, IOA, and MG while CALPUFF showed a good prediction in NMSE and VG. Also, AERMOD predicted NO2 well with NMSE, IOA, MG, and VG compared with FB for CALPUFF. The MRS results showed higher hourly maximum concentrations (107.4 µg/m3 for SO2 and 31.7 µg/m3 for NO2). Maximum daily concentrations were slightly higher in HRS (37.7 µg/m3 for SO2 and 9.6 µg/m3 for NO2) compared to MRS and DS. The performace of the models may provide a better understanding for future epidemiological studies.
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Amoatey et al. (2018) studied this question.
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