LAUSR

Abstract In this paper three well known Gaussian dispersion models have been evaluated for a case study of a steel plant using complete and incomplete upper air meteorological data. In developing countries, the availability of surface and upper air meteorological data is limited. AMS/EPA Regulatory Model (AERMOD), Advanced Dispersion Modeling System (ADMS) and Industrial Source Complex Model (ISC3) have been evaluated for both real and estimated upper meteorological data and the results have been compared with field measurements both in the horizontal and vertical directions. The results show significant differences in predicted concentrations when modeling with real (actual) and estimated upper meteorological data. The differences ranged from 100% to 450%. Comparison of model performance suggests that AERMOD and ADMS with real meteorological data produce consistent results in the horizontal direction while ISC3 output over-predicts in general. In AERMOD and ISC3 the predicted concentrations have a similar trend of variation in the vertical direction but in ADMS the concentration variation in the vertical direction exhibited different trends. In general, the ADMS predicted concentrations under-estimated field observations. The paper suggests that upper data must be used for modeling and the default values must be used with care. In absence of upper meteorological data, users could estimate upper meteorological data by different available algorithm rather than only default option of models.