Role of weather data in validating air quality models

Abstract

Air quality dispersion models have been used to predict the ground level concentrations (GLC) of air pollutants such as Particulate matter, SO2 and NOx etc. Industrial Source Complex Short Term Version 3 (ISCST3), a dispersion model developed by United States Environment Protection Agency (USEPA) is widely adopted in India to predict the GLC due to emissions from the industries. American Meteorological Society/Environment Protection Agency Regulatory Model Improvement Committee has developed an improved version model, Aermic dispersion Model (AERMOD) to predict the GLC. USEPA has adopted AERMOD as its regulatory model since 2005. This study examines the suitability of AERMOD for Indian conditions especially for a rural area near by Chennai. The validity of AERMOD model is examined considering a point source of emission from an industry which uses furnace oil as fuel. The study has been conducted to compare the predicted value using AERMOD and the actual value of GLC by field observations. The study also used ISCST3 to predict the GLC and the values obtained have been compared between the models. This study aimed at the comparison of the AERMOD and ISCST3 models for ambient air quality prediction. Further in this paper, local meteorological data have been used to a greater accuracy to validate the models AERMOD and ISCST3 for the point source of emission of SO2. It is clear from this study that weather data playing a vital role in validation of model and to predict the air pollution concentration in a particular station. And also it is clear that both AERMOD and ISCST3 have under predicted the concentrations than that of the observed value and the accuracy of the predicated data is mainly depending on the weather data.