Prediction of Ground Level Concentrations of No x in a Thermal Power Project using ISCST3 Model
Background: Present study deals with the prediction of nitrogen oxides in the vicinity of the Rayalaseema Thermal Power Project, Andhra Pradesh, India. It provides information to the public and the control agencies to efficiently implement the control strategies of the air quality management program. Methods: In this prediction, the industrial source complex short term version 3 (ISCST3) model was used. ISCST3 is the preferred model of USEPA. ISCST3 is a refined dispersion modeling technique using site specific input data. Findings: Predictions were made around the power plant with the radius of 10,000 meters; for the period of one year from June 2012 to May 2013. ISCST3 and Golden software surfer version 8 was used to produce Isopleths and 3 Dimensional view of NOX in the vicinity of the Rayalaseema Thermal Power Project. Similarity beside measurements of Ambient Air Quality Monitoring Stations (AAQMS) was made. Genuine results were found well with measured data. Coefficients of determination (R2) were found in the range between 0.76 to 0.96. The ISCST3 model can be used for NOX prediction with good accuracy. Application and Improvement: Further forecasting can be carried out in coal fired power stations for using wide ranging parameters, which will have significant impact on human health and environment using ISCST3 modeling technique.