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Haqa Amin ul, Nadeema Qaisar, Farooqa Amjad, Irfana Naseem, Ahmada Masroor, Rizwan AliaMuhammad, Sadiq KhanbSadaf
Parameterization study of CALMET/CALPUFF modeling system was performed in a short term short range release scenario over complex terrain in Pakistan. A comprehensive dataset developed through a tracer field experiment was used to analyze its performance in a mountainous region in Islamabad city. In most complex terrain regions of world and especially in Pakistan, scarcely located observational stations cannot provide spatial variability of meteorological fields, especially the turbulent parameters over complex terrain. Therefore, use of prognostic model seems to be imperative for adequate meteorological input to dispersion model. For this purpose meso-scale meteorological model WRF was coupled with CALPUFF to provide 3D meteorological input. Parameterization study of CALMET and CALPUFF was performed to find out the best configuration of model for current meteorological and topographical conditions of test site. In this regard different computational variants in CALMET/CALPUFF were tested and their impact on pollutant concentration was analyzed using standard statistical indices. The best results were achieved for the CALMET grid resolution of 300 m, SRTM3 dataset and high temporal resolution of meteorological input into CALPUFF. The selection of appropriate dispersion coefficients is imperative for simulations over complex terrain. Dispersion coefficients based on similarity theory provided better results as compared to dispersion coefficients derived from Pasquill-Gifford (PG) curves in short term release scenarios. Model strongly under-predicts at lower concentration at receptors away from source and starts to perform better at higher concentrations. However, peak concentration was slightly underestimated in this experiment. CALPUFF model has proven to fulfill criteria for a ‘good’ dispersion model for application over complex terrain for short term short range release scenarios, when used with prognostic meteorological data option only.