Open Journal of Air Pollution, 2016, 5, 27-36 Published Online March 2016 in SciRes. http://www.scirp.org/journal/ojap http://dx.doi.org/10.4236/ojap.2016.51003 How to cite this paper: Affum, H.A., Akaho, E.H.K., Niemela, J.J., Armenio, V. and Danso, K.A. (2016) Validating the Califor- nia Puff (CALPUFF) Modelling System Using an Industrial Area in Accra, Ghana as a Case Study. Open Journal of Air Pollution, 5, 27-36. http://dx.doi.org/10.4236/ojap.2016.51003 Validating the California Puff (CALPUFF) Modelling System Using an Industrial Area in Accra, Ghana as a Case Study H. A. Affum 1* , E. H. K. Akaho 2 , J. J. Niemela 3 , V. Armenio 4 , K. A. Danso 2 1 Department of Nuclear Sciences and Application, School of Nuclear and Allied Sciences, University of Ghana, Legon, Ghana 2 Department of Nuclear Engineering, School of Nuclear and Allied Sciences, University of Ghana, Legon, Ghana 3 Applied Physics Section, International Centre for Theoretical Physics, Trieste, Italy 4 Dipartimento di Ingegneria e Architettura, Universita di Trieste, Trieste, Italia Received 20 January 2016; accepted 28 March 2016; published 31 March 2016 Copyright © 2016 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract The performance of the California Puff (CALPUFF) modelling system has been evaluated using a case study in Ghana. The performance evaluation consisted of a quantitative comparison of dispersion simulation results of SO 2 and NO 2 with measurements at the Tema Oil Refinery, and meteorological simulation results with observations from the Tema Meteorological Station, both in the Greater Ac- cra region of Ghana. Four statistical indicators—Index of Agreement (IOA), Fractional Bias (FB), Normalized Mean Square Error (NMSE) and the Pearson correlation coefficient(R) employed in the assessment indicate sufficient reliability of both CALPUFF and its meteorological simulator, CALMET. IOA values of 0.73 and 0.67 and FB values of 1.65 and 1.42 were obtained for SO 2 and NO 2 respec- tively. IOA between measured and modelled emissions were 0.72 and 0.69 for SO 2 and NO 2 respec- tively. The correlations between the simulated and observed emission were 0.66 and 0.08 for SO 2 and NO 2 respectively. An IOA value of 0.66 was obtained for both wind speed and wind direction with correlations of 0.29 and 0.58 in comparison with observations from the meteorological station. Keywords Performance Evaluation, Emissions, Dispersion, Observations 1. Introduction Dispersion models are useful tools in assessing the impact of emissions to air from a given source. However, in * Corresponding author.