Validating the California Puff (CALPUFF) Modelling System Using an Industrial Area in Accra, Ghana as a Case Study

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 Accra 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 respectively. IOA between measured and modelled emissions were 0.72 and 0.69 for SO 2 and NO 2 respectively. 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.

Accuracy Assessment of WRF Model in the Context of Air Quality Modeling in Complex Terrain

“…Its applications include, among many others, short-term meteorological forecasting [13,14], climatologic research [15,16], prediction of extreme events such as hurricanes [17,18], wind power forecasting [19,20] and air quality assessment and forecasting [2,5,[21][22][23][24][25][26][27][28][29][30]. Apart from regional applications, the results from the WRF model are implemented in air quality modeling systems on a local scale (<50 km) for air quality impact assessment, e.g., [3,5,[20][21][22][23][24] in the areas of urban agglomerations in order to assess air quality, determine the location of air quality monitoring stations and to quantify the contribution of each emission source in air quality deterioration [31][32][33][34][35][36][37]. Many of the aforementioned studies focused on conducting an air quality model assessment, but meteorological model assessment was occasionally neglected.…”