The Chemical Mass Balance (CMB) model is one of several receptor models that have been applied to air quality management. This model quantifies contributions using chemical signatures characterizing source-types rather than contributions from individual emitters. The CMB model uses the chemical composition of ambient pollution samples to estimate the contributions of different source types to the measured pollutant concentrations. The disadvantage of the model is that it cannot separate the sources having similar chemical compositions or for those sources for which source composition profiles are unavailable. Since CMB analysis is done on a sample-by-sample basis, it is possible to estimate the daily contributions of individual sources, and can thereby provide useful information based on a limited number of samples to address air quality management issues. Samples of fine and coarse fractions of airborne particulate matter (PM) were collected using a ‘Gent’ stacked filter unit in two fractions of 0-2.2 μm and 2.2-10 μm sizes in a semi-residential (Atomic Energy Centre Dhaka, AECD) area from June 2001 to June 2002 of Dhaka. These samples were analyzed for elemental concentrations with PIXE. The chemical composition data set was analyzed by CMB using local source profiles obtained using a Principal Components Analysis (PCA) and regression analysis of data from this site and the source contributions are quantitatively estimated for each of the samples. The results of the CMB analysis were compared with the results obtained using positive matrix factorization (PMF) that had been done previously. It is observed that CMB provides comparable results except for limited discrepancies, especially for the PM2.2 fractions where sources have similar elemental signatures.