Balakrishna Gurugubelli - School of Studies in Chemistry, Pt.Ravishankar Shukla University, Raipur. 492010.
Shamsh Shamsh - School of Studies in Chemistry, Pt.Ravishankar Shukla University, Raipur. 492010

Different approaches of source apportionment of dust fractions have been reported world-over. Prediction of source categories within receptor chemical profiles using regression and factor analysis using PCA has been reported to evaluate possible source/routes of air pollution mass significantly. The present study is focused on application of all three approaches to investigate higher degree of significance in soil dust contribution in micro environment. Modeled source categories obtained from regression and factor analysis (using PCA) has shown potential support in the selection of source profiles in CMB. About 65-78% agreement has been obtained between results of source signatures of dust fallout obtained from three approaches. The application of combined approach has been extended to respirable fine particulates measured indoors. Both fractions have shown different dominance of selected source of emissions. Practical implications: Major approaches of source signatures has been investigated in combination with the hypothesis that prediction and modeled source profiles will support the selection and inclusion of field based source profiles in source apportionment of indoor dust fractions using CMB. A stratified random sampling plan using longitudinal study design has been adopted for dust fallout source apportionment.

Source apportionment, CMB, regression analysis, micro environment