Potential of receptor models in source apportionment of atmospheric aerosols: A review
Air quality monitoring, identification of pollution sources and their quantification needed to implement air pollution control strategies. Air quality is a serious concern for India and become one of the most important problems of megacities and has serious impacts on public health, visibility, and can cause heat island effects on the urban scale. Most of the urban city of India has high concentrations of airborne particulate matter therefore; application of effective abatement measures is a high urgency. This study reviewing the application of receptor models for source apportionment. Previous studies applied multivariate receptor models including principal components analysis (PCA), chemical mass balance (CMB), positive matrix factorization (PMF), and back trajectory receptor models for source apportionment. The assignment of factors from multivariate receptor models to specific source categories is in many cases highly uncertain, this uncertainty in terms of presence of tracer elements may be the result of genuine collinearity of diverse sources, or more probably arises from methodological problems. The proper markers for wide range of source are still required to remove the ambiguity in source interpretation.