Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analys...

Introduction Conclusions References

Several studies have been conducted to develop more accurate and precise indices for hydrocarbons source apportionment. The present study, however, develops a new multi-metric index for hydrocarbons source apportionment. It measures Poly Aromatic Hydrocarbons (PAHs) concentration at six stations with well known petrogenic origin, calculating Phe/An, Flu/Py, Chr/BaA, BaA/Chr, An/(An+Ph), Flu/(Fl...

The components and quantities of atmospheric dusts fallout has been reported to be the pollution indicator of large urban areas. The multiplicity and complexity of sources of atmospheric dusts in urban regions (e.g. industrial complexes composed of a variety of industrial processes, automobiles, construction activities etc.) has put forward the need of source apportionment of these sources indi...

Several studies have been conducted to develop more accurate and precise indices for hydrocarbons source apportionment. The present study, however, develops a new multi-metric index for hydrocarbons source apportionment. It measures Poly Aromatic Hydrocarbons (PAHs) concentration at six stations with well known petrogenic origin, calculating Phe/An, Flu/Py, Chr/BaA, BaA/Chr, An/(An+Ph), Flu/(Fl...

BACKGROUND Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemica...