Source apportionment modelling

In addition, in view of the results of Schwartz, et al. (32), on filter artifacts associated with the fraction, further studies are warranted before developing a source apportionment model. 

Multiple Regression Source Apportionment Models for Airborne Particulate Organic Matter in New York City... 

The source apportionment models proposed for the CYC and ACE fractions were ... 

A COMPARISON OF SOURCE APPORTIONMENT MODELS FROM AMBIENT AND DISPERSION NORMALIZED DATA ... 

Source Apportionment Models for the Cyclohexane-Soluble Fraction of Respirable Suspended Particulate Matter. Stepwise multiple regression analysis was used to determine the coefficients of the source tracers for the models proposed for CYC in equations (7)-(9). These models are shown in Table IV. As expected from the factor analyses, the coefficient for V, accounting for the greatest proportion of the variance of CYC, was fitted first into the equation. Equation (14) was the simplest and the F value was slightly higher than for equations (15) and (16). In addition, as will be discussed later in this paper, the coefficient for PB was in reasonable agreement with the ratio of CYC /PB for samples collected in the Allegheny Tunnel. 

SOURCE APPORTIONMENT MODELS FOR CYCLOHEXANE-SOLUBLE PARTICULATE ORGANIC MATTER ... 

Multivariate source. apportionment models have been developed for two fractions of respirable particulate organic matter which together constitute about 90% of the total organic solvent-extractable mass. The independent variables used for developing the models were trace metals, water-soluble sulfate and meteorological variables. Two of the three POM fractions extracted sequentially with cyclohexane (CYC), dlchloromethane (DCM) and acetone (ACE) were used as individual dependent variables. 

There are a number of different types of source apportionment models, including the chemical mass balance method, factor analysis, multiple linear regression analysis, and Lagrangian modeling. The chemical... 

Daisey, J. M., J. L. Cheney, and P. J. Lioy, Profiles of Organic Particulate Emissions from Air Pollution Sources Status and Needs for Receptor Source Apportionment Modeling, J. Air Pollut. Control Assoc., 36, 17-33 (1986b). 

State-of-the-art methods include the combination of source apportionment models with high time-resolved source apportionment techniques for organic aerosols datasets using the Aerodyne Aerosol Mass Spectrometer (AMS), obtaining contributions from primary organic emissions from traffic [60, 61]. 

Thus for risk assessment in health effect studies or for aerosol source apportionment modeling local emission source profiles and emission factors are mandatory. 

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