Source resolution, factor analysis

Hopke, P.K. The Application of Factor Analysis to Urban Aerosol Source Resolution, ACS SYMPOSIUM SERIES, No. 167, 1981. 

The Application of Factor Analysis to Urban Aerosol Source Resolution... 

Among these techniques are various forms of a statistical method called factor analysis. Several forms of factor analysis have been applied to the problem of aerosol source resolution. These different forms provide several different frameworks in which to examine aerosol composition data and Interpret it in terms of source contributions. 

With many sampling stations and sampling periods it is possible to do a curve resolution giving the number of sources, the pure source profiles and the contribution of each profile to each sample [Hopke 1991], This curve resolution problem was earlier solved by factor analysis, but lately three-way solutions have been applied. The establishment of source profiles relies a lot on factor rotation. Bilinearity is very much dependent on the dispersion process. 

In principle GD-MS is very well suited for analysis of layers, also, and all concepts developed for SNMS (Sect. 3.3) can be used to calculate the concentration-depth profile from the measured intensity-time profile by use of relative or absolute sensitivity factors [3.199]. So far, however, acceptance of this technique is hesitant compared with GD-OES. The main factors limiting wider acceptance are the greater cost of the instrument and the fact that no commercial ion source has yet been optimized for this purpose. The literature therefore contains only preliminary results from analysis of layers obtained with either modified sources of the commercial instrument [3.200, 3.201] or with homebuilt sources coupled to quadrupole [3.199], sector field [3.202], or time-of-flight instruments [3.203]. To summarize, the future success of GD-MS in this field of application strongly depends on the availability of commercial sources with adequate depth resolution comparable with that of GD-OES. 

The results of the PCA from each subset are similar except that the data subsets which did not either Include the meteorological data or normalize the data to reduce meteorological variability (subsets 2 and 3) were not able to separate several of the components probably due to the atmospheric masltlng effect. Information on the wind direction and rainfall quantity dependence of seasalt and metals Is obtained when meteorological data are Included In the analysis. From the standpoint of separation of chemical factors the fourth subset (normalization to fractional composition) provided the best resolution of the data. Using deposition or concentrations, a component that Indicated a combined Influence of sulfate, nitrate, lead and calcium emission sources was resolved Into separate components when the fractional composition data were analyzed by PCA. 

Hopke, P.K. "Source Identification and Resolution Through Application of Factor and Cluster Analysis." Annals of the New York Academy of Sciences, ed. K. Knelp, 1980. 

XPS analysis of y-APS applied to nickel and silicon substrates was also carried out using a Surface Science Instruments SSX-100-03 instrument equipped with a monochromatic A1 Ka source. The X-ray source had an energy of 1487 eV and the instrument operated at a spot size of 600 //m. Pass energies for survey and high resolution spectra were 150 and 52 eV, respectively. Atomic concentrations were once again obtained from the high resolution spectra using sensitivity factors provided with the software. 

Griffiths et al. (9) have compared the signal to noise ratios of interferometers and monochrometers under the assumption that the source temperature and resolution for both types of instrument are equivalent. Their analysis involves a comparison of the factors appearing in equation 8 and a representation of the advantage of an interferometer over a monochrometer as the ratio of the factors associated with each instrument. A summary of Griffith et al. s (9) analysis is presented in the balance of this section. 

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