Data analysis

4.5.1 Factor analysis - PCA

Principal components analysis (PCA) is multivariate statistical method of data analysis that has been commonly used for analysis of atmospheric data since the 1980s. This includes meteorological data reduction, grouping of synoptic and chemical variables, forecasting atmospheric parameters, determining variability in atmospheric fields (Richman, 1986), and more

recently for assessing sources of particulate pollution (Hopke, et al., 1982; Ames, et al., 2000). As

a source apportionment tool for determining sources of particulate matter, PCA considers the covariance between concentrations of different species present in airborne particles.

In this study, PCA was used to determine a number of factors, referred to as profiles or fingerprints, which represent the similarity of relative concentrations of elements contained within particulate collected daily on filters. These profiles represent the ratios between different elements characteristic of different sources of particulate.

The particulate mass filters used in the PCA analysis were collected using the SASS sampling system described in Section 4.4. A total of 250 filters were analysed for total mass of elements using Proton-Induced X-ray Emission (PIXE) by Geological & Nuclear Sciences (GNS). The PIXE ion beam analysis method determines concentrations from the element specific X-ray emissions associated with the electron de-excitation process that occurs following bombardment of the filter with a proton beam. The x-ray scattering occurs across an angle of around 135 degrees and typically measures concentrations to accuracy of 1-10% (Trompetter & Markwitz, 2001). Elements measured using PIXE included sodium (11), bromine (35) iodine (53), lead (82) and mercury (80). Carbon (6) on the filters was also measured by GNS using a light absorbance method (Trompetter & Markwitz, 2001), based on the assumption that carbon was responsible for all absorbance. A Teflon filter media was used for the first 75 filters, which were collected from 9 February to 21 June 2000. Analysis of these filters found concentrations of many elements on the filters to be frequently below the detection limits. In an attempt to reduce this data loss, GNS recommended the use of polycarbonate filters. From 22 June 2000 until the completion of the study (filters 75 to 250) the filter medium used for the speciation sampling was polycarbonate.

The detection limits by element, compound and filter type are detailed in Table 4.2. Concentrations of elements below detection limits were included in the results for the PIXE analysis to prevent bias in PCA correlations. The dates, filter numbers and sampling duration for each of the filters is shown in Appendix B.

A separate set of 250 filters, collected using the same SASS sampling system and sampling regime, were analysed for nitrate nitrogen, sulphate, chloride and ammonium nitrogen. These were collected on a nylon filter medium and denuder system used to minimise loss of nitrogen. The nylon filters were stored in P35 vials filled with 20 mls of deionised water and analysed using a Dionex DX500 ion chromatography system. The mass of inorganic ions on the filters was measured using ion chromatography (IC).

Table 4.2: Limits of detection (LOD) for PIXE and IC analyses.

Limits of detection (LOD) ng cm2

Na _Mg Al Si p s Cl K Ca Sc Ti V Cr Mn

Teflon 98 38 31 29 62 37 33 42 38 35 41 53 51 88

Polycarbonate 1 15 43 29 22 43 25 20 17 15 18 15 1 3 7 7

o/o above LOD 44 86 88 92 1 96 93 47 50 _{3 0 0 26 3}

Limits of detection (LOD) ng cm2

Fe Co Ni Cu Zn Ga Ge As Se Br I _Hg Pb Ei C

Teflon 80 88 96 126 157 188 238 292 361 443 94 652 784 350

Polycarbonate 6 8 5 5 ₆ 5 _{7 9 10 15 1 15 17 23 350}

o/o above LOD 73 9 30 10 20 2 0 3 1 1 1 22 1 1 90

Limits of detection (LOD) pg/filter

Ammonia N Chloride Nitrate N Sulphate S

Nylon 0.1 µg 0.1 µg 0.1 µg 0.1 µg

o/o above LOD 46 73 38 68

The PIXE (mass per unit area) and ion chromatography results (total mass per filter) were converted to concentrations based on:

• The volume of airflow through the filter sample lines throughout the period of measurement (collected at the SASS control unit).

• A conversion of mass per unit area to mass per filter based on the exposure area of the 47mm filter being 11.94 cm2.

The mass concentration of PM2.s was measured gravimetrically from the Teflon and polycarbonate

filters prior to PIXE analysis. Results of all analyses were collated in an Excel spreadsheet.

Concentrations of elements and ions were copied to a statistical analysis package SYSTAT version 9. Factor analysis using PCA was then performed on the data using an eigenvector analysis of the correlation matrix. A transformation of the data using a varimax rotation was then applied to produce factors closer to actual source profiles.

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Of the 32 species measured, only 18 were included in the PCA analysis. Elements were initially excluded from the analysis if more than 30% of the data were below the limit of detection (Table 4.2). Exceptions were then made in the case of Zn, Sc and Mn because of their potential significance for local sources of particles. Source profiles and contributions to PM2s mass determined from this analysis are detailed in Chapter 6.

As a test of the sensitivity of the data to the different filter media, a PCA analysis was carried out separately for the Teflon and Polycarbonate filters. Data were separated into two SYSTAT data files representing filters collected using each media and PCA analysis with varimax rotation applied to each. Results of this test are also discussed in Chapter 6.

4.5.2 Multiple regression analysis

Multiple regression analysis was used to determine the contribution of different sources of particles, identified using the PCA analysis, to light scattering. The multiple regression analysis was carried out using a backwards-stepwise regression. The stepwise analysis was set up to remove any sources from the equation if their alpha ('p ') factor was greater than or equal to O .15, that is if there was a 15% or greater probability that the relationship was due to chance.

The dependent variable in the analysis was the Bsp (dry) outputs from the nephelometer, averaged

for the period (e.g., 06:00 to 13:00 hours) to coincide with the time of filter sampling. The independent variables were the factor scores for the six factors identified in the PCA analysis.