Multi-criteria ranking and source apportionment of fine particulate matter in Brisbane, Australia

This paper reports the application of multicriteria decision making techniques, PROMETHEE and GAIA, and receptor models, PCA/APCS and PMF, to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. While PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulphate, sea salt and road dust/soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

Source apportionment of fine particles at a suburban site in Queensland, Australia

Airborne fine particles were collected at a suburban site in Queensland, Australia between 1995 and 2003. The samples were analysed for 21 elements, and Positive Matrix Factorisation (PMF), Preference Ranking Organisation METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) were applied to the data. PROMETHEE provided information on the ranking of pollutant levels from the sampling years while PMF provided insights into the sources of the pollutants, their chemical composition, most likely locations and relative contribution to the levels of particulate pollution at the site. PROMETHEE and GAIA found that the removal of lead from fuel in the area had a significant impact on the pollution patterns while PMF identified 6 pollution sources including: Railways (5.5%), Biomass Burning (43.3%), Soil (9.2%), Sea Salt (15.6%), Aged Sea Salt (24.4%) and Motor Vehicles (2.0%). Thus the results gave information that can assist in the formulation of mitigation measures for air pollution.

Source apportionment of ultrafine and fine particle concentrations in Brisbane, Australia

Purpose: To investigate the significance of sources around measurement sites, assist the development of control strategies for the important sources and mitigate the adverse effects of air pollution due to particle size. Methods: In this study, sampling was conducted at two sites located in urban/industrial and residential areas situated at roadsides along the Brisbane Urban Corridor. Ultrafine and fine particle measurements obtained at the two sites in June-July 2002 were analysed by Positive Matrix Factorization (PMF). Results: Six sources were present, including local traffic, two traffic sources, biomass burning, and two currently unidentified sources. Secondary particles had a significant impact at Site 1, while nitrates, peak traffic hours and main roads located close to the source also affected the results for both sites. Conclusions: This significant traffic corridor exemplifies the type of sources present in heavily trafficked locations and future attempts to control pollution in this type of environment could focus on the sources that were identified.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

First measurements of source apportionment of organic aerosols in the Southern Hemisphere

An Aerodyne Aerosol Mass Spectrometer was deployed at five urban schools to examine spatial and temporal variability of organic aerosols (OA) and positive matrix factorization (PMF) used for the first time in the Southern Hemisphere to apportion the sources of the OA across an urban area. The sources identified included hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and oxygenated OA (OOA). At all sites, the main source was OOA, which accounted for 62–73% of the total OA mass and was generally more oxidized compared to those reported in the Northern Hemisphere. This suggests that there are differences in aging processes or regional sources in the two hemispheres. Unlike HOA and BBOA, OOA demonstrated instructive temporal variations but not spatial variation across the urban area. Application of cluster analysis to the PMF-derived sources offered a simple and effective method for qualitative comparison of PMF sources that can be used in other studies.

Characterisation and source apportionment of polycyclic aromatic hydrocarbons in the sediments of Brisbane River

The thesis was a step forward in predicting the levels and sources of polycyclic aromatic hydrocarbons (PAHs) in sediments of Brisbane river, especially after the Brisbane floods in 2011. It employed different statistical techniques to provide valuable information that may assist source control and formulation of pollution mitigation measures for the river.

Source apportionment of airborne particulate matter : an overview of Australian and New Zealand studies

Despite the existence of air quality guidelines in Australia and New Zealand, the concentrations of particulate matter have exceeded these guidelines on several occasions. To identify the sources of particulate matter, examine the contributions of the sources to the air quality at specific areas and estimate the most likely locations of the sources, a growing number of source apportionment studies have been conducted. This paper provides an overview of the locations of the studies, salient features of the results obtained and offers some perspectives for the improvement of future receptor modelling of air quality in these countries. The review revealed that because of its advantages over alternative models, Positive Matrix Factorisation (PMF) was the most commonly applied model in the studies. Although there were differences in the sources identified in the studies, some general trends were observed. While biomass burning was a common problem in both countries, the characteristics of this source varied from one location to another. In New Zealand, domestic heating was the highest contributor to particle levels on days when the guidelines were exceeded. On the other hand, forest back-burning was a concern in Brisbane while marine aerosol was a major source in most studies. Secondary sulphate, traffic emissions, industrial emissions and re-suspended soil were also identified as important sources. Some unique species, for example, volatile organic compounds and particle size distribution were incorporated into some of the studies with results that have significant ramifications for the improvement of air quality. Overall, the application of source apportionment models provided useful information that can assist the design of epidemiological studies and refine air pollution reduction strategies in Australia and New Zealand.

Weak acid extractable metals in Bramble Bay, Queensland, Australia : temporal behaviour, enrichment and source apportionment

Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, enrichment factors and Principal Component Analysis –Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Characterisation, toxicity and source apportionment of atmospheric organic pollutants in urban schools

Airborne organic pollutants have significant impacts on health; however their sources, atmospheric characteristics and resulting human exposures are poorly understood. This research characterized chemical composition of atmospheric volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyls in representative number of primary schools in Brisbane Metropolitan Area, quantified their concentrations, assessed their toxicity and apportioned them to their sources. The findings expand scientific knowledge of these pollutants, and will contribute towards science based management of risks associated with pollution emissions and air quality in schools and other urban and indoor environments.

Atmospheric polycyclic aromatic hydrocarbons in the urban environment: Occurrence, toxicity and source apportionment

Polycyclic Aromatic Hydrocarbons (PAHs) represent a major class of toxic pollutants because of their carcinogenic and mutagenic characteristics. People living in urban areas are regularly exposed to PAHs because of abundance of their emission sources. Within this context, this study aimed to: (i) identify and quantify the levels of ambient PAHs in an urban environment; (ii) evaluate their toxicity; and (iii) identify their sources as well as the contribution of specific sources to measured concentrations. Sixteen PAHs were identified and quantified in air samples collected from Brisbane. Principal Component Analysis – Absolute Principal Component Scores (PCA- APCS) was used in order to conduct source apportionment of the measured PAHs. Vehicular emissions, natural gas combustion, petrol emissions and evaporative/unburned fuel were the sources identified; contributing 56%, 21%, 15% and 8% of the total PAHs emissions, respectively, all of which need to be considered for any pollution control measures implemented in urban areas.