Author Identifiers

Miles Sowden
ORCID: 0000‐0003‐4920‐4680

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


School of Science

First Advisor

Associate Professor Ute Mueller

Second Advisor

Dr David Blake


Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar orbiting imagers, which means that aerosol is only derived during the daytime, and only once or twice per day.

Sub-hourly, infrared (IR), geostationary data, such as the ten-minute data from Himawari-8, are required to monitor these events to ensure that sporadic dust events can be continually observed and quantified. Newer quantification methods using geostationary data have focussed on detecting the presence, or absence, of a dust event. However, limited attention has been paid to the determination of composition, and particle size, using IR wavelengths exclusively. More appropriate IR methods are required to quantify and classify aerosol composition in order to improve the understanding of source impacts.

The primary research objectives were investigated through a series of scientific papers centred on aspects deemed critical to successfully determining ground-level concentrations. A literature review of surface particulate monitoring of dust events using geostationary satellite remote sensing was undertaken to understand the theory and limitations in the current methodology. The review identified (amongst other findings) the reliance on visible wavelengths and the lack of temporal resolution in polar-orbiting satellite data. As a result of this, a duststorm was investigated to determine how rapidly the storm passed and what temporal data resolution is required to monitor these and other similar events. Various IR dust indices were investigated to determine which are optimum for determining spectral change. These indices were then used to qualify and quantitate dust events, and the methodology was validated against three severe air quality events of a dust storm; smoke from prescribed burns; and an ozone smog incident.

The study identified that continuous geostationary temporal resolution is critical in the determination of concentration. The Himawari-8 spatial resolution of 2 km is slightly coarse and further spatial aggregation or cloud masking would be detrimental to determining concentrations. Five dual-band BTD combinations, using all IR wavelengths, maximises the identification of compositional differences, atmospheric stability, and cloud cover and this improves the estimated accuracy. Preliminary validation suggests that atmospheric stability, cloud height, relative humidity, PM2.5, PM10, NO, NO2, and O3 appear to produce plausible plumes but that aerosol speciation (soil, sea-spray, fires, vehicles, and secondary sulfates) and SO2 require further investigation.

The research described in the thesis details the processes adopted for the development and implementation of an integrated approach to using geostationary remote sensing data to quantify population exposure (who), qualify the concentration and composition (what), assess the temporal (when) and spatial (where) concentration distributions, to determine the source (why) of aerosols contribution to resulting ground-level concentrations