There is a recognised need for the continued improvement of both the techniques and technology for spatial decision support in infrastructure site selection. Many authors have noted that current methodologies are inadequate for real-world site selection decisions carried out by heterogeneous groups of decision-makers under uncertainty. Nevertheless despite numerous limitations inherent in current spatial problem solving methods, spatial decision support systems have been proven to increase decision-maker effectiveness when used. However, due to the real or perceived difficulty of using these systems few applications are actually in use to support decision-makers in siting decisions. The most common difficulties encountered involve standardising criterion ratings, and communicating results. This research has focused on the use of Approximate Reasoning to improve the techniques and technology of spatial decision support, and make them easier to use and understand. The algorithm developed in this research (ARAISS) is based on the use of natural language to describe problem variables such as suitability, certainty, risk and consensus. The algorithm uses a method based on type II fuzzy sets to represent problem variables. ARAISS was subsequently incorporated into a new Spatial Decision Support System (InfraPlanner) and validated by use in a real-world site selection problem at Australia's Brisbane Airport. Results indicate that Approximate Reasoning is a promising method for spatial infrastructure planning decisions. Natural language inputs and outputs, combined with an easily understandable multiple decision-maker framework created an environment conducive to information sharing and consensus building among parties. Future research should focus on the use of Genetic Algorithms and other Artificial Intelligence techniques to broaden the scope of existing work.

In an era of acute concern about airline safety, bird strikes are still one of the major hazards to aviation worldwide. The severity of the problem is such that it is mandatory in all developed countries to include bird management as part of airport safety management programs. In Australia, there are approximately 500 bird aircraft strikes per year (Bailey 2000). Brisbane airport has a relatively high occurrence of strikes, with an average of 77 recorded every year (2002-2004). Given the severity of the problem, a variety of techniques have been employed by airports to reduce bird strikes. Scare devices, repellents, continuous patrols for bird hazing, use of raptors to clear airspace of birds and depredation are used by many airports. Even given the diversity of control methods available, it is accepted that habitat management is the most effective long term way to control birds in and around the airport space. Experimental studies have shown that habitat manipulation and active scaring measures (shooting, scaring etc), can reduce bird numbers to an acceptable level. The current study investigated bird populations in six major vegetation habitat types identified within the operational and surrounding areas of Brisbane airport. In order to determine areas where greater bird control and management should be focused, bird abundance, distribution, and activity were recorded and habitats that pose the greatest bird strike risk to aircraft were identified. Secondly, species with high hazard potential were identified and ranked according to their hazard potential to aircraft. This study also investigated the effectiveness of different vegetation management options to reduce bird species abundance within operational areas of Brisbane airport. Four different management options were compared. Each management option was assessed for grass structural complexity and potential food resources available to hazardous bird species. Analysis of recorded data showed that of the habitats compared within the Brisbane airport boundaries, grasslands surrounding runways, taxiways and aprons possess the greatest richness and abundance of bird species that pose the greatest potential hazard to aircraft. Ibis and the Australian kestrel were identified as the bird species that pose the greatest risk to aircraft at Brisbane airport, and both were found in greatest numbers within the managed grasslands surrounding operational areas at the airport. An improved reporting process that allows correct identification of all individual bird species involved in bird strikes will not only increase the accuracy of risk assessments, but will also allow implementation of more effective control strategies at Brisbane airport. Compared with current grassland management practice, a vegetation management option of maintaining grass height at 30-50cm reduced total bird utilisation by 89% while utilisation of grassland by potentially hazardous birds was also reduced by 85%. Maintaining grass height within the 30-50cm range also resulted in a 45% reduction in the number of manipulations required per year (11 to 6), when compared with current management practices, and a 64% reduction in annual maintenance cost per hectare. When extrapolated to the entire maintained grass area at Brisbane airport, this resulted in a saving of over $60 000 annually. Optimisation of potential hazard reduction will rely on future studies that investigate the effect of particular vegetation species that could replace the existing mix of grasses used at Brisbane airport and an understanding of the relative importance of vegetation structure and food supply in determining utilisation by potentially hazardous bird species.

Emissions from airport operations are of significant concern because of their potential impact on local air quality and human health. The currently limited scientific knowledge of aircraft emissions is an important issue worldwide, when considering air pollution associated with airport operation, and this is especially so for ultrafine particles. This limited knowledge is due to scientific complexities associated with measuring aircraft emissions during normal operations on the ground. In particular this type of research has required the development of novel sampling techniques which must take into account aircraft plume dispersion and dilution as well as the various particle dynamics that can affect the measurements of the aircraft engine plume from an operational aircraft. In order to address this scientific problem, a novel mobile emission measurement method called the Plume Capture and Analysis System (PCAS), was developed and tested. The PCAS permits the capture and analysis of aircraft exhaust during ground level operations including landing, taxiing, takeoff and idle. The PCAS uses a sampling bag to temporarily store a sample, providing sufficient time to utilize sensitive but slow instrumental techniques to be employed to measure gas and particle emissions simultaneously and to record detailed particle size distributions. The challenges in relation to the development of the technique include complexities associated with the assessment of the various particle loss and deposition mechanisms which are active during storage in the PCAS. Laboratory based assessment of the method showed that the bag sampling technique can be used to accurately measure particle emissions (e.g. particle number, mass and size distribution) from a moving aircraft or vehicle. Further assessment of the sensitivity of PCAS results to distance from the source and plume concentration was conducted in the airfield with taxiing aircraft. The results showed that the PCAS is a robust method capable of capturing the plume in only 10 seconds. The PCAS is able to account for aircraft plume dispersion and dilution at distances of 60 to 180 meters downwind of moving a aircraft along with particle deposition loss mechanisms during the measurements. Characterization of the plume in terms of particle number, mass (PM2.5), gaseous emissions and particle size distribution takes only 5 minutes allowing large numbers of tests to be completed in a short time. The results were broadly consistent and compared well with the available data. Comprehensive measurements and analyses of the aircraft plumes during various modes of the landing and takeoff (LTO) cycle (e.g. idle, taxi, landing and takeoff) were conducted at Brisbane Airport (BNE). Gaseous (NOx, CO2) emission factors, particle number and mass (PM2.5) emission factors and size distributions were determined for a range of Boeing and Airbus aircraft, as a function of aircraft type and engine thrust level. The scientific complexities including the analysis of the often multimodal particle size distributions to describe the contributions of different particle source processes during the various stages of aircraft operation were addressed through comprehensive data analysis and interpretation. The measurement results were used to develop an inventory of aircraft emissions at BNE, including all modes of the aircraft LTO cycle and ground running procedures (GRP). Measurements of the actual duration of aircraft activity in each mode of operation (time-in-mode) and compiling a comprehensive matrix of gas and particle emission rates as a function of aircraft type and engine thrust level for real world situations was crucial for developing the inventory. The significance of the resulting matrix of emission rates in this study lies in the estimate it provides of the annual particle emissions due to aircraft operations, especially in terms of particle number. In summary, this PhD thesis presents for the first time a comprehensive study of the particle and NOx emission factors and rates along with the particle size distributions from aircraft operations and provides a basis for estimating such emissions at other airports. This is a significant addition to the scientific knowledge in terms of particle emissions from aircraft operations, since the standard particle number emissions rates are not currently available for aircraft activities.