| Summary: | Aviation contributes to worldwide connectivity and the global economy; furthermore, the growth in recent years is forecast to continue. However, airports emit a range of pollutants that degrade local air quality to the detriment of human health, which restricts the capacity expansion required to meet future demand. This thesis analyses aircraft ground operations and demonstrates methods to evaluate the efficacy of pollutant emission reduction operating strategies at airports. A case study of 7,090 high-resolution flight data records (FDRs) is utilised, covering aircraft activities at London Heathrow, which is a major international, air quality critical airport. Firstly, aircraft taxiing with half of the engines deactivated after landing reduces both NOX and CO emissions by ~30% on average. Analysis of taxi operations finds that reducing the time taken to deactivate the engines by ~20 seconds reduces NOX and CO emissions by a further 9 and 14% respectively. Secondly, reducing thrust to below maximum during takeoff, while accounting for constraints including aircraft weight, reduces NOX emissions by 42%. Analysis of the variation in observed takeoff thrust finds that NOX emissions could be reduced by ~6%, when adopting thrust settings that correspond to minimum emissions. The results of both analyses are presented in this thesis to enable integration with aircraft operators’ existing procedures. Finally, locally measured NOX and CO concentrations, downstream of Heathrow runway activities, increase by 144 and 88% respectively, compared to periods of runway inactivity. This thesis presents the first comparison of FDRs to measured emission indices (EIs), finding that these are dependent on aircraft, engine and thrust setting. However considerable variation in EI(NOX) and EI(CO) is observed. This thesis provides implementable strategies to reduce emissions at airports by optimising aircraft ground operations, contributing to reductions in the air quality impacts of airports to enable further capacity expansion.
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