Big data enabling quieter and cleaner air transport

Abstract: seconda parte ----------------------------------------------------------------------------- Two data collection campaigns were run in June 2018 and July 2019, and daily flight tracking data were retrieved for several European airports of different sizes and traffic intensity. Comparisons with EUROCONTROL data show a good reconstruction of air traffic for 2018 and an excellent one for 2019, highlighting also the reasons why discrepancies exist. Ground track maps, noise contour maps, and noise levels at monitoring stations around Heathrow, Gatwick, Schiphol, and Vienna International airports are compared with official results, showing an overall very good agreement but indicating that departure flight profiles need improving. Future traffic scenarios for 2025 were built using the 2018 traffic data for Heathrow, Frankfurt, and Vienna airports, and the changes in noise contour maps and areas suggest that the algorithms for fleet renewal and additional flight events are highly effective. The calculation of emissions and pollutant dispersion was made using only the 2019 traffic data. The comparison of modelled and official emission inventories for Heathrow indicates that aircraft emissions are modelled well, although limited underestimations are observed. On the contrary, the poor comparison between measured and modelled pollutant concentration levels around Heathrow, Gatwick and Madrid-Barajas airports shows very clearly the need for considering non-aircraft emissions and for a better spatial allocation of pollutants released during taxi operations. Thanks to an innovative approach that consists in exploiting Internet-based data sources, the present modelling tool can be applied to any airport worldwide for any time period, enabling assessment of the environmental impact of past, present and future air traffic scenarios. As soon as a few upgrades are implemented, this tool will be able to assist policy-makers in developing guidelines and regulations aimed at mitigating the detrimental effects of air traffic around civil airports.

Abstract: prima parte ----------------------------------------------------------------------------- The steady growth of air traffic, only temporarily halted by COVID-19, is causing several problems in the management of flight movements around civil airports, leading to congestion, delays, and ultimately increased noise and pollutant emissions in airport areas. These emissions can be estimated with several prediction models, but the lack of input data on flight movements often limits their effectiveness. In recent years, however, the introduction of ADS-B transponders and the development of the Internet have led to the birth of flight tracking websites, which report and offer to the public large amounts of information on aircraft movements and airport weather conditions. At the same time, many websites provide complementary information on aircraft models and engines, airport layouts, and topography of airport areas. This thesis presents an innovative modelling tool that enables calculation of noise, chemical emissions, and pollutant dispersion from civil air traffic in airport areas on the basis of input data collected from the Internet. The reconstruction of aircraft flight performance and emissions relies on pre-existing prediction models, which require special implementation to deal with the Internet-based input data. The first operation performed by the present modelling tool is the reconstruction of air traffic in airport areas. The flight tracking and weather data are collected from flight tracker FlightAware and combined in a pre-processing stage with information on aircraft models/engines and airport runways to define daily departures and arrivals, collectively named flight events. Future traffic scenarios are also built from historical flight events accounting for fleet renewal and air traffic increase according to EUROCONTROL forecasts with two custom-made algorithms. The flight events are then processed to reconstruct the aircraft motion over time during each event. This is done by determining the segmented flight path, which is built by merging the ground track with the flight profile. The former represents the aircraft motion on the ground and is calculated with a specially developed algorithm, while the latter consists in the variation of height, speed, and thrust along the ground track and is modelled relying on the ECAC flight procedures. The processing goes on to calculate noise and chemical emissions. First, a specially implemented version of the ECAC Doc 29 model is used to compute single-event noise levels in the airport area using a 2-D grid of observers, and then engine fuel flow and emissions of HC, CO, NOx, PM2.5, SO2, CO2, H2O are calculated on the basis of the FAA’s AEDT methodology. An empirical correlation from the literature is also included to estimate NO2 emissions. In the final stage, all results concerning emissions are obtained. Cumulative noise metrics and indices are computed from single-event noise levels, while emission inventories are built from the previously calculated chemical emissions. The released amounts of pollutants NO2, PM2.5 and SO2 are then extracted and allocated spatially in the airport area. This allocation leads to a number of pollutant emission sources that are fed, together with the weather data, into AUSTAL2000, which provides the pollutant concentration levels around the airport.