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ATS International Journal
Editor in Chief: Prof. Alessandro Calvi
Address: Via Vito Volterra 62,
00146, Rome, Italy.
Mail to: alessandro.calvi@uniroma3.it

An investigation into the impact of airport operations on ambient air quality: the case study of Sphinx International Airport

I.M.I. Ramadan, A.T.A. Ali, H.M.B. Shalaby, F. Tosti, I.G. Shaaban
Pages: 197-212

Abstract:

This investigation focuses on the predicted environmental impact due to emissions and air pollutants resulting from planned airport operations. The analysis relies on the application of the descriptive and analytical approach on a case study developed at the new Sphinx International Airport (ICAO: HESX, IATA: SPX) serving the city of Giza, Egypt. The theoretical part reviews previous studies in the field to draw the most important results. It contains air pollutant monitoring and measuring in the area where the airport is to be established, weather forecast data, calculation of air traffic and plane emissions as well as the implementation of all necessary data for the emission dispersion modelling mapping program. This is instrumental to predict the pollutant concentrations from all activities at the airport. This research has found that the levels of emission concentrations in the airport area are acceptable and below maximum permissible thresholds. However, the emissions from certain specific sources would be considerably lower if mitigation measures will be implemented. Other sources will increase emissions with lower capacity for mitigation. By way of comparison between the results of the actual analyses of the emissions from planes and the energy consumption, different impact was found on the areas adjacent to the airport. To ensure that the outcomes of the analyses for the emissions comply with national and international standards, recommendations are also suggested. This study indicates that the most important measures must be focused on mitigating emissions during the operational phase.
Keywords: air pollutants; emissions; ICAO; pollutant dispersion prediction

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