Trajectory Modelling of Atmospheric Pollutants Emitted by Aircraft for Air Quality Assessment over the Metropolitan Region of Rio de Janeiro-Brazil: Experimental Investigation

The impacts of aviation on the climate contribute not only to regional but also global climate change because of emissions of carbon dioxide (CO2), nitrogen oxides (NOx), water vapour, sulphates and soot. Aviation is suffering a large increase in recent years and as result there is a consequent increase in emissions of these air pollutants. Air pollution is definitely one of the most significant effects of aviation's impact on the climate, but regional environmental changes caused by an airport situated in specific areas are also a challenge for this transport sector. The identification of the trajectories of these pollutants leads to the implementation of measures to mitigate their harmful effects. The highest exposure levels of air pollution in airports and near them are found in the Landing and Take-off (LTO) cycle responsible for negative impacts on air quality. The city of Rio de Janeiro situated in the coastal area of the Southeast region of Brazil, has two major airports; an International airport and one for domestic flights. Both are near the Guanabara Bay (GB), in Metropolitan Region of Rio de Janeiro (MRRJ). In this research, the pollutant trajectories emitted by these two airports are verified, using the Brazilian Regional Atmospheric Modelling System (BRAMS) to generate wind fields in the MRRJ. The pollutant trajectories are calculated from the wind fields, using a 3D kinematic trajectories Lagrangian model. Atmospheric instability indices are tested from the BRAMS simulations to verify the days with more stable atmospheric conditions in winter month, being the Total Totals index (TT) more appropriate for the purpose of this study. Results show that the cities of Rio de Janeiro and Duque de Caxias, in the western side of the MRRJ, are critical points continually affected by pollutant transport because of the prevailing meteorological conditions, harming the air quality in the region. These models captured the influence of meso and large scale systems, showing the dependence of daily and seasonal variations in the trajectories of pollutants and, therefore, they are important tools in decision-making for the control of emissions, contributing to better management of urban air quality. At a time of great demand, it is essential to create solutions focused in long-term prosperity of aicraft transport and they must be synchronized with standards of environmental protection.