One of the main tasks of ICAO's Committee on Aviation Environmental Protection (CAEP) is to identify and carry out analyses of the future trends and various options available to limit or reduce the current and future impact of international civil aviation noise and emissions. The aim of these analyses is to assess the technical feasibility, the economic reasonableness, and the environmental benefits, as well as the interdependencies of the options considered. In doing so, CAEP has relied on the use of a variety of computer-based models and databases offered by Member States and international organizations that participate in CAEP.
As the need for a better informed policy-making process grows, CAEP's modelling requirements in terms of coverage (i.e. noise, emissions, costs and benefits, etc.) and accuracy increase. Each model and database has its strengths and weaknesses, and the use of multiple models provided CAEP insight into sensitivities of the results. Going forward, the model evaluation process has established a framework for the future evaluation of new models and updates to the existing tools.
The CAEP models facilitate the robust analysis of the interrelationships between noise, local air quality, and greenhouse gas emissions. As experience is gained investigating these interdependencies, and as the models mature further, more informed decision making on aviation environmental protection will become possible. To support the analyses for the eleventh meeting of CAEP in February 2019, the following models were used:
Of key importance is the fact that the input databases are common to all of the contributing models. These databases cover specific input parameters and data sets and are continuously updated in accordance with adopted SARPs and requirements. These databases are supplemented with additional information, as needed to ensure the analyses are as comprehensive as possible. To support the analyses for the eleventh meeting of CAEP in February 2019, the following databases were used:
Population Database based on: