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AERO2K project will be managed by the co-ordinator, QinetiQ. It has been broken down into Work Packages that are explained briefly below.
WP1—Co-ordination and data integration—serves two purposes: a conventional oversight, co-ordination and project management of all the WPs; also, the data integration is incorporated into this.  The ‘data integration’ consists of constructing the software tool that brings all the components and outputs of the WPs together. We favour a combination of GIS (Geographical Information System) techniques combined with programming and databases. 
WP2—Air traffic movement database construction—is at the very core of the project. This WP collects the data on civil and military aircraft movements across the world. Particular studies of regions such as China and Russia for domestic aircraft movements will be made.  Data collected and compiled within WP2 form input to the ‘data integration’ package described in WP1. LTO cycle variability will be surveyed so that variation of, in particular, taxiing time can be accounted for. Air traffic movements will be determined from ATC (Air Traffic Control) data as a primary source, supplemented by timetable data as a secondary source where ATC data are unavailable.  Previous approaches have used both pure timetable and hybrid ATC/timetable approaches.  Here, we will use the hybrid ATC/timetable approach. The timetable approach has the advantage of simplicity but the disadvantage of lack of complete coverage: the hybrid approach gives a more complete coverage but is inherently more difficult to compile. The details of the ‘standard’ landing/take-off (LTO) cycle will be examined with a survey of patterns of taxi-out time and power settings in take-off and climb-out. These vary significantly from place to place and this aspect of the study will increase the usefulness of the data for preliminary local air quality investigations.
WP3—Aircraft representation, profiling and fuel prediction—in this WP, the group concerned will consider the way in which aircraft types may be grouped together to form ‘generic types’.  Then, a number of flight profiling and fuel prediction models will be used. Limited data are available that will allow a validation of the accuracy and validity of a modelling approach. The purpose of this exercise is to compare different methodologies and output data in order to understand the limits and uncertainties of using different methods and approaches. For example, fuel cycle/engine models have been developed by DERA, DLR and NLR and also by an independent software vendor: such models will be examined.  Validation data of profiles and fuel flow will be used as the ‘benchmark’ to judge the accuracy of modelling approaches.
WP4—Emissions parameterisation— A number of algorithms for fuel to pollutant transformation are available for species such as nitrogen oxides (NOx), carbon monoxide (CO) and hydrocarbons (HCs) and will be compared.  Thus, competing approaches will be directly addressed in order to quantify the magnitude of these different potential approaches on emission output data. In addition, particle number density data will be parameterised from data that have become available recently on both the volatile and non-volatile fractions: these data have been generated from field measurements from one of the partners and no competing approaches are available.
WP5—Air traffic and emissions forecasting—Civil aviation forecasting on 10–25 year time-scales is not so contentious: a number of approaches have been attempted in the past based upon extrapolation of aviation trends.  However, sensitivities on data assumptions will be tested to determine the potential range of results as an uncertainty analysis. Competing approaches will be determined from the different approaches and stand-points of the partners from industry, governmental and air traffic management approaches.
　
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本文鏈接地址：AERO2K Flight Movement Inventory Project Report(87)