Improved estimation of air pollutant emissions from landing and takeoff cycles of civil aircraft in China

2019 
Abstract Civil aircraft emissions during landing and takeoff (LTO) are important air pollutant sources, but have been given insufficient attention in China. Accurate estimation of these emissions is limited by a lack of important parameters, such as detailed flight information and the dynamic time in climb and approach modes during LTO that are dependent on mixing layer height (MLH). We developed a flight-time/flight-height relationship using real-time height information in Aircraft Meteorological Data Relay data, and then calculated the actual time for each flight in those two modes based on the actual MLH from meteorological observation. Hourly emissions of civil aircraft were then estimated based on the database of each flight. Total emissions of NO x , CO, SO 2 , HC and PM from LTO cycles of domestic flights in China during 2015 were 37.78 Gg, 30.25 Gg, 12.00 Gg, 2.38 Gg and 0.75 Gg, respectively. Substantial monthly, daily and hourly variations of emissions due to the flight schedule as well as MLH were calculated. Large differences were found between the new estimation and emissions calculated based on traditional method. Compared with the emissions estimated based on default parameter obtained from International Civil Aviation Organization, the average difference of annual emission among airports with new estimation for various pollutants was approximately 30.3% in climb mode and 81.4% in approach mode; compared with the emissions estimated based on the method proposed by China National Guide, the average difference of annual emission among airports were 37.4% (NO x ), 8.4% (CO), 73.1% (HC) and 58.1% (PM) during LTO process. The monthly airport-specific emissions per LTO were also proposed. These can provide necessary and meaningful support for the revision of the values in National Guide.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    53
    References
    11
    Citations
    NaN
    KQI
    []