Improving the accuracy of the airport aircraft’s CO2 inventory is an important issue for the development of green civil aviation. Firstly, this study uses the flight operation data and meteorological data of Guangzhou Baiyun International Airport in 2019 as the driving force to improve key parameters (i.e., engine fuel flow rate, mixing layer height, and flight operation stage duration). Secondly, the CO2 emission inventories are established and compared based on the standard and improved models. Finally, the emission characteristics are explored from three dimensions: aircraft types, temporal, and spatial. The results show that the annual CO2 emissions obtained by the data-driven model are 31.6% lower than the ICAO standard model. The B738 and A320 have lower emission intensities, which are more in line with the need for carbon reduction. The peak emissions of CO2 occur from 8:00 to 9:00 in the morning, while the off-peak emission times are from 1:00 to 2:00 in the early morning. CO2 emissions increase in November and December when the mixing layer height increases. The emissions are concentrated in the directions corresponding to LMN, YIN, and VIBOS departure route points.


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    Titel :

    Data-Driven Airport Aircraft CO2 Emission Inventory and Its Characteristic Analysis


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Meng, Lingyun (Herausgeber:in) / Qian, Yongsheng (Herausgeber:in) / Bai, Yun (Herausgeber:in) / Lv, Bin (Herausgeber:in) / Tang, Yuanjie (Herausgeber:in) / Sun, Jiaojiao (Autor:in) / Hu, Rong (Autor:in) / Pan, Xiaoran (Autor:in) / Deng, Songwu (Autor:in) / Guan, Zhaowei (Autor:in)

    Kongress:

    International Conference on Traffic and Transportation Studies ; 2024 ; Lanzhou, China August 23, 2024 - August 25, 2024



    Erscheinungsdatum :

    14.11.2024


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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