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Developing a High-Resolution Emission Inventory of China's Aviation Sector Using Real-World Flight Trajectory Data.

Jingran ZhangShaojun ZhangXiaole ZhangJing WangYe WuJiming Hao
Published in: Environmental science & technology (2022)
Economic growth and globalization have led to a surge in civil aviation transportation demand. Among the major economies in the world, China has experienced a 12-fold increase in terms of total passenger aviation traffic volume since 2000 and is expected to be the largest aviation market soon. To better understand the environmental impacts of China's aviation sector, this study developed a real-world flight trajectory-based emission inventory, which enabled the fine-grained characterization of four-dimensional (time, longitude, latitude, and altitude) emissions of various flight stages. Our results indicated that fuel consumption and CO 2 emissions showed two peaks in altitude distribution: below 1,000 m and between 8,000 and 12,000 m. Various pollutants depicted different vertical distributions; for example, nitrogen oxides (NO X ) had a higher fraction during the high-altitude cruise stage due to the thermal NO X mechanism, while hydrocarbons had a dominant fraction at the low-altitude stages due to the incomplete combustion under low-load conditions. This improved aviation emission inventory approach identified that total emissions of CO 2 and air pollutants from short-distance domestic flights would be significantly underestimated by the conventional great-circle-based approach due to underrepresented calculation parameters (particularly, flight distance, duration, and cruise altitude). Therefore, we suggest that more real-world aviation flight information, especially actual trajectory records, should be utilized to improve assessments of the environmental impacts of aviation.
Keyphrases
  • life cycle
  • high resolution
  • municipal solid waste
  • molecular dynamics
  • healthcare
  • electronic health record
  • health insurance
  • psychometric properties
  • deep learning
  • artificial intelligence
  • big data