Abstract
An estimation model on LTO emissions of civil aviation airports was developed in this paper, LTO big data was acquired by analysing the internet with Python, while the LTO emissions was dynamically calculated based on daily LTO data, an uncertainty analysis was conducted with Monte Carlo method. Through the model, the emission of LTO in Shuangliu International Airport was calculated, and the characteristics and temporal distribution of LTO in 2015 was analysed. Results indicates that compared with the traditional methods, the model established can calculate the LTO emissions from different types of airplanes more accurately. Based on the hourly LTO information of 302 valid days, it was obtained that the total number of LTO cycles in Chengdu Shuangliu International Airport was 274,645 and the annual amount of emission of SO2, NOx, VOCs, CO, PM10 and PM2.5 was estimated, and the uncertainty of the model was around 7% to 10% varies on pollutants.
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