Imperial College London

Dr Ke Han

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Senior Lecturer
 
 
 
//

Contact

 

+44 (0)20 7594 5682k.han Website CV

 
 
//

Assistant

 

Mrs Maya Mistry +44 (0)20 7594 6100

 
//

Location

 

605Skempton BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Chen:2016:10.1016/j.trd.2016.08.003,
author = {Chen, D and Hu, M and Han, K and Zhang, H and Yin, J},
doi = {10.1016/j.trd.2016.08.003},
journal = {Transportation Research Part D: Transport and Environment},
pages = {46--62},
title = {Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand},
url = {http://dx.doi.org/10.1016/j.trd.2016.08.003},
volume = {48},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth.
AU - Chen,D
AU - Hu,M
AU - Han,K
AU - Zhang,H
AU - Yin,J
DO - 10.1016/j.trd.2016.08.003
EP - 62
PY - 2016///
SN - 1361-9209
SP - 46
TI - Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand
T2 - Transportation Research Part D: Transport and Environment
UR - http://dx.doi.org/10.1016/j.trd.2016.08.003
UR - http://hdl.handle.net/10044/1/39535
VL - 48
ER -