Rapid estimation of global civil aviation emissions with uncertainty quantification . Simone, N. W., Stettler, M. E., & Barrett, S. R. Transportation Research Part D: Transport and Environment , 25:33 - 41, 2013.
Rapid estimation of global civil aviation emissions with uncertainty quantification  [link]Paper  doi  abstract   bibtex   
Abstract In this paper we describe the methods used to develop the open source Aviation Emissions Inventory Code and produce a global emissions inventory for scheduled civil aviation, with quantified uncertainty. We estimate that in 2005, scheduled civil aviation was responsible for 180.6 Tg of fuel burn, which agrees to within 4% of other published emissions inventories for 2004 and 2006. By comparing the Aviation Emissions Inventory Code with flight data records, we show that the mean bias in predicted fuel burn at the airport-pair level is +1% for an ensemble of 132 flights, and less than 10% for 5 of the 6 aircraft types used in the validation.
@article{Simone201333,
title = "Rapid estimation of global civil aviation emissions with uncertainty quantification ",
journal = "Transportation Research Part D: Transport and Environment ",
volume = "25",
number = "",
pages = "33 - 41",
year = "2013",
note = "",
issn = "1361-9209",
doi = "http://dx.doi.org/10.1016/j.trd.2013.07.001",
url = "http://www.sciencedirect.com/science/article/pii/S1361920913001028",
author = "Nicholas W. Simone and Marc E.J. Stettler and Steven R.H. Barrett",
keywords = "Aircraft emissions",
keywords = "Aviation fuel burn",
keywords = "Aviation Emissions Inventory Code ",
abstract = "Abstract In this paper we describe the methods used to develop the open source Aviation Emissions Inventory Code and produce a global emissions inventory for scheduled civil aviation, with quantified uncertainty. We estimate that in 2005, scheduled civil aviation was responsible for 180.6 Tg of fuel burn, which agrees to within 4% of other published emissions inventories for 2004 and 2006. By comparing the Aviation Emissions Inventory Code with flight data records, we show that the mean bias in predicted fuel burn at the airport-pair level is +1% for an ensemble of 132 flights, and less than 10% for 5 of the 6 aircraft types used in the validation. "
}

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