Articles | Volume 19, issue 5
https://doi.org/10.5194/acp-19-2881-2019
https://doi.org/10.5194/acp-19-2881-2019
Research article
 | 
07 Mar 2019
Research article |  | 07 Mar 2019

Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model

Ksenia Aleksankina, Stefan Reis, Massimo Vieno, and Mathew R. Heal

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Cited articles

Air Quality Expert Group: Mitigation of United Kingdom PM 2.5 Concentrations, available at: https://uk-air.defra.gov.uk/assets/documents/reports/cat11/1508060903_DEF-PB14161_Mitigation_of_UK_PM25.pdf (last access: 15 May 2018), 2013. 
Aleksankina, K.: Advanced methods for uncertainty assessment and global sensitivity analysis of a Eulerian atmospheric chemistry transport model [Data set], Zenodo, available at: https://doi.org/10.5281/zenodo.2213633, 2018. 
Aleksankina, K., Heal, M. R., Dore, A. J., Van Oijen, M., and Reis, S.: Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study, Geosci. Model Dev., 11, 1653–1664, https://doi.org/10.5194/gmd-11-1653-2018, 2018. 
Asher, M. J., Croke, B. F. W., Jakeman, A. J., and Peeters, L. J. M.: A review of surrogate models and their application to groundwater modeling, Water Resour. Res., 51, 5957–5973, https://doi.org/10.1002/2015WR016967, 2015. 
Beddows, A. V., Kitwiroon, N., Williams, M. L., and Beevers, S. D.: Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode, Environ. Sci. Technol., 51, 6229–6236, https://doi.org/10.1021/acs.est.6b05873, 2017. 
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Short summary
Atmospheric chemistry transport models are widely used to underpin policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Understanding the level of confidence in model predictions is thus vital. We present a comprehensive approach for uncertainty assessment and global variance-based sensitivity analysis to propagate uncertainty from model input data and identify the extent to which uncertainty in different emissions drives the model output uncertainty.
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