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A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

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journal contribution
posted on 2016-12-08, 09:50 authored by Michael Hutchinson, Hyondong Oh, Wen-Hua ChenWen-Hua Chen
Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research.

Funding

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) grant number EP/K014307/1, the MOD University Defence Research Collaboration in Signal Processing and the Future Innovation Research Fund (Project Number 1.160086) of UNIST (Ulsan National Institute of Science and Technology).

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Information Fusion

Citation

HUTCHINSON, M., OH, H. and CHEN, W-H., 2016. A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors. Information Fusion, 36, pp. 130-148.

Publisher

Elsevier © The Authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

2016-11-15

Publication date

2016

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at http://creativecommons.org/licenses/by/4.0/.

ISSN

1566-2535

Language

  • en