Towards a Comprehensive Framework for Climate Change Multi-Risk Assessment in the Mining Industry

Mavrommatis, Evangelos; Damigos, Dimitris; Mirasgedis, Sevastianos

dc.contributor.author	Mavrommatis, Evangelos
dc.contributor.author	Damigos, Dimitris
dc.contributor.author	Mirasgedis, Sevastianos
dc.date.accessioned	2021-01-14T16:29:28Z
dc.date.available	2021-01-14T16:29:28Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/52782
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.20480
dc.rights	Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/3.0/gr/	*
dc.subject	climate change	en
dc.subject	risk assessment	en
dc.subject	mining	en
dc.subject	adaptation	en
dc.subject	Bayesian networks	en
dc.title	Towards a Comprehensive Framework for Climate Change Multi-Risk Assessment in the Mining Industry	en
heal.type	journalArticle
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2019-06-26
heal.bibliographicCitation	Mavrommatis, E., Damigos, D., & Mirasgedis, S. (2019). Towards a Comprehensive Framework for Climate Change Multi-Risk Assessment in the Mining Industry. Infrastructures, 4(3), 38. https://doi.org/10.3390/infrastructures4030038	en
heal.abstract	Changing climate conditions affect mining operations all over the world, but so far, the mining sector has focused primarily on mitigation actions. Nowadays, there exists increasing recognition of the need for planned adaptation actions. To this end, the development of a practical tool for the assessment of climate change-related risks to support the mining community is deemed necessary. In this study, a comprehensive framework is proposed for climate change multi-risk assessment at the local level customized for the needs of the mining industry. The framework estimates the climate change risks in economic terms by modeling the main activities that a mining company performs, in a probabilistic model, using Bayes’ theorem. The model permits incorporating inherent uncertainty via fuzzy logic and is implemented in two versatile ways: as a discrete Bayesian network or as a conditional linear Gaussian network. This innovative quantitative methodology produces probabilistic outcomes in monetary values estimated either as percentage of annual loss revenue or net loss/gains value. Finally, the proposed framework is the first multi-risk methodology in the mining context that considers all the relevant hazards caused by climate change extreme weather events, which offers a tool for selecting the most cost-effective action among various adaptation strategies.	en
heal.publisher	MDPI	en
heal.journalName	Infrastructures	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	false
dc.identifier.doi	10.3390/infrastructures4030038	el