Latest revision as of 12:30, 16 February 2021

Abstract

Major accidents may cause both direct damages to the exposed population and damage to the environment, indirectly affecting the population by the contamination of land, surface water and groundwater. A wide attention was paid to date to the assessment of the direct risk for the population deriving from major accidents (fires, explosions, toxic releases). Less work was devoted to the quantitative assessment of the risk due to the environmental consequences of major accidents. In the present study, an innovative GIS-based approach was developed for the quantitative assessment of the risk caused by damage to the environment deriving from major accidents involving pipelines. The method allows the calculation of local and overall environmental risk indexes, expressed both in physical and monetary terms. These are structured so that in perspective they can be combined with the risk obtained for the exposed population, providing a comprehensive risk figure of the potential consequences of major accidents involving oil pipelines. A specific software tool was developed to support the application of the methodology. A real-life case-study is presented and discussed in order to assess the potentiality of the approach. The results confirm that, in the frame of safety guidelines and good practices for pipelines, the proposed methodology represents a useful tool to fulfil requirements concerning the comprehensive risk assessment of pipeline operation, providing useful information on safety-critical segments and on the expected severity and economic impact of spill scenarios. © 2018 Elsevier Ltd

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.1016/j.jlp.2018.11.005

• http://hdl.handle.net/11585/667778

• https://api.elsevier.com/content/article/PII:S0950423018307095?httpAccept=text/xml,

https://api.elsevier.com/content/article/PII:S0950423018307095?httpAccept=text/plain,

http://dx.doi.org/10.1016/j.jlp.2018.11.005 under the license https://www.elsevier.com/tdm/userlicense/1.0/

• https://www.sciencedirect.com/science/article/pii/S0950423018307095,

https://academic.microsoft.com/#/detail/2898913705