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Application of Partial Orders and Hasse Matrices in Ranking Contaminated Sites

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Multi-indicator Systems and Modelling in Partial Order

Abstract

Contaminated site cleanup is a multibillion dollar issue in Canada. Practical decision support tools are needed to help prioritise contaminated site cleanup funding across a portfolio of many sites. This chapter illustrates the concept of prioritising contaminated site management decisions using environmental risk, societal perception and environmental liability as the measures. Using previously published information on 20 contaminated sites located in Canada, these three aspects are combined by applying partial order concepts to prioritise sites. The authors show how societal perception and environmental liability influence site prioritisation compared to prioritisation based on environmental risk alone. They recommended additional research in quantifying the societal perception of contaminated sites prior to practical application of the concepts explained in the chapter.

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Notes

  1. 1.

    A Phase 2 Environmental Site Assessment (ESA) is a contaminated site investigation where soil, sediment, soil vapour, surface water or groundwater samples are obtained and analysed for contaminants.

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Author information

Authors and Affiliations

  1. Schulich School of Engineering, University of Calgary, ENF 262, 2500 University Drive NW, Calgary, AB, Canada, T2N 1N4

    Ron J. Thiessen & Gopal Achari

Authors
  1. Ron J. Thiessen
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  2. Gopal Achari
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Correspondence to Ron J. Thiessen .

Editor information

Editors and Affiliations

  1. Leibniz-Institut für Gewässerökologie und Binnenfischerei, Berlin, Berlin, Germany

    Rainer Brüggemann

  2. Awareness-Center, Roskilde-Veddelev, Denmark

    Lars Carlsen

  3. HTW Berlin, University of Applied Sciences, Berlin, Germany

    Jochen Wittmann

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Thiessen, R.J., Achari, G. (2014). Application of Partial Orders and Hasse Matrices in Ranking Contaminated Sites. In: Brüggemann, R., Carlsen, L., Wittmann, J. (eds) Multi-indicator Systems and Modelling in Partial Order. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8223-9_12

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