Research Article

Uncertainty Quantification of Non- Carcinogenic Soil Risk Assessment of Heavy Metal Contamination Near Oil Refinary Area: A Case Study

by  Hrishikesh Boruah
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Issue 113
Published: June 2026
Authors: Hrishikesh Boruah
10.5120/ijcad2fd9fe5d6c9
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Hrishikesh Boruah . Uncertainty Quantification of Non- Carcinogenic Soil Risk Assessment of Heavy Metal Contamination Near Oil Refinary Area: A Case Study. International Journal of Computer Applications. 187, 113 (June 2026), 68-70. DOI=10.5120/ijcad2fd9fe5d6c9

                        @article{ 10.5120/ijcad2fd9fe5d6c9,
                        author  = { Hrishikesh Boruah },
                        title   = { Uncertainty Quantification of Non- Carcinogenic Soil Risk Assessment of Heavy Metal Contamination Near Oil Refinary Area: A Case Study },
                        journal = { International Journal of Computer Applications },
                        year    = { 2026 },
                        volume  = { 187 },
                        number  = { 113 },
                        pages   = { 68-70 },
                        doi     = { 10.5120/ijcad2fd9fe5d6c9 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2026
                        %A Hrishikesh Boruah
                        %T Uncertainty Quantification of Non- Carcinogenic Soil Risk Assessment of Heavy Metal Contamination Near Oil Refinary Area: A Case Study%T 
                        %J International Journal of Computer Applications
                        %V 187
                        %N 113
                        %P 68-70
                        %R 10.5120/ijcad2fd9fe5d6c9
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Uncertainty is inherent in almost all aspects of our life. We usually ignore uncertainty to avoid complexity. However, solutions so obtained are quite far from the reality and ignoring uncertainty may lead to over (under) estimation. So, we need to quantify the uncertainty so as to be aware of the risk involved in any decision-making process. Uncertainties can be modeled and analyzed using different theories, viz. Probability theory, Possibility theory, Evidence theory etc. Modeling of an uncertain parameter depends on the nature of the information available. This paper considered uncertainty quantification of parameters in the case of risk assessment. Risk means, risk associated with the heavy metal released into the environment. There are various pathways through which the heavy metal can reach human being namely inhalation, ingestion through drinking water and through contaminate food. The main aim of risk assessment is to determine the potential detriment to human health from exposure to a substance or activity that under plausible circumstances can cause to human health. This paper analyzed the propagation of the risk in terms of probability theory. One advanced method of probabilistic risk assessment (PRAs), P-box method is discussed in this paper. A case study is also carried out with this method.

References
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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Uncertainty Variability Probability bounds analysis Probability-box(p-box)

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