title: The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils.
abstract: This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil-water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil-water reaction in this case study). The probabilities of cells belonging to classes of oil-water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.
authors.affiliation: Departamento de Ciências da Terra (GeoBioTec), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. soniaroxo@gmail.com.
authors.forename: Sónia
authors.initials: S
authors.lastname: Roxo
authors.affiliation: Departamento de Ciências da Terra (GeoBioTec), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. ja@fct.unl.pt.
authors.forename: José António
authors.initials: JA
authors.lastname: de Almeida
authors.affiliation: Departamento de Ciências da Terra (GeoBioTec), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. filipavmatias@gmail.com.
authors.forename: Filipa Vieira
authors.initials: FV
authors.lastname: Matias
authors.affiliation: ILATTI - Universidade Federal da Integração Latino Americana, Foz do Iguaçu, Brazil. helima@ist.utl.pt.|CERENA-Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal. helima@ist.utl.pt.
authors.forename: Herlander
authors.initials: H
authors.lastname: Mata-Lima
authors.affiliation: Departamento de Ciências da Terra (GeoBioTec), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. svtb@fct.unl.pt.
authors.forename: Sofia
authors.initials: S
authors.lastname: Barbosa
mesh_terms: D004784:Environmental Monitoring / Q000379:methods*; D006838:Hydrocarbons / Q000032:analysis*; D008956:Models, Chemical; D010578:Petroleum / Q000032:analysis*; D059392:Petroleum Pollution / Q000032:analysis* / Q000706:statistics & numerical data; D012987:Soil / Q000737:chemistry; D012989:Soil Pollutants / Q000032:analysis*; D062206:Spatial Analysis
chemical_list: D006838:Hydrocarbons; D010578:Petroleum; D012987:Soil; D012989:Soil Pollutants
keywords: Combining hard data and soft data; Mapping of uncertainty; Sensory perception indicators; Soil contamination; Stochastic simulation; Total petroleum hydrocarbons (TPHs)
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