title: Analyzing the spatial distribution of PCB concentrations in soils using below-quantification limit data.
abstract: Polychlorinated biphenyls (PCBs) are highly toxic environmental pollutants that can accumulate in soils. We consider the problem of explaining and mapping the spatial distribution of PCBs using a spatial data set of 105 PCB-187 measurements from a region in the north of France. A large proportion of our data (35%) fell below a quantification limit (QL), meaning that their concentrations could not be determined to a sufficient degree of precision. Where a measurement fell below this QL, the inequality information was all that we were presented with. In this work, we demonstrate a full geostatistical analysis-bringing together the various components, including model selection, cross-validation, and mapping-using censored data to represent the uncertainty that results from below-QL observations. We implement a Monte Carlo maximum likelihood approach to estimate the geostatistical model parameters. To select the best set of explanatory variables for explaining and mapping the spatial distribution of PCB-187 concentrations, we apply the Akaike Information Criterion (AIC). The AIC provides a trade-off between the goodness-of-fit of a model and its complexity (i.e., the number of covariates). We then use the best set of explanatory variables to help interpolate the measurements via a Bayesian approach, and produce maps of the predictions. We calculate predictions of the probability of exceeding a concentration threshold, above which the land could be considered as contaminated. The work demonstrates some differences between approaches based on censored data and on imputed data (in which the below-QL data are replaced by a value of half of the QL). Cross-validation results demonstrate better predictions based on the censored data approach, and we should therefore have confidence in the information provided by predictions from this method.
authors.affiliation: INRA, US 1106 InfoSol, Orleans, France. Thomas.Orton@derm.qld.gov.au
authors.forename: Thomas G
authors.initials: TG
authors.lastname: Orton
authors.forename: Nicolas P A
authors.initials: NP
authors.lastname: Saby
authors.forename: Dominique
authors.initials: D
authors.lastname: Arrouays
authors.forename: Claudy C
authors.initials: CC
authors.lastname: Jolivet
authors.forename: Estelle J
authors.initials: EJ
authors.lastname: Villanneau
authors.forename: Jean-Baptiste
authors.initials: JB
authors.lastname: Paroissien
authors.forename: Ben P
authors.initials: BP
authors.lastname: Marchant
authors.forename: Giovanni
authors.initials: G
authors.lastname: Caria
authors.forename: Enrique
authors.initials: E
authors.lastname: Barriuso
authors.forename: Antonio
authors.initials: A
authors.lastname: Bispo
authors.forename: Olivier
authors.initials: O
authors.lastname: Briand
mesh_terms: D004784:Environmental Monitoring; D005602:France; D008962:Models, Theoretical; D011078:Polychlorinated Biphenyls / Q000737:chemistry*; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000737:chemistry*
chemical_list: D012987:Soil; D012989:Soil Pollutants; D011078:Polychlorinated Biphenyls