RESUMEN
In this project, we apply the method of partial ordering on the ranking of 74 contaminated sites located in the county of West Zealand (Denmark). The method is based on the concept that the parameters are kept separated through the ranking analysis, and thus no weighing of the different parameter values is necessary. The ranking is displayed in a graphical form by the Hasse diagram technique to ease the interpretation. A critical comparison is made of the ranking of contaminated sites by the partial ordering method and an index function used by the county of West Zealand. Comparing the ranking by the partial ordering method to the index function shows that the choice of score points and index function highly influences the ranking result, as only four sites are equally ranked. The importance of the parameters used to identify the environmental hazard of the contaminated sites is analyzed in order to evaluate the influence of each parameter on the ranking. From among a total of six different parameters, two have high influence, two medium, and two low because of both the construction of the scoring system and the characteristics of the data.
Asunto(s)
Medición de Riesgo/métodos , Suelo/análisis , Contaminación Química del Agua/estadística & datos numéricos , Dinamarca , Modelos Estadísticos , Administración de la Seguridad , Contaminantes Químicos del Agua/análisisRESUMEN
Partial order theory (POT) is an attractive and operationally simple method that allows ordering of compounds, based on selected structural and/or electronic descriptors (modeled order), or based on their end points, e.g., solubility (experimental order). If the modeled order resembles the experimental order, compounds that are not experimentally investigated can be assigned a position in the model that eventually might lead to a prediction of an end-point value. However, in the application of POT in quantitative structure-activity relationship modeling, only the compounds directly comparable to the noninvestigated compounds are applied. To explore the possibilities of improving the methodology, the theory is extended by application of the so-called linear extensions of the model order. The study show that partial ordering combined with linear extensions appears as a promising tool providing probability distribution curves in the range of possible end-point values for compounds not being experimentally investigated.