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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. [ABSTRACT FROM AUTHOR]

In this investigation, a new and simple way to analyze, interpret, and generalize monitoring data of occurrence of pesticide active ingredients in surface waters was developed. The occurrence is quantified using the variables frequency of detection and the concentration level. These two parameters are associated with basically different ecotoxicological effects; for example, a high frequency of detection may be related to bioaccumulation problems, while the level of concentration also controls the acute toxicological effects. The active ingredients were ranked on the basis of the monitoring data in relation to both the frequency of finding and concentration level using the concept of partial ordered sets. The resulting rankings was correlated with other rankings based on descriptors such as sprayed area, applied dose, adsorption to soil organic carbon, vapor pressure, and soil dissipation half-life. A similarity index was applied in order to compare the ranking of the monitoring data with the ranking of the descriptors. It is shown how partial order theory can be used to evaluate the relevance of every single descriptor. The dosage is found to be the most important descriptor, followed by the sprayed area and the adsorption to organic carbon ending up a very close similarity between, respectively, the rankings using monitoring data and rankings using these three descriptors. [ABSTRACT FROM AUTHOR]

The risk of five different pyrogenic polycyclic aromatic hydrocarbons (PAHs) toward two soil-dwelling organisms (i.e., springtail [Folsomia fimetaria] and earthworm [Eisenia veneta]) has been investigated with respect to lethality and reproduction at two soil depths in a typical Danish soil. Predicted environmental concentrations (PECs) are calculated with a model describing diffusion, bulk flow, and microbial degradation. Predicted no-effect concentrations (PNECs) are derived from laboratory experiments performed with nominal soil concentrations in the range from 0 to 300 µg PAH/g dry weight. Risk is estimated through a stochastic approach as well as with the conventional point estimate. The point estimate predicts a potential risk for pyrene, log PEC/PNEC = -0.01, with respect to springtail reproduction at 5 cm soil depth. In all other scenarios, the point-estimate log-ratios are significantly lower than 0. For the stochastic approach risk is defined when the probability for risk (i.e., the probability for log PEC/PNEC > 0), is larger than 5%. The results show that risk is present only for springtail and in the following five scenarios: For anthracene, the probability for risk with respect to lethality is 12% at 5 cm soil depth, and 17 and 5% with respect to reproduction at 5 and 50 cm soil depth, respectively; for pyrene the probability for risk with respect to reproduction is 49 and 14% at 5 and 50 cm, respectively. The results show that risk cannot be defined unambiguously with the two approaches. The probabilistic approach is less restrictive, and even small probabilities may be used as early-warning indications that risk may be posed under unfavorable circumstances. [ABSTRACT FROM AUTHOR]