Selection of priority properties to assess environmental hazard of pesticides

Abstract We assess the environmental hazard of 50 pesticides used in Italy by means of Hasse diagrams, a method based on graph theory. The criteria we use for ranking are persistence, and the physical-chemical properties, vapour pressure and water solubility, and yearly usage. When only the physical-chemical properties plus persistence are used to assess environmental hazard of pesticides in soils, eleven out of the 50 compounds studied here, methylbromide, bentazone, dalapon, diquat, linuron, mancozeb, metham-Na, TCA, metolachlor, paraquat, and simazine are considered potentially hazardous for the combination of long persistence in soil, high water solubility and low vapour pressure. Alachlor, atrazine, chloridazon, terbuthylazine and ziram are also a problem of concern because of their high loadings. To test whether the theoretical ranking is realistic, the list of identified compounds was compared with the results of monitoring studies carried out in the River Po. The assumption for this comparison is that, if the ranking method is correct, the probability of finding chemicals identified as hazardous should be higher than the probability of finding less hazardous chemicals. Chemicals ranked lower have less probability of being found both because of lower usage and because they are less persistent and/or less leachable. Results are quite encouraging since seven pesticides identified by our ranking method as most hazardous, alachlor, atrazine, bentazone, linuron, metolachlor, simazinc and terbuthylazine of the 8 analyzed for (previous plus TCA) were found, a success ratio of 88%. Results for all the other chemicals are presented in the paper. The second purpose of this study was the identification of the most important criteria to assess the chemicals; this assessment was performed using a matrix W. We concluded that the elimination of the criterion “usage” affects ranking more than the elimination of water solubility. However, none of the criteria, water solubility, vapour pressure, persistence and yearly usage can be eliminated, too much information would be lost if they were omitted. This conclusion is consistent with our decision to use only few criteria to rank the chemicals, criteria that are deemed to be independent of each other.

[1]  A. G. Hornsby,et al.  The SCS/ARS/CES Pesticide Properties Database for Environmental Decision-Making. II. Additional Compounds , 1994 .

[2]  Marcello G. Reggiani,et al.  On ranking chemicals for environmental hazard , 1986 .

[3]  David I. Gustafson,et al.  Groundwater ubiquity score: a simple method for assessing pesticide leachability , 1989 .

[4]  R. Brüggemann,et al.  Numerical and analytical model of pesticide root uptake model comparison and sensitivities , 1995 .

[5]  Rainer Brüggemann,et al.  A validation study for the estimation of aqueous solubility from n-octanol/water partition coefficients , 1991 .

[6]  A. G. Hornsby,et al.  The SCS/ARS/CES pesticide properties database for environmental decision-making. , 1992, Reviews of environmental contamination and toxicology.

[7]  Efraim Halfon,et al.  Is there a best model structure? I. Modeling the fate of a toxic substance in a lake , 1983 .

[8]  Frank Harary,et al.  Graph Theory , 2016 .

[9]  Brian A. Davey,et al.  An Introduction to Lattices and Order , 1989 .

[10]  R Brüggemann,et al.  Toxicology databases in the metadatabank of online databases. , 1995, Toxicology.

[11]  Marcello G. Reggiani,et al.  On Assessing Model Adequacy , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  S. Galassi,et al.  The use of biological methods for pesticide monitoring. , 1993, The Science of the total environment.

[13]  S. Pfleeger,et al.  Introduction to discrete structures , 1985 .

[14]  Milan Randić,et al.  The nature of chemical structure , 1990 .

[15]  Michael Matthies,et al.  Modellgestütztes Verfahren zur vergleichenden Verhaltensanalyse von Umweltchemikalien , 1987, Informatikanwendungen im Umweltbereich.

[16]  Rainer Brüggemann,et al.  An algebraic/graphical tool to compare ecosystems with respect to their pollution II: Comparative regional analysis , 1994 .

[17]  Rainer Brüggemann,et al.  An algebraic/graphical tool to compare ecosystems with respect to their pollution. The German River Elbe as an example. I : Hasse-diagrams , 1994 .

[18]  Efraim Halfon,et al.  Comparison of an index function and a vectorial approach method for ranking waste disposal sites , 1989 .

[19]  Rainer Brüggemann,et al.  Partially Ordered Sets — A Computerized Tool to Compare Environmental Databases , 1996 .

[20]  E. E. Kenaga,et al.  Relationship between water solubility, soil sorption, octanol-water partitioning, and concentration of chemicals in biota , 1980 .

[21]  R. Brüggemann,et al.  Advances in comparative analysis of adverse effects in aquatic ecosystems with emphasis on studies with humic substances and on progress in mathematical analysis techniques , 1995 .

[22]  T. Albanis,et al.  Herbicide contamination of Mediterranean estuarine waters : Results from a MED POL pilot survey , 1993 .

[23]  Efraim Halfon,et al.  Is there a best model structure? II. Comparing the model structures of different fate models , 1983 .

[24]  J. Weber The Pesticide Scorecard. , 1977 .