Leaching potential of some phenylureas and their main metabolites through laboratory studies

BACKGROUND, AIMS AND SCOPE: Laboratory studies were conducted with the aim of defining the leaching potential of some phenylureas and their metabolites. A first study was performed for calculating their leaching index (as GUS) on the base of intrinsic properties: persistence (as DT50) and mobility (as Koc) in soil. Another study consisted of aged column leaching experiments whose meaning was to semi-quantify the occurrence of the tested compounds in the leachates, so simulating in field conditions. METHODS: The tested compounds were: diuron, linuron and monolinuron (parents); 3,4-dichloroaniline (DCA), 4-chloroaniline (CLA), 1-(3,4-dichlorophenyl)-3-methylurea (DCPMU), 1-(3,4-dichlorophenyl)urea (DCPU), 1-(4-chlorophenyl)urea (CPU) and monuron, this latter considered both as a metabolite and parent compound. The Koc values of the examined substances were determined by the HPLC screening methods, according to the OECD TG 121. DT50 determinations and aged column leaching experiments were carried out according to SETAC procedures. RESULTS AND DISCUSSION: The examined compounds showed a rather wide range of persistence in soil, with DT50 values less than 2 days for DCA and CLA, close to 8 days for DCPU and CPU and from 16 (diuron) up to 24.8 (DCPMU) days for the others. Their mobility was generally high, based on their Koc values, which ranged from 33 (CPU) to 406 (linuron). The GUS indices indicated that monuron has a clear potential to contaminate groundwater (> 2.8); DCPMU, monolinuron, CPU and diuron are intermediate contaminants (1.8-2.8). Linuron, DCPU, CLA and DCA exhibited a non-leaching behaviour (< 1.8). The aged leaching column experiments showed that parents were found in the leachates at very high percentages respect to the doses applied. The metabolites reached much less percentages, the highest values were observed for monuron from diuron (5.7), CPU (7.2) and DCPMU (8.2%). CONCLUSION: Diuron, Monuron, CPU and DCPMU on the basis of their intrinsic properties, formation from their parents and occurrence in leachates from aged column leaching studies, seem to possess the characteristics of groundwater contaminants. The methodological approach of this study is relatively easy and rapid, hence it can represent a tool for a first screening of compounds such as pesticide metabolites (generally available only in small quantities and for which a field study is not conceivable) or other compounds for which not adequate environmental data are available.     

人工神经网络模拟芳基脲土壤吸附系数研究

对38种芳基脲类化合物的土壤吸附系数进行了定量结构－活性相关研究。利用量子化学的AM1方法提取化合物的结构参数，运用多元回归分析和人工神经网络对该化合物进行比较研究。研究结果表明，神经网络法所得结果优于多元回归分析结果，并对分析结果进行了吸附机理讨论。