Wolt J D, Nelson H P, Cleveland C B, van Wesenbeeck I J
Dow AgroSciences, 9330 Zionsville Road, Indianapolis, IN 46268, USA.
Rev Environ Contam Toxicol. 2001;169:123-64. doi: 10.1007/978-1-4613-0107-3_2.
Understanding pesticide risks requires characterizing pesticide exposure within the environment in a manner that can be broadly generalized across widely varied conditions of use. The coupled processes of sorption and soil degradation are especially important for understanding the potential environmental exposure of pesticides. The data obtained from degradation studies are inherently variable and, when limited in extent, lend uncertainty to exposure characterization and risk assessment. Pesticide decline in soils reflects dynamically coupled processes of sorption and degradation that add complexity to the treatment of soil biodegradation data from a kinetic perspective. Additional complexity arises from study design limitations that may not fully account for the decline in microbial activity of test systems, or that may be inadequate for considerations of all potential dissipation routes for a given pesticide. Accordingly, kinetic treatment of data must accommodate a variety of differing approaches starting with very simple assumptions as to reaction dynamics and extending to more involved treatments if warranted by the available experimental data. Selection of the appropriate kinetic model to describe pesticide degradation should rely on statistical evaluation of the data fit to ensure that the models used are not overparameterized. Recognizing the effects of experimental conditions and methods for kinetic treatment of degradation data is critical for making appropriate comparisons among pesticide biodegradation data sets. Assessment of variability in soil half-life among soils is uncertain because for many pesticides the data on soil degradation rate are limited to one or two soils. Reasonable upper-bound estimates of soil half-life are necessary in risk assessment so that estimated environmental concentrations can be developed from exposure models. Thus, an understanding of the variable and uncertain distribution of soil half-lives in the environment is necessary to estimate bounding values. Statistical evaluation of measures of central tendency for multisoil kinetic studies shows that geometric means better represent the distribution in soil half-lives than do the arithmetic or harmonic means. Estimates of upper-bound soil half-life values based on the upper 90% confidence bound on the geometric mean tend to accurately represent the upper bound when pesticide degradation rate is biologically driven but appear to overestimate the upper bound when there is extensive coupling of biodegradation with sorptive processes. The limited data available comparing distribution in pesticide soil half-lives between multisoil laboratory studies and multilocation field studies suggest that the probability density functions are similar. Thus, upper-bound estimates of pesticide half-life determined from laboratory studies conservatively represent pesticide biodegradation in the field environment for the purposes of exposure and risk assessment. International guidelines and approaches used for interpretations of soil biodegradation reflect many common elements, but differ in how the source and nature of variability in soil kinetic data are considered. Harmonization of approaches for the use of soil biodegradation data will improve the interpretative power of these data for the purposes of exposure and risk assessment.
了解农药风险需要以一种能够在广泛多样的使用条件下进行广泛概括的方式来描述环境中的农药暴露情况。吸附和土壤降解的耦合过程对于理解农药潜在的环境暴露尤为重要。从降解研究中获得的数据本质上是可变的,而且当范围有限时,会给暴露特征描述和风险评估带来不确定性。土壤中农药的减少反映了吸附和降解的动态耦合过程,这从动力学角度给土壤生物降解数据的处理增加了复杂性。研究设计的局限性也带来了额外的复杂性,这些局限性可能没有充分考虑测试系统中微生物活性的下降,或者可能不足以考虑给定农药的所有潜在消散途径。因此,数据的动力学处理必须采用各种不同的方法,从关于反应动力学的非常简单的假设开始,如果现有实验数据有必要,再扩展到更复杂的处理方法。选择合适的动力学模型来描述农药降解应该依靠对数据拟合的统计评估,以确保所使用的模型没有过度参数化。认识到实验条件和降解数据动力学处理方法的影响对于在农药生物降解数据集之间进行适当比较至关重要。评估不同土壤之间土壤半衰期的变异性是不确定的,因为对于许多农药来说,土壤降解速率的数据仅限于一两种土壤。在风险评估中,合理的土壤半衰期上限估计是必要的,以便能够从暴露模型中得出估计的环境浓度。因此,了解环境中土壤半衰期的可变和不确定分布对于估计边界值是必要的。对多土壤动力学研究的集中趋势度量进行统计评估表明,几何平均值比算术平均值或调和平均值更能代表土壤半衰期的分布。基于几何平均值的上90%置信区间的土壤半衰期上限估计值,在农药降解速率由生物因素驱动时往往能准确代表上限,但在生物降解与吸附过程广泛耦合时似乎高估了上限。将多土壤实验室研究和多地点田间研究中农药土壤半衰期分布进行比较的现有有限数据表明,概率密度函数是相似的。因此,从实验室研究确定的农药半衰期上限估计值,在暴露和风险评估方面保守地代表了田间环境中的农药生物降解情况。国际上用于解释土壤生物降解的指南和方法反映了许多共同要素,但在如何考虑土壤动力学数据变异性的来源和性质方面存在差异。统一土壤生物降解数据的使用方法将提高这些数据在暴露和风险评估方面的解释力。