Juhler R K, Henriksen T H, Ernstsen V, Vinther F P, Rosenberg P
Geological Survey of Denmark and Greenland, GEUS, Øster Voldgade 10, DK-1350 Copenhagen K, Denmark.
J Environ Qual. 2008 Aug 8;37(5):1719-32. doi: 10.2134/jeq2006.0230. Print 2008 Sep-Oct.
Dissipation time is a key parameter when studying and modeling the environmental fate of pesticides. This study was conducted to characterize the variability of pesticide disappearance in soil and to identify possible controlling parameters related to intrinsic soil properties and microbiology. Multivariate data analysis was used to study spatial variability in three horizons from 24 sandy soil profiles. The time for 50% disappearance (DT(50)) was characterized for two herbicides, metribuzin (MBZ) and MCPA, and methyltriazine amine (MTA; transformation product of metsulfuron-methyl, tribenuron-methyl, thifensulfuron-methyl, and chlorsulfuron). Normal and log-normal distributions were compared for DT(50) and soil properties and descriptive statistics were calculated. Conformity with log-transformed distributions was observed and assuming normality of the DT(50) data would cause 5 to 35% overestimation. Mean DT(50) were: MCPA 9.5, MBZ 168, and MTA 127. Significant effect of soil depth on DT(50) was shown for MCPA and MBZ, with low values in deeper horizons. Simple linear correlation for combinations of MCPA, MTA, pH, and total organic carbon (TOC) was observed. Using partial least squares regression (PLS) 71 to 85% of the total DT(50) variance was explained. A specific predictor variable could not be identified as the controlling components differed within horizons and compounds. For MCPA the overall important predictor variables were microbiology and TOC, whereas for MTA and MBZ it was inorganic variables (Al, Fe, cation exchange capacity, base saturation percent, and pH) and microbiology. The study indicates that PLS generated input data can improve pesticide fate modeling and reduce the uncertainty in dissipation estimation.
在研究农药的环境归趋并对其进行建模时，消散时间是一个关键参数。本研究旨在表征农药在土壤中消失的变异性，并确定与土壤固有性质和微生物学相关的可能控制参数。采用多变量数据分析方法研究了24个砂质土壤剖面三个土层的空间变异性。对两种除草剂嗪草酮（MBZ）和2甲4氯（MCPA）以及甲基三嗪胺（MTA；甲磺隆、苯磺隆、噻吩磺隆和氯磺隆的转化产物）的50%消失时间（DT(50)）进行了表征。比较了DT(50)和土壤性质的正态分布与对数正态分布，并计算了描述性统计量。观察到与对数转换分布的一致性，假设DT(50)数据呈正态分布会导致高估5%至35%。DT(50)的平均值分别为：MCPA为9.5，MBZ为168，MTA为127。对于MCPA和MBZ，土壤深度对DT(50)有显著影响，较深土层的值较低。观察到MCPA、MTA、pH和总有机碳（TOC）组合之间存在简单线性相关性。使用偏最小二乘回归（PLS）解释了DT(50)总方差的71%至85%。由于不同土层和化合物的控制成分不同，无法确定特定的预测变量。对于MCPA，总体重要的预测变量是微生物学和TOC，而对于MTA和MBZ，是无机变量（铝、铁、阳离子交换容量、碱饱和度百分比和pH）和微生物学。该研究表明，PLS生成的输入数据可以改善农药归趋建模并降低消散估计中的不确定性。
