Clausen J L, Georgian T, Gardner K H, Douglas T A
U.S. Army Corps of Engineers, Engineer Research Development Center, Cold Regions Research and Engineering Laboratory, 72 Lyme Road, Hanover, NH, 03755, USA.
U.S. Army Corps of Engineers, 1616 Capitol Avenue, Omaha, NE, 68102, USA.
Bull Environ Contam Toxicol. 2018 Jan;100(1):155-161. doi: 10.1007/s00128-017-2252-x. Epub 2017 Dec 21.
This study compares conventional grab sampling to incremental sampling methodology (ISM) to characterize metal contamination at a military small-arms-range. Grab sample results had large variances, positively skewed non-normal distributions, extreme outliers, and poor agreement between duplicate samples even when samples were co-located within tens of centimeters of each other. The extreme outliers strongly influenced the grab sample means for the primary contaminants lead (Pb) and antinomy (Sb). In contrast, median and mean metal concentrations were similar for the ISM samples. ISM significantly reduced measurement uncertainty of estimates of the mean, increasing data quality (e.g., for environmental risk assessments) with fewer samples (e.g., decreasing total project costs). Based on Monte Carlo resampling simulations, grab sampling resulted in highly variable means and upper confidence limits of the mean relative to ISM.
本研究将传统的抓取采样与增量采样方法(ISM)进行比较,以表征军事小武器靶场的金属污染情况。抓取样本结果具有较大的方差、正偏态非正态分布、极端异常值,并且即使样本彼此位于几十厘米范围内,重复样本之间的一致性也很差。极端异常值对主要污染物铅(Pb)和锑(Sb)的抓取样本均值有很大影响。相比之下,ISM样本的金属浓度中位数和均值相似。ISM显著降低了均值估计的测量不确定性,用更少的样本提高了数据质量(例如,用于环境风险评估)(例如,降低了项目总成本)。基于蒙特卡罗重采样模拟,相对于ISM,抓取采样导致均值和均值的置信上限变化很大。