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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils
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Applying Incremental Sampling Methodology to Soils Containing Heterogeneously Distributed Metallic Residues to

J L Clausen1, T Georgian2, K H Gardner3

  • 1U.S. Army Corps of Engineers, Engineer Research Development Center, Cold Regions Research and Engineering Laboratory, 72 Lyme Road, Hanover, NH, 03755, USA. jay.l.clausen@usace.army.mil.

Bulletin of Environmental Contamination and Toxicology
|December 23, 2017
PubMed
Summary
This summary is machine-generated.

Incremental sampling methodology (ISM) provides more accurate metal contamination data than grab sampling at military firing ranges. ISM reduces uncertainty and costs by using fewer samples, improving environmental risk assessments.

Keywords:
HeterogeneityMetallic residueSmall-arms rangeSoil samplingSpatial statistical analysisUpper confidence limit

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Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Geospatial Analysis

Background:

  • Military small-arms ranges are often contaminated with metals like lead (Pb) and antimony (Sb).
  • Conventional grab sampling methods can yield highly variable and unreliable data for characterizing such contamination.
  • High variability in grab samples is due to spatial heterogeneity and extreme outliers.

Purpose of the Study:

  • To compare the effectiveness of incremental sampling methodology (ISM) against conventional grab sampling for characterizing metal contamination.
  • To assess the impact of sampling methodology on data quality, uncertainty, and cost-efficiency.
  • To determine the optimal sampling strategy for accurate metal contamination assessment at contaminated sites.

Main Methods:

  • Comparison of grab sampling and incremental sampling methodology (ISM) at a military small-arms range.
  • Statistical analysis of metal concentration data (Pb, Sb) including variance, distribution, and outlier detection.
  • Monte Carlo resampling simulations to evaluate the variability of sample means and confidence limits.

Main Results:

  • Grab samples exhibited large variances, non-normal distributions, and poor duplicate agreement, heavily influenced by extreme outliers for Pb and Sb.
  • Incremental sampling methodology (ISM) yielded similar median and mean metal concentrations, indicating greater data stability.
  • ISM significantly reduced measurement uncertainty and improved data quality for environmental risk assessments.

Conclusions:

  • Incremental sampling methodology (ISM) is superior to grab sampling for accurately characterizing metal contamination at complex sites like military ranges.
  • ISM enhances data reliability and cost-effectiveness by reducing sample numbers and measurement uncertainty.
  • Adopting ISM improves the quality of environmental risk assessments and site remediation decisions.