Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data
Sung-Min Kim; Yosoon Choi · 2017 · International Journal of Environmental Research and Public Health
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-r
Abstract by Sung-Min Kim; Yosoon Choi, International Journal of Environmental Research and Public Health (2017) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3390/ijerph14060654