Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A study examining the relationship between alexithymia and challenging behaviour in adults with intellectual disability.

Journal of intellectual disability research : JIDR·2015
Same author

The UK geochemical environment and cardiovascular diseases: magnesium in food and water.

Environmental geochemistry and health·2014
Same author

Airs, waters and places.

Environmental geochemistry and health·2013
Same author

Evolution.

Environmental geochemistry and health·2013
Same author

Editorial.

Environmental geochemistry and health·2013
Same author

Airs, waters and places.

Environmental geochemistry and health·2013

Related Experiment Video

Updated: May 6, 2026

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores
10:31

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

Published on: December 6, 2015

29.2K

Data handling and pattern recognition for metal contaminated soils.

B E Davies1

  • 1Department of Environmental Science, University of Bradford, BD7 1DP, Bradford, West Yorkshire, England.

Environmental Geochemistry and Health
|November 9, 2013
PubMed
Summary
This summary is machine-generated.

Interpreting metal contamination in soils requires statistical analysis of variable field data. This approach uses statistical tests and computer graphics to identify pollution patterns and excesses.

More Related Videos

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples
09:51

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

Published on: September 19, 2025

663
Deployment and Retrieval of Mineral Samplers
05:52

Deployment and Retrieval of Mineral Samplers

Published on: January 20, 2026

380

Related Experiment Videos

Last Updated: May 6, 2026

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores
10:31

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

Published on: December 6, 2015

29.2K
TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples
09:51

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

Published on: September 19, 2025

663
Deployment and Retrieval of Mineral Samplers
05:52

Deployment and Retrieval of Mineral Samplers

Published on: January 20, 2026

380

Area of Science:

  • Environmental Science
  • Geochemistry
  • Soil Science

Background:

  • Laboratory science excels at controlled experiments, but field science faces inherent data variability.
  • Hypothesis testing in field sciences necessitates robust statistical interpretation of noisy data.
  • Distinguishing natural metal presence from anthropogenic contamination in soils is challenging.

Purpose of the Study:

  • To present a systematic methodology for interpreting results from metal-contaminated soil surveys.
  • To outline statistical approaches for identifying anthropogenic metal excesses in soil.
  • To describe the use of computer graphics for evaluating spatial patterns of soil pollution.

Main Methods:

  • Application of statistical tests to soil survey data to detect metal excesses.
  • Utilizing computergraphic techniques to analyze spatial distribution patterns of contaminants.
  • Interpreting inherently variable field data through careful statistical analysis.

Main Results:

  • Development of a systematic approach for analyzing metal contamination in soils.
  • Successful identification of anthropogenic metal excesses using statistical methods.
  • Evaluation of distinct spatial patterns indicative of pollution processes.

Conclusions:

  • Statistical interpretation and spatial analysis are crucial for understanding metal contamination in field soils.
  • The described methods enable reliable identification of pollution sources in complex environmental settings.
  • This systematic approach enhances the accuracy of environmental risk assessments for contaminated soils.