A three-dimensional sampling design based on the coefficient of variation method for soil environmental damage...

Area of Science:

• Environmental Science
• Geostatistics
• Soil Science

Background:

• Traditional grid soil sampling methods often lack efficiency and accuracy.
• Contaminated sites, such as nonferrous metal processing plants, require precise soil sampling for effective remediation.
• Arsenic (As) contamination poses significant environmental and health risks.

Purpose of the Study:

• To develop and validate a cost-effective, high-accuracy soil sampling strategy.
• To optimize sampling density and depth for site contamination assessment.
• To reduce the financial burden associated with soil sampling and testing.

Main Methods:

• Utilized a three-dimensional kriging interpolation model based on preliminary investigation data.
• Applied the coefficient of variation method to estimate surface soil sampling density within pollution intervals.
• Determined optimal sampling depth based on vertical prediction results of pollution intervals.

Main Results:

• The optimized soil sampling method achieved higher accuracy with fewer sampling points.
• Sampling accuracy reached 87.62% after depth optimization.
• Significant cost reductions were observed: 66.13% for sampling and 56.93% for testing compared to full deployment.

Conclusions:

• The developed method offers a novel and economical approach for predicting site contamination.
• Optimized sampling strategies enhance accuracy and reduce resource expenditure.
• Provides crucial data for guiding effective post-remediation strategies at contaminated sites.