Quantifying uncertainty of the reference sampling procedure used at Dornach under different soil conditions

Area of Science:

• Environmental Science
• Analytical Chemistry
• Soil Science

Background:

• Reference soil sampling procedures are crucial for accurate environmental monitoring.
• Understanding and quantifying uncertainty in soil sampling and analysis is essential for data reliability.

Purpose of the Study:

• To quantify the combined uncertainty of soil sampling and chemical analysis.
• To evaluate a 'top-down' approach for assessing measurement uncertainty in soil monitoring.

Main Methods:

• Analysis of Variance (ANOVA) was employed to dissect sampling and analytical uncertainty.
• A 'top-down' approach was used to integrate sampling and analysis into a single measurement process.
• The methodology was applied to data from the CEEM soil project, a sampling proficiency test, and the Swiss national soil-monitoring network (NABO).

Main Results:

• ANOVA effectively quantified both sampling and analytical contributions to overall uncertainty.
• The 'top-down' approach successfully integrated sampling and analytical steps, treating systematic errors as random in comparative assessments.
• The reference sampling procedure demonstrated applicability across diverse soil conditions and monitoring networks.

Conclusions:

• The integrated 'top-down' approach provides a robust framework for quantifying combined soil sampling and analysis uncertainty.
• Accurate uncertainty assessment is vital for the integrity of soil pollution monitoring data.
• Standardized sampling and analysis protocols enhance the comparability and reliability of environmental data.