Mineralogical and elemental data for soil discriminating and geolocation tracing

Area of Science:

• Forensic geology
• Geochemistry
• Mineralogy

Background:

• Soil analysis is crucial for forensic science, aiding in geolocation and identifying soil diversities.
• Forensic geologists utilize soil characteristics to link evidence to specific locations.

Purpose of the Study:

• To investigate the potential of mineralogical and elemental composition for discriminating soil origins.
• To classify soil samples based on their elemental and mineral profiles to their city of origin in China.

Main Methods:

• X-ray diffraction (XRD) for mineralogical analysis.
• X-ray fluorescence (XRF) for elemental oxide weight percentages.
• Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), and K-Nearest Neighbors (KNN) for data analysis and classification.

Main Results:

• Mineralogical analysis identified key minerals (montmorillonite, kaolinite, amphibole, feldspar, calcite, dolomite) indicative of northern or southern Chinese origins.
• Elemental analysis quantified 10 oxides (Al2O3, SiO2, Fe2O3, K2O, Na2O, MgO, CaO, P2O5, MnO, TiO2).
• Statistical models successfully classified all 80 soil samples to their precise city of origin.

Conclusions:

• Both mineralogical and elemental compositions are powerful indicators for soil discrimination.
• The study confirms the effectiveness of integrated analytical and statistical approaches for forensic soil source tracing.