A comprehensive geochemical modeling project for climate change mitigation through enhanced rock weathering, using real-world data from the USGS Alaska Geochemical Database.
This project demonstrates advanced geochemical modeling techniques to analyze the potential of Enhanced Rock Weathering (ERW) for CO₂ sequestration and agricultural applications. Using Python and PHREEQC integration, the analysis processes over 23,000 rock samples from Alaska to evaluate weathering potential, nutrient release, and carbon sequestration capabilities.
- Multi-component geochemical modeling using PHREEQC-Python integration
- Real-world data analysis from USGS Alaska Geochemical Database (AGDB4)
- Advanced visualization suite with 9-panel analysis dashboard
- Climate impact assessment through CO₂ sequestration calculations
- Agricultural potential evaluation via nutrient release analysis
- Professional technical reporting with comprehensive documentation
- pH Buffering: 5.60 → 8.00 (Δ = +2.40 pH units)
- Total Cation Release: 1.01 mmol/L (Ca²⁺: 0.64, Mg²⁺: 0.37)
- CO₂ Sequestration: 228.8 mg CO₂/L
- Alkalinity Generation: 6.00 meq/L
- Mineral Saturation: Calcite and Dolomite supersaturated
- Database: USGS Alaska Geochemical Database (AGDB4)
- Sample Universe: 23,032 rock samples from Alaska, USA
- Data Format: CSV files from AGDB4_text.zip
- Source URL: https://www.sciencebase.gov/catalog/item/6500b2bed34ed30c2057f99b
- Engine: PHREEQC v3.x with WATEQ4F thermodynamic database
- Python Integration: PhreeqPy v0.6.0
- Simulation Approach: Kinetic mineral dissolution with equilibrium precipitation
- Quality Control: Multi-database fallback with synthetic validation
- Python Libraries: pandas, matplotlib, numpy, phreeqpy
- Geochemical Modeling: PHREEQC integration
- Data Processing: Multi-dataset integration and preprocessing
- Visualization: Advanced matplotlib plotting with scientific formatting
- Python 3.7+
- PHREEQC software (optional, fallback included)
- Git
- Clone the repository
git clone https://github.com/yourusername/enhanced-rock-weathering.git cd enhanced-rock-weathering
-
Install dependencies pip install -r requirements.txt
-
Download USGS data
- Download AGDB4_text.zip from the USGS source
- Extract to
data/AGDB4_text/directory
- Run the analysis python ERW1.py
pandas>=1.3.0 matplotlib>=3.4.0 numpy>=1.21.0 phreeqpy>=0.6.0
The analysis generates a comprehensive 9-panel visualization including:
- pH Evolution - Acid neutralization capacity
- Major Cation Release - Ca²⁺ and Mg²⁺ mobilization
- Alkali Metal Release - Na⁺ and K⁺ for agricultural potential
- Silicon Mobilization - Silicate weathering indicators
- Carbon Sequestration - CO₂ capture potential
- Mineral Saturation - Precipitation potential assessment
- Cumulative Weathering - Total nutrient release
- Weathering Efficiency - Performance metrics
- Rock Composition - Major oxide distribution
- CO₂ sequestration through enhanced weathering
- Carbon capture quantification
- Climate impact assessment
- Nutrient release analysis (Ca, Mg, K)
- Soil pH buffering capacity
- Sustainable agriculture applications
- Acid mine drainage treatment
- pH buffering for contaminated sites
- Geochemical modeling validation
This project demonstrates:
- Advanced technical skills in geochemical modeling
- Real-world problem solving for climate change
- Professional data science workflows
- Scientific computing expertise
- Environmental applications of data science
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
- USGS for providing the Alaska Geochemical Database (AGDB4)
- PHREEQC development team for geochemical modeling software
- Scientific Python community for excellent libraries
Author: Manadip
Project: Enhanced Rock Weathering Analysis
Date: May 2025
*This project showcases advanced technical skills in geochemical modeling, data science, and environmental applications.