Pollutant Degradation Kinetics Visualizer

A Streamlit-based application for analyzing and visualizing pollutant degradation kinetics data.

Features

• Simple and intuitive interface for data input
• Pseudo-first-order kinetic model fitting
• Real-time visualization of experimental data and fitted curves
• Basic error analysis (R² and RMSE)
• Support for catalyst loading and light intensity parameters

Installation

1. Clone the repository:

git clone https://github.com/yourusername/pollutant-degradation-visualizer.git
cd pollutant-degradation-visualizer

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

Usage

1. Start the Streamlit application:

streamlit run app.py

2. Open your web browser and navigate to the URL shown in the terminal (typically http://localhost:8501)

3. Enter your experimental parameters:

   • Initial concentration (C₀)
   • Time-concentration data pairs
   • Catalyst loading
   • Light intensity

4. View the results:

   • Fitted curve plot
   • Rate constant (k)
   • R² value
   • RMSE
   • Half-life

Development

The project is structured as follows:

pollutant-degradation-visualizer/
├── app.py                      # Main Streamlit application
├── requirements.txt            # Dependencies
├── README.md                   # Project documentation
├── src/                        # Source code
│   ├── models/                 # Kinetic models
│   │   └── first_order.py      # First-order model implementation
└── tests/                      # Unit tests
    └── test_models.py          # Tests for kinetic models

Testing

Run the test suite:

python -m pytest tests/

Deployed at: pdegrade.streamlit.app
GitHub repository: raymsm/pollutant-degradation-visualizer
For updates or collaboration, contact raymsm.

License

This project is licensed under the MIT License - see the LICENSE file for details.