GHG Monitor - Greenhouse Gas Monitoring System

A comprehensive web application for monitoring, analyzing, and visualizing greenhouse gas emissions from agricultural systems using chamber-based measurement techniques.

🌱 Overview

GHG Monitor is a full-stack application designed for researchers and agricultural professionals to track CO₂, N₂O, and H₂O emissions from soil chambers. The system provides real-time data visualization, statistical analysis, and quality control assessment for greenhouse gas flux measurements.

✨ Features

📊 Dashboard

• Real-time Overview: Summary statistics with active chambers, total records, and site status
• Recent Data Preview: Latest 10 measurements with all sensor readings
• Most Recent File Info: Automatic detection of latest data files with metadata
• Smart Data Validation: Filters out invalid chamber IDs and malformed data

🔬 Analysis Tools

(a) Individual Cycle Data

• Whole Measurement Cycle: Complete time-series visualization for all chambers
• Per-Chamber Analysis: Multi-chamber comparison with color-coded traces
• Linear Regression: Backend-calculated slope, R², intercept, and flux rates
• Time Window Control: Adjustable analysis windows for precise calculations

(b) Flux Quality Check

• R² vs Time: Diurnal patterns of regression quality
• R² vs Flux Correlation: Quality-flux relationship analysis
• Custom Range Controls: User-defined flux ranges for focused analysis
• Quality Statistics: Automated pass/fail assessment based on configurable thresholds

(c) Subdaily Flux Dynamics

• Time-Series Analysis: Complete date-time range visualization
• Treatment Statistics: Mean ± standard error across replicates
• Quality Filtering: Real-time application of R² and flux thresholds
• Error Bar Visualization: Statistical uncertainty display

(d) Daily/Cumulative Flux

• Advanced Processing Pipeline: 4-step interpolation and aggregation
• Linear Interpolation: Per-chamber between measurement cycles
• Daily Aggregation: Treatment-level statistics with SE calculation
• Cumulative Analysis: Running totals with baseline correction
• Quality Inheritance: Automatic use of criteria from subdaily analysis

⚙️ Configuration Management

• Site Management: Multi-site support with individual configurations
• Chamber Specifications: Customizable dimensions and measurement frequency
• Quality Thresholds: Configurable R² minimums and flux criteria
• User Authentication: Secure access with JWT tokens

📈 Data Processing

• Automated Flux Calculations: CO₂ (kg C/ha/d) and N₂O (g N/ha/d)
• Temperature/Pressure Corrections: Molar volume adjustments
• Statistical Processing: Mean, standard error, and replicate counting
• Data Quality Assurance: Comprehensive validation and filtering

🏗️ Technology Stack

• Frontend: React 18, TypeScript, TailwindCSS, Recharts
• Backend: Node.js, Express, TypeScript
• State Management: Context API + React Query
• Charts: Recharts with custom error bars and statistical overlays
• Authentication: JWT tokens with secure session management

Project Structure

ghg-monitor/
├── frontend/          # React SPA application
├── backend/           # Node.js API server
├── data-processing/   # Python data processing scripts
├── data/             # Data storage directory
├── scripts/          # Original R analysis scripts
└── docs/             # Documentation

Getting Started

Prerequisites

• Node.js 18+
• Python 3.9+
• Git

Installation

1. Clone the repository:

git clone [repository-url]
cd ghg-monitor

2. Install frontend dependencies:

cd frontend
npm install

3. Install backend dependencies:

cd ../backend
npm install

4. Install Python dependencies:

cd ../data-processing
pip install -r requirements.txt

Running the Application

1. Start the backend server:

cd backend
npm run dev

2. Start the frontend development server:

cd frontend
npm run dev

3. Access the application at http://localhost:5173

Login Credentials

• Password: ghgmonitor

The application uses simple password authentication. Enter ghgmonitor when prompted to log in.

Data Structure

The application expects GHG flux data in CSV format with the following columns:

• site id, run id, chamber id, date, time
• CO2 (ppm), H2O (ppm), N2O (ppb)
• Status and pressure readings

Data files should be organized by site in the data/ directory.

Configuration

Site configurations are managed in data/site_registry.json. Each site can have:

• Unique identifier
• Location information
• Chamber configurations
• Processing parameters
• Access controls

Contributing

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

License

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