Interactive 3D Carbon Emissions Globe

An interactive 3D digital globe that displays carbon emissions for every country. Users can click on countries to view detailed emission data, including historical trends and annual values.

Features

• 3D Globe Visualization: Interactive 3D globe using Plotly's orthographic projection
• Color-Coded Countries: Countries are colored based on their CO₂ emission levels (green = low, red = high)
• Interactive Click Events: Click on any country to view detailed information
• Historical Data: View annual CO₂ emission values from 1750 to present
• Trend Analysis: See emission trends (increasing/decreasing) for each country
• Year Slider: Navigate through different years to see how emissions have changed over time
• Trend Charts: Visual charts showing emission trends for selected countries

Installation

1. Install the required dependencies:

pip install -r requirements.txt

Usage

1. Prepare data (first run only)

The app stores all emissions data locally under the data/ directory. Populate or refresh the dataset with:

python prepare_data.py

This step downloads the latest Our World in Data CO₂ dataset, converts it into the app's format, and saves both the raw and processed JSON files locally for offline use.

2. Start the application

Run the application:

python app.py

Data Sources

• Annual Historical Data: Our World in Data (OWID) - CO₂ emissions dataset
  • Stored locally in data/owid_co2_raw.json
  • Processed country-level metrics cached in data/emissions_processed.json

How It Works

1. Data Fetching: The data_fetcher.py module fetches CO₂ emissions data from Our World in Data
2. Data Processing & Persistence: Country data is processed, then saved to data/emissions_processed.json for reuse
3. Visualization: The globe_visualizer.py module creates the 3D globe using Plotly
4. Interactivity: Dash framework handles user interactions (clicks, slider changes)

Project Structure

carbon_globe/
├── app.py                 # Main Dash application
├── data_fetcher.py        # Data fetching and processing
├── globe_visualizer.py    # Globe visualization logic
├── prepare_data.py        # CLI to download & cache data locally
├── data/                  # Stored raw & processed emission datasets
├── Procfile               # Production start command (Render/Heroku)
├── render.yaml            # Render deployment blueprint
├── requirements.txt       # Python dependencies
└── README.md             # This file

Features in Detail

Globe Visualization

• Uses Plotly's choropleth map with orthographic projection for 3D globe effect
• Countries colored on a Red-Yellow-Green scale based on emission levels
• Interactive rotation and zoom capabilities

Country Information Panel

When you click a country, you'll see:

• Latest emission data (year and value)
• Trend indicator (increasing/decreasing)
• Historical range (min/max emissions)
• Data coverage information
• Interactive trend chart

Year Navigation

• Use the slider to navigate through different years
• Globe updates in real-time to show emissions for the selected year
• Historical data available from 1750 onwards

Future Enhancements

• Near-real-time estimates from Carbon Monitor API
• Daily emission estimates
• Comparison mode (compare multiple countries)
• Export functionality for data and charts
• Additional emission metrics (per capita, per GDP, etc.)

License

This project uses data from Our World in Data, which is available under the Creative Commons BY license.