Description:

The Greenhouse Gas Emission Tracker is a web-based data science application designed to monitor, analyze, and predict greenhouse gas emissions across industries, cities, and regions.
It aggregates real-time industrial output, transportation activity, energy consumption, and agricultural production data to estimate CO₂, CH₄, and N₂O emissions.
This tool helps governments, environmental agencies, businesses, and researchers to track progress toward emission reduction targets and support climate change mitigation efforts.

Key Features:

1. Real-Time Emission Monitoring – Tracks CO₂, methane, and nitrous oxide levels from various sources.

2. Sector-Wise Breakdown – Categorizes emissions by industry, transportation, energy, agriculture, and waste management.

3. Geospatial Visualization – Displays emissions on interactive maps with regional hotspots.

4. Historical Trend Analysis – Shows past emission patterns and seasonal variations.

5. Predictive Analytics – Forecasts future emission levels based on economic growth and policy changes.

6. Carbon Footprint Calculator – Allows individuals and businesses to estimate their own emissions.

7. Compliance & Reporting – Generates reports aligned with international standards (e.g., UNFCCC, IPCC).

8. Reduction Target Tracking – Monitors progress toward sustainability and net-zero goals.

Technology Stack:

• Backend: Node.js / PHP / Java (handles data aggregation, API calls, and model execution)

• Frontend: HTML, CSS, Bootstrap, JavaScript (for dashboards and interactive maps)

• Database: MySQL / PostgreSQL / MongoDB (stores historical and real-time emission data)

• Data Science Layer: Python (Pandas, NumPy, Scikit-learn, ARIMA or Prophet for forecasting)

• APIs & Data Sources:

  • World Bank Climate Data

  • UNFCCC datasets

  • Copernicus Atmosphere Monitoring Service (CAMS) API

  • Industrial IoT sensors (optional)

• Visualization: Leaflet.js / Mapbox for mapping, Chart.js for sector-wise graphs

Example Use Case:

• A city government uses the tracker to monitor emissions from transport, industries, and electricity usage.

• The dashboard shows increased emissions from private vehicle usage during winter.

• Predictive analytics warn that without policy changes, CO₂ levels will exceed last year’s peak by 12%.

• The government uses this data to enforce low-emission zones and promote public transport.