Carbon Catalyst ⚡

Inspiration 💭

This project is born out of a deep love for our planet and the undeniable truth that every action we take ripples across the world we share. Imagine the forests breathing cleaner air, the oceans thriving with life, and a future where generations after us inherit a world filled with hope and abundance—not ruin.

But change begins with awareness. Too often, we go through life unaware of the quiet harm we cause—the energy we waste, the pollution we emit, the resources we consume. Yet, with knowledge comes power—the power to make deliberate, compassionate choices that heal rather than harm.

This project is not just about numbers or calculations; it’s about connection. It’s about seeing the impact of our lives on the fragile ecosystems that sustain us, and realizing that we hold the power to write a new story—one of restoration, resilience, and renewal. When you calculate your carbon footprint, you're not just identifying the problem; you're igniting the spark of a solution. You're taking a step toward aligning your actions with the love and care the Earth so desperately needs. This isn’t just about saving the planet; it’s about saving ourselves, our communities, and everything we hold dear. Together, through awareness and action, we can ensure that the beauty of this world will never fade.

What it does ❓

This app helps you calculate your personal carbon footprint by analyzing your daily activities, such as energy use, travel, and consumption habits. It provides actionable insights on how to reduce your impact, adopt eco-friendly practices, and contribute to a healthier planet. With easy-to-follow recommendations, it empowers you to make a real difference in fighting climate change.

How it works ⚙️

The application uses data-driven algorithms and user-friendly interactions to calculate and analyze your carbon footprint. Here's a detailed breakdown:

Data Collection
- Users provide inputs in five main categories:
  - Personal Details: Includes information such as age, household size, and general lifestyle habits.
  - Travel: Accounts for daily transportation (e.g., car, bike, public transport), annual flights, and distances traveled.
  - Waste: Evaluates waste generation and recycling practices.
  - Energy Usage: Measures energy consumption in the form of electricity, gas, and renewable sources.
  - Consumption Habits: Considers purchasing patterns of food, clothing, and electronics.
Emission Factors
- The backend uses scientifically validated coefficients to calculate carbon emissions based on user input. For example:
  - Travel: Calculates emissions using vehicle-specific data, such as 0.24 kg CO₂ per mile for an average gasoline car.
  - Energy: Differentiates between clean energy sources and fossil fuels.
  - Consumption: Accounts for embodied emissions in products (e.g., 14.5 kg CO₂ for 1 kg of beef).
Dynamic Calculations
- Using tools like NumPy and Pandas, the app processes user input dynamically to generate real-time outputs.
Visualization
- Matplotlib creates interactive and easy-to-understand visualizations, such as pie charts that break down the carbon footprint into categories.
Offset Calculations
- The app calculates the number of trees needed to offset emissions, based on an average tree absorbing 22 kg of CO₂ annually.
Recommendations
- Provides actionable insights for users to reduce their carbon footprint, such as:
  - Opting for public transportation.
  - Switching to renewable energy sources.
  - Reducing meat consumption.
Donation Integration
- Users are directed to reputable organizations like Plant with Purpose and The Nature Conservancy to offset their emissions through donations.
Interactive Learning
- Includes a "Did You Know?" section with engaging facts about carbon emissions and sustainable living.

Usage Instructions 🌳

Access the Calculator
- Visit the calculator through this link: Save The Tree.
Explore the Main Page
- The main page introduces our initiative, explains why reducing carbon footprints matters, and outlines the benefits of taking action.
Proceed to the Calculator
- Scroll to the bottom of the page and click "Proceed to enter data" to access the calculator.
Provide Information
- The calculator is divided into five tabs:
  - Personal, Travel, Waste, Energy, and Consumption.
  - Use sliders, text boxes, and drop-down menus to input your data.
Navigate Between Tabs
- Use the tab navigation at the top to complete each section.
Calculate Your Carbon Footprint
- Click the green footprint button on the final tab (Consumption) to generate results.
View Results
- The final page displays:
  - A pie chart showing contributions from different categories.
  - A tree-planting calculation to offset emissions.
  - A donation button to contribute to tree-planting efforts.
Experiment with Variables
- Adjust the calculator's inputs to explore how lifestyle changes can reduce emissions.
Learn Fun Facts
- Click the "Did you know?" button to discover interesting insights about emissions.
Alternate Donation Links
- Use the "Save a Tree" button at the bottom to contribute to The Nature Conservancy, combating climate change and promoting sustainability.

Backend 🗝️

Data Handling with Pandas:
- Utilizes Pandas for efficient data analysis and organization.
NumPy for Numeric Operations:
- Handles advanced computations for emission calculations.
Machine Learning with scikit-learn:
- Provides tailored recommendations based on user inputs.
IO Operations:
- Manages smooth communication between app components.
Data Visualization:
- Employs Matplotlib for impactful visual representations.
Image Processing with Pillow:
- Enhances interface visuals for better user engagement.
Base64 Encoding/Decoding:
- Ensures seamless storage and display of images.

Frontend 💻

Streamlit Setup:
- Developed with Streamlit for an interactive experience.
User Interface Design:
- Combines CSS and JavaScript for a polished look and feel.
Testing:
- Ensures smooth navigation and accurate functionality.

Backend Challenges 🧩

Data Integration:
- Balancing data accuracy while handling inconsistencies.
Complex Calculations:
- Debugging advanced numerical processes.
Machine Learning Models:
- Ensuring lightweight, efficient implementations.
Image Processing:
- Avoiding bottlenecks during visual asset rendering.

Frontend Challenges ❌

Streamlit Customization:
- Enhancing Streamlit's limited flexibility with custom design.
User Experience:
- Iterating layouts to balance aesthetics and usability.
Dynamic Visualizations:
- Creating responsive charts updated in real-time.

General Challenges 🤔

Testing and Debugging:
- Integrating backend and frontend components seamlessly.
Performance Optimization:
- Reducing latency during complex operations.
Collaboration:
- Managing code changes across the team via GitHub.

Accomplishments that we're proud of ☺️

Accurate Calculations:
- Leveraged Pandas and NumPy for reliable data analysis.
Personalized Insights:
- Introduced tailored recommendations with scikit-learn.
Intuitive Design:
- Delivered a smooth interface with custom enhancements.
Dynamic Visualizations:
- Provided clear, engaging data representations.
Performance Efficiency:
- Maintained a responsive user experience.

What's next for Carbon Catalyst ⚡

Localized Recommendations:
- Provide real-time region-specific suggestions.
Gamification:
- Introduce challenges and rewards to encourage sustainable habits.
Community Features:
- Build a platform for users to share progress and inspire action.