Inspiration

When shopping online, the environmental impact of what we buy is almost completely hidden.
Every product we click "Add to Cart" on, from T-shirts to milk to furniture carries, a carbon footprint made up of materials, manufacturing, shipping, and packaging.

We were inspired by the United Nations Sustainable Development Goals, particularly:

  • Goal 12: Responsible Consumption and Production
  • Goal 13: Climate Action

These goals emphasize the urgent need to make consumption patterns more sustainable and to reduce our carbon emissions. However, achieving these goals isn't just about systemic change; it’s about empowering individuals to make more informed, conscious decisions every day.

We built Carbon Count to bridge that gap:
Helping everyday shoppers see the hidden environmental costs of their purchases and nudge behavior toward a more sustainable future. Because real climate action starts with awareness and awareness starts with information.

Category

Sustainability & Climate Tech – AI solutions for green conservation and smart resource management

What it does

Carbon Count is a Chrome extension that automatically analyzes the carbon footprint of products while you shop online on Amazon, Walmart, and Target.

As soon as you open a product page, Carbon Count:

  • Detects the type of product you're viewing.
  • Sends the product information to OpenAI to estimate the carbon footprint.
  • Shows the likely manufacturing location of the product.
  • Instantly displays carbon count including a breakdown of emissions, from materials and manufacturing to packaging and transportation.
  • Shows how many mature trees would be needed to offset that product's carbon impact.
  • Suggests greener alternatives when available, helping you make better choices without any extra effort.

How we built it

  • Chrome Extension: Built using HTML, CSS, and JavaScript.
  • Content Scripts: Detect when a supported product page is loaded and inject a sidebar UI.
  • OpenAI API: Used to dynamically generate carbon footprint estimates based on product descriptions and categories.
  • Developer Tools: Heavy reliance on Chrome DevTools for debugging and refining content injection without breaking native page design.

Challenges we ran into

  • Finding a reliable carbon estimation model was tough, so we used OpenAI to generate estimates.
  • Web search has recently been added to the OpenAI 4.1 models. The documentation of this functionality was sparse and we had to go through lot of trial and error to get it right.
  • Debugging Chrome extensions across dynamic sites like Amazon and Walmart required use of console logging and careful scripting. We relied on developer tools that come built into the Chrome browser.

Accomplishments that we're proud of

  • Built a fully functional, responsive Chrome extension that works across Amazon, Walmart, and Target.
  • Created a clean user experience that integrates seamlessly into the browsing flow without disrupting shopping behavior.
  • Enabled real-time carbon footprint visibility for some of the most visited e-commerce sites in the world.

What we learned

  • How to navigate Chrome extension security models, content scripts, and permission challenges.
  • How to design AI-driven products that stay lightweight and user-friendly without sacrificing performance.
  • We learned how powerful it is to translate abstract environmental data into relatable visuals, like the number of trees needed to offset a product’s carbon impact, making sustainability more tangible and actionable for everyday users.

What's next for Carbon Count

  • Expanding Carbon Count support to more online fast fashion retailers like H&M, ZARA, and sites like Best Buy and Home Depot.
  • Building a personalized dashboard for users to track their cumulative carbon savings over time.
  • Adding badge certifications for verified sustainable products.
  • Moving the OPENAI_API_KEY from the plugin to a server so everyone can use the product for free.

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