Carbon Footprint: Data Analysis.

Your emissions information lives in different places (utility bills, supplier reports, travel expense sheets). Instead of manually building spreadsheets, use AI to read through these files, organize them, and show you which activities create the most emissions.

You have fragmented emissions data across your operations, supply chain, and products. AI can help you consolidate, clean, and analyze it to identify hotspots and track progress.

1. 1

   Identify where your emissions data lives

   • Write down the actual documents you have:
   • Monthly electricity and gas bills (from your utility company)
   • Water usage invoices
   • Fuel receipts or mileage logs for company vehicles
   • Flight bookings or travel expense reports
   • Supplier sustainability questionnaires or carbon reports
   • Production logs (if you manufacture)
   • Waste management invoices
   • For each, note: Do you have a file? Where is it stored?
2. 2

   Collect your files in one place

   • Gather the actual files (PDFs, spreadsheets, emails with data)
   • Don't worry about organizing them—just have them ready
   • If data is in an email, copy it into a simple text file or screenshot it
3. 3

   Ask AI to summarize your emissions

   • Open ChatGPT and upload your files (use the paperclip icon)
   • Ask AI to read through them and calculate total emissions
   • Ask what your biggest emission sources are
4. 4

   Identify patterns and anomalies

   • Ask AI: "Which months had the highest energy use? Is there a seasonal pattern?"
   • Ask: "Are any of our suppliers significantly higher-emitting than others?"
   • Ask: "What's changed compared to last year?"
5. 5

   Document your findings

   • Ask AI to create a simple 1-page summary of your emissions
   • Include: total emissions, top 3 sources, year-over-year trend
   • Save this summary for your records

Adapt to your actual files and context before using.

I'm uploading our 2024 monthly electricity and gas bills (Jan–Dec). These are PDFs from our utility company. Can you:
- Calculate our total energy-related emissions (assume 0.5 kg CO2 per kWh for electricity, 2.0 kg CO2 per therm for gas)
- Show which months used the most energy
- Tell me if our energy use is going up or down over the year

I'm uploading a spreadsheet with data from our 12 top suppliers. It shows: supplier name, annual spending with them, and their reported carbon emissions. Can you:
- Rank them by total emissions (highest to lowest)
- Calculate what percentage of our supply chain emissions come from the top 3 suppliers
- Identify any suppliers that seem like outliers (much higher emissions than expected)

I have three files: (1) our 2024 utility bills, (2) a spreadsheet of employee business flights from our expense system, and (3) our annual waste management report. Can you:
- Calculate total emissions from each source (energy, travel, waste)
- Show which one is the biggest contributor (as a percentage)
- Create a simple summary sentence for each category

- Task 1: List your data sources → Date completed: ___
- Task 2: Collect files → Date completed: ___
- Task 3: Run first analysis → Date completed: ___
- Task 4: Document findings → Date completed: ___
- Key finding: What's your #1 emission source? ___
- Next step: When will you update this analysis?