Methodology & Research
GreenByte's CO₂ estimates are grounded in peer-reviewed research, international emission databases and established energy models. Here we explain exactly how we calculate, why we trust our numbers, and where they come from.
How the calculation works
Activity classification
The extension categorizes each network request by content type: video streaming, audio, images, documents, API calls, and general browsing. Each category has a distinct energy profile based on data center processing and network transfer requirements.
Data transfer measurement
We measure the volume of data transferred (bytes sent/received) per activity using the browser's Performance API and webRequest API. This provides the foundation for energy estimation: more data transferred = more energy consumed across the network.
Energy model application
Each byte is converted to energy (kWh) using a hybrid 3-layer model built on top of the 1-byte methodology. Unlike simple "1 byte = X CO₂" calculators, we apply category-aware coefficients (video, audio, browsing, AI) across three energy layers: data center processing, network transmission, and end-user device consumption. Coefficients are derived from Shift Project, IEA and peer-reviewed studies.
Country carbon intensity
The energy consumed (kWh) is multiplied by the carbon intensity factor of the user's country electricity grid (gCO₂/kWh). We use Ember's annual Global Electricity Review data, covering 200+ countries. A country with more renewables produces less CO₂ per kWh.
Real-time aggregation
Results are aggregated per session, day, week and month. The dashboard shows trends, comparisons and personalized reduction tips powered by AI analysis of your usage patterns.
Emission factors by activity
| Activity | Energy factor | Source |
|---|---|---|
| Video streaming (HD) | 0.077 kWh/GB | IEA, Carbon Trust |
| General browsing | 0.06 kWh/GB | Shift Project |
| Audio streaming | 0.04 kWh/GB | IEA |
| Video calls | 0.1 kWh/GB | Greenspector, Purdue University |
| AI queries (ChatGPT, etc.) | ~0.001–0.01 kWh/query* | IEA, Luccioni et al. (2023) |
| Cloud storage sync | 0.06 kWh/GB | Masanet et al. (2020) |
* Depends on model size, token count, provider infrastructure and inference length.
Core formula
Disclaimer — GreenByte provides scientifically informed estimates, not direct physical measurements. Actual emissions depend on hardware, network infrastructure, server utilization and electricity mix at the time of use.
Example calculation
Here's how GreenByte calculates emissions for 1 hour of YouTube (1080p) in Germany:
Country carbon intensity coefficients
Carbon intensity varies dramatically by country depending on the energy mix. GreenByte uses annually updated data from Ember's Global Electricity Review and the European Environment Agency (EEA). Here are several examples:
Research & data sources
Our methodology is built upon peer-reviewed research, institutional reports and open datasets from leading organizations:
Data Centres and Data Transmission Networks
International Energy Agency report on global energy consumption of data centres and networks. Provides baseline energy-per-byte coefficients used in our model.
Read articleLean ICT: Towards Digital Sobriety
The Shift Project's comprehensive analysis of ICT energy consumption. Source of the 1-byte model methodology and video streaming emission factors.
Read articleGlobal Electricity Review 2024
Annual dataset covering electricity generation, capacity and emissions for 200+ countries. Primary source for our country-level carbon intensity coefficients.
Read articleRecalibrating global data center energy-use estimates
Masanet et al. (2020) in Science. Recalibrated global data center energy models, showing efficiency gains. Used to refine our per-byte energy coefficients.
Read articlePower Hungry Processing: Watts Driving the Cost of AI Deployment?
Luccioni, Viguier & Ligozat (2023). Comprehensive energy measurements of AI model inference. Source of our per-query AI emission estimates.
Read articleCarbon impact of video streaming
Carbon Trust & DIMPACT study on the carbon footprint of streaming one hour of video. Cross-referenced with our video emission factors.
Read articleCO₂ emission intensity of electricity generation
European Environment Agency dataset on CO₂ intensity per kWh across EU member states. Supplementary source for European country coefficients.
Read articleThe overlooked environmental footprint of increasing Internet use
Obringer et al. (2021). Purdue University study quantifying the carbon, water and land footprints of internet activities including streaming, gaming and video calls.
Read articleGreen Software Foundation: SCI Standard
Industry consortium defining the Software Carbon Intensity (SCI) specification. Provides standardized methodology for measuring software carbon emissions across infrastructure.
Read articleKnown limitations
Like any estimation model, GreenByte has inherent limitations. We believe transparency about these makes the tool more trustworthy:
How we ensure accuracy
Our estimation model combines multiple scientific approaches to maximize precision within browser-level constraints:
Transparency is our principle
We openly share our methodology, data sources and limitations. As research evolves, so will our models. The desktop application is designed to improve estimated accuracy beyond 90% with system-level power telemetry, GPU sensors and per-process energy attribution.
greenbyte.ukr@gmail.com