Carbon Footprint Modeling Tool: Advancing Sustainability through Data Transparency

The Carbon Footprint Modeling Tool is a comprehensive data model and viewer designed to facilitate the creation, sharing, and comparison of carbon footprint scenarios. This tool aims to improve data quality and transparency in environmental impact assessments, crucial for driving informed decisions in sustainability practices.

Objectives and Goals

The primary objectives of the Carbon Footprint Modeling Tool are to:

Develop a universal data scheme for modeling carbon emission scenarios, split by scopes, consumer components, and energy sources.
Create a modular structure for nested scenarios to capture complex emission patterns accurately.
Provide transparent support for reference sources, ensuring traceability and reliability of data.

Features and Functionality

Key features of the tool include:

Automated Unit Conversion: Ensures consistency and accuracy in emission calculations by standardizing units.
Emission Type Detection: Automatically identifies and categorizes different types of emissions.
Editable Input Fields: Allows users to test various settings and parameters, facilitating scenario customization.
Data Export and Sharing: Enables easy sharing and exporting of data in various formats, including JSON files and encoded URLs.
Deployment Options: Supports no-deployment using encoded URLs and serverless applications for flexible and scalable deployment.

Usage and Implementation

Users can interact with the tool to view, create, or extend carbon footprint scenarios. The tool supports both JSON file storage and URL embedding, making it versatile for different use cases. Scenarios can be modified directly in the user interface, and changes are reflected in real-time.

Comparison with Similar Projects

Unlike many other carbon footprint calculators, the Carbon Footprint Modeling Tool offers unique features such as automated unit conversion, modular scenario structures, and the ability to include various data sources for consumer components and energy sources. These functionalities enhance user engagement and ensure accurate data representation.

Future Development

Future plans include:

Expanding the model’s training corpus to include more diverse emission sources.
Exploring additional fine-tuning tasks to enhance the tool’s capabilities.
Integrating the tool into decision-support systems for investors and regulators.

Practical Applications

The tool is valuable for environmental scientists, policymakers, and organizations aiming to assess and reduce their carbon footprints. It provides a transparent and reliable means to model and understand complex emission scenarios.

Foundation in Research

The development of the Carbon Footprint Modeling Tool is based on extensive research, primarily detailed in two key papers:

“Transparent and Human-centered Carbon Footprinting” by Ruf, B., Mortas, F., & Detyniecki, M. (ACM CHI ’24) - Introduces a human-centered data viewer that complements the open and linked data model for carbon footprint scenarios, emphasizing the importance of transparency and user engagement.
“Assessing Carbon Footprint Estimations of ChatGPT” by d’Aramon, I., Ruf, B., & Detyniecki, M. (ICREC 2023) - Evaluates different methodologies for estimating the carbon footprint of ChatGPT, highlighting the disparities and potential improvements in carbon footprint modeling.

Sources and Facts

GitHub: Carbon Footprint Modeling Tool
Ruf, B., Mortas, F., & Detyniecki, M. (2024). Transparent and Human-centered Carbon Footprinting. ACM CHI ’24.
d’Aramon, I., Ruf, B., & Detyniecki, M. (2023). Assessing Carbon Footprint Estimations of ChatGPT. ICREC 2023.