Introduction
The Greenhouse Gas (GHG) Protocol is a widely recognized framework for measuring and managing greenhouse gas emissions - over 90% of Fortune 500 companies use this methodology to calculate their scope 1, 2 and 3 emissions. It provides comprehensive guidelines for organizations to quantify and report their emissions, helping them to track progress and identify areas for improvement.
At Coolset, we use the GHG Protocol as the methodological basis for calculating scope 1, 2 and 3 emissions. Two key methods for estimating GHG emissions are the spend-based method and the activity-based method. This article provides an overview of these methods, highlighting their processes, advantages, and examples.
Spend-based method
Overview
The spend-based method estimates GHG emissions based on the financial expenditures of an organization. It uses economic data and emission factors to approximate the emissions associated with purchased goods and services. This method is particularly useful when detailed activity data is not available.
Process
Identify spending categories: Determine the different categories of expenditures (e.g., office supplies, travel, energy).
Collect financial data: Gather financial data for each category.
Apply emission factors: Use published emission factors that correlate financial spend to emissions (e.g., kg CO2e per dollar spent). Coolset has over 9.000 spend-based emission factors.
Calculate emissions: Multiply the financial spend by the corresponding emission factor for each category to estimate the emissions.
Advantages
Simplicity: Easier to implement with basic financial data.
Broad scope: Covers all types of purchased goods and services.
Time-efficient: Faster estimation compared to detailed data collection.
Example
An office spends €10,000 on office supplies annually. If the emission factor for office supplies is 0.1 kg CO2e per euro, the emissions would be:
€10,000×0.1 kg CO2e/euro = 1,000 kg CO2e
Activity-based method
Overview
The activity-based method estimates GHG emissions based on specific activity data, such as fuel consumption, electricity usage, or distance traveled. It uses precise data and corresponding emission factors to calculate emissions, offering higher accuracy.
Process
Identify activities: Determine the activities that generate emissions (e.g., fuel consumption, electricity usage).
Collect activity data: Gather detailed data on these activities (e.g., liters of fuel used, kWh of electricity consumed).
Apply emission factors: Use specific emission factors for each activity (e.g., kg CO2e per liter of fuel).
Calculate emissions: Multiply the activity data by the corresponding emission factor for each activity to estimate the emissions.
Advantages
Accuracy: Provides more precise estimates due to detailed data.
Specific insights: Identifies emissions from specific activities, facilitating targeted reduction strategies.
Enhanced tracking: Enables more accurate monitoring of changes over time.
Example
A company consumes 5,000 liters of diesel annually. If the emission factor for diesel is 2.68 kg CO2e per liter, the emissions would be: 5,000 liters×2.68 kg CO2e/liter=13,400 kg CO2e
Comparison and use cases
When to use spend-based method
Lack of detailed data: Ideal when specific activity data is unavailable or incomplete.
Preliminary estimates: Useful for initial assessments and broad overviews.
Resource constraints: Suitable for organizations with limited resources for data collection.
When to use activity-based method
High data availability: Best when detailed and accurate activity data is accessible.
Precision required: Essential for organizations aiming for precise emissions tracking and reduction.
Regulatory compliance: Often needed for compliance with specific reporting standards requiring detailed data.
Conclusion
Both the spend-based and activity-based methods provide valuable approaches for estimating GHG emissions under the Greenhouse Gas Protocol. The choice between these methods depends on data availability, desired accuracy, and resource constraints. At Coolset, we advise companies to use a mix between spend and activity-based data, based on the available data.