The data confidence score is determined by the granularity of the activity data and its geographic location. Here’s how it works:
Terrascope assigns a score to each activity based on the type of data provided.
Scores are weighted by emission volume to highlight the importance of focusing on major emission sources. For instance, low-scoring activities with higher emission volumes have a greater impact on the overall score.
Scoring framework
Activity data is categorised and ranked as Low, Medium, or High based on two factors: activity granularity and geographic granularity.
Data confidence metric | High (1) | Medium (3) | Low (5) |
Activity granularity | Site-based data
(Activity is tied to a specific site) | Activity-based data
(Activity is not tied to a specific site) | Spend-based data
(Activity with currency as the unit) |
Geographic granularity | Country/site-specific data | Regional data | Global data |
Key
High (1): Highest confidence level with the most precise and accurate data.
Medium (3): Moderate confidence level with fairly accurate data.
Low (5): Lowest confidence level with the least precise data.
Example 1 (Spend-based, Country/site-specific)
Activity description: Almonds
Quantity: 11,694.81
Unit: USD
Location: US
Activity confidence score is 5 (low) since this is spend-based data, while geo location confidence score is 1 (high) as the location is categorised as Country/Site-specific.
Example 2 (Non spend-based, Global)
Activity description: Rice
Quantity: 1,500
Unit: j (energy)
Location: null (global)
Activity confidence score is 3 (medium) since the unit is not a currency, therefore it is non spend-based data. For non spend-based data, the confidence score depends on the geo location of the activity.
Therefore, the geo location confidence score is 5 (low) as the location is categorised as Global.
By combining these factors, the data confidence score gives you a clear picture of how reliable and precise the collected data is. This helps you focus on the most significant emission activities.