General5 regions available
prune
Compare carbon footprint data for prune across multiple sourcing regions to identify lower-emissions alternatives.
Last updated 2026-02-09
Lowest footprint
2.698
kg CO2e / kg
Spain
Highest footprint
2.755
kg CO2e / kg
France
Emissions factors by sourcing region
Identify the lowest-carbon sourcing options for your Scope 3 Category 1 reporting.
| Region | kg CO2e | Unit | Cost | Year | Components | Details |
|---|---|---|---|---|---|---|
| Spain | 2.698 | kg CO2e / kg | AI cost calculator | 2024 | View details → | |
| Netherlands | 2.708 | kg CO2e / kg | AI cost calculator | 2024 | View details → | |
| United Kingdom | 2.713 | kg CO2e / kg | AI cost calculator | 2024 | View details → | |
| Denmark | 2.726 | kg CO2e / kg | AI cost calculator | 2024 | View details → | |
| France | 2.755 | kg CO2e / kg | AI cost calculator | 2024 | View details → |
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Frequently asked questions
- What is the emissions factor for prune?
- The emissions factor for prune ranges by sourcing region. Publicly visible values are 2.698 to 2.755 kg CO2e / kg, while some sources are locked in this public view.
- Which country has the lowest carbon footprint for prune?
- Based on available data, the lowest emissions option is 2.698 kg CO2e / kg in Spain.
- How do I reduce Scope 3 Category 1 emissions from prune?
- Switching to lower-emissions sourcing regions is one of the most effective ways to reduce Scope 3 Category 1 emissions from prune. Use the comparison table on this page to identify lower-carbon options.
- What lifecycle stages are included in the prune emissions factor?
- The emissions factor includes land use change (LUC), land management (LMGT), and energy inputs (ENI) where data is available, covering the full farm-gate carbon footprint.
- Can I use these prune emissions factors for supplier-level reporting?
- Yes. These emissions factors can serve as activity-based estimates for Scope 3 Category 1 (purchased goods and services) reporting under GHG Protocol. For higher accuracy, supplier-specific primary data is recommended.
