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Why We Improved Our Energy and Material Database with Consumption Mix Data

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Electricity is one of the most influential factors in sustainability calculations. Whether in Product Carbon Footprints (PCFs), Life Cycle Assessments (LCAs), or broader carbon accounting, electricity-related emissions often have a significant impact on final results. At the same time, the electricity consumed within a country can differ substantially from the electricity produced there due to imports, exports, and renewable energy certificate systems such as Guarantees of Origin (GOOs).

Despite this complexity, electricity data is still often modeled using simplified national averages that do not fully reflect actual consumption conditions within a country or region. This creates a problem: electricity grids are far more dynamic and interconnected than they appear at first glance.

To improve the quality and realism of sustainability calculations, sustamize expanded and enhanced its energy and material database with improved consumption mix methodology and datasets. The objective was not only to refine electricity emission factors themselves, but also to strengthen the representativeness of carbon emissions data across both energy and material-related calculations.

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Production Mix and Consumption Mix Are Not the Same

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When discussing national electricity data, many people instinctively think about the energy sources a country produces domestically. This is commonly referred to as the production mix. But from a sustainability perspective, this does not always represent the electricity that is ultimately consumed.

Electricity markets across Europe and globally are heavily interconnected. Countries continuously importand export electricity depending on demand, pricing, grid stability, and energy availability. In addition, renewable electricity certificates and Guarantees of Origin (GOOs) further influence how electricity is accounted for on paper.

As a result, the electricity consumed within a country can differ substantially from the electricity produced there. A country with a large share of hydropower or renewable generation may still consume electricity associated with a more carbon-intensive grid mix due to imports or certificate trading mechanisms. Conversely, countries with more fossil-heavy production can appear differently depending on how electricity attribution is handled.

This is where consumption mix data becomes important. Consumption mix datasets aim to represent the actual electricity mix consumed within a region by considering factors such as imports, exports, market structures, and energy attribution mechanisms.

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Why This Matters for Sustainability Calculations

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The difference between production-based and consumption-based electricity data can significantly influence footprint results.

For manufacturers and sustainability teams, this affects much more than a single number in a report. Electricity datasets directly influence how products, suppliers, and production locations are evaluated.

In practice, inaccurate or oversimplified electricity data can lead to:

• distorted Product Carbon Footprints (PCFs)
• inconsistent supplier comparisons
• unrealistic manufacturing impact assessments
• weaker decision-making in product development and sourcing

Especially in energy-intensive industries, even moderate changes in electricity emission factors can noticeably change overall product footprints.

This becomes increasingly relevant as sustainability data moves from high-level reporting toward operational decision-making. Companies are no longer only reporting emissions; they are using carbon data to evaluate suppliers, compare materials, optimize production processes, and prepare for regulatory requirements such as CBAM. In this context, the quality of underlying electricity data becomes critical.

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What We Improved in the sustamize Database

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By integrating improved consumption mix datasets into our database infrastructure, we further enhance the quality and representativeness of carbon emissions data across both energy and material databases. This helps create more consistent and realistic results across products, suppliers, and manufacturing locations. The update includes:

• enhanced methodology for country-specific electricity datasets, now considering net imports, import mixes as well as     transmission and distribution (T&D) losses
• better alignment with consumption-based emissions accounting
• expanded database coverage for 11 additional countries

The improvements also strengthen alignment with consumption-based emissions accounting methodologies as well as important industry standards such as ISO 14067 and the Catena-X PCF Rulebook.

By integrating these methodological improvements more deeply into the overall database structure, sustainability calculations become more representative across products, suppliers, manufacturing locations, and material datasets.

Better Sustainability Data Leads to Better Decisions

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One of the biggest challenges in sustainability is not only collecting data but ensuring that the data is meaningful enough to support decisions. Many sustainability calculations appear highly precise on the surface, while the underlying datasets remain heavily generalized. Electricity data is one of the clearest examples of this issue because electricity impacts influence not only direct energy calculations, but also broader material and supply chain assessments.

Improving the quality of energy and material datasets helps reduce the gap between theoretical reporting and practical decision-making. More representative sustainability data supports companies in:

• understanding the real impact drivers within supply chains
• identifying meaningful decarbonization opportunities
• comparing suppliers more fairly
• improving footprint transparency
• building more reliable sustainability strategies

As sustainability requirements continue to increase, expectations around data quality will continue to rise as well. Accurate calculations increasingly depend on the quality, transparency, and methodological consistency of underlying datasets.

At sustamize, we continuously work on improving the depth, transparency, and usability of sustainability data.

Enhancing our energy and material database with improved consumption mix data is part of that broad ereffort. It reflects our focus on making sustainability calculations not only scalable, but also more representative of real-world conditions.

Because ultimately, better sustainability decisions start with better underlying data.

If you want to learn more about our approach to energy data, PCFs, and scalable sustainability intelligence, get in touch with the sustamize team or book a demo to explore the sustamizer.

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