Published 12.12.25
From Manual LCAs to Cloud-Scale Measurement: Microsoft’s CHEM Methodology
The challenge: You can’t decarbonize what you can’t measure
For hyperscalers and data center operators, embodied carbon in ICT hardware represents a major share of Scope 3 emissions. In a recent whitepaper, Microsoft notes that reducing this impact requires reliable and granular measurement across a rapidly evolving hardware landscape and a deeply layered global supply chain.
While life cycle assessment (LCA) is a well established methodology for quantifying environmental impacts, Microsoft states that traditional approaches are difficult to apply consistently at cloud scale. Manual steps such as reconstructing complex BOMs and mapping materials to life cycle inventory datasets can take more than 100 hours per server, which makes it difficult to scale process-based LCA across thousands of hardware configurations without significant effort.
The shift: From manual modeling to scalable measurement
To overcome these limitations, Microsoft developed the Cloud Hardware Emissions Methodology, or CHEM. CHEM is an LCA based methodology designed to automate and scale embodied carbon measurement across Azure hardware, while preserving the level of detail needed to identify emissions hotspots and evaluate decarbonization interventions.
How CHEM is built
CHEM was developed using Azure data services alongside cloud based automated LCA software, including Makersite, which Microsoft uses to implement and scale process based LCA models across complex hardware configurations. This is combined with proxy mapping tooling and state of the art semiconductor life cycle inventory data from the imec Sustainable Semiconductor Technologies and Systems program.
Integrating product data
To reduce manual effort and improve consistency, CHEM integrates directly with Microsoft’s internal product data management systems and full material declarations. This allows complex BOMs hierarches to be transferred automatically into the LCA modeling environment, helping assessments stay aligned as hardware designs evolve.
Automating material to inventory mapping
CHEM automates the mapping of material compositions to representative life cycle inventory datasets from third party sources such as ecoinvent. By reducing manual modeling work, this approach allows practitioners to focus on data quality, supplier specific inputs, and interpretation rather than data entry.
Modeling semiconductors at higher resolution
Microsoft identifies semiconductor components as the primary drivers of embodied carbon in datacenter hardware. To improve accuracy, CHEM incorporates detailed manufacturing data from the imec Sustainable Semiconductor Technologies and Systems program.
Microsoft integrates this data into custom LCA models and uses its automated LCA software environment, including Makersite, to run and scale those models across large numbers of hardware configurations.
Why this matters
By applying CHEM across its cloud hardware fleet, Microsoft describes several practical outcomes:
- More robust Scope 3 reporting
Process based data replaces high level financial proxies, supporting disclosures that are more consistent, auditable, and repeatable at scale. - Clearer supply chain hotspot identification
Granular modeling makes it possible to trace embodied carbon impacts multiple tiers deep and evaluate where targeted interventions could have the greatest effect. - Carbon informed hardware design
CHEM data can be used by system architects to consider embodied carbon alongside power, performance, and cost during hardware design decisions. - More precise carbon roadmapping
Aggregated results across parts, assemblies, and configurations support carbon reduction roadmaps that reflect real manufacturing processes rather than estimates.
A signal for the industry
Microsoft presents CHEM as part of a broader shift toward more scalable, data driven approaches to understanding and reducing the embodied carbon impact of cloud hardware. Th company also highlights ongoing collaboration with industry groups such as the Open Compute Project and the Semiconductor Climate consortium to help improve consistency and standardization in LCA based carbon accounting.
Together, these efforts point toward a future where embodied carbon data is not just reported but operationalized. For organizations managing complex hardware fleets, the CHEM approach illustrates what is required to move from high level estimates towards measurement that can support real supply chain, design, and roadmapping decisions.
This blog is an interpretive summary of Microsoft’s whitepaper ‘How Microsoft is advancing embodied carbon measurement at scale for Azure hardware’, published in 2026.
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More InformationStill Have Questions? Let’s Dig Deeper
How does Microsoft measure embodied carbon for Azure hardware?
Microsoft measures embodied carbon for Azure hardware using the Cloud Hardware Emissions Methodology (CHEM), a process based life cycle assessment methodology. CHEM integrates internal product and supply chain data with environmental lifecycle inventory data to quantify emissions across the full hardware lifecycle.
What is the difference between spend-based and process-based LCA for data centers?
Spend-based methods estimate emissions using financial proxies, which can obscure the true drivers of embodied carbon. Process-based LCA, as used in CHEM, models emissions based on physical manufacturing processes and material flows, enabling more granular and actionable insights into where emissions originate.
How does Microsoft handle the complexity of semiconductor emissions?
Recognizing that semiconductors are a major contributor to embodied carbon, Microsoft incorporates detailed semiconductor life cycle inventory data into CHEM.This includes the use of advanced “virtual fab” models developed with data from the imec Sustainable Semiconductor Technologies and Systems program to represent specific manufacturing process steps rather than generic averages.
Can Life Cycle Assessment (LCA) be automated for hyperscale hardware?
Microsoft’s CHEM methodology demonstrates that significant parts of process-based LCA can be automated when product data systems are connected to cloud-based LCA modeling tools. This reduces the manual effort required to reconstruct BOMs and map materials to life cycle inventory datasets at hyperscale.
What role does Makersite play in the CHEM methodology
Microsoft uses Makersite as part of the CHEM implementation to support automated LCA modeling across complex hardware configurations. Makersite is used to map product structures and materials to environmental datasets, enabling scalable, process-based emission modeling.
