GHG Protocol · ESRS E1 · Technology

Scope 3 Emissions Estimator
for Technology

Estimate Scope 3 emissions for technology entities. Hardware procurement, data centre energy, cloud infrastructure, and the use-phase emissions of sold products drive the technology sector's Scope 3 profile.

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The GHG Protocol defines 15 Scope 3 categories. Select the categories relevant to your organisation. Excluded categories should be justified per GHG Protocol guidance.

0 of 15 categories selected — document exclusion rationale for completeness

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Scope 3 emissions estimation for Technology

Technology companies present a distinctive Scope 3 profile that varies sharply depending on whether the entity is a hardware manufacturer, a software provider, or a cloud services platform. For hardware manufacturers (servers, laptops, smartphones, networking equipment), Category 1 (purchased components and materials) and Category 11 (use of sold products) dominate. A laptop manufacturer's Category 11 emissions over the assumed three to five year product lifetime typically exceed the manufacturing emissions by a factor of two to four, depending on the grid carbon intensity in the markets where the product is used. For pure software and SaaS companies, Category 1 shifts toward purchased cloud computing services, and Category 8 (upstream leased assets, including co-located data centre space) becomes significant. ESRS E1-6 does not distinguish between technology sub-sectors, so every technology entity subject to CSRD must screen all 15 categories against its own value chain.

The technical complexity for technology companies lies in allocation. Cloud service providers sell compute capacity to thousands of customers, and each customer's Scope 3 Category 1 includes a share of the provider's data centre emissions. How that share is allocated (by revenue, by compute hours, by data storage volume) materially affects the result. The GHG Protocol does not prescribe a single allocation method, but it requires the chosen method to be documented and consistently applied. For SaaS companies that rely on hyperscale cloud providers (AWS, Azure, GCP), obtaining the upstream emission data requires using the provider's carbon reporting tools (AWS Customer Carbon Footprint Tool, Microsoft Emissions Impact Dashboard, Google Cloud Carbon Footprint). These tools report location-based and market-based emissions for the customer's cloud workload, but their methodologies differ, which creates comparability issues when an entity uses multiple providers. Category 6 (business travel) is material for technology companies with global sales and consulting teams. Category 7 (employee commuting) requires adjustment for remote and hybrid working patterns, which reduce commuting emissions but may increase Category 8 emissions if home offices are treated as upstream leased assets.

Assurance providers reviewing technology Scope 3 disclosures flag several recurring issues. First, SaaS companies that report zero or near-zero Scope 3 because they "don't manufacture anything" have typically failed to account for purchased cloud services (Category 1), purchased hardware for employees (Category 2), and the electricity consumed by end users running the software (Category 11). Second, hardware companies that estimate Category 11 using lab-tested energy consumption rather than real-world usage patterns tend to understate emissions by 20% to 40%. Third, technology companies with complex corporate structures involving subsidiaries, joint ventures, and equity investments often misclassify Category 15 (investments) emissions or exclude them without adequate screening documentation. Fourth, ISAE 3410 practitioners frequently find that the entity's reported Scope 3 boundary does not align with its financial consolidation boundary.

When applying this estimator for a technology entity, first classify your business model: are you primarily a hardware manufacturer, a software or SaaS provider, or a hybrid? For hardware, map your bill of materials and apply component-level emission factors from ecoinvent or manufacturer-provided product carbon footprints. For software and SaaS, obtain cloud provider emission reports for all major workloads, then add purchased IT hardware (employee devices, networking equipment) in Category 2. For Category 11, estimate the electricity consumption of your product in use. For software, this means the energy per user-hour on typical hardware. For hardware, use energy consumption ratings adjusted for real-world usage profiles published by the IEA or national energy agencies. Document every allocation decision, factor source, and boundary judgment.

Frequently asked questions: Technology

How should a SaaS company estimate Category 1 emissions from cloud computing?
Use the carbon reporting tools provided by your cloud infrastructure providers. AWS, Azure, and GCP all publish customer-specific emission data based on actual compute, storage, and networking usage. If you use multiple providers, document each provider's methodology and note any differences in allocation approach. Supplement with emission data for any on-premises infrastructure, co-located servers, and content delivery networks.
Are use-phase emissions (Category 11) material for software products?
Yes, for most software products. Every user running your software consumes electricity on their device. For a SaaS product with 100,000 active users each spending two hours per day, the aggregate electricity consumption is material. Estimate using average device power draw per hour (IEA data suggests 20 to 60 watts for laptops depending on workload) multiplied by user-hours, then apply grid emission factors for your user base geography.
How should technology companies handle remote workers in Category 7?
For employees who work from home, Category 7 (employee commuting) emissions drop, but you should consider whether home office energy use falls within your Scope 3 boundary. The GHG Protocol does not explicitly require reporting home office emissions, but some frameworks (including the UK's EcoAct homeworking emission factors) provide methods to estimate them. At minimum, adjust your commuting estimates for hybrid patterns rather than assuming five-day-per-week office attendance for all employees.
What about emissions from data stored on behalf of customers?
Data storage emissions sit in different categories depending on your role. If you are a cloud provider, the energy to run storage infrastructure is your Scope 1 and Scope 2. If you are a SaaS company storing customer data on a third-party cloud, it is your Category 1 (purchased services). The emission intensity of data storage varies enormously by storage type (SSD versus HDD), redundancy level, and data centre power usage effectiveness (PUE). Use provider-specific data rather than industry averages where possible.

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