The French regulatory GHG assessment methodology and guidelines is called "Bilan d'Émissions de Gaz à Effet de Serre (BEGES)". The current version is the fifth one (BEGES v5). It is the French equivalent of the GHG Protocol.
❗ Descriptions below correspond to BEGES v4 guidelines.
⬇️ For the up-to-date methodology:
Scope 3 emissions correspond to non-energy related indirect emissions that are induced by upstream and downstream operations and activities outside the organisational boundary of the legal entity.
Scope 3 is divided into 16 categories (categories 8 to 23)
8. Upstream energy emissions not included in categories 1 to 7
GHG emissions related to this category result from all upstream energy GHG emissions that haven't been accounted for in Scope 1 and 2. E.g. construction and maintenance of power plants; upstream emissions of purchased fuels and electricity (extraction, production, and transportation); transmission and distribution losses; etc.
GHG emissions are computed using emissions factors published by the International Energy Agency or the French Environment Agency (ADEME).
9. Purchases of goods and services
Purchases of goods
Emissions related to this category are caused by extraction, production and processing of products, consumables and raw materials that are purchased by the organisation.
Emissions related to the purchase of fixed assets are not included in this category, but in category 10 "Capital goods".
Purchases of products
Product-related emissions are estimated via a monetary approach, using the carbon intensity of the supplier or of the sector of activity, or by using product-specific monetary emission factors.
Accuracy can be improved by implementing an activity-based approach, using other metrics and flows (quantity, tons, litres, etc. of purchased products, raw materials used to manufacture the product, energy used in the industrial process, life cycle assessment, etc.).
Consumable purchases
Emissions related to consumable purchases are automatically computed via a monetary approach: monetary ratios of food purchases, paper, plastic, metals, etc. are included in Greenly's database.
Accuracy can be improved via an activity-based approach (by specifying the quantities consumed). An activity-based approach will be implemented in priority for the most important sources of GHG emissions.
Once the emissions have been computed via an activity-based approach, automation is ensured by estimating a consumable-specific monetary emissions factor.
Raw material purchases
Emissions related to the production of raw materials are computed using Life Cycle Assessments (LCAs). These emissions are then divided by the price of the raw material, a monetary emission factor is estimated and calculations can be automated.
However, for the purchase of raw material, it is preferable to use an activity-based approach and multiply physical quantities and flows (kg/lbs, liter/gallon, etc.) by activity EFs.
Greenly plans to connect to business management software products via APIs (e.g. SAP) to automatically collect the most up-to date activity-based data.
Purchases of services
Emissions related to this category are induced by the purchase of services (banking, advertising, consulting, technical studies, digital services, etc.).
Purchases of services
As activity-based data resulting from activities and operations of service companies are very diverse, monetary emission factors are used to estimate total emissions related to these activities. Emissions are computed by multiplying the amounts spent by a monetary emission factor (in kgCO2e/€).
These emission factors are computed using two methods:Carbon intensity of the service provider. When the service provider report and disclose their GHG emissions publicly or share data directly with Greenly (via Greenly Corporate Impact or Supplier Engagement), total emissions are divided by the company's turnover and a monetary ratio is computed.
Carbon intensity of a business sector. For companies that do not publish a GHG assessment, the carbon intensity of the business sector is used instead. This method is widely used for MSMEs, who do not often share information on their environmental impact. The data used comes from studies carried out by Greenly or from public databases. The accuracy can then be improved by engaging service providers in the process or by using other metrics (e.g. number of FTE).
Focus on digital services
Total GHG emissions induced by digital services are estimated via a monetary approach, using either the carbon intensity of the service provider or the one of the sector (data centre, IT licence, SaaS, video conferencing, web advertising, etc.).
Accuracy can be improved by carrying out an activity-based study. Greenly has become a true expert in this field and can compute the carbon impact of digital products, particularly the one of data centres, with great accuracy. Indeed, a specific study can be done using the type of storage, cloud computing and processing power, the amount of data transfers, etc. and the country where resources and data centres are located.
10. Capital goods
Emissions related to this category are caused by the manufacturing of the company's fixed assets: buildings and other infrastructures, vehicles, machinery, IT equipment, furniture, etc.
Unliked the GHG Protocol, these emissions are amortized over the life of the asset. For example: if, on average, the construction of a computer emits 300 kgCO2e and if one assumes a lifespan of 3 years, accounted emissions are of 100 kgCO2e per year for three years.
Building
Construction
Emissions related to the construction of a building are estimated by using an average kgCO2e per square meter (or square foot) ratio for each building type (office, housing, data centre, warehouse, etc.). These ratios are estimated via emission factors that are provided by public agencies and bodies. Total emissions are then amortized over 50 years.Renovation
Renovation-related emissions are amortized over 10 years, and are accounted for using a monetary approach. A more in-depth study can be carried out to gain in accuracy (e.g. component analysis).
IT equipment
IT-related emissions are computed via an activity-based approach using data provided by the organisation (IT equipment inventory). Average emission factors by type of equipment, the latest life cycle assessments published by manufacturers (Apple, Dell, Lenovo, Boavizta), etc. are included in Greenly's database. Therefore, a high level of accuracy can be obtained for IT equipment GHG emissions.Vehicle fleet
Emissions related to the manufacturing of vehicles are computed based on the number and type of vehicles used.
Accuracy can be improved when manufacturers publish life cycle assessments of their vehicles.Furniture
For most cases, furniture-related GHG emissions account for a very small part of the organisation's total emissions. Therefore, to estimate these emissions, a kgCO2e per employee ratio is used.
Accuracy can be improved by collecting and using additional data.
11. Waste generated in operations
Emissions related to this category are caused by the transport, treatment and disposal of waste (incineration, compost, landfill, recycling, etc.) generated by activities and operations within the organisational perimeter of the legal entity.
Waste-related emissions are accounted for in different ways. In most cases, these GHG emissions represent a very small part of the organisation's total emissions. Therefore, a kgCO2e per employee ratio is used. Accuracy can be improved by collecting further data: the weight and type of waste generated by the company.
Emissions related to the treatment and disposal of industrial and construction waste are systematically computed by collecting data on the type and weight of waste generated.
12. Upstream transport and distribution
Emissions related to this category are caused by the transport of goods by truck, train, boat, plane, moped, etc., the cost of which is borne by the Legal Entity.
To estimate the GHG emissions linked to this category, a monetary approach is implemented using specific monetary emission factors for each mean of transport.
Accuracy can be improved by implementing an activity-based approach: emissions are computed using the total distance travelled, the weight transported and the type of vehicle and fuel used. Monitoring these emissions can be automated by establishing specific monetary emission factors (computed by using the activity-based data provided by the organisation).
13. Business travel
Emissions related to this category are caused by employee travelling by plane, train, car, taxi, etc. or public transport for business purposes.
These emissions are computed using the expenses found in the general ledger of the organisation. An activity-based approach can also be implemented to gain in accuracy.
14. Upstream leased assets
These emissions are related to assets that are leased by third parties (who own them) to the organisation (vehicles, machinery, buildings, etc.).
The method used to compute these emissions is the same as for category 10. "Capital goods".
15. Investments
Emissions related to this category are induced by activities and projects financed by the legal entity.
These emissions are not directly accounted for on the SaaS.
However, when relevant, these emissions can be added to the SaaS. Financed-emissions are allocated using the share invested in the company or project.
16. Visitor and client transport
Emissions related to this category are caused by means of transports used by visitors and clients to travel to one of the organisation's sites (plane, train, rented car, taxi, e-bike, etc. or public transport).
These emissions are computed using an activity-based approach when relevant (the company provides data on the distance, mean of transport and number of visitors).
17. Downstream transport and distribution
Emissions related to this category are caused by the transport of goods by truck, train, boat, plane, moped, etc., the cost of which is not borne by the Legal Entity.
The organisation does not directly pay for the transport, hence only an activity-based approach is used to compute these GHG emissions.
Automation is ensured by applying a monthly average and by regularly updating the data used. Greenly plans to connect to business management software products via APIs (e.g. SAP) to automatically collect the most up-to date activity-based data.
18. Use of sold goods
Emissions related to this category are caused by the production of energy and raw materials that are consumed throughout the life of the sold products.
Depending on the sold product, different methods exist.
Digital products and websites
Emissions are induced by the power consumption of terminals and networks (cloud computing, data transfers, data centres, storage etc.) used by end-users. These emissions are computed using the total time spent (in hours), the country where the terminals and networks are located (the carbon intensity of electricity varies depending on the country) and the estimated average energy consumption per hour. Network traffic emissions are estimated using the total amount of transferred data. Automation is ensured via a monthly average that is regularly updated.
Energy consuming products
Emissions are induced by the energy consumption of sold products. These emissions are computed using the average energy consumption per product and the country where the energy is produced and consumed (the carbon intensity of electricity varies depending on the country). Automation is ensured via a monthly average that is regularly updated.
Semifinished goods
Semifinished goods still need to be processed or assembled. As for energy consuming products, emissions are computed using the average energy consumption needed in the process and the country where the energy is produced and consumed (the carbon intensity of electricity varies depending on the country).To include these emissions in the SaaS, a more in-depth study needs to be carried out.
19. End-of-life treatment of sold products
Emissions related to this category are caused by the transport, treatment and disposal of sold products (incineration, compost, landfill, recycling, etc.).
Emissions related to the treatment and disposal of the sold products are computed by collecting data on the type and weight of waste generated.
20. Downstream franchises
GHG emissions related to this category result from the activities and operations of franchises.
21. Downstream leased assets
These emissions are related to assets that are owned by the organisation and leased to third parties (vehicles, machinery, buildings, etc.).
The method used to compute these emissions is the same as for category 10. "Capital goods".
22. Commuting
Emissions related to this category are caused by commuting (car, public transport, motorcycle, moped, electric bicycle, etc.)
These emissions are estimated using an employee questionnaire sent to all employees of the organisation.
23. Other indirect emissions
Emissions related to this category are indirect emissions resulting from activities and operations outside the organisational boundary of the legal entity and which cannot be accounted for in one of the other categories.