Once a company has identified the activities to include in its GHG inventory, the next step is to collect the necessary data to calculate its scope 3 emissions.
Prioritizing data collection
Companies should prioritize data collection efforts on activities that;
- are expected to have the most significant emissions,
- offer the most significant GHG reduction opportunities,
- are most relevant to the company’s business goals
Collecting high quality data allows businesses to focus resources on the most significant GHG emissions in the value chain, more effectively set reduction targets, and track GHG reductions over time.
There are various methods for prioritizing scope 3 activities.
Based on the magnitude of GHG emissions
The main way to identify priority scope 3 activities is through a method called screening. The screening process typically involves estimating emissions from various value chain activities using industry averages, environmentally-extended input output (EEIO) models, proxy data and rough estimates. The scope 3 activities are then ranked from largest to smallest according to their estimated GHG emissions to determine which scope 3 activities have the most significant impact. Screening helps organizations identify hotspots, prioritize efforts, and focus on the most significant sources of indirect emissions for effective reduction strategies.
Based on the activity’s financial significance
Here, companies may choose to prioritize scope 3 emissions based on the financial significance of the scope 3 activity. They may use a financial analysis to rank upstream activities by their contribution to the company’s total expenditure. Similarly, they may rank downstream activities based on their contribution to the total revenue.
Caution should be taken while using the monetary impacts of scope 3 activities to determine the priority ones. This is because spend and revenue may not correlate well with emissions. For example, some activities may have high market value, but have low emissions. Conversely, some may have a low market value but have relatively high emissions. Companies should also prioritize activities that have a significant GHG impact, even if their contribution to financial spend or revenue is not that huge.
Based on other criteria
Companies should also prioritize data collection efforts for activities that ;
- the company has influence over
- contribute to the company’s risk exposure
- stakeholders deem critical
- have been identified as significant by sector-specific guidance
- meet any additional criteria developed by the company or industry sector
- appear in the value chain of purchased and sold products
GHG emissions data types
There are two types of GHG emissions data types:
Activity data: This is a quantitative measure of a level of activity that results in GHG emissions. Examples include liters of fuel consumed, kilowatt-hours of electricity consumed, kilograms of material consumed, hours of time operated, quantity of money used, etc.
Emissions factors: An emission factor converts activity data into GHG emissions. Examples include kg CO2 emitted per liter of fuel consumed, kg CO2 emitted per liter of fuel consumed, kg CO2 emitted per kWh of electricity consumed, t CO2 emitted per kilometer traveled, kg HFC emitted per kg of product sold, g CH4 emitted per kg of waste generated.
GHG emissions are quantified by multiplying activity data by an emission factor and the respective GWP value (in a case where the gas involved is not CO2).
\[GHG = Activity~Data ~ X ~ Emission~Factor ~ X ~ GWP\]
Material/product emission factors
There are two types of emission factors that can be used for calculating emissions associated with a material or product.
Life cycle emission factors, which include emissions that occur at every stage of a material/product’s life, from raw material acquisition or generation of natural resource to end of life.
Upstream emissions also known as cradle-to-gate emissions. They include all emissions that occur in the lifecycle of a material/product up to the point of sale by the producer.
Upstream emissions should be used to calculate emissions associated with goods or services e.g. category 1 (Purchased goods and services) and category 2 (Capital goods).
Energy emission factors
There are two types of emission factors that are used to convert energy activity data into emissions data.
Life cycle emission factors, which include the emissions that occur in the life cycle of the fuel i.e. extraction, processing, transportation, and combustion.
Combustion emission factors, which include only the emissions that occur from combusting the fuel.
Combustion factors are used to calculate scope 1 emissions (in the case of fuels) and scope 2 emissions (in the case of electricity). Life cycle emission factors are used to calculate emissions from fuels and electricity consumed in the reporting company’s value chain, except for category 3 (Fuel- and energy-related activities not included in scope 1 and scope 2).
Energy emission factors in scope 1 and scope 2 accounting
Scope 1 and scope 2 emissions are calculated using combustion emission factors. Scope 2 includes emissions from the generation of purchased electricity, steam, heating, and cooling that is consumed by the reporting company.
Non-generation activities related to electricity are accounted for in scope 3, category 3 (Fuel- and energy-related activities not included in scope 1 and scope 2).
Energy emission factors in scope 3 accounting
Life cycle emission factors represent all emissions in the upstream supply chain of fuels and energy. These emissions should be used to calculate scope 3 emissions related to fuel and energy consumed in the reporting company’s value chain, except for category 3.
Energy emission factors in scope 3, category 3
To calculate emissions from the first two activities within category 3, i.e.;
Upstream emissions of purchased fuels i.e., extraction, production, and transportation of fuels consumed by the reporting company,
Upstream emissions of purchased electricity i.e., extraction, production, and transportation of fuels consumed in the generation of electricity, steam, heating, and cooling consumed by the reporting company,
companies should use life cycle emission factors that exclude emissions from combustion, since these emissions are accounted for in scope 1 (in the case of fuels) and scope 2 ( in the case of electricity).
Primary and secondary data
Companies may use two types of data to calculate scope 3 emissions:
Primary data:
This is data from specific activities within a company’s value chain. It includes data provided by suppliers or other value chain partners related to specific activities in the company’s value chain. This data may take the form of primary activity data, or emissions data calculated by suppliers that are specific to suppliers’ activities. Examples include distance traled and mode of transpiort collected from employees, actual distance traveled, metric-tons of waste generated, site-specific energy use data collected by utility bills or meters, etc
Secondary data:
This is data that is not from specific activities within a company’s value chain. It includes industry-average data (e.g from published databases, government statistics, literature studies, and industry associations), financial data, proxy data, and other generic data. When specific data from one activity in the value chain is used to estimate emissions for another activity in the value chain, this data is proxy data hence considered secondary data, since it is not specific to the activity whose emissions are being calculated.
Companies should ensure that they collect high quality data to ensure that the inventory appropriately reflects the GHG emissions of the company, supports the company’s goals, and serves the decision-making needs of users, both internal and external to the company. Companies should collect secondary data for:
Activities not prioritized based on initial estimation methods or other criteria.
Activities for which primary data is not available e.g. where a value chain partner is unable to provide data.
Activities for which the quality of secondary data is higher than primary data (e.g. when a value chain partner is unable to provide data of sufficient quality).
Next: Engaging suppliers
