Overview of VCI Guidances

VCI Guidance v1.1 – What is the guidance for?​

• ​Written through the lens of companies with Scope 3 GHG targets.​
• ​Aim: Accounting for reductions/removals through interventions.​
• ​Primarily focus on Interventions that affect purchased goods and services (Scope 3, Category 1). 

Life-cycle approach

They agreed that a life-cycle approach should be used when it came to calculating emissions, in that all direct and relevant upstream emissions associated with producing a purchased good or service should be accounted for.​

Example. Understanding Upstream Emissions in Value Chain Interventions

A supply chain process for ready-to-drink (RTD) milk-based coffee and how upstream emissions are generated at different stages of production, from raw materials to final product delivery.

1.Raw Materials (Inputs)

• Coffee (x), Milk (y), and Sugar cane (z) are the primary raw materials involved in producing the milk-based coffee. Each of these materials undergoes a specific process that contributes to the carbon footprint.

2. Processing Stages

• Milling: Coffee goes through a milling process, generating CO₂ emissions (labeled as “a”).
• Homogenization: Milk is processed through homogenization, emitting CO₂ emissions (labeled as “b”).
• Refining: Sugar cane is refined, emitting CO₂ emissions (labeled as “c”).

3. Transportation

• After processing, the raw materials (coffee, milk, and sugar cane) are transported, with additional CO₂ emissions generated during shipping. The equation provided, T + (x + a) + (y + b) + (z + c), reflects the combined emissions from each stage of production, including transportation.

4. Upstream Emissions

• Upstream emissions, refer to the emissions that occur before the product reaches its final stage. This includes emissions from raw material production, processing, and transportation.

5. Final Product: RTD Milk-Based Coffee

• After processing and transportation, the final product is the ready-to-drink milk-based coffee. The emissions related to this entire process are categorized as Scope 3 emissions, which are typically reported as part of the company’s value chain emissions.

Understanding the different stages in a product’s life cycle contributes to its overall carbon footprint, particularly focusing on upstream emissions. This knowledge is critical for reporting and managing Scope 3 emissions in a value chain, as well as for implementing interventions to reduce emissions at various stages.

Understanding Data Calculation Methods for Scope 3 Emissions Reporting

Figure 3 (from GHG Protocol, Scope 3 Standard) outlines different calculation methods used for measuring and reporting Scope 3 emissions in the product life cycle. Specifically, it focuses on how various data types (supplier-specific, hybrid, average-data, or spend-based) are used to estimate upstream emissions, which are essential for calculating a company’s total carbon footprint. Let’s break down each method and its application:

1. Supplier-Specific Method

• Data Used: Supplier-specific data is collected for both the product’s upstream emissions and the supplier’s Scope 1 and 2 emissions.
• Application: This method is the most accurate as it uses data directly from the supplier’s operations and emissions, specific to their product. All data is tailored to the supplier’s product, ensuring high precision.

2. Hybrid Method

• Data Used: A mix of supplier-specific data and average data is used. For upstream emissions, either specific or average data can be applied.
• Application: This method is flexible, allowing for a combination of data sources when supplier-specific data is partially available. It still ensures a high level of accuracy for the supplier’s Scope 1 and 2 emissions while using more generalized data for other upstream processes. Scope 1 and 2 emissions are supplier-specific, while all other upstream emissions can be either supplier-specific or based on average data.

3. Average-Data Method

• Data Used: This method relies solely on average data for both the product’s upstream emissions and the supplier’s Scope 1 and 2 emissions.
• Application: It’s useful when supplier-specific data is unavailable, but it sacrifices precision by using secondary process data. The entire data set is based on general industry averages, making it less precise but easier to gather.

4. Spend-Based Method

• Data Used: All data is derived from financial expenditures (spend) rather than physical activity data, using Economic Input-Output (EEIO) models.
• Application: This method is typically used when detailed process or supplier-specific data is not accessible. It’s less precise but provides a simplified, cost-based estimate of emissions. The data is based on industry-level estimates from economic activity, so it is less detailed than the other methods.

By understanding the differences between these calculation methods, you will be able to identify which method to apply based on data availability and project requirements. The goal is to ensure accurate and transparent reporting of Scope 3 emissions while balancing practicality and data accessibility.

Intervention & Intervention Activity, Supply Shed and Integrate ‘project accounting’ into ‘inventory’

Various concepts were agreed upon, which are in-depth and could each have a lesson of their own, but we will provide an overview of three of these concepts below.

Emission factors can be defined at different scales 

Concept 1 – Intervention & Intervention Activity

Intervention: Any action that introduces a change to a Scope 3 activity or activities. An Intervention may include changes to several activities that reduce or remove emissions in different ways and that may or may not be included within the Scope 3 Inventory.​

​Intervention Activity: Technology or practice that reduces or removes GHG emissions in the intervention

• Interventions are limited to one geography​
• Different activities may have different quantification approaches, different baselines, and different process data

Concept 2 – Supply Shed

What is a Supply Shed? 

• A supply shed is a group of suppliers providing functionally equivalent goods or services, located within a fixed and spatially defined area that is demonstrably part of the company’s supply chain. 

Why is the Supply Shed concept useful? 

In many cases, it may not be feasible to trace materials directly to a specific supplier upstream. The supply shed concept helps identify and account for the group of suppliers likely involved in the supply chain. For instance, a company sourcing wheat in the U.S. might not know the exact farm of origin but can confidently link its sourcing to a supply shed defined by regional or varietal boundaries.  

Key criteria for supply shed design 

To effectively design and utilize a supply shed, it is helpful to consider the following criteria: 

• Link to points of aggregation. A supply shed should connect to specific Points of Aggregation (PoA) or Processing (e.g., CoC checkpoints) within the supply chain. Example: For palm oil, the supply shed could be linked to mills where audits confirm the value chain connection. 

• Consistent Geographic Boundaries. Boundaries can be defined by a sourcing radius around a checkpoint, allowing for varying levels of granularity, or existing jurisdictional boundaries (e.g., state or provincial borders). Flexibility in boundary setting allows for alignment with practical supply chain realities. 

• Geographic scale. Supply sheds aligned with the LSRG sourcing region framework are typically defined at a maximum sub-national level, ensuring homogeneity in terms of geography or commodity production. In smaller countries that are relatively homogeneous, a national-scale supply shed may also be appropriate.  

However, in cases where supply sheds follow other principles (such as a Market Based Mechanism approach), a broader geographic scope may be considered. This flexibility allows companies to adapt the supply shed size to practical supply chain needs and ongoing discussions in the field. 

• Credibility. The supply shed should operate on a credible and practical scale, influenced by: 

0. The product’s characteristics. 

1. Infrastructure and logistics (e.g., cold storage for dairy). 

2. The shelf life of the product. 

Example: A dairy supply shed might span a larger area with proper refrigeration, while a palm oil supply shed requires proximity to mills to prevent spoilage. 

• Physical/Ecological Characteristics. Ecological conditions can further refine supply shed boundaries. Example: Soil type variations or climate zones within a region can determine a supply shed’s scope. 

• This structured approach ensures that the supply shed concept remains adaptable, credible, and aligned with the company’s supply chain realities and ongoing developments in the field. 

Example – Wheat grown in the United States​ of America

• The three primary varieties of wheat that are sown domestically are winter wheat, spring wheat, and durum. Winter wheat varieties are sown in the fall and usually become established before going into dormancy when cold weather arrives. In the spring, plants resume growth and grow rapidly until the summertime harvest. Spring and durum wheat are typically planted as soon as soil conditions permit in mid-March through April and harvested in the late summer or fall of the same year. 
• The three categories of wheat can be disaggregated further into major classes: hard red winter, hard red spring, soft red winter, white, and durum. Each class has a somewhat different end use, and production tends to be region-specific. 
  • Hard red winter wheat (HRW) accounts for about 40 percent of total production and is grown primarily in the Great Plains (northern Texas through Montana). HRW is principally used to make bread flour. 
  • Hard red spring (HRS) wheat accounts for about 20 percent of production and is grown primarily in the Northern Plains (North Dakota, Montana, Minnesota, and South Dakota). HRS wheat is valued for its high protein levels, which make it suitable for specialty breads and blending with lower protein wheat. 
  • Soft red winter (SRW) wheat accounts for 15-20 percent of total production and is grown primarily in States along the Mississippi River and in eastern States. Flour produced from milling-grade SRW is used for cakes, cookies, and crackers. 
  • White wheat (both winter and spring) accounts for 10-15 percent of total production and is grown in Washington, Oregon, Idaho, Michigan, and New York. Its flour is used for noodle products, crackers, cereals, and white crusted breads. 
  • Durum wheat accounts for 3-5 percent of total production and is grown primarily in North Dakota and Montana. Durum wheat is used in the production of pasta. 
• Each class has a somewhat different end use, and production tends to be region-specific

One could consider the 6 wheat classes in the US as 6 wheat-related supply-sheds in the U.S.

Concept 3 – Integrate ‘project accounting’ into ‘inventory’

Reductions in Scope 3 (S3) greenhouse gas (GHG) emissions from specific projects or interventions can be quantified and integrated into your company’s overall emissions inventory. We’ll break this down into two key types of accounting methods:

1. Project Accounting

Project accounting focuses on measuring the greenhouse gas (GHG) reductions achieved by specific projects or interventions compared to a baseline scenario. This involves:

• Baseline Scenario Emissions: These are the emissions that would have occurred without the intervention. They remain constant over time, assuming no change in activity.
• Project/Intervention Emissions: These emissions reflect the reductions achieved due to the intervention. Ideally, this line will show a downward trend over time, indicating a successful reduction in emissions.

The gap between the baseline and intervention emissions represents the estimated GHG effect, or the reduction in emissions that the project or intervention has achieved.

In this stage, you’re quantifying the emissions saved by specific initiatives, such as switching to more sustainable supply chain practices, energy efficiency upgrades, or other carbon-reducing activities.

2. Inventory Accounting

Inventory accounting, on the other hand, looks at your organization’s overall emissions inventory, which includes all your emissions across different scopes (Scope 1, 2, and 3). This accounting method tracks absolute emissions year over year:

• Year 1 Emissions: Represents your baseline emissions level before any interventions.
• Year 2 Emissions: Shows your updated emissions after integrating the reductions achieved from various interventions.

The goal here is to calculate the absolute GHG reductions, or the total decrease in emissions relative to the previous year’s inventory. By integrating the reductions from your project accounting into your overall inventory, you can demonstrate how specific interventions contribute to a measurable decrease in your company’s carbon footprint.

The process of integrating project and inventory accounting allows for a more detailed understanding of how individual projects impact the broader sustainability goals of your organization. This approach is aligned with established frameworks like the Greenhouse Gas Protocol and initiatives like the Science Based Targets Initiative.

Concept 4 – Process Substitution Methods for Emissions Reduction

This method involves replacing or improving specific operations that contribute to emissions, which are then verified and compared with a baseline to determine their impact. Let’s break down the approach:

1. Baseline Scenario (BAU – Business as Usual)

In the baseline scenario, often referred to as Business as Usual (BAU), the emissions from all operations are calculated without any interventions. This includes:

• Operation EF₁ (Emission Factor 1): This represents the GHG emissions generated by a specific operation under normal conditions.
• Verification of Emissions and Removals: The baseline emissions and removals are verified to ensure accuracy before any changes are made. This verification is critical to establish a benchmark for comparison.

At this stage, the emissions from each operation is recorded as they would occur in the absence of any interventions.

2. Post-Intervention Scenario

After an intervention or improvement is implemented, the emissions are recalculated in the Post-Intervention Scenario:

• Targeted operation’ EF is Substituted: In this step, the emission factor (EF) for the targeted process is replaced with a new, lower EF that reflects the reduced emissions due to the intervention. This intervention could be related to energy efficiency, technology upgrades, or process optimization.
• Non-Targeted Process-Related EFs: Emissions from non-targeted operations remain based on average data and are assumed to stay the same before and after the intervention. These processes are not affected by the changes and continue as usual.
• Verification of Emissions and Removals Post-Intervention: Just like in the baseline scenario, the emissions and removals after the intervention are verified to ensure the reductions are accurately measured and attributed to the changes in the targeted process.

This method focuses on substituting high-emission operations with more sustainable alternatives and quantifying the impact. By verifying both the baseline and post-intervention emissions, this approach provides a transparent and reliable way to track the effectiveness of interventions. This method is especially useful when targeting specific processes within a larger system for emissions reduction.