Beginning the Carbon Accounting Process in the Food Sector

In this edition, we will explore:?

• First steps for carbon accounting in the food sector
• Building a greenhouse gas inventory
• Agricultural value chain data collection

There's a reason that with each new year we like to come up with resolutions and goals for ourselves. Research has found that following temporal landmarks, humans are more likely to take a big-picture view of their lives and as a result, identify imperfections to work through and improve upon.1 The "fresh start effect" is a phrase coined by psychologists to describe this pattern.

Climate change presents humanity with a temporal landmark: ecosystems that societies have evolved with for thousands of years are becoming increasingly unrecognisable at rates never seen before. This requires us to reimagine business-as-usual. Some really cool changes are already being made to food systems around the world. But, in order to scale practices such as regenerative agriculture and meet emission goals, companies first have to get into the nitty-gritty of carbon accounting. After all, if we don’t know how much we’re emitting, we’ll never know how much we’ve improved!

Previously, we introduced scope 3 emissions and explained how critical they are in efforts to decarbonize food value chains. This edition will break down the emission measurement journey into three steps:

1. Building the GHG inventory
2. Collecting data
3. Utilising your data

Before we focus on each step, it's critical to underscore the importance of timing in the carbon accounting process. The food sector value chain is especially complex: agricultural inputs, machinery, and supplier networks represent a host of upstream sources of emissions. Collecting emissions data is not a simple task. However, carbon accounting provides a unique opportunity for highly sector-specific risk mitigation and strategic planning.

Building the GHG inventory:

A greenhouse gas inventory is a depository for emissions data that a business's value chain produces (their Scope 3 emissions). In this sense, an emissions inventory tells the story of a product's life cycle. It can tell us where and who along the value chain emits the most greenhouse gases, and therefore, what reduction efforts should be prioritized.

For example, most emissions in the beef production process are released by cattle on the farm. While transportation emissions should be reduced, the priority should be to reduce cattle emissions.

As a company begins to think about the various steps in their product life-cycle, the complexity of their value chain can make the task overwhelming. The “Greenhouse Gas Protocol Corporate Value Chain (Scope 3) Accounting and Reporting Standard” shares two organizational tools to make inventory building a bit easier: the emissions boundary and Scope 3 categories.2

A company’s emission boundary is synonymous with the breadth of their GHG inventory. However, a single product can have a litany of up or downstream emissions, making it necessary to draw the emissions reporting line somewhere, or the task would become too exhausting and costly. These six questions help us draw that line:

Defining Emission Boundaries:

Source: Greenhouse Gas Protocol Corporate Value Chain (Scope 3) Accounting and Reporting Standard

Note that if any emission sources are deemed immaterial, a justification of the decision must be disclosed. The next table identifies emissions activity-type.

Scope 3 Emissions Categories:

Source: Greenhouse Gas Protocol Corporate Value Chain (Scope 3) Accounting and Reporting Standard

Some of these categories may be more helpful to pay attention to than others in the food sector depending on your supply chain location, but in general, the bulk of food sector emissions come from agricultural production.3

While the three emission scopes encompass practically every value-chain activity,? the GHG Protocol’s agricultural guidance currently requires particular CO? land use change emissions to be reported under a separate biogenic carbon category.? The three main biogenic activities are land use management of carbon fluxes, land use change (LUC) sequestration, and CO? biofuel combustion. It’s worth exploring biogenic processes reporting rules in greater detail if your value chain is especially involved in land use management.?

To review, a greenhouse gas inventory helps us store emissions data. The GHG Protocol's two tools help us identify the type of value chain emission source and at what point we stop reporting data. Now, we can move on to data collection.

Data Collection:

This step consists of (1) selecting supply chains, (2) contacting suppliers, and (3) interpreting data. After selecting emission sources for prioritization and defining the boundary, companies should select a supply chain correlated to the production of a single material.

As an example, rice has a high carbon footprint due to its release of methane gases. A cereal company that uses rice might identify it as a capital good for emission reduction prioritization. After selecting rice production as the supply chain of focus, they should identify all steps necessary to produce rice (i.e. agricultural inputs, transportation).

Then, all suppliers should be contacted to begin the data collection process. It may be helpful to send out online questionnaires, meet virtually, or visit suppliers in person depending on the nature of the emissions source, and the data quality's dependence on clear communication.

At first, datasets will likely be filled with gaps as issues with measuring methodologies arise. However, this should not prevent emissions measurements! While primary source data from your suppliers will certainly be the most accurate representation of a product's emissions, secondary data can fill gaps in data sets.

Secondary data can be taken from similar primary source activities on the same value chain or industry average activity emissions. After datasets are collected and stored in the inventory, we can move on to making use of the data!?

Making the numbers come alive:?

Now that we have an organisational structure to identify, collect, and store data, we can begin to process data, run quality control assessments, and develop models.

Processing data requires companies to communicate with suppliers directly to review measurement methods, unexpected results, and recommendations for future measurement improvements. Data processing goes hand-in-hand with quality control assessments—they should both be integrated into consistent revaluations of supply chain structures and supplier production methods.?

After data sets are finalised, building transparent models will allow the numbers to be put to work. Emissions models can predict the effects of environmental changes or emission reductions on supply chains, thereby informing future risk mitigation.

This carbon accounting process is essential if companies are to meet their emissions reduction targets. By building a system to collect data and consistently reassess the validity of the various methods and materials of focus, reduction efforts will be better targeted, making their implementation more efficient and effective.

References: [1], [2], [3], [4]