Food production accounts for more than a quarter of greenhouse gas emissions globally. For food companies, carbon emissions are no longer an invisible byproduct of doing business. Instead, a food company’s carbon footprint is a growing liability. Pressure from investors, customers, regulators and the public has created a strong business case for measuring and reducing your greenhouse gas emissions.
In this article, we’ll explore how CarbonCloud calculates carbon footprints in the food sector — an industry known for its complex and opaque production chains.
Challenges for food companies calculating carbon footprints
Food supply chains are notoriously complex. More steps in a supply chain means more places for greenhouse gas emissions to be generated. Calculating the climate footprint of a final food product shipped to market is therefore highly intricate and can vary widely depending on which activities and factors are included in the scope, leading to different footprint calculations for the same product.
It can also be difficult for companies to get reliable primary data from suppliers and partners, leading many companies to rely on less precise spend-based estimates for their carbon footprint.
But product carbon footprints are becoming increasingly important for food companies. Some may be subject to carbon prices based on their emissions, while others with voluntary net zero or carbon neutrality targets may effectively be paying a carbon price when purchasing carbon credits equivalent to their emissions in a given year. This financial reality, combined with the very real reputational threats of disclosing inaccurate environmental data, means that a lot hinges on food companies producing highly accurate, credible emissions data for their products.
This is why CarbonCloud has developed a rigorous, science-backed methodology to calculate the carbon footprint of specific foods with a high degree of accuracy.
👉 Curious to learn more? Read our Product Carbon Footprint (PCF) guide and Corporate Carbon Footprint guide.
How CarbonCloud calculates product carbon footprints
Our approach
CarbonCloud calculates the carbon footprint of food products in accordance with ISO 14067 and GHG Protocol Product Life Cycle Accounting and Reporting Standard. We use the attributional (bookkeeping) approach to life cycle accounting, meaning that we consider all significant activities and their emissions in the production of a particular food item. The carbon footprint of a particular food item is typically expressed per kilogram (kg) of the food product, no matter the size of the package.
What’s in scope for a food carbon footprint?
Because food products typically have long production processes leading up to them appearing on store shelves, what you include in a carbon footprint (the ‘scope’) can result in major discrepancies in your final Scope 3 emissions calculations. To calculate a product’s carbon footprint in a fair and representative way, any major source of emissions throughout a product’s supply chain needs to be included, and the calculation or methodology used for one product should closely align with that used for other products to ensure comparability.
The term life cycle is often used to represent the environmental impact of the life of a product. However, because the final destination for food is often sewage systems, we typically don’t need to calculate the impact of the entire ‘life’ of food products — just the impact from cradle (where the food comes out of the earth) to the gate (in our case, a grocery store shelf). This approach covers all the major emissions hotspots during food production, while also allowing the footprints of different food items to be reliably compared.
Illustration of a food supply chain and the stages.
Calculating emissions at each stage of the food supply chain
CarbonCloud takes a specialized approach to calculating emissions at each stage of the food supply chain. (For a more technical breakdown of our methodology, read our Methodology page, or dive deeper into each of the stages using the links below).
Stage 1: Agriculture
The first stage we consider is agriculture. This is a complex calculation that involves data from various biological activities and multiple greenhouse gases, each of which vary widely between crops. A number of mechanisms and activities influence the carbon footprint of the agricultural stage, including (but not limited to) pesticide and fertilizer production, deforestation from land use changes, farm machinery, and irrigation.
To accurately assess the climate impact of any particular crop, CarbonCloude created a comprehensive dataset for all crops grown globally, combining reliable data on agricultural activities and relevant parameters to assess the environmental impact.
Stage 2: Refinement
The CarbonCloud refinement model calculates greenhouse gas emissions from food processing stages. We refer to refinement as the process of turning raw agricultural products into processed forms.
When calculating refinement emissions, CarbonCloud requires users to specify the amount and type of input in kg per kg of output during a particular refinement step, as well as the energy used during that step. It will also ask users whether the removed parts serve as by-products. If they are, emissions are allocated according to the economic value of the by-products and main product. This helps determine how emissions will be allocated between the main product and by-products. We also use a 13.3% spoilage rate as per United Nations data.
Stage 3: Energy use
Whether it’s drying, storing, refrigerating, heating, or processing, virtually all stages of food production beyond the farm gate require energy. CarbonCloud adds an energy ‘node’ to the relevant processes in your food product’s supply chain to account for the emissions from electricity and fuel.
Wherever possible, CarbonCloud uses a market-based method to calculate energy emissions (based on a specific energy supplier). If such data is unavailable, CarbonCloud will rely on the ‘residual mix’ emission factor, which represents the total emissions of a country’s energy once renewable electricity has been deducted. If we can’t source supplier-specific or residual-mix data, CarbonCloud will resort to the location-based method, which takes the average mix of electricity in a particular place over a given period.
In short, we will always seek precise data for calculating energy-related emissions, working our way down the data hierarchy depending on availability.
Stage 4: Transportation
The CarbonCloud transportation model calculates emissions based on fuel type, vehicle type, and operational parameters like capacity utilization and empty returns. It covers various transportation modes, including trucks, trains, ships, and planes, and incorporates factors like refrigeration needs, distance, and load characteristics. The model accounts for upstream emissions of fuel production and allocates emissions based on cargo weight or volume.
Stage 5: Packaging
Lastly, CarbonCloud calculates packaging emissions. By accounting for the carbon embedded in each respective material as well as the processing that gives the packing material its final form, we achieve a high level of accuracy. Additionally, we account for the energy consumed in processing materials like plastic, aluminum, paper, and glass.
When it comes to recycled packaging material, CarbonCloud accounts only for the emissions that come from the recycling process to avoid double-counting the carbon embedded into the material. Our model factors in regional variations in energy intensity and recycled content, ensuring precise emission allocation.
CarbonCloud’s Automated Modeling
CarbonCloud has developed an innovative climate footprint calculation engine that we call ‘Automated modeling’. This process automatically generates the climate footprint and digital twin for every product based on standard product information and the bill of materials.
When you input a product, our system processes it through a modeling pipeline. The engine does three things:
- It compares the product to similar ones.
- It matches it with relevant properties.
- It models an appropriate production process
The modeling engine has two key parts:
- Product Classifier: Categorizes the product based on its properties using CarbonCloud’s category tree.
- Modeling Engine: Creates a production model based on the assigned category.
By entering (at minimum) a product name, the market the product is sold, the production volume, and unit weight, CarbonCloud’s automated modeling can produce a climate footprint modeled on the same methodology and scope outlined above.
Talk to CarbonCloud today
If you’re just getting started on your climate journey, it can be difficult to know where to begin.
At CarbonCloud, we’ve helped dozens of food companies navigate the complexity of carbon accounting, reporting, and decarbonization.
Find out how we can help today.
