Climate footprint data on food products
- Reduce business risks connected to coming climate policy
- Increase customer loyalty through transparency and quantitative climate labels on your products
- Win procurements with reliable third-party data on climate footprints
- Highlight your awesomeness compared to you competition or benchmarks
- Reduce climate footprints with quantified climate footprints throughout the production chain and hotspot identification. Focus efforts where you get most bang for the buck
- Save time with climate calculations more than 90% faster than traditional LCA-based methods
- Save money with climate calculations 90% cheaper than traditional LCA-based methods
Modelled climate footprint with cradle-to-gate perspective
CarbonCloud offers a unique tool for food producers to calculate their climate footprints. The tool, CarbonData, is based on more than 20 years cutting edge research and is the base for a long range of scientific studies and investigations for administrative authorities, such as the Swedish EPA. CarbonData is based on a computer model that explicitly models the different processes needed to produce a foodstuff. The model calculates with high precision how large emissions of different greenhouse gases that are generated at each process step along the production chain. The results are communicated in a pedagogical and comprehensible way to the user. The model deals with the entire production chain from all the agricultural processes all the way to the grocery store.
User friendly and relevant climate calculations
CarbonData enables much quicker and less resource demanding calculations than with traditional life cycle assessments (LCA). Yet, several important emission sources are calculated with higher accuracy. The calculations are thus more advanced at the same time as they are quicker and easier to perform. Importantly, calculating all products with the same model makes climate footprint comparisons between products relevant and fair.
Always up to date
The underlying model gets updated when there are advancements made in the underlying scientific base, as the team in CarbonCloud is actively conducting research in the area. This enables CarbonCloud to always deliver state-of-the-art precision calculations. Climate footprint data is perishable. We encourage our customers to improve their processes, so naturally we make sure that they always have access to up to date climate footprint data for their products.
Do you want to get climate footprint data for your products?
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The Science Background
CarbonData is based on a biophysical model that has been developed during more than 20 years of scientific endeavours. The model can calculate climate footprints quickly and with a high degree of accuracy.
Climate footprints for food
Climate Footprints for food describe how much a given food product contributes to climate change. It is usually expressed per kilogram (kg) of the food product, even if the package size is bigger or smaller than one kg. This works the same way as when emissions are declared per km for cars, or nutritional values per 100 grams for food.
Most food stuffs have a long chain of production steps behind them before they end up in a grocery store. This chain is made up of e.g. the production of agricultural inputs, followed by agriculture or fishing, transports, refinements, and additional transport. The chain can be long and complicated. To calculate a climate footprint in fair and representative way, all substantial emissions along the chain need to be included. To make climate footprints for different products comparable with each other, it is important that the calculations are made as similarly as possible.
The phrase Life Cycle is commonly, and somewhat erroneously, used when talking about climate footprints. A life cycle contains the entire production chain, but also the usage phase and disposal phase of the product. It is, however, only the production phase that is referred to when talking about life cycle for food, because the usage phase is when the food is in our bodies, and the disposal phase is after the food leaves our bodies and is taken care of by the sewage systems. There are, of course, emissions associated with these latter phases, but they are rarely attributed to the individual food items.
CarbonData hence calculates emissions from the cradle to the gate. The cradle is the production of agricultural inputs and the gate is a shelf in your typical grocery store. All substantial and relevant steps and processes that cause greenhouse gas emissions are represented in the model. This approach ensures that all food products are calculated in the same way, and can be fairly compared to each other.
It is essential with massive amounts of data to make these types of calculations. Long-running scientific endeavours, combined with national statistics, ensures that we have a sufficient base to make representative calculations for the conditions in different countries. To make the calculations as accurate as they can be, we combine these data with specific data from our customers. This allows us to quickly make calculations that are specific, such as pasta from a given company, or more generic, such as average pasta produced in Germany.
Comparing climate footprints between products
CarbonData is at the scientific frontier of climate footprint calculations for food and has several advantages compared to other methods. The most common commercially available method for calculating climate footprints for food is life cycle assessments (LCA). An LCA is typically performed by a consultant who follows a standardized method to analyse the product’s different steps along its production chain. Even though standardized, there are three aspects that frequently makes it fallacious to compare LCA-results between products and studies. These three aspects are allocation, system boundaries, and the treatment of energy systems. Different choices can be made for all these in an LCA while still adhering to the standards. CarbonData is different to LCAs in the important aspect that all these three aspects are consistently treated the same for all calculations, which makes CarbonData results for different products comparable between each other.
Allocation treats how the responsibility for emissions is distributed between different products. This is primarily a problem when one process produces more than one product.
Probably the most obvious example is a dairy cow, who produces milk, calves, meat, and leather. Throughout her life the animal causes a quantity of greenhouse gas emissions. At the same time, she produces a number of calves, a quantity milk, and finally—after slaughter—she produces meat and leather. The meat also consists of more or less expensive cuts. There is not one objective truth for how her emissions should be allocated between the products she has produces throughout her life, but different allocation can be argued for to answer different questions. This is the reason why comparisons between different LCA-studies can be misleading. All allocations are always treated the same in CarbonData.
System boundaries is about where to draw the line for which emissions to include in the calculations. The fuel for the tractor is e.g. always included, but should the production of the tractor be included or not? Are emissions for transport and distribution included? CarbonData treats system boundaries consistently.
Energy is required to produce food. How to treat emissions from the energy system is not obvious, however. This is particularly true for electricity. How large the climate footprint is per kWh of electricity differs significantly between geographical locations and over times of year and times of day. The Swedish electricity system is almost carbon dioxide free, but Denmark and Germany use significant shares of coal-based power. Companies sometimes purchase green electricity, and how should that be treated in the calculations? CarbonData has data on electricity production for different regions and countries, and consistently treats electricity the same for all products.
Adding different greenhouse gasses together
There are many different greenhouse gasses and carbon dioxide (CO2) is the most widely known. Different greenhouse gasses impact the climate in slightly different ways, some stay in the atmosphere for a long time, some stay for a shorter time. Some cause more warming per molecule in the atmosphere than others.
There is an exchange rate for greenhouse gasses that allow us to compare emissions of different gasses to each other. This exchange rate explains how many kg of CO2 that a given emission of another gas is equivalent to, from a climate change perspective. This exchange rate is called Global Warming Potential and is abbreviated GWP. The unit for these emissions is kilogram carbon dioxide equivalents (kg CO2e). This means that an activity has caused emissions of different greenhouse gasses that combined affect the climate equally to a given amount of carbon dioxide emissions would, during a time-frame of 100 years.
Selected publications relevant to CarbonData
Bryngelsson, D., Hedenus, F., Johansson, D.J., Azar, C. and Wirsenius, S., 2017. How do dietary choices influence the energy-system cost of stabilizing the climate?. Energies, 10(2), p.182.
Bryngelsson, D., Wirsenius, S., Hedenus, F. and Sonesson, U., 2016. How can the EU climate targets be met? A combined analysis of technological and demand-side changes in food and agriculture. Food Policy, 59, pp.152-164.
Hedenus, F., Bryngelsson, D. and Wirsenius, S., 2015. Matkonsumtionens klimatpåverkan och markanvändning. Hållbara konsumtionsmönster – analyser av maten, flyget och den totala konsumtionens klimatpåverkan idag och 2050. En forskarantologi. p. 24-33. Rapport 6653. Naturvårdsverket.
Hedenus, F., Wirsenius, S. and Johansson, D.J., 2014. The importance of reduced meat and dairy consumption for meeting stringent climate change targets. Climatic change, 124(1-2), pp.79-91.
Herrero, M., Wirsenius, S., Henderson, B., Rigolot, C., Thornton, P., Havlík, P., De Boer, I. and Gerber, P.J., 2015. Livestock and the environment: what have we learned in the past decade?. Annual Review of Environment and Resources, 40, pp.177-202.
Ranganathan, J., Vennard, D., Waite, R.I.C.H.A.R.D., Dumas, P., Lipinski, B. and Searchinger, T., 2016. Shifting diets for a sustainable food future. World Resources Institute.
Wirsenius, S., 2000. Human use of land and organic materials: modeling the turnover of biomass in the global food system. Chalmers University of Technology.
Wirsenius, S., 2003. Efficiencies and biomass appropriation of food commodities on global and regional levels. Agricultural Systems, 77(3), pp.219-255.
Wirsenius, S., 2003. The biomass metabolism of the food system: A model‐based survey of the global and regional turnover of food biomass. Journal of Industrial Ecology, 7(1), pp.47-80.
Wirsenius, S., Azar, C. and Berndes, G., 2010. How much land is needed for global food production under scenarios of dietary changes and livestock productivity increases in 2030?. Agricultural systems, 103(9), pp.621-638.
Wirsenius, S., Hedenus, F. and Mohlin, K., 2011. Greenhouse gas taxes on animal food products: rationale, tax scheme and climate mitigation effects. Climatic change, 108(1-2), pp.159-184.
Wirsenius, S., Hedenus, F. and Johansson, D.J., 2014. Why reduced beef, lamb and dairy consumption may be necessary for meeting stringent climate targets. The Food Climate Research Network (FCRN)