Conversion of goods & services to footprint

This endpoint provides the cradle-to-gate footprint of an item, and the carbon savings achieved as a result of circular actions like renting, repairing or buying a used item

All inputs, outputs and defaults can be seen in the Convert goods and services technical API docs.

Note that this endpoint converts items that can be linked to GPC brick codes. Services, which cannot be linked to GPC brick codes, are covered by the Convert Finance endpoint, where their footprint is specified by their price.


Required input fields: 

Optional input fields:

  • Number of items
  • Price of the item
  • Duration of the rental period
  • Business model: Online or Physical
  • Weight of the item


The endpoint returns:

  • co2e: the cradle-to-gate footprint of producing a new item(s) of the type specified 
  • circularCo2eSavings: the avoided emissions due to the circular action performed on this item. 

For example, if the item you input is a t-shirt, and the purchase mode is buying used, you are returned the footprint of producing a t-shirt and the avoided emissions from buying it used.

When multiple items are selected, the order of the output (cradle-to-gate footprint of an item) matches the order of the input items. The unique item identifier as input (GPC code or string) is also returned.

How can this data be used for reporting?

The data returned by this endpoint can be used for reporting in the following ways:

  • The output “co2e” is the footprint of a new item, and is the amount that a company would attribute to their scope 3, category 1 “Purchased goods and services” if the item was purchased new. In the case where an item is purchased used or repaired, the company's scope 3 emissions are expected to decrease by this amount as they no longer need to buy a new item. So if a company is making a plan to reduce their scope 3 emissions, circular actions are a possible pathway of reducing Purchased goods & services.
  • The output “circularCo2eSavings” are the avoided emissions of the action, which are formally reported under Scope 4.  This can also be referred to as handprint, meaning emissions that cannot be included in a company’s scope 1-3 emissions, but a measure of how their actions reduce others’ footprints.

This means  that co2e (cradle-to-gate footprint) and circularCo2eSavings (avoided emissions) exist in two different scopes and as such should not be treated as numbers that can be added and subtracted from each other. From a formal sense, co2e (footprint of a new item)  is part of a company’s scope 3 emissions, while circularCo2eSavings (avoided emissions) due to not purchasing a new item belong in scope 4.

Calculations and sources

Buying used

When buying an item used, we assume that the used item displaces the need to buy a new item. However, we recognize that this isn’t always a one-to-one trade-off. A used item might have a shorter lifespan than the corresponding new item. Additionally, used items are typically cheaper and often have lower perceived value, so a consumer might choose to purchase more of them. 

The concept of a replacement rate is how many new items a used item replaces. Inspired by the model applied in Thomas et al. (2010), we use the ratio of the used price to the new price as a proxy for the replacement rate. The price data is obtained from online shopping websites - for Norway we use for used prices and for new prices. The median price value of the top 30-50 hits for each type item is used for the calculations. We recognize that this isn’t a perfect solution, but ultimately the replacement rate depends on individual consumption patterns. We do think it is flawed to assume a replacement rate of one, despite this being the de-facto standard in the literature, as this would lead to an inflated footprint savings.

In its simplest format, the savings for buying used is the footprint of the item multiplied by the replacement rate. Additionally, we subtract contributions for transport and preparation for reuse associated with buying the item used, if this data is available. However, studies have shown that these contributions are typically negligible compared to the replacement of the production of a new item.

We have chosen not to include end-of-life (recycling/incineration) emissions in our buying used calculations. This is because, from a life cycle perspective, buying used postpones the end-of-life of the item but does not remove it from the picture indefinitely.

Since we consider the effect of a single item purchased used, we neglect any market effects - that is, how the market might change if the demand for used items drastically increases.

Renting or lending

The calculation method for estimating CO2 savings due to renting is similar to that of buying used, but with a few differences. Since renting involves a shorter duration of product usage, we assume a 100% replacement rate for the duration of the rental; that is, the user does not buy a corresponding product during the rental period. The CO2 savings are allocated based on the number of uses during the rental period to the total number of uses across the lifetime of the item. We use the duration of the rental to estimate the number of uses. For example, if you rent for a longer duration, we assume that you would use the item more, and therefore, would avoid more emissions.


The calculation method for repairing is similar to buying used, but with the addition of accounting for the emissions due to repair. For each item, we identify the most common type of repair action and the emissions associated with that action, based on the work of H. Lauvland (2021) and S. Privett (2018). The final CO2e savings are calculated by subtracting the repair and transport emissions from the emissions saved by offsetting the manufacturing of a new item.

Accounting for transport

The transport emissions are calculated for downstream transportation between the retail store or warehouse and the final customer. We consider two different types of business models: e-commerce and retail/in-store. For each business model, we have defined a transport scenario with default parameters that describe the average distances and the most common mode of transport based on the work of Zampoeri et al (2019)

Based on your selection of the type of store (online or retail), the average distances to the consumer are combined with the multiplier of the most commonly used transport vehicle to estimate the transport emissions. This provides an estimate of the climate footprint associated with the transport of the product to its final destination. The number of items affect the transport emissions in the online scenario, since the multiplier for the online scenario is on a per-tonne basis. The more items you order, the greater would be the weight of your shipment, and therefore, greater the transport emissions.

Data sources and disclaimer

For these calculations, a mixture of input-output analysis and life cycle assessment (LCA) is used to estimate the carbon footprint of specific products. We use LCAs, where available, as they provide the most accurate footprint values for specific items. In cases where there are no relevant LCAs, we use CO2e multipliers from input-output analysis along with average pricing data to estimate the footprint of an item. These estimates are then based on the average emissions of the sector of the economy producing this type of product, rather than the emissions from a specific supply chain producing a certain good.

We carefully evaluate each LCA we use to ensure that it has a scope, functional unit and system boundaries that are relevant. However, an LCA is performed on a specific value chain, and may not be representative of the exact supply chain of a given item. The purpose of this endpoint is to give an estimate of the footprint, and the savings that can be achieved by performing actions that increase the circularity of an item, by extending its functional life. We therefore consider LCAs of sufficient quality to be acceptable proxies for a full supply chain analysis of a unique product.

Please note that the data provided by this endpoint should not be used for cross-product comparisons, as we do not have the resolution necessary to compare similar products produced via different supply chains.