This report uses the same methodology across all Adevinta marketplaces. To access the complete report on the Adevinta group. The analysis was based on data from more than 18.3 million items sold (1) on Marktplaats, further enriched by insights gathered from more than 32.000 Adevinta users about their purchasing and selling behaviours.
Product categories included in the analysis:
Fashion | Bags & Luggage | Home & Garden | Personal Care & Wellbeing | Family | Child & Baby | Leisure | Sport & Hobbies | Electronics | DIY
Exclusions
Real-Estate and Motorised Vehicles were not considered due to the current challenges in developing a reliable LCA methodology to measure the emissions savings accurately, specifically the significant variability in emissions, influenced by factors such as driving habits, maintenance, and fuel efficiency. This remains an area of future research and improvement, with the objective of contributing to and eventually including the measurement of impact from second-hand vehicles in the future.
Similarly, Services or Tickets and Arts & Antiques are omitted from the scope as they are deemed not to contribute to emissions avoidance — with Arts & Antiques regarded as unique items that do not replace new purchases.
Approach
Vaayu’s approach used consequential LCA to calculate avoided emissions, extending beyond examining individual product sales and aiming to evaluate the broader systemic impacts:
● Avoided emissions: the potential reduction in emissions resulting from users buying second-hand items instead of buying new products elsewhere
● Consequential LCA: a comprehensive method recognised globally for its robustness in calculating avoided emissions
The methodology closely followed the World Resource Institute (2) guidelines, which focused on comparative product emissions analysis.
Chart: Our approach to calculating the avoided emissions of Adevinta’s marketplaces
Several factors influenced the potential to reduce emissions through second-hand purchases:
● Alternative scenario: the emissions from producing and distributing a comparable new item (see more in the Generated Emissions section below) which second-hand shopping may “avoid” to a certain extent (the Replacement Rate)
● The Replacement Rate: the metric that assessed whether a second-hand item was a suitable substitute for a new one, indicating how likely it is that a second-hand purchase via Adevinta replaced a new purchase (see more in the Replacement Rate section below)
● Generated emissions: included the emissions generated by second-hand purchases on Marktplaats via our delivery and packaging, as well as the associated business operations from the overall management and maintenance of the marketplaces
LCA Methodology
To calculate the avoided emissions, Vaayu analysed more than 150 million second-hand transactions across all relevant product categories. The information was processed using Kria, Vaayu’s proprietary LCA Impact Modelling Engine and database.
To accurately quantify the total net impact, emissions from on-platform deliveries and packaging associated with all successfully sold items were also incorporated into the GHG inventory and emissions assessment.
Items labelled as 'new' are included in the overall calculation because they contribute to the platform's operational footprint. However, since these items a
This methodology aligns with a conservative approach to assessing avoided emissions, aiming to prevent over-accounting in the absence of a model that accurately predicts the substitution rate for new products.
Consumer Survey
To deepen the understanding of user behaviour on the eight marketplaces in scope, Vaayu commissioned surveys with 32.000 respondents across the Adevinta group second-hand markets.
Their purpose was to gather essential data for calculating the Replacement Rate and the potential avoided emissions from the sale of second-hand items. They also collected additional delivery logistics data, including the types of packaging and packaging materials.
The survey size ensured a representative sample by considering factors such as market specifics, product category, and user activity levels on the marketplaces in the prior 6-12 months. For Marktplaats, an EU average was used.
Replacement Rate
Calculating a perfect like-for-like replacement of new products with second-hand items is not straightforward. To account for this challenge, the Replacement Rate is:
● A key metric driven by consumer behaviour, measuring the substitution ratio and clarifying how effectively second-hand items can replace new ones
● Pivotal in evaluating the environmental advantages of reuse
● An influencer in calculating the extent to which carbon emissions from the production and distribution of similar new products are “offset” by purchases on the marketplaces
In this analysis, users were surveyed on their rate of avoided purchases within the product categories specified. The Replacement Rate was derived from responses of buyers to the survey question: “If you had not found this product on the platform, would you have bought this, or a similar product, brand new?”
Chart: Calculating the Replacement Rate
* Replaced purchases = 100% of ‘Yes’ responses and 50% of ‘Maybe’ responses while excluding all unplanned purchases
** Total responses = total number of responses to the above core question. All replies from professional sellers or businesses were omitted from the calculations of the Replacement Rate. It is assumed that their engagement is primarily for economic benefits rather than sustainability-driven motivations. Additionally, their responses do not accurately represent the purchasing patterns of typical users, hence their exclusion.
For calculating avoided emissions, the Replacement Rate was tailored to each category and marketplace, provided there was a statistically adequate sample size (i.e., more than 100 responses per category after excluding those from professional sellers). Where it was not adequate, a Europe-market average Replacement Rate per category was used instead.
Alternative Scenario
To estimate the carbon emissions avoided by purchasing second-hand items on each marketplace instead of these comparable new ones, it was necessary to account for the emissions from producing new products through their distribution.
Vaayu evaluated this impact using a cradle-to-consumer life cycle assessment approach. This approach includes the calculation of energy and material usage, transportation, extraction of natural resources and waste management at each stage of the product life cycle.
Emissions from the product use and end-of-life stages were excluded from avoided emissions calculations because the impacts from using both new and second-hand products are considered equivalent in the comparative analysis.
This means that the emissions generated during the use and disposal of products are assumed to be the same for both second-hand and new products, and so neutralise each other when comparing the two scenarios (i.e., purchasing a second-hand product versus buying a similar new product).
Chart: The product life cycle considered (both second-hand and new products)
It is important to note that the product carbon footprint assessment for calculating potentially avoided cradle-to-consumer emissions, as well as the assessment of emissions from deliveries and packaging of second-hand items, was performed at the product category level. This approach accounts for varying taxonomy trees across different marketplaces.
The data analysed were available only at the product category level, meaning different product types can be listed under a single category. LCA data were therefore used by assuming certain reference products for specific product categories.
Consequently, the calculated emissions should be interpreted as representative of the entire category rather than individual transactions or specific product models.
In cases where a direct correspondence in Vaayu’s taxonomy (3) could not be established for a product category, a proxy or average emissions figure was applied to ensure comprehensive assessment.
Generated Emissions
Deliveries
Emissions associated with deliveries were analysed using Vaayu’s unique logistics model, integrating data from consumer surveys to enhance accuracy.
This model calculates the carbon emissions associated with various delivery methods, including meet-ups, PUDO points, and home deliveries, employing a fuel-based calculation approach based on the total distance travelled during delivery.
Logistics calculations for on-platform sales:
● Primary data regarding seller and buyer locations (home or PUDO points), carrier and delivery methods was used where available
● When the cities, localities or postal codes of both the buyer and seller were available, the distance between the two was calculated
● Where both the buyer and seller locations could not be geolocated (e.g. only having postal code data for the seller), a country-specific, population-weighted average distance was used
● In the absence of explicit delivery methods, multiple approaches were taken;
● Where carrier was used and carrier name was provided: Research was conducted by Vaayu to determine the delivery methods offered by the carrier partners.
● Where other delivery methods were used: Delivery method distributions for both origin and destination were taken from the seller and buyer surveys, respectively
● Where there was not a statistically adequate sample size: Europe-market average delivery method distributions were used instead
● The package mass and volume of each delivery were estimated based on the mapped category to account for the variance in categories being sold across the marketplace.
● Logistics calculations for off-platform sales:
The distribution among meet-up, PUDO, and home delivery methods was derived from the buyer and seller surveys and then used to calculate a weighted average delivery impact per category
The proportion of meet-ups was determined by averaging the responses from both sellers and buyers
Where there was not a statistically adequate sample size, Europe-market average delivery method distributions were used instead
Meet-up distances per marketplace and category were estimated using the seller and buyer survey responses
● Transport times were multiplied by average vehicle speeds to determine distance per time frame and vehicle type
A weighted average distance for each vehicle type was then calculated, and a further weighted average was computed based on the distribution of vehicle types as indicated by the survey
Where there was not a statistically adequate sample size, European market meet-up distance was used instead
Packaging
Emissions attributed to secondary packaging were calculated using Vaayu’s Logistics Calculation Engine, where the secondary packaging distribution on a per-category basis was derived from the survey data.
Each packaging element type was estimated by calculating volume or mass using quality LCA data in Vaayu’s taxonomy. The emissions impact of each element was multiplied by its distribution within a product category, so the emissions contributions from secondary packaging could then be calculated on a per-sale basis.
Where there was not a statistically adequate sample size, a Europe-market packaging distribution was used instead.
Reused packaging elements were presumed to have zero emissions since they are designed for single use only and were therefore excluded from these calculations.
Business Operations
The calculation of operational footprint encompassed a comprehensive inventory of Scope 1-3 emissions related to business operations in line with the minimum boundaries defined in the technical guidance by the GHG Protocol (4). The full Adevinta Group Corporate Carbon Inventory and GHG emissions results for the reporting year 2023 can be found in Adevinta’s Annual Report 2023 (5).
The organisational boundary for the report was set using the operational control approach, including all operations under Adevinta's control or its subsidiaries. The emissions from each activity were allocated to the different marketplaces in scope of these avoided emissions calculations, based on the allocation approach provided by Adevinta’s Global Sustainability Team, to provide a holistic view of environmental impact.
The emissions per Scope were calculated as follows:
● Scope 1: emissions from fuel combustion in leased company vehicles;
Quantified using Adevinta’s primary data on fuel consumption.
● Scope 2: emissions from electricity, heating and cooling for Adevinta’s leased offices, electric company vehicles and on-premise data centres;
Calculated and tracked using market-based and location-based methods, in line with the GHG Protocol Scope 2 technical guidance
● Scope 3: emissions from purchased goods and services, capital goods, energy (not covered by Scope 1 or 2), upstream transportation, upstream leased assets, waste, business travel, employee commuting, investments, packaging, and deliveries related to on-platform transactions;
Employee commute, waste generated in operations, digital platform use, cloud and hosting services, and upstream leased assets were calculated using activity-based methodology
For categories including purchased goods and services, capital goods, business travel and investments, a mixture of activity-based and spend-based methodologies were applied.
1. Sold products are the total amount of products sold on the marketplaces. This is the sum of known sales (i.e. on-platform transactions) and assumed sales of classifieds, the latter based on an indicator provided by the marketplaces.
2. World Resources Institute (WRI), Estimating and reporting the comparative emissions impacts of products, Russell, S., 2019.
3. The classification system within Vaayu’s database used to categorise and store emissions and impact data.
4. Greenhouse Gas (GHG) Protocol, Corporate Standard.
5. Adevinta, Annual Report 2023: Changing commerce together.
