Expanding the toolkit

This report has been produced by the Trase project with the strategic inputs of the Stockholm Environmental Institute at the University of York and the Institute of Environmental Science (CML), Department of Industrial Ecology at Leiden University in the Netherlands, and with the financial support of Sitra, the Finnish Innovation Fund. The report reflects only the views of its authors and not the donors.

Executive Summary

Context

The European Union’s (EU) consumption of forest-risk agricultural commodities is a major driver of forest and biodiversity loss globally. While the EU Deforestation Regulation (EUDR) introduces mandatory obligations for companies to demonstrate due diligence in supply chains in order to ‘de-risk’ the EU from exposure to commodity driven deforestation, its successful implementation faces significant political and logistical pressure. This report uses exploratory scenario analysis to model changes in the EU’s environmental footprint. By examining the seven commodities covered by the EUDR (cattle, cocoa, coffee, oil palm, rubber, soy, and timber), the study calculates the potential reduction in global deforestation, associated emissions, and biodiversity impacts resulting from the implementation of EU policy measures. These measures include both the EUDR and a wider suite of policy levers that promote sustainable domestic consumption, sustainable domestic production, and sustainable supply chains via border adjustment costs. These policy levers are tested in combination to assess the potential for deeper reductions in the EU’s footprint than might be achieved via supply chain de-risking alone. Overall, the results demonstrate substantial potential to reduce the EU’s footprint, with the largest reductions coming from a combination of policy measures.

Purpose and scope

This report establishes a baseline account of the EU27’s deforestation footprint, associated deforestation emissions, and biodiversity impacts linked to the seven EUDR commodities. It then explores how these footprints change under different hypothetical levels of EUDR implementation ambition and under a set of non-EUDR policy levers designed to influence both demand and supply of deforestation-implicated materials. The scenarios are comparative rather than timebound forecasts, providing a “before versus after” assessment of the relative effects of different policy measures against the baseline.

Approach

The analysis employs a hybridised multi-regional input-output (MRIO) framework to explore the impact of future scenario space, in contrast with Trase’s previous analysis which has explored historical supply chain impacts. The material footprint for the baseline (against which scenarios are compared) is derived from a model of the global economy for 2022 and is extended to environmental impacts by combining it with commodity-specific deforestation estimates (derived from the DeDuCE dataset) and a biodiversity metric (Forest-LIFE). Three footprints are calculated throughout: deforestation area (ha), associated deforestation emissions (tCO2e), and biodiversity impacts measured as annualised species extinctions. Absolute footprint values should be interpreted as model outputs, with the primary emphasis on relative differences between scenarios.

Baseline footprint and hotspots

In the 2022 baseline, the EU27’s estimated deforestation footprint according to the model implemented in this analysis is 162,240 ha across the seven focal commodities, with associated deforestation emissions of 59,417,088 tCO2e, and an associated biodiversity impact (Forest-LIFE score) of 0.2946 annualised species extinctions. This deforestation footprint represents an extent of annual deforestation five times the size of Malta, and is equivalent to over 200,000 full-sized football pitches. The associated carbon footprint is approximately equivalent to 60 million passenger return flights between London and New York. The footprint is dominated by cattle (about 48% of the total), while cocoa, oil palm and timber each contribute roughly 12-13%, followed by soy (around 6%), rubber (around 5.1%) and coffee (around 3.7%).

Footprints are unevenly distributed across member states: Germany has the highest absolute footprint (around 23.4% of the EU total), and the five largest contributors (Germany, France, Italy, Spain and the Netherlands) account for around 70% of the total. At the same time, the footprint is also concentrated across points of origin, with the top 15 origin countries accounting for around 72% of the EU27 deforestation footprint. Brazil is the single largest origin (around 18.8% of the total), dominated by cattle and soy, while China is a major origin largely through timber and Indonesia through oil palm. Other commodities have more concentrated origin profiles, with Côte d’Ivoire dominating cocoa, Cambodia dominating rubber, and Peru dominating coffee.

Impact of the EUDR

The EUDR was adopted in 2023 and requires operators placing relevant commodities and products on, or exporting them from, the EU market to collect plot-level geolocation data and submit due diligence statements showing the products are deforestation free (no deforestation or forest degradation after 31st December 2020) and produced in accordance with relevant laws in the country of production. Implementation has been pushed back and, following the latest postponements, it now applies from 30th December 2026 for large and medium operators and 30th June 2027 for small and micro operators (European Union, 2025a). These delays increase the near-term relevance of complementary policy levers that can reduce impacts even where EUDR implementation is phased, uneven, or weaker than initially anticipated.

The EUDR scenarios developed in this analysis comprise different hypothetical implementation scopes and enforcement strengths, applied across low, medium and high ambition settings which influence the degree to which EU supply chains are ‘de-risked’. In practical terms, ‘low’ ambition reflects more limited scope and weaker enforcement and compliance, while ‘high’ ambition reflects an expansion to broader product scope and stronger enforcement and compliance (with ‘medium’ ambition in between). Following the implementation of these scenarios, deforestation footprint reductions are substantial and increase with ambition. From the baseline of 162,240 ha, the EU’s deforestation footprint that is associated with the seven focal commodities falls to 127,096 ha under low ambition implementation (a 21.7% reduction), 109,668 ha under medium ambition (32.4% reduction), and 51,582 ha under high ambition (68.2% reduction). In other words, the modelled deforestation footprint reduction ranges from around one fifth under low ambition to around two thirds under high ambition. Under low, medium and high ambition implementation, overall emissions fall to 44,191,481 tCO2e (25.6% reduction), 36,974,116 tCO2e (37.8% reduction) and 19,416,277 tCO2e (67.3% reduction), respectively, with Forest-LIFE scores falling to 0.240 (18.5% reduction), 0.211 (28.4% reduction) and 0.104 (64.8% reduction).

Policy levers beyond the EUDR and combined outcomes

The non-EUDR mechanisms modelled in this report are a central part of the scenario set, designed to test how far demand-side, production-side and trade-related measures could reduce the EU’s footprint, both on their own and in combination with the EUDR. The policy levers explored (Table a provides a summary) are not exhaustive options, but instead illustrate realistic and, as applied under low, medium and high scenario space, increasingly ambitious options for reducing the EU’s footprint. Across levers, ambition levels reflect differences in the assumed scale and uptake of the measures: low ambition represents modest innovation or adoption, medium represents wider uptake, and high ambition reflects more transformative policy, technological development and scale-up. Demand-side measures explored in the analysis include those that reduce consumption of high-impact commodities and materials, such as dietary shifts away from beef and measures to reduce food waste (including food waste linked to animal feed). Supply-side examples include shifts in production and material use that reduce pressure on deforestation-linked supply chains. The border adjustment mechanisms explored include levies applied to imports that attach a carbon-related cost, with more ambitious variants extending this logic to costs linked to biodiversity impacts.

Table a. summarises the policies explored in this analysis, the focal commodities targeted/ influenced by these policy areas and example measures (which influence one or more commodities) as well as their ambition levels. The commodity-specific sections of the report should be referred to for further detail, including the full scope of measures explored and their ambition levels.

Figure A summarises the headline cross-commodity results reported here. In isolation, combined low ambition non-EUDR levers reduce the EU deforestation footprint associated with the seven focal commodities to 151,436 ha (a 6.7% reduction), while medium ambition non-EUDR scenarios reduce it to 119,891 ha (26.1% reduction). Under high ambition non-EUDR combinations, the footprint falls to 97,613 ha (39.8% reduction). The most transformative reductions arise when non-EUDR levers are combined with the EUDR (see Figure A). Implementing low ambition EUDR (which – at the time of writing – is considered the most ‘realistic’ of our scenarios given the 10 challenges that the EUDR has faced to date) on top of high ambition non-EUDR levers reduces the EU’s deforestation footprint associated with the seven focal commodities to 64,845 ha (a 60.0% reduction). Implementing high ambition EUDR on top of high ambition non-EUDR levers reduces the footprint further to 23,849 ha (an 85.3% reduction; versus 51,582 ha, 68.2% reduction under the high ambition EUDR scenario applied in isolation). These results indicate that, while the EUDR can deliver large reductions, the largest and most resilient reductions arise when de-risking is combined with measures that reshape demand, production and incentives across the EU market.

Differences across deforestation, emissions and biodiversity outcomes

While deforestation drives associated changes in emissions and biodiversity in this analysis, the results highlight important differences in how these footprints manifest. In the baseline, oil palm accounts for 12.6% of the deforestation footprint but 22.1% of emissions and 25.4% of biodiversity impacts. This underlines that relatively small deforestation reductions in biodiversity hotspots can have outsized effects on biodiversity footprints, and that targeting areas with the largest absolute decreases in deforestation does not necessarily align with regions where biodiversity is most vulnerable.

Implications and recommendations

Overall, these results demonstrate substantial potential for policy interventions to reduce the EU’s footprint linked to the EUDR commodities. The EUDR can reduce the EU’s exposure to deforestation through de-risking supply chains, but the scenario results indicate that the largest reductions arise via a combination of measures that reshape demand and production, and incentivise sustainable supply chains.

Four priority recommendations emerge from the analysis and associated discussion of the results (see the Discussion section of the main report). First, pursue effective implementation of the EUDR, including strengthening enforcement and compliance. Second, ramp up the non-EUDR measures explored in the scenarios (Table a), particularly those linked to circular economy approaches, including consumption shifts away from commodities that drive deforestation, improvements in sustainable product design and business model innovation, and reductions in demand through material efficiency and waste reduction. Third, build on the scenarios explored here by testing additional policy levers and exploring more targeted packages. This includes deepening analysis for member states with large residual footprints, including interventions tailored to country-level consumption patterns (e.g. targeting the residual footprint linked to beef in Germany, France and Italy), sourcing profiles (e.g. targeting the outsized role of car manufacturing linked to rubber in Germany, or the residual cocoa footprints of the German and Dutch cocoa industries), and implementation constraints. Fourth, invest in knowledge transfer (in both directions) between consuming and producing regions to tackle deforestation, including building capacity, sharing best practices, and supporting implementation of zero-deforestation measures in producer-country landscapes where deforestation pressures are most acute.

Limitations and future work

This assessment is designed as a comparative baseline-versus-scenario exercise rather than a forecast. It translates exploratory policy interventions into modelled changes in consumption, sourcing and production patterns, but it does not capture all potential feedbacks, price effects, or interactions between policy levers. Future work could deepen the analysis through more targeted interventions, expand policy coverage within supply chains and across commodities, conduct sensitivity testing of key assumptions, and include complementary approaches that focus on reducing deforestation at source (including methods that consider the additional costs, resourcing requirements and implementation constraints that this would imply).