Comparing the ambition of EU companies with science-based targets to EU regulation-imposed reductions

The study investigates whether the climate commitments of EU companies with Science Based Targets initiative (SBTi) approvals as of 2020 align with or complement EU climate policies then in force, which aimed for a 40% GHG reduction by 2030 relative to 1990. It addresses uncertainty around the impact and transparency of voluntary corporate targets and their interaction with national instruments—particularly the EU Emissions Trading System (ETS) and Effort Sharing Regulation (ESR). Focusing on company scope 1 and 2 emissions, the research asks: What is the potential impact by 2030 on GHG emissions resulting from climate actions taken in 2020 by EU SBTi-approved companies in the context of EU policies? The study emphasizes sector- and instrument-specific interactions (including the ETS waterbed effect) to accurately assess additionality beyond current policies.

The paper situates its inquiry within literature assessing non-state and subnational actors’ mitigation potential and interactions with national policies. Prior studies (e.g., Kuramochi et al., Lui et al.) suggest additional reductions when non-state targets exceed national policy trajectories, but often at economy-wide levels without detailed treatment of policy-instrument interactions. Research highlights the need for improved transparency and MRV for corporate targets and notes potential synergies between governmental regulation and voluntary actions (the ambition loop). Equity and cost-effectiveness debates around 2 °C-consistent pathways are noted, with cost-optimal EU pathways indicating ~45% reductions by 2030 relative to 1990, while equity-based allocations can suggest differing national effort levels. The paper identifies a gap: limited analysis of how corporate targets interact with specific EU policy instruments (ETS vs ESR) at sectoral and geographic levels.

Data and scope: The analysis uses datasets released in 2020, with 2019 as the latest historical year. EU and Member State historical emissions and projections for ETS and ESR were obtained from the European Environment Agency (EEA). Company-level emissions and targets were sourced from CDP’s 2020 questionnaire, and ETS participation, allowances, and verified emissions from the European Union Transaction Log (EUTL) via EUETS.INFO. The study focuses on scope 1 and 2 emissions of SBTi-approved companies with EU branches (EU-27, Norway, Iceland). Scope 3 and LULUCF are excluded.

Company selection and matching: From 335 companies with SBTi-approved targets (670 MtCO2eq in 2019), 200 companies with 1,063 EU branches (243 MtCO2eq in 2019) were included. Companies with ETS obligations were identified by fuzzy name matching between CDP and EUTL datasets (Nijhuis algorithm). ETS account holders and installations linked to these companies were mapped (217 account holders, 443 installations).

Policy-instrument coverage classification: Emissions were allocated to ETS vs ESR based on scope and activity: scope 2 always falls under ETS (power sector emissions); scope 1 from heavy industry and aviation activities covered by ETS; other scope 1 activities fall under ESR. Companies are categorized as with ETS installations (heavy industry/aviation) or without ETS installations (light industry). For companies with ETS installations, scope 1 emissions up to verified ETS levels are allocated to ETS, with any excess scope 1 allocated to ESR; all scope 2 are ETS.

Additionality concept: Additional impact is defined as the portion of SBTi-related reductions exceeding reductions implied by EU policy projections, assuming company actions do not displace other reductions in ESR. In ETS, due to the waterbed effect, additional reductions are zero unless flanking measures remove allowances from the market.

Scenario design: Three normative scenarios project 2019–2030 emissions for SBTi companies:

• PS (EU 2020 policies scenario): Uses EEA With Existing Measures (WEM) projections for ETS and ESR, starting from 2019 inventories. Average annual declines 2019–2030: ETS ~0.9%, ESR ~0.8%, both missing stated caps/targets.
• PS+SBTi: Builds on PS, adds full implementation of SBTi targets. For targets with years before 2030, emissions beyond target year follow PS ETS/ESR trends. For targets beyond 2030, linear interpolation from 2019 to target year. Additional reductions under ETS set to zero (waterbed effect). ESR reductions counted as additional, assuming no displacement elsewhere.
• PS+SBTi+ (flanking measures): Same as PS+SBTi but assumes flanking measures (e.g., a mutual fund that buys and cancels ETS allowances) to materialize additional ETS reductions by effectively tightening the cap.

Target handling: Two targets per company were selected prioritizing scope 1+2, then scope 1, then scope 2, choosing those closest to 2030. Targets exclude offsets per CDP guidance (acknowledging possible inconsistencies). Emissions after early target years evolve with ETS/ESR trends.

Assumptions and limitations in modeling: Uniform application of ETS/ESR trends from WEM at company level; full target achievement by companies; no cross-sectoral or cross-geography leakage/displacement in ESR sectors; flanking measures perfectly cancel and permanently remove allowances in PS+SBTi+.

• Coverage and baseline (2019): 200 SBTi companies with 1,063 EU branches accounted for 243 MtCO2eq (6.4% of total EU emissions excl. LULUCF). Of these, 58 companies owned ETS installations (no aircraft operators in sample), linked to 217 ETS account holders and 443 installations.
• Emissions split (2019):
  • Companies without ETS installations: 64 MtCO2eq total (scope 1 ESR: 52; scope 2 ETS: 12).
  • Companies with ETS installations: 179 MtCO2eq total (ETS: 86 [72 scope 1 + 14 scope 2]; ESR: 93).
  • Overall coverage: 40% of SBTi emissions under ETS; 60% under ESR.
• Target characteristics: 53% of targets had target years between 2016–2030; 31% between 2020–2025; most set in 2019; average time since inception 3.3 years.
• Scenario results (2030):
  • PS (reference, EU 2020 policies): 221 MtCO2eq total (198 ESR + 23 ETS from scope splits shown in Table 2).
  • PS+SBTi (no ETS materialization): 212 MtCO2eq; additional reduction vs PS: 8 MtCO2eq (3.8% vs PS), equivalent to 12.6% below 2019.
  • PS+SBTi+ (with flanking measures): 189 MtCO2eq; additional reduction vs PS: 31 MtCO2eq (14.2% vs PS), equivalent to 22.1% below 2019.
• Contributions by company type (additional vs PS, by 2030):
  • Companies without ETS installations: +12 MtCO2eq (increase vs PS).
  • Companies with ETS installations: −21 to −43 MtCO2eq depending on flanking measures (−1 from ETS in PS+SBTi due to rounding; −21 with ESR only; −21 ETS and −21 ESR in PS+SBTi+; see Table 2 breakdown).
• Ambition relative to policy goals: Total SBTi company targets in 2020 were at best aligned with, or only modestly more ambitious than, a 2 °C-consistent EU pathway (40–45% reduction by 2030 vs 1990). Companies regulated by ETS exhibited higher estimated ambition than those solely under ESR.
• Sensitivity to reference scenario: Using alternative references (EEA WAM or caps/targets-based trajectories) would further emphasize that additional reductions require ETS flanking measures; absent such measures, company targets could correspond to higher emissions vs those references.

The findings indicate that EU companies with SBTi-approved targets (as of 2020) provide at most modest additional reductions beyond EU policies by 2030. The additionality strongly depends on policy-instrument interactions: under ETS, voluntary overcompliance does not reduce total emissions unless allowances are cancelled (waterbed effect), whereas in ESR sectors, additional corporate actions can yield extra reductions provided they do not displace reductions elsewhere. Companies with ETS installations demonstrate higher projected ambition than those without, suggesting that strong regulatory frameworks may foster more ambitious corporate targets and potentially contribute to an ambition loop between policy and business action. Relative to EU’s 40% by 2030 (cost-effective 2 °C pathway), aggregate SBTi targets are broadly aligned to modestly more ambitious, but not transformative. The choice of reference matters: using WEM (implemented policies) highlights the potential for voluntary action to complement current efforts, while stricter reference pathways make clear that flanking measures are essential for materializing ETS-related voluntary cuts. Post-2020 policy updates (Fit for 55, expanded ETS) and evolving corporate net-zero standards underscore the need for reassessment under updated frameworks and improved corporate disclosure and MRV.

This study integrates company-level SBTi targets with EU policy-instrument contexts (ETS and ESR) to quantify potential additional reductions by 2030. It shows that, absent flanking measures to cancel ETS allowances, voluntary corporate ambition in ETS sectors will not translate into additional system-wide reductions; with such measures, additional reductions of ~31 MtCO2eq (14.2% vs PS by 2030) are possible. Companies with ETS installations exhibit higher ambition than those solely under ESR. The work provides a policy-relevant template: where voluntary actions overlap with cap-and-trade systems, flanking measures are required to ensure additionality; for conservative estimates, assume zero additionality under ETS without such measures. Future research should: reassess under updated EU policies (Fit for 55, ETS expansion); improve sectoral granularity (especially transport/buildings under ESR); enhance transparency and MRV of corporate targets and progress; and explore governance mechanisms (e.g., allowance cancellation funds) to secure real additional reductions. Extending this approach to other regions and to cities could further clarify interactions between voluntary action and regulatory frameworks.

• Data scope and timing: Historical data up to 2019; forward-looking assessment does not evaluate ex-post achievements beyond inventory baselines; high-performing historical reductions are embedded in starting inventories and not separately credited.
• Sectoral granularity: Limited sector breakdown in CDP data constrains differentiation within ESR (notably transport and buildings) and within ETS (power vs energy-intensive industry with free allocations).
• Target implementation details: Insufficient information on how companies implement targets across countries and scopes; assumption that scope 1+2 targets apply to EU branches.
• Reporting consistency and offsets: Uncertainty regarding consistent adherence to CDP reporting guidance (e.g., exclusion of offsets) may affect estimated reductions.
• Modeling assumptions: Uniform application of EU WEM ETS/ESR trends at company level; full achievement of SBTi targets; no displacement of ESR reductions; perfect and permanent cancellation of ETS allowances in flanking scenario; name-matching uncertainties between CDP and EUTL datasets.