The impacts of decarbonization pathways on Sustainable Development Goals in the European Union

The study addresses how European Union decarbonization strategies interact with progress toward the UN 2030 Agenda for Sustainable Development beyond 2030. While Paris Agreement pledges could keep warming below 2°C if met, mitigation policies have far-reaching implications across SDGs. Existing SDG monitoring largely measures historical gaps without aligning with climate targets or offering long-term projections. Integrated assessment models (IAMs) can assess climate action but have historically focused on energy, climate, and infrastructure, with limited coverage of social and environmental SDG dimensions. Motivated by the need for broader, robust, and region-specific insights, the paper evaluates EU- and country-level SDG outcomes under current policies and alternative net-zero pathways, identifying synergies and trade-offs to inform policy design.

Prior quantitative SDG assessments track progress using diverse indicators, but typically lack alignment with climate mitigation pathways or long-term projections. IAMs have evolved to integrate energy, water, land, and climate science and have supported analyses of mitigation impacts on selected SDG aspects (poverty and inequality; land use; water access and use; health impacts of pollution; biodiversity risks). However, IAMs’ original focus has limited coverage of many social and environmental SDGs; comprehensive global assessments across a broad SDG subset are rare (e.g., Soergel et al.). The strong interconnections among SDGs and limited political attention necessitate widening SDG coverage, enhancing robustness, and providing policy-relevant, region-specific insights.

The study employs a multi-model integrated assessment framework to quantify EU-wide and national SDG outcomes under harmonized scenarios. Model ensemble: GCAM (partial equilibrium, coupled to TM5-FASST for air quality and Hector for climate/ocean pH), GEMINI-E3 and ICES-XPS (computable general equilibrium), NEMESIS (macroeconometric), EU-TIMES (energy system), FORECAST (industry, buildings), and ALADIN (transport). Harmonization: common socioeconomic inputs (GDP, population, labor force from the 2018 Ageing Report), historical emissions, techno-economic parameters (costs, efficiencies, lifetimes) across power, transport, buildings, and industry, and climate policies from recent literature. Outputs are not fed back between models; GDP is endogenous in macro models for mitigation scenarios. Scenario design: - Current Policies baseline reflects implemented mitigation to 2030 (Nikas et al.) and extrapolates a carbon price post-2030 proportional to per-capita GDP growth to 2050; includes COVID-19 effects on GDP and fossil prices. - NZE Benchmark: cost-efficient EU pathway to -55% GHG by 2030 relative to 1990 and climate neutrality by 2050; models freely allocate abatement across sectors (ETS vs ESR) to minimize costs. - NZE Policy Standard: incorporates the Fit for 55 sectoral split (2030: -61% ETS, -40% ESR vs 2005; 2050: -80% ESR and required ETS reductions to reach net zero). Non-EU regions follow current policies in both NZE scenarios. Indicators and SDG coverage: 32 indicators across 15 SDGs (excluding SDG 5 and 16 due to model limitations). Indicators are either direct model outputs (e.g., CO2 intensities, renewable electricity share, PM2.5, sector intensities, water withdrawals/prices, material intensity, residential emissions, ocean pH, land cover) or estimated via the ICES-XPS SDG module using cross-country panel regressions combined with ICES-XPS outputs (e.g., poverty prevalence, undernourishment, healthy life expectancy, education completion, Palma ratio). Normalization and aggregation: Indicators are normalized to 0–100 using policy targets or literature benchmarks; otherwise by bounds from scenario-year distributions. SDG outcomes are averages across all models covering each indicator; country SDG scores average across indicators within each SDG and across SDGs. Regional/national disaggregation uses model-resolved countries or imputations where needed. Model variance is assessed across models per indicator in 2050 for each scenario.

- Under Current Policies, EU+ shows broad SDG improvements by 2050: higher wealth (SDG 8), reduced poverty and between/within-country inequality (SDG 1, 10), higher education levels (SDG 4), increased life expectancy (SDG 3), higher renewable electricity shares (SDG 7), reduced industrial energy use and sectoral carbon intensities (SDG 9, 11, 12, 13), lower PM2.5-related mortality (SDG 3), and reduced ocean acidification (SDG 14). - Notable changes 2020→2050 (Current Policies): renewable electricity share rises from ~30% to ~55% (SDG 7); PM2.5 concentration declines from ~9 to ~4.6 µg/m³ (SDG 11); between-country Gini declines 0.18→0.14 and Palma ratio 1.2→0.9 (SDG 10), mainly via socioeconomic trends and partly mitigation costs falling more on higher-income countries. - Potential trade-offs under Current Policies: modest worsening in food prices and natural resource pressures (freshwater withdrawals, natural/forest cover), and a slight increase in undernourishment from 2.1% (2020) to 2.4% (2050) due to higher agricultural production costs. - NZE scenarios vs Current Policies (2050): • Health co-benefits: healthy life expectancy slightly higher (71.8→72.1 years); mortality due to air pollution lower (Policy Standard: 58 vs Benchmark: 65 years of life lost per 100,000). • Ocean chemistry: ocean pH declines from 8.11 (2020) to 8.04 (2050) with global emissions cuts driving acidification metrics. • Agriculture/air quality: crop yield losses due to ozone fall from 6.4% (2020) to 5.1% (2050) under Current Policies; NZE scenarios do not further reduce these losses due to additional methane from greater bioenergy use. • Macroeconomy: stricter NZE policies reduce GDP by ~0.4–0.9% on average for 2020–2050 (NEMESIS, GEMINI-E3); ICES-XPS projects higher costs. • Social outcomes: relative to Current Policies in 2050, NZE increases poverty prevalence from 0.13% to 0.18% and undernourishment from 2.4% to 3.3% (SDGs 1–2). • Trade with LDCs: imports share from LDCs increases from 7.5% (2020) to 14% (Current Policies) and 16.5% (NZE), potentially benefiting LDC welfare (SDG 17). - NZE Benchmark vs NZE Policy Standard: • Benchmark is more cost-efficient and yields slightly better poverty outcomes, but relies more on natural resources, worsening some air pollution, energy, and emissions intensities. • Policy Standard entails deeper sectoral decarbonization with lower intensities than Benchmark in 2050: industry CO2 intensity 5 vs 9 g CO2/MJ; transport 33 vs 39 g CO2/MJ; residential emissions 100 vs 140 kg CO2 per capita; and lower air-pollution mortality (58 vs 65 YLL per 100,000). - Model variance: largest across models in water prices, renewable shares, per-capita GDP growth, and transport CO2 intensities, driven by structural/technology representation (e.g., GCAM’s higher bioenergy use raising water prices; limited transport detail in GCAM/ICES-XPS/GEMINI-E3 vs detailed ALADIN/EU-TIMES; biomass unavailable in ICES-XPS). - Country-level patterns: mitigation policies reduce SDG performance gaps by 2050. Laggards in 2020 (Hungary, Spain, Poland) see the largest improvements due to air pollution co-benefits, better energy and CO2 intensities, higher renewables, and reduced within-country inequality. High performers in 2020 (France, Finland, Sweden) progress more slowly. Policy Standard tends to benefit lower-performing countries more; Benchmark slightly better for high initial performers.

Mitigation pathways in the EU+ generate substantial environmental co-benefits alongside decarbonization—improving health, air quality, energy system sustainability, and some water and agricultural metrics—while revealing socioeconomic trade-offs under stringent policies. Without corrective measures, NZE pathways can slightly worsen SDG 8 metrics (GDP-related) and increase poverty, undernourishment, and food prices due to mitigation costs and land competition. These trade-offs should not slow climate action; rather, policy packages should be designed to reduce adverse social impacts, such as recycling carbon tax revenues to compensate vulnerable households and supporting low-carbon R&D to lower abatement costs. Countries currently lagging in SDG performance stand to gain most from ambitious mitigation, indicating decarbonization can help bridge intra-EU SDG gaps. Integrating broader global mitigation and climate impact assessments would likely shift the cost-benefit balance in favor of ambitious action by quantifying avoided damages, but such analysis is beyond the present scope.

This first multi-model assessment of EU climate neutrality pathways vis-à-vis SDG progress at EU and Member State levels demonstrates that: (i) current policies already improve many SDG-aligned outcomes; (ii) ambitious net-zero policies further enhance environmental and health indicators and especially benefit current SDG laggards; and (iii) socioeconomic trade-offs emerge for poverty, hunger, and economic growth without corrective policy design. The findings underscore the need to pair decarbonization with redistributive and innovation-support policies to ensure a fair, SDG-consistent transition. Future research should integrate climate impact damages with mitigation benefits, expand SDG coverage, enhance model robustness (e.g., sensitivity/robustness analyses, portfolio approaches), refine sectoral detail, and explore broader SDG-relevant policy scenarios to strengthen policy relevance and reliability.

- Climate change impact damages are not quantified; only mitigation costs are modeled, likely underestimating NZE benefits and overestimating Current Policies relative to low-ambition, high-damage futures. - Limited SDG coverage due to model capabilities (e.g., SDGs 5 and 16 excluded; within-country social indicators partly proxied). - Sectoral and technology representation varies across models (e.g., limited transport detail in some IAMs; biomass absent in ICES-XPS), contributing to variance. - Government expenditure projections are not linked to carbon-tax revenue recycling; education/R&D indicators change little across scenarios. - No feedback of model outputs across the ensemble (e.g., GCAM food prices not fed to ICES-XPS undernourishment), potentially underestimating some impacts. - Scenarios emphasize EU ambition; non-EU regions assumed to follow current policies, affecting global feedbacks (e.g., ocean pH). - National disaggregation is incomplete for some indicators; some country results rely on imputations from regional aggregations. - Indicator normalization uses simulated bounds/benchmarks; absolute distances to official SDG targets are not always quantifiable.