The European Green Deal (EGD), launched in 2019, is a comprehensive plan to transform the European Union (EU) into a more sustainable and climate-resilient society while fostering economic growth and social equity. It serves as an environmental, social, and economic blueprint and encompasses various aspects such as climate action, energy, agriculture, industry, infrastructure, environment and biodiversity, transportation, finance and development, as well as research and innovation.

The SDGs are interconnected and designed to address the most urgent and pressing global challenges regarding poverty, health and education, inequalities, economic growth, and climate change by simultaneously preserving the ecosystem services derived from our oceans and forests. The 17 SDGs are a holistic framework that encompasses the environmental, social, and economic dimensions of sustainability and provide a comprehensive roadmap for global action to achieve a sustainable future for all, recognising the interrelated nature of environmental sustainability, social inclusion, and economic development. Each goal is supported by specific targets and indicators that monitor progress and ensure accountability.

Methodological Approach

The primary objective of our work was to answer the question of the previous section and bridge the literature gap regarding the integration of SDGs into the EGD framework by exploiting the abilities provided by Machine Learning (ML). Our analysis began with the selection of 74 policy documents published from 2019 to 2023, directly derived from the EGD. We focus on official documents released by the European Commission, including strategies, communications, and action plans that explicitly contribute to the objectives outlined in the EGD. This selection provided a comprehensive dataset of textual material for analysis, covering the broad scope of EGD's ambitions across various sectors and themes.

The core of our methodological approach was the utilization of ML text-mining techniques for the extraction of meaningful information from large volumes of text, making it possible to uncover patterns, trends, and insights that are difficult to discern through manual analysis alone. Specifically, we employed natural language processing (NLP), a subset of ML that enables computers to understand, interpret, and generate human language. We used a pre-trained ML model known as Bidirectional Encoder Representations from Transformers (BERT) and fine-tuned it to our specific task of detecting and quantifying the presence of SDG-related content within the EGD policy documents. BERT is particularly suitable for understanding the context of words in text, making it highly effective for complex text-analysis tasks, such as ours.

Key Findings and Outcomes - How Sustainable is the European Policy Framework?

Our approach uncovered the interaction between these two frameworks, examining how EGD aligns with and supports the achievement of SDGs. The research findings highlight a strong correlation between the Circular Economy Plan and SDG12 (Responsible Consumption and Production), demonstrating a high alignment, which mirrors the plan's emphasis on sustainability in resource management and waste reduction. Similarly, the EU Energy Integration Strategy and the EU Hydrogen Strategy show a notable alignment with SDG12 and SDG13 (Climate Action), underscoring the initiatives' focus on energy system integration and climate change mitigation. The Sustainable Growth Strategy 2021 aligns significantly with SDG17 (Partnerships for the Goals), suggesting a focus on collaborative efforts for sustainable growth. These relationships, quantified through similarity scores, validate the anticipated connections between specific EGD policies and relevant SDGs.

Over time (Figure 1), the analysis reveals that SDG7 (Affordable and Clean Energy), SDG12, SDG13, and SDG17 are the most frequently aligned with EGD policies, reflecting the EU's prioritization of climate neutrality, clean energy, and climate action.

The importance of SDG17 indicates a recognition of the essential role of partnerships in achieving the broad goals of the EGD. The analysis also shows that while some SDGs, such as those focused on industry, sustainable communities, and biodiversity, receive significant attention, others related to social welfare and environmental health have moderate representation. The least represented SDGs in EGD initiatives—concerning poverty, education, gender equality, and inequalities—highlight the challenges of integrating complex social factors within primarily environmental policy frameworks. Over the years, the policy focus within the EGD has evolved, indicating a diversification and increased emphasis on various SDGs beyond the initial focus on clean energy and climate action, with recent years showing a rising attention to previously overlooked SDGs, suggesting shifts in policy priorities and the necessity for strategic adjustments to maintain progress toward a sustainable future.

Conclusions and future directions

To sum up, our research is particularly valuable for policymakers, as a practical tool for evaluating the sustainability content of upcoming policies, laws, regulations, or other legislative documents. The utilization of machine learning techniques has revealed complex interactions across various SDGs, underscoring the multifaceted approach required for holistic sustainable development. We found the EGD to be a robust strategy for a climate-neutral Europe by 2050. However, our analysis highlighted some underrepresentation of social issues, such as inequalities, poverty, health, and education, in EGD policies when compared to environmental targets such as clean energy and climate action. This discrepancy suggests that while the EGD is ambitious in its environmental goals, it may fall short of addressing the full spectrum of sustainability as defined by the SDGs.

By utilizing our research, policymakers can identify areas within legislation that may require additional emphasis on specific SDGs, depending on the desired outcomes, and prioritise efforts to address the overlooked social dimensions of sustainability. This proactive approach ensures that new policies contribute effectively to a balanced achievement of all SDGs, particularly by addressing the most “ignored” social dimensions of sustainability. Furthermore, our findings underscore the importance of continually revising and adapting policy priorities in response to new challenges, to sustain momentum towards achieving sustainability goals.

Our research offers valuable insights also for other regions and sub-European levels aspiring to develop their own sustainability frameworks. By examining the EGD's alignment with the SDGs, our findings can serve as a valuable benchmark for territories outside of the European Union or within its borders but at a more localized level, to assess and refine their own "Green Deals." This is particularly relevant for regions looking to craft policies that prioritize sustainability while ensuring their actions are in harmony with global sustainability goals. We mention for example, the “Green Agenda for the Western Balkans” which mirrors the EGD's ambition for achieving climate neutrality and environmental sustainability by 2050.

Future research should investigate the implications of our conclusions for the European Union's policy and funding strategies. This includes identifying areas that require greater investment within the EGD framework and examining how these areas align with the SDGs. Additionally, broadening the scope of the study to encompass other significant EU initiatives could provide a more comprehensive understanding of Europe's progress towards sustainability.