Synergizing Circular Economy and Artificial Intelligence for Industrial Decarbonization: A 24‐Year Analysis of European Sustainability

ABSTRACT Circular Economy (CEI) and Artificial Intelligence (AII) are considered as a major contributor to the decarbonization of industry and environmental sustainability. With modes of dealing with climate neutrality, it is important to understand overall impact of economy. This paper will highlight CEIs, AII and their interaction in lowering carbon intensity in 27 European union countries in the year 2000 through 2023. Time Specific Heterogeneous Factor Analysis (TSHFA), is used in building composite indices of CEI and AII to reflect the dynamism over time. The second‐generation econometric models, namely, Panel Quantile Regression (PQR), Pooled Mean Group (PMG) and Common Correlated Effects (CCE) are used in the empirical analysis to explain the cross‐sectional dependence and heterogeneity. The findings indicate that CEI, AII, and their synergy among themselves are highly effective, though positively, on decarbonization, specially to high‐emission economies. Trade openness, on the other hand, is counterproductive to decarbonization, research and development show mixed results and economic growth is of minimal effect. Disaggregated indicators of robustness checks ensure the credibility of results. These findings highlight a severe necessity of interconnecting circular economy practices and digital innovation and harmonizing trade and research policies and sustainability goals. The paper can offer important policy recommendations to the progress in EU towards becoming climate neutral and meeting a wide set of needs of its member countries.

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Publication Details

Journal
Sustainable Development
Published
2026-01-08
DOI
https://doi.org/10.1002/sd.70635
Citations
1
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
99.81
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article

Synergizing Circular Economy and Artificial Intelligence for Industrial Decarbonization: A 24‐Year Analysis of European Sustainability

Ethan Carter, Chen Lin
1 citations
Sustainable Development
Economic and Technological Innovation
99.81
article

Synergizing Circular Economy and Artificial Intelligence for Industrial Decarbonization: A 24‐Year Analysis of European Sustainability

Ethan Carter, Chen Lin
article en
1 citations

Abstract

ABSTRACT Circular Economy (CEI) and Artificial Intelligence (AII) are considered as a major contributor to the decarbonization of industry and environmental sustainability. With modes of dealing with climate neutrality, it is important to understand overall impact of economy. This paper will highlight CEIs, AII and their interaction in lowering carbon intensity in 27 European union countries in the year 2000 through 2023. Time Specific Heterogeneous Factor Analysis (TSHFA), is used in building composite indices of CEI and AII to reflect the dynamism over time. The second‐generation econometric models, namely, Panel Quantile Regression (PQR), Pooled Mean Group (PMG) and Common Correlated Effects (CCE) are used in the empirical analysis to explain the cross‐sectional dependence and heterogeneity. The findings indicate that CEI, AII, and their synergy among themselves are highly effective, though positively, on decarbonization, specially to high‐emission economies. Trade openness, on the other hand, is counterproductive to decarbonization, research and development show mixed results and economic growth is of minimal effect. Disaggregated indicators of robustness checks ensure the credibility of results. These findings highlight a severe necessity of interconnecting circular economy practices and digital innovation and harmonizing trade and research policies and sustainability goals. The paper can offer important policy recommendations to the progress in EU towards becoming climate neutral and meeting a wide set of needs of its member countries.

Sustainable Development
University of Stirling (GB), Fuzhou University (CN)
Openalex Percentile: Top 1%
Economic and Technological Innovation
99.81
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