Artificial Intelligence (AI)-driven approach to climate action and sustainable development
Abstract Countries have pledged commitment to the 2030 Sustainable Development Goal (SDGs) and the Paris Agreement to combat climate change. To maximize synergies between SDGs and climate actions (CAs), we evaluate the alignment of national commitment to SDGs and emissions reduction targets by compa...
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| Format: | Article |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-53956-1 |
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| _version_ | 1832571517029842944 |
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| author | Haein Cho Emmanuel Ackom |
| author_facet | Haein Cho Emmanuel Ackom |
| author_sort | Haein Cho |
| collection | DOAJ |
| description | Abstract Countries have pledged commitment to the 2030 Sustainable Development Goal (SDGs) and the Paris Agreement to combat climate change. To maximize synergies between SDGs and climate actions (CAs), we evaluate the alignment of national commitment to SDGs and emissions reduction targets by comparing action plans embodied in Voluntary National Review (VNR) reports and the Nationally Determined Contributions (NDCs) across 67 countries. An Artificial Intelligence (AI)-based approach is proposed in this study to explore the interconnectedness by applying machine learning classifier and natural language processing. Middle- and low-income countries with high emissions tend to have low NDC targets and contain similar information in VNR reports. High-income countries show less alignment between their NDCs and VNRs. The economic status of countries is found to be connected to their climate actions and SDGs alignment. Here, we demonstrate utility and promise in using AI techniques to unravel interactions between CA and SDG. |
| format | Article |
| id | doaj-art-5c9d2e15fa0b45509abb1842318d81d5 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-5c9d2e15fa0b45509abb1842318d81d52025-02-02T12:32:44ZengNature PortfolioNature Communications2041-17232025-01-0116111210.1038/s41467-024-53956-1Artificial Intelligence (AI)-driven approach to climate action and sustainable developmentHaein Cho0Emmanuel Ackom1National Assembly Futures InstituteDepartment of Geosciences, College of Arts, Sciences and Engineering, University of North AlabamaAbstract Countries have pledged commitment to the 2030 Sustainable Development Goal (SDGs) and the Paris Agreement to combat climate change. To maximize synergies between SDGs and climate actions (CAs), we evaluate the alignment of national commitment to SDGs and emissions reduction targets by comparing action plans embodied in Voluntary National Review (VNR) reports and the Nationally Determined Contributions (NDCs) across 67 countries. An Artificial Intelligence (AI)-based approach is proposed in this study to explore the interconnectedness by applying machine learning classifier and natural language processing. Middle- and low-income countries with high emissions tend to have low NDC targets and contain similar information in VNR reports. High-income countries show less alignment between their NDCs and VNRs. The economic status of countries is found to be connected to their climate actions and SDGs alignment. Here, we demonstrate utility and promise in using AI techniques to unravel interactions between CA and SDG.https://doi.org/10.1038/s41467-024-53956-1 |
| spellingShingle | Haein Cho Emmanuel Ackom Artificial Intelligence (AI)-driven approach to climate action and sustainable development Nature Communications |
| title | Artificial Intelligence (AI)-driven approach to climate action and sustainable development |
| title_full | Artificial Intelligence (AI)-driven approach to climate action and sustainable development |
| title_fullStr | Artificial Intelligence (AI)-driven approach to climate action and sustainable development |
| title_full_unstemmed | Artificial Intelligence (AI)-driven approach to climate action and sustainable development |
| title_short | Artificial Intelligence (AI)-driven approach to climate action and sustainable development |
| title_sort | artificial intelligence ai driven approach to climate action and sustainable development |
| url | https://doi.org/10.1038/s41467-024-53956-1 |
| work_keys_str_mv | AT haeincho artificialintelligenceaidrivenapproachtoclimateactionandsustainabledevelopment AT emmanuelackom artificialintelligenceaidrivenapproachtoclimateactionandsustainabledevelopment |