Urban Content of NDCs:Local Climate Action Explored Through in-depth Country Analyses. 2024 Report
Bibliographic record
Abstract
Cities are responsible for approximately 67 per cent of global primary energy consumption and 70 per cent of global greenhouse gas emissions. This significant contribution makes cities essential partners in achieving the goals of the Paris Agreement.<br/><br/>Nationally Determined Contributions (also known as NDCs) are the cornerstone of the Paris Agreement and are the main policy instruments used to indicate national contributions toward global efforts for climate change mitigation and adaptation. It’s essential for countries’ NDCs to reflect urban climate solutions. This report – jointly prepared by UNDP, UN-Habitat and the University of Southern Denmark with support from C40 Cities – analyzes urban content and urban climate strategies in the 194 NDCs submitted by as of 27 June 2023.<br/><br/>This report provides analysis and guidance to policymakers and practitioners working on climate, development and NDCs to: (i) facilitate better understanding of the urban focus in NDCs, (ii) highlight climate challenges and opportunities in cities, (iii) support countries to place cities at the center of their climate ambition, and (iv) provide a unique set of climate data to inform policymaking.<br/><br/>Key findings include:<br/><br/>1. 66 percent of the 194 NDCs contain either a moderate or strong level of urban content, indicating space to place greater emphasis on urban priorities and urban solutions.<br/><br/>2. A large number of NDCs (160) highlight the need for finance to facilitate NDC implementation at the national level, while only 26 included specific requests for finance at the urban level.<br/><br/>3. 47 percent of the NDCs emphasize both adaptation and mitigation in an urban context with the most references to energy, transport and mobility and waste for mitigation, and to infrastructure and water for adaptation.<br/><br/>4. Emphasis on climate hazards is prevalent throughout 89 percent of NDCs; however, only 40 percent of NDCs mentioned climate hazards the urban level despite the climate vulnerability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".