State-of-play in international carbon markets 2025
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
- This policy brief gives an overview of existing carbon pricing mechanisms and outlines the trends of mandatory and voluntary carbon markets (VCMs) in 2023. It also reviews the integration of carbon markets. - As of April 2023, 73 carbon taxes and emissions trading systems (ETSs) were in operation, covering approximately 23% of global GHG emissions. - 28 of these compliance carbon pricing instruments were ETSs at regional, national or subnational levels and covered about 17% of global GHG emissions. The number of ETSs in force will likely rise in the coming years as 8 systems are currently under development and 11 are under consideration. - After growing rapidly in 2020 and 2021, the issuance of offset credits declined slightly in 2022. Several factors contributed to this decline, including the challenging macroeconomic conditions, public skepticism about the quality of credits, and the absence of commonly accepted guidance on best-practice for the use of credits to support net-zero claims. - Linked ETSs include: the EU and Swiss ETSs since 2020, the California and Québec Cap-and-Trade Programs since 2014, an evolving set of US states participating in the Regional Greenhouse Gas Initiative (RGGI) since 2009, and the Tokyo Cap-and-Trade Program and the Saitama ETS since 2011. - Progress on the integration of compliance carbon markets via linking has not been rapid. Each system is tailored to its domestic circumstances which makes the required level of alignment for successful links difficult to achieve. Moreover, the potential increase in regulatory uncertainty and the expected negative impacts on the robustness of each system act as strong barriers to linking. - Connecting ETSs with VCMs should be treated with great caution due to concerns about credit quality as well as monitoring, reporting and verification issues connected with offsets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it