Regional surface temperature changes in China caused by reduced air pollution and halogenated greenhouse gases
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
China's vast territory across a large latitude makes it an ideal country to investigate the mechanisms causing regional climate changes. Here, we showed that the temporal patterns in regional surface temperature are very different between low- and high latitude regions and between lightly and severely polluted regions, and that a reversal in surface temperature occurs earlier at higher-latitude regions. The latter is affected by recent drastic reductions in air pollution, which give rise to positive net radiative forcings that are the primary cause for China's regional temperature rises in the last decade. These regional climate patterns are in good agreement with both the cosmic-ray driven electron-induced reaction (CRE) theory of ozone depletion and the physics model of warming caused by halogen-containing greenhouse gases (halo-GHGs, mainly chlorofluorocarbons (CFCs)). Using the IPCC-given globally averaged radiative forcings of aerosols and ozone, our calculated results by the CFC-warming physics model showed good agreement with the observed regional surface temperature changes since 1990, giving correlation coefficients of 0.70–0.96. In lightly polluted regions, such as northeast and northwest China (Heilongjiang, Xinjiang and Inner Mongolia), Hainan and Guangdong, our calculations reproduced close observations, while underestimating temperatures in highly polluted regions such as Beijing (Hebei), Fujian, and Jiangsu. This discrepancy is explained by larger reductions in post-2013 air pollution, causing greater positive radiative forcings. Our results revealed the mechanisms for regional and global climate change.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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