The change of renewable energy and zero-carbon economy in an anthropogenically warming climate
Bibliographic record
Abstract
Anthropogenetic global warming has led to increasingly significant environmental issues, biodiversity losses, and socioeconomic impacts. There is a rising demand for transition from fossil fuels to renewable energy (RE), reducing carbon emissions, and thus realizing zero-carbon economy. Nevertheless, it remains a challenge to achieve the carbon-free economy and mitigate global warming, without fully understanding the ongoing RE development. The major objectives of this research are to (1) investigate the changes of different RE types compared with fossil fuels in the U.S., U.K., Mexico, Canada, and China; (2) examine the relationships between RE, temperature anomalies, and GDP; and (3) propose potential strategies for zero-carbon economy and climate change. The annual mean energy, temperature, and GDP data in these five selected countries during 1980 to 2021 are collected for analysis, and their relation-ships are addressed through Pearson's correlation analysis, along with significance test. The results suggest an increasing trend of RE and rising RE-fossil fuels ratio during the past four decades. All five countries either showed exponential or linear increasing trends in GDP and RE. The correlation analysis suggests a significantly positive correlation between RE and GDP in both countries. For example, different from the U.S., the synchronized growth in RE and fossil fuels in China leads to a significantly positive correlation between these two. All five countries provide their unique data of renewable development, which can stimulate the research and enable further study. This study will shed light over possible strategic plans for an optimized use of renewable energy, ensuring below 1.5°C temperature rise, and reaching carbon neutrality by 2050.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".