ArticleF1000Research2025
Research on statistical measure under double carbon target - Self-moving regression model of grey prediction based on entropy weight method.
Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: At the 2020 UN General Assembly, China pledged to peak carbon emissions before 2030 and achieve carbon neutrality by 2060. However, the traditional social development model has led to increasing carbon emissions annually, highlighting the need to resolve the contradiction between development and carbon reduction. This study examines the relationship between carbon emissions, economy, population, and energy consumption in a specific region to support carbon peak and neutrality goals. Methods: A comprehensive indicator system was established, encompassing economic, population, energy consumption, and carbon emissions indicators. The study analyzed these factors during the 12th and 13th Five Year Plans, comparing total carbon emissions in 2010 and across the plans, and assessing trends. It also comprehensively analyzed the relationships and mutual influences among these factors. The study identified the main challenges in achieving carbon peak and neutrality. Using the Kaya model and various factor models, it calculated carbon peak times for three scenarios: baseline (2022), natural (2036), and ambitious (2021). These findings provide a basis for dual carbon path planning. Result: The research results indicate that carbon emissions are closely related to the economy, population, and energy consumption. The prediction shows that the future trend of carbon emissions is controllable. Suggestions for dual carbon path planning are proposed to provide empirical basis for policy formulation. Under the baseline scenario, the peak carbon emissions are expected to occur around 2022; Under natural circumstances, the peak carbon emissions will be postponed to 2036; In the ambitious scenario, the carbon peak time can be advanced to 2021. Conclusion: The research results are crucial for achieving carbon reduction targets and sustainable development and can be used to formulate targeted policies to promote regional development and support China's carbon neutrality commitments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.