ArticleHeliyon2022
Carbon emission quota allocation of high energy consumption industries in undeveloped areas - A case study of Inner Mongolia Autonomous Region.
Article in Heliyon, 2022. 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the approaching of the target year of carbon peak, all world countries have gradually strengthened carbon emission reduction actions. However, most of the undeveloped countries or regions do not belong to the Annex I countries in the Kyoto Protocol, and the development of carbon emission trading mechanisms is relatively slow. Therefore, setting emission quota standards for industries in underdeveloped regions is necessary. Considering the principles of fairness, efficiency, and sustainability, we establish a "multi-objective information entropy allocation model" (i.e., IEMMA method) for underdeveloped areas. Take China's Inner Mongolia Autonomous Region as an example, and the allocation results show that: (1) The "historical emissions", "carbon emission intensity", "cumulative emissions", "energy structure", and "energy intensity" are assigned higher weights. Such industries will carry a higher responsibility for emissions reductions, they should gradually transfer emission quotas to industries with smaller historical emissions to increase enthusiasm for reducing emissions. (2) Compared with the historical emissions allocation scheme, the IEMMA model can increase the emission limits for industries with large historical emissions. For industries with relatively small emissions, their emission quotas can be appropriately relaxed to promote the sustainable development of the industry. (3) Under the allocation scheme of the IEMMA model, the difference in the reduction of carbon emission intensity of different industries is small. Carbon emission intensity becomes a relative emission reduction indicator, which reflects the fairness of allocation while maintaining economic development. (4) The "quota gap" formed by the allocation plan of the IEMMA model is large, which is conducive to promoting the active emission reduction of high-emission enterprises. Larger "allowance gaps" are conducive to increasing the activity of the carbon trading market. In summary, the IEMMA model is conducive to achieving long-term emission reduction goals in underdeveloped regions and is more suitable for the allocation of quotas to high energy-consuming industries.
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.