Evidence map›Paper›PMID 36081425›Full record

ArticleJournal of environmental and public health2022

Analysis on the Nonlinear Impact of Financial Risks on CO

Xuan Huang, Meihua Chen

Abstract read
In one paragraph

Article in Journal of environmental and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Xuan HuangSchool of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, China.
Meihua ChenSchool of Public Administration, Nanchang University, Nanchang, Jiangxi 330031, China.ORCID 0000-0002-9905-058X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For the purpose of coping with or eliminating the influence of carbon dioxide emissions effectively, it is crucial to apply the green investment models to carry out a qualitative analysis of carbon dioxide emission evolution. The effect of financial risks on the implementation of the carbon dioxide emission limit is essential for the distribution of resources, and it is necessary to summarize the patterns and make innovations in the process of limiting the emissions of carbon dioxide effectively. In the case of fully complying with the principles of low-carbon economic development and related policy protection, the appropriate model for low-carbon economic development is identified. In this article, the multivariate primary nonlinear model is applied to the analysis of the nonlinear influence of financial risks on carbon dioxide emissions to cope with the problem of financial risks on carbon dioxide emissions at present. In this method, a multivariate primary nonlinear model is established based on the detailed analysis of the financial development features, and the parameters are optimized mainly from various aspects such as the structure of the model, the features of data, and the dynamic changes of the model so as to obtain the optimal values for the parameters of the constructed multivariate primary nonlinear model. The results of the practical case analysis indicate that the influence of financial risks on the limits of domestic carbon dioxide emissions is differentiated in accordance with the results and related categories. Only in this way can the regional division of carbon emission factors be properly classified. The relationship between economic growth and carbon emission increase and changes indicates that effective strategies for carbon emission reduction should be adopted. The established panel data model is used to carry out an in-depth analysis of the influence of carbon dioxide limitations in Asian countries.

Indexed as

Carbon DioxideSustainable DevelopmentAsiaEconomic DevelopmentCarbon Dioxide

Identifiers

PMID36081425
PMCPMC9448573

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Registered trials

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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.