Evidence map›Paper›PMID 36841209›Full record

ArticleMarine pollution bulletin2023

Impacts of the COVID-19 epidemic on carbon emissions from international shipping.

Lang Xu, Zhihui Yang, Jihong Chen, Zeyuan Zou

Open access · greenAbstract read
In one paragraph

Article in Marine pollution bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
7.2field-weighted citation impact, top 2% of its field
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

1 citing paper in PubMed, 59 citations in OpenAlex.

  1. Article
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

4 authors at 2 institutions in 1 country.

Lang XuCollege of Transport & Communications, Shanghai Maritime University, Shanghai, China. Electronic address: xulang@shmtu.edu.cn.
Zhihui YangCollege of Transport & Communications, Shanghai Maritime University, Shanghai, China.
Jihong ChenCollege of Management, Shenzhen University, Shenzhen, China. Electronic address: cxjh2004@163.com.
Zeyuan ZouCollege of Transport & Communications, Shanghai Maritime University, Shanghai, China.
Shanghai Maritime University · CNShenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 epidemic made the most countries to take strict lockdown measures, what has seriously caused an unprecedented impact in the shipping industries, whereas these measures have also played a significant impact to control carbon emissions from international shipping. Here, we try to use the threshold generalized autoregressive conditional heteroscedasticity and the exponential generalized autoregressive heteroscedasticity to investigate whether the fluctuations of the control variable on carbon emissions from international shipping are asymmetric or not. On this basis, the GARCH-MIDAS model is introduced to discuss whether the newly confirmed cases are independent of control variables and have an impact on the fluctuation of carbon emissions. From the results, we find that the information contained in the newly confirmed cases cannot be covered when adding the other control variables. In addition, the newly confirmed cases have a negative impact on the volatility of carbon emissions, while the other control variables significantly increase carbon emissions. This study provides a quantitative research method for the analysis of the volatility and impact factors on international shipping carbon emissions, which helps to formulate more reasonable emission reduction measures and promote the low-carbon transformations of the global shipping industry.

Indexed as

CarbonCOVID-19Communicable Disease ControlHumansCarbonCarbon emissionCOVID-19 epidemicGARCH modelInternational shipping

Identifiers

PMID36841209
PMCPMC9928736
OpenAlexW4320922054

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.