Evidence map›Paper›PMID 35975111›Full record

ArticleJournal of cleaner production2022

The negative impact of the COVID-19 on renewable energy growth in developing countries: Underestimated.

Shuyu Li, Qiang Wang, Xue-Ting Jiang, Rongrong Li

Open access · greenAbstract read
In one paragraph

Article in Journal of cleaner production, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

4 citing papers in PubMed, 34 citations in OpenAlex.

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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 2 countries.

Shuyu LiSchool of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.
Qiang WangSchool of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.
Xue-Ting JiangCrawford School of Public Policy, The Australian National University, Canberra, ACT, 2601, Australia.
Rongrong LiSchool of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.
China University of Petroleum, East China · CNAustralian National University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to the United Nations Environment Programme, the COVID-19 pandemic has created challenges for the economy and the energy sector, as well as uncertainty for the renewable energy industry. However, the impact on renewable energy during the pandemic has not been consistently determined. Instead of relying on data from year-to-year comparisons, this study redesigned the analytical framework for assessing the impact of a pandemic on renewable energy. First, this research designed an "initial prediction-parameter training-error correction-assignment combination" forecasting approach to simulate renewable energy consumption in a "no pandemic" scenario. Second, this study calculates the difference between the "pandemic" and "no pandemic" scenarios for renewable energy consumption. This difference represents the change in renewable energy due to the COVID-19 pandemic. Various techniques such as nonlinear grey, artificial neural network and IOWGA operator were incorporated. The MAPEs were controlled to within 5% in 80% of the country samples. The conclusions indicated that renewable energy in China and India declined by 8.57 mtoe and 3.19 mtoe during COVID-19 period. In contrast, the rise in renewable energy in the US is overestimated by 8.01 mtoe. Overall, previous statistics based on year-to-year comparisons have led to optimistic estimates of renewable energy development during the pandemic. This study sheds light on the need for proactive policy measures in the future to counter the global low tide of renewable energy amid COVID-19.

Indexed as

COVID-19Neural network modelRenewable energyScenario estimation

Identifiers

PMID35975111
PMCPMC9371588
OpenAlexW4284893456

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.