Evidence map›Paper›PMID 33965708›Full record

ArticleJournal of environmental management2021

Quantitative estimation of meteorological impacts and the COVID-19 lockdown reductions on NO

Jinxi Hua, Yuanxun Zhang, Benjamin de Foy, Jing Shang, James J Schauer, Xiaodong Mei, Ishaq Dimeji Sulaymon, Tingting Han

Abstract read
In one paragraph

Article in Journal of environmental management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Effects of short-term PMScientific reports · 2023
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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

8 authors.

Jinxi HuaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Yuanxun ZhangCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen, China. Electronic address: yxzhang@ucas.ac.cn.
Benjamin de FoyDepartment of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, USA.
Jing ShangInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China.
James J SchauerWisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA.
Xiaodong MeiCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Ishaq Dimeji SulaymonCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Tingting HanInstitute of Urban Meteorology, China Meteorological Administration, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unprecedented travel restrictions due to the COVID-19 pandemic caused remarkable reductions in anthropogenic emissions, however, the Beijing area still experienced extreme haze pollution even under the strict COVID-19 controls. Generalized Additive Models (GAM) were developed with respect to inter-annual variations, seasonal cycles, holiday effects, diurnal profile, and the non-linear influences of meteorological factors to quantitatively differentiate the lockdown effects and meteorology impacts on concentrations of nitrogen dioxide (NO

Indexed as

Air PollutantsAir PollutionCOVID-19Communicable Disease ControlEnvironmental MonitoringHumansMeteorologyNitrogen DioxidePandemicsParticulate MatterSARS-CoV-2Air PollutantsNitrogen DioxideParticulate MatterCOVID-19 lockdownDiurnal profilesGAM analysismeteorologySpatial patterns

Identifiers

PMID33965708
PMCPMC8096144

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.