Evidence map›Paper›PMID 33485198›Full record

ArticleThe Science of the total environment2021

Impacts of El Niño-Southern Oscillation on surface dust levels across the world during 1982-2019.

Jing Li, Eric Garshick, Shaodan Huang, Petros Koutrakis

Abstract read
In one paragraph

Article in The Science of the total environment, 2021. 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

4 authors.

Jing LiDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA.
Eric GarshickPulmonary, Allergy, Sleep, and Critical Care Medicine Section, Medical Service, VA Boston Healthcare System, Boston, MA 02132, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Shaodan HuangDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA. Electronic address: shhuang@hsph.harvard.edu.
Petros KoutrakisDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA.

Funding

Intramural VA VA999999
6 · The paper itself

Abstract

Dust pollution has become a significant concern worldwide. Both human activities and climate conditions affect dust levels. This study investigates the influence of El Niño-Southern Oscillation (ENSO), an important large-scale climate phenomenon, on surface dust levels in different regions. We used surface dust concentrations from Retrospective analysis for Research and Applications version 2 reanalysis and Southern Oscillation index (SOI) as dust and ENSO indicators, respectively. First, we first described characteristics of the global surface dust concentrations spanning a period of 37 years (1982-2019). Subsequently, we investigated the associations between monthly surface dust concentrations and SOI in regions with relative high dust levels, (i.e., North Africa, Northwest China and Mongolia, the Middle East, and South Australia) using time-series generalized additive models, controlled for meteorological variables and normalized difference vegetation index (NDVI). In order to capture the delayed effects of ENSO on dust, we fitted the model for SOI with 13 different moving averages starting from 12 months before. The highest average surface dust concentration for our study regions was 306.68 μg/m

Indexed as

Climate changeDustEl Niño–Southern Oscillation (ENSO)Southern Oscillation index (SOI)

Identifiers

PMID33485198
PMCPMC7969440

What OpenQuestion holds

Textmetadata
LicenceTDM
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.