Evidence map›Paper›PMID 37383022›Full record

ArticlePNAS nexus2023

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas.

Zhengyang Hou, Yang Li, Liqiang Zhang, Changqing Song, Jintai Lin, Chenghu Zhou, Yuebin Wang, Ying Qu, Xin Yao, Peichao Gao

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PNAS nexus, 2023. 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
0.2field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

10 authors at 3 institutions in 1 country.

Zhengyang HouFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Yang LiFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Liqiang ZhangFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.ORCID https://orcid.org/0000-0002-4175-7590
Changqing SongFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Jintai LinLaboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.ORCID https://orcid.org/0000-0002-2362-2940
Chenghu ZhouState Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China.
Yuebin WangFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Ying QuFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Xin YaoFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Peichao GaoFaculty of Geographical Science, Beijing Normal University, Beijing 100875, China.ORCID https://orcid.org/0000-0003-1714-779X
Beijing Normal University · CNChinese Academy of Sciences · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFS

Indexed as

COVID-19 lockdownheterogeneous impactsHimalayassnow and ice darkeningtransboundary pollution

Identifiers

PMID37383022
PMCPMC10299077
OpenAlexW4382469270

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.