Evidence map›Paper›PMID 40210854›Full record

ArticleNature communications2025

Delayed leaf green-up is associated with fine particulate air pollution in China.

Wendi Qu, Hao Hua, Ting Yang, Constantin M Zohner, Josep Peñuelas, Jing Wei, Le Yu, Chaoyang Wu

Abstract read
In one paragraph

Article in Nature communications, 2025. 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
–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

1 citing paper in PubMed.

  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

8 authors.

Wendi Qu *The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Hao Hua *The Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-1679-412X
Ting Yang *State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
Constantin M ZohnerDepartment of Environmental Systems Science, Institute of Integrative Biology, ETH, Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-8302-4854
Josep PeñuelasCSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Catalonia, Spain.ORCID http://orcid.org/0000-0002-7215-0150
Jing WeiDepartment of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
Le YuDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China. leyu@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3115-2042
Chaoyang WuThe Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. wucy@igsnrr.ac.cn.ORCID http://orcid.org/0000-0001-6163-8209

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42125101
6 · The paper itself

Abstract

Climate warming has led to earlier leaf green-up dates (GUD) with a greening trend of land surfaces in spring, yet the influence of multi-source particle pollution is not well understood. Using ground records and satellite observations of green-up date and fine particulate matter below 2.5 μm (PM

Indexed as

Air PollutantsAir PollutionParticulate MatterPlant LeavesCarbonChinaClimate ChangeEcosystemEnvironmental MonitoringPhotosynthesisSeasonsAir PollutantsCarbonParticulate Matter

Identifiers

PMID40210854
PMCPMC11985989

What OpenQuestion holds

Textmetadata
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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.