Evidence map›Paper›PMID 32535826›Full record

ArticleEnvironmental science and pollution research international2020

Spatio-temporal variations and trends of major air pollutants in China during 2015-2018.

Kamal Jyoti Maji, Chinmoy Sarkar

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Air Pollution and Migration Intention: Evidence from the Unified National Graduate Entrance Examination.International journal of environmental research and public health · 2022
    Article
  4. Article
  5. Article
  6. Article
  7. Spatio-Temporal Characteristics of SOInternational journal of environmental research and public health · 2021
    Article
  8. Article
  9. 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

2 authors.

Kamal Jyoti MajiDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China. kjmaji@hku.hk.
Chinmoy SarkarHealthy High Density Cities Lab, HKUrbanLab, University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Chinese government, as a policy response, has continued to invest efforts and resources to implement cost-effective air pollution control technologies and stringent regulation to reduce emissions from the most contributing sectors to protect the environment and public health. The higher density of monitoring stations (> 1600) distributed across China provides a timely opportunity to use them to study in detail the national pollution trends in light of more stringent air pollution control policies. In the present study, air quality datasets comprising hourly concentrations of PM

Indexed as

Air PollutantsAir PollutionChinaEnvironmental MonitoringParticulate MatterAir PollutantsParticulate MatterAir pollutionChinaMonitoring stations dataResponsible Editor: Gerhard LammelSpatio-temporal analysisTrend analysis

Identifiers

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.