Evidence map›Paper›PMID 35489858›Full record

ArticleChaos (Woodbury, N.Y.)2022

Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19.

Weiping Wang, Saini Yang, Kai Yin, Zhidan Zhao, Na Ying, Jingfang Fan

Open access · bronzeAbstract read
In one paragraph

Article in Chaos (Woodbury, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 49% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. To what extent the traffic restriction policies can improve its air quality? An inspiration from COVID-19.Stochastic environmental research and risk assessment : research journal · 2023
    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

6 authors at 4 institutions in 1 country.

Weiping WangSchool of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China.
Saini YangSchool of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China.
Kai YinSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.
Zhidan ZhaoChina Complexity Computation Lab, Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China.ORCID 0000000194597984
Na YingChina State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.ORCID 0000000322243364
Jingfang FanSchool of Systems Science, Beijing Normal University, Beijing 100875, China.
Beijing Normal University · CNBeijing Jiaotong University · CNChinese Research Academy of Environmental Sciences · CNShantou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.

Indexed as

Air PollutionCOVID-19Traffic-Related PollutionHumansSpatio-Temporal Analysis

Identifiers

PMID35489858
PMCPMC9058978
OpenAlexW4221155818

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.