Evidence map›Paper›PMID 35753487›Full record

ArticleThe Science of the total environment2022

Air pollution rebound and different recovery modes during the period of easing COVID-19 restrictions.

Xinyang Dong, Xinzhu Zheng, Can Wang, Jinghai Zeng, Lixiao Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Science of the total environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

5 authors.

Xinyang DongState Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China.
Xinzhu ZhengSchool of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China.
Can WangState Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China. Electronic address: canwang@tsinghua.edu.cn.
Jinghai ZengState Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China.
Lixiao ZhangSchool of Environment, Beijing Normal University, Beijing 100875, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although COVID-19 lockdown policies have improved air quality in numerous countries, there is a lack of empirical evidence on the extent to which recovery has resulted in air pollution rebound, and the differences and similarities among regions' recovery modes during the period of easing COVID-19 restrictions. Here, we used daily air quality data and the recovery index constructed by a city-pair inflow index for 119 cities in China to quantify the impact of recovery on air pollution from March 2 to October 30, 2020. Findings show that recovery has significantly increased air pollution. When the recovery level increased by 10 %, the concentration of PM

Indexed as

Air PollutantsAir PollutionCOVID-19ChinaCitiesCommerceCommunicable Disease ControlEnvironmental MonitoringHumansInternationalityParticulate MatterAir PollutantsParticulate MatterAir pollution reboundCounterfactual analysisRecovery modesThe period of easing COVID-19 restrictionsTime series clusteringWavelet transform

Identifiers

PMID35753487
PMCPMC9222490

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.