Evidence map›Paper›PMID 35350168›Full record

ArticleAtmospheric environment (Oxford, England : 1994)2022

Evaluation of NOx emissions before, during, and after the COVID-19 lockdowns in China: A comparison of meteorological normalization methods.

Qinhuizi Wu, Tao Li, Shifu Zhang, Jianbo Fu, Barnabas C Seyler, Zihang Zhou, Xunfei Deng, Bin Wang, Yu Zhan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Atmospheric environment (Oxford, England : 1994), 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
–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

2 citing papers in PubMed.

  1. Global daily COScientific data · 2026
    Article
  2. Counterintuitive PMInternational journal of environmental research and public health · 2026
    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

9 authors.

Qinhuizi WuDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Tao LiDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Shifu ZhangDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Jianbo FuDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Barnabas C SeylerDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Zihang ZhouChengdu Academy of Environmental Sciences, Chengdu, Sichuan, 610072, China.
Xunfei DengInstitute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, 310021, China.
Bin WangDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Yu ZhanDepartment of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meteorological normalization refers to the removal of meteorological effects on air pollutant concentrations for evaluating emission changes. There currently exist various meteorological normalization methods, yielding inconsistent results. This study aims to identify the state-of-the-art method of meteorological normalization for characterizing the spatiotemporal variation of NOx emissions caused by the COVID-19 pandemic in China. We obtained the hourly data of NO

Indexed as

COVID-19Emission reductionMeteorological normalizationNitrogen dioxideSpatiotemporal distribution

Identifiers

PMID35350168
PMCPMC8949849

What Socratic 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 Socratic graph.