Evidence map›Paper›PMID 35409512›Full record

ArticleInternational journal of environmental research and public health2022

Multi-Year Variation of Ozone and Particulate Matter in Northeast China Based on the Tracking Air Pollution in China (TAP) Data.

Hujia Zhao, Ke Gui, Yanjun Ma, Yangfeng Wang, Yaqiang Wang, Hong Wang, Yu Zheng, Lei Li, Lei Zhang, Yuqi Zhang and 2 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Exploratory thresholds for ambient PMBMC public health · 2026
    Article
  2. Article
  3. 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

12 authors.

Hujia ZhaoInstitute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China.
Ke GuiState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.
Yanjun MaInstitute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China.
Yangfeng WangInstitute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China.
Yaqiang WangState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.ORCID 0000-0002-4829-0276
Hong WangState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.
Yu ZhengState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.ORCID 0000-0002-5991-8014
Lei LiState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.
Lei ZhangState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.
Yuqi ZhangLiaoning Meteorological Service Center, Liaoning Meteorological Bureau, Shenyang 110166, China.
Huizheng CheState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.ORCID 0000-0002-9458-3387
Xiaoye ZhangState Key Laboratory of Severe Weather (LASW), Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of economy and urbanization acceleration, ozone (O3) pollution has become the main factor of urban air pollution in China after particulate matter. In this study, 90th percentile of maximum daily average (MDA) 8 h O3 (O3-8h-90per) and PM2.5 data from the Tracking Air Pollution in China (TAP) dataset were used to determine the mean annual, seasonal, monthly, and interannual distribution of O3-8h-90per and PM2.5 concentrations in Northeast China (NEC). The O3-8h-90per concentration was highest in Liaoning (>100 μg/m3), whereas the highest PM2.5 concentration was observed mainly in urban areas of central Liaoning and the Harbin−Changchun urban agglomeration (approximately 60 μg/m3). The O3-8h-90per concentrations were highest in spring and summer due to more intense solar radiation. On the contrary, the PM2.5 concentration increased considerably in winter influenced by anthropogenic activities. In May and June, the highest monthly mean O3-8h-90per concentrations were observed in central and western Liaoning, about 170−180 μg/m3, while the PM2.5 concentrations were the highest in January, February, and December, approximately 100 μg/m3. The annual mean O3-8h-90per concentration in NEC showed an increasing trend, while the PM2.5 concentration exhibited an annual decline. By 2020, the annual mean O3-8h-90per concentration in southern Liaoning had increased considerably, reaching 120−130 μg/m3. From the perspective of city levels, PM2.5 and O3-8h-90per also showed an opposite variation trend in the 35 cities of NEC. The reduced tropospheric NO2 column is consistent with the decreasing trend of the interannual PM2.5, while the increased surface temperature could be the main meteorological factor affecting the O3-8h-90per concentration in NEC. The results of this study enable a comprehensive understanding of the regional and climatological O3-8h-90per and PM2.5 distribution at distinct spatial and temporal scales in NEC.

Indexed as

Air PollutantsAir PollutionOzoneChinaEnvironmental MonitoringParticulate MatterAir PollutantsOzoneParticulate Mattercity leveldistributioninterannualNortheast ChinaO3-8h-90perPM2.5

Identifiers

PMID35409512
PMCPMC8997942

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Registered trials

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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.