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Atmosphere
Special Issues
Air Pollution: Emission Characteristics and Formation Mechanisms
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Air Pollution: Emission Characteristics and Formation Mechanisms

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 835

Special Issue Editors

Dr. Wenkai Guo

E-Mail Website
Guest Editor
School of Environmental Science and Engineering, Southwest Jiaotong University, Chengdu, China
Interests: emission inventory; ozone; air quality modeling; photochemical pollution mechanisms; meteorology–pollution interaction
Prof. Dr. Qiang Chen

E-Mail Website
Guest Editor
College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Interests: atmospheric chemistry; source apportionment; emission inventory; ozone; particulate matter; meteorology–pollution synergy

Special Issue Information

Dear Colleagues,

Air pollution remains a significant global environmental issue, profoundly impacting human health and atmospheric processes. This Special Issue, titled "Air Pollution: Emission Characteristics and Formation Mechanisms", aims to showcase recent advancements to further our understanding of the sources, emission patterns, and formation mechanisms of key air pollutants.

We welcome contributions that investigate the emission characteristics of primary air pollutants—such as particulate matter (PM), volatile organic compounds (VOCs), nitrogen oxides (NOx), and sulfur dioxide (SO2)—from both anthropogenic and natural sources. Studies focusing on spatiotemporal variations of emissions, the influence of land use and meteorological factors, and region-specific emission patterns are particularly encouraged.

In addition, this Special Issue seeks to highlight research on the chemical and physical processes driving the formation, transformation, and accumulation of secondary pollutants such as ozone (O3) and fine particulate matter (PM2.5). Submissions addressing the complex interactions between precursors, meteorological conditions, and atmospheric dynamics and analyzing the causes of heavy pollution episodes are highly welcome.

We also invite the submission of studies that apply advanced tools—including air quality modeling, remote sensing, source apportionment techniques, and field observations—to improve our understanding of emission sources and the underlying drivers of air pollution in various environments.

This Special Issue provides a focused platform for researchers to share novel insights into pollutant emissions and the mechanisms responsible for pollution formation, supporting the scientific basis for future air quality assessment and management.

Dr. Wenkai Guo
Prof. Dr. Qiang Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • air pollutant emissions
  • pollution formation mechanisms
  • particulate matter (PM)
  • ozone formation
  • emission inventory
  • meteorology–pollution interaction

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Published Papers (2 papers)

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Research

18 pages, 9625 KiB  
Article
Tracking Long-Term Ozone Pollution Dynamics in Chinese Cities with Meteorological and Emission Attribution
by Hongrui Li, Xiaoyong Liu, Zijian Liu, Mengyang Li, Tong Wu, Peicheng Li and Peng Zhou
Atmosphere 2025, 16(7), 768; https://doi.org/10.3390/atmos16070768 - 23 Jun 2025
Viewed by 292
Abstract
Although China has achieved substantial reductions in particulate matter pollution, continually rising ground-level ozone now constitutes the primary challenge to further air-quality improvements. A systematic assessment of the long-term spatiotemporal behavior of ozone (O3) and its links to meteorology and emissions [...] Read more.
Although China has achieved substantial reductions in particulate matter pollution, continually rising ground-level ozone now constitutes the primary challenge to further air-quality improvements. A systematic assessment of the long-term spatiotemporal behavior of ozone (O3) and its links to meteorology and emissions is still lacking. Here, we develop a novel framework that couples Kolmogorov–Zurbenko (KZ) filtering with an optimized random forest (RF) regression model to examine daily maximum 8 h average ozone (O3-8h) in 372 Chinese cities from 2013 to 2023. The approach quantitatively disentangles meteorological and emission contributions at the national scale, overcoming the limitations of traditional linear methods in capturing non-linear processes. Long-term components explain, in general, <40% of total O3 variance. In eastern urban agglomerations, long-term meteorological factors—particularly temperature and surface ultraviolet radiation—account for up to 80% of the trend, whereas long-term emission contributions remain modest (≈5–6%), with pronounced signals in the Beijing–Tianjin–Hebei and Fenwei Plain regions. Empirical orthogonal function analysis further reveals distinct spatial patterns of emission influence: long-term O3 trends in mega-cities such as Beijing, Tianjin, and Shanghai are driven mainly by local emissions (1.5–3% contribution), while key transport hubs including Xi’an, Tangshan, and Langfang are markedly affected by traffic-related emissions (>2%). These findings clarify the heterogeneous mechanisms governing O3 formation across China and provide a scientific basis for designing and implementing the next phase of region-specific, joint prevention-and-control policies. Full article
(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)
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27 pages, 2653 KiB  
Article
Temporal and Machine Learning-Based Principal Component and Clustering Analysis of VOCs and Their Role in Urban Air Pollution and Ozone Formation
by Balendra V. S. Chauhan, Maureen J. Berg, Ajit Sharma, Kirsty L. Smallbone and Kevin P. Wyche
Atmosphere 2025, 16(6), 724; https://doi.org/10.3390/atmos16060724 - 15 Jun 2025
Viewed by 405
Abstract
This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside [...] Read more.
This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside ozone (O3) and meteorological data, were analysed using correlation matrices, regression, cross-correlation, diurnal/seasonal analysis, wind-sector analysis, PCA (Principal Component Analysis), and clustering. Strong inter-VOC correlations (e.g., benzene–ethylbenzene: r = 0.86, R2 = 0.75; ethene–propene: r = 0.68, R2 = 0.53) highlighted dominant vehicular sources. Diurnal peaks of benzene, toluene, and ethylbenzene aligned with rush hours, while O3 minima occurred in early mornings due to NO titration. VOCs peaked in winter under low mixing heights, whereas O3 was highest in summer. Wind-sector analysis revealed dominant VOC emissions from SSW (south-southwest)–WSW (west-southwest) directions; ethyne peaked from the E (east)/ENE (east-northeast). O3 concentrations were highest under SE (southeast)–SSE (south-southeast) flows. PCA showed 39.8% of variance linked to traffic-related VOCs (PC1) and 14.8% to biogenic/temperature-driven sources (PC2). K-means clustering (k = 3) identified three regimes: high VOCs/low O3 in stagnant, cool air; mixed conditions; and low VOCs/high O3 in warmer, aged air masses. Findings highlight complex VOC–O3 interactions and stress the need for source-specific mitigation strategies in urban air quality management. Full article
(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)
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