Characteristics and Trends of Air Pollutants and Their Relationship to Atmospheric Circulations

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 893

Special Issue Editors


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Guest Editor
School of Marine Science and Engineering, Hainan University, Haikou, China
Interests: arctic and antarctic climates and environmental research

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Guest Editor
School of Marine Science and Engineering, Hainan University, Haikou, China
Interests: the coupling relationship between the atmosphere, ocean, and ice sheets in geologic history

Special Issue Information

Dear Colleagues,

This Special Issue, "Characteristics and Trends of Air Pollutants and Their Relationship to Atmospheric Circulations", explores the physical and chemical processes of air pollution and its interaction with atmospheric circulation patterns. Air pollutants, such as particulate matter (PM), ozone (O₃), nitrogen oxides (NOₓ), sulphur dioxide (SO₂), carbon monoxide (CO), and volatile organic compounds (VOCs), are major contributors to environmental degradation and public health issues. Characteristics, including their chemical composition, sources, and distribution patterns, are influenced by both natural and anthropogenic factors. Human activities like fossil fuel combustion, industrial emissions, and agricultural practices dominate the generation of pollutants, while natural events such as wildfires and volcanic eruptions also contribute significantly.

Atmospheric circulations play a pivotal role in shaping the distribution, transport, and transformation of air pollutants. Large-scale systems, such as the jet stream, monsoons, and trade winds, influence pollutant dispersion across continents, while localized phenomena like sea breezes and mountain–valley circulations affect regional air quality. Stagnant weather patterns can exacerbate episodes of pollution, leading to phenomena like smog and haze, whereas dynamic systems can transport pollutants over long distances, impacting areas far from the source.

Understanding the relationship between air pollutants and atmospheric circulations is critical for improving air quality forecasting, public health strategies, and environmental policies. By integrating air quality monitoring with meteorological analysis, policymakers and researchers can better predict episodes of pollution, assess long-term trends, and develop adaptive measures to protect environmental and public health. As global climate patterns shift, continued research on this interplay is essential to address emerging challenges in air quality management.

This Special Issue intends to collect articles on the characteristics and trends of air pollutants and their relationship to atmospheric circulations. We invite contributions that deal with the variability and predictability of atmospheric pollutants, particularly in the polar regions, and the relationship between the characteristics and trends of these pollutants and atmospheric circulation. We welcome submissions, including original articles and reviews on this topic that aim to provide a valuable resource for scientists, policymakers, and environmental managers to help address the growing challenge of air pollution in the context of climate change and changing atmospheric dynamics.

Prof. Dr. Jianjun Wang
Prof. Dr. Xufeng Zheng
Guest Editors

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Keywords

  • air pollution
  • atmospheric circulation
  • particulate matter (PM)
  • nitrogen oxides (NOx)
  • sulphur dioxide (SO2)
  • ozone
  • meteorological factors
  • climate variability
  • pollution trends
  • air quality

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Published Papers (1 paper)

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Research

17 pages, 3678 KiB  
Article
Modeling Greenhouse Gas Emissions from Agriculture
by Alina Bărbulescu
Atmosphere 2025, 16(3), 295; https://doi.org/10.3390/atmos16030295 - 28 Feb 2025
Viewed by 707
Abstract
This study analyzes the series of annual emissions of greenhouse gases (GHGs) from agriculture in the European Union countries for 32 years. The outliers, autocorrelation, and change points were detected for each series and the Total one using the boxplot, autocorrelation function (ACF), [...] Read more.
This study analyzes the series of annual emissions of greenhouse gases (GHGs) from agriculture in the European Union countries for 32 years. The outliers, autocorrelation, and change points were detected for each series and the Total one using the boxplot, autocorrelation function (ACF), and Pettit, Hubert, and CUSUM tests. The existence of a monotonic trend in the data series was checked against the randomness by the Mann–Kendall test; further, the slope of the linear trend was determined by Sen’s nonparametric approach and classical regression. The best distribution was fitted for each data series. The results indicate that most series present aberrant values (indicating periods with high emissions), are autocorrelated, and have a decreasing tendency over time (showing the diminishing of GHG emissions from agriculture during the study period). The distributions that best fit the individual series were of Wakeby, Johnson SB, Burr, and Log-logistic type. The Total series has a decreasing trend, presents a second-order autocorrelation, and is right-skewed. An ARIMA(1,1,2) model was built and validated for it and was used for the forecast. Full article
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