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Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd...
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Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition)

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

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 7440

Special Issue Editors

Dr. Chong Wei

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Guest Editor
Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
Interests: greenhouse gases; polycyclic aromatic hydrocarbons; black carbon; atmospheric monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Nan Li

E-Mail Website
Guest Editor
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: air pollution; atmospheric chemical model; remote sensing; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Xingjun Xie

E-Mail Website
Guest Editor
School of Geography and Tourism, Zhengzhou Normal University, Zhengzhou 450011, China
Interests: environmental science; quaternary geology
Special Issues, Collections and Topics in MDPI journals
Dr. Xin Long

E-Mail Website
Guest Editor
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
Interests: air pollution; big data; microplastic transport
Special Issues, Collections and Topics in MDPI journals
Dr. Shuai Yin

E-Mail
Guest Editor
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: biomass burning; air pollution; global climate change; remote sensing; geospatial science

Special Issue Information

Dear Colleagues,

Climate change and air pollution are two global environmental issues. Anthropogenic activities lead to large amounts of greenhouse gases and air pollutants being released into the atmosphere, and therefore change the atmospheric composition. These anthropogenic atmospheric compositions can alter the Earth’s radiation balance, causing climate change on a macro scale; it can also have an effect on the human respiratory system, introducing health risks from the air pollutants on the micro scale. Therefore, it is necessary to monitor and simulate the spatio-temporal distribution of the atmospheric composition, identify emission sources and contributions, and assess the potential ecological risks and health effects, as well as exchanges with other environmental mediums.

This Special Issue aims to present the most recent and outstanding results of atmospheric composition studies. Topics of interest for this Special Issue cover different aspects of studies on atmospheric composition, including, but not limited to:

  • New technologies to monitor or measure atmospheric composition.
  • Temporal and spatial distribution of the constituents of atmospheric composition, including greenhouse gases and air pollutants.
  • Source appointment method to determine atmospheric composition.
  • Emission inventory of greenhouse gases and air pollutants.
  • Ecological and health risk assessment of atmospheric composition.
  • Exchange and transformation of atmospheric composition in different environmental mediums.

Dr. Chong Wei
Dr. Nan Li
Dr. Xingjun Xie
Dr. Xin Long
Dr. Shuai Yin
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 pollutants
  • greenhouse gases
  • atmospheric monitoring
  • atmospheric modeling
  • spatio-temporal distribution
  • source appointment
  • emission inventory
  • health risk assessment

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Published Papers (6 papers)

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Research

15 pages, 4366 KiB  
Article
Varying Drivers of 2013–2017 Trends in PM2.5 Pollution over Different Regions in China
by Yanan Tao, Guangjin Liu, Bowen Sun, Yawei Dong, Lei Cao, Bei Zhao, Mei Li, Zeman Fan, Yaqing Zhou and Qiaoqiao Wang
Atmosphere 2024, 15(7), 789; https://doi.org/10.3390/atmos15070789 - 29 Jun 2024
Viewed by 852
Abstract
A significant decrease in surface PM2.5 concentrations has been reported since the implementation of the Air Pollution Prevention and Control Action Plan in 2013. In this study, we use the GEOS-Chem model to simulate the trend in surface PM2.5 pollution in [...] Read more.
A significant decrease in surface PM2.5 concentrations has been reported since the implementation of the Air Pollution Prevention and Control Action Plan in 2013. In this study, we use the GEOS-Chem model to simulate the trend in surface PM2.5 pollution in China from 2013 to 2017, as well as the relative contributions of emission reduction and meteorology. The simulated decline rate averaged over monitoring sites in China is around −4.7 μg m−3 yr−1 in comparison with the value of −6.4 μg m−3 yr−1 from observations. The model also captures the variations over different regions, with r in the range of 0.85–0.95. Based on the sensitivity tests against emissions and meteorology, the study finds that the decline in PM2.5 concentrations is mainly driven by the reduction in anthropogenic emissions. The variation in open biomass burning (OBB) is not significant, except in Northeast China (NEC) and Pearl River Delta (PRD), where the changes originated from OBB are 40% and 30% of those associated with anthropogenic emission reductions. Changes in meteorology from 2013 to 2017 led to significant increases in PM2.5 concentrations in most areas in China, except in NEC. The increase attributed to meteorology, to a large extent, could be explained by the significant decrease in surface wind speed (WS) and planetary boundary layer height (PBLH) between 2013 and 2017, combined with their negative correlation with PM2.5. The decrease in PM2.5 concentrations in NEC, on the other hand, could be explained by the significant decrease in relative humidity (RH) there combined with the positive correlation of RH with PM2.5, while the changes in WS and PBLH there are relatively small compared with other areas. The change in meteorology, therefore, hinders the improvement of air quality via emission controls in most of China. In Sichuan Basin (SCB), the increase due to meteorology almost compensates for the decrease associated with emission reduction, leading to the least change in PM2.5 concentrations, although the decrease due to emission controls is the largest compared with other areas. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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18 pages, 8587 KiB  
Article
Analysis of Diffusion Characteristics and Influencing Factors of Particulate Matter in Ship Exhaust Plume in Arctic Environment Based on CFD
by Yuanqing Zhu, Qiqi Wan, Qichen Hou, Yongming Feng, Jia Yu, Jie Shi and Chong Xia
Atmosphere 2024, 15(5), 580; https://doi.org/10.3390/atmos15050580 - 9 May 2024
Cited by 1 | Viewed by 936
Abstract
The gradual opening of the Arctic shipping route has made navigation possible. However, the harm caused by ship exhaust emissions is increasingly severe. Therefore, it is necessary to study the diffusion characteristics of ship exhaust plumes during Arctic navigation. The study focuses on [...] Read more.
The gradual opening of the Arctic shipping route has made navigation possible. However, the harm caused by ship exhaust emissions is increasingly severe. Therefore, it is necessary to study the diffusion characteristics of ship exhaust plumes during Arctic navigation. The study focuses on a merchant vessel as the subject of investigation, employing computational fluid dynamics (CFD) simulation techniques to analyze the diffusion characteristics of particulate matter (PM) within ship exhaust plumes under Arctic environmental conditions. The diffusion law of ship exhaust plume PM is clarified, and the influence of three factors, synthetic wind speed, yaw angle and chimney angle, on the PM diffusion is analyzed. It was found that after the PM was discharged from the chimney, the majority of the PM dispersed directly backward along with the external flow field, while a minor fraction lingered at the stern of the ship for an extended period before eventually diffusing backward. Among them, 1235 particles were captured within a range of 200 m from the stern, with a capture rate of 0.6%. When the synthetic wind shows a yaw angle, the capture rate of PM in the interval increases rapidly with the increase of yaw angle, while other factors have less influence on the capture rate of PM. This study provides foundational guidance for predicting PM diffusion from ship exhaust plumes in Arctic environments, thereby enabling more effective strategies for managing such emissions. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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21 pages, 20948 KiB  
Article
Analysis of Primary Air Pollutants’ Spatiotemporal Distributions Based on Satellite Imagery and Machine-Learning Techniques
by Yanyu Li, Meng Zhang, Guodong Ma, Haoyuan Ren and Ende Yu
Atmosphere 2024, 15(3), 287; https://doi.org/10.3390/atmos15030287 - 27 Feb 2024
Cited by 1 | Viewed by 1204
Abstract
Accurate monitoring of air pollution is crucial to human health and the global environment. In this research, the various multispectral satellite data, including MODIS AOD/SR, Landsat 8 OLI, and Sentinel-2, together with the two most commonly used machine-learning models, viz. multi-layer backpropagation neural [...] Read more.
Accurate monitoring of air pollution is crucial to human health and the global environment. In this research, the various multispectral satellite data, including MODIS AOD/SR, Landsat 8 OLI, and Sentinel-2, together with the two most commonly used machine-learning models, viz. multi-layer backpropagation neural network (MLBPN) and random forest (RF), have been employed to analyze the spatiotemporal distributions of the primary air pollutant from 2019 to 2022 in Guanzhong Region, China. In the conducted experiments, the RF-based model, using the MODIS AOD data, has generally demonstrated the “optimal” estimation performance for the ground-surface concentrations of the primary air-pollutants. Then, the “optimal” estimation model has been employed to analyze the spatiotemporal distribution of the various air pollutants—in terms of temporal distribution, the annual average concentrations of PM2.5, PM10, NO2, and SO2 in the research area showed a decreasing trend from 2019 to 2022, while the annual average concentration of CO remained relatively stable and the annual average concentration of O3 slightly increased; in terms of the spatial distribution, the air pollution presents a gradual increase from west to east in the research area, with the distribution of higher concentrations in the center of the built-up areas and lower in the surrounding rural areas. The proposed estimation model and spatiotemporal analysis can provide reliable methodologies and data support for the further study of the air pollution characteristics in the research area. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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15 pages, 6021 KiB  
Article
Temporal Dynamics of Negative Air Ion Concentrations in Nanjing Tulou Scenic Area
by Zhihui Li, Changshun Li, Bo Chen, Yu Hong, Lan Jiang, Zhongsheng He and Jinfu Liu
Atmosphere 2024, 15(3), 258; https://doi.org/10.3390/atmos15030258 - 21 Feb 2024
Viewed by 1519
Abstract
Negative air ions (NAIs) are crucial for assessing the impact of forests on wellbeing and enhancing the physical and mental health of individuals. They serve as pivotal indicators for assessing air quality. Comprehensive research into the distribution patterns of NAI concentrations, especially the [...] Read more.
Negative air ions (NAIs) are crucial for assessing the impact of forests on wellbeing and enhancing the physical and mental health of individuals. They serve as pivotal indicators for assessing air quality. Comprehensive research into the distribution patterns of NAI concentrations, especially the correlation between NAI concentrations and meteorological elements in tourist environments, necessitates the accumulation of additional long-term monitoring data. In this paper, long-term on-site monitoring of NAI concentrations, air temperature, relative humidity, and other factors was conducted in real time over 24 h, from April 2020 to May 2022, to explore the temporal dynamic patterns of NAIs and their influencing factors. The results showed that (1) the daily dynamics of NAI concentrations followed a U-shaped curve. The peak concentrations usually occurred in the early morning (4:30–8:00) and evening (19:10–22:00), and the lowest concentrations usually occurred at noon (12:50–14:45). (2) At the monthly scale, NAI concentrations were relatively high in February, August, and September and low in January, June, and December. At the seasonal scale, NAI concentrations were significantly higher in winter than in other seasons, with higher concentrations occurring in the summer and autumn. (3) Relative humidity, air temperature, and air quality index (AQI) were the primary factors that influenced NAI concentrations. Relative humidity showed a significant positive correlation with NAI concentrations, while air temperature and AQI both exhibited a significant negative correlation with NAI concentrations. Higher air quality corresponds to higher NAI concentrations. Our research provides new insights into NAI temporal dynamics patterns and their driving factors, and it will aid in scheduling outdoor recreation and forest health activities. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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17 pages, 29053 KiB  
Article
Wildfire CO2 Emissions in the Conterminous United States from 2015 to 2018 as Estimated by the WRF-Chem Assimilation System from OCO-2 XCO2 Retrievals
by Jiuping Jin, Qinwei Zhang, Chong Wei, Qianrong Gu and Yongjian Huang
Atmosphere 2024, 15(2), 186; https://doi.org/10.3390/atmos15020186 - 31 Jan 2024
Viewed by 1136
Abstract
Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for [...] Read more.
Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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14 pages, 9408 KiB  
Article
Aircraft Measurements of Tropospheric CO2 in the North China Plain in Autumn and Winter of 2018–2019
by Hui Zhang, Qiang Yang, Hongjie Yuan, Dongliang Ma, Zhilei Liu, Jianguang Jia, Guan Wang, Nana Zhang, Hailiang Su, Youyu Shi, Yongjing Ma, Lindong Dai, Baojiang Li and Xiao Huang
Atmosphere 2023, 14(12), 1835; https://doi.org/10.3390/atmos14121835 - 18 Dec 2023
Cited by 1 | Viewed by 1156
Abstract
Quantifying the level of CO2, the main greenhouse gas (GHG), is essential for research on regional and global climate change, especially in the densely populated North China Plain with its severe CO2 emissions. In this study, 12 airborne flights were [...] Read more.
Quantifying the level of CO2, the main greenhouse gas (GHG), is essential for research on regional and global climate change, especially in the densely populated North China Plain with its severe CO2 emissions. In this study, 12 airborne flights were managed and conducted during the autumn–winter period of 2018–2019 in downtown Shijiazhuang and its surrounding areas, which are representative of the typical urban conditions in the North China Plain, to explore the spatial and temporal distributions of CO2. The results showed that the measured columnar averages of CO2 ranged between 399.9 ± 1.5 and 443.8 ± 31.8 ppm; the average of the 12 flights was 412.1 ppm, slightly higher than the globally averaged 410.5 ± 0.20 ppm and the 2 background concentrations of 411.6 ± 2.1 ppm and 411.4 ± 0.2 ppm in low-latitude Mauna Loa and middle-latitude Waliguan in 2019, indicating the potential influences of anthropogenic activities. The typical stratification of the planetary boundary layer (PBLH), residual layer (RL), and elevated inversion layer (IL) was crucial in constraining the high CO2 concentrations. This illustrated that the warming effect of CO2 within the PBLH may also have some influences on regulating the thermal structure of the low troposphere. Based on a backward trajectory analysis, it was evidenced that there were three different categories of air masses for autumn and one category for winter. Both trajectories in the PBL, i.e., below 1000 m, from the local and southern areas with tremendous anthropogenic emissions (autumn) and from the western regions (winter) led to comparatively high levels of CO2, but the mid-tropospheric CO2 concentrations above 1000 m were commonly homogeneously distributed, with higher levels appearing in winter because the concentration in the free troposphere followed the global seasonal pattern, with a summer minimum and winter maximum as a result of the seasonality of the net CO2 exchange and the balance between photosynthesis and respiration. These results provide an in-depth understanding of the vertical concentrations of tropospheric CO2 in the North China Plain, which will offer scientific references for the evaluation of carbon accounting and carbon emissions. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions (2nd Edition))
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