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Atmosphere
Special Issues
Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions
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Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions

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

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 11377

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. Chong Shi

E-Mail Website
Guest Editor
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: aerosol retrieval; radiative transfer; atmospheric remote sensing; air pollution
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

Special Issue Information

Dear Colleagues,

The atmosphere is constituted by various atmospheric compositions. The composition of the atmosphere is changed because of a large number of greenhouse gases and air pollutants emitted from anthropogenic activities. These anthropogenic atmospheric compositions can alter the earth’s radiation balance causing climate change on a macro-scale, and also can enter into 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 atmospheric compositions, identify their emission sources and contributions, and assess their 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 compositions, including, but are not limited to:

  • New technologies to monitor or measure atmospheric compositions.
  • Temporal and spatial distribution of atmospheric compositions like greenhouse gases and air pollutants.
  • Source appointment method of atmospheric compositions.
  • Ecological and health risks assessment of atmospheric compositions.
  • Exchange and transformation of atmospheric compositions in different environmental mediums.

Dr. Chong Wei
Dr. Chong Shi
Dr. Nan Li
Dr. Xingjun Xie
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
  • health risk assessment

Published Papers (7 papers)

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Research

13 pages, 5015 KiB  
Article
Spatiotemporal Characteristics of Ozone Pollution and Resultant Increased Human Health Risks in Central China
by Yuren Tian, Yun Wang, Yan Han, Hanxiong Che, Xin Qi, Yuanqian Xu, Yang Chen, Xin Long and Chong Wei
Atmosphere 2023, 14(10), 1591; https://doi.org/10.3390/atmos14101591 - 22 Oct 2023
Cited by 1 | Viewed by 968
Abstract
The spatiotemporal characteristics of ozone pollution and increased human health risks in Central China were investigated using a long time series of ozone concentrations from 2014 to 2020. We found a gradual increase in ozone pollution, with the highest concentrations observed in the [...] Read more.
The spatiotemporal characteristics of ozone pollution and increased human health risks in Central China were investigated using a long time series of ozone concentrations from 2014 to 2020. We found a gradual increase in ozone pollution, with the highest concentrations observed in the northeastern region. The spatial distribution of population density showed distinct patterns, with the northeastern and east-central regions coinciding with areas of high ozone concentrations. The study found an overall increasing trend in MDA8 ozone concentrations, with a regional average increase of 3.5 (μg m−3) per year, corresponding to a 4.4% annual increase. We observed a significant clustering of areas at a higher risk of premature mortality associated with long-term ozone exposure, particularly in the northeastern region. Estimated premature mortality due to ozone pollution in Central China between 2014 and 2020 shows an increasing trend from 2014 to 2019 and a decreasing trend in 2020 due to the occurrence of extreme ozone pollution and the subsequent recovery of ozone concentrations after the closures due to COVID-19. Premature mortality due to ozone exposure is affected by both ozone levels and the exposed population, with high correlation coefficients exceeding 0.95. The high total population (more than 220 million per year) and increasing ozone levels exacerbate the problem of premature mortality due to ozone pollution. This study improves our understanding of the impact of ozone pollution on human health and emphasizes the dynamic nature of ozone pollution and its impacts on human health over time. It underscores the need for further study and comprehensive action to mitigate these health risks. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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15 pages, 3695 KiB  
Article
Source-Specific Health Risk of PM2.5-Bound Metals in a Typical Industrial City, Central China, 2021–2022
by Ziguo Liu, Changlin Zhan, Hongxia Liu, Shan Liu, Jihong Quan, Xianli Liu, Jiaquan Zhang and Chengkai Qu
Atmosphere 2023, 14(9), 1406; https://doi.org/10.3390/atmos14091406 - 06 Sep 2023
Cited by 3 | Viewed by 1055
Abstract
In order to study the pollution characteristics, sources, and health risks of heavy metals in urban atmospheric PM2.5, samples were collected in Huangshi City from June 2021 to May 2022. The contents of 16 kinds of metal elements were analyzed by [...] Read more.
In order to study the pollution characteristics, sources, and health risks of heavy metals in urban atmospheric PM2.5, samples were collected in Huangshi City from June 2021 to May 2022. The contents of 16 kinds of metal elements were analyzed by XRF, and the pollution degree and sources of elements were analyzed by the enrichment factor method, correlation analysis, and cluster analysis. The health risk of heavy metal elements was evaluated by the USEPA health risk assessment model. The results of enrichment factor analysis show that the metal elements carried by PM2.5 were affected by human emissions except for Ti. Heavy metals mainly come from industrial sources, motor vehicle sources, mixed combustion sources, and dust sources, according to correlation analysis and cluster analysis. Mn had a non-carcinogenic risk to children, and the non-carcinogenic risk of other elements to the human body was generally acceptable. The carcinogenic risks of Cr, As, Cd, and Co exceeded the acceptable carcinogenic risk threshold (10−6 ~10−4), and there were potential carcinogenic risks. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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21 pages, 5341 KiB  
Article
Investigating the Synergy between CO2 and PM2.5 Emissions Reduction: A Case Study of China’s 329 Cities
by Shangjiu Wang, Shaohua Zhang and Liang Cheng
Atmosphere 2023, 14(9), 1338; https://doi.org/10.3390/atmos14091338 - 24 Aug 2023
Cited by 1 | Viewed by 862
Abstract
The synergetic reduction of CO2 and PM2.5 emissions has received much attention in China in recent years. A comprehensive evaluation of the synergy between CO2 emission reduction (CER) and PM2.5 emission reduction (PER) would provide valuable information for developing [...] Read more.
The synergetic reduction of CO2 and PM2.5 emissions has received much attention in China in recent years. A comprehensive evaluation of the synergy between CO2 emission reduction (CER) and PM2.5 emission reduction (PER) would provide valuable information for developing synergetic control policies. Thus, we constructed a comprehensive CO2-PM2.5-emission-reduction index system and evaluated the synergy between CER and PER, using the coupling coordination degree (CCD) and relative development degree (RDD) model in China’s 329 cities from 2003 to 2017. The spatiotemporal characteristics of the CCD were analyzed on the national, regional, and urban scales. Furthermore, we used the spatial autocorrelation analysis, kernel density estimation, and Dagum Gini coefficient to investigate the spatial autocorrelation, evolutionary characteristics, and regional differences of the CCD. The results indicate that (1) the synergy between CO2 and PM2.5 emissions’ reductions showed an upward trend, and the lowest CCD values occurred in NW and Shanghai on the regional and urban scales, respectively; (2) the CCD showed obvious spatial clustering characteristics, with 75% of the cities located in the “High–High” or “Low–Low” clustering zones in the Moran scatter plots in 2017; (3) the polarization of CCD in SC, MYR, and SW showed intensified trends; (4) and the hypervariable density was the largest contributor to the overall difference in the CCD. Our findings suggest that more attention should be paid to the top-level design of the policies, technological innovation, and cross-regional or intercity cooperation. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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21 pages, 6439 KiB  
Article
Assessing the Impacts of COVID-19 on SO2, NO2, and CO Trends in Durban Using TROPOMI, AIRS, OMI, and MERRA-2 Data
by Boitumelo Mokgoja, Paidamwoyo Mhangara and Lerato Shikwambana
Atmosphere 2023, 14(8), 1304; https://doi.org/10.3390/atmos14081304 - 17 Aug 2023
Viewed by 1181
Abstract
This research report investigated the impacts of the COVID-19 lockdown restrictions on CO, SO2, and NO2 trends in Durban from 2019 to 2021. The COVID-19 lockdown restrictions proved to decrease greenhouse gas (GHG) emissions globally; however, the decrease in GHG [...] Read more.
This research report investigated the impacts of the COVID-19 lockdown restrictions on CO, SO2, and NO2 trends in Durban from 2019 to 2021. The COVID-19 lockdown restrictions proved to decrease greenhouse gas (GHG) emissions globally; however, the decrease in GHG emissions was for a short period only. Space-borne technology has been used by researchers to understand the spatial and temporal trends of GHGs. This study used Sentinel-5P to map the spatial distribution of CO, SO2, and NO2. Use was also made of the Atmospheric Infrared Sounder (AIRS), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), and the Ozone Monitoring Instrument (OMI) to understand the temporal trends of CO, SO2, and NO2, respectively. To validate the results of this study, we used the Sequential Mann–Kendall (SQMK) test. This study indicated that there were no significant changes in all the investigated gases. Therefore, this study failed to reject the null hypothesis of the SQMK test that there was no significant trend for all investigated gasses. Increasing trends were observed for CO, SO2, and NO2 trends during winter months throughout the study period, whereas a decreasing trend was observed in all investigated gases during the spring months. This shows that meteorological factors play a significant role in the accumulation of air pollutants in the atmosphere. Most importantly, this study has noted that there was an inverse relationship between the trends of all investigated gases and the COVID-19 lockdown restrictions. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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25 pages, 3471 KiB  
Article
Assessing Spatiotemporal Characteristics and Driving Factors of Urban Public Buildings Carbon Emissions in China: An Approach Based on LMDI Analysis
by Zhidong Zhang, Yisheng Liu and Tian Ma
Atmosphere 2023, 14(8), 1280; https://doi.org/10.3390/atmos14081280 - 13 Aug 2023
Cited by 2 | Viewed by 1016
Abstract
Urban public buildings carbon emissions exhibit an upward trend and have a large potential in carbon emission reduction. The analysis of spatiotemporal characteristics and driving factors for urban public buildings carbon emissions is essential in formulating effective policies for carbon reduction, meeting commitments [...] Read more.
Urban public buildings carbon emissions exhibit an upward trend and have a large potential in carbon emission reduction. The analysis of spatiotemporal characteristics and driving factors for urban public buildings carbon emissions is essential in formulating effective policies for carbon reduction, meeting commitments to peak carbon emissions and achieving carbon neutrality. This study takes China’s urban public buildings carbon emissions as the research object, employing methods such as spatial autocorrelation analyses, kernel density estimation analyses, and the LMDI decomposition methods to explore the spatiotemporal characteristics and regional disparities in carbon emissions from 2006 to 2019. Furthermore, it quantifies the contributions of driving factors to the spatiotemporal changes in urban public buildings carbon emissions. The results show the following: (1) Urban public buildings carbon emissions among provinces are consistently increasing, indicating an overall upward trend. The spatial distribution highlights significant regional disparities. (2) The spatial characteristics of urban public buildings carbon emissions were basically stable. The eastern coastal regions demonstrate a high-high cluster, while the western regions exhibit a low-low cluster. The overall cluster evolution showed a decreasing trend from east to west. (3) Per capita urban public building area, economic density, urbanization rate, and population size serve as driving factors for carbon emissions from urban public buildings, while energy efficiency and energy consumption intensity act as inhibitory factors. The findings of this research can assist policymakers in getting a deeper comprehension of urban public buildings carbon emissions and providing a scientific basis to formulate appropriate carbon emission reduction policies. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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16 pages, 1886 KiB  
Article
Temporal Dynamics of CO2 Fluxes Measured with Eddy Covariance System in Maize, Winter Oilseed Rape and Winter Wheat Fields
by Robert Czubaszek and Agnieszka Wysocka-Czubaszek
Atmosphere 2023, 14(2), 372; https://doi.org/10.3390/atmos14020372 - 14 Feb 2023
Viewed by 1441
Abstract
The full understanding of variation and temporal changes in carbon dioxide (CO2) fluxes in cropland may contribute to a reduction in CO2 emissions from agriculture. The aim of this study was to determine the CO2 exchange intensity in the [...] Read more.
The full understanding of variation and temporal changes in carbon dioxide (CO2) fluxes in cropland may contribute to a reduction in CO2 emissions from agriculture. The aim of this study was to determine the CO2 exchange intensity in the three most popular crops in Poland. The CO2 fluxes in summer maize, winter oilseed rape and winter wheat fields were measured using the eddy covariance system. The seasonal dynamics of CO2 fluxes for all studied crops varied from each other due to individual dynamics in atmospheric CO2 assimilation of each species through the growing season. The weighted average values of CO2 fluxes calculated for the entire vegetation period were −22.22 µmol CO2 m−2 s−1, −14.27 µmol CO2 m−2 s−1 and −11.95 µmol CO2 m−2 s−1 for maize, oilseed rape and wheat, respectively. All the studied agro-ecosystems were carbon sinks during the growing season. The highest negative values of CO2 fluxes (−36.31 µmol CO2 m−2 s−1 and −33.56 µmol CO2 m−2 s−1) were observed in the maize field due to the high production of biomass. However, the maize field was also the most significant carbon source due to slow growth of plants at the beginning of the growing season, and due to leaving the field fallow after harvest until the next sowing. In these two periods, the CO2 fluxes ranged from 0.59 µmol CO2 m−2 s−1 to 3.72 µmol CO2 m−2 s−1. CO2 exchange over wheat and oilseed rape fields was less intense, but more even throughout the growing season. In the wheat field, the CO2 fluxes ranged from −1.70 µmol CO2 m−2 s−1 to −23.49 µmol CO2 m−2 s−1 and in the oilseed rape field they ranged from −1.40 µmol CO2 m−2 s−1 to −22.08 µmol CO2 m−2 s−1. In addition, the catch crop in the oilseed rape field contributed to the intensive absorption of CO2 after harvesting the main crop. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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13 pages, 9105 KiB  
Article
Health Impact Related to Ambient Particulate Matter Exposure as a Spatial Health Risk Map Case Study in Chiang Mai, Thailand
by Kannika Jarernwong, Shabbir H. Gheewala and Sate Sampattagul
Atmosphere 2023, 14(2), 261; https://doi.org/10.3390/atmos14020261 - 28 Jan 2023
Cited by 1 | Viewed by 4124
Abstract
Chiang Mai has been one of the most polluted cities globally, exceeding the PM2.5 quality standards for decades and facing hazardous air pollution on an annual basis. As ambient PM2.5 strongly affects human health, this study aims to investigate the hotspots [...] Read more.
Chiang Mai has been one of the most polluted cities globally, exceeding the PM2.5 quality standards for decades and facing hazardous air pollution on an annual basis. As ambient PM2.5 strongly affects human health, this study aims to investigate the hotspots of PM2.5 and health impact areas due to exposure to PM2.5 by illustrating a spatial distribution via a Chiang Mai health risk map. The association between PM2.5 concentration and human health impact were assessed using Pearson’s correlation, focused on the peak period from January to April 2021 in Chiang Mai. The primary data on PM2.5 concentration were collected using low-cost sensors. The health impact is based on the number of hospital admissions in all incidences of diseases due to PM2.5 exposure following the ICD-10. The results showed that the highest polluted and health-risk areas were located in the center of Chiang Mai, especially in the Mueang district. PM2.5 concentration was highly correlated with the incidence of dermatitis (R = 0.84), conjunctivitis (R = 0.81), stroke (R = 0.74), and lung cancer (R = 0.73). Thus, the increased PM2.5 concentration resulted in heightened hospital admissions. The results provide insightful information for policymakers and local public health organizations regarding priority areas in resource management. Full article
(This article belongs to the Special Issue Sources, Spatio-Temporal Distribution and Health Effects of Atmospheric Compositions)
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