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Atmosphere
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Assessing Atmospheric Pollution and Its Impacts on the Human Health
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Assessing Atmospheric Pollution and Its Impacts on the Human Health

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

Deadline for manuscript submissions: closed (1 December 2021) | Viewed by 24843

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Alina Barbulescu

E-Mail Website
Guest Editor
Department of Civil Engineering, Transilvania University of Brașov, 5, Turnului Street, 900152 Brașov, Romania
Interests: hydrology; time series analysis; applied statistics; mathematical modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, atmospheric pollution is one of the main threats to the environment and human health. Under conditions of urbanization and industrial expansion, the reduction of pollution is an important direction to be followed by governments and populations worldwide. This issue will focus on new techniques for estimating, modeling, and forecasting atmospheric pollution and its impacts on human health. We invite authors to submit original research papers and review articles with the following topics:

  • Estimating air quality using statistical and artificial intelligence methods;
  • Monitoring and forecasting of pollution dynamics at local and regional scales using statistical, geostatistical, and artificial intelligence methods;
  • Emphazing the impacts of atmospheric pollution on human health;
  • Proposing new tools and indicators for assessing air quality;
  • Assessing the pollution risk to human health using statistical methods;
  • Related topics.

Prof. Dr. Alina Barbulescu
Guest Editor

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 quality
  • Risk assessment
  • Spatiotemporal variation
  • Statistical methods
  • Artificial intelligence methods
  • Health risk

Published Papers (11 papers)

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Editorial

Jump to: Research

4 pages, 207 KiB  
Editorial
Assessing Atmospheric Pollution and Its Impact on the Human Health
by Alina Bărbulescu, Cristian Ștefan Dumitriu and Nicolae Popescu-Bodorin
Atmosphere 2022, 13(6), 938; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060938 - 09 Jun 2022
Cited by 1 | Viewed by 1614
Abstract
In recent decades, atmospheric pollution has become a major risk for public health and ecosystems [...] Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)

Research

Jump to: Editorial

14 pages, 4941 KiB  
Article
The Impact of Air Pollution on Pulmonary Diseases: A Case Study from Brasov County, Romania
by Carmen Maftei, Radu Muntean and Ionut Poinareanu
Atmosphere 2022, 13(6), 902; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060902 - 02 Jun 2022
Cited by 12 | Viewed by 2781
Abstract
Air pollution is considered one of the most significant risk factors for human health. To ensure air quality and prevent and reduce the harmful impact on human health, it is necessary to identify and measure the main air pollutants (sulfur and nitrogen oxides, [...] Read more.
Air pollution is considered one of the most significant risk factors for human health. To ensure air quality and prevent and reduce the harmful impact on human health, it is necessary to identify and measure the main air pollutants (sulfur and nitrogen oxides, PM10 and PM2.5 particles, lead, benzene, carbon monoxide, etc.), their maximum values, as well as the impact they have on mortality/morbidity rates caused by respiratory diseases. This paper aims to assess the influence of air pollution on respiratory diseases based on an analysis of principal pollutants and mortality/morbidity data sets. In this respect, four types of data are used: pollution sources inventory, air quality data sets, mortality/morbidity data at the local and national level, and clinical data of patients diagnosed with different forms of lung malignancies. The results showed an increased number of deaths caused by respiratory diseases for the studied period, correlated with the decreased air quality due to industrial and commercial activities, households, transportation, and energy production. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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12 pages, 2082 KiB  
Article
On the Spatio-Temporal Characteristics of Aerosol Optical Depth in the Arabian Gulf Zone
by Alina Bărbulescu
Atmosphere 2022, 13(6), 857; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060857 - 24 May 2022
Cited by 3 | Viewed by 1327
Abstract
The article investigates some of the available measurements (Terra MODIS satellite data) of the aerosol optical depth (AOD) taken in the Arabian Gulf, a zone traditionally affected by intense sand-related (or even sand-driven) meteorological events. The Principal Component Analysis (PCA) reveals the main [...] Read more.
The article investigates some of the available measurements (Terra MODIS satellite data) of the aerosol optical depth (AOD) taken in the Arabian Gulf, a zone traditionally affected by intense sand-related (or even sand-driven) meteorological events. The Principal Component Analysis (PCA) reveals the main subspace of the data. Clustering of the series was performed after selecting the optimal number of groups using 30 different methods, such as the silhouette, gap, Duda, Dunn, Hartigan, Hubert, etc. The AOD regional and temporal tendency detection was completed utilizing an original algorithm based on the dominant cluster found at the previous stage, resulting in the regional time series (RTS) and temporal time series (TTS). It was shown that the spatially-indexed time series (SITS) agglomerates along with the first PC. In contrast, six PCs are responsible for 60.5% of the variance in the case of the temporally-indexed time series (TITS). Both RTS and TTS are stationary in trend and fit the studied data series set well. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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25 pages, 10911 KiB  
Article
Influence of Anomalies on the Models for Nitrogen Oxides and Ozone Series
by Alina Bărbulescu, Cristian Stefan Dumitriu, Iulia Ilie and Sebastian-Barbu Barbeş
Atmosphere 2022, 13(4), 558; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13040558 - 30 Mar 2022
Cited by 9 | Viewed by 1652
Abstract
Nowadays, observing, recording, and modeling the dynamics of atmospheric pollutants represent actual study areas given the effects of pollution on the population and ecosystems. The existence of aberrant values may influence reports on air quality when they are based on average values over [...] Read more.
Nowadays, observing, recording, and modeling the dynamics of atmospheric pollutants represent actual study areas given the effects of pollution on the population and ecosystems. The existence of aberrant values may influence reports on air quality when they are based on average values over a period. This may also influence the quality of models, which are further used in forecasting. Therefore, correct data collection and analysis is necessary before modeling. This study aimed to detect aberrant values in a nitrogen oxide concentration series recorded in the interval 1 January–8 June 2016 in Timisoara, Romania, and retrieved from the official reports of the National Network for Monitoring the Air Quality, Romania. Four methods were utilized, including the interquartile range (IQR), isolation forest, local outlier factor (LOF) methods, and the generalized extreme studentized deviate (GESD) test. Autoregressive integrated moving average (ARIMA), Generalized Regression Neural Networks (GRNN), and hybrid ARIMA-GRNN models were built for the series before and after the removal of aberrant values. The results show that the first approach provided a good model (from a statistical viewpoint) for the series after the anomalies removal. The best model was obtained by the hybrid ARIMA-GRNN. For example, for the raw NO2 series, the ARIMA model was not statistically validated, whereas, for the series without outliers, the ARIMA(1,1,1) was validated. The GRNN model for the raw series was able to learn the data well: R2 = 76.135%, the correlation between the actual and predicted values (rap) was 0.8778, the mean standard errors (MSE) = 0.177, the mean absolute error MAE = 0.2839, and the mean absolute percentage error MAPE = 9.9786. Still, on the test set, the results were worse: MSE = 1.5101, MAE = 0.8175, rap = 0.4482. For the series without outliers, the model was able to learn the data in the training set better than for the raw series (R2 = 0.996), whereas, on the test set, the results were not very good (R2 = 0.473). The performances of the hybrid ARIMA–GRNN on the initial series were not satisfactory on the test (the pattern of the computed values was almost linear) but were very good on the series without outliers (the correlation between the predicted values on the test set was very close to 1). The same was true for the models built for O3. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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17 pages, 6422 KiB  
Article
Study of Atmospheric Pollution and Health Risk Assessment: A Case Study for the Sharjah and Ajman Emirates (UAE)
by Yousef Nazzal, Nadine Bou Orm, Alina Barbulescu, Fares Howari, Manish Sharma, Alaa E. Badawi, Ahmed A. Al-Taani, Jibran Iqbal, Farid El Ktaibi, Cijo M. Xavier and Cristian Stefan Dumitriu
Atmosphere 2021, 12(11), 1442; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12111442 - 01 Nov 2021
Cited by 14 | Viewed by 3328
Abstract
Dust is a significant pollution source in the United Arab Emirates (UAE) that impacts population health. Therefore, the present study aims to determine the concentration of heavy metals (Cd, Pb, Cr, Cu, Ni, and Zn) in the air in the Sharjah and Ajman [...] Read more.
Dust is a significant pollution source in the United Arab Emirates (UAE) that impacts population health. Therefore, the present study aims to determine the concentration of heavy metals (Cd, Pb, Cr, Cu, Ni, and Zn) in the air in the Sharjah and Ajman emirates’ urban areas and assesses the health risk. Three indicators were used for this purpose: the average daily dose (ADD), the hazard quotient (HQ), and the health index (HI). Data were collected during the period April–August 2020. Moreover, the observation sites were clustered based on the pollutants’ concentration, given that the greater the heavy metal concentration is, the greater is the risk for the population health. The most abundant heavy metal found in the atmosphere was Zn, with a mean concentration of 160.30 mg/kg, the concentrations of other metals being in the following order: Ni > Cr > Cu > Pb > Cd. The mean concentrations of Cd, Pb, and Cr were within the range of background values, while those of Cu, Ni, and Zn were higher than the background values, indicating anthropogenic pollution. For adults, the mean ADD values of heavy metals decreased from Zn to Cd (Zn > Ni > Cr > Cu > Pb > Cd). The HQ (HI) suggested an acceptable (negligible) level of non-carcinogenic harmful health risk to residents’ health. The sites were grouped in three clusters, one of them containing a single location, where the highest concentrations of heavy metals were found. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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21 pages, 2580 KiB  
Article
Unorganized Machines to Estimate the Number of Hospital Admissions Due to Respiratory Diseases Caused by PM10 Concentration
by Yara de Souza Tadano, Eduardo Tadeu Bacalhau, Luciana Casacio, Erickson Puchta, Thomas Siqueira Pereira, Thiago Antonini Alves, Cássia Maria Lie Ugaya and Hugo Valadares Siqueira
Atmosphere 2021, 12(10), 1345; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12101345 - 14 Oct 2021
Cited by 6 | Viewed by 1712
Abstract
The particulate matter PM10 concentrations have been impacting hospital admissions due to respiratory diseases. The air pollution studies seek to understand how this pollutant affects the health system. Since prediction involves several variables, any disparity causes a disturbance in the overall system, [...] Read more.
The particulate matter PM10 concentrations have been impacting hospital admissions due to respiratory diseases. The air pollution studies seek to understand how this pollutant affects the health system. Since prediction involves several variables, any disparity causes a disturbance in the overall system, increasing the difficulty of the models’ development. Due to the complex nonlinear behavior of the problem and their influencing factors, Artificial Neural Networks are attractive approaches for solving estimations problems. This paper explores two neural network architectures denoted unorganized machines: the echo state networks and the extreme learning machines. Beyond the standard forms, models variations are also proposed: the regularization parameter (RP) to increase the generalization capability, and the Volterra filter to explore nonlinear patterns of the hidden layers. To evaluate the proposed models’ performance for the hospital admissions estimation by respiratory diseases, three cities of São Paulo state, Brazil: Cubatão, Campinas and São Paulo, are investigated. Numerical results show the standard models’ superior performance for most scenarios. Nevertheless, considering divergent intensity in hospital admissions, the RP models present the best results in terms of data dispersion. Finally, an overall analysis highlights the models’ efficiency to assist the hospital admissions management during high air pollution episodes. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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16 pages, 3775 KiB  
Article
Multi-Media Exposure to Polycyclic Aromatic Hydrocarbons at Lake Chaohu, the Fifth Largest Fresh Water Lake in China: Residual Levels, Sources and Carcinogenic Risk
by Ning Qin, Wei He, Qishuang He, Xiangzhen Kong, Wenxiu Liu, Qin Wang and Fuliu Xu
Atmosphere 2021, 12(10), 1241; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12101241 - 23 Sep 2021
Cited by 3 | Viewed by 2323
Abstract
The residual levels of 16 priority polycyclic aromatic hydrocarbons (PAHs) in environment media and freshwater fish were collected and measured from Lake Chaohu by using Gas chromatography-mass spectrometry. Potential atmospheric sources were identified by molecular diagnostic ratios and the positive matrix factorization (PMF) [...] Read more.
The residual levels of 16 priority polycyclic aromatic hydrocarbons (PAHs) in environment media and freshwater fish were collected and measured from Lake Chaohu by using Gas chromatography-mass spectrometry. Potential atmospheric sources were identified by molecular diagnostic ratios and the positive matrix factorization (PMF) method. PAH exposure doses through inhalation, intake of water and freshwater fish ingestion were estimated by the assessment model recommended by US EPA. The carcinogenic risks of PAH exposure were evaluated by probabilistic risk assessment and Monte Carlo simulation. The following results were obtained: (1) The PAH16 levels in gaseous, particulate phase, water and fish muscles were 59.4 ng·m−3, 14.2 ng·m−3, 170 ng·L−1 and 114 ng·g−1, respectively. No significant urban-rural difference was found between two sampling sites except gaseous BaPeq. The relationship between gaseous PAHs and PAH in water was detected by the application of Spearman correlation analysis. (2) Three potential sources were identified by the PMF model. The sources from biomass combustions, coal combustion and vehicle emission accounted for 43.6%, 30.6% and 25.8% of the total PAHs, respectively. (3) Fish intake has the highest lifetime average daily dose (LADD) of 3.01 × 10−6 mg·kg−1·d−1, followed by the particle inhalation with LADD of 2.94 × 10−6 mg·kg−1·d−1. (4) As a result of probabilistic cancer risk assessment, the median ILCRs were 3.1 × 10−5 to 3.3 × 10−5 in urban and rural residents, which were lower than the suggested serious level but higher than the acceptable level. In summary, the result suggests that potential carcinogenic risk exists among residents around Lake Chaohu. Fish ingestion and inhalation are two major PAH exposure pathways. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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17 pages, 3643 KiB  
Article
Levels, Sources, and Health Damage of Dust in Grain Transportation and Storage: A Case Study of Chinese Grain Storage Companies
by Pengcheng Cui, Tao Zhang, Xin Chen and Xiaoyi Yang
Atmosphere 2021, 12(8), 1025; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12081025 - 11 Aug 2021
Cited by 4 | Viewed by 2589
Abstract
A large amount of mixed dust exists in grain, which can easily stimulate the respiratory system and cause diseases. This study explored contamination levels and health effects of this grain dust. A total of 616 dust samples from different stages and types of [...] Read more.
A large amount of mixed dust exists in grain, which can easily stimulate the respiratory system and cause diseases. This study explored contamination levels and health effects of this grain dust. A total of 616 dust samples from different stages and types of grain were collected in China—in Hefei (Anhui), Shenzhen (Guangdong), Chengdu (Sichuan), Changchun (Jilin), and Shunyi (Beijing)—and analyzed using the filter membrane method and a laser particle size analyzer. A probabilistic risk assessment model was developed to explore the health effects of grain dust on workers in the grain storage industry based on the United States Environmental Protection Agency risk assessment model and the Monte Carlo simulation method. Sensitivity analysis methods were used to analyze the various exposure parameters and influencing factors that affect the health risk assessment results. This assessment model was applied to translate health risks into disability-adjusted life years (DALY). The results revealed that the concentration of dust ranged from 25 to 70 mg/m3, which followed normal distribution and the proportion of dust with a particle size of less than 10 μm exceeded 10%. Workers in the transporting stage were exposed to the largest health risk, which followed a lognormal distribution. The average health risks for workers in the entering and exiting zones were slightly below 2.5 × 10−5. The sensitivity analysis indicated that average time, exposure duration, inhalation rate, and dust concentration made great contributions to dust health risk. Workers in the grain storage and transportation stage had the health damage, and the average DALY exceeded 0.4 years. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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20 pages, 2959 KiB  
Article
The Influence of Transport on PAHs and Other Carbonaceous Species’ (OC, EC) Concentration in Aerosols in the Coastal Zone of the Gulf of Gdansk (Gdynia)
by Joanna Klaudia Buch, Anita Urszula Lewandowska, Marta Staniszewska, Kinga Areta Wiśniewska and Karolina Venessa Bartkowski
Atmosphere 2021, 12(8), 1005; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12081005 - 05 Aug 2021
Cited by 4 | Viewed by 1656
Abstract
The aim of this study was to determine the influence of transport on the concentration of carbon species in aerosols collected in the coastal zone of the Gulf of Gdansk in the period outside the heating season. Elemental carbon (EC), organic carbon (OC), [...] Read more.
The aim of this study was to determine the influence of transport on the concentration of carbon species in aerosols collected in the coastal zone of the Gulf of Gdansk in the period outside the heating season. Elemental carbon (EC), organic carbon (OC), and the ΣPAHs5 concentrations were measured in aerosols of two size: <3 μm (respirable aerosols) and >3 μm in diameter (inhalable aerosols). Samples were collected between 13 July 2015 and 22 July 2015 (holiday period) and between 14 September 2015 and 30 September 2015 (school period). In both periods samples were taken only during the morning (7:00–9:00 a.m.) and afternoon (3:00–5:00 p.m.) road traffic hours. The highest mean values of the ΣPAHs5 and EC were recorded in small particles during the school period in the morning road traffic peak hours. The mean concentration of OC was the highest in small aerosols during the holiday period. However, there were no statistically significant differences between the concentrations of organic carbon in the morning and afternoon peak hours. Strict sampling and measurement procedures, together with the analysis of air mass backward trajectories and pollutant markers, indicated that the role of land transport was the greatest when local to regional winds prevailed, bringing pollution from nearby schools and the beltway. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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13 pages, 2160 KiB  
Article
Characteristics of Particulate Matter at Different Pollution Levels in Chengdu, Southwest of China
by Yi Huang, Li Wang, Xin Cheng, Jinjin Wang, Ting Li, Min He, Huibin Shi, Meng Zhang, Scott S. Hughes and Shijun Ni
Atmosphere 2021, 12(8), 990; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12080990 - 31 Jul 2021
Cited by 7 | Viewed by 2025
Abstract
Air pollution is becoming increasingly serious along with social and economic development in the southwest of China. The distribution characteristics of particle matter (PM) were studied in Chengdu from 2016 to 2017, and the changes of PM bearing water-soluble ions and heavy metals [...] Read more.
Air pollution is becoming increasingly serious along with social and economic development in the southwest of China. The distribution characteristics of particle matter (PM) were studied in Chengdu from 2016 to 2017, and the changes of PM bearing water-soluble ions and heavy metals and the distribution of secondary ions were analyzed during the haze episode. The results showed that at different pollution levels, heavy metals were more likely to be enriched in fine particles and may be used as a tracer of primary pollution sources. The water-soluble ions in PM2.5 were mainly Sulfate-Nitrate-Ammonium (SNA) accounting for 43.02%, 24.23%, 23.50%, respectively. SO42−, NO3−, NH4+ in PM10 accounted for 34.56%, 27.43%, 19.18%, respectively. It was mainly SO42− in PM at Clean levels (PM2.5 = 0~75 μg/m3, PM10 = 0~150 μg/m3), and mainly NH4+ and NO3− at Light-Medium levels (PM2.5 = 75~150 μg/m3, PM10 = 150~350 μg/m3). At Heavy levels (PM2.5 = 150~250 μg/m3, PM10 = 350~420 μg/m3), it is mainly SO42− in PM2.5, and mainly NH4+ and NO3− in PM10. The contribution of mobile sources to the formation of haze in the study area was significant. SNA had significant contributions to the PM during the haze episode, and more attention should be paid to them in order to improve air quality. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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16 pages, 315 KiB  
Article
Chemical Composition of PM2.5 in Wood Fire and LPG Cookstove Homes of Nepali Brick Workers
by James D. Johnston, John D. Beard, Emma J. Montague, Seshananda Sanjel, James H. Lu, Haley McBride, Frank X. Weber and Ryan T. Chartier
Atmosphere 2021, 12(7), 911; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12070911 - 15 Jul 2021
Cited by 5 | Viewed by 2290
Abstract
Household air pollution is a major cause of morbidity and mortality worldwide, largely due to particles ≤ 2.5 µm (PM2.5). The toxicity of PM2.5, however, depends on its physical properties and chemical composition. In this cross-sectional study, we compared [...] Read more.
Household air pollution is a major cause of morbidity and mortality worldwide, largely due to particles ≤ 2.5 µm (PM2.5). The toxicity of PM2.5, however, depends on its physical properties and chemical composition. In this cross-sectional study, we compared the chemical composition of PM2.5 in brick workers’ homes (n = 16) based on use of wood cooking fire or liquefied petroleum gas (LPG) cookstoves. We collected samples using RTI International particulate matter (PM) exposure monitors (MicroPEMs). We analyzed filters for 33 elements using energy-dispersive X-ray fluorescence and, for black (BC) and brown carbon (BrC), integrating sphere optical transmittance. Wood fire homes had significantly higher concentrations of BC (349 µg/m3) than LPG homes (6.27 µg/m3, p < 0.0001) or outdoor air (5.36 µg/m3, p = 0.002). Indoor chlorine in wood fire homes averaged 5.86 µg/m3, which was approximately 34 times the average level in LPG homes (0.17 µg/m3, p = 0.0006). Similarly, potassium in wood fire homes (4.17 µg/m3) was approximately four times the level in LPG homes (0.98 µg/m3, p = 0.001). In all locations, we found aluminum, calcium, copper, iron, silicon, and titanium in concentrations exceeding those shown to cause respiratory effects in other studies. Our findings suggest the need for multi-faceted interventions to improve air quality for brick workers in Nepal. Full article
(This article belongs to the Special Issue Assessing Atmospheric Pollution and Its Impacts on the Human Health)
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