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The 2nd Edition: Outdoor and Indoor Air Quality

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Air".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 4197

Special Issue Editors


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Guest Editor
Department of Biology, University of Bari Aldo Moro, 70126 Bari, Italy
Interests: atmospheric chemistry and modeling; aerosol science; Indoor Air Quality (IAQ); Volatile Organic Compounds (VOCs), Particulate Matter (PM); breath analysis; monitoring strategies; odors monitoring; emissions from materials; sensors network; PM chemical characterization; sustainability; environmental health
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Via Orabona 4, 70126 Bari, Italy
Interests: atmospheric pollution; indoor air quality (IAQ); volatile organic compounds (VOCs); particulate matter (PM); breath analysis; monitoring strategies; odors monitoring; emissions from materials and consumer products; primary and secondary pollutants; test emission chambers; sensors networks; PM chemical characterization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Biosciences, Biotechnologies and Environment, University “Aldo Moro”, Via Orabona 4, 70126 Bari, Italy
Interests: atmospheric chemistry and modeling; indoor air quality (IAQ); volatile organic compounds (VOCs); particulate matter (PM); breath analysis; monitoring strategies; odors monitoring; emissions from materials; sensors networks; PM chemical characterization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, increasing urbanization along with industrial development have remarkably contributed to particulate matter (PM) and gaseous pollutant concentration into the atmosphere. Epidemiological studies show a high correlation between inhalation exposure to atmospheric pollutants and increased incidence of respiratory diseases and cancer. In fact, it has been estimated that more than 8.0 million people worldwide are dying every year as a result of atmospheric pollution exposure. Overall exposure may be exacerbated in complex industrial and urban settlements where different anthropogenic sources coexist and synergistically affect air quality (power plants, industries, vehicle exhausts, combustion processes).

Conventional methodological approaches for air quality monitoring and control are based on the measurement and characterization of the main pollutants emitted by ducted emission sources and at fixed sites, as prescribed by EU legislation. These approaches, however, do not allow accurately discriminating among different emissive contributions to identify both short-term emission sources and fugitive emissions to monitor in real time the impact of pollutants on the surrounding area and to intervene in case of critical events through processing control and abatement strategies. Therefore, in addition to conventional approaches, the development of innovative methodological approaches providing high temporal and spatial resolution data should be promoted in order to improve air quality monitoring and to preserve public health. Inhalation exposure to pollutants of concern may occur both outdoors and indoors. In the last few decades, indeed, the use of synthetic materials in building and furnishing, the adoption of new lifestyles, the progressive isolation of buildings, and the extensive use of products for cleaning and personal hygiene have contributed to the deterioration of indoor air quality (IAQ) and introduced new sources of risk to humans. 

It is therefore a priority to evaluate both indoor and outdoor air quality in order to identify critical issues and risk factors for human health. Given the success of the first edition of the Special Issue “Outdoor and Indoor Air Quality” published in the International Journal of Environmental Research and Public Health (IJERPH)(https://www.mdpi.com/journal/ijerph/special_issues/out_in_Air), we would like to continue exploring this topic.  

Prof. Dr. Gianluigi de Gennaro
Dr. Jolanda Palmisani
Dr. Alessia Di Gilio
Guest Editors

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Keywords

  • VOCs
  • particulate matter
  • metals
  • odors
  • atmospheric pollution
  • indoor air quality
  • high resolution monitoring
  • remediation strategies
  • exposure assessment
  • environmental risk

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Published Papers (2 papers)

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Research

20 pages, 2957 KiB  
Article
Indoor Exposure and Regional Inhaled Deposited Dose Rate during Smoking and Incense Stick Burning—The Jordanian Case as an Example for Eastern Mediterranean Conditions
by Tareq Hussein
Int. J. Environ. Res. Public Health 2023, 20(1), 587; https://doi.org/10.3390/ijerph20010587 - 29 Dec 2022
Cited by 1 | Viewed by 1927
Abstract
Tobacco smoking and incense burning are commonly used in Jordanian microenvironments. While smoking in Jordan is prohibited inside closed spaces, incense burning remains uncontrolled. In this study, particle size distributions (diameter 0.01–25 µm) were measured and inhaled deposited dose rates were calculated during [...] Read more.
Tobacco smoking and incense burning are commonly used in Jordanian microenvironments. While smoking in Jordan is prohibited inside closed spaces, incense burning remains uncontrolled. In this study, particle size distributions (diameter 0.01–25 µm) were measured and inhaled deposited dose rates were calculated during typical smoking and incense stick-burning scenarios inside a closed room, and the exposure was summarized in terms of number and mass concentrations of submicron (PNSub) and fine particles (PM2.5). During cigarette smoking and incense stick-burning scenarios, the particle number concentrations exceeded 3 × 105 cm−3. They exceeded 5 × 105 cm−3 during shisha smoking. The emission rates were 1.9 × 1010, 6.8 × 1010, and 1.7 × 1010 particles/s, respectively, for incense, cigarettes, and shisha. That corresponded to about 7, 80, and 120 µg/s, respectively. Males received higher dose rates than females, with about 75% and 55% in the pulmonary/alveolar during walking and standing, respectively. The total dose rates were in the order of 1012–1013 #/h (103–104 µg/h), respectively, for PNSub and PM2.5. The above reported concentrations, emissions rates, and dose rates are considered seriously high, recalling the fact that aerosols emitted during such scenarios consist of a vast range of toxicant compounds. Full article
(This article belongs to the Special Issue The 2nd Edition: Outdoor and Indoor Air Quality)
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33 pages, 7185 KiB  
Article
Air Quality Modeling with the Use of Regression Neural Networks
by Szymon Hoffman, Mariusz Filak and Rafał Jasiński
Int. J. Environ. Res. Public Health 2022, 19(24), 16494; https://doi.org/10.3390/ijerph192416494 - 8 Dec 2022
Cited by 5 | Viewed by 1638
Abstract
Air quality is assessed on the basis of air monitoring data. Monitoring data are often not complete enough to carry out an air quality assessment. To fill the measurement gaps, predictive models can be used, which enable the approximation of missing data. Prediction [...] Read more.
Air quality is assessed on the basis of air monitoring data. Monitoring data are often not complete enough to carry out an air quality assessment. To fill the measurement gaps, predictive models can be used, which enable the approximation of missing data. Prediction models use historical data and relationships between measured variables, including air pollutant concentrations and meteorological factors. The known predictive air quality models are not accurate, so it is important to look for models that give a lower approximation error. The use of artificial neural networks reduces the prediction error compared to classical regression methods. In previous studies, a single regression model over the entire concentration range was used to approximate the concentrations of a selected pollutant. In this study, it was assumed that not a single model, but a group of models, could be used for the prediction. In this approach, each model from the group was dedicated to a different sub-range of the concentration of the modeled pollutant. The aim of the analysis was to check whether this approach would improve the quality of modeling. A long-term data set recorded at two air monitoring stations in Poland was used in the examination. Hourly data of basic air pollutants and meteorological parameters were used to create predictive regression models. The prediction errors for the sub-range models were compared with the corresponding errors calculated for one full-range regression model. It was found that the application of sub-range models reduced the modeling error of basic air pollutants. Full article
(This article belongs to the Special Issue The 2nd Edition: Outdoor and Indoor Air Quality)
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