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Applied Sciences
Special Issues
Exposure to Environmental Pollutants and Effects on Human Health
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Special Issue "Exposure to Environmental Pollutants and Effects on Human Health"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (30 May 2023) | Viewed by 2039

Special Issue Editor

Dr. Alessandro Borgini

E-Mail Website
Guest Editor
Environmental Epidemiology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
Interests: air quality; exposure assessment; air pollution health effects; air sampling; air pollution modeling; indoor air pollution; second-hand smoke exposure

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to the assessment of exposure to specific contaminants in different environmental matrices (air, water and soil), and to the acute and chronic human health effects on populations living in different areas (large cities, industrialized areas, etc.) exposed to the emissions and relative concentrations of different contaminants. Exposure to different levels of air pollution, such as atmospheric particulate matter (PM) at different granulometries (PM 10, PM 2.5, PM 1, PM 0.1); nitrogen oxides (NOx); volatile organic compounds (VOCs) like benzene, formaldehyde, tetrachloroethylene, toluene, xylene, and 1,3-butadiene; black carbon; polycyclic aromatic hydrocarbons (PAHs); and many other persistent organic contaminants in the environment can cause a variety of adverse health outcomes. This exposure can increase the risk of respiratory infections, heart disease, and lung cancer. Both short- and long-term exposure to air pollutants have been associated with health impacts. More severe impacts affect people who are already ill. In this Special Issue it is important to evaluate the correlation of the exposure to pollutants (short- and long-term) to determine the main health risks for citizens in a given territory, such as mortality, various diseases of the respiratory or cardiovascular system, etc.

Dr. Alessandro Borgini
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2300 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.

Published Papers (2 papers)

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Research

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Article
Activity Prediction Based on Deep Learning Techniques
by
Jinsoo Park
,
Chiyou Song
,
Mingi Kim
and
Sungroul Kim
Appl. Sci. 2023, 13(9), 5684; https://doi.org/10.3390/app13095684 - 05 May 2023
Viewed by 598
Abstract
Studies on real-time PM2.5 concentrations per activity in microenvironments are gaining a lot of attention due to their considerable impact on health. These studies usually assume that information about human activity patterns in certain environments is known beforehand. However, if a person’s [...] Read more.
Studies on real-time PM2.5 concentrations per activity in microenvironments are gaining a lot of attention due to their considerable impact on health. These studies usually assume that information about human activity patterns in certain environments is known beforehand. However, if a person’s activity pattern can be inferred reversely using environmental information, it can be easier to access the levels of PM2.5 concentration that affect human health. This study collected the actual data necessary for this purpose and designed a deep learning algorithm that can infer human activity patterns reversely using the collected dataset. The dataset was collected based on a realistic scenario, which includes activity patterns in both indoor and outdoor environments. The deep learning models used include the well-known multilayer perception (MLP) model and a long short-term memory (LSTM) model. The performance of the designed deep learning algorithm was evaluated using training and test data. Simulation results showed that the LSTM model has a higher average test accuracy of more than 15% compared to the MLP model, and overall, we were able to achieve high accuracy of over 90% on average. Full article
(This article belongs to the Special Issue Exposure to Environmental Pollutants and Effects on Human Health)
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Article
Air Quality Integrated Assessment: Environmental Impacts, Risks and Human Health Hazards
by
Ioana Tanasa
,
Marius Cazacu
and
Brindusa Sluser
Appl. Sci. 2023, 13(2), 1222; https://doi.org/10.3390/app13021222 - 16 Jan 2023
Cited by 1 | Viewed by 983
Abstract
The monitoring and evaluation of air quality is a topic of great global interest as, with the decline of air quality, there are negative effects on human health and ecosystems. Thus, the purpose of this paper was to evaluate the air quality over [...] Read more.
The monitoring and evaluation of air quality is a topic of great global interest as, with the decline of air quality, there are negative effects on human health and ecosystems. Thus, the purpose of this paper was to evaluate the air quality over 11 years, in the period 2011–2021, in four cities in Romania, reported as most polluted, namely, Brasov, Cluj-Napoca, Iasi, and Timisoara. Pollutants of interest included arsenic, carbon monoxide, and PM2.5. The measured concentrations of the selected pollutants were collected from the National Environmental Protection Agency public reports. The database considered the daily measurements for the selected pollutants, from three monitoring stations in each city so that the air quality and trends for the last 11 years and impact assessment could be developed. Therefore, the input data were statistically analyzed to identify the trends of air quality, and then, on this basis, the environmental impacts and risks and health hazards were quantified. High concentrations of PM2.5 were recorded for Iasi city, while for Timisoara city, significant concentrations of arsenic were reported. The results regarding the air quality aggregate index, air pollution index, and health hazard index were in the regular range, but in the case of sensitive, vulnerable targets such as children, they were triple compared to adults. The results show that the alert threshold value for PM2.5 was exceeded every year in all four cities, while in the case of Timisoara city, the arsenic air pollution proved to be at a significant level with a major risk for human health. Full article
(This article belongs to the Special Issue Exposure to Environmental Pollutants and Effects on Human Health)
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