Environmental Contamination and Human Health

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

Deadline for manuscript submissions: 20 August 2024 | Viewed by 6423

Special Issue Editors


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Guest Editor
Interdisciplinary Department of Medicine, Hygiene Section, University of Bari Aldo Moro, Piazza G. Cesare 11, 70124 Bari, Italy
Interests: waste management; hygiene and public health; data analysis and statistical modeling
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Interdisciplinary Department of Medicine, Hygiene Section, University of Bari Aldo Moro, Piazza G. Cesare 11, 70124 Bari, Italy
Interests: infectious disease epidemiology; water hygiene; environmental health; public health; Legionella; waterborne diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human health can be influenced by many factors, including exposure to physical, chemical, biological, and radiological contaminants in all kinds of environmental matrices (soil, water, and air).

Between 2030 and 2050, climate change is expected to cause approximately 250,000 additional deaths per year, from malnutrition, malaria, diarrhoea, and heat stress alone. The direct damage costs to health is estimated to be between USD 2–4 billion per year by 2030 (WHO).

Therefore, elaborate assessment of environmental/human health risks are urgently needed.

Manuscripts addressing these themes are invited for this Special Issue, especially those can deliver novel data both quantitative and qualitative assessment framework, to prevent risks of environmental contamination and human health.

Dr. Fabrizio Fasano
Dr. Osvalda De Giglio
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. 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 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

  • quantitative and qualitative assessment
  • environmental health risks
  • human health risks
  • risk characterization
  • health and environmental prevention
  • multivariate analysis
  • machine and deep learning
  • SARS-CoV-2
  • legionella

Published Papers (5 papers)

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Research

17 pages, 14432 KiB  
Article
Influence of Building Height Variation on Air Pollution Dispersion in Different Wind Directions: A Numerical Simulation Study
by Jiaye Pan and Jinnan Ji
Appl. Sci. 2024, 14(3), 979; https://doi.org/10.3390/app14030979 - 23 Jan 2024
Viewed by 554
Abstract
Due to the rapid advancement of urbanization, traffic–related pollutants in street canyons have emerged as the primary source of PM2.5, adversely impacting residents’ health. Therefore, it is necessary to reduce PM2.5 concentrations. In this study, a three–dimensional steady–state simulation was [...] Read more.
Due to the rapid advancement of urbanization, traffic–related pollutants in street canyons have emerged as the primary source of PM2.5, adversely impacting residents’ health. Therefore, it is necessary to reduce PM2.5 concentrations. In this study, a three–dimensional steady–state simulation was conducted using Computational Fluid Dynamics (CFD). Three representative wind directions (θ = 0°, 45°, and 90°, corresponding to parallel, oblique, and perpendicular winds) and five different building height ratios (BHR = 0.25, 0.5, 1, 2, and 4) were used to explore the effect of building height variations on PM2.5 dispersion within street canyons. The results indicated that wind direction significantly influenced PM2.5 dispersion (p < 0.001). As θ increased (θ = 0°, 45°, and 90°), PM2.5 concentration in the canyon increased, reaching the most severe pollution under perpendicular wind. Building height variations had a minor impact compared to wind direction, but differences in PM2.5 concentration were still observed among various BHRs. Specifically, under parallel wind, the influence of BHR on PM2.5 dispersion was relatively small as compared to oblique and perpendicular winds. For oblique wind, PM2.5 concentrations varied based on BHR. Street canyons composed of low–rise or multi–story buildings (BHR = 0.25 or 4) slightly increased PM2.5 concentrations within the canyon, while the lowest PM2.5 concentration was observed at a BHR of 0.5. Under perpendicular wind, symmetrical (BHR = 1) and step–down canyons (BHR = 2 and 4) exhibited comparable peak concentrations of PM2.5, whereas step–up canyons (BHR = 0.25 and 0.5) showed relatively lower concentrations. Full article
(This article belongs to the Special Issue Environmental Contamination and Human Health)
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13 pages, 1036 KiB  
Article
The Safe Return of Face-to-Face Teaching in the Post-COVID-19 Era at a University in Southern Italy: Surface Monitoring as an Early Warning System
by Osvalda De Giglio, Francesco Triggiano, Francesca Apollonio, Canio Buonavoglia, Loredana Capozzi, Michele Camero, Giuseppe Colafemmina, Raffaele Del Prete, Fabrizio Fasano, Gianvito Lanave, Helena Mateos, Lorenzo Pace, Adriana Mosca, Gerardo Palazzo, Antonio Parisi, Pasquale Stefanizzi, Valentina Terio, Silvio Tafuri and Maria Teresa Montagna
Appl. Sci. 2023, 13(24), 13214; https://doi.org/10.3390/app132413214 - 13 Dec 2023
Viewed by 616
Abstract
Environmental monitoring for SARS-CoV-2 has become a useful adjunct to clinical testing because it is widely available and relatively inexpensive. During the period May–December 2022 (spring–summer: May–September–autumn: October–December), we assessed the presence and viability of the virus on surfaces in university settings in [...] Read more.
Environmental monitoring for SARS-CoV-2 has become a useful adjunct to clinical testing because it is widely available and relatively inexpensive. During the period May–December 2022 (spring–summer: May–September–autumn: October–December), we assessed the presence and viability of the virus on surfaces in university settings in the Apulia region (Southern Italy) after the resumption of face-to-face teaching activities and evaluated surface monitoring as an early warning system. The sampling plan provided for the selection of 75% of the surface types (e.g., student and teacher desks, computer, handrail) in different materials (plasticized wood, wood, metal, plastic) present in different environments. Overall, 5.4% of surfaces (all students’ desks) resulted in positive with RT-PCR and negative with viral culture. Greater contamination was found in the spring–summer period than in the autumn (χ2 test with Yates correction = 7.6003; p-value = 0.006). The Poisson regression model showed a direct association between the average number of COVID-19 cases among university students in the seven days following sampling and the percentage of SARS-CoV-2 positive swabs on sampling day and (Intercept = 5.32498; β = 0.01847; p < 0.001). Our results show that environmental monitoring for SARS-CoV-2, especially in crowded settings such as universities, could be a useful tool for early warning, even after the end of the COVID-19 emergency. Full article
(This article belongs to the Special Issue Environmental Contamination and Human Health)
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23 pages, 3475 KiB  
Article
Prediction and Comparison of In-Vehicle CO2 Concentration Based on ARIMA and LSTM Models
by Jie Han, Han Lin and Zhenkai Qin
Appl. Sci. 2023, 13(19), 10858; https://doi.org/10.3390/app131910858 - 29 Sep 2023
Cited by 2 | Viewed by 935
Abstract
An increase in the carbon dioxide (CO2) concentration within a vehicle can lead to a decrease in air quality, resulting in numerous adverse effects on the human body. Therefore, it is very important to know the in-vehicle CO2 concentration level [...] Read more.
An increase in the carbon dioxide (CO2) concentration within a vehicle can lead to a decrease in air quality, resulting in numerous adverse effects on the human body. Therefore, it is very important to know the in-vehicle CO2 concentration level and to accurately predict a concentration change. The purpose of this research is to investigate in-vehicle concentration levels of CO2, comparing the accuracy of an autoregressive integrated moving average (ARIMA) model and a long short-term memory (LSTM) model in predicting the change in CO2 concentration. We conducted a field test to obtain in-vehicle original concentration data of CO2 while driving, establishing a prediction model of CO2 concentration with ARIMA and LSTM. We selected mean absolute percentage error (MAPE) and root mean squared error (RMSE) as the evaluation indicators. The findings indicate the following: (1) With the vehicle windows closed and recirculation ventilation mode activated, in-vehicle CO2 concentration increases rapidly. During testing, CO2 accumulation rates were measured at 1.43 ppm/s for one occupant and 3.52 ppm/s for three occupants within a 20 min driving period. Average concentrations exceeded 1000 ppm, so it is recommended to improve ventilation promptly while driving. (2) The MAPE of ARIMA and LSTM prediction results are 0.46% and 0.56%, respectively. The RMSE results are 19.62 ppm and 22.76 ppm, respectively. The prediction results demonstrate that both models effectively forecast changes in a vehicle’s interior environment CO2, but the prediction accuracy of ARIMA is better than that of LSTM. The research findings provide theoretical guidance to traffic safety managers in selecting suitable models for predicting in-vehicle CO2 concentrations and establish an effective in-vehicle ventilation warning control system. Full article
(This article belongs to the Special Issue Environmental Contamination and Human Health)
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16 pages, 3132 KiB  
Article
Bacteria Filtration Efficiency for Different Types of Protective Face Masks
by Željko Linšak, Lucija Ražov, Nikolina Furlan, Gabrijela Begić, Sandra Pavičić Žeželj, Goran Crvelin, Dalibor Broznić and Dijana Tomić Linšak
Appl. Sci. 2023, 13(10), 5972; https://doi.org/10.3390/app13105972 - 12 May 2023
Viewed by 1465
Abstract
Emerging infectious diseases that we are witnessing in the modern age are among the leading public health concerns. They most often occur in the form of epidemics or pandemics, and they have not been sufficiently researched. Owing to the current coronavirus disease 2019 [...] Read more.
Emerging infectious diseases that we are witnessing in the modern age are among the leading public health concerns. They most often occur in the form of epidemics or pandemics, and they have not been sufficiently researched. Owing to the current coronavirus disease 2019 (COVID-19) pandemic, the World Health Organization has published various recommendations to prevent the spread of this communicable disease, including a recommendation to wear protective facial masks. Therefore, this study aimed to determine the filtration effectiveness of bacteria, yeasts, and molds on three different commonly and commercially available masks used in children’s educational institutions. In addition, the bacterial content of indoor air bioaerosols was identified. The genera Staphylococcus and Micrococcus were dominant in all samples, whereas bacteria of the genera Bacillus, Acinetobacter, and Corynebacterium were identified at a significantly smaller number. Bacterial, yeast, and mold filtering effectiveness increased from the single-layer cloth mask, which proved to be the least effective, to the surgical mask, to the filtering facepiece type 2 (FFP2) mask. Furthermore, surveys are needed to study the effectiveness of protective measures. Full article
(This article belongs to the Special Issue Environmental Contamination and Human Health)
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26 pages, 5285 KiB  
Article
Lithium Metal: The Key to Green Transportation
by Philemon Lindagato, Yongjun Li, Jan Macháček, Gaoxue Yang, Irénée Mungwarakarama, Anastase Ndahimana and Henri Patrick Kanimba Ntwali
Appl. Sci. 2023, 13(1), 405; https://doi.org/10.3390/app13010405 - 28 Dec 2022
Cited by 6 | Viewed by 2124
Abstract
Lithium is a chemical element on the cutting edge due to its lithium-ion batteries used in both electronics and electric vehicles. The emerging use of lithium-ion batteries in electric vehicles comes as a promising solution to sustain green transportation. The implications of green [...] Read more.
Lithium is a chemical element on the cutting edge due to its lithium-ion batteries used in both electronics and electric vehicles. The emerging use of lithium-ion batteries in electric vehicles comes as a promising solution to sustain green transportation. The implications of green transportation could be understood by exploring lithium production and its application concepts. This article expands on those concepts by discussing the lithium supply and how vital lithium is to green technology. Statistical analysis has been applied to determine: (1) The degree of balance and interdependence between lithium raw materials and electric vehicle production, (2) the influence of electric vehicle demand on lithium production, and (3) the contribution of electric vehicles to reducing carbon emissions from road transport. This study provides necessary information on the availability and demand for lithium, which could be the basis for drawing up policies for electric vehicle expansion and lithium supply efficiency. Full article
(This article belongs to the Special Issue Environmental Contamination and Human Health)
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