New Insights into Ventilation, Comfort and Air Pollution

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

Deadline for manuscript submissions: closed (25 January 2022) | Viewed by 3062

Special Issue Editor


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Guest Editor
1. Department of Mechanical Engineering, University of Western Macedonia, 50100 Kozani, Greece
2. Atmospheric Chemistry & Innovative Technologies Laboratory, INRASTES, National Center for Scientific Research “DEMOKRITOS”, 15310 Athens, Greece
Interests: indoor air quality; air pollution; occupants’ comfort; ventilation; statistics; climate change; AQ modeling
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Special Issue Information

Dear Colleagues,

People spend a significant amount of their time daily in their workplaces. New indoor environments are now being created in modern buildings as a result of international trends in urban design, residential, commercial or office building design and reduced construction costs, following new standards, new construction/equipment materials and energy efficiency strategies (for lighting, heating, cooling, ventilation etc.). Thus, the Indoor Environment Quality (IEQ) is important for occupants’ health and comfort and is determined by a set of parameters such as temperature, humidity, Indoor Air Quality (IAQ)/air pollution, noise, lighting and ventilation conditions. Improving the well-being and providing healthy, comfortable conditions for buildings’ occupants will become a very demanding issue the next years.

For achieving not only acceptable but even high-quality IAQ and IEQ levels in indoor environments, additional work should be carried out. Hygiene and IAQ with high health safety levels will be of priority after the experience of COVID-19 in all types of indoor environments. An increasing concern about the IAQ will raise not only in office buildings as well as in residences due to the widespread implementation of teleworking. It should be noted that air renewal and high-performance ventilation will be demanded and this will affect occupants’ perception of comfort and health. Further to residences, offices, commercial or public buildings, more indoor environments, especially indoor microenvironments with occupants belonging to vulnerable groups (children, elderly, sick people), such as homes, schools, nursing homes, etc., should be investigated.

Therefore, this Special Issue invites research including, but not limited to, the following areas:

  • Indoor air pollution monitoring/modeling;
  • Ventilation/infiltration/air flow monitoring/modeling;
  • Ventilation system/building designing;
  • Ventilation versus IAQ and indoor biological agents;
  • Ventilation versus COVID-19, investigation using natural or mechanical systems/usage of air purifiers etc.;
  • IAQ/IEQ comfort/health impact assessment.

Dr. Ioannis A. Sakellaris
Guest Editor

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Keywords

  • air quality
  • indoor air pollution
  • ventilation
  • air flow modeling
  • building design
  • IEQ perception
  • comfort
  • occupants’ health

Published Papers (1 paper)

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Research

14 pages, 536 KiB  
Article
A Practical and Adaptive Approach to Predicting Indoor CO2
by Giacomo Segala, Roberto Doriguzzi-Corin, Claudio Peroni, Tommaso Gazzini and Domenico Siracusa
Appl. Sci. 2021, 11(22), 10771; https://doi.org/10.3390/app112210771 - 15 Nov 2021
Cited by 7 | Viewed by 2447
Abstract
COVID-19 has underlined the importance of monitoring indoor air quality (IAQ) to guarantee safe conditions in enclosed environments. Due to its strict correlation with human presence, carbon dioxide (CO2) represents one of the pollutants that most affects environmental health. Therefore, forecasting [...] Read more.
COVID-19 has underlined the importance of monitoring indoor air quality (IAQ) to guarantee safe conditions in enclosed environments. Due to its strict correlation with human presence, carbon dioxide (CO2) represents one of the pollutants that most affects environmental health. Therefore, forecasting future indoor CO2 plays a central role in taking preventive measures to keep CO2 level as low as possible. Unlike other research that aims to maximize the prediction accuracy, typically using data collected over many days, in this work we propose a practical approach for predicting indoor CO2 using a limited window of recent environmental data (i.e., temperature; humidity; CO2 of, e.g., a room, office or shop) for training neural network models, without the need for any kind of model pre-training. After just a week of data collection, the error of predictions was around 15 parts per million (ppm), which should enable the system to regulate heating, ventilation and air conditioning (HVAC) systems accurately. After a month of data we reduced the error to about 10 ppm, thereby achieving a high prediction accuracy in a short time from the beginning of the data collection. Once the desired mobile window size is reached, the model can be continuously updated by sliding the window over time, in order to guarantee long-term performance. Full article
(This article belongs to the Special Issue New Insights into Ventilation, Comfort and Air Pollution)
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