Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.1
2.9
Journals
Atmosphere
Special Issues
Advanced Technologies in Air Science: Monitoring, Analyzing, Modeling, and Implementation
share announcement

Advanced Technologies in Air Science: Monitoring, Analyzing, Modeling, and Implementation

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

Deadline for manuscript submissions: closed (20 October 2021) | Viewed by 9173

Special Issue Editors

Dr. Lexuan Zhong

E-Mail Website
Guest Editor
University of Alberta, 10-351 DICE, 9211-116 Street NW, Edmonton, AB T6G 1H9, Canada
Interests: indoor/outdoor air quality; health exposure assessment; building energy; green buildings; climate change; wildfire pollution; ozone pollution
Dr. Md. Aynul Bari

E-Mail Website
Guest Editor
Department of Environmental and Sustainable Engineering, University at Albany, State University of New York (SUNY), Albany, NY 12222, USA
Interests: ambient air quality monitoring and characterization; indoor and outdoor behavior of air pollutants; particulate air pollution; source characterization and apportionment; sustainable air pollution management; atmospheric deposition of air pollutants; environmental impact assessment; influence of energy development on air quality; residential wood burning; low-cost air pollution sensors; air pollution exposure and public health risk assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With technology development and the subsequent air pollution and health effects, ambient air quality has received more attention in the past 20 years from all aspects. In contrast, less attention has been given by government agencies to monitor indoor air quality (IAQ). Although significant achievements have been made in air science, emerging technologies have been driving the development of products and systems for improved performance. In addition, the occurrence of the COVID-19 pandemic poses new issues and challenges of air pollution studies. In this context, this special issue is initiated to cover the following research aspects:

  • Evaluation of new air quality sensors for indoor and outdoor air quality monitoring;
  • Characteristics of emerging air pollutants (e.g., PFAS) under various environments;
  • Air quality modeling in combination with machine learning;
  • Adverse health effects of air pollutants in ambient and built environment;
  • Interventions and strategies to reduce health risks of outdoor air pollutant exposures;
  • Emerging air cleaning technologies for air pollutant treatment and remediation;
  • Advanced ventilation design and operation strategies to improve IAQ;
  • Building features and occupant behaviour on IAQ;
  • Impacts of COVID-19 pandemic on indoor and outdoor air quality;
  • Effective ventilation infection control under the COVID-19 pandemic;
  • Future IAQ trends under climate change and energy conservation in buildings.

Manuscripts to address challenging future research for Air Science are invited for submission to this Special Issue.

Dr. Lexuan Zhong
Prof. Dr. Md. Aynul Bari
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. 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

  • Indoor air quality
  • Outdoor air quality
  • Ventilation
  • Volatile organic compounds
  • Per- and polyfluoroalkyl substances (pfas)
  • Aerosols/bioaerosols
  • Particulate matter
  • Health exposure
  • Air cleaning technologies

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

12 pages, 1529 KiB  
Article
Indoor Environmental Health Assessment in Eco-Building and Its Case Study
by Jing Yuan, Xiaohui Zhao, Giwa Abdulmoseen Segun, Mohammadtaghi Vakili and Lexuan Zhong
Atmosphere 2021, 12(6), 794; https://doi.org/10.3390/atmos12060794 - 21 Jun 2021
Cited by 2 | Viewed by 2523
Abstract
It is necessary to consider all aspects of environmental factors when assessing the health impact of an eco-building environment on its occupants. However, the multi-criteria and imprecise nature of the indoor-environment in the eco-buildings has caused difficulties in quantifying the indoor environmental pollution [...] Read more.
It is necessary to consider all aspects of environmental factors when assessing the health impact of an eco-building environment on its occupants. However, the multi-criteria and imprecise nature of the indoor-environment in the eco-buildings has caused difficulties in quantifying the indoor environmental pollution level. This paper describes the optimal classification and priority weight methods, which are particularly useful for assessing the indoor environmental quality (IEQ) of an eco-building to demonstrate its innovative applications. The analytic hierarchy process (AHP) was used to set up the strategic decision-making evaluation system for computing the indoor environment index (IEI) risk ranking of eco-buildings. Combined with this, a Microsoft Delphi-based IEQ intelligent forecasting software simulations package was developed, and the innovative application of indoor environmental comprehensive assessment was verified by a case study in Shanghai. The evaluation result was analyzed by the priority weight methods and the AHP decision-making system noted above. This health assessment method and system provides an innovative way for the indoor environment risk evaluation of eco-buildings and is helpful to standardize the local building market. Full article
(This article belongs to the Special Issue Advanced Technologies in Air Science: Monitoring, Analyzing, Modeling, and Implementation)
►▼ Show Figures

Figure 1

12 pages, 1591 KiB  
Article
Effect of Metal Oxides and Smelting Dust on SO2 Conversion to SO3
by Haipeng Liu, Qin Zhang, Hongying Yang, Yanan Wu, Jiacheng Chen and Shen Hu
Atmosphere 2021, 12(6), 734; https://doi.org/10.3390/atmos12060734 - 08 Jun 2021
Cited by 3 | Viewed by 2487
Abstract
The purpose of this study was to investigate the effects of metal oxides and smelting dust on the formation of sulfur trioxide during copper, lead, zinc smelting process and flue. Focusing on the effects of SO2 concentration, O2 concentration, and temperature [...] Read more.
The purpose of this study was to investigate the effects of metal oxides and smelting dust on the formation of sulfur trioxide during copper, lead, zinc smelting process and flue. Focusing on the effects of SO2 concentration, O2 concentration, and temperature on SO2 oxidation conversion rate under homogeneous test conditions, and under various metal oxide oxidation conditions, further in dust (mainly electric dust removal ash in copper, lead, zinc smelting process), which were studied by single factor experiment test. The results showed that the effect of heterogeneous catalytic oxidation on SO2 conversion rate is much greater than that of pure gas phase oxidation. The addition of five pure metal oxides such as Fe2O3, CuO, Al2O3, ZnO, and CaO obviously promoted the SO2 conversion rate under different conditions. At different temperatures, the ability of metal oxides to promote SO2 conversion is ranked: Fe2O3 > CuO > CaO > ZnO > Al2O3. The catalytic oxidation of copper, lead, and zinc smelting dust to SO2 conversion rate was studied, and the conclusion was drawn that the metal oxides that promoted SO2 conversion rate in copper smelting dust were Fe2O3, Al2O3, ZnO, CaO, and the main substance was Fe2O3; the metal oxides that promoted SO2 conversion in zinc smelting dust were Fe2O3, Al2O3, ZnO, CaO, CuO, and the main substances were Fe2O3 and ZnO; the metal oxides that promoted SO2 conversion rate in lead smelting dust were Fe2O3. Whether metal oxides or copper, zinc, lead smelting dust in the experiment, Fe2O3 displayed the strongest catalytic oxidation capacity. Full article
(This article belongs to the Special Issue Advanced Technologies in Air Science: Monitoring, Analyzing, Modeling, and Implementation)
►▼ Show Figures

Figure 1

24 pages, 7634 KiB  
Article
Air Quality Modeling for Sustainable Clean Environment Using ANFIS and Machine Learning Approaches
by Osman Taylan, Abdulaziz S. Alkabaa, Mohammed Alamoudi, Abdulrahman Basahel, Mohammed Balubaid, Murad Andejany and Hisham Alidrisi
Atmosphere 2021, 12(6), 713; https://doi.org/10.3390/atmos12060713 - 31 May 2021
Cited by 8 | Viewed by 3098
Abstract
Air quality monitoring and assessment are essential issues for sustainable environmental protection. The monitoring process is composed of data collection, evaluation, and decision-making. Several important pollutants, such as SO2, CO, PM10, O3, NOx, H2S, location, [...] Read more.
Air quality monitoring and assessment are essential issues for sustainable environmental protection. The monitoring process is composed of data collection, evaluation, and decision-making. Several important pollutants, such as SO2, CO, PM10, O3, NOx, H2S, location, and many others, have important effects on air quality. Air quality should be recorded and measured based on the total effect of pollutants that are collectively prescribed by a numerical value. In Canada, the Air Quality Health Index (AQHI) is used which is one numerical value based on the total effect of some concentrations. Therefore, evolution is required to consider the complex, ill-defined air pollutants, hence several naive and noble approaches are used to study AQHI. In this study, three approaches such as hybrid data-driven ANN, nonlinear autoregressive with external (exogenous) input (NARX) with a neural network, and adaptive neuro-fuzzy inference (ANFIS) approaches are used for estimating the air quality in an urban area (Jeddah city—industrial zone) for public health concerns. Over three years, 1771 data were collected for pollutants from 1 June 2016 until 30 September 2019. In this study, the Levenberg-Marquardt (LM) approach was employed as an optimization method for ANNs to solve the nonlinear least-squares problems. The NARX employed has a two-layer feed-forward ANN. On the other hand, the back-propagation multi-layer perceptron (BPMLP) algorithm was used with the steepest descent approach to reduce the root mean square error (RMSE). The RMSEs were 4.42, 0.0578, and 5.64 for ANN, NARX, and ANFIS, respectively. Essentially, all RMSEs are very small. The outcomes of approaches were evaluated by fuzzy quality charts and compared statistically with the US-EPA air quality standards. Due to the effectiveness and robustness of artificial intelligent techniques, the public’s early warning will be possible for avoiding the harmful effects of pollution inside the urban areas, which may reduce respiratory and cardiovascular mortalities. Consequently, the stability of air quality models was correlated with the absolute air quality index. The findings showed notable performance of NARX with a neural network, ANN, and ANFIS-based AQHI model for high dimensional data assessment. Full article
(This article belongs to the Special Issue Advanced Technologies in Air Science: Monitoring, Analyzing, Modeling, and Implementation)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop