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Air Quality Monitoring and Assessment for Enhanced Living Environments and Public Health

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

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 20970

Special Issue Editor

Polytechnic of Coimbra, ESTGOH, Rua General Santos Costa, 3400-124 Oliveira do Hospital, Portugal
Interests: gas sensors; internet of things; Ambient Assisted Living; Wireless Sensor Network; indoor air quality; smart cities; Zigbee; air quality monitoring; indoor environment

Special Issue Information

Dear Colleagues,

Air quality has a significant impact on overall public health. According to the World Health Organization, ambient pollution is a leading cause of death and disease globally. Particulate matter (PM), ozone (O3), nitrogen dioxide (NO2) and sulphur dioxide (SO2) are the most dangerous pollutants for public health. Poor air quality is responsible for the increase in hospital admissions and emergency room visits and for a higher risk of premature death. Moreover, 4.2 million premature deaths are associated with ambient air pollution resulting in heart disease, stroke, chronic obstructive pulmonary disease, lung cancer, and acute respiratory infections in children.

Most people spend more than 90% of their time inside buildings. Therefore, indoor air quality has a material impact on occupational health and wellbeing. Poor indoor air quality is associated with Sick Building Syndrome, reduced productivity in offices, and impaired learning in schools. Therefore, it is relevant to provide real-time monitoring in buildings for enhanced living environments.

The Internet of Things can be understood as the connection of physical objects to the internet. These cyber-physical systems which incorporate sensing capabilities can be handled via unique addresses and support cooperation capabilities. Continuous tectological enhancements have decreased the cost of microcontrollers and sensors. Several connectivity methods are available for short-range and long-range communication such as Wi-Fi, RFID, NFC, BLE, GSM, 3G/4G, ZigBee, and LoRa. These technologies offer a relevant opportunity in the development of cyber-physical systems for air quality monitoring and assessment. Moreover, mobile computing technologies can be used for data analytics and visualization. Smartphones are an indispensable device for daily social routines, and people carry them in their pockets. Therefore, mobile applications can be understood as an enhanced method for data consulting and notifications regarding air quality assessment.

This Special Issue aims to provide a multidisciplinary look at state-of-art research on air quality monitoring and assessments which merge the environmental science domain with computer science technologies for enhanced living environments and public health. Furthermore, the main interest is to provide insights related to the research challenges and comprehensive results on these topics. On the one hand, this Special Issue aims to present new results concerning air quality evaluation regarding people’s exposure in indoor and outdoor environments and the resultant health effects. On the other hand, this Special Issue also aims to present recent research on the Internet of Things and Wireless Sensor Networks in the development of innovative air quality monitoring methods. The development of intelligent cyber-physical systems regarding the smart city and smart home environments provides a consistent approach to promote occupational health and wellbeing. In sum, this Special Issue aims to publish original research articles and reviews to disseminate new findings and extend the current state- of-the-art research on air quality monitoring and its impact on public health.

Dr. Gonçalo Marques
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. International Journal of Environmental Research and Public Health 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 2500 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

  • Air Quality
  • Indoor Air Quality Assessment
  • Occupational Health
  • Public Health
  • Enhanced Living Environments
  • Internet of Things
  • Wireless Sensor Networks
  • Air Quality sensors
  • Mobile computing technologies
  • Innovative monitoring approaches

Published Papers (4 papers)

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Research

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13 pages, 651 KiB  
Article
How Do Air Quality Issues Caused by Particulate Matter Affect Consumers’ Emotional Response to Tourism Destinations and Willingness to Visit?
by Jongsik Yu, Kyeongheum Lee, Antonio Ariza-Montes, Alejandro Vega-Muñoz and Heesup Han
Int. J. Environ. Res. Public Health 2021, 18(19), 10364; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph181910364 - 01 Oct 2021
Cited by 1 | Viewed by 1926
Abstract
This study identifies the perceived risk factors of particulate matter (PM) and the effect of the perceived risk factors of PM on the relationship between tourists’ trust and aspiration regarding the tourist destination, the customer return on investment, and the willingness to visit [...] Read more.
This study identifies the perceived risk factors of particulate matter (PM) and the effect of the perceived risk factors of PM on the relationship between tourists’ trust and aspiration regarding the tourist destination, the customer return on investment, and the willingness to visit a tourism destination. Accordingly, this study discussed the severity of PM, which plays a key role in causing air quality issues, and classified the factors for perceived risk of PM into physical, psychological, financial, functional, and time risks to verify its effect on consumers’ emotional response and willingness to visit. Data collection for empirical analysis took place in April 2021 for two weeks. A total of 285 significant data points were obtained on tourists with travel experience in the past year. The demographic characteristics were confirmed using SPSS 22.0 (IBM, New York, NY, USA) and AMOS 22.0 (IBM, New York, NY, USA), and the measurement and structural models were verified through a confirmatory factor analysis and structural equation modeling, respectively. The empirical analysis showed that the perceived risk of PM has a negative effect on trust in the tourism destination and desire for it, and the behavioral intention of customers. Furthermore, alternative attractiveness was found to play a significant moderating role. The results of this study proved the negative effect of PMs on tourism destinations and provided implications and insights to present a meaningful strategy for minimizing PMs’ perceived risk. Full article
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13 pages, 693 KiB  
Article
Effect of Hotel Air Quality Management on Guests’ Cognitive and Affective Images and Revisit Intentions
by Junghyun Park, Jae Leame Yoo and Jongsik Yu
Int. J. Environ. Res. Public Health 2021, 18(17), 9346; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18179346 - 04 Sep 2021
Cited by 3 | Viewed by 2766
Abstract
Although city air pollution levels significantly affect the hotel industry, few studies have addressed the impact of air quality management on guests’ cognitive and affective image formation and revisit intentions. Therefore, this research examined the effects of hotel air quality management on the [...] Read more.
Although city air pollution levels significantly affect the hotel industry, few studies have addressed the impact of air quality management on guests’ cognitive and affective image formation and revisit intentions. Therefore, this research examined the effects of hotel air quality management on the formation of guests’ cognitive and affective images and their revisit intentions. A total of 322 valid samples were obtained by surveying hotel guests who had perceived hotel air quality management activities in the past year, with SPSS 22.0 (IBM, New York, NY, USA) and AMOS 22.0 (IBM, New York, NY, USA) employed for the empirical analysis. The cognitive and affective image constructs revealed that cognitive (perceived value and perceived quality) image influenced revisit intentions but affective image did not. These results provide insights into the need for hotel managers to develop positive cognitive and emotional images through good air quality management and the need to induce customers to revisit based on these images. Full article
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20 pages, 5217 KiB  
Article
Investigation of the Impact of Land-Use Distribution on PM2.5 in Weifang: Seasonal Variations
by Chengming Li, Kuo Zhang, Zhaoxin Dai, Zhaoting Ma and Xiaoli Liu
Int. J. Environ. Res. Public Health 2020, 17(14), 5135; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17145135 - 16 Jul 2020
Cited by 17 | Viewed by 2458
Abstract
As air pollution becomes highly focused in China, the accurate identification of its influencing factors is critical for achieving effective control and targeted environmental governance. Land-use distribution is one of the key factors affecting air quality, and research on the impact of land-use [...] Read more.
As air pollution becomes highly focused in China, the accurate identification of its influencing factors is critical for achieving effective control and targeted environmental governance. Land-use distribution is one of the key factors affecting air quality, and research on the impact of land-use distribution on air pollution has drawn wide attention. However, considerable studies have mostly used linear regression models, which fail to capture the nonlinear effects of land-use distribution on PM2.5 (fine particulate matter with a diameter less than or equal to 2.5 microns) and to show how impacts on PM2.5 vary with land-use magnitudes. In addition, related studies have generally focused on annual analyses, ignoring the seasonal variability of the impact of land-use distribution on PM2.5, thus leading to possible estimation biases for PM2.5. This study was designed to address these issues and assess the impacts of land-use distribution on PM2.5 in Weifang, China. A machine learning statistical model, the boosted regression tree (BRT), was applied to measure nonlinear effects of land-use distribution on PM2.5, capture how land-use magnitude impacts PM2.5 across different seasons, and explore the policy implications for urban planning. The main conclusions are that the air quality will significantly improve with an increase in grassland and forest area, especially below 8% and 20%, respectively. When the distribution of construction land is greater than around 10%, the PM2.5 pollution can be seriously substantially increased with the increment of their areas. The impact of gardens and farmland presents seasonal characteristics. It is noted that as the weather becomes colder, the inhibitory effect of vegetation distribution on the PM2.5 concentration gradually decreases, while the positive impacts of artificial surface distributions, such as construction land and roads, are aggravated because leaves drop off in autumn (September–November) and winter (December–February). According to the findings of this study, it is recommended that Weifang should strengthen pollution control in winter, for instance, expand the coverage areas of evergreen vegetation like Pinus bungeana Zucc. and Euonymus japonicus Thunb, and increase the width and numbers of branches connecting different main roads. The findings also provide quantitative and optimal land-use planning and strategies to minimize PM2.5 pollution, referring to the status of regional urbanization and greening construction. Full article
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Review

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22 pages, 1625 KiB  
Review
Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review
by Jagriti Saini, Maitreyee Dutta and Gonçalo Marques
Int. J. Environ. Res. Public Health 2020, 17(14), 4942; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17144942 - 09 Jul 2020
Cited by 88 | Viewed by 11924
Abstract
Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is [...] Read more.
Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency. Full article
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