The Potential Use of Low-Cost Air Pollution Sensors in Variety of Indoor and Outdoor Applications

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (26 August 2021) | Viewed by 12209

Special Issue Editor

University of Surrey, Stag Hill, University Campus, Guildford GU2 7XH, UK
Interests: air quality; air pollution control; low-cost air pollution monitors; environmental monitoring and assessment; combustion chemistry; energy and environment

Special Issue Information

Dear Colleagues,

The evolution of low-cost sensors (LCSs) has made the Spatio-temporal mapping of the indoor and outdoor air pollution possible but the diversity of them for various applications make their optimum selection challenging. In this special issue, we aim to discuss the use of LCSs for the control of both indoor and outdoor environments. We encourage authors to explore the key steps by focusing on sensor selection, deployment strategies, data assimilation and processing, and development of predictive models in different settings. This also includes studies based on citizen science approach, where the public is involved in the monitoring and assessment of their living/working environments. This special issue aims to address this need by highlighting high-quality research into the development of affordable but trustable LCSs networks for long-term deployment. Thereby laboratory and field measurements and modelling research to meet the above objectives, such as below items are welcomed:

  • Development and evaluation of next-generation LCSs for indoor/outdoor applications
  • New and innovative methods/techniques for calibration of LCSs
  • Optimum deployment strategies of networked-LCSs
  • Development of methods/techniques which make LCSs reliable for long-term applications
  • Advanced data assimilation, data processing, and innovative modelling apprach for monitoring and pridicting air pollution in networked structurs
  • Exposure and health impact assessment using stationary and mobile-based LCSs
  • Co-designing and -development of LCS-based systems with suppport of citizen scientists
  • Other related studies that satisfy the special issue aims and objectives.

Dr. Hamid Omidvarborna
Guest Editor

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Keywords

  • low-cost air pollution sensors
  • smart cities/buildings
  • sensor network
  • deployment strategies
  • data assimilation and analysis
  • predictive modelling
  • citizen science

Published Papers (3 papers)

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Research

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17 pages, 2077 KiB  
Article
Applications and Limitations of Quantifying Speciated and Source-Apportioned VOCs with Metal Oxide Sensors
by Kristen Okorn and Michael Hannigan
Atmosphere 2021, 12(11), 1383; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12111383 - 22 Oct 2021
Cited by 1 | Viewed by 1792
Abstract
While low-cost air quality sensor quantification has improved tremendously in recent years, speciated hydrocarbons have received little attention beyond total lumped volatile organic compounds (VOCs) or total non-methane hydrocarbons (TNMHCs). In this work, we attempt to use two broad response metal oxide VOC [...] Read more.
While low-cost air quality sensor quantification has improved tremendously in recent years, speciated hydrocarbons have received little attention beyond total lumped volatile organic compounds (VOCs) or total non-methane hydrocarbons (TNMHCs). In this work, we attempt to use two broad response metal oxide VOC sensors to quantify a host of speciated hydrocarbons as well as smaller groups of hydrocarbons thought to be emanating from the same source or sources. For sensors deployed near oil and gas facilities, we utilize artificial neural networks (ANNs) to calibrate our low-cost sensor signals to regulatory-grade measurements of benzene, toluene, and formaldehyde. We also use positive matrix factorization (PMF) to group these hydrocarbons along with others by source, such as wet and dry components of oil and gas operations. The two locations studied here had different sets of reference hydrocarbon species measurements available, helping us determine which specific hydrocarbons and VOC mixtures are best suited for this approach. Calibration fits on the upper end reach above R2 values of 0.6 despite the parts per billion (ppb) concentration ranges of each, which are magnitudes below the manufacturer’s prescribed detection limits for the sensors. The sensors generally captured the baseline trends in the data, but failed to quantitatively estimate larger spikes that occurred intermittently. While compounds with high variability were not suited for this method, its success with several of the compounds studied represents a crucial first step in low-cost VOC speciation. This work has important implications in improving our understanding of the links between health and environment, as different hydrocarbons will have varied consequences in the human body and atmosphere. Full article
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15 pages, 5132 KiB  
Article
Real-Time Low-Cost Personal Monitoring for Exposure to PM2.5 among Asthmatic Children: Opportunities and Challenges
by Dohyeong Kim, Yunjin Yum, Kevin George, Ji-Won Kwon, Woo Kyung Kim, Hey-Sung Baek, Dong In Suh, Hyeon-Jong Yang, Young Yoo, Jinho Yu, Dae Hyun Lim, Sung-Chul Seo and Dae Jin Song
Atmosphere 2021, 12(9), 1192; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12091192 - 15 Sep 2021
Cited by 2 | Viewed by 2843
Abstract
This study aims to evaluate the accuracy and effectiveness of real-time personal monitoring of exposure to PM concentrations using low-cost sensors, in comparison to conventional data collection method based on fixed stations. PM2.5 data were measured every 5 min using a low-cost [...] Read more.
This study aims to evaluate the accuracy and effectiveness of real-time personal monitoring of exposure to PM concentrations using low-cost sensors, in comparison to conventional data collection method based on fixed stations. PM2.5 data were measured every 5 min using a low-cost sensor attached to a bag carried by 47 asthmatic children living in the Seoul Metropolitan area between November 2019 and March 2020, along with the real-time GPS location, temperature, and humidity. The mobile sensor data were then matched with station-based hourly PM2.5 data using the time and location. Despite some uncertainty and inaccuracy of the sensor data, similar temporal patterns were found between the two sources of PM2.5 data on an aggregate level. However, average PM2.5 concentrations via personal monitoring tended to be lower than those from the fixed stations, particularly when the subjects were indoors, during nighttime, and located farther from the fixed station. On an individual level, a substantial discrepancy is observed between the two PM2.5 data sources while staying indoors. This study provides guidance to policymakers and researchers on improving the feasibility of personal monitoring via low-cost mobile sensors as an alternative or supplement to the conventional station-based monitoring. Full article
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Review

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33 pages, 1404 KiB  
Review
Low-Cost Air Quality Sensing towards Smart Homes
by Hamid Omidvarborna, Prashant Kumar, Joe Hayward, Manik Gupta and Erick Giovani Sperandio Nascimento
Atmosphere 2021, 12(4), 453; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12040453 - 02 Apr 2021
Cited by 23 | Viewed by 6179
Abstract
The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping of indoor air quality (IAQ) possible in real-time but the availability of a diverse set of LCSs make their selection challenging. Converting individual sensors into a sensing network requires the knowledge of [...] Read more.
The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping of indoor air quality (IAQ) possible in real-time but the availability of a diverse set of LCSs make their selection challenging. Converting individual sensors into a sensing network requires the knowledge of diverse research disciplines, which we aim to bring together by making IAQ an advanced feature of smart homes. The aim of this review is to discuss the advanced home automation technologies for the monitoring and control of IAQ through networked air pollution LCSs. The key steps that can allow transforming conventional homes into smart homes are sensor selection, deployment strategies, data processing, and development of predictive models. A detailed synthesis of air pollution LCSs allowed us to summarise their advantages and drawbacks for spatio-temporal mapping of IAQ. We concluded that the performance evaluation of LCSs under controlled laboratory conditions prior to deployment is recommended for quality assurance/control (QA/QC), however, routine calibration or implementing statistical techniques during operational times, especially during long-term monitoring, is required for a network of sensors. The deployment height of sensors could vary purposefully as per location and exposure height of the occupants inside home environments for a spatio-temporal mapping. Appropriate data processing tools are needed to handle a huge amount of multivariate data to automate pre-/post-processing tasks, leading to more scalable, reliable and adaptable solutions. The review also showed the potential of using machine learning technique for predicting spatio-temporal IAQ in LCS networked-systems. Full article
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