Special Issue "Development of Low-Cost PM Sensors Deployed to Air Quality Measurements"

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

Deadline for manuscript submissions: 28 April 2023 | Viewed by 893

Special Issue Editor

Department of Environmental Science and Engineering, Tunghai University, Taichung 407302, Taiwan
Interests: aerosol technology; air-quality monitoring; numerical simulation calculation

Special Issue Information

Dear Colleagues,

PM sensors, which possess advantages such as low cost and small size, can be used to provide information on the air quality in areas with limited regulatory monitoring stations. They are also expected to be applicable for hotspot identification, emission inventories of pollutants creation, and real-time exposure assessment, which help with the design of mitigation strategies. In order to improve the correctness of low-cost sensors datasets, the linear regression method, multivariate linear regression method, and deep-learning methods have been used to calibrate the values measured by low-cost sensors. However, measures for large-scale PM sensors network calibration and strategies for regional deployment are still in need of development.

This Special Issue aims to provide original and the state-of-the-art studies on the deployment of low-cost PM sensors for air-quality measurements. Studies on calibration methods for sensors networks, site selection protocols for sensors deployment, spatial–temporal characterization of PM concentrations, hotspot identification, exposure assessment, and source tracing based on sensor datasets are welcome. The applicability of sensor networks for environmental enforcement is also of interest.

Dr. Guan-Yu Lin
Guest Editor

Manuscript Submission Information

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  • low-cost PM sensors
  • sensors network
  • spatial-temporal characterization
  • air quality monitoring
  • sensors calibration model
  • environmental enforcement

Published Papers (1 paper)

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Seasonal Field Calibration of Low-Cost PM2.5 Sensors in Different Locations with Different Sources in Thailand
Atmosphere 2023, 14(3), 496; https://doi.org/10.3390/atmos14030496 - 03 Mar 2023
Viewed by 589
Low-cost sensors (LCS) have been increasingly deployed to monitor PM2.5 concentrations. More than 1500 LCS have been installed in Thailand to increase public awareness of air quality. However, performance of these sensors has not been systematically investigated. In this study, PM2.5 [...] Read more.
Low-cost sensors (LCS) have been increasingly deployed to monitor PM2.5 concentrations. More than 1500 LCS have been installed in Thailand to increase public awareness of air quality. However, performance of these sensors has not been systematically investigated. In this study, PM2.5 LCS were co-located next to a PM2.5 federal equivalent method (FEM) reference instrument at three Thai locations—in the north, center and northeast. We evaluated the performance of a PM2.5 LCS (PMS7003, Plantower) to understand the key factors affecting performance, including emission sources, relative humidity, temperature and PM2.5 concentration. Low PM concentration and high humidity levels had a significant impact on performance. Sensors in a high traffic emission area showed low correlation. The unadjusted PM2.5 LCS performance varied with locations. Errors were mainly observed at low concentrations. They significantly underestimated concentrations in congested urban environments. After calibration, accuracy was improved with multiple regression models. The performance of sensors only at Chiang Mai (CM) during the dry season and Ubon Ratchathani (URT) during the dry and wet seasons were acceptable with coefficient of variation: 5.8 ± 4.7–6.8 ± 5.0%, slope: 0.829–0.945, intercept: 1.12–5.49 µg/m3, R2: 0.880–0.934 and RMSE: 4.3–5.1 µg/m3. In the congested area in Bangkok (BKK), they underestimated concentrations of small particles. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Spatial mapping of air pollution hotspots around commercial meat cooking restaurants: mobile monitoring by a bicycle
Authors/emails: (Corresponding) Kyung-Hwan Kwak/[email protected]

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