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Open AccessArticle
Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments
by
Zdravko Kunić
Zdravko Kunić 1,*
,
Leo Mršić
Leo Mršić
He holds a diploma in the field of insurance (Department of Foreign Trade) and a master's degree in [...]
He holds a diploma in the field of insurance (Department of Foreign Trade) and a master's degree in business statistics (Department of Informatics), both achieved at the Faculty of Economics and Business in Zagreb. He is also the holder of a Doctor of Philosophy degree in information sciences in the field of graph theory and the application of statistical models in business (Department of Information Sciences), achieved at the Faculty of Humanities and Social Sciences in Zagreb. He holds the academic titles of Full Professor, with tenure in the field of information sciences (5.04/HR); Associate Professor, in the field of informatics (5.13/SLO); and Assistant Professor, in the field of computing (2.07/SLO). His teaching title is a Professor of Professional Studies, with tenure in the field of economics (5.01/HR). He is a permanent court expert in the fields of finance, accounting, bookkeeping and informatics (12 years) with a large number (150+) of successfully completed complex publications. He is also an IPMA A Certified Project Director with 100+ successfully completed complex projects and an IEEE Senior Member (R8). He is Vice Rector for science and research at Algebra University and a Member of the National Council for Higher Education, Science and Technological Development in the Republic of Croatia, where he serves as Vice President for technology development.
1,2,*
,
Goran Đambić
Goran Đambić 3
and
Tomislav Ražov
Tomislav Ražov 3
1
Department of Information Systems and Business Analytics, Algebra University, Gradišćanska 24, 10000 Zagreb, Croatia
2
Rudolfovo—Science and Technology Centre, Podbreznik 15, 8000 Novo Mesto, Slovenia
3
Department of Software Engineering, Algebra University, Gradišćanska 24, 10000 Zagreb, Croatia
*
Authors to whom correspondence should be addressed.
Sensors 2024, 24(17), 5477; https://doi.org/10.3390/s24175477 (registering DOI)
Submission received: 30 July 2024
/
Revised: 15 August 2024
/
Accepted: 21 August 2024
/
Published: 23 August 2024
Abstract
Smart cities rely on a network of sensors to gather real-time data on various environmental factors, including air quality. This paper addresses the challenges of improving the accuracy of low-cost particulate matter sensors (LCPMSs) which can be compromised by environmental conditions, such as high humidity, which is common in many urban areas. Such weather conditions often lead to the overestimation of particle counts due to hygroscopic particle growth, resulting in a potential public concern, although most of the detected particles consist of just water. The paper presents an innovative design for an indicative air-quality measuring station that integrates the particulate matter sensor with a preconditioning subsystem designed to mitigate the impact of humidity. The preconditioning subsystem works by heating the incoming air, effectively reducing the relative humidity and preventing the hygroscopic growth of particles before they reach the sensor. To validate the effectiveness of this approach, parallel measurements were conducted using both preconditioned and non-preconditioned sensors over a period of 19 weeks. The data were analyzed to compare the performance of the sensors in terms of accuracy for PM1, PM2.5, and PM10 particles. The results demonstrated a significant improvement in measurement accuracy for the preconditioned sensor, especially in environments with high relative humidity. When the conditions were too severe and both sensors started measuring incorrect values, the preconditioned sensor-measured values were closer to the actual values. Also, the period of measuring incorrect values was shorter with the preconditioned sensor. The results suggest that the implementation of air preconditioning subsystems in LCPMSs deployed in smart cities can provide a cost-effective solution to overcome humidity-related inaccuracies, thereby improving the overall quality of measured air pollution data.
Share and Cite
MDPI and ACS Style
Kunić, Z.; Mršić, L.; Đambić, G.; Ražov, T.
Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments. Sensors 2024, 24, 5477.
https://doi.org/10.3390/s24175477
AMA Style
Kunić Z, Mršić L, Đambić G, Ražov T.
Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments. Sensors. 2024; 24(17):5477.
https://doi.org/10.3390/s24175477
Chicago/Turabian Style
Kunić, Zdravko, Leo Mršić, Goran Đambić, and Tomislav Ražov.
2024. "Innovative Air-Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments" Sensors 24, no. 17: 5477.
https://doi.org/10.3390/s24175477
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