Air pollution is a mixture of natural and man-made substances in the air we breathe. Air pollution has a major impact on the environment, global warming, and human health. Exposure to indoor and outdoor air pollutants causes and/or exacerbates respiratory diseases and diseases in other organ systems.
According to WHO, the combined effects of ambient (outdoor) and household air pollution cause about seven million premature deaths every year, largely as a result of increased mortality from stroke, heart disease, chronic obstructive pulmonary disease, lung cancer and acute respiratory infections. WHO data shows that 9 out of 10 people breathe air that exceeds WHO guideline limits containing high levels of pollutants, with low- and middle-income countries suffering from the highest exposures. (Source: WHO)
Monitoring air pollution levels has become very important to detect pollution peaks and better control air pollution. Improved understanding of the air leading to the better-quality living conditions for all citizens.
Paper on air pollution monitoring – Reliable Low-Cost Air Quality Monitoring Using Off-The-Shelf Sensors and Statistical Calibration by Dr Dejan Drajic and Dr Nenad Gligoric
Modern cities are densely populated spaces and the number of people living in cities is increasing rapidly by years. Air monitoring stations exist in most cities to monitor air pollution. However, their number is insufficient having in mind the high cost of stations, as well as annual calibration cost. The potential solution is to use low-cost off-the-shelf sensors to monitor related air quality parameters, but they are not reliable due to the low accuracy, calibration issues, and short life cycle.
In this paper, the methodology is proposed for calibration off-the-shelf air quality sensors using statistical algorithms and offset values from the official public measurement stations. The possibilities are analysed to improve the reliability of low-cost sensors by processing the obtained raw data. Special attention is devoted to the detection and elimination of short intervals when the raw results have extraordinary high value-peaks and to the corresponding interpolation of these data. The new algorithm for “peaks” detection and elimination is proposed and evaluated. Common Air Quality Index (CAQI) is calculated and evaluated in comparison with the public monitoring stations. It is shown that low-cost sensors could be used with high reliability as a complementary network to public monitoring stations.
Read the full paper in the ELEKTRONIKA IR ELEKTROTECHNIKA journal.
Dr Dejan Drajic holds a Ph.D. degree from the University of Belgrade, Serbia for his work in the area of chip equalization in advanced receivers for WCDMA downlink. His main research interests are WSN (Wireless Sensors Networks), IoT and their applications in Smart cities, ecology, and circular economy. Since 2010 he is involved in FP7 projects related to these areas (SENSEI, Citisense) and H2020 (U4IoT, TagItSmart, Smart Impact, LOGISTAR) where he works as a researcher (tasks and work packages leader). He is a product manager for the ekoNET air quality monitoring solution.
Dr Nenad Gligoric holds a Ph.D. from the Faculty of Organisational Sciences, University of Belgrade. He was engaged as a software engineer in Ericsson on research projects: FP7 HOBNET, FP7 EXALTED, OUTSMART, and FP7 SmartSantander. In DunavNET company, he had several roles (developer, researcher, project manager) and is active in the proposal preparation, successfully obtaining grants for a number of projects (H2020 LOGISTAR, Novi Sad city challenges, DIATOMIC, Smart Impact, FP7 SOCIOTAL project, H2020 TagItSmart, H2020 Privacy Flag, H2020 DEMETER Project, etc).
