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Air pollution is responsible for increased morbidity and mortality due to respiratory problems mainly caused by long term exposure. Although the emissions of principal air pollutants are highly regulated, there is a lack of information about the real extent of personal exposure for an accurate health impact assessment. To tackle these challenges, local air pollution measurements and citizen involvement based on the small IoT devices became necessary. The Tel-MonAer platform is based on IoT devices and Edge/Cloud computing technologies and allows the (near) real-time monitoring of Particulate Matter air pollutants considering the complex chemistry and influence of various parameters (i.e. air humidity, wind speed, temperature). The aim of this paper is the assessment of the influence that air humidity has on the PM concentrations measured with IoT devices based on laser beam technologies. The results showed that in order to increase the accuracy of PM concentrations values a threshold value for relative humidity of 80% needs to be considered. When humidity values are below 80%, the PM concentration values are considered valid, while for values over the threshold, a specific correction algorithm needs to be applied. This paper presents the correction algorithm (based on the type of sensor and humidity) and the testing results (an increase of at least 2.5 times of the correlation coefficient between the corrected and reference values).

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