The World Health Organization has indicated that exposure to air pollution will be one of the most significant challenges related to health in the following years, and air quality monitoring actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating methodologies and datasets that support policy makers in the decision process is essential in identifying and proposing mitigation scenarios is essential. In this context, the IoT paradigm allows for to collect of real-time, being the strength of this approach is the use of wearable devices in citizen science methodologies to collect personal exposure data and engage citizens about the pollution in neighbourhoods and cities. However, these hyperlocal IoT sensors present several challenges in terms of data quality. For this reason, this paper aims to evaluate the Atmotube Pro wearable device to assess its performance for citizen science approaches, by conducting field tests against the reference device GRIMM 11-D. Our results show that Atmotube Pro presents an acceptable accuracy - with R2 values ranging from 0.47 to 0.93, depending on particle size and sampling time - highlighting that the system is suitable for citizen science applications and community engagement.