A Micro-volunteering Engine to drive crowd-measuring of Air Quality in Citizen Science

Citizen Science (CS) is a great instrument to drive societal challenges. In a glimpse, CS enables the collection and analysis of data relating to the natural world by members of the general public, typically as part of a collaborative project with professional scientists. Sometimes, researchers need to frame their data collection in concentrated or sparse areas. However, there not exist a digital tool that allow to specify and area and provide geopositionded recommendations to citizen scientists to get evidence from specific points. The Micro-Volunteering Engine (MVE) that is presented in this article is responsible to provide the best fitting spatial cells that need to be measured given a user's location. MVE is used in EU project SOCIO-BEE, a project where members with different profiles organize, manage, and execute CS campaigns. Through CS campaign simulations, it is demonstrated how this engine may be usable to mobilize and drive citizens to carry out crowd-sourcing campaigns which help understanding better the effects of air pollution and, hence, aid decision-making, i.e., co-design of pro-environmental mitigation actions. The MVE is evaluated through a series of dimulations in which its performance is measured to prove its effectiveness for real uses cases of any nature.