Correction and Long-Term Performance Evaluation of Fine Particulate Mass Monitoring with Low-Cost Sensors

Low-cost particulate sensors can allow for establishing a dense monitoring network to increase the spatial resolution of air quality information, which is particularly of interest in urban areas. However, these sensors are often affected by environmental factors such as temperature and humidity, the effects of which must be accounted for so that the accuracy of these sensors in field conditions can be quantified. In this paper, we conduct long-term tests of two types of low-cost particulate sensors: Met-One NPM and PurpleAir units. We assess the self-consistency of larger groups (12 to 25) of sensors, develop empirical equations for correcting the measurements of these sensors to better match those of regulatory-grade instruments, and assess the long-term performance of these sensors during deployments lasting over a year. These assessments are used to assess sensor performance in two different use cases: improving community awareness of air quality with a focus on short-term qualitative indications and p...