Quantifying PM2.5 Concentrations From Multi-Weather Sensors Using Hidden Markov Models

This letter presents a novel approach to quantify the ambient concentrations of fine particulate matter (PM2.5) from multi-weather sensors based on hidden Markov models-oriented statistical methodology. Compared with one current state-of-theart, the proposed methodology produces a better result, showing potential applications in the existing network of the multi-weather sensors for the PM complementary measurements.