Comparison of classical and machine-learning methods on spatio-temporal modeling of daily Ozone concentrations

Effective actions to mitigate air pollution require of availability of high-resolution observations. Low-cost sensor technologies have emerged as an affordable solution to cope with this deficiency. However, since low-cost sensors are built with low-cost materials, they are prone to errors, gaps, bias, and noise. These problems need to be solved before data can be used to support research or decis...