Particle radioactivity is a property of airborne particles caused by the presence of naturally occurring or anthropogenic radionuclides. Recent studies have found associations between particle radioactivity and adverse health outcomes, including changes in blood pressure and lung function. However, the spatiotemporal distribution of particle radioactivity and factors influencing its variability have not been extensively studied. We address these knowledge gaps using measurements of gross beta activity, collected at seven Environmental Protection Agency (EPA) RadNet monitors located in and around Massachusetts. We apply back-trajectory analysis to identify prevailing air mass trajectories and find that these trajectories strongly influence seasonal trends in beta activity. We also evaluate the effects of different meteorological predictors on daily beta activity concentrations using a mixed-effect model. Important predictors of beta activity include air mass trajectories, temperature, and relative humidity. Finally, we create a series of random forest models to impute missing beta activity concentrations at each RadNet monitor for use in future health studies. This is the first study to analyze spatiotemporal trends in particle radioactivity using measurements from the EPA RadNet system.