MIT scholars acquired geographically and time-referenced 3G mobile traffic data from several operators. These assets included data from mobile devices such as phones and tablets corresponding to several million people in New York. The dataset enabled researchers to identify aggregated spatial and temporal patterns of movement of New York's population at the cell tower level. Researchers then assigned corresponding time and geographically variable air pollution exposure values to residents to map New York City's population with their air pollution exposure levels. This research attempts to use digital datasets to "predict the impacts of the urban environment on human health" to inform environmental and public health policy.