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Modeling Spatiotemporal Patterns Of Pm2.5 At The Sub-Neighborhood Scale Using Low-Cost Sensor Networks, Philip Jeffrey Orlando

Dissertations and Theses

Epidemiological research has demonstrated an adverse relationship between fine particulate matter (PM_2.5) and human health. While PM_2.5 continues to pose a significant global health risk, there is still the need to further characterize exposures at the intra-urban scale. Land use regression is a statistical modeling technique which is used to predict air pollution concentrations at high resolution from a limited number of monitoring sites. However, the existing regulatory monitoring networks are typically not dense enough to apply these techniques. We explored the potential of using low-cost PM_2.5 sensor networks to overcome the limitations of the existing …