Using Machine Learning and Dispersion Modeling to Estimate Emissions


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Several communities in the Bay Area are disproportionately impacted by poor air quality. Some cities have established community air monitoring programs to monitor air pollution concentrations in real-time to determine impacts to communities from various pollution sources in the area. Varsha’s talk will focus on a novel methodology developed in her work at Ramboll to determine distinct sources of emissions in the area using a combination of ambient air monitoring data, machine learning, and air dispersion modeling. The talk will focus on the results of the study and how the study provides communities an independent way to monitor emissions from nearby pollution sources.