Towards More Accurate Estimates of Air Pollution in Beijing

Faculty
Assistant Professor Karen Yan
About This Project

headshot of Assistant Professor Karen YanBy: Aselia Urmanbetova

In her research co-authored with Yanqin Fan and Lei Hou and published in Economic Letters in 2018, Assistant Professor Karen Yan uses non-parametric k-nearest neighbor (knn) density estimation to fit daily smog data from the US Embassy in Beijing from 2015-16.

The estimation method proposed by the authors fits the data of smog in Beijing better than other (non-parametric) methods. In addition, the authors’ method differentiates smog density in summer vs. winter and that in winter, there is higher probability of worse smog conditions/outcomes.

Similarly, by estimating the density for different hours during the day, they show that morning and evening rush hours have worse air quality than non-rush hours. These findings are consistent with winter months having more coal burning for heating and cars being responsible for smog, especially during rush hours.

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