Towards More Accurate Estimates of Air Pollution in Beijing

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.

Explore more research by faculty in the School of Economics on our featured project page!