Statistica Sinica 28 (2018), 921-940
Abstract: Air pollution is driven by non-local dynamics, in which air quality at a site is determined by transport of pollutants from distant pollution emission sources to the site by atmospheric processes. To understand the underlying nature of pollution generation, it is crucial to employ physical knowledge to account for pollution transport by wind. However, in most cases, it is not possible to utilize physics models to obtain useful information; this would require massive calibration and computation. In this paper, we propose a method to estimate the pollution emission from the domain of interest by using the physical knowledge and observed data. The proposed method uses an efficient optimization algorithm to estimate the emission from each of the spatial locations, while incorporating physics knowledge. We demonstrate the effectiveness of the new method through a simulation study.
Key words and phrases: Alternating direction method of multipliers, dispersion, inverse model, penalized regression.