题目：Air-Quality Assessment with Spatial and Temporal Adjustment to Meteorological Confounding

报告人：北京大学讲席教授，陈松蹊教授

时 间： 2017年11月6日（星期一）9：00

地 点： 数学楼629室

摘要： Although air pollution is caused by emission of pollutants to the atmosphere, the observed pollution levels are largely affected by meteorological conditions which determine the dispersion condition of the pollutants. Effective air quality management requires statistical measures that are immune to the meteorological confounding in order to evaluate {spatial and temporal} changes of the pollution concentration objectively. Motivated by a challenging task of assessing changes and trends in the underlying pollution concentration in a region near Beijing,

we propose a spatial and temporal adjustment approach for the PM$_{2.5}$ and other five pollutants with respect to the meteorological conditions by constructing a spatial and temporal baseline weather condition based on historic data to remove the meteorological confounding.

The adjusted mean pollution concentration is shown to be able to capture changes in the underlying emission while being able to control the meteorological variation. Estimation of the adjusted average is proposed together with asymptotic and numerical analyzes. We apply the approach to conduct assessments on six pollutants in the Beijing region from Year 2013 to Year 2016, which reveal some intriguing patterns and trends that are useful for the air quality management.