Online Program Home
My Program

Abstract Details

Activity Number: 190 - Contributed Poster Presentations: Section on Statistics and the Environment
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #305134
Title: Modeling Air Pollution in Beijing with Meteorological Data
Author(s): Ying Zhang* and Song Xi Chen and Le Bao
Companies: Pennsylvania State University and Peking University and Pennsylvania State University
Keywords: Air Pollution; Spatio-temporal Model; Kriging

The air pollution problem has been a serious environmental concern in China. A commonly used measurement of air pollution is the concentration of PM2.5. PM2.5 stands for the particulate matter with a size generally less than 2.5 micrometers, and they can diminish lung function, trigger heart disease or even worse for human health. The hourly PM2.5 and other meteorological data are collected from 36 monitoring locations in Beijing, China, between 2013 and 2017. We use spatio-temporal models to estimate PM2.5 concentration over time and space, understand how it changes with meteorological variables, and extrapolate the PM2.5 at locations without ground monitoring data.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program