title: Identifying likely PM2.5 sources on days of elevated concentration: a simple statistical approach.
abstract: A simple statistical method is described for identifying the likely importance of local sources of PM2.5 in a region on days when the National Ambient Air Quality Standard is exceeded. The method requires only PM2.5 mass concentration and wind direction data, and makes use of the EPA database on PM2.5 emissions in the local region of interest. The method has been illustrated using data from the Pittsburgh Air Quality Study, and suggests that local sources can be very important in affecting PM2.5 exceedances. The results have implications for many of the urban areas in the eastern United States downwind of large sources in the Midwest, and shows that simple statistical tests can be of value in identifying regions where further testing with sophisticated air quality dispersion models and source-receptor models is warranted.
authors.affiliation: Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA.
authors.forename: Nanjun
authors.initials: N
authors.lastname: Chu
authors.forename: Joseph B
authors.initials: JB
authors.lastname: Kadane
authors.forename: Cliff I
authors.initials: CI
authors.lastname: Davidson
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D010316:Particle Size
chemical_list: D000393:Air Pollutants