Environmental Engineering Reference
In-Depth Information
7.3 Integrated Application of Source Apportionment
Tools to Support Development and Implementation
of Air Quality Regulations to Protect Public Health
D. Hammond, T. Watkins, and G. Norris
Human Exposure and Atmospheric Sciences Division, U.S. Environmental Protection
Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Abstract Air pollution is associated with increased health and ecological effects.
A complex mixture of local, urban, and regional sources contribute to air pollution,
presenting a challenge to separate sources dispersed across the range of spatial
scales. Understanding the relative contribution of these sources is important because
recent health studies suggest differences in exposure relationships and health effects
for different sources. In addition, air quality management decisions require infor-
mation on the sources contributing to air pollution to develop effective air pollution
control strategies. This paper will describe efforts to identify and quantify sources
of air pollution using a multidisciplinary research approach focused on the inte-
grated application of sampling methods, analytical methods, and receptor-based
modeling tools.
The application of high time resolution sampling methods, such as the Semi-
continuous Elements in Aerosol Sampler (SEAS), provides valuable data for
source apportionment. When samples collected are analyzed with high resolution
analytical methods, source marker compounds are identified which can be used
as inputs to multivariate receptor-based modeling tools, such as Positive Matrix
Factorization and Unmix, that provide information to identify relative source
contributions. The application of the Air Pollution Transport to Receptor (APTR)
model provides additional information regarding the location of sources. APTR
has a local component based on nonparametric wind regression and a regional
component based on Quantitative Transport Bias Analysis.
This paper will present results from the intensive source apportionment studies
conducted in various location in the US, including St. Louis, Missouri, Dearborn,
Michigan, and Steubenville, Ohio. The paper will demonstrate how the results of
these studies have provided valuable information for air quality management
decisions, as well as, information to support development of air quality regulations
to protect public health. Finally, the paper will also discuss future efforts to
integrate receptor-based approaches with source-oriented models to enhance
source apportionment capabilities.
Keywords Source-oriented modeling, receptor modeling, source apportionment,
air quality
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