The 7th
Annual
NC
Undergraduate
Summer Research Symposium
Computation
for Undergraduate Statistics Program (CUSP)
Abstracts are listed in
alphabetical order by the last name of the corresponding author.
|
Gore, Kristen
L. Bader, Nicole
J. Gaddis, Marshall
G. |
|
|
Home Institution: |
NCSU |
|
Program: |
Computation for Undergraduate Statistics
Program (CUSP) |
|
College: |
PAMS |
|
Department(s): |
Statistics Marine, Earth, and Atmospheric
Sciences |
|
Research |
William F. Hunt,
Jr./Statistics Gentry White/Statistics Chris Franck (Graduate
Assistant)/Statistics |
|
Title of Presentation: |
Did Reductions in Nitrogen
Oxides Emissions from Utilities Reduce Fine Particulate Matter Levels in
North Carolina? |
Fine particulate matter (PM2.5) is particulate matter
that is 2.5 microns in diameter and less. Ambient PM can be attributed to
both anthropocentric and natural sources. Such sources include
construction, industrial processes, fossil fuel combustion, dust storms,
deserts, and forest fires. Classified according to its effective
aerodynamic diameter, PM can have varying health impacts upon inhalation.
Larger PM particles can induce respiratory illnesses, and smaller PM particles,
which penetrate the respiratory system further than larger particles, can cause
cardiovascular illnesses. Air quality affects many forms of life.
Thus, the presence of air quality monitoring is eminent. In 2001, the EPA
implemented the Nitrogen Oxides State Implementation Call (NOx-SIP
Call) in an effort to mitigate ozone formation. However, the ability to
measure the true effectiveness of such emission control legislation is
complicated by the impact of meteorological factors on ambient air
quality. By creating an autoregressive linear model which accounted for
these meteorological variables, it was determined that the NOx-SIP
Call was successful in curbing ozone formation in North Carolina. Was
this legislation successful in curbing PM concentrations, as well? The
purpose of this project was to use the EPA’s continuous hourly Air Quality
System data for Site 14 in Raleigh, North Carolina to create an autoregressive
linear time series model which takes into account meteorological and seasonal
variations in PM from November 1998 to January 2007. This will be
supplemented with an examination of the North Carolina Department of the Environment
and Natural Resources air quality monitoring sites.
Fine particulate matter (PM fine) is a complex
mixture of tiny particles of solids and liquids suspended in the air.
PM2.5 consists of particles that measure 2.5 micrometers in diameter or less,
and is composed of sulfates, metals, crustal matter,
and other elements. The main source of PM2.5 comes from the combustion or
burning of fuels via power plants, industries, and motor vehicles. Scientific
studies have identified the following health problems to be associated with
high exposure to PM2.5: aggravated asthma, chronic bronchitis, and even
premature death. National emissions inventory has been using 31.4% to
describe the ratio of crustal matter to total PM2.5,
while ambient air samples suggest a lower ratio. This study is being conducted
to better understand the discrepancy between emissions inventory estimates and
actual measurements from ambient air samples, as well as improve the accuracy
of the current ratio being used. Ambient air samples are taken from Speciation
Trends Network (STN) sites and Interagency Monitoring for Protected Visual
Environments (IMPROVE) sites. Previously it has been discovered that higher
ratios exist in the West compared to the East, and in the South verses the
North. Work currently being conducted shows that taking the log of the crustal matter and PM2.5 measurements, normalizes the data
and allows assumptions associated with regression to be met. We are furthering
this analysis by incorporating meteorology and harvest data with the
transformed data. This work will result in recommendations on how to “adjust”
the emissions inventory so that it more closely agrees with ambient air
samples, which may improve the air quality management process. It is critical
to explore this discrepancy so that U.S Environmental Protection Agency, along
with state and local environmental agencies, will take necessary action to use
the most accurate ratio.
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Last modified June 2008 by Sharon E. Hunt