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The International Year of Statistics (Statistics2013)
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Department of

Statistics

NCSU Dept of Statistics
5109 SAS Hall
2311 Stinson Drive
Raleigh, NC 27695-8203

Tel: (919) 515-2528
Fax: (919) 515-7591

Computation for Undergraduates in Statistics Program


2008 - 2009 Projects


Better Understanding the Discrepancy in the Ratio of Crustal Matter to fine Particulate Matter for Emission Inventories versus Ambient Air Quality Monitoring Data

Background: The crustal matter found in fine particulate matter comes from the earth's crust. It includes fugitive dust, which consists of unpaved roads, agricultural tilling, construction, etc. Stacy Jones, Lauren Klein and William Jeff Rice have found that crustal matter is affected by environmental factors such as season, wind speed, and day of the week, etc. In 2001, the National Emissions Inventory estimated that the National total percentage of crustal matter to fine particulate matter (PM2.5) was estimated at 31.4%. The ratio of crustal matter in ambient air ranges from 5-10%. Why?

Purpose: To better understand the impact of crustal matter (CM) on fine particulate matter (PM fine) air quality.

  1. Can a model be developed to explain the reason for the discrepancy in the ratio of crustal matter to fine Particulate Matter for emission inventories versus ambient air quality monitoring data?
  2. Why the discrepancy in the ratio of crustal matter to PM fine for emission inventories (31%) and ambient air quality data (5 to 10%)?
  3. What advice can be provided to the USEPA to adjust their emission inventories for air quality modeling purposes? In order for the models to provide the most accurate predictions of future fine particulate matter levels, it is critically important that the emissions inventory data are consistent with the fractions of crustal material that are observed in measured data.

Data Sources: The ambient air measurements are taken from ambient air quality monitoring sites, located in both urban areas and in national parks and wilderness areas. The Speciation Trends Network (STN) consists of approximately 50 trends sites in 2002, which are mostly urban monitoring stations. A second air monitoring network - the IMPROVE network consists of 140 air monitoring sites in 2002. This is a long-term monitoring network located in both rural areas and Federal Class I areas designated for visibility monitoring. The data consists of the many components that make up fine particulate matter including crustal material. In addition, meteorological data will be provided by the National Oceanic and Atmospheric Administration.

Client: Mr. Tom Pace, Office of Air Quality Planning and Standards, USEPA

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