Paper No. 3
Presentation Time: 8:00 AM-12:00 PM
COMBINING REMOTE SENSING WITH GROUND MONITOR DATA TO PREDICT SHORT-TERM ATMOSPHERIC DISTRIBUTION OF FINE PARTICULATE MATTER IN SOUTHWEST VIRGINIA
Virginia City, located in Wise County, Virginia has been selected as a site for a new coal-fired power plant, which will begin operation in 2012. Because coal-fired power plants are the largest source of the United States' most harmful air pollutants, understanding regional air quality and short term atmospheric circulation is crucial to predicting the potential effects of power plant emissions on regional air quality. We used satellite imagery to assess current regional air quality and computer models to predict short-term atmospheric circulation patterns. Fine mass particulate matter 2.5 was compared to the aerosol optical depth parameter collected by the Terra and Aqua satellite platforms. Comparisons of aerosol optical depth with ground data show close correlations between the two data sources, indicating that aerosol optical depth is an acceptable substitute for surface monitors within the study region. In addition, we used NOAA's HYSPLIT model to create seventy-two hour trajectories for each day that ground data was collected to determine how frequently national parks and major cities surrounding the area were intersected by trajectories plotted from the site of the proposed power plant. Results show that 40% of trajectories created for the year 2005 intersect major cities in the region, with 11% intersecting the city of Knoxville alone. There are three national parks within close proximity of the proposed site of the power plant and 17% of plotted trajectories for the year 2005 intersected these parks. Emissions from coal-fired power plants in southwest Virginia will likely affect the quality of air in densely populated areas and national parks, including the metropolitan area surrounding Knoxville, Tennessee, and the Great Smoky Mountains National Park, both of which frequently are subject to poor air quality conditions.