P1.38
Atmospheric Aerosol Monitoring of Particulate Matters in the Washington DC Airshed
Esther B. Effiong, Washington, DC; and V. Morris, D. Raghavan, and C. Hosten
Atmospheric aerosol particulate matters (PM) are known to contain in/organic materials in variable amounts depending on source and location. In most part of Washington DC, inorganic compounds comprise the majority of the total suspended particle mass due to the presence of power plant, heavy road traffic, and industrial activities from nearby states, thereby supporting the Center for Disease Control ranking (1999) as one of the nation's cities with the worst air quality for a population of 550,521 (2005 estimates), necessitating continuous monitoring. PM sizes are an important factor in zeroing the site of deposition in the respiratory tract, however, it is unclear whether the mass load itself, coupled with other factors such as number of particles, total surface area, chemical and biological compositions could be the causative parameters since they persist in the airspace for long periods of time. This project is a two study design intended to address associations between ambient PM seasonal concentrations to exposure risk pattern. The first will be a time-series analysis of cause relating to deviation in particle trend and co-pollutant level in order to determine the relationship of particle exposures / time variation to the concentrations measured with controlled Laser Particle Counters (LPC) indoor, for later outdoor comparison to establish the key factors influencing this relationship. The second phase will compare outcomes of preceding analysis with results from Howard University, Beltsville, which may likely have different PM compositions measured by a central monitoring station against WHO/NAAQ standards. This should add significant new information about the relative contributions of particle count, size, chemical compositions; as well as link concentration data with health outcomes. Preliminary results so far indicate PM indoor concentrations with a linear trend and an average correlation of 0.41, and time series plot indicates same trend for different size bin. Research is on-going.
Poster Session 1, Poster Session I
Thursday, 12 November 2009, 5:15 PM-6:15 PM
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