Identifying pollutant source directions using multiple analysis methods at a rural location in New York

Abstract: We identify the directionality of sources contributing to observed pollutant concentrations at a rural site through the use of the analysis methods of Conditional Probability Function (CPF) and the Source Direction Probability (SDP). Input data consists of hourly averaged PM2.5 mass, Organic Mass (OM) from Organic Carbon (OC), optical Elemental Carbon (optical EC), SO2, CO, NOy, O3 concentrations and metrological data from Pinnacle State Park site in rural New York State for the period of Dec 2004 to Dec 2008. These measured pollutants are coupled with on-site wind data to identify the directionality of the sources; which are then compared to known stationary source locations from the EPA Air Data web site. Although the CPF plot of the O3 showed no distinct directionality source area, the Pinnacle State Park site was frequently impacted by plumes of relatively high PM2.5 mass, SO2, CO, NOy, optical EC and OM concentrations. Further analysis of the enhanced pollution occurrence frequency from the eastern sector revealed two peaks in the time-of-day distribution of elevated CO, NOy, and optical EC, which provides additional information on the sources. This contrasts with the enhanced pollution occurrence frequency from the south for CO, OM, and optical EC, which shows a single morning peak in its time-of-day distribution and indicates a somewhat more distant, but common source for these carbon-containing pollutants. PM2.5 mass corresponds to the source areas related to emission facilities listed in the EPA Emissions Inventory, which is further confirmed by correlation and analysis of aerosol optical depth (AOD) data from Moderate-resolution Imaging Spectrometer (MODIS) on board Terra and Aqua satellites. We present evidence that most of the high pollution episodes likely arise from emission sources located several hundred kilometers from the site, indicating mid-long range transport of pollutants to this location. [Copyright &y& Elsevier]