Application of the pseudo-deterministic receptor model to resolve power plant influences on air quality in Pittsburgh

A multivariate pseudo-deterministic receptor model was applied to determine emission and ambient source contributions rates Of SO2 and elements from four small coal-fired boilers influencing air quality at the Carnegie Mellon University (CMU) Supersite. The model was applied to ambient SO2 and particle measurements, the latter, made every 30-min for 10 elements (Al, As, Cr, Cu, Fe, Mn, Ni, Ph, Se, and Zn) during a 12.5-h period on April 1, when winds blew from between 290-330 degrees in which the four coal boilers are situated. Agreement between predicted and observed SO2 concentrations was excellent (r of 0.92; and their ratio, 1.09 +/- 0.22) when 4 emission sources were used in the model. Average ratios of predicted and observed concentrations for As, Cr, Cu, Ni, Ph, Se, and Zn varied from 0.97 +/- 10.20 for Cr to 1.07 +/- 0.44 for As. Performance indices for these elements were all well within acceptable ranges. Emission rate ratios of various metal species to Se predicted are similar for the three of the coal boilers, but differed substantially for the fourth, as expected for a boiler with minimal particle control technology. All are within the range derived from previous PDRM results and in-stack measurements (except Al) at 7 Eastern U.S. coal-fired power plants. The results suggest that the PDRM approach is applicable to a city encompassing complex topography and may successfully be applied using commonly available meteorological data.