PNNL

Abstract

The Pacific Northwest National Laboratory (PNNL) operates multidisciplinary laboratory Research and Development (R&D) facilities for the U. S. Department of Energy and sampled air chemical emissions from some of these facilities from 1998 until 2008. Although sampling was not required for environmental compliance, PNNL conducted sampling to provide data to compare estimated release fractions to those used for emissions estimates and to verify that methods used to determine compliance with air regulations and permits conservatively predict actual emissions. Sampling also identifies and quantifies air toxics emitted to compare with compliance limits established by the State. The sampling data provides a unique opportunity to quantify emissions and investigate factors potentially impacting emissions. Previous work using this data set include a paper by Woodruff, Benar, and McCarthy1 who summarized the compliance approach used by PNNL and described sampling and analytical measurements for the first sampling campaigns. Conclusions reported in the paper were that none of the measurements of the target compounds exceeded a State acceptable source impact level (ASIL)2 even using significant overestimation factors, and that an average release fraction calculated from the data provided reasonable validation of the factor used in compliance assessments. Other reports using the data include the following: • A metric was developed by Ballinger, Duchsherer, and Metoyer3 to compare chemical signatures. The analysis found similarities in chemical signatures from three of the buildings but a markedly different signature from the fourth building. • A method was developed and used on the data to rank the chemical compounds that present the greatest risk to a potential downstream receptor and to determine whether the sampling parameters and detection limits provided sufficient resolution to verify compliance at potential receptor locations.4 • The stack data from one of the buildings was analyzed using a statistical technique called Positive Matrix Factorization (PMF) to identify the number and composition of major contributing sources to measured stack concentrations.5 In this analysis, a method is described that uses a Monte Carlo technique to produce a distribution of emission estimates from the measured data. The method is applied to one of the chemicals previously identified as more significant than others using the ranking process.4 Variations on the method are investigated and compared to determine their effects on the emission estimates.