Abstract
Research and development (R&D) facility emissions are difficult to characterize due to their variable processes, changing nature of research, and large number of chemicals. Positive matrix factorization (PMF) was applied to volatile organic compound (VOC) concentrations measured in the main exhaust stacks of four different R&D buildings to identify the number and composition of major contributing sources. PMF identified between 9 and 11 source-related factors contributing to stack emissions, depending on the building. Similar factors between buildings were major contributors to trichloroethylene (TCE), acetone, and ethanol emissions; other factors had similar profiles for two or more buildings but not all four. At least one factor for each building was identified that contained a broad mix of many species and constraints were used in PMF to modify the factors to resemble more closely the off-shift concentration profiles. PMF accepted the constraints with little decrease in model fit.
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