Quantification of Variability and Uncertainty in Air Pollutant Emission Inventories. H. C. Frey, S. Li, and S. Bammi, North Carolina State University
Air pollutant emission inventories are used for a variety of purposes, including emissions budgeting, trends analysis, as input to air quality models, and as input to exposure and risk assessments. Information regarding variability in air pollutant emissions is needed to identify high emitters or highly exposed populations. Information regarding uncertainty is needed to characterize the quality of an emissions inventory and to target data collection to reduce uncertainty. Our objectives are: (1) to develop methods for quantifying variability and uncertainty in air pollutant emissions; (2) to develop methods for identifying key sources of variability and uncertainty in assessments of emissions; (3) to demonstrate the methods via detailed case studies; and (4) to characterize the benefits of the methods with respect to environmental and research management. We have implemented methods for quantifying variability and uncertainty for specific inputs in an emission inventory. These methods address small data sets, averaging times, selection of parametric distributions, random sampling error, censored data sets, and mixture distributions. A two-dimensional numerical method for propagation of both variability and uncertainty through an inventory is a key feature of this work. As a component of this work, we have developed a prototype software tool for quantitative analysis of variability and uncertainty in air pollutant emissions from power plants. We have also developed specific case studies for a variety of other emission source categories, such as highway vehicles, nonroad mobile sources, natural gas-fueled engines, and gasoline bulk loading. We will present key methodological elements of this work and illustrate their application to specific case studies.
This work has been supported by the U.S. Environmental Protection Agency via two STAR grants and the Office of Air Quality Planning and Standards.
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