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NARSTO Workshop on Innovative Methods for Emission Inventory Development and Evaluation University of Texas, Austin October 14-17, 2003 |
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Integrated SOx Emission Trend Estimation for the Sustainability Transition
R. Husar, J. Agan, K. Miller, J. Reynolds and C. Reid, J. Husar, S. Falke
Washington University in St. Louis
This is an integrated trend analysis for the aggregate US SOx emission, for the period 1940-2100. The emissions model is based on a causality tree that linearly links emissions to population dynamics through a set of coefficients that account for energy consumption, fuel mix and technological factors. The analysis is based largely on historical data (1940-2000) on the causal factors: population, economic activity, energy/fuel use and SOx emissions. The time-pattern of the coefficients is fitted to historical data. Special attention is focused on the time trends of fuel switching and sulfur removal and/or recovery in various source categories.
A spatial allocation methodology based on mass and energy conservation will be demonstrated. In particular, the resulting spatial transfer functions (tensors) associated with the distribution of electric energy (electric power grid) and the flow of coal from the mines to the consumers will be illustrated.
The exploration of future SOx emissions during the sustainability transition, (2000-2100) is conducted by scenarios which include (1) assumed pattern of key drivers, population and energy-materials use/per person (2) extrapolation of trends in fuel mix and sulfur removal/recovery in each of the major sectors, particularly for electric utilities.
The emissions model is initially developed for sulfur oxides, which is the dominant man-made PM2.5 component in most areas of the US. However, the methodology is applicable to other pollutants mobilized by fuels and minerals, e.g. mercury. The SOx emissions analysis is intended to aid long-term air quality management processes such as those specified by the Regional Haze Rule (attainment by 2065). Anticipated users of the model include EPA, Regional Planning Organizations and individual state agencies.