Improved Strategies for Mobile Emissions Processing

摘要

The preparation of mobiel-source emissions for urban and regional air quality modeling is a complex, multiple-stage, data-intensive process that requires an integrated, organized, and efficient appraoch. Current mobiel processing methods are inefficient for two reasons: (1) the use of MOBILE5 to calculate emission factors for many input configurations with spatially and temporally varying temperatures, and (2) the arrangement of the various processing stages. This paper summaries the major challenges of mobile emissions processing, and then addresses these using the Sparse Matrix Operator Kernel Emissions (SMOKE) processign approach.