Highway emissions represent a major source of many pollutants. Use of local data to model these emissions can have a large impact on the magnitude and distribution of emissions predicted and can significantly improve the accuracy of local scale air quality modeling assessments. This paper provides a comparison of top-down and bottom-up approaches for developing emission inventories for modeling in one urban area, Philadelphia, in calendar year 1999. A bottom-up approach relies on combining motor vehicle emission factors and vehicle activity data from a travel demand model estimated at the road link level to generate hourly emissions data. This approach can result in better estimates of levels and spatial distribution of on-road motor vehicle emissions than a top-down approach that relies on more aggregated information and default modeling inputs. (A) "Reprinted with permission from Elsevier".
Abstract