Seminar

Abstract

Emission inventories are used in models to predict or estimate the atmospheric chemical composition at mesoscale (air quality forecasts) and global scale (climate system). Emission inventories are difficult to estimate at mesoscale because observations with good spatial (~km) and temporal (~hour) resolution covering a large domain are required.

In this talk, I present an inverse modeling method to evaluate emission inventories at mesoscale using aircraft observations. The presentation focuses on results in the Houston area using aircraft measurements during the 2000 and 2006 Texas Air Quality Study (TexAQS 2000 and 2006) field campaigns. Houston is known for having serious problems with non-attainment of air quality standards, and its surface emissions are often poorly represented in inventories. Evaluations of CO, NOy and SO₂ emission in the most recent 4-km resolution EPA NEI inventory are presented. Using the measurements in 2000 and 2006, the interannual variability of surface emissions is shown and linked to variations in industrial and urban activity.

Finally, we present a new method to calculate an emission inventory for an anthropogenic pollutant without a prior emission estimate. This method employs linear relationships between mixing ratios of a given pollutant (for instance, CO₂) with other co-emitted tracers measured by the aircraft in conjunction with the optimized emission inventories of those tracers (in this case, CO, NOy, and SO₂). We demonstrate the validity of this technique by constructing an emission inventory of anthropogenic CO₂ in the Houston area and comparing it to the Vulcan CO₂ inventory.