Development of a Tagged Species Source Apportionment Algorithm to Characterize 3-Dimensional Transport and Transformation of Precursors and Secondary PollutantsEPA Grant Number: R832163
Title: Development of a Tagged Species Source Apportionment Algorithm to Characterize 3-Dimensional Transport and Transformation of Precursors and Secondary Pollutants
Investigators: Tonnesen, Gail
Institution: University of California - Riverside
EPA Project Officer: Chung, Serena
Project Period: January 20, 2005 through January 19, 2007
Project Amount: $260,126
RFA: Source Apportionment of Particulate Matter (2004) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
Fine particles (PM2.5) in ambient air have been linked to a range of serious respiratory and cardiovascular health problems. However, the relationship between sources and ambient concentrations of these particles is poorly understood. The objective of this project is to develop a new algorithm in the Community Multiscale Air Quality (CMAQ) model for tracking the contributions of selected emissions sources to the formation of fine particles. We hypothesize that the new algorithm will provide results that are consistent with data analysis methods for source apportionment and that the method will be useful in modeling studies for identifying important emissions categories and developing emissions reduction strategies to attain PM air quality goals.
Numerical algorithms using reactive tracers will be developed for use in air quality models to track the mass contribution of selected emissions source categories and source regions. This effort will build on our previous work to implement a tagged species source apportionment algorithm in the Community Multiscale Air Quality (CMAQ) model. In this study, we will explore several new algorithms for updating the tracer concentrations at each time step in the model. We will also extend the current algorithm to include formation and source attribution of organic aerosols. To test the new algorithms, we will perform CMAQ model simulations using scenarios that we have previously developed for annual simulations of fine PM and regional haze for the continental U.S. Results of the new algorithm will be compared with other types of source apportionment analysis including model sensitivity simulation and ambient data analysis methods.
Results of this research will include new algorithms for attributing PM at receptor sites to its sources of precursor emissions. Post-processing programs that will be developed to visualize the results of the source apportionment algorithm. These will include processors to allow the use of VIS5D to visualize 3-dimensional transport of the tracers fields and software tools to provide bar plots showing source contributions to speciated PM and selected receptor sites. Evaluation of the tools will include CMAQ model performance results at the receptor site by comparison with several ambient monitoring networks and comparison of source attributions to results of research currently being carried out at DRI using data analysis methods.