Grantee Research Project Results
2006 Progress Report: Development of a Tagged Species Source Apportionment Algorithm to Characterize 3-Dimensional Transport and Transformation of Precursors and Secondary Pollutants
EPA Grant Number: R832163Title: 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 Period Covered by this Report: January 20, 2006 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
Objective:
The goal of this project was to develop new algorithms in the Community Multiscale Air Quality (CMAQ) model to evaluate source apportionment of fine particulate matter, and to test the results of the algorithm by comparing results to other modeling or data analysis methods. The new algorithm can be used to evaluate the emissions source categories and source regions that contribute to PM2.5 at any given receptor site in CMAQ model simulations.
Progress Summary:
We implemented the Tagged Species Source Apportionment (TSSA) algorithm in CMAQ version 4.5. This required the development of 23 new subroutines in the CMAQ model, and modifications to 18 existing subroutine, and approximately 10,000 lines of new code were written as part of this effort. The TSSA algorithm was tested by comparing the TSSA source apportionment results to model sensitivity simulations for: (1) trace species with no chemical reactions, for which the TSSA results and sensitivity results were nearly identical; and (2) trace species with chemical reactions, for which TSSA results and sensitivity results were similar but not identical because of non-linearity in the chemistry in the model sensitivity simulations. We also compared the TSSA source apportionment results to a similar algorithm in the CAMx air quality model, using the same model scenario and input data, and we found that the results were generally similar between the two models, although there significant differences in the contributions from boundary conditions in the two models, and there were generally small differences in the rank order of the major source contributors at receptor sites. Detailed results of the testing and model comparisons are available on the project webpage: http://www.cert.ucr.edu/aqm/tssa Exit . We also attempted to compare the CMAQ TSSA results to back-trajectory modeling studies completed by the Desert Research Institute (DRI) at the University of Nevada, however, the DRI results were not available on a temporal resolution that could be compared to our results. The new TSSA algorithms in CMAQ provide a useful modeling tool for identifying specific emissions sources that contribute to fine particulate matter and to haze at any given location. This will be useful to regulators and policy makers in identifying emissions sources that should be further evaluated in developing emissions reductions strategies for attaining ambient air quality goals.
Future Activities:
None. The code development is complete and it has been submitted to the USEPA Office of Research and Development.
Supplemental Keywords:
aerosols, sulfate, nitrate,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Air Quality, Environmental Chemistry, Monitoring/Modeling, Environmental Monitoring, Environmental Engineering, particulate organic carbon, atmospheric dispersion models, atmospheric measurements, model-based analysis, source apportionment, chemical characteristics, emissions monitoring, environmental measurement, airborne particulate matter, air quality models, 3 dimensional transport model, community multiscale air quality model, air quality model, air sampling, speciation, particulate matter mass, analytical chemistry, aersol particles, modeling studies, chemical transport models, real-time monitoring, aerosol analyzers, chemical speciation sampling, particle size measurementRelevant Websites:
A project website has been created to display results of the code testing and model comparisons: http://www.cert.ucr.edu/aqm/tssa Exit .
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.