Grantee Research Project Results
Final Report: Source-Oriented Chemical Transport Model for Primary and Secondary Organic Aerosol
EPA Grant Number: R831082Title: Source-Oriented Chemical Transport Model for Primary and Secondary Organic Aerosol
Investigators: Kleeman, Michael J. , Griffin, Robert J. , Clegg, Simon
Institution: University of California - Davis , University of New Hampshire
EPA Project Officer: Chung, Serena
Project Period: October 1, 2003 through September 30, 2006 (Extended to September 30, 2008)
Project Amount: $450,000
RFA: Measurement, Modeling, and Analysis Methods for Airborne Carbonaceous Fine Particulate Matter (PM2.5) (2003) RFA Text | Recipients Lists
Research Category: Air , Air Quality and Air Toxics , Particulate Matter
Objective:
Model the formation of secondary organic aerosol using a state-of-the-science air quality model, and to determine source contributions to primary organic aerosol (POA) and secondary organic aerosol (SOA) concentrations in Los Angeles, the San Joaquin Valley, and St. Louis . In the first phase of the project we will determine if the treatment of the aerosol as an internal mixture in bulk equilibrium with the surrounding gas phase biases SOA calculations. In the second phase of the project we will predict source contributions to primary and secondary organic aerosl, and compare these predictions to the results of receptor-oriented source aportionment models where possible. Improvements will be made to the mechanisms that predict SOA formation throughout the project so that the most accurate sourceapportionment can be achieved.
Summary/Accomplishments (Outputs/Outcomes):
Improvements to the SOA formation mechanisms for monoterpenes and alkanes within the Caltech Atmospheric Chemistry Mechanism (CACM) generally increase predicted SOA concentrations. The latest version of CACM was integrated into the UCD/CIT source-oriented air quality model and CMAQ. Comparisons were made to previous mechanisms for SOA formation to verify performance during a severe photochemical smog episode. Despite a small increase in predicted SOA concentrations, the total organic aerosol concentrations during each of the episodes were still under-predicted by 30-50% except in cases where POA concentrations were very large.
Reasonable ranges of vapor pressures for semi-volatile organic surrogate species were calculated using a several alternative compound estimation techniques. Simulations conducted for the South Coast Air Basin during a severe photochemical smog event showed that uncertainty in estimated vapor pressures for surrogate species could change predicted SOA concentrations by a factor of two. The majority of the additional SOA produced by this change would not be water-soluble. Increasing the amount of predicted water insoluble SOA with no changes to predicted water-soluble SOA concentrations would not match measured trends. This suggests that systematic under-predictions for SOA are not caused by uncertainty of parameter estimation within the current SOA framework. Rather, it is likely that an important mechanism for the formation of water-soluble SOA is simply missing from current model calculations.
The representation of the aerosol as an internal mixture or a source-oriented external mixture had little effect on SOA formation because our current understanding and representation of the primary organic aerosol is so rudimentary that mixing state has little effect on calculated activity coefficients. It is expected that if the formation pathway for water-soluble SOA was understood, then mixing state of the aerosol would influence SOA formation. Future improvements in water-soluble SOA mechanisms can easily be tested with the modeling tools developed in the current project.
Grid model apportionment tools developed for primary organic aerosol (POA) generally agree with CMB calculations for source contributions to POA during 3 different field studies within California . The grid model source apportionment tools are able to provide a regional analysis of source contributions. Sharp spatial gradients were apparent in certain source contributions, such as biomass combustion POA during winter episodes within the SJV. The regional model calculations also revealed sources that have been missed in previous measurement studies, including the Port of Los Angeles and Los Angeles International Airport.
Grid model apportionment tools developed for secondary organic aerosol (SOA) were developed by tracking precursor VOC emissions from different sources separately through the full photochemical oxidation system. These SOA source apportionment tools are useful because they explain source contributions to the fraction of SOA formation that is currently understood, and they can be applied to future SOA mechanisms. The current SOA source apportionment studies predict that gasoline combustion dominates SOA formation in central Los Angeles with much smaller contributions from diesel engines. Biogenic sources can make a surprisingly large contribution in the northern and southern portions of the South Coast Air Basin surrounding Los Angeles . Winter SOA concentrations in central California are dominated by solvent use, with gasoline combustion making the next largest contribution. Diesel engines once again played a minor role in SOA production in central California . All of the source apportionment tools can be applied to future SOA formation mechanisms once the source of atmospheric water-soluble SOA is better understood.
Conclusions:
Tools for the regional source apportionment of primary and secondary organic aerosol were successfully developed and applied in multiple air quality studies across the United States . Modeled episodes include the eastern United States (Aug 3-4, 2000), the South Coast Air Basin (Sept 7-9, 1993; Sept 23-25, 1996) and the San Joaquin Valley (Jan 4-6, 1996; Dec 15 2000 – Jan 7, 2001). General patterns and conclusions can be draw by synthesizing across these multiple episodes.
Journal Articles on this Report : 13 Displayed | Download in RIS Format
Other project views: | All 28 publications | 13 publications in selected types | All 13 journal articles |
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Chen J, Griffin RJ. Modeling secondary organic aerosol formation from oxidation of α-pinene, β-pinene, and d-limonene. Atmospheric Environment 2005;39(40):7731-7744. |
R831082 (2004) R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Chen J, Mao H, Talbot RW, Griffin RJ. Application of the CACM and MPMPO modules using the CMAQ model for the eastern United States. Journal of Geophysical Research--Atmospheres 2006;111(D23):D23S25 (12 pp.). |
R831082 (2006) R831082 (2007) R831082 (Final) R831454 (2005) R831454 (2006) R831454 (2007) R831454 (Final) |
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Chen J, Ying Q, Kleeman MJ. Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study. Atmospheric Environment 2010;44(10):1331-1340. |
R831082 (Final) |
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Clegg SL, Kleeman MJ, Griffin RJ, Seinfeld JH. Effects of uncertainties in the thermodynamic properties of aerosol components in an air quality model – Part 1: treatment of inorganic electrolytes and organic compounds in the condensed phase. Atmospheric Chemistry and Physics 2008;8(4):1057-1085. |
R831082 (2006) R831082 (2007) R831082 (Final) |
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Clegg SL, Kleeman MJ, Griffin RJ, Seinfeld JH. Effects of uncertainties in the thermodynamic properties of aerosol components in an air quality model – Part 2: predictions of the vapour pressures of organic compounds. Atmospheric Chemistry and Physics 2008;8(4):1087-1103. |
R831082 (2006) R831082 (2007) R831082 (Final) |
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Griffin RJ, Dabdub D, Seinfeld JH. Development and initial evaluation of a dynamic species-resolved model for gas phase chemistry and size-resolved gas/particle partitioning associated with secondary organic aerosol formation. Journal of Geophysical Research – Atmospheres 2005;110(D5):D05304 (16 pp.). |
R831082 (2004) R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Held T, Ying Q, Kleeman MJ, Schauer JJ, Fraser MP. A comparison of the UCD/CIT air quality model and the CMB source-receptor model for primary airborne particulate matter. Atmospheric Environment 2005;39(12):2281-2297. |
R831082 (2004) R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Jordan CE, Ziemann PJ, Griffin RJ, Lim YB, Atkinson R, Arey J. Modeling SOA formation from OH reactions with C8-C17 n-alkanes. Atmospheric Environment 2008;42(34):8015-8026. |
R831082 (Final) |
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Kleeman MJ, Ying Q, Lu J, Mysliwiec MJ, Griffin RJ, Chen J, Clegg S. Source apportionment of secondary organic aerosol during a severe photochemical smog episode. Atmospheric Environment 2007;41(3):576-591. |
R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Vutukuru S, Griffin RJ, Dabdub D. Simulation and analysis of secondary organic aerosol dynamics in the South Coast Air Basin of California. Journal of Geophysical Research–Atmospheres 2006;111(D10):D10S12 (13 pp.). |
R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Ying Q, Kleeman MJ. Source contributions to the regional distribution of secondary particulate matter in California. Atmospheric Environment 2006;40(4):736-752. |
R831082 (2004) R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Ying Q, Fraser MP, Griffin RJ, Chen J, Kleeman MJ. Verification of a source-oriented externally mixed air quality model during a severe photochemical smog episode. Atmospheric Environment 2007;41(7):1521-1538. |
R831082 (2005) R831082 (2006) R831082 (2007) R831082 (Final) |
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Ying Q, Lu J, Kaduwela A, Kleeman M. Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) using the UCD/CIT Source Oriented Air Quality Model – Part II. Regional source apportionment of primary airborne particulate matter. Atmospheric Environment 2008;42(39):8967-8978. |
R831082 (Final) |
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Supplemental Keywords:
Secondary Organic Aerosols, Source-oriented Chemical Transport Model, Source Apportionment, Inorganic – Organic Interactions;, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, RESEARCH, particulate matter, Air Quality, air toxics, Environmental Chemistry, Air Pollution Effects, Monitoring/Modeling, Analytical Chemistry, Monitoring, Environmental Monitoring, Engineering, Chemistry, & Physics, Environmental Engineering, carbon aerosols, air quality modeling, particle size, atmospheric particulate matter, health effects, atmospheric dispersion models, atmospheric measurements, secondary organic aerosols, aerosol particles, mass spectrometry, human health effects, air modeling, air quality models, monitoring stations, air sampling, gas chromatography, thermal desorption, carbon particles, air quality model, emissions, source oriented CMT, modeling, particulate matter mass, human exposure, secondary organic aerosol, particle phase molecular markers, monitoring of organic particulate matter, modeling studies, transport modeling, particle dispersion, aerosol analyzersRelevant Websites:
http://cee.engr.ucdavis.edu/faculty/kleeman/Default.htm 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.
Project Research Results
- 2007 Progress Report
- 2006 Progress Report
- 2005 Progress Report
- 2004 Progress Report
- Original Abstract
13 journal articles for this project