Grantee Research Project Results
2005 Progress Report: Integrated Source/Receptor-Based Methods for Source Apportionment and Area of Influence Analysis
EPA Grant Number: R832159Title: Integrated Source/Receptor-Based Methods for Source Apportionment and Area of Influence Analysis
Investigators: Russell, Armistead G. , Odman, Mehmet Talat
Institution: Georgia Institute of Technology
EPA Project Officer: Chung, Serena
Project Period: December 27, 2004 through December 26, 2007
Project Period Covered by this Report: December 27, 2004 through December 26, 2005
Project Amount: $444,899
RFA: Source Apportionment of Particulate Matter (2004) RFA Text | Recipients Lists
Research Category: Particulate Matter , Air Quality and Air Toxics , Air
Objective:
The objectives of this research project are to: (1) assess the impact of emission categories on fine particulate matter (PM2.5) by reconciling the receptor and air quality modeling methods; (2) identify the reasons of the discrepancy of sources of PM2.5 apportioned from the air quality model with those from the receptor model; and (3) improve the emission inventory for each source category via inverse modeling.
Progress Summary:
The primary goal of this project is to assess the impact of emission categories on PM2.5 by reconciling emission-based and receptor-based air quality modeling methods. The emission-based method selected was the Community Multiscale Air Quality (CMAQ) model, part of the U.S. Environmental Protection Agency Models-3, and the receptor-based method used was the chemical mass balance (CMB) models, extended here using an optimizing technique developed by Marmur and coworkers as part of this work. The modeling was done over the United States from July 2001 to January 2002, periods that correspond to the Eastern Supersite Program. Much of the progress in 2006 was to improve emission estimates via Four-Dimensional Data Assimilation using CMAQ coupled with Decoupled Direct Method 3D for PM developed by Napelenok, et al., along with inverse modeling. Separate scaling factors for six regions of the United States were calculated for weekdays and weekends. Emission adjustments improved air quality model performance. Analysis of CMAQ and CMB comparisons and inverse modeling is available in the publications/presentations resulting from this grant.section.
Future Activities:
Future activities include: (1) further inverse modeling for each source category defined in CMB and CMAQ, (2) more detailed comparison between CMAQ and CMB, and (3) further regional apportionment of primary and secondary PM sources.
Journal Articles on this Report : 5 Displayed | Download in RIS Format
| Other project views: | All 50 publications | 24 publications in selected types | All 24 journal articles |
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Marmur A, Unal A, Mulholland JA, Russell AG. Optimization-based source apportionment of PM2.5 incorporating gas-to-particle ratios. Environmental Science & Technology 2005;39(9):3245-3254. |
R832159 (2005) R832159 (2006) R832159 (2007) R832159 (Final) R829213 (2006) R829213 (Final) R830960 (Final) R831076 (2004) R831076 (2007) R831076 (Final) |
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Marmur A, Park S-K, Mulholland JA, Tolbert PE, Russell AG. Source apportionment of PM2.5 in the southeastern United States using receptor and emissions-based models:conceptual differences and implications for time-series health studies. Atmospheric Environment 2006;40(14):2533-2551. |
R832159 (2005) R832159 (2006) R832159 (2007) R832159 (Final) R829213 (Final) R830960 (Final) R831076 (2007) R831076 (Final) |
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Napelenok SL, Cohan DS, Hu Y, Russell AG. Decoupled direct 3D sensitivity analysis for particulate matter (DDM-3D/PM). Atmospheric Environment 2006;40(32):6112-6121. |
R832159 (2005) R832159 (2006) R832159 (2007) R832159 (Final) R831076 (2006) R831076 (Final) |
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Park S-K, Marmur A, Kim SB, Tian D, Hu Y, McMurry PH, Russell AG. Evaluation of fine particle number concentrations in CMAQ. Aerosol Science and Technology 2006;40(11):985-996. |
R832159 (2005) R832159 (2006) R832159 (2007) R832159 (Final) R830960 (Final) R831076 (2005) R831076 (2006) R831076 (Final) |
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Park S-K, Cobb CE, Wade K, Mulholland J, Hu Y, Russell AG. Uncertainty in air quality model evaluation for particulate matter due to spatial variations in pollutant concentrations. Atmospheric Environment 2006;40(Suppl 2):563-573. |
R832159 (2005) R832159 (2006) R832159 (2007) R832159 (Final) R830960 (Final) R831076 (2006) R831076 (Final) |
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Supplemental Keywords:
Source apportionment, inverse modeling, direct sensitivity, Analysis, emissions inventory analysis, air quality, atmospheric sciences, environmental modeling, particulate matter, aerosol particles, chemical characteristics, model-based analysis, particulate matter mass, particulate organic carbon,, RFA, Ecosystem Protection/Environmental Exposure & Risk, Scientific Discipline, Air, particulate matter, Air Quality, Atmosphere, Environmental Chemistry, Monitoring/Modeling, Air Pollution Effects, Atmospheric Sciences, climate change, Environmental Engineering, Environmental Monitoring, atmospheric dispersion models, source receptor based methods, air sampling, chemical characteristics, aersol particles, airborne particulate matter, emissions monitoring, atmospheric chemistry, real-time monitoring, speciation, modeling studies, environmental measurement, area of influence analysis, particulate matter mass, air quality model, particulate organic carbon, aerosol analyzers, source apportionment, chemical speciation sampling, particle size measurement, air quality models, analytical chemistry, atmospheric measurementsProgress 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.