2006 Progress Report: Integrated Source/Receptor-Based Methods for Source Apportionment and Area of Influence Analysis

EPA Grant Number: R832159
Title: 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, 2005 through December 26,2006
Project Amount: $444,899
RFA: Source Apportionment of Particulate Matter (2004) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air

Objective:

  • Assess the impact of emission categories on PM2.5 by reconciling the receptor and air quality modeling methods.
  • Identify the reasons for the discrepancy between sources of PM2.5 apportioned from the air quality model and those from the receptor model.
  • Improve the emission inventory for each source category via inverse modeling.
  • Apply Area of Influence (AOI) analysis to quantify the influence of any source’s emissions on the air quality at the receptor’s location.

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 is the Community Multiscale Air Quality (CMAQ) model, part of EPA MODELS-3, and the receptor-based method used is the Chemical Mass Balance models (CMB). The modeling was done over the United States for July 2001 and January 2002, periods that correspond to the Eastern Supersite Program. Receptor-oriented sensitivities were then found by inverting the set of forward sensitivities and can be used to identify areas whose emissions potentially have a large influence on air quality at a specific receptor, i.e., the AOI. Much of the progress in the previous year was to identify AOI in Atlanta, GA, for ozone and particulate matter (PM) and to improve AOI performance by adding more “seed points.”

All the publications and presentations related with this project are listed below.

Future Activities:

Future activities include: (1) further inverse modeling for each source category defined in CMB and CMAQ; and (2) further regional apportionment of primary and secondary PM sources.


Journal Articles on this Report : 8 Displayed | Download in RIS Format

Other project views: All 50 publications 24 publications in selected types All 24 journal articles
Type Citation Project Document Sources
Journal Article 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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  • Journal Article 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)
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    R829213 (Final)
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  • Journal Article Marmur A, Mulholland JA, Russell AG. Optimized variable source-profile approach for source apportionment. Atmospheric Environment 2007;41(3):493-505. R832159 (2006)
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  • Journal Article 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)
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  • Journal Article Napelenok SL, Habermacher FD, Akhtar F, Hu Y, Russell AG. Area of influence (AOI) sensitivity analysis: application to Atlanta, Georgia. Atmospheric Environment 2007;41(27):5605-5617. R832159 (2006)
    R832159 (Final)
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  • Journal Article 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)
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  • Journal Article 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)
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    R830960 (Final)
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  • Journal Article Wade KS, Mulholland JA, Marmur A, Russell AG, Hartsell B, Edgerton E, Klein M, Waller L, Peel JL, Tolbert PE. Effects of instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, Georgia. Journal of the Air & Waste Management Association 2006;56(6):876-888. R832159 (2006)
    R832159 (Final)
    R829213 (2006)
    R829213 (Final)
  • Abstract from PubMed
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  • Supplemental Keywords:

    source apportionment, inverse modeling, direct sensitivity analysis, area of interest,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Air Quality, Environmental Chemistry, climate change, Air Pollution Effects, Monitoring/Modeling, Environmental Monitoring, Atmospheric Sciences, Environmental Engineering, Atmosphere, particulate organic carbon, atmospheric dispersion models, atmospheric measurements, model-based analysis, source receptor based methods, area of influence analysis, source apportionment, chemical characteristics, emissions monitoring, environmental measurement, airborne particulate matter, air quality models, air quality model, air sampling, speciation, particulate matter mass, analytical chemistry, aersol particles, modeling studies, real-time monitoring, aerosol analyzers, chemical speciation sampling, particle size measurement

    Progress and Final Reports:

    Original Abstract
  • 2005 Progress Report
  • Final Report