2005 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, 2004 through December 26, 2005
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:

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
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)
  • Abstract from PubMed
  • Full-text: ES&T-Full Text HTML
    Exit
  • Abstract: ES&T-Abstract
    Exit
  • Other: ES&T-Full Text PDF
    Exit
  • 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)
    R832159 (2007)
    R832159 (Final)
    R829213 (Final)
    R830960 (Final)
    R831076 (2007)
    R831076 (Final)
  • Full-text: ScienceDirect-Full Text HTML
    Exit
  • Abstract: ScienceDirect-Abstract
    Exit
  • Other: ScienceDirect-Full Text PDF
    Exit
  • 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)
    R832159 (2006)
    R832159 (2007)
    R832159 (Final)
    R831076 (2006)
    R831076 (Final)
  • Full-text: Science Direct-Full Text HTML
    Exit
  • Abstract: Science Direct-Abstract
    Exit
  • Other: Science Direct-Full Text PDF
    Exit
  • 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)
    R832159 (2006)
    R832159 (2007)
    R832159 (Final)
    R830960 (Final)
    R831076 (2005)
    R831076 (2006)
    R831076 (Final)
  • Full-text: Taylor & Francis-Full Text HTML
    Exit
  • Abstract: Taylor & Francis-Abstract
    Exit
  • Other: Taylor & Francis-Full Text PDF
    Exit
  • 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)
    R832159 (2007)
    R832159 (Final)
    R830960 (Final)
    R831076 (2006)
    R831076 (Final)
  • Full-text: Science Direct-Full Text HTML
    Exit
  • Abstract: Science Direct-Abstract
    Exit
  • Other: Science Direct-Full Text PDF
    Exit
  • 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, 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
  • 2006 Progress Report
  • Final Report