Grantee Research Project Results
2008 Progress Report: Development and Assessment of Environmental Indicators: Application to Mobile Source Impacts on Emissions, Air Quality and Health Outcomes
EPA Grant Number: R833626Title: Development and Assessment of Environmental Indicators: Application to Mobile Source Impacts on Emissions, Air Quality and Health Outcomes
Investigators: Russell, Armistead G. , Sarnat, Stefanie Ebelt , Mulholland, James , Sarnat, Jeremy , Pachon, Jorge , Klein, Mitchel , Tolbert, Paige
Current Investigators: Russell, Armistead G. , Sarnat, Stefanie Ebelt , Mulholland, James , Sarnat, Jeremy , Klein, Mitchel , Tolbert, Paige
Institution: Georgia Institute of Technology , Emory University
EPA Project Officer: Hahn, Intaek
Project Period: October 1, 2007 through September 30, 2010 (Extended to September 30, 2011)
Project Period Covered by this Report: October 1, 2007 through September 30,2008
Project Amount: $499,512
RFA: Development of Environmental Health Outcome Indicators (2006) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air Toxics , Human Health , Air
Objective:
- Develop approaches to identify outcome-based indicators and apply those approaches to mobile sources in Atlanta for the period 1998-2004 using data and methods of varying detail and complexity.
- Test a range of integrated indicators for the impact of mobile source emission changes on air quality and cardiovascular health.
- Develop and apply approaches for assessing these indicators for their ability to represent a range of outcomes associated with mobile source emissions and policies.
- Evaluate select indicators using an independent, new data set of emissions, air quality and cardiovascular health endpoints for 2005-2009 to assess the approaches developed for identifying, testing, assessing and refining outcome indicators.
Progress Summary:
One of the objectives during the first year was to develop a method to assess health outcomes from mobile source pollutants. Among the methods that will be tried to complete this task, the factor analysis technique (specifically Positive Matrix Factorization) has been shown to be effective and useful.1 During the period covered by the report, particulate and gaseous phase data from 1999-2004 in Atlanta were collected, evaluated and analyzed. These data were used to run the EPA-PMF v1.1 and the new released PMF v3.0, in order to identify the profiles and daily impacts of the main emission sources in Atlanta. Special attention was given to uncertainties, both in the input and output files (profiles and source impacts).
In the identification of factors by EPA-PMF, temperature-resolved carbon fractions (OC1 thru OC4, EC1 thru EC3 and OP) and gas species (NOx, NOy, SO2, CO, O3) were helpful. Typical sources for Atlanta aerosol and their contribution to the PM2.5 were identified as: Secondary Sulfate (41%), Wood burning (9%), Secondary Nitrate (7%), Diesel vehicles (17%), Metal processing (3%), Gasoline vehicles (5%), Soil Dust (2%), cement (4%), and an unknown OC source (12%) possibly related with secondary aerosols. These results were compared with previous studies in the area2-5 demonstrating good performance of the PMF technique.
Since the organic carbon constitutes a significant fraction (at least 30%) of the PM2.5 in Atlanta, and it is by far the most uncertain species within all the components, we performed an empirical estimation of the primary (POC) and secondary organic carbon (SOC) using the original data from 1999-2004. We found that between 24% and 36% of the total organic carbon can be of secondary origin. These fractions were included as a new set of data to run the PMF, resulting in the finding of a new factor associated with the SOC fraction and responsible for approximately 9% of the PM2.5 in the ambient air.
Future Activities:
- Looking at previous results with sensitivity analysis in Atlanta we will estimate and include the vehicular fraction of the ozone in our PMF analysis. This will give us more confidence about the contribution of mobile sources in the source apportionment method.
- Include residuals in the health outcomes, in the form of Emergency Department (ED) visits from a Poisson regression model, in the PMF analysis. The health outcomes accompanied by the respective uncertainties will be gathered from 41 Hospitals in the Atlanta area from the period 1999-2004. In this case, the residuals are the difference between the observed and expected ED visits based upon non-air quality factors (e.g., temperature, day of week).
- Complementary to the PMF analysis, we will conduct CMB using the optimized source profiles provided by the ensemble-trained source apportionment study.
References:
- Sarnat Jeremy, Marmur Amit, Klein Mitchel, Kim, Eugene, Russell Armistead, Sarnat Stefanie, Mulholland James, Hopke Philip K, Tolbert Paige E. 2008. Fine particle sources and cardiorespiratory morbidity: An application of chemical mass balance and factor analytical source-apportionment methods. Environmental Health Perspectives 116: 459-466.
- Kim Eugene, Hopke Philip and Edgerton Eric. 2003. Source Identification of Atlanta Aerosol by Positive Matrix Factorization. J. Air & Waste Manage. Assoc. 53:731-739.
- Kim Eugene, Hopke Philip and Edgerton Eric. 2004. Improving source identification of Atlanta aerosol using temperature resolved carbon fractions in positive matrix factorization. Atmospheric Environment 38: 3349-3362.
- Marmur A, Unal A, Mulholland J, Russell A. 2005. Optimization based source apportionment of PM2.5 incorporating gas-to-particle ratios. Environmental Science and Technology 39: 3245-3254.
- Marmur A, Unal A, Mulholland J, Russell A. 2005. Optimized variable source-profile approach for source apportionment. Atmospheric Environment 41: 493-505.
- Cohan Daniel, Hakami Amir, Hu Yongtao, Russell Armistead. Nonlinear response of ozone to emissions: source apportionment and Sensitivity Analysis. Environ. Sci. Technol. 2005, 39: 6739-6748.
- Liao K.J., Efthimios Tagaris, Kasemsan Manomaiphiboon, Sergey L. Napolenok, Jung-Hun Woo, Shan He, Praveen Amar, and Armistead G. Russell. Environmental Science & Technology 2007, 41: 8355–8361.
- Siv Balachandran, Dongho Lee Jorge Pachon, Sangil Lee, and Armistead G. Russell. Ensemble-Trained PM2.5 Source Apportionment Approach for Health Studies. In preparation.
Journal Articles:
No journal articles submitted with this report: View all 19 publications for this projectSupplemental Keywords:
source apportionment, PMF, secondary aerosols, mobile sources,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.