2009 Progress Report: Development and Assessment of Environmental Indicators: Application to Mobile Source Impacts on Emissions, Air Quality and Health OutcomesEPA Grant Number: R833626
Title: Development and Assessment of Environmental Indicators: Application to Mobile Source Impacts on Emissions, Air Quality and Health Outcomes
Investigators: Russell, Armistead G. , Klein, Mitchel , Mulholland, James , Sarnat, Stefanie Ebelt , Sarnat, Jeremy , Tolbert, Paige
Institution: Georgia Institute of Technology , Emory University
EPA Project Officer: Nolt-Helms, Cynthia
Project Period: October 1, 2007 through September 30, 2010 (Extended to September 30, 2011)
Project Period Covered by this Report: October 1, 2008 through September 30,2009
Project Amount: $499,512
RFA: Development of Environmental Health Outcome Indicators (2006) RFA Text | Recipients Lists
Research Category: Health Effects , Health
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.
During the period covered by this report we have focused on the following activities: analysis of health outcome residuals, design of air quality indicators from mobile sources, and comparison of estimates of secondary organic carbon (SOC).
Our analysis of health outcome residuals from epidemiologic models in which air pollution has not been included as a variable, has been useful to identify air quality indicators more associated with health endpoints. We have tested relationships between different air quality species and respiratory and cardiovascular diseases. We found weak correlations between species and outcomes (R2 <0.1), but yet statistically significant (p-value <0.05).
We have confirmed that summer-related species, such as sulfate (SO4) and ozone (O3), have significant association with respiratory diseases and species that are more prominent in winter, such as NOx, EC, OC, Br, K and Zn, are better correlated with cardiovascular diseases. These results support our approach to use health outcome residuals in the design of more complex air quality indicators.
In fact, using dimension-reduction techniques, we identified groups of pollutants that show association with health. Combustion-related factors (mobile and wood burning), more prominent in colder months, showed association with cardiovascular diseases, and summer-related factors, such as secondary sulfate, were more correlated with respiratory diseases.
In the design of air quality indicators we have integrated information from singles species associated with mobile sources (EC, CO, NO). The Integrated Mobile Source Indicator (IMSI), as called in this study, has a typical daily-pattern of automobile activity and a smoother performance on an annual-basis, compensating for the difference in summer/winter concentrations of singles species.
We have also advanced in the estimation of the vehicular fraction of the ozone. We have used sensitivity fields of ozone to NOx and to VOC from Air Quality Models (AQM) and ratios of mobile/total NOx and VOC emissions, to assess the contribution of mobile sources to ambient ozone.
Future Activities:Our focus for the subsequent period will be the design of a greater number of air quality indicators that integrate information on mobile source impacts and show association with health endpoints. We will use a variety of grouping techniques and assess the correlation between the different metrics. These sets of indicators will be implemented in the epidemiologic models to confirm and quantify associations with health endpoints. Finally, the chosen indicators will be evaluated and refined using an independent set of emissions, air quality and health endpoints from the period 2005-2009.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
|Other project views:||All 9 publications||4 publications in selected types||All 4 journal articles|
||Lee D, Balachandran S, Pachon J, Shankaran R, Lee S, Mulholland JA, Russell AG. Ensemble-trained PM2.5 source apportionment approach for health studies. Environmental Science & Technology 2009;43(18):7023-7031.||