Halûk Özkaynak US EPA, Office of Research and Development National Exposure Research Laboratory, RTP, NC Presented at the CMAS Special Symposium on Air Quality October 13, 2010 Air Pollution Exposure and Health Effects

Use of Air Quality and Exposure Information in Health Related Studies Epidemiology (acute and chronic health effects at population or individual level) Risk Assessment (health effects due to exposures to single or multiple pollutants) Risk Management (determining optimum local vs. regional emissions controls by source-specific modeling) Accountability (evaluating impacts of Federal, State, City and local local-scale pollution reduction programs)

Exposure science in risk assessment and risk management is critical to EPA’s mission to promote public health and welfare EPA conducts exposure assessments to determine the route, magnitude, frequency, and distribution of exposure Epidemiology studies are vital in estimating the risk and the impact of air pollution on human health. Latest research in epidemiology emphasizes the need for more reliable estimates or surrogates of human exposures Role of Exposure Science and Epidemiology in Developing Air Quality Regulations and Controls Air Quality Exposure Epidemiology Integrated Science Assessment Risk and Exposure Assessment Risk Management Role of Exposure Science and Epidemiology in EPA

Air Quality and Exposure Modeling Considerations in Air Pollution Epidemiology Epidemiologic study designs:  Time-series/case-crossover (e.g., daily or hourly resolution)\  Panel or cohort studies  Cross-sectional (e.g., multi-city, multi-region)  Hybrid (e.g., varied resolution either over space or time, such as data aggregated over the entire city, by zip code, etc.) Health data types:  Group/population level (e.g., hospital, mortality, insurance data)  Individual level (e.g., subject data at address level) Exposure-related issues:  Individual pollutants, multiple pollutants, PM species and co- pollutants, source-specific contributions

Rationale for the NERL Coop Program Numerous epidemiologic studies have used measurements from central-site ambient monitors to estimate exposures to air pollution Central-site monitors may not account for:  spatial and temporal heterogeneity of urban air ambient pollution  human activity patterns  infiltration of ambient pollutants indoors  contributions of indoor sources that may be effect modifiers Central-site are especially problematic for certain PM components and species (e.g., EC, OC, coarse, ultrafine) that exhibit significant spatial heterogeneity A number of enhanced exposure assessment approaches have recently been developed and applied in the investigation of air pollution health effects

Average Time Spent in Each Microenvironment TOTAL INDOORS: 86.9% National Human Activity Pattern Survey (NHAPS) Adapted by Klepeis et al., 2001 IN RESIDENCE (68.7%) OUTDOORS (7.6%) IN VEHICLE (5.5%) OTHER INDOOR (11%)

Exposure Information Relevant to Health Studies Health data analysis Epidemiological statistical models: log(E(Y kt )) = α + β exposure metric kt +  k γ k area kt + …other covariates Tiers of Exposure Metrics Personal Behavior/Time Activity Microenvironmental Characteristics Ambient Monitoring Data: Central Site or Interpolated Land-Use Regression Modeling Air Quality Modeling (CMAQ, AERMOD, hybrid) Exposure Modeling (SHEDS, APEX) Statistical modeling (Data blending) Monitoring Data Emissions Data Meteorological Data Land-Use/Topography Monitoring Data Emissions Data Meteorological Data Land-Use/Topography Input data ComplexityReliability vs. Uncertainty

Exposure= Outdoor Exposure+ Indoor Exposure Assuming no indoor sources and most time spent indoors (>85%), then: Exposure ≈ Infiltration Rate x Ambient Concentration Exposure ≈ Inf x Ambient Concentration Definition Of Exposure Predictors

Tiers of Exposure Predictors Used in Recent Epidemiological Analysis Tier 1: Refers to Central Site Monitoring Data (single monitor or averaged across multiple stations) Tier 2: Refers to exposures to ambient pollution that has infiltrated indoors into residences Tier 3: Refers to ambient exposures to Air Quality Model predicted values Tier 4: Refers to exposures based on population Exposure Model predictions

Estimated Effects of Ambient PM 2.5 on Acute Mortality in the US (Tier 1)* ▪ represents estimates; lines around ▪ are 95% confidence interval (*Source of data: Franklin et al. 2007)

Influence of an Indoor Infiltration Indicator (Normalized Leakage) on Estimated Ambient PM 2.5 Effect on Respiratory Mortality (Tier 2) Source: Baxter et al (in preparation)

Findings from Further Analysis of Daily Ambient PM 2.5 and Mortality in the US There is considerable heterogeneity in the predicted PM effects on acute mortality across the 27 cities studied The variation in the predicted PM health effects can partially be explained by the geographic differences in housing stock which influence how much outdoor air infiltrates indoors  Cities with homes that have greater indoor infiltration of outdoor air (represented by higher normalized leakage) have larger PM effect estimates potentially due to greater indoor exposures to ambient PM

Association between 24-hour BC, 24-hour NO 2 and HRV for ambient, outdoor, indoor, and personal exposure measures Source: Suh and Zanobetti (2010) BC NO 2

15 Office of Research and Development National Exposure Research Laboratory Comparison of ozone concentration vs. exposures, 10 ppb unit change (Source: Shao et al. (2010) Relative risk is high for exposure, but is exposure modeling better discerning the relationships between air quality and human health outcomes? How do we compare risks based on different exposure metrics (i.e., concentration vs. exposure)? Concentrations Exposures Preliminary Results of Epidemiologic Analysis of Hospital Admissions in New York

EPA Coop Program Goal and Approach Goal Overall aim is to enhance the results from epidemiologic studies of ambient PM, PM components and gaseous air pollution through the use of more reliable approaches for characterizing exposures Approach Research conducted under a two-year, plus 6-12m no-cost extension, Cooperative (Coop) Agreement program with EPA/NERL and three academic institutions:  Emory University  Rutgers  University of Washington Coops started around the end of 2008 and will run through 2011 First year activities focus on exposure metric development and second year research focuses on their applications and evaluations EPA is a strong partner in this Coop program and provides air quality model (e.g., CMAQ, AERMOD) and exposure (e.g., SHEDS, APEX) model results along with methodologies for assimilating measurement and modeling information

Research Goals and Objectives Emory Coop Develop and evaluate six exposure metrics for ambient traffic-related (CO, NO x and PM 2.5 EC) and regional (O 3 and SO 4 2- ) pollutants by applying them to two of ongoing epidemiologic studies on ambient air pollution and acute morbidity in Atlanta, GA Rutgers Coop Examine associations between PM 2.5 mass and species and adverse health using two established epidemiology studies in New Jersey by testing four different tiers of exposure specification University of Washington Coop Improve air pollution cohort study health effect estimates by (i) incorporating dispersion model output into an existing spatio-temporal concentration model and (ii) quantifying the impact of exposure misspecification and methods for minimizing this source of error

Exposure models are structured mathematical representations used for predicting real-world exposure events by linking measurements or modeling information on:  Emissions  Concentrations (e.g., Ambient, Indoor, Commuting)  Behavioral information  Exposure factors  Other exposure related data What are Exposure Models?

Stochastic Human Exposure and Dose Simulation (SHEDS) Model for Air Pollutants

21 Office of Research and Development National Exposure Research Laboratory Tools Needed for Advancing Exposure Science Factors below that Impact Exposures Need to be Incorporated into AQ Model Local sources (mobile, area and point) on outdoor residential concentrations Local meteorology on outdoor residential concentrations and infiltration rates Housing type and house operations on infiltration and indoor concentration Locations and Activities on personal exposure An integrated modeling system that can be operationally applied in air quality management practices (e.g., standard setting, standard implementation, risk mitigation, accountability) Human Activity Indoor Penetration Personal Sources toto t1t1 TIME E X P. or D O S E Inhalation Emissions Meteorology Dispersion Chemistry Air Quality Modeling Exposure Modeling

Key Programmatic Issues Type of an epidemiologic study design is important for determining the requirements needed for spatio-temporal resolution of exposure data or its surrogates needed for health effects research (one size does not fit all in terms of sophistication needed in exposure assignment) Important to better understand the sources and factors influencing uncertainties in ambient epidemiology analyses as well as compounding of errors as exposure metrics are refined NERL Coop Program has greatly facilitated exchange and transfer of relevant information between multiple EPA groups, scientists and academic institutions Establishing causality will depend on building sufficient weight of evidence regarding the utility/performance of exposure models and metrics through their application in new or refined epidemiological analysis

Acknowledgements Halûk Özkaynak (EPA) Vlad Isakov (EPA) Lisa Baxter (EPA) Janet Burke (EPA) Larry Reiter ST Rao New York State Dept. of Health Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy