1. Relationships of Indoor, Outdoor and Personal Air (RIOPA) Study Clifford P. Weisel Environmental and Occupational Health Sciences Institute, Piscataway, NJ With: J Zhang, BJ Turpin, MT Morandi, S Colome, Thomas H. Stock, & DM Spektor Presented at: The 2004 MIT Endicott Air Toxics Symposium

2. EXPOSURE CONSIDERATIONS  People spend more time indoors (home, work, school, recreation, etc.) than outdoor, but also in transit –Percent time can vary by location & season  Air toxics –have outdoor sources which can enter (though often modified) indoors –can be produced from activities or generated indoors –can be elevated in “special” micro- environments (i.e. automobile cabins)

3. RIOPA STUDY HYPOTHESES  1) At residences immediately adjacent to outdoor sources a measurable and significant portion of the air toxic exposures will be attributable to ambient sources  2) Residential air exchange rates and ambient air measurements can predict the contribution from ambient sources to indoor air & personal exposure

4. STUDY DESIGN   Sample 100 homes twice, 3 months apart in each of three urban centers:   Elizabeth, NJ; Houston, TX; Los Angeles, CA   Target air toxics: VOCs, Aldehydes, PM2.5 for mass, metals & PAHs   Personal, indoor & outdoor air samples collected over 48 hours   Personal samples from: Adults who stay primarily at home & children   Air exchange measurements

5. ATTRIBUTING AIR TOXIC SOURCES – OUTDOOR/INDOOR  Examine scatter plots of personnel air, indoor air and outdoor air concentrations for each sampling set  Model the indoor concentrations based on outdoor concentrations, penetration factors and air exchange rates  Use statistical analyses to predict personal concentration based on activity data (future analyses)

6. OUTDOOR SOURCE DOMINATED Scatter around 1:1 line for all three plots are fairly random – outdoor source dominate with little loss from outdoor

7. OUTDOOR SOURCE DOMINATED Compounds that fit this category Methyl tert butyl ether (MTBE) Methylene chloride Carbon tetrachloride TrichloroethylenePropionaldehydeCrotonaldehyde These are not compound present in many consumer products

8. INDOOR SOURCE DOMINATED Elevated levels for both the indoor and personal concentration compared to the outdoor levels, while the personal and indoor scatter around the 1:1 line - indoor sources dominate

9. INDOOR SOURCE DOMINATED Compounds that fit this category  Major Indoor Component Chloroform α-Pinene β-Pinene d-Limonene1,4-DichlorobenzeneFormaldehydeAcetaldehyde  Borders on 1:1 Line StyreneAcetoneBenzaldehyde Some home show very strong indoor sources

10. MIXED SOURCES Elevated levels for both the indoor and personal concentration compared to the outdoor levels for some samples – indoor sources dominate other samples scatter around the 1:1 line – outdoor sources dominate

11. MIXED SOURCES Compounds that fit this category BenzeneTolueneTetrachloroethylene m,p Xylene o Xylene Ethyl benzene

12. LOSSES DURING TRANSPORT Lower indoor values indicative of losses during penetration Individual higher indoor values -- indoor sources dominate Personal higher than indoor or outdoor -- indicative of an activity source.

13. LOSSES DURING TRANSPORT Compounds that fit this category PM 2.5 Acrolein

14. SUMMARY OF SCATTER PLOTS  Compounds can be classified into four groups dependant on indoor-outdoor concentration –Majority of homes dominated by outdoor air –Majority of homes dominated by indoor sources –Significant portion of homes dominated by outdoor air with others showing indoor sources –Losses of compounds when penetration indoors occurs with indoor/personal sources evident

15. MODELING OUTDOOR CONTRIBUTIONS TO INDOORS  Goal to evaluate the role of outdoor intrusion on the indoor air concentration –Use indoor & outdoor levels and AER –Account for penetration factors and loss terms  Mass balance model  Random Component super-position statistical model

16. OUTDOOR CONTRIBUTIONS TO INDOOR AIR TOXIC CONCENTRATIONS USING A MASS BALANCE MODEL - FOR PM Loss rate (k) in hr-1; indoor source strength (S/V) in µg m -3 hr -1, & median outdoor contributions to indoor air toxic concentrations in %

17. OUTDOOR CONTRIBUTIONS TO INDOOR AIR TOXIC CONCENTRATIONS USING A MASS BALANCE MODEL -FOR CARBONYLS

18. OUTDOOR CONTRIBUTIONS TO INDOOR AIR TOXIC CONCENTRATIONS USING A MASS BALANCE MODEL -FOR VOCS

19. SUMMARY OF MODELS  PM showed loss during penetration indoor with improvement in the estimate as individual home variability was accounted for  Carbonyls showed loss (water solubility effects?) on some strong indoor sources  Non-polar VOCs no losses during penetration with ambient influence consistent with scatter plot suggestions

20. AFFECT OF PROXIMITY ON AMBIENT AIR CONCENTRATION Mobile Sources  Assign locations to all homes and source location using GIS techniques  Calculate distances between home and closest point to roadway and each point or area source  Conduct statistical evaluation – linear regression analyses – after appropriate transformations. –Distance and meteorology as independent variables. –Evaluate statistical appropriateness of associations and outliers

21. SUMMARY OF PROXIMITY ANALYSES  Mobile source compounds were inversely related to distance to major highways & gas stations, wind speed (some) – positive to atmospheric stability –MTBE stronger to Gas Stations –Toluene had point source influence –Carbonyls not related to distance only meteorology  Tetrachloroethylene was inversely related to distance to drycleaners, temperature, wind speed - positive to atmospheric stability

22. CONCLUSION  Ambient levels do not predict exposure to all compounds  Indoor air can be modeled from outdoor levels and AER to quantitatively evaluated for outdoor air influence  Proximity to sources can be statistically identified as affecting the ambient air around houses for a number of compounds

23. ACKNOWLEDGEMENTS Funding by (presentation not reviewed by agencies)  Mickey Leland National Urban Air Toxics Center  Health Effects Institute  NIEHS Center of Excellence Program  US EPA  Participants who allowed for life disruption Sampling and Analyses Team  Leo Korn, Arthur Winer, Shahnaz Alimokhtari, Jaymin Kwon, Krishnan Mohan, Robert Harrington, Robert Giovanetti, William Cui, Masoud Afshar, Silvia Maberti, Derek Shendell, Qing Yu Meng, Adam Reff, Andrea Polrdori, Robert Porcja, Yelena Naumova, Jong Hoon Lee, Lin Zhang, Tina Fan, Jennifer Jones, L Farrar, Yangrid Blossiers, and Marian Fahrey