1. Introduction
Methods
Results
Conclusions
The Dependence of Indoor PAH
Concentrations on Outdoor PAHs and
Traffic Volume in an Urban Residential
Environment
B. Rey de Castro, Sc.D.
Westat
Rockville, Maryland USA
March 25, 2010
reyDecastro@westat.com Indoor PAHs @ Gradient

2. Introduction
Methods
Results
Conclusions
Outline
1 Introduction
2 Methods
Monitoring Site
Measurements
Imputation of Missing Values
3 Results
Exploratory Analysis
Time Series Models
4 Conclusions
reyDecastro@westat.com Indoor PAHs @ Gradient

3. Introduction
Methods
Results
Conclusions
Outline
1 Introduction
2 Methods
Monitoring Site
Measurements
Imputation of Missing Values
3 Results
Exploratory Analysis
Time Series Models
4 Conclusions
reyDecastro@westat.com Indoor PAHs @ Gradient

4. Introduction
Methods
Results
Conclusions
PAH Health Risks
PAHs among Mobile Source Air Toxics
Potential population at risk: 17.8 million residences
Toxicity: Cancer
18th Century scrotal cancer among chimney sweeps
Lung cancer from occupational exposures
Toxicity: Neurodevelopment
Low birthweight
Respiratory deficits
Chromosomal degradation
Diminished cognition
reyDecastro@westat.com Indoor PAHs @ Gradient

5. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Outline
1 Introduction
2 Methods
Monitoring Site
Measurements
Imputation of Missing Values
3 Results
Exploratory Analysis
Time Series Models
4 Conclusions
reyDecastro@westat.com Indoor PAHs @ Gradient

6. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Monitoring Site
reyDecastro@westat.com Indoor PAHs @ Gradient

7. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Monitoring Site
reyDecastro@westat.com Indoor PAHs @ Gradient

8. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Monitoring Site
reyDecastro@westat.com Indoor PAHs @ Gradient

9. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Baltimore Traffic Study Objectives
Sustained, continuous monitoring: 12 months
High temporal resolution: 10-minute intervals
Simultaneous monitoring of traffic & covarying factors
Control expected autocorrelation: time series analysis
Conclude long-term characteristics of PAH exposure
reyDecastro@westat.com Indoor PAHs @ Gradient

10. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Measurements
PAHs
EcoChem PAS 2000
Selective ionization of particle-bound PAHs
Alternating indoor-outdoor 5-minute sampling
Combined into 10-minute observations
Traffic
Pneumatic counter
5-minute counts
Weather
Rooftop weather station (30-minute)
NWS airport measurements (60-minute)
All data transformed to 10-minute observational interval
reyDecastro@westat.com Indoor PAHs @ Gradient

11. Introduction
Monitoring Site
Methods
Measurements
Results
Imputation of Missing Values
Conclusions
Imputation of Missing Values
Linear regression with reference data
Predictions substituted for missing values
Add pseudorandom variate to reduce bias
Yimpute = Ypredict + N(0, σ 2 )
N = 52,560
July 1, 2002 to June 30, 2003
reyDecastro@westat.com Indoor PAHs @ Gradient

12. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Outline
1 Introduction
2 Methods
Monitoring Site
Measurements
Imputation of Missing Values
3 Results
Exploratory Analysis
Time Series Models
4 Conclusions
reyDecastro@westat.com Indoor PAHs @ Gradient

13. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Variability over Time
reyDecastro@westat.com Indoor PAHs @ Gradient

14. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Workday vs. Non-Workday
reyDecastro@westat.com Indoor PAHs @ Gradient

15. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Temperature & Dew Point
reyDecastro@westat.com Indoor PAHs @ Gradient

16. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Mixing Height & Wind Speed
reyDecastro@westat.com Indoor PAHs @ Gradient

17. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Models With Autocorrelation
Indoor PAH
Traffic, outdoor PAHs, wind speed, wind direction,
temperature, dew point, season, workday
ARMA[3,3] autocorrelation
p
MA(1 : 3)
Yt,in = µin + βi Xi,t + + t,in
i=1
AR(1 : 3) × AR(144) × AR(1008)
Outdoor PAH
Traffic, wind speed, wind direction, temperature, dew
point, season, workday
ARMA[1,1] autocorrelation
p
MA(1)
Yt,out = µout + βi Xi,t + + t,out
i=1
AR(1) × AR(144) × AR(1008)
reyDecastro@westat.com Indoor PAHs @ Gradient

18. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Indoor Parameters: Treemap Visualization
reyDecastro@westat.com Indoor PAHs @ Gradient

19. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Outdoor Parameters: Treemap Visualization
reyDecastro@westat.com Indoor PAHs @ Gradient

20. Introduction
Methods Exploratory Analysis
Results Time Series Models
Conclusions
Wind Direction: Outdoor vs. Indoor
Indoor PAHs, SW–S–SE: 0.59 – 1.16 ng/m3
Outdoor PAHs, WSW–S–NE: 0.95 – 9.78 ng/m3
reyDecastro@westat.com Indoor PAHs @ Gradient

21. Introduction
Methods
Results
Conclusions
Outline
1 Introduction
2 Methods
Monitoring Site
Measurements
Imputation of Missing Values
3 Results
Exploratory Analysis
Time Series Models
4 Conclusions
reyDecastro@westat.com Indoor PAHs @ Gradient

22. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
reyDecastro@westat.com Indoor PAHs @ Gradient

23. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
reyDecastro@westat.com Indoor PAHs @ Gradient

24. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
3 Observed diminished effect of traffic volume in afternoon
reyDecastro@westat.com Indoor PAHs @ Gradient

25. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
3 Observed diminished effect of traffic volume in afternoon
4 Season (Spring & Summer 2003) was strongest predictor
of indoor & outdoor PAHs
reyDecastro@westat.com Indoor PAHs @ Gradient

26. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
3 Observed diminished effect of traffic volume in afternoon
4 Season (Spring & Summer 2003) was strongest predictor
of indoor & outdoor PAHs
5 Contributions from wind direction differ between indoor &
outdoor PAHs
reyDecastro@westat.com Indoor PAHs @ Gradient

27. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
3 Observed diminished effect of traffic volume in afternoon
4 Season (Spring & Summer 2003) was strongest predictor
of indoor & outdoor PAHs
5 Contributions from wind direction differ between indoor &
outdoor PAHs
6 Meteorology & workday had significant effects
reyDecastro@westat.com Indoor PAHs @ Gradient

28. Introduction
Methods
Results
Conclusions
Conclusions
1 Indoor PAHs depend on both traffic volume & outdoor
PAHs
2 Outdoor PAHs depend on traffic volume
3 Observed diminished effect of traffic volume in afternoon
4 Season (Spring & Summer 2003) was strongest predictor
of indoor & outdoor PAHs
5 Contributions from wind direction differ between indoor &
outdoor PAHs
6 Meteorology & workday had significant effects
7 Autocorrelation was significant
reyDecastro@westat.com Indoor PAHs @ Gradient

29. Introduction
Methods
Results
Conclusions
Acknowledgements
Patrick N. Breysse Timothy J. Buckley
Jana N. Mihalic Alison S. Geyh
Lu Wang
EPA grant
On SlideShare: http://cli.gs/BTSpahIndoorGradient
B. Rey de Castro, Sc.D.
410-929-3583
reyDecastro@westat.com Indoor PAHs @ Gradient

30. Introduction
Methods
Results
Conclusions
Summary: Quantitative
Indoor PAHs
0.57 ng/m3 per 100 vehicles every 10 minutes
0.16 ng/m3 per ng/m3 outdoor PAH
Combination of fresh and aged PAHs
Outdoor PAHs
3.17 ng/m3 per 100 vehicles every 10 minutes
Season (Spring & Summer 2003) was strongest predictor
Indoor PAHs: 9.27 – 9.99 ng/m3
Outdoor PAHs: 9.26 – 9.78 ng/m3
Workday
Indoor PAHs: 1.64 ng/m3
Outdoor PAHs: 3.01 ng/m3
reyDecastro@westat.com Indoor PAHs @ Gradient

31. Introduction
Methods
Results
Conclusions
Summary: Quantitative
Meteorology
Indoor PAHs
Wind speed: -0.38 ng/m3 per m/s
Temperature: -2.48 ng/m3 per 5 C
Dew point: 1.87 ng/m3 per 5 C
Outdoor PAHs
Wind speed: -0.79 ng/m3 per m/s
Temperature: -3.45 ng/m3 per 5 C
Dew point: 2.77 ng/m3 per 5 C
reyDecastro@westat.com Indoor PAHs @ Gradient