1. Diurnal Variability of Aerosols Observed by Ground-based Networks Qian Tan (USRA), Mian Chin (GSFC), Jack Summers (EPA), Tom Eck (GSFC), Hongbin Yu (UMD), Caterina Tassone (NOAA), Yan Zhang (MSU), EPA/AQS, NASA/AERONET, NOAA/NCDC

2. Outline  Diurnal variability of surface PM2.5  How significant  Variations on other time scales.  Linkage between diurnal cycle of surface PM2.5 and column AOT  Correlation on their diurnal cycles  Possible meteorological impacts

3. Measuring Aerosol Variations in Different Ways Day 1Day 2Day 3Day 4Day 5………Day n Day-to-day variation (EPA 24-hr filter) Sun-synchronized orbit Better spatial coverage Geo-stationary orbit EPA hourly obs.

4. Aerosols Diurnal Variation  Continuous ground based observations.  EPA AQS hourly PM2.5 observations.  Diurnal variation vs daily average  Comparison to seasonal variations.

5. Averaged PM 2.5 Diurnal Variations PM 2.5 (ug/m^3) Max-Min Std. Dev 2004 2005 2006 2007 Significant diurnal variation is observed: ~ 15-22 ug/m 3, EPA PM2.5 standard: 35 ug/m 3 for 24hr, 15 ug/m 3 annual average.

6. Compared with Daily Average Percentage (%) (Max-Min) / Mean Std. Dev/ Mean Variations of surface PM2.5 within a day is comparable to its daily mean: Maximum-minimum is 120-170% of its mean Standard deviation is ~30-50%. 2004 2005 2006 2007

7. Seasonal & Year-Year Difference Max-Min Std Dev On average, the standard deviation of PM2.5 within a day is comparable to the seasonal variation.

8. Co-located PM2.5 and AOT  Using column AOT, i.e. what satellites observe, to estimate the surface concentration of PM2.5 (criteria pollutant)  Chu et al., (2003), Wang & Christopher (2003), Engel-Cox (2004), Al-Saadi et al., (2005),…, Hoff & Christopher (2009)  Co-located AERONET and AQS observations  New York City (CCNY)  Baltimore (MD Science Center)  Houston (University of Houston)  Fresno (California) Within 8km. Hourly data available Close by hourly meteorological & PBL observations

9. Day-to-Day PM2.5 vs AOT On daily based, AOT shows good correspondence with surface PM2.5 concentration. Their correlation has large spatial differences (both r 2 and slope).

10. Diurnal Cycle of PM2.5 & AOT -- Houston PM2.5 shows clearer diurnal pattern, it changes with season. AOT diurnal pattern is less pronounced, larger seasonal variation Daily PM2.5 minimum is at noon time during fall and winter.

11. Correlation between AOT and PM2.5 on finer temporal frequency Koelemeijer et al., 2006; Hoff & Christopher (2009) Causes of variations PM2.5 emissions, chemistry, deposition, dynamics, … AOT all of above aerosol optical property composition size and shape aerosol vertical profile PBL local, regional, and long range transport other factors clouds, (surface albedo) solar zenith angle

12. Diurnal Variation of PBL PBL peaks in the early afternoon PBL is higher in summer (in Houston, less seasonal difference)

13. PBL vs. PM2.5 Houston Baltimore New York City Winter In winter, if PBL is high, then PM2.5 will be low -- in Houston, the minimum PM2.5 occurred around noon time.

14. AOT vs. PM 2.5 * PBL R 2 = 0.39 (2010) R 2 =0.26 When PBL is high (>1000m), AOT is more correlated with PM2.5 When PBL is high (>1000m), AOT is more correlated with PM2.5 R 2 = 0. 51 PBL > 1000m

15. AOT vs PM2.5 * PBL *f(RH) R 2 = 0.17 R 2 = 0.40 R 2 = 0.064 * F (RH) R 2 = 0.42 All PBL condition PBL >1000m + surface RH 1.Low PBL will degrade correlation between AOT and PM2.5 2.When PBL is high, it is more likely to estimate PM2.5 using AOT.

16. Conclusion  Significant daily variation is observed in surface PM2.5 concentration.  Daily average of PM2.5 and AOT is correlated well at urban sites.  Diurnal cycle of PM2.5 and AOT is different.  better correlated when PBL is high

17. Extra slides

18. Diurnal Cycle of PM2.5 and AOT -- NYC PM2.5 diurnal variation follow emission (traffic) pattern, & PBL AOT diurnal pattern is less pronounced, large seasonal variation No clear pattern in summer months.

19. Correlation between AOT and PM2.5  Many studies to explore the linkage between the two  Using column AOT, i.e. what satellite can observe, to estimate the surface concentration of PM2.5 (criteria pollutant)  Chu et al., (2003), Wang & Christopher (2003), Engel-Cox (2004), Al-Saadi et al., (2005),…, Hoff & Christopher (2009)