Diurnal Variability of Aerosols Observed by Ground-based Networks

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), CaterinaTassone (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-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 Max-Min Std. Dev PM 2.5 (ug/m^3) 2004200520062007 Significant diurnal variation is observed: ~ 15-22 ug/m3, EPA PM2.5 standard: 35 ug/m3 for 24hr, 15 ug/m3 annual average.

6. Compared with Daily Average (Max-Min) / Mean Std. Dev/ Mean Percentage (%) 2004200520062007 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%.

7. Seasonal & Year-Year Difference Std Dev Max-Min 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 r2 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)

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 New York City Baltimore 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 (2010) R2 = 0.39 R2=0.26 PBL > 1000m When PBL is high (>1000m), AOT is more correlated with PM2.5 R2 = 0. 51

15. AOT vs PM2.5 * PBL *f(RH) R2 = 0.17 R2 = 0.064 All PBL condition PBL >1000m + surface RH R2 = 0.40 R2 = 0.42 Low PBL will degrade correlation between AOT and PM2.5 When PBL is high, it is more likely to estimate PM2.5 using AOT. * F (RH)

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)