1. Analysis of Mercury Data A Cooperative Experiment NESCAUM Monitoring & Assessment Committee April, 2007 Charlie Pietarinen NJDEP

3. “An Analysis of Continuous Mercury Air Pollution Data Collected in Elizabeth and New Brunswick, NJ.” Presented By: Fawn Hornsby & Wilma “Billie” Jackson Client: Mr. Charles Pietarinen NJ Department of Environment

4. Methodology I An example of “good” data: First, we needed to sort through the measurements to find the “good” data

5. Methodology I Applied NJDEP criteria to identify “good” data: –Example of “good” data is a two-hour block with measurements recorded every 5 minutes (for 34 measurements) conforming to the following (in order): »2 black or 0 values »12 elemental values > 0 »1 blank value >= 0 »2 blank or 0 values »1 particulate value of 0 »1 particulate value >= 0 »A particulate value <= previous particulate value »A particulate value of 0 »A reactive gas value >= 0 »A reactive gas value <= previous reactive gas value »A reactive gas value of 0

6. The Combined Distributions of Elemental Mercury: FREQUENCY Ave_z FREQUENCY Elemental Mercury Distribution Without outliers: Elemental Mercury Distribution With outliers:

7. Reactive Gas Mercury R1 TIMEBLOCK Comparison of Reactive Gas Mercury distributions (omitting outliers), and Ozone measurements: Reactive Gas Mercury Box Plot Without outliers: HOUR FREQUENCY (Donaghy & Sorrell 2002) Box Plot for 1 hour max ozone:

8. Presented By: Fawn Hornsby, Wilma “Billie” Jackson, Carrie Larsen, & Roberta O’Donnell Client: Mr. Charles Pietarinen NJ Department of Environment "How do Ambient Air Pollution Mercury Levels Compare Between Elizabeth and New Brunswick, NJ?"

9. Percentage of Particulate Mercury Values Found At Each Site Daily Average of Particulate Measurements Elizabeth: New Brunswick:

10. Methodology for linking meteorology data with mercury data: (Source: NJDEP) For Particulate and Reactive Gas Mercury Correlated to Wind Speed and Direction: 1.The hourly average of each 15-minute measurement taken for wind speed and direction were paired to these phases of mercury. Elemental Mercury correlated to Wind Speed and Direction: 1.The averages of every set of three 5-minute elemental mercury measurements were computed in order to be compared with 15- minute measurements taken for wind speed and direction. 2.The sets of data were paired together using the last timestamp taken to compute the elemental mercury average. –For example, if the wind speed and direction was observed at 1:15, then the respective speed and direction value would be paired with the elemental mercury measurements taken at 1:05, 1:10, and 1:15.

11. Elemental Mercury versus Wind Speed at Elizabeth and New Brunswick Elizabeth:New Brunswick: Phase IV Wind Speed

12. Particle Mercury versus Wind Speed at Elizabeth and New Brunswick Elizabeth:New Brunswick: Wind Speed

13. Methodology for Finding Direction Graphs Normalized values were computed by multiplying wind speed times the daily average mercury data, then plotted against the wind direction. Direction is given in degrees: Phase V

14. Normalized Elemental vs. Direction at Elizabeth Highest concentrations from 140-170, and 190-220 degrees Normalized Elemental Mercury Measurements Direction

15. New Brunswick, NJ New Brunswick NJ Wind Direction Map of High Value Outliers Particulate RGM Elemental Sun Icon: Coal/Oil Fired Power Plants Yellow Icon: Steel remanufacturing/Smelters Green Icon: Sewage Sludge Incinerators Red Icon: WTE Plants

16. Extreme Outliers in New Brunswick

17. Preliminary Analysis by: Fawn Hornsby 1, Charles Rogers 2, & Sarah Thornton 3 1,3 North Carolina State University 2 University of Texas at El Paso Client: Mr. Charles Pietarinen NJ Department of Environment Tuesday, July 25, 2006 @ North Carolina State University Graduate Assistant: Mr. Andrew Moore Faculty Mentor: Dr. William Hunt

18. Elemental Mercury: Highest concentrations from 140-170, and 190-220 degrees Source Graphs For Elizabeth Particulate Mercury: Highest concentrations from 180-230 and 240-270 degrees Reactive Gas Mercury: Highest concentrations coming from the directions of: 0-20, 120-160, and 220-280 degrees

19. Elemental Mercury Values During the Summer Seasons New Brunswick: Elizabeth:

20. Particulate Hg Day of the Week Effect

21. Relationship Between Elemental Mercury, Ozone, & Temperature New Brunswick: Elizabeth:

22. Examining Temperatures versus Particulate Mercury in New Brunswick Scatter Plot: Box Plot:

23. County Emissions of Mercury and Mercury Compounds 2004 0-1 18-48 51-58 74-172 Total On-Site Disposal (pounds)

24. Primary Wind Directions in New Brunswick 90° 180° 270°

25. Comparison of Correlations By Direction Using 30 degree increments Elemental Mercury Particulate Mercury Reactive Gas Mercury New Brunswick (wind direction) East-Southeast 90-120°

26. Modeling Mercury Concentrations in New Jersey November 28, 2006 Elizabeth Christoph and Sarah Thornton Client: Mr. Charles Pietarinen, NJDEP Mentor: Dr. W. F. Hunt Post-Doc Advisor: Dr. Curtis B. Storlie Graduate Advisor: Andrew S. Moore

27. The Traditional Model Y = b 0 + b 1 u + b 2 v Y = Mercury Concentration b 0 = Baseline Concentration u = -Wind Speed*cosine (2π*Wind direction / 360) v = -Wind Speed*sine (2π*Wind direction / 360)

28. The Meteorological Model Y = b 0 + b 1 x 1 + b 2 x 2 +... + b 14 x 14 Y = Mercury Concentration b 0 = Baseline Concentration x 1 = cosine (2π*Wind Direction /360) x 2 = sine (2π*Wind Direction /360) x 3 = cosine (4π*Wind Direction /360) x 4 = sine (4π*Wind Direction /360) …….. x 11 = Wind Speed x 12 = ( Wind Speed ) ² x 13 = Average Daily Temperature x 14 = Precipitation

29. The Logarithmic Transformation Y = b 0 + b 1 x 1 + b 2 x 2 +... + b 14 x 14 Y = Natural Log (Mercury Concentration) b 0 = Baseline Concentration x 1 = cosine (2π*Wind Direction /360) x 2 = sine (2π*Wind Direction /360) x 3 = cosine (4π*Wind Direction /360) x 4 = sine (4π*Wind Direction /360) …….. x 11 = Wind Speed x 12 = ( Wind Speed ) ² x 13 = Average Daily Temperature x 14 = Precipitation

30. Elizabeth New Brunswick R² = 0.0313 Predicted Values Residuals vs. Predicted Values R² = 0.0317 Predicted Values Residuals vs. Predicted Values

31. Elizabeth New Brunswick R² = 0.2672 Predicted Values Residuals vs. Predicted Values R² = 0.2113 Predicted Values Residuals vs. Predicted Values

32. Modeling Mercury Concentrations Interim Briefing March 21, 2007 Liz Christoph Fawn Hornsby

33. The Normalized Model Y = b 0 + b 1 x 1 + b 2 x 2 +... + b 14 x 14 Y = Mercury Concentration*Wind Speed b 0 = Baseline Concentration x 1 = cosine (2π*Wind Direction /360) x 2 = sine (2π*Wind Direction /360) x 3 = cosine (4π*Wind Direction /360) x 4 = sine (4π*Wind Direction /360) …….. x 11 = Wind Speed x 12 = ( Wind Speed ) ² x 13 = Average Daily Temperature x 14 = Precipitation

34. ElemPartRGM Normalized Meteorological 0.56060.1692.2863 Inverse 0.52540.3316.3789 Normalized Logarithmic 0.81350.5289.6108 ElemPartRGM Traditional.0313.0028.0126 Meteorological.1755.0973.1351 Logarithmic.2672.2699.1528 R-squared Values for Elizabeth

35. Predicted Concentrations vs. Actual Concentrations in Elizabeth: Elemental Previous Model: Normalized Model: Previous Model: METEOROLOGICALLOGARITHMIC

36. Modeling Mercury Concentrations Final Briefing April 16, 2007 Elizabeth Christoph Fawn Hornsby

37. The Log Normal Model Y = b 0 + b 1 x 1 + b 2 x 2 +... + b 20 x 20 Y = Natural Log (Mercury Concentration* Wind Speed) b 0 = Baseline Concentration x 1 = cosine (2 π *Wind Direction /360) x 2 = sine (2π*Wind Direction /360) x 3 = cosine (4π*Wind Direction /360) x 4 = sine (4π*Wind Direction /360) …….. x 11 = Wind Speed x 12 = ( Wind Speed ) ² x 13 = Average Daily Temperature x 14 = Precipitation x 15 = ( Average Daily Temperature ) ² x 16 =( Precipitation ) ² x 17 = Wind Speed * Wind Direction x 18 = Wind Speed * Temperature x 19 = Wind Speed * Precipitation x 20 = Precipitation * Temperature Cyclical patterns Meteorological Factors Interactions

38. ElemPartRGM Normalized Meteorological 0.56060.1692.2863 Normalized Logarithmic 0.81350.5289.6108 R-squared Values in Elizabeth ElemPartRGM Normalized Meteorological0.57640.1829 0.2980 Normalized Logarithmic0.8073 0.4996 0.6101 WITH Quality Control:

39. Predicted Conc. vs. Actual Conc. in Elizabeth: Elemental Previous Model: METEOROLOGICALLOGARITHMIC Normalized Model with QC: