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Pairing aermod concentrations with the 50th percentile monitored value

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Presentation delivered to the Background Concentrations Workgroup for Air Dispersion Modeling organized by the Minnesota Pollution Control Agency. delivered on March 25, 2014. Three topics covered include 1) Screening monitoring data, 2) AERMOD’s time-space mismatch, and
3) Proposed 50th % Bkg Method

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Pairing aermod concentrations with the 50th percentile monitored value

  1. 1. PAIRING AERMOD CONCENTRATIONS WITH THE 50TH PERCENTILE MONITORED VALUE Background Concentrations Workgroup for Air Dispersion Modeling Minnesota Pollution Control Agency March 25, 2014 Sergio A. Guerra - Wenck Associates, Inc.
  2. 2. Roadmap • Temporal pairing • Statistical description • Examples
  3. 3. AERMOD Model Accuracy Appendix W: 9.1.2 Studies of Model Accuracy a. A number of studies have been conducted to examine model accuracy, particularly with respect to the reliability of short-term concentrations required for ambient standard and increment evaluations. The results of these studies are not surprising. Basically, they confirm what expert atmospheric scientists have said for some time: (1) Models are more reliable for estimating longer time-averaged concentrations than for estimating short-term concentrations at specific locations; and (2) the models are reasonably reliable in estimating the magnitude of highest concentrations occurring sometime, somewhere within an area. For example, errors in highest estimated concentrations of ± 10 to 40 percent are found to be typical, i.e., certainly well within the often quoted factor-of-two accuracy that has long been recognized for these models. However, estimates of concentrations that occur at a specific time and site, are poorly correlated with actually observed concentrations and are much less reliable. • Bowne, N.E. and R.J. Londergan, 1983. Overview, Results, and Conclusions for the EPRI Plume Model Validation and Development Project: Plains Site. EPRI EA–3074. Electric Power Research Institute, Palo Alto, CA. • Moore, G.E., T.E. Stoeckenius and D.A. Stewart, 1982. A Survey of Statistical Measures of Model Performance and Accuracy for Several Air Quality Models. Publication No. EPA–450/4–83–001. Office of Air Quality Planning & Standards, Research Triangle Park, NC.
  4. 4. Monitored vs Modeled Data: Paired in time and space AERMOD performance evaluation of three coal-fired electrical generating units in Southwest Indiana Kali D. Frost Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  5. 5. SO2 Concentrations Paired in Time & Space Probability analyses of combining background concentrations with model-predicted concentrations Douglas R. Murray, Michael B. Newman Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  6. 6. SO2 Concentrations Paired in Time Only Probability analyses of combining background concentrations with model-predicted concentrations Douglas R. Murray, Michael B. Newman Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  7. 7. Hit it Big!!! Example • You have 2 chances out of 100 to win the Powerball. Or you have 98 chances out of a 100 of not winning the power ball. • You have 2 chances out of 100 to win the Mega Millions. Or you have 98 chances out of a 100 of not winning the Mega Millions. • What are the chances of winning both the Powerball and the Mega Millions?
  8. 8. Marginal Probability P(PB ∩ Mega) = P(PB) * P(Mega) Where: P(PB ∩ Mega)= the marginal probability of winning the PowerBall and at the same time winning the Mega. P(PB) = the marginal probability of winning the Powerball (98th percentile). P(Mega) = the marginal probability of winning the Mega (98th percentile).
  9. 9. Probability of Winning both Lottos P(PB ∩ Mega) = P(PB) * P(Mega) = (1-0.98) * (1-0.98) = (0.02) * (0.02) = (1/50) * (1/50) = 0.0004 = 1 / 2,500 = 99.96th percentile of the combined distribution
  10. 10. Combining 98th percentile Pre and Bkg (1-hr NO2 and 24-hr PM2.5) P(Pre ∩ Bkg) = P(Pre) * P(Bkg) = (1-0.98) * (1-0.98) = (0.02) * (0.02) = 0.0004 = 1 / 2,500 = 99.96th percentile of the combined distribution
  11. 11. Combining 99th percentile Pre and Bkg (1-hr SO2) P(Pre ∩ Bkg) = P(Pre) * P(Bkg) = (1-0.99) * (1-0.99) = (0.01) * (0.01) = 0.0001 = 1 / 10,000 = 99.99th percentile of the combined distribution
  12. 12. Proposed Approach to Combine Modeled and Monitored Concentrations • Combining the 98th (or 99th for 1-hr SO2) % monitored concentration with the 98th % predicted concentration is too conservative. • A more reasonable approach is to use a monitored value closer to the main distribution (i.e., the median). Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation Sergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  13. 13. Combining 98th Pre and 50th Bkg P(Pre ∩ Bkg) = P(Pre) * P(Bkg) = (1-0.98) * (1-0.50) = (0.02) * (0.50) = 0.01 = 1 / 100 = 99th percentile of the combined distribution Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation Sergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  14. 14. Combining 99th Pre and 50th Bkg P(Pre ∩ Bkg) = P(Pre) * P(Bkg) = (1-0.99) * (1-0.50) = (0.01) * (0.50) = 0.005 = 1 / 200 = 99.5th percentile of the combined distribution Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation Sergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  15. 15. Positively Skewed Distribution http://www.agilegeoscience.com
  16. 16. 24-hr PM2.5 observations at Shakopee 2008-2010 Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation Sergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
  17. 17. Blaine ambient monitor location.
  18. 18. Histogram of 1-hour NO2 observations
  19. 19. Conclusion • Use of 50th % monitiored concentration is statistically conservative when pairing it with the 98th (or 99th) % predicted concentration • Method is simple and statistically sound • Method is protective of the NAAQS while providing a reasonable level of conservatism
  20. 20. QUESTIONS… Sergio A. Guerra, PhD Environmental Engineer Phone: (952) 837-3340 sguerra@wenck.com www.SergioAGuerra.com

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