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Techniques for Evaluating Wildfire Smoke Impact on Ozone for Possible Exceptional Events Daniel Alrick 1, Clinton MacDonald 1, Brigette Tollstrup 2, Charles.

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Presentation on theme: "Techniques for Evaluating Wildfire Smoke Impact on Ozone for Possible Exceptional Events Daniel Alrick 1, Clinton MacDonald 1, Brigette Tollstrup 2, Charles."— Presentation transcript:

1 Techniques for Evaluating Wildfire Smoke Impact on Ozone for Possible Exceptional Events Daniel Alrick 1, Clinton MacDonald 1, Brigette Tollstrup 2, Charles Anderson 2 1 Sonoma Technology, Inc. (STI) 2 Sacramento Metropolitan Air Quality Management District (SMAQMD) Presented at the National Air Quality Conferences March 7–10, 2011 San Diego, CA 4069

2 2 What are Exceptional Events? “Unusual or naturally occurring events that can affect air quality but are not reasonably preventable...”

3 3 What Makes an Event Exceptional? To justify data exclusion, evidence must show that 1.“There is a clear causal relationship between the measurement under consideration and the event that is claimed to have affected the air quality in the area.” 2.“The event is associated with a measured concentration in excess of normal historical fluctuations, including background.” 3.“There would have been no exceedance or violation but for the event.” The “but for” clause is often the most difficult to satisfy –No one data set necessarily has all the information –Availability and use of good meteorological data and analysis tools is critical

4 4 Northern California Wildfires, Summer 2008 Smoke on July 11, 2008 Basin Complex 2008

5 5 Northern California Wildfires, Summer 2008 Fires started by lightning in June 2008 Below average precipitation across California during February through June 2008 Drought, Lightning, and Fires Lightning strikes: more than 6,000 from June 20 to 21, 2008

6 6 Wildfire Impact on Air Quality Wildfire smoke contains VOCs, NO x, and PM During wildfires, several ozone exceedances occurred in the Sacramento area

7 7 Tools for Evaluating Impact of Smoke Conceptual model –Examination of local meteorological conditions on days with high ozone concentrations Identification of matching days Regression analysis –Equations describing the relationship between pollutant concentrations and meteorological parameters Ozone = (Temp) ∙ m 1 + (Wind Speed) ∙ m 2 +... + constant

8 8 Conceptual Model (1 of 4) Describes meteorological conditions typical of high ozone levels Using surface and upper air observations, STI developed rules of thumb for high ozone levels in Sacramento Meteorological ParameterRule of Thumb 925 mb temperature from Oakland sounding ≥25°C 500 mb geopotential height over Sacramento ≥5,850 m Sacramento high temperature≥93°F Sacramento morning wind speed<4 knots Sacramento morning wind direction>150° and <270° Fairfield morning wind speed<15 knots Morning San Francisco to Sacramento pressure gradient <3.0 mb

9 9 Conceptual Model (2 of 4) Did weather conditions meet the rules of thumb for high ozone levels? Meteorological Parameter Rules of Thumb Smoke Day Observations 925 mb temperature from Oakland sounding ≥25°C21°C 500 mb geopotential height over Sacramento ≥5,850 m5,840 m Sacramento high temperature ≥93°F86°F Sacramento morning wind speed <4 knots2 knots Sacramento morning wind direction >150° and <270°190° Fairfield morning wind speed <15 knots17 knots Morning San Francisco to Sacramento pressure gradient <3.0 mb3.3 mb Maximum 1-hr ozone concentration 161 ppb

10 10 Conceptual Model (3 of 4) Primary pattern for high ozone levels is an upper-level ridge over the West Coast Surface thermal trough over Sacramento

11 11 Conceptual Model (4 of 4) Did the weather pattern fit with the conceptual model? Zonal upper flow across northern California – does not fit with conceptual model Surface thermal trough located near Sacramento

12 12 Identification of Matching Days (1 of 2) Compare days with and without smoke that have similar meteorological conditions and look at the difference in ozone concentrations. Smoke Day Matching Day Example of a relatively good match of upper-level patterns between smoke day and matching day.

13 13 Identification of Matching Days (2 of 2) Result: Ozone concentrations are higher on smoke day compared to matching day. Meteorological Parameter Rules of Thumb Smoke Day Observations Matching Day Observations 925 mb temperature from Oakland sounding ≥25°C21°C19°C 500 mb Geopotential height over Sacramento ≥5,850 m5,840 m5,830 m Sacramento high temperature ≥93°F86°F84°F Sacramento morning wind speed <4 knots2 knots6 knots Sacramento morning wind direction >150° and <270°190°211° Fairfield morning wind speed <15 knots17 knots19 knots Morning San Francisco to Sacramento pressure gradient <3.0 mb3.3 mb3.2 mb Maximum 1-hr ozone concentration 161 ppb79 ppb

14 14 Regression Tools (1 of 2) Developed using historical ozone observations (daily 1-hr maximum ozone) Compare model predictions to observed ozone concentrations on smoke days Observation – Max. Prediction = Estimated Smoke Contribution 1-hour Maximum Ozone Concentration (ppb) Date00Z ETA12Z ETA12Z ETA MOSObserved Estimated Smoke Contribution Smoke Day 1767772161 85 Smoke Day 2767160130 54 Smoke Day 3116109118166 48 Smoke Day 4958576151 56

15 15 Consider Regression Model Error (2 of 2) In model development, calculated error range on regression predictions for the entire data set Estimated smoke contribution to ozone ranged from 48 to 85 ppb on the four example smoke days Error on most days (95%) was ±35 ppb Example for one model: Error (Model – Obs)

16 16 Conclusion Existing and proven forecasting tools can be useful in determining smoke impact on air quality.


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