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Real-time PM 2.5 Reporting. Prepared by: Dianne S. Miller Adam N. Pasch Alan C. Chan Timothy S. Dye Sonoma Technology, Inc. Petaluma, CA Presented to the National Air Quality Conference Dallas, TX March 3, 2009. STI-3549. Real-time Hourly AQI Values for PM 2.5. Why is it Needed?.
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Real-time PM2.5 Reporting Prepared by: Dianne S. Miller Adam N. Pasch Alan C. Chan Timothy S. Dye Sonoma Technology, Inc. Petaluma, CA Presented to the National Air Quality Conference Dallas, TX March 3, 2009 STI-3549
Why is it Needed? We have: Step 1: Real-time hourly PM2.5 concentrations 24-hr avg. PM2.5 concentrations Surrogate We need: real-time PM2.5 AQI Step 2: Convert to AQI Insert Map
Goal of the Presentation • Provide an overview of the PM2.5 surrogate • What is it? • How does it work? • Why is it important? • Present performance expectations • Discuss its performance • Suggest possible methods for improving it
What is the Surrogate? (1 of 2) • The surrogate is an hourly estimation of the midpoint 24-hr average PM2.5 concentration for a given site. • The Conroy Method is currently being used (See McMillan and Hamilton, 2003). Unknown 4-hr average Have 12 hours of data 12-hr average Need 24 hours of data to compute the AQI
What is the Surrogate? (2 of 2) Surrogate = ((12*12-hr average)+12*(4-hr adjusted average))/24 • Where the • 12-hr PM2.5 average represents what has already happened • Adjusted 4-hr PM2.5 average captures short-term changes to better estimate the future 12 hours. The adjustment to the average depends on • How high or low the concentration is • How rapidly the concentration is changing
Why is an Accurate Surrogate Important? • Protect public health • Avoid false alarms • Provide real-time information about PM2.5
Performance Expectations • The surrogate should • Work for all regions • Be easily implemented • Be within 80% of the observed PM2.5 concentrations 80% of the time • Identify PM2.5 spikes and recover rapidly when concentrations drop • Not be overly sensitive to local sources
Performance Evaluation - Methods • Data used • 2006-2007 daily and hourly PM2.5 data from AIRNow • Six cities • Bakersfield Sacramento • Chicago Atlanta • Liberty, PA Baltimore • Test metrics • Metric 1 - How accurate is the surrogate by time of day? • Metric 2 - How accurate is the surrogate within a four-hour window? • Metric 3 - How does the peak daily surrogate AQI compare with the observed daily maximum AQI?
Liberty 12 am Baltimore 59% 37% 0% 5% 6 pm 6 am 6 pm 6 am 39% 74% 0% 7% 12 pm 12 pm 12 am 12 am Chicago Atlanta 28% 50% 47% 40% 6 pm 6 am 6 pm 6 am 71% 30% 45% 59% 12 pm 12 pm Sacramento 12 am Bakersfield 12 am 73% 37% 56% 79% 6 pm 6 am 6 pm 6 am 64% 6% 52% 74% 12 pm 12 pm Metric 1 USG hours Percentage of hours by time of day the surrogate correctly predicted the observed USG+ AQI category 12 am
Liberty Baltimore 16% 20% 24% 56% 84% Atlanta Chicago 35% 55% 53% 47% 10% Bakersfield Sacramento 20% 28% 45% 3% 78% 28% Metric 2 USG hours Percentage of hours the surrogate AQI category matches within four hours of occurrence of the observed AQI
Metric 3 • Air quality agencies often show both the surrogate AQI and forecasted AQI on their websites. • The surrogate AQI and the forecasted AQI are often perceived as the same metric, which can lead to reduced public confidence in the forecast when they differ. Percent of time the peak surrogate matched the daily observed AQI category
Alternative Methods • Re-work the current surrogate method. • Moderate level of effort, low likelihood of improvement • Use characteristics of PM2.5 at each site to determine surrogate. Taking into consideration diurnal variability, geographic region, season, and time of day. • Moderate to high level of effort, moderate likelihood of improvement • Use PM2.5 model predictions to estimate missing 12 hours of data. • Larger level of effort, higher likelihood of improvement
Challenge! • A challenge to you: experiment with new surrogate formulations • Contact airnowdmc@sonomatech.com for a dataset to use Thanks!