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PM Event Detection from Time Series

PM Event Detection from Time Series. Contributed by the FASNET Community, Sep. 2004 Correspondence to R Husar , R Poirot Coordination Support by Inter-RPO WG Fast Aerosol Sensing Tools for Natural Event Tracking, FASTNET NSF Collaboration Support for Aerosol Event Analysis

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PM Event Detection from Time Series

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  1. PM Event Detection from Time Series Contributed by the FASNET Community, Sep. 2004 Correspondence to R Husar , R Poirot Coordination Support by Inter-RPO WG Fast Aerosol Sensing Tools for Natural Event Tracking, FASTNET NSF Collaboration Support for Aerosol Event Analysis NASA REASON Coop EPA -OAQPS Event : Deviation > x*percentile

  2. Temporal Analysis • The time series for typical monitoring data are ‘messy’; the signal variation occurs at various scales and the time pattern at each scale is different • Inherently, aerosol events are spikes in the time series of monitoring data but extracting the spikes from the noisy data is a challenging endeavor Typical time series of daily AIRNOW PM25 over the Northeastern US • The temporal signal can be meaningfully decomposed into a • Seasonal component with stable periodic pattern • Random variation with ‘white noise’ pattern • Spikes or events that are more random in frequency and magnitude • Each signal component is caused by different combination of the key processes: emission, transport, transformations and removal

  3. Temporal Signal Decomposition and Event Detection EUS Daily Average 50%-ile, 30 day 50%-ile smoothing • First, the median and average is obtained over a region for each hour/day (thin blue line) • Next, the data are temporally smoothed by a 30 day moving window (spatial median - red line; spatial mean – heavy blue line). These determine the seasonal pattern. Event : Deviation > x*percentile Deviation from %-ile Average • Finally, the hourly/daily deviation from the the smooth median is used to determine the noise (blue) and event (red) components Mean Seasonal Conc. Median Median Seasonal Conc.

  4. Seasonal PM25 by Region The 30-day smoothing average shows the seasonality by region The Feb/Mar PM25 peak is evident for the Northeast, Great Lakes and Great Plains This secondary peak is absent in the South and West

  5. Northeast – Southeast Comparison • Northeast and Southeast differ in the pattern of seasonal and event variation • Northeast has two seasonal peaks and more events–values well above the median • Southeast peaks in September and has few values much above the noise Northeast Southeast

  6. Causes of Temporal Variation by Region The temporal signal variation is decomposable into seasonal, meteorological noise and events Assuming statistical independence, the three components are additive: V2Total =V2Season +V2MetNoise +V2Event The signal components have been determined for each region to assess the differences Northeast exhibits the largest coeff. variation (56%); seasonal, noise and events each at 30% Southeast is the least variable region (35%), with virtually no contribution from events Southwest, Northwest, S. Cal. and Great Lakes/Plains show 40-50% coeff. variation mostly, due to seasonal and meteorological noise. Interestingly, the noise is about 30% in all regions, while the events vary much more, 5-30%

  7. ‘Composition’ of Eastern US Events • The bar-graph shows the various combinations of species-events that produce Reconstructed Fine Mass (RCFM) events • ‘Composition’ is defined in terms of co-occurrence of multi-species events (not by average mass composition) • The largest EUS RCFM events are simultaneously ‘events’ (spikes) in sulfate, organics and soil! • Some EUS RCFM events are events in single species, e.g. 7-Jul-97 (OC), 21-Jun-97 (Soil) Based on VIEWS data

  8. Northeast

  9. Great Lakes

  10. Great Lakes-Plains

  11. Northeast

  12. Great Plains

  13. NorthWest

  14. S. California

  15. Southeast

  16. Southwest

  17. Event Definition:Time Series Approach • Eastern US aggregate time series

  18. Sulfate EUS Daily Average 50%-ile, 30 day 50%-ile smoothing Deviation from %-ile Event – Deviation > percentile value Mean Seasonal Conc. Median Seasonal Conc.

  19. Reconstructed Fine Mass RCFM

  20. Organic Carbon

  21. Eelemental Carbon

  22. SOIL

  23. Nitrate

  24. Temporal Pattern Regional Speciated Analysis - VIEWS • Aerosol species time series: • ammSO4f • OCf • ECf • SOILf • ammNO3f • RCFM Regions of Aggregation

  25. Dust US Seasonal + spikes East – west events are independent East events occur several times a year, mostly in summer West events are lest frequent, mostly in spring East West

  26. Dust Northeast asgasgasfg Southeast Southwest

  27. Dust Northwest dfjdjdfjetyj Great Plaines S. California

  28. Amm. Sulfate US wdthehreherh East West

  29. Amm. Sulfate Northeast stheherheyju Southeast Southwest

  30. Amm. Sulfate Northwest shheherh Great Plaines S. California

  31. Organic Carbon US sdhdfhefheryj East West

  32. Organic Carbon Northeast sdheherh Southeast Southwest

  33. Organic Carbon Northwest erheryeyj Great Plaines S. California

  34. Reconstructed Fine Mass US estrhertheryu East West

  35. Reconstructed Fine Mass Northeast werty3rueru Southeast Southwest

  36. Reconstructed Fine Mass Northwest wthwrthwerhtr Great Plaines S. California

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