Post on 13-Dec-2015
PM Event Detection from Time Series
Contributed by the FASNET Community, Sep. 2004Correspondence 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
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
The temporal signal can be meaningfully decomposed into a
1. Seasonal component with stable periodic pattern
2. Random variation with ‘white noise’ pattern
3. 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
Typical time series of daily AIRNOW PM25 over the Northeastern US
Temporal Signal Decomposition and
Event Detection
• 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.
EUS Daily Average 50%-ile, 30 day 50%-ile smoothing
Deviation from %-ile
Event : Deviation > x*percentile
Median Seasonal Conc.
Mean Seasonal Conc.
Average
Median
• Finally, the hourly/daily deviation from the the smooth median is used to determine the noise (blue) and event (red) components
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
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
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 = V2
Season + V2MetNoise + V2
Event
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 eventsSouthwest, 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%
‘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
Northeast
Great Lakes
Great Lakes-Plains
Northeast
Great Plains
NorthWest
S. California
Southeast
Southwest
Event Definition:Time Series Approach
• Eastern US aggregate time series
Sulfate
EUS Daily Average
50%-ile, 30 day 50%-ile smoothing
Deviation from %-ile
Event – Deviation > percentile value
Median Seasonal Conc.
Mean Seasonal Conc.
Reconstructed Fine Mass RCFM
Organic Carbon
Eelemental Carbon
SOIL
Nitrate
Temporal Pattern Regional Speciated Analysis - VIEWS
• Aerosol species time series:– ammSO4f– OCf– ECf– SOILf– ammNO3f– RCFM
Regions of Aggregation
Dust
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
US
West
East
Dust
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Northeast
Southwest
Southeast
Dust
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Northwest
S. California
Great Plaines
Amm. Sulfate
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US
West
East
Amm. Sulfate
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Northeast
Southwest
Southeast
Amm. Sulfate
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Northwest
S. California
Great Plaines
Organic Carbon
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US
West
East
Organic Carbon
sdheherh
Northeast
Southwest
Southeast
Organic Carbon
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Northwest
S. California
Great Plaines
Reconstructed Fine Mass
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US
West
East
Reconstructed Fine Mass
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Northeast
Southwest
Southeast
Reconstructed Fine Mass
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Northwest
S. California
Great Plaines