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PM2.5 Forecasting Method Development and Operations for Salt Lake City, Utah

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Title: PM2.5 Forecasting Method Development and Operations for Salt Lake City, Utah


1
PM2.5 Forecasting Method Development and
Operations for Salt Lake City, Utah
  • Presented by
  • Timothy S. Dye Dianne S. Miller
  • Craig B. Anderson Clinton P. MacDonald
  • Charley A. Knoderer Beverly S. Thompson
  • Sonoma Technology, Inc.
  • Petaluma, CA
  • (707) 665-9900
  • www.sonomatech.com
  • tim_at_sonomatech.com
  • Presented at EPAs National Air Quality
    Conference
  • Mapping and Forecasting
  • San Francisco, CA
  • February 4-6, 2002

901491-2146
2
Objective and Outline
  • Objective Develop PM2.5 forecasting methods and
    forecast PM2.5 for Salt Lake City area during
    winter 2002
  • Outline
  • Data analysis
  • Forecasting method (tool) development
  • Operational forecasting
  • Initial results
  • Data issues
  • Future plans

3
Data Analysis
  • Description of data sources
  • PM2.5 and PM10 data (AIRS database)
  • Winter months (Oct. Mar.)
  • 5 years of PM10 data (1996 2001)
  • 2 to 4 years of PM2.5 data (1998 2001)
  • 14 sites with PM10 data, 16 sites with PM2.5 data
  • Used only the 24-hr filter data
  • Continuous PM2.5 and PM10 data from three TEOM
    monitors (1999 2001)
  • Meteorological data (NOAA)
  • 5 years of hourly surface observations and
    upper-air soundings from Salt Lake City airport
  • Daily Weather Maps
  • Data processing
  • Performed quality control checks and time/units
    standardization
  • Used an MS Access database to store raw and
    computed data values

4
Data Analysis
5
Data Analysis
  • Developed a climatology Examined the frequency
    and characteristics of PM episodes in Salt Lake
    City
  • Examined the following based on an AQI computed
    from PM2.5
  • Yearly trend
  • Monthly frequency
  • Day of week frequency
  • Overview of results
  • Higher PM2.5 tends to occur
  • on Thursday Sunday
  • in December and January

Average monthly distribution of AQI categories
(based on PM2.5) for Salt Lake City
6
Data Analysis
  • Day-of-week frequency for AQI categories (based
    on PM2.5) in the Salt Lake City region
    (1998-2001)

7
Forecasting Method Development
  • Analyzed PM2.5 episodes for general relationships
    in weather conditions and identified several
    important variables
  • 500-mb pattern (ridge or trough overhead)
  • Strength and duration of temperature inversion
  • Surface wind speed and direction
  • Developed forecast guidelines based on these
    variables (subjective)
  • Developed regression equations and Classification
    and Regression Tree (objective)

8
Forecast Guidelines
Forecast PM2.5 ranges and associated
meteorological conditions
9
Forecasting Method Development
  • Objective Tools
  • Produced scatter plots of PM2.5 and
    meteorological data
  • Ran CART and linear regression to develop
    equations
  • Resulting regression equation
  • Next Day PM2.5 53.4 3.4Holiday 0.2Precip
    0.5WSday 1.0(700T12Z Tmin) 0.8(700T00Z
    Tmax) 0.2700Td00Z 0.3850WS00Z 0.3Tmax
  • Checked physical relationship between each
    variable and PM2.5
  • Tested both techniques operationally during two
    weeks of forecasting

10
Data Acquisition and Dissemination
STI Weather Center
E-mail forecast to Utah DEQ
- Data collection - Formatting - Quality
control - 24-hr average calcs. - Conversion
factor - AQI calculations - Forecast creation
FTP
STI SmogWatch web page for Salt Lake City
Phone
11
Daily Forecasting
  • 0900 - 1000 MST
  • Verify that current data is being received
  • 1100 MST
  • Review previous days observations and forecast
  • Review current days AQ data, weather forecast
    data, and NWS discussions
  • Run regression equation
  • Run CART
  • Create and review current- and next-day forecasts
  • 1200 MST
  • E-mail forecast to UDEQ
  • Afternoon
  • Monitor conditions for any dynamic changes

12
Forecast Dissemination
Sample Daily E-mail
Daily PM2.5 Forecast for Salt Lake City,
UT Today's Date January 25, 2002 Yesterday's
regional maximum AQI 49 (15 ug/m3) -
Good Today's forecasted regional maximum AQI
60 (20 ug/m3) - Moderate Tomorrow's forecasted
regional maximum AQI 60 (20 ug/m3) -
Moderate Discussion The upper-level low
pressure system that was expected to move towards
Utah today has slowed some resulting in a
stronger inversion than originally anticipated.
The models keep the inversion intact today
despite increased winds aloft. This will result
in Moderate PM2.5 values for today. The
upper-level low pressure system moves towards
Utah tomorrow increasing winds aloft however,
the inversion is forecasted to remain intact
through Sunday resulting in Moderate PM2.5
levels. Forecaster Charley Knoderer Sonoma
Technology, Inc. (707) 665-9900
13
Forecast Dissemination
Salt Lake City SmogWatch Web Page
14
Initial Results
  • Slight tendency to overpredict the next-day
    forecast

15
Data Issues
  • Continuous PM2.5 values from the TEOMs can be
    significantly less than the FRM filter values.
    Difference varies, based on several
    meteorological parameters.
  • Continuous PM2.5 monitoring network is limited -
    only one site in each air basin.
  • How to communicate hourly AQI when standard is
    based on a 24-hour average?

16
Data Issues TEOM vs. FRM
  • Collocated TEOM (continuous) and FRM (filter)
  • TEOM PM2.5 underestimates the FRM

PM2.5 Continuous vs. Filter Intercomparison for
the Lindon site (24-hr average data from
December to March of 1999, 2000, and 2001)
Unhealthy
USG
Moderate
R2 0.63
R2 0.63
17
Data Issues TEOM vs. FRM
  • Adjusted TEOM data using a site specific
    regression equation that incorporated temperature
    and humidity
  • Reduces underestimation by TEOM

Adjusted PM2.5 Continuous vs. Filter
Intercomparison for the Lindon site (24-hr
average data from December to March of 1999,
2000, and 2001)
Tc 1.98 1.08 TEOM 0.67 Avg. Temp. 0.08
Avg. RH
18
Next Steps
  • Implement relative humidity and temperature
    conversion factor to adjust continuous TEOM data
    to better match FRM filter data.
  • Continue forecasting until March 1
  • Modify and adjust forecasting tools as new
    truths are learned
  • Continue to evaluate forecast performance
  • Acknowledgments
  • Utah Department of Environmental Quality
  • U.S. Environmental Protection Agency
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