Classificatory performance evaluation of air quality forecasting in georgia
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Classificatory performance evaluation of air quality forecasting in Georgia. Yongtao Hu 1 , M. Talat Odman 1 , Michael E. Chang 2 and Armistead G. Russell 1 1 School of Civil & Environmental Engineering, 2 Brook Byers Institute of Sustainable Systems Georgia Institute of Technology.

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Classificatory performance evaluation of air quality forecasting in Georgia

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Classificatory performance evaluation of air quality forecasting in georgia

Classificatory performance evaluation of air quality forecasting in Georgia

Yongtao Hu1, M. Talat Odman1, Michael E. Chang2 and Armistead G. Russell1

1School of Civil & Environmental Engineering,

2Brook Byers Institute of Sustainable Systems

Georgia Institute of Technology

9th Annual CMAS Conference, October 12th, 2010


Classificatory performance evaluation of air quality forecasting in georgia

Overview

  • The Hi-Res air quality forecasting system

  • O3 and PM2.5 performance for metro Atlanta

  • New SOA module and its impact on PM2.5 performance

  • Classificatory performance evaluation: linking forecast performance to weather types and emissions conditions


Classificatory performance evaluation of air quality forecasting in georgia

Hi-Res: forecasting ozone and PM2.5 at 4-km resolution for metro areas in Georgia

Georgia Institute of Technology


Snapshots from hi res homepage http forecast ce gatech edu

Hi-Res Forecast Products

Snapshots from Hi-Res homepage: http://forecast.ce.gatech.edu

  • “Single Value” Report: tomorrow’s AQI, ozone and PM2.5 by metro area in Georgia

  • Air Quality Forecasts: AQI, ozone and PM2.5, 48-hrs spatial plots and station profiles

  • Meteorological Forecasts: precipitation, temperature and winds, 48-hrs spatial plots and station profiles

  • Performance Evaluation: time series comparison and scatter plots for the previous day

Georgia Institute of Technology


Classificatory performance evaluation of air quality forecasting in georgia

Evolution of Hi-Res during 2006-2010

  • Updated to latest release of WRF each year before the ozone season.

    • WRF 2.1, 2.2, 3.0, 3.1 and 3.2

  • CMAQ is typically one version behind.

    • CMAQ 4.6 with Georgia Tech extensions

  • Projected NEI to current year in the very beginning of each year.

  • Updated forecast products website each year before ozone season.

  • Switched from single-cycle forecasting to two-cycles in 2008.

  • Enlarged 4-km domain to cover the entire state of Georgia in 2009.

  • Introduced Georgia Tech’s new SOA module in 2009.


Ambient monitoring sites for performance evaluation

Ambient Monitoring Sites for Performance Evaluation


Performance metrics

Performance Metrics

NAAQS

Forecast

NAAQS

Observation


Overall 2006 2010 performance ozone season atlanta metro

Overall 2006-2010 Performance (Ozone Season): Atlanta Metro

PM2.5

Ozone

Georgia Institute of Technology


Ozone performance

Ozone Performance


Forecast vs observed o 3

Forecastvs. Observed O3

2008

2007

2010

2009

Georgia Institute of Technology


2009 o 3 performance hi res vs ga epd s

2009 O3 Performance: Hi-Res vs. GA EPD’s

Our 4-km Forecast

EPD Ensemble Forecast

Economic down turn?


2010 o 3 performance hi res vs ga epd s

2010 O3 Performance: Hi-Res vs. GA EPD’s

Our 4-km Forecast

EPD Ensemble Forecast

Economic recovery?


Pm 2 5 performance

PM2.5 Performance


Summer

Summer


Forecast vs observed pm 2 5

Forecastvs. Observed PM2.5

2007

2008

2009

2010

Georgia Institute of Technology


2009 pm 2 5 performance 4 km vs ga epd s

2009 PM2.5 Performance: 4-km vs. GA EPD’s

Our 4-km Forecast

EPD Ensemble Forecast

Economic down turn?

New SOA module?


2010 pm 2 5 performance 4 km vs ga epd s

2010 PM2.5 Performance: 4-km vs. GA EPD’s

Our 4-km Forecast

EPD Ensemble Forecast

New SOA module?


Classificatory performance evaluation of air quality forecasting in georgia

Aging process:

+OH,+O3

Aerosol

+OH,+O3

LSVOC

HSVOC

New SOA Module (Baek, J., Georgia Tech, 2009)

SOA species in CMAQ:

Included processes:

  • SOA partitioned from anthropogenic VOCs’ oxidations (8 SVOCs)

  • From monoterpenes (2 SVOCs)

  • From isoprene (2 SVOCs added)

  • From sesquiterpenes (1 SVOC added, gas phase oxidation reactions added for α-caryphyllene, β-humulene, and other sesquiterpenes)

  • Aging of all semi-volatile organic carbons (SVOCs)added

  • AORGAJ and AORGAI

  • AORGBJ and AORGBI

  • AORGBISJ and AORGBISI

  • AORGBSQJ and AORGBSQI

  • AORGAGJ and AORGAGI


Classificatory performance evaluation of air quality forecasting in georgia

Forecastvs. Observed OC at South DeKalb

Ozone Season May-September

OC

PM2.5

2009


Met performance

Met. Performance


Overall 2006 2010 performance ozone season atlanta metro1

Overall 2006-2010 Performance (Ozone Season): Atlanta Metro

Humidity

Temperature

Georgia Institute of Technology


Forecast vs observed temperature

Forecastvs. Observed Temperature

Georgia Institute of Technology


Forecast vs observed humidity

Forecastvs. Observed Humidity

Georgia Institute of Technology


Classificatory performance evaluation during 2006 2009

Classificatory Performance Evaluation during 2006-2009

Hu, Y., et al. 2010, "Using synoptic classification to evaluate an operational air quality forecasting system in Atlanta," Atmos. Pol. Res., 1, 280-287.


Classificatory performance evaluation of air quality forecasting in georgia

Spatial Synoptic Classification (Sheridan 2002, http://sheridan.geog.kent.edu/ssc.html): Atlanta Calendar(ozone season)

Weather Types

  • DP (dry polar): lowest in temp, clear and dry.

  • DM (dry moderate): air is mild and dry.

  • DT (dry tropical): hottest and driest.

  • MP (moist polar): cloudy, humid and cool.

  • MM (moist moderate): warmer and more humid.

  • MT (moist tropical): warm and very humid.

  • TR (transitional): one type yields to another, large shifts in P,Td,V.


Classificatory performance evaluation of air quality forecasting in georgia

Forecasting error versus observation for spatial synoptic classifications

*Statistics are for 2006-2009 summers where not specified.


Classificatory performance evaluation of air quality forecasting in georgia

Observations Grouped by Weather Type

PM2.5

Ozone

Georgia Institute of Technology


Classificatory performance evaluation of air quality forecasting in georgia

8-hr O3 Performance Grouped by Weather Type

2009

2006-2008


Classificatory performance evaluation of air quality forecasting in georgia

24-hr PM2.5 Performance by Weather Type

2006-2008

2009


Classificatory performance evaluation of air quality forecasting in georgia

GA EPD forecasting Performance by Weather Type

Ozone

PM2.5


Classificatory performance evaluation of air quality forecasting in georgia

Linking Performance to Emissions Conditions

Ozone

PM2.5

  • Emissions Conditions Classification:

    • Special weekdays (Monday and Friday)

    • Typical weekdays

    • Weekends/holidays


Summary

Summary

  • 2006-2010 ozone forecasts are good.

    • Overall bias is +16% and error is 23%

  • 2006-2008 PM2.5 forecasts are not very accurate.

    • May-September bias is -37% and error is 43%

  • The new SOA module improved 2009 and 2010 PM2.5 performances

    • May-September bias is 8% and error is 25% for 2009

    • May-September bias is 4% and error is 21% for 2010

  • 2006-2010 temperature and humidity performances are good.

  • Better ozone performance and, during 2009-2010, better PM2.5 performance are associated with dry weather types.

  • Forecast performance is worse on weekend/holidays

Georgia Institute of Technology


Classificatory performance evaluation of air quality forecasting in georgia

Acknowledgements

We thank Georgia EPD for funding the Hi-Res forecasts,

Our former group member Dr. Jaemeen Baek for the new SOA module, and

Dr. Carlos Cardelino of Georgia Tech for team forecasts.


Forecast vs observed 2006

Forecastvs. Observed 2006

PM2.5

O3

Temperature

Humidity

Georgia Institute of Technology


Winter

Winter


Forecasted vs observed pm 2 5

Forecastedvs. Observed PM2.5

2007

2008

2009


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