Short-Term Air Quality Forecasts for the Pacific Northwest and Long-Range Global Change Predictions for the US Jack Chen Committee Members: Brian Lamb,

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Presentation transcript:

Short-Term Air Quality Forecasts for the Pacific Northwest and Long-Range Global Change Predictions for the US Jack Chen Committee Members: Brian Lamb, Hal Westberg, George Mount, and Alex Guenther Washington State University May 4 th 2007

Exposures to elevated levels of ozone (O 3 ) and fine particulate matters increase respiratory illnesses, premature deaths, cardiovascular problems Regional haze, degrade visibility National Ambient Air Quality Standards (NAAQS): O 3, CO, Pb, SO 2, NO 2, PM 10, PM 2.5, PollutantConcentrationUnitsAveraging Period O3O3 80ppbv8-hour PM µg/m 3 Annual Mean 35µg/m 3 24-hour Air Quality Standards

US Regional Air Quality Counties Designated Non-attainment or Maintenance Most populated areas are in non-attainment or maintenance “Brown cloud” in Seattle US EPA (2006) 5 NAAQS Pollutants 4 NAAQS Pollutants 3 NAAQS Pollutants 2 NAAQS Pollutants 1 NAAQS Pollutant

Numerical Air Quality Forecasts Short-Range Forecasts – hourly air quality predictions for the next 24 hours Long-Range Predictions – general air quality conditions 50 years in the future from influence of global change

Air Pollution Chemistry Clean Air Photochemistry Urban Pollution Increase Ozone Production (1)NO 2 + hv  NO + O (2)O + O 2  O 3 (3)O 3 + NO  NO 2 + O 2 (4)RH + OH.   RO 2. + HO 2. + R’CHO (5)RO 2. + NO  NO 2 + RO. (6)HO 2. + NO  NO 2 + HO. NOx + VOC + sunlight  O 3 NOx (NO+NO 2 ): Combustion sources, soils, lightening VOC: Combustion sources, solvents, trees, etc

Air Pollution Chemistry Primary Emissions: –Smoke, dust, flyash, pollens, etc. Secondary formation: SO 2 + [OH., O 3, H 2 O]  H 2 SO 4 NO 2 + OH.  HNO 3 N 2 O 5 + H 2 O  2 HNO 3 NH 4 HSO 4, (NH 4 ) 3 H(SO 4 ) 2, (NH 4 ) 2 SO 4 NH 4 NO 3 Aromatic HC or HC-8 + [OH·, NO 3 ·, O 3 ]  SOA NH 3 NOx VOC SO 2

Numerical Grid Model Forecast Meteorological Model Chemical Transport Model Gridded Biogenic / Anthropogenic Emissions Forecast Air Quality Conditions Evaluate with Observational data

California Air Resources Board (1989) EPA: MCIP  CMAQ Short-Range Air Quality Forecast System: AIRPACT-3 AIRPACT has been providing hourly air quality forecasts for the Pacific Northwest since May 2001 O 3 CO NO 2 Primary PM tracers Secondary PM 2.5 PSO4, PNO3, PNH4, PEC, POC AIRPACT-1/2AIRPACT-3 State-of-science knowledge in atmospheric chemistry and physics Cloud effect on atmospheric chemistry Multiphase chemistry (gas, aqueous, aerosol) and aerosol dynamics CMAQ has a wide user community with active development and support from the public and EPA Gridded Emissions US EPA: (1999) Forecast Meteorology (MM5) CALMET/MCIP  CALGRID

Short-Range Air Quality Forecast System: AIRPACT-3 Dynamic Initial Conditions Dynamic Boundary Conditions 2005 Anthropogenic Emissions (SMOKE) Wild and Prescribed Fire Emissions Gridded Emissions EPA Biogenic Emission Model (BEIS3) EPA CMAQ WSU Dairy NH 3 Emissions Module Anthropogenic NOx Emissions Biogenic VOC Emissions

Short-Range Air Quality Forecast System: AIRPACT-3 AIRPACT-1, AIRPACT-2 AIRPACT-1: 62 x 67 at 4-km AIRPACT-2: 81 x 138 at 4-km 13 vertical layers AIRPACT-3 AIRPACT-3: 95 x 95 at 12-km 21 vertical layers (first layer height at 16m) Elevation

Dairy NH 3 Emission Module WA Dairy NH 3 (ton/yr) Housing8,634 Storage5,441 Application4,364 Total18,439 OR Dairy NH 3 (ton/yr) Housing9,469 Storage5,079 Application3,420 Total17,967

Wild and Prescribed Fire Emission from the Forest Service BlueSky System MODIS Image for Sept BlueSky System at Forest Service Observed Fire Events AIRPACT retrieves: fire location, fire size, heat flux, emissions (CO, PM 2.5, TOG) Predicted 24-hr PM 2.5 for Aug WSU Pullman

AIRPACT-3 Evaluation Monitor Network# Station EPA-AQS O 3 30 EPA-AQS PM 2.5 (Speciated PM) 37 (8) IMPROVE PM SWCAA PM August – November 2004 Covers both ozone and PM 2.5 pollution seasons

Daily Max 8-hr O 3 Performance P/O vs Observed Timing errors (running 8-hr means)

Overall Daily Max 8-hr O 3 Performance Obs. Avg.42.9 ppbv Mod. Avg.43.0 ppbv MB2.7 ppbv ME7.2 ppbv R0.55

Ranked Daily Max 8-hr O 3 Performance

Overall 24-hr PM 2.5 Performance EPA-AQS Stations Obs. Avg.11 (μg/m 3 ) Mod. Avg.13 (μg/m 3 ) MB2.0 (μg/m 3 ) ME8.0 (μg/m 3 ) R0.46 IMPROVE Stations Obs. Avg.6.0 (μg/m 3 ) Mod. Avg.8.0 (μg/m 3 ) MB2.2 (μg/m 3 ) ME5.5 (μg/m 3 ) R0.53

Stagnation Event (all units in μg/m 3 )

Long Range Air Quality Predictions for the US general air quality conditions 50 years in the future from influence of global change

Impact of Global Change on Regional Air Quality Forecast Meteorology MM5 EPA CMAQ Gridded Emissions Anthropogenic Biogenic Wild Fire Simulate two 10-year periods Current case ( ) vs Future case ( ) O 3 CO NO 2 Primary PM tracers Secondary PM 2.5 Global Climate Model (NCAR-PCM) Global Chemistry Model (NCAR-MOZART2 ) Global Scale

Long Range Predictions – Domain Right: Regional Meteorology (MM5) and Air Quality (CMAQ) model domain. Left: Global Climate (PCM) and Chemistry (MOZART2) model domain.

Global Scenario on Future Air Quality? IPCC Global Emission Scenarios: A2—"Business as usual” 11 billion 230 Mt/yr +1.5 o C 70 Mt/yr

Western BC [ppbv] CurrentFuture  O3O % NO X % NO Y % VOC % Eastern BC [ppbv] CurrentFuture  O3O % NO X % NO Y % VOC % up to 500 mb

Future Regional Anthropogenic NOx Current Decade Future Difference current emissions (percent increase) USA (1000 ton/day) anthropogenic NO X 60 (6%)

Future Regional Biogenic VOC Current Decade Future Difference current emissions (percent change) USA (1000 ton C/day) anthropogenic VOC51 (+50%) biogenic VOC160 (-38%)

Current decade: comparison of observed and simulated ozone distributions EPA – AQS ozone data for Summer

Current decade daily max 8-hr ozone (2nd, 20th, median, 80th and 98th percentiles)

Current decade episodic ozone conditions (98 th percentile daily max 8-hr ozone) Model [ppbv] Measured

Mean summer daily max 2-m temperature Current vs Future CurrentFuture Difference

(2nd, 20th, median, 80th and 98th percentiles) Future changes in daily max 8-hr ozone

Future Changes daily max 8-Hr ozone (Episodic Condition - 98 th Percentile) [ppbv] Current Difference Future

Future ozone changes at select sites Eight sites across US with 98 th percentile observed daily max. 8-hr O 3 exceed the EPA 80 ppbv standard

Future Changes in Episodic Ozone Season Average days per months across the eight sites.

Future Changes in Ozone Episode Duration Consecutive days 8-hr daily max O 3 exceed 80 ppbv % change from current decade

Summary Short-Term air quality forecasts –AIRPACT-3 with One-Atmosphere approach for PNW air quality –Includes dynamic treatment of anthropogenic, biogenic, dairy NH 3 and wildfire emissions –Evaluation showed good forecast performances –Peak ozone values correctly predicted, but over-estimated low levels –PM 2.5 concentrations were better captured in urban areas than rural regions –Good match with PNO3, PNH4 observations but underestimated PSO4 Long-Range air quality predictions –Coupled global and regional AQ modeling system for the US –System reproduced current observed episodic ozone conditions –Under IPCC-A2 scenario, future 8-hr ozone increase by 5 to 10 ppbv –Larger areas of the US are impacted by ozone >80ppbv –Longer episodic ozone seasons and longer ozone episodes –Future land use have significant impact on biogenic emissions

Acknowledgements Advisor: Dr. Brian Lamb Committee: Drs. Hal Westberg, George Mount, Alex Guenther Funding from NW-AIRQUEST for the AIRPACT project Funding from EPA STAR for the long-term AQ predictions project Collaborating agencies: WA ECY, SWCAA, NCAR, USDA-FS, UW, EPA-R10 Staff at the CE department office –Maureen Clausen, Lola Gillespie, Vicki Ruddick, Tom Weber, and Cyndi Whitmore.

Acknowledgements Past and present LAR graduate students –Dr. Mike Barna, Dr. Susan O’Neill, Dr. Guangfeng Jiang –Dr. Joe Vaughan, Dr. Shelley Pressley –Jeremy Avise, Tara Strand, Ying Xie, Farren Thorpe, Matt Porter, Charleston Ramos, Brian Rumburg, Obie Cambaliza … Friends and Family

Questions? Thank you!

Presentation Outline Background Short-term air quality forecasts: –Modeling approach –Results Long-term air quality predictions: –Modeling approach –Results Summary and conclusion Acknowledgement and questions

Conservation Equation in an Eulerian Framework (1) (2a) (2b) (2c) (3a) (3b) (3c) (4) (5) (6) (1)Change of pollutant concentration (2a,b) Horizontal Advection (2c) Vertical Advection (3a,b) Horizontal Dispersion (3c) Vertical Diffusion (4) Chemical Reaction (5) Deposition (6) Emission/Source Term Chemical Transport Model

Aug Surface Temp. ( o C) Wind Direction (deg) Wind Speed (m/s) Precip (mm) RH (%) Mean Bias (MB) Mean Error (ME) N Nov Surface Temp. ( o C) Wind Direction (deg) Wind Speed (m/s) Precip (mm) RH (%) Mean bias (MB) Mean error (ME) N km MM5 Forecast Performance

POC PEC PSO4 Columbia River Gorge (Bonneville Dam)

US Regional Emissions Current (1000 tons/day) & future/current ratio AreaMobileOff-roadPointFireBiogenic CO NOx N/A VOC

Average daily max 8-hr ozone and 98 th percentile daily max 8-hr ozone

Future changes in average daily max 8-hr ozone and 98 th percentile daily max 8-hr ozone

Future Biogenic Emissions from Land Use, Land Cover Changes Simulated future July months with different vegetation distributions Case 1Current decade Case 2Future with current vegetation Case 3Future decade Case 4Future with afforestation Case 2 – Case 1 Case 4 – Case 1 Isoprene Emission Difference

Change LULC on Future Biogenic Emissions Total Continental Emissions

Change LULC on Future Ozone and BSOA Average Continental Concentrations

Long Range Forecast – Current Status Average temperature across PNW showed 2 o C increase